tag:theconversation.com,2011:/global/topics/modeling-28501/articlesModeling – The Conversation2023-11-20T13:16:27Ztag:theconversation.com,2011:article/2151352023-11-20T13:16:27Z2023-11-20T13:16:27ZPooling multiple models during COVID-19 pandemic provided more reliable projections about an uncertain future<figure><img src="https://images.theconversation.com/files/559148/original/file-20231113-21-81g8j.jpg?ixlib=rb-1.1.0&rect=11%2C383%2C3479%2C2610&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">The sum is greater than the parts when researchers build an ensemble from multiple coordinated but independent models.</span> <span class="attribution"><span class="source">Matteo Chinazzi</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span></figcaption></figure><p>How can anyone decide on the best course of action in a world full of unknowns?</p>
<p>There are few better examples of this challenge than the COVID-19 pandemic, when officials fervently compared potential outcomes as they weighed options like whether to implement lockdowns or require masks in schools. The main tools they used to compare these futures were epidemic models.</p>
<p>But often, models included numerous unstated assumptions and considered only one scenario – for instance, <a href="https://doi.org/10.7326/M20-1565">that lockdowns would continue</a>. Chosen scenarios were rarely consistent across models. All this variability made it difficult to compare models, because it’s unclear whether the differences between them were due to different starting assumptions or scientific disagreement.</p>
<p>In response, we came together with colleagues to found the <a href="https://covid19scenariomodelinghub.org">U.S. COVID-19 Scenario Modeling Hub</a> in December 2020. We provide real-time, long-term projections in the U.S. for use by federal agencies such as the Centers for Disease Control and Prevention, local health authorities and the public. We work directly with public health officials to identify which possible futures, or scenarios, would be most helpful to consider as they set policy, and we convene multiple independent modeling teams to make projections of public health outcomes for each scenario. Crucially, having multiple teams address the same question allows us to better envision what could possibly happen in the future.</p>
<p>Since its inception, the Scenario Modeling Hub has generated 17 rounds of projections of COVID-19 cases, hospitalizations and deaths in the U.S. across varying stages of the pandemic. In a recent study published in the journal Nature Communications, we looked back at all these projections and <a href="https://doi.org/10.1038/s41467-023-42680-x">evaluated how well they matched the reality</a> that unfolded. This work provided insights about when and what kinds of model projections are most trustworthy – and most importantly supported our strategy of combining multiple models into one ensemble.</p>
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<a href="https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="line graph that ends in multiple colored options on the right" src="https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=200&fit=crop&dpr=1 600w, https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=200&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=200&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=251&fit=crop&dpr=1 754w, https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=251&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/557558/original/file-20231103-19-f0po1g.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=251&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Collecting projections from multiple independent models provides a fuller picture of possible futures − as in this graph of potential hospitalizations − and allows researchers to generate an ensemble.</span>
<span class="attribution"><span class="source">COVID-19 Scenario Modeling Hub</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
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<h2>Multiple models are better than just one</h2>
<p>A founding principle of our Scenario Modeling Hub is that multiple models are more reliable than one.</p>
<p>From tomorrow’s temperature on your weather app to predictions of interest rates in the next few months, you likely use the combined results of multiple models all the time. Especially in times like the COVID-19 pandemic when uncertainty abounds, <a href="https://doi.org/10.1016/0169-2070(89)90012-5">combining projections from multiple models into an ensemble</a> provides a fuller picture of what could happen in the future. Ensembles have become ubiquitous in many fields, primarily because <a href="https://doi.org/10.1016/S1574-0706(05)01004-9">they work</a>.</p>
<p><iframe id="3xdrr" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/3xdrr/5/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<p>Our analysis of this approach with COVID-19 models resoundingly showed the strong performance of the Scenario Modeling Hub ensemble. Not only did the <a href="https://doi.org/10.1038/s41467-023-42680-x">ensemble give us more accurate predictions</a> of what could happen in the future overall, it was substantially more consistent than any individual model throughout the different stages of the pandemic. When one model failed, another performed well, and by taking into account results from all of these varying models, the ensemble emerged as more accurate and more reliable.</p>
<p>Researchers have previously shown performance benefits of ensembles for short-term forecasts of <a href="https://doi.org/10.1038/s41598-018-36361-9">influenza</a>, <a href="https://doi.org/10.1073/pnas.1909865116">dengue</a> and <a href="https://doi.org/10.1073/pnas.2113561119">SARS-CoV-2</a>. But our recent study is one of the first times researchers have tested this effect for long-term projections of alternative scenarios. </p>
<h2>A ‘hub’ makes multimodel projections possible</h2>
<p>While scientists know combining multiple models into an ensemble improves predictions, it can be tricky to put an ensemble together. For example, in order for an ensemble to be meaningful, model outputs and key assumptions need to be standardized. If one model assumes a new COVID-19 variant will gain steam and another model does not, they will come up with vastly different results. Likewise, a model that projects cases and one that projects hospitalizations would not provide comparable results. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="people seated around an open conference table with whiteboards" src="https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=311&fit=crop&dpr=1 600w, https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=311&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=311&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=391&fit=crop&dpr=1 754w, https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=391&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/559121/original/file-20231113-22-5b1rrh.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=391&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Meeting frequently helps multiple modeling teams stay on the same page.</span>
<span class="attribution"><span class="source">Matteo Chinazzi</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
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<p>Many of these challenges are overcome by <a href="https://doi.org/10.2105/AJPH.2022.306831">convening as a “hub.”</a> Our modeling teams meet weekly to make sure we’re all on the same page about the scenarios we model. This way, any differences in what individual models project are the result of things researchers truly do not know. Retaining this scientific disagreement is essential; the success of the Scenario Modeling Hub ensemble arises because each modeling team takes a different approach.</p>
<p>At our hub we work together to <a href="https://www.medrxiv.org/content/10.1101/2023.10.11.23296887v1">design our scenarios strategically</a> and in close collaboration with public health officials. By projecting outcomes under specific scenarios, we can estimate the impact of particular interventions, like vaccination.</p>
<p>For example, a scenario with higher vaccine uptake can be compared with a scenario with current vaccination rates to understand how many lives could potentially be saved. Our projections have informed recommendations of <a href="https://doi.org/10.1016/j.lana.2022.100398">COVID-19 vaccines for children</a> and bivalent boosters for all age groups, both in <a href="http://dx.doi.org/10.15585/mmwr.mm7145a2">2022</a> and <a href="http://dx.doi.org/10.15585/mmwr.mm7224a3">2023</a>. </p>
<p>In other cases, we design scenarios to explore the effects of important unknowns, such as the impact of a new variant – <a href="https://doi.org/10.7554/eLife.73584">known</a> or <a href="https://doi.org/10.1016/j.lana.2022.100398">hypothetical</a>. These types of scenarios can help individuals and institutions know what they might be up against in the future and plan accordingly.</p>
<p>Although the hub process requires substantial time and resources, our results showed that the effort has clear payoffs: The information we generate together is more reliable than the information we could generate alone. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="woman filling out a form with a COVID vaccine sign in the foreground" src="https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/559966/original/file-20231116-17-51u1pb.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">What models suggest are likely futures can inform real-world decisions, such as when to run a vaccine clinic.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/woman-fills-out-a-registration-form-to-receive-a-dose-of-a-news-photo/1250226576">Eric Lee for The Washington Post via Getty Images</a></span>
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<h2>Past reliability, confidence for future</h2>
<p>Because Scenario Modeling Hub projections can inform real public health decisions, it is essential that we provide the best possible information. Holding ourselves accountable in retrospective evaluations not only allows us to identify places where the models and the scenarios can be improved, but also helps us build trust with the people who rely on our projections.</p>
<p>Our hub has expanded to produce <a href="https://fluscenariomodelinghub.org">scenario projections for influenza</a>, and we are introducing projections of respiratory syncytial virus, or RSV. And encouragingly, other groups abroad, <a href="https://covid19scenariohub.eu">particularly in the EU</a>, are replicating our setup.</p>
<p>Scientists around the world can take the hub-based approach that we’ve shown improves reliability during the COVID-19 pandemic and use it to support a comprehensive public health response to important pathogen threats.</p><img src="https://counter.theconversation.com/content/215135/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Emily Howerton is funded by the US National Science Foundation to support this work. </span></em></p><p class="fine-print"><em><span>Justin Lessler receives funding from the US CDC and the NIH to support this work. He has also served as an expert witness on cases where the likely length of the pandemic was of issue. </span></em></p><p class="fine-print"><em><span>Cecile Viboud does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>Policymakers rely on models during uncertain times to figure out how their choices could affect the future. Over the pandemic, an ensemble of many COVID-19 models outperformed any one alone.Emily Howerton, Postdoctoral Scholar in Biology, Penn StateCecile Viboud, Senior Research Scientist, National Institutes of HealthJustin Lessler, Professor of Epidemiology, University of North Carolina at Chapel HillLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1961002023-01-10T13:30:06Z2023-01-10T13:30:06ZOrgan-on-a-chip models allow researchers to conduct studies closer to real-life conditions – and possibly grease the drug development pipeline<figure><img src="https://images.theconversation.com/files/501906/original/file-20221219-18-6xab1c.jpg?ixlib=rb-1.1.0&rect=0%2C0%2C2044%2C1581&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">The lung-on-a-chip can mimic both the physical and mechanical qualities of a human lung.</span> <span class="attribution"><a class="source" href="https://flic.kr/p/HQBa1g">Wyss Institute for Biologically Inspired Engineering, Harvard University/Flickr</a></span></figcaption></figure><p><a href="https://doi.org/10.1007/s40273-021-01065-y">Bringing a new drug to market</a> costs billions of dollars and can take over a decade. These high monetary and time investments are both strong contributors to today’s skyrocketing health care costs and significant obstacles to delivering new therapies to patients. One big reason behind these barriers is the lab models researchers use to develop drugs in the first place.</p>
<p><a href="https://www.fda.gov/patients/drug-development-process/step-2-preclinical-research">Preclinical trials</a>, or studies that test a drug’s efficacy and toxicity before it enters clinical trials in people, are mainly conducted on cell cultures and animals. Both are limited by their poor ability to mimic the conditions of the human body. <a href="https://doi.org/10.1016%2FB978-0-12-803077-6.00009-6">Cell cultures</a> in a petri dish are unable to replicate every aspect of tissue function, such as how cells interact in the body or the dynamics of living organs. And <a href="https://doi.org/10.1093/bioinformatics/btu611">animals</a> are not humans – even small genetic differences between species can be amplified to major physiological differences. </p>
<p><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3902221/">Fewer than 8%</a> of successful animal studies for cancer therapies make it to human clinical trials. Because animal models often fail to predict drug effects in human clinical trials, these late-stage failures can significantly drive up both costs and patient health risks. </p>
<p>To address this translation problem, researchers have been developing a promising model that can more closely mimic the human body – organ-on-a-chip. </p>
<p>As an <a href="https://scholar.google.com/citations?user=FppSA-0AAAAJ&hl=en">analytical chemist</a>, I have been working to develop organ and tissue models that avoid the simplicity of common cell cultures and the discrepancies of animal models. I believe that, with further development, organs-on-chips can help researchers study diseases and test drugs in conditions that are closer to real life.</p>
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<iframe width="440" height="260" src="https://www.youtube.com/embed/CpkXmtJOH84?wmode=transparent&start=0" frameborder="0" allowfullscreen=""></iframe>
<figcaption><span class="caption">Organs-on-chips offer an alternative model for early-phase biomedical research.</span></figcaption>
</figure>
<h2>What are organs-on-chips?</h2>
<p>In the late 1990s, researchers figured out a way to <a href="https://gmwgroup.harvard.edu/files/gmwgroup/files/1073.pdf">layer elastic polymers</a> to control and examine fluids at a microscopic level. This launched the field of <a href="https://doi.org/10.1016/j.mne.2019.01.003">microfluidics</a>, which for the biomedical sciences involves the use of devices that can mimic the dynamic flow of fluids in the body, such as blood.</p>
<p>Advances in microfluidics have provided researchers a platform to culture cells that function more closely to how they would in the human body, specifically with <a href="https://doi.org/10.1038/s41578-018-0034-7">organs-on-chips</a>. The “chip” refers to the microfluidic device that encases the cells. They’re commonly made using the same technology as computer chips. </p>
<p>Not only do organs-on-chips mimic blood flow in the body, these platforms have microchambers that allow researchers to integrate multiple types of cells to mimic the diverse range of cell types normally present in an organ. The fluid flow connects these multiple cell types, allowing researchers to study how they interact with each other.</p>
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<figcaption><span class="caption">Microfluidics can be used for many applications in biological research.</span></figcaption>
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<p>This technology can overcome the limitations of both static cell cultures and animal studies in several ways. First, the presence of fluid flowing in the model allows it to mimic both what a cell experiences in the body, such as how it receives nutrients and removes wastes, and how a drug will move in the blood and interact with multiple types of cells. The ability to control fluid flow also enables researchers to fine-tune the optimal dosing for a particular drug.</p>
<p>The <a href="https://doi.org/10.1126/science.1188302">lung-on-a-chip</a> model, for instance, is able to integrate both the mechanical and physical qualities of a living human lung. It’s able to mimic the dilation and contraction, or inhalation and exhalation, of the lung and simulate the interface between the lung and air. The ability to replicate these qualities allows researchers to better study lung impairment across different factors.</p>
<h2>Bringing organs-on-chips to scale</h2>
<p>While organ-on-a-chip pushes the boundaries of early-stage pharmaceutical research, the technology has <a href="https://doi.org/10.1016/j.drudis.2019.03.011">not been widely integrated</a> into drug development pipelines. I believe that a core obstacle for wide adoption of such chips is its high complexity and low practicality.</p>
<p>Current organ-on-a-chip models are difficult for the average scientist to use. Also, because most models are single-use and allow only one input, which limits what researchers can study at a given time, they are both expensive and time- and labor-intensive to implement. The <a href="https://doi.org/10.1039/c6lc01554a">high investments required</a> to use these models might dampen enthusiasm to adopt them. After all, researchers often use the least complex models available for preclinical studies to reduce time and cost.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="Close-up of blood-brain barrier on a chip" src="https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=433&fit=crop&dpr=1 600w, https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=433&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=433&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=544&fit=crop&dpr=1 754w, https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=544&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/501643/original/file-20221216-13-pjt0d0.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=544&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">This chip mimics the blood-brain barrier. The blue dye marks where brain cells would go, and the red dye marks the route of blood flow.</span>
<span class="attribution"><a class="source" href="https://flic.kr/p/HRUHqg">Vanderbilt University/Flickr</a></span>
</figcaption>
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<p>Lowering the technical bar to make and use organs-on-chips is critical to allowing the entire research community to take full advantage of their benefits. But this does not necessarily require simplifying the models. <a href="https://chenresearchlab.umbc.edu">My lab</a>, for example, has designed various <a href="https://doi.org/10.26434/chemrxiv.12964604.v1">“plug-and-play” tissue chips</a> that are standardized and modular, allowing researchers to readily assemble premade parts to run their experiments.</p>
<p>The advent of <a href="https://pubs.acs.org/doi/full/10.1021/ac403397r">3D printing</a> has also significantly facilitated the development of organ-on-a-chip, allowing researchers to directly manufacture entire tissue and organ models on chips. 3D printing is ideal for fast prototyping and design-sharing between users and also makes it easy for mass production of standardized materials.</p>
<p>I believe that organs-on-chips hold the potential to enable breakthroughs in drug discovery and allow researchers to better understand how organs function in health and disease. Increasing this technology’s accessibility could help take the model out of development in the lab and let it make its mark on the biomedical industry.</p><img src="https://counter.theconversation.com/content/196100/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Chengpeng Chen receives funding from the NIH.</span></em></p>Successes in the lab mostly don’t translate to people. Research models that better mimic the human body could close the gap.Chengpeng Chen, Assistant Professor of Chemistry and Biochemistry, University of Maryland, Baltimore CountyLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1958732023-01-06T13:30:53Z2023-01-06T13:30:53ZVisualizing the inside of cells at previously impossible resolutions provides vivid insights into how they work<figure><img src="https://images.theconversation.com/files/501408/original/file-20221215-16-mtk39u.jpg?ixlib=rb-1.1.0&rect=0%2C0%2C1078%2C913&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Cryo-electron tomography shows what molecules look like in high-resolution – in this case, the virus that causes COVID-19.</span> <span class="attribution"><a class="source" href="https://nanographics.at/projects/coronavirus-3d/">Nanographics</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span></figcaption></figure><p>All life is <a href="https://www.khanacademy.org/science/biology/intro-to-biology/what-is-biology/a/what-is-life">made up of cells</a> several magnitudes <a href="https://learn.genetics.utah.edu/content/cells/scale/">smaller than a grain of salt</a>. Their seemingly simple-looking structures mask the intricate and complex molecular activity that enables them to carry out the functions that sustain life. Researchers are beginning to be able to visualize this activity to a level of detail they haven’t been able to before.</p>
<p>Biological structures can be visualized by either starting at the level of the whole organism and working down, or starting at the level of single atoms and working up. However, there has been a resolution gap between a cell’s smallest structures, such as the cytoskeleton that supports the cell’s shape, and its largest structures, such as the ribosomes that make proteins in cells.</p>
<p>By analogy of Google Maps, while scientists have been able to see entire cities and individual houses, they did not have the tools to see how the houses came together to make up neighborhoods. Seeing these neighborhood-level details is essential to being able to understand how individual components work together in the environment of a cell.</p>
<p>New tools are steadily bridging this gap. And ongoing development of one particular technique, <a href="https://doi.org/10.1002/1873-3468.13948">cryo-electron tomography, or cryo-ET</a>, has the potential to deepen how researchers study and understand how cells function in health and disease. </p>
<figure>
<iframe width="440" height="260" src="https://www.youtube.com/embed/026rzTXb1zw?wmode=transparent&start=0" frameborder="0" allowfullscreen=""></iframe>
<figcaption><span class="caption">Cryo-EM won the 2017 Nobel Prize in chemistry.</span></figcaption>
</figure>
<p>As the former <a href="https://www.science.org/content/article/jeremy-berg-named-science-editor-chief">editor-in-chief of Science magazine</a> and as a <a href="https://scholar.google.com/citations?user=MZ6qrPUAAAAJ&hl=en">researcher</a> who has studied hard-to-visualize large protein structures for decades, I have witnessed astounding progress in the development of tools that can determine biological structures in detail. Just as it becomes easier to understand how complicated systems work when you know what they look like, understanding how biological structures fit together in a cell is key to understanding how organisms function.</p>
<h2>A brief history of microscopy</h2>
<p>In the 17th century, <a href="https://doi.org/10.1098/rsob.150019">light microscopy</a> first revealed the existence of cells. In the 20th century, electron microscopy offered even greater detail, revealing the <a href="https://www.nobelprize.org/prizes/medicine/1974/summary/">elaborate structures within cells</a>, including organelles like the endoplasmic reticulum, a complex network of membranes that play key roles in protein synthesis and transport.</p>
<p>From the 1940s to 1960s, biochemists worked to separate cells into their molecular components and learn how to determine the 3D structures of proteins and other macromolecules at or near atomic resolution. This was first done using X-ray crystallography to visualize the structure of <a href="https://www.historyofinformation.com/detail.php?entryid=3015">myoglobin</a>, a protein that supplies oxygen to muscles. </p>
<p>Over the past decade, techniques based on <a href="https://www.nobelprize.org/prizes/chemistry/2002/press-release/">nuclear magnetic resonance</a>, which produces images based on how atoms interact in a magnetic field, and <a href="https://doi.org/10.1016/j.molcel.2015.02.019">cryo-electron microscopy</a> have rapidly increased the number and complexity of the structures scientists can visualize.</p>
<h2>What is cryo-EM and cryo-ET?</h2>
<p><a href="https://theconversation.com/scientists-uncovered-the-structure-of-the-key-protein-for-a-future-hepatitis-c-vaccine-heres-how-they-did-it-193705">Cryo-electron microscopy, or cryo-EM</a>, uses a camera to detect how a beam of electrons is deflected as the electrons pass through a sample to visualize structures at the molecular level. Samples are rapidly frozen to protect them from radiation damage. Detailed models of the structure of interest are made by taking multiple images of individual molecules and averaging them into a 3D structure.</p>
<p><a href="https://doi.org/10.1038/nmeth.4115">Cryo-ET</a> shares similar components with cryo-EM but uses different methods. Because most cells are too thick to be imaged clearly, a region of interest in a cell is first thinned by using an ion beam. The sample is then tilted to take multiple pictures of it at different angles, analogous to a CT scan of a body part – although in this case the imaging system itself is tilted, rather than the patient. These images are then combined by a computer to produce a 3D image of a portion of the cell. </p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="Cryo-ET image of algal chloroplast" src="https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=932&fit=crop&dpr=1 600w, https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=932&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=932&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1172&fit=crop&dpr=1 754w, https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1172&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/501410/original/file-20221215-27-mqhygu.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1172&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">This is a cryo-ET image of the chloroplast of an algal cell.</span>
<span class="attribution"><a class="source" href="https://dx.doi.org/10.7554/eLife.04889">Engel et al. (2015)</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>The resolution of this image is high enough that researchers – or computer programs – can identify the individual components of different structures in a cell. Researchers have used this approach, for example, to show how proteins move and are degraded inside an <a href="https://doi.org/10.1073/pnas.1905641117">algal cell</a>.</p>
<p>Many of the steps researchers once had to do manually to determine the structures of cells are becoming automated, allowing scientists to identify new structures at vastly higher speeds. For example, combining cryo-EM with artificial intelligence programs like <a href="https://doi.org/10.1038/s41586-021-03819-2">AlphaFold</a> can facilitate image interpretation by predicting protein structures that have not yet been characterized. </p>
<h2>Understanding cell structure and function</h2>
<p>As imaging methods and workflows improve, researchers will be able to tackle some key questions in cell biology with different strategies.</p>
<p>The first step is to decide what cells and which regions within those cells to study. Another visualization technique called <a href="https://doi.org/10.1002/1873-3468.14421">correlated light and electron microscopy, or CLEM</a>, uses fluorescent tags to help locate regions where interesting processes are taking place in living cells.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="Cryo-EM image of human T-cell leukemia virus type-1 (HTLV-1)" src="https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=406&fit=crop&dpr=1 600w, https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=406&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=406&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=510&fit=crop&dpr=1 754w, https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=510&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/501414/original/file-20221215-13-dadsmp.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=510&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">This is a cryo-EM image of a human T-cell leukemia virus type-1 (HTLV-1).</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/photo/cryo-em-structure-of-human-t-cell-leukemia-virus-royalty-free-image/1300707029">vdvornyk/iStock via Getty Images Plus</a></span>
</figcaption>
</figure>
<p>Comparing the <a href="https://doi.org/10.1016/j.isci.2018.07.014">genetic difference between cells</a> can provide additional insight. Scientists can look at cells that are unable to carry out particular functions and see how this is reflected in their structure. This approach can also help researchers study how cells interact with each other.</p>
<p>Cryo-ET is likely to remain a specialized tool for some time. But further technological developments and increasing accessibility will allow the scientific community to examine the link between cellular structure and function at previously inaccessible levels of detail. I anticipate seeing new theories on how we understand cells, moving from disorganized bags of molecules to intricately organized and dynamic systems.</p><img src="https://counter.theconversation.com/content/195873/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Jeremy Berg does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>Many microscopy techniques have won Nobel Prizes over the years. Advancements like cryo-ET that allow scientists to see the individual atoms of cells can reveal their biological functions.Jeremy Berg, Professor of Computational and Systems Biology, Associate Senior Vice Chancellor for Science Strategy and Planning, University of PittsburghLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1816722022-04-21T12:18:01Z2022-04-21T12:18:01ZAchoo! 5 essential reads for pollen season<figure><img src="https://images.theconversation.com/files/458973/original/file-20220420-14894-m6e6re.jpg?ixlib=rb-1.1.0&rect=0%2C0%2C6016%2C4007&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Common hazel dispersing pollen in early spring. </span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/common-hazel-close-up-of-male-catkins-dispersing-pollen-in-news-photo/971552142">Arterra/Universal Images Group via Getty Images</a></span></figcaption></figure><p>As spring expands across North America, trees, shrubs and flowers are releasing <a href="https://www.britannica.com/science/pollen">pollen</a>. This fine, powdery substance is produced by the male structures of cone-bearing and flowering plants. When it’s carried to the plants’ female structures by wind, water or pollinators, fertilization happens. </p>
<p>As pollen travels, it also triggers allergies in <a href="https://www.aafa.org/allergy-facts/#">some 25 million Americans</a>. Pollen exposure can cause sneezing, coughing, itchy eyes, runny nose and postnasal drip – unwelcome signs of spring for sufferers. This roundup of articles from our archives describes recent findings on protecting pollinators and coping with pollen season.</p>
<h2>1. Hey pollinators, over here</h2>
<p>Since pollen grains carry the cells that fertilize plants, it’s critical for them to get where they need to go. Often wind or gravity is all it takes, but for many plants, a pollinator has to carry the pollen grains. Some plants offer nectar or edible pollen to attract insects, bats or other animals, which carry pollen from plant to plant as they forage. Many flowers also <a href="https://theconversation.com/why-do-flowers-smell-151672">lure pollinators with scent</a>. </p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="Bee flying, coated with bright yellow particles." src="https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=467&fit=crop&dpr=1 600w, https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=467&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=467&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=586&fit=crop&dpr=1 754w, https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=586&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/458976/original/file-20220420-25-8bves7.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=586&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A thistle long-horned bee (<em>Melissodes desponsa</em>) covered with flower pollen.</span>
<span class="attribution"><a class="source" href="https://flic.kr/p/D8E563">Dejen Mengis, USGS</a></span>
</figcaption>
</figure>
<p>“Similar to the perfumes at a department store counter, flower scents are made up from a large and diverse number of chemicals which evaporate easily and float through the air,” writes Mississippi State University horticulturalist <a href="https://scholar.google.com/citations?user=dJ8gD7MAAAAJ&hl=en">Richard L. Harkess</a>. “To differentiate itself from other flowers, each species’ flowers put out a unique scent to attract specific pollinators. … Once pollinated, the flower stops producing a floral scent and nectar and redirects its energy to the fertilized embryo that will become the seed.”</p>
<hr>
<p>
<em>
<strong>
Read more:
<a href="https://theconversation.com/why-do-flowers-smell-151672">Why do flowers smell?</a>
</strong>
</em>
</p>
<hr>
<h2>2. Bees at the buffet</h2>
<p>It’s well known that many species of insects have <a href="https://theconversation.com/insect-apocalypse-not-so-fast-at-least-in-north-america-141107">declined in recent years</a>. One big focus is <a href="https://www.aphis.usda.gov/aphis/ourfocus/planthealth/plant-pest-and-disease-programs/honey-bees/honeybees">honeybees</a> and <a href="https://theconversation.com/beyond-honey-bees-wild-bees-are-also-key-pollinators-and-some-species-are-disappearing-89214">other species of bees</a>, which pollinate many important crops. </p>
<p>In a 2021 study, University of Florida agricultural extension specialist <a href="https://scholar.google.com/citations?user=I8IjAnIAAAAJ&hl=en">Hamutahl Cohen</a> found that when bees visited fields where sunflowers, grown as crops, were blooming over many acres, they <a href="https://theconversation.com/planting-mixes-of-flowers-around-farm-fields-helps-keep-bees-healthy-170527">picked up parasites at a high rate</a>. In contrast, bees that foraged in hedgerows around crop fields and could choose from diverse types of flowers to feed on spread out farther and had lower rates of infection. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="Diverse shrubs in a planted border with inset photos of beneficial insects that they attract." src="https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=447&fit=crop&dpr=1 600w, https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=447&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=447&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=561&fit=crop&dpr=1 754w, https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=561&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/458979/original/file-20220420-18-33gaht.jpeg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=561&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Hedgerows like this one in California have been shown to increase the number of beneficial insects like (left to right) lady beetles, syrphid flies and their larvae, shown feeding on aphids.</span>
<span class="attribution"><a class="source" href="https://ucanr.edu/sites/calagjournal/archive/?image=img6504p200.jpg">UCANR</a>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>“The more bees in sunflower fields, the more parasites,” Cohen observed. “Sunflower blooms were aggregating bees, which in turn was amplifying disease risk.” However, “in the presence of many flower types, bees disperse and spread across resources, reducing each individual bee’s likelihood of encountering an infected individual.” </p>
<hr>
<p>
<em>
<strong>
Read more:
<a href="https://theconversation.com/planting-mixes-of-flowers-around-farm-fields-helps-keep-bees-healthy-170527">Planting mixes of flowers around farm fields helps keep bees healthy</a>
</strong>
</em>
</p>
<hr>
<h2>3. Warmer weather means more pollen</h2>
<p>As climate change raises average temperatures across the U.S., growing seasons are starting earlier and ending later in the year. That’s <a href="https://theconversation.com/pollen-season-is-getting-longer-and-more-intense-with-climate-change-heres-what-allergy-sufferers-can-expect-in-the-future-179158">bad news for allergy sufferers</a>. </p>
<p>“The higher temperature will extend the growing season, giving plants more time to emit pollen and reproduce,” write University of Michigan atmospheric scientists <a href="https://clasp.engin.umich.edu/people/zhang-yingxiao/">Yingxiao Zhang</a> and <a href="https://scholar.google.com/citations?user=3dWPwz8AAAAJ&hl=en">Allison L. Steiner</a>. And by increasing the concentration of carbon dioxide in Earth’s atmosphere, climate change will make it possible for plants to grow larger and generate more pollen. </p>
<p>“Southeastern regions, including Florida, Georgia and South Carolina, can expect large grass and weed pollen increases in the future. The Pacific Northwest is likely to see peak pollen season a month earlier because of the early pollen season of alder,” Zhang and Steiner report.</p>
<hr>
<p>
<em>
<strong>
Read more:
<a href="https://theconversation.com/pollen-season-is-getting-longer-and-more-intense-with-climate-change-heres-what-allergy-sufferers-can-expect-in-the-future-179158">Pollen season is getting longer and more intense with climate change – here's what allergy sufferers can expect in the future</a>
</strong>
</em>
</p>
<hr>
<p><div data-react-class="Tweet" data-react-props="{"tweetId":"1511731348821745683"}"></div></p>
<h2>4. Providing better forecasts</h2>
<p>With all that pollen out there, how can allergy sufferers know when counts are high? Today the U.S. has only a rudimentary network of 90 pollen observation stations across the country, staffed by volunteers and run only during pollen season, so often there isn’t good information available when people need it.</p>
<p><a href="https://scholar.google.com/citations?user=sUwveOEAAAAJ&hl=en">Fiona Lo</a>, an environmental health scientist at the University of Washington, is working with colleagues to develop a model that can predict airborne pollen releases. “Our forecast can predict for specific pollen types because our model includes information about how each plant type interacts differently with the environment,” Lo reports.</p>
<p>So far, the model only predicts levels of four types of common pollen in areas where there are observation stations. Ultimately, though, Lo and her collaborators “want to provide a forecast every day during pollen season to give allergy sufferers the information they need to manage their symptoms. Allergies are often undertreated, and knowledge about self-care is limited, so a reliable pollen forecast that is easy to access – for example, via an app on your phone – along with education on allergy management, could really help allergy sufferers.”</p>
<hr>
<p>
<em>
<strong>
Read more:
<a href="https://theconversation.com/sunny-with-a-chance-of-sneezing-im-building-a-tool-to-forecast-pollen-levels-that-will-help-allergy-sufferers-know-when-its-safe-to-go-outside-162073">Sunny with a chance of sneezing – I'm building a tool to forecast pollen levels that will help allergy sufferers know when it's safe to go outside</a>
</strong>
</em>
</p>
<hr>
<h2>5. Support pollinators in your garden</h2>
<p>Pollen season is also gardening season, since it’s when plants are blooming. West Virginia University mycologist <a href="https://www.researchgate.net/profile/Brian-Lovett">Brian Lovett</a> offers advice for gardeners who want to <a href="https://theconversation.com/to-help-insects-make-them-welcome-in-your-garden-heres-how-153609">attract beneficial insects to their yards</a> for pollination and other purposes. </p>
<p>One step is to replace grass with native wildflowers, which will provide pollen and nectar for insects like ants, bees and butterflies. “Just as you may have a favorite local restaurant, insects that live around you have a taste for the flowers that are native to their areas,” Lovett notes.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="Striped black and yellow butterfly feeding on purple flower" src="https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/458980/original/file-20220420-13790-30cq5q.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Swallowtail butterflies, shown here on a liatris flower in Washington state, are efficient pollinators that can be attracted to home gardens.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/swallowtail-butterfly-on-a-liatris-spicata-flower-in-july-news-photo/624174230">Wolfgang Kaehler/LightRocket via Getty Images</a></span>
</figcaption>
</figure>
<p>Replacing white lightbulbs with yellow or warm-hued LED bulbs, and providing water in dishes or other containers, are also insect-friendly steps. Local university extension offices and gardening stores can offer other suggestions. </p>
<p>“In my view, humans all too often see ourselves as separate from nature, which leads us to relegate biodiversity to designated parks,” Lovett observes. “In fact, however, we are an important part of the natural world, and we need insects just as much as they need us.”</p>
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Read more:
<a href="https://theconversation.com/to-help-insects-make-them-welcome-in-your-garden-heres-how-153609">To help insects, make them welcome in your garden – here's how</a>
</strong>
</em>
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Pollen brings seasonal misery to millions of Americans, but it serves a critical purpose: fertilizing many kinds of plants, including food crops.Jennifer Weeks, Senior Environment + Cities Editor, The ConversationLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1708562021-12-01T13:35:43Z2021-12-01T13:35:43ZCharting changes in a pathogen’s genome yields clues about its past and hints about its future<figure><img src="https://images.theconversation.com/files/434799/original/file-20211130-14-gx51zb.jpg?ixlib=rb-1.1.0&rect=50%2C100%2C6176%2C4134&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">A virus's genes hold a record of where it's traveled, and when.</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/photo/global-pandemic-infographic-royalty-free-image/1270842570">imaginima/E+ via Getty Images</a></span></figcaption></figure><p>More than <a href="https://ourworldindata.org/covid-cases?country=%7EOWID_WRL">250 million people worldwide</a> have tested positive for SARS-CoV-2, usually after a diagnostic nose swab. Those swabs aren’t trash once they’ve delivered their positive result, though. For <a href="https://scholar.google.com/citations?user=L7pQoysAAAAJ&hl=en&oi=ao">scientists</a> <a href="https://scholar.google.com/citations?user=aDRW1JMAAAAJ&hl=en&oi=ao">like</a> <a href="https://scholar.google.com/citations?user=9hWmfYoAAAAJ&hl=en&oi=ao">us</a> they carry additional valuable information about the coronavirus. Leftover material from swabs can help us uncover hidden aspects of the COVID-19 pandemic.</p>
<p>Using what are called phylodynamic methods that can track a pathogen’s travels via changes in its genes, researchers are able to pinpoint factors like <a href="https://doi.org/10.1073/pnas.2012008118">where and when outbreaks start</a>, the <a href="https://doi.org/10.1038/s43856-021-00031-1">number of undetected infections</a> and <a href="https://doi.org/10.1038/s41467-020-19346-z">common routes of transmission</a>. Phylodynamics can also aid in understanding and tracking the spread of new pathogen variants, such as the recently detected <a href="https://twitter.com/trvrb/status/1464353224417325066">omicron variant of SARS-CoV-2</a>.</p>
<h2>What’s in a swab?</h2>
<p>Pathogens, just like people, each have a genome. This is RNA or DNA that contains an organism’s genetic code – its instructions for life and the information necessary for reproduction. </p>
<p>It’s now relatively <a href="https://www.nature.com/articles/d42859-020-00103-7">fast</a> and <a href="https://www.genome.gov/about-genomics/fact-sheets/DNA-Sequencing-Costs-Data">cheap</a> to sequence a pathogen’s genome. In Switzerland, <a href="https://bsse.ethz.ch/cevo/research/sars-cov-2/swiss-sars-cov-2-sequencing-consortium.html">a consortium of government and academic scientists</a> that we’re a part of as already extracted viral genome sequences from <a href="https://cov-spectrum.ethz.ch/explore/Switzerland/AllSamples/AllTimes">almost 80,000 SARS-CoV-2 positive swab tests</a>.</p>
<p>By lining up genetic sequences obtained from different patients, scientists can see which positions in the sequence differ. These differences represent mutations, small errors incorporated into the genome when the pathogen copies itself. We can use these mutational differences as clues to reconstruct chains of transmission and learn about epidemic dynamics along the way. </p>
<h2>Phylodynamics: Piecing together genetic clues</h2>
<p><a href="https://doi.org/10.1126/science.1090727">Phylodynamic methods</a> provide a way to describe how mutational differences relate to epidemic dynamics. These approaches allow researchers to get from the raw data about where mutations have occurred in the viral or bacterial genome to understanding all the implications. It might sound complicated, but it’s actually pretty easy to give an intuitive idea of how it works. </p>
<p>Mutations in the pathogen genome get passed from person to person in a transmission chain. Many pathogens acquire lots of <a href="https://doi.org/10.1016/S0169-5347(03)00216-7">mutations over the course of an epidemic</a>. Scientists can summarize these mutational similarities and differences using what’s essentially a family tree for the pathogen. Biologists call it <a href="https://docs.nextstrain.org/en/latest/learn/interpret/how-to-read-a-tree.html">a phylogenetic tree</a>. Each branching point represents a transmission event, when the pathogen moved from one person to another.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="diagram of sample to sequence to tree" src="https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=225&fit=crop&dpr=1 600w, https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=225&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=225&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=283&fit=crop&dpr=1 754w, https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=283&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/434467/original/file-20211129-19-1niweey.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=283&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A phylogenetic tree is an approximation of the past transmission chain, based on variations in the pathogen’s genetic sequence.</span>
<span class="attribution"><span class="source">Guinat, Windels, Nadeau</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>The branch lengths are proportional to the number of differences between sequenced samples. Short branches mean little time between branching points – fast transmission from person to person. Studying the length of branches on this tree can tell us about pathogen spread in the past – maybe even before we knew an epidemic was on the horizon.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="diagram of hypothetical virus outbreak's phylogenetic tree" src="https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=254&fit=crop&dpr=1 600w, https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=254&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=254&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=319&fit=crop&dpr=1 754w, https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=319&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/434470/original/file-20211129-15-rzms02.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=319&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Pathogen genome sequences can be used to construct phylogenetic trees and estimate hidden epidemic dynamics. Shorter branches stand for quicker transmission.</span>
<span class="attribution"><span class="source">Guinat, Windels, Nadeau</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<h2>Mathematical models of disease dynamics</h2>
<p>Models in general are simplifications of reality. They try to describe core real-life processes with mathematical equations. In phylodynamics, these equations describe the relationship between epidemic processes and the phylogenetic tree. </p>
<p>Take, for example, tuberculosis. It’s the <a href="https://www.who.int/publications/i/item/9789240037021">deadliest bacterial infection in the world</a>, and it is getting even more threatening because of the widespread evolution of antibiotic resistance. If you catch an antibiotic-resistant version of the tuberculosis bacterium, <a href="https://doi.org/10.1186/s40249-016-0214-x">treatment can take years</a>.</p>
<p>To predict the future burden of resistant tuberculosis, we want to estimate how fast it spreads.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="diagram of epidemiological processes in transmission of TB" src="https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=432&fit=crop&dpr=1 600w, https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=432&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=432&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=543&fit=crop&dpr=1 754w, https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=543&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/434837/original/file-20211130-14-kaj3am.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=543&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Epidemiologists work to track infections as the pathogen moves through a population.</span>
<span class="attribution"><span class="source">Guinat, Windels, Nadeau</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>To do this, we need a model that captures two important processes. First, there’s the course of infection, and second, there’s the development of antibiotic resistance. In real life, infected people can infect others, get treatment and, in the end, either be cured or, in the worst case, die from the infection. On top of this, the pathogen can develop resistance.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="diagram of information fed into mathematical model" src="https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=282&fit=crop&dpr=1 600w, https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=282&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=282&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=354&fit=crop&dpr=1 754w, https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=354&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/434480/original/file-20211129-27-e5whvt.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=354&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Phylodynamic models capture real-life epidemiological processes into mathematical equations and parameters.</span>
<span class="attribution"><span class="source">Guinat, Windels, Nadeau</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>We can translate these epidemiological processes into a mathematical model with two groups of patients – one group infected with normal tuberculosis and one with antibiotic-resistant tuberculosis. The important processes – transmission, recovery and death – can happen at different rates for each group. Finally, patients whose infection develops antibiotic resistance move from the first group to the second.</p>
<p>This model does ignore some aspects of tuberculosis outbreaks, such as asymptomatic infections or relapses after treatment. Even so, when applied to a set of tuberculosis genomes, this model helps us <a href="https://doi.org/10.1016/j.epidem.2021.100471">estimate how fast resistant tuberculosis spreads</a>. </p>
<h2>Capturing hidden aspects of epidemics</h2>
<p>Uniquely, phylodynamic approaches can help researchers answer questions in situations where diagnosed cases do not give the full picture. For example, what about the number of undetected cases or the source of a new epidemic? </p>
<p>A good example of this type of genome-based investigation is our recent work on <a href="https://ec.europa.eu/food/animals/animal-diseases/diseases-and-control-measures/avian-influenza_en#hpai-epidemic-20162017">highly pathogenic avian influenza (HPAI)</a> H5N8 in Europe. This epidemic spread to poultry farms and wild birds across <a href="https://doi.org/10.1111/tbed.12861">30 European countries</a> in 2016. In the end, <a href="https://www.bbc.com/news/world-europe-54825971">tens of millions of birds</a> were culled, devastating the poultry industry.</p>
<p>But were poultry farms or wild birds the real driver of spread? Obviously we cannot ask the birds themselves. Instead, phylodynamic modeling based on H5N8 genomes sampled from poultry farms and wild birds helped us get an answer. It turns out that in some countries the pathogen mainly spread from farm to farm, while in others it spread from wild birds to farms. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="ducks outside" src="https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=381&fit=crop&dpr=1 600w, https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=381&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=381&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=479&fit=crop&dpr=1 754w, https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=479&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/433527/original/file-20211123-21-lof9wy.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=479&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Phylodynamic models can estimate the number of avian influenza virus transmissions between wild birds and poultry.</span>
<span class="attribution"><span class="source">C. LeGall</span>, <a class="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">CC BY-NC-ND</a></span>
</figcaption>
</figure>
<p>In the case of HPAI H5N8, <a href="https://doi.org/10.1101/2021.10.22.465255">we helped animal health authorities focus control efforts</a>. In some countries this meant limiting transmission between poultry farms while in others limiting contact between domestic and wild birds.</p>
<p>More recently, phylodynamic analyses helped evaluate the impact of control strategies for SARS-CoV-2, including the <a href="https://doi.org/10.1073/pnas.2012008118">first border closures</a> and <a href="https://doi.org/10.1038/s41467-020-20235-8">strict early lockdowns</a>. A big advantage of phylodynamic modeling is that it can account for undetected cases. The models can even describe early stages of the outbreak in the absence of samples from that time period. </p>
<p>Phylodynamic models are under intensive development, continuously expanding the field to new applications and larger datasets. However, there are still challenges in extending genome sequencing efforts to undersampled species and regions and upholding <a href="https://doi.org/10.1038/d41586-021-00331-5">rapid public data sharing</a>. Ultimately, these data and models will help everyone gain new insights on epidemics and how to control them.</p>
<p>[<em>The Conversation’s science, health and technology editors pick their favorite stories.</em> <a href="https://theconversation.com/us/newsletters/science-editors-picks-71/?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=science-favorite">Weekly on Wednesdays</a>.]</p><img src="https://counter.theconversation.com/content/170856/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Claire Guinat receives funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 842621.</span></em></p><p class="fine-print"><em><span>Sarah Nadeau receives funding from the Swiss National Science Foundation and ETH Zurich. </span></em></p><p class="fine-print"><em><span>Etthel Windels does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>After a nose swab tests positive for a virus or bacteria, scientists can use the sample’s genetic sequence to figure out where and when the pathogen emerged and how fast it’s changing.Claire Guinat, Postdoctoral Fellow in Computational Evolution, Swiss Federal Institute of Technology ZurichEtthel Windels, Postdoctoral Fellow in Computational Evolution, Swiss Federal Institute of Technology ZurichSarah Nadeau, PhD Student in Computational Evolution, Swiss Federal Institute of Technology ZurichLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1620732021-08-03T12:34:16Z2021-08-03T12:34:16ZSunny with a chance of sneezing – I’m building a tool to forecast pollen levels that will help allergy sufferers know when it’s safe to go outside<figure><img src="https://images.theconversation.com/files/414210/original/file-20210802-26-1mcpjqh.jpg?ixlib=rb-1.1.0&rect=0%2C0%2C5539%2C3820&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Advance warning of high pollen levels could help people plan their activities to avoid allergies.</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/photo/car-driver-using-asthma-inhaler-royalty-free-image/1304794626">Dobrila Vignjevic/E+ via Getty Images</a></span></figcaption></figure><p>Do flowers blossoming in spring make you miserable? Are you sworn enemies with fall bloomers like ragweed? If you suffer from pollen allergies, imagine the usefulness of a reliable pollen forecast that could help you manage your symptoms by providing an early warning when pollen conditions are bad.</p>
<p>We’re working on it! <a href="https://scholar.google.com/citations?user=sUwveOEAAAAJ&hl=en&oi=ao">As an atmospheric scientist, I study</a> the weather, climate and anything in our Earth’s atmosphere, including pollen. One in three people in the U.S. <a href="https://doi.org/10.1056/NEJMcp1412282">suffer from allergic rhinitis</a>, otherwise known as “allergies,” and pollen is the most common cause.</p>
<p>While allergic rhinitis is not curable, its symptoms can be successfully treated. Two main methods are medication and pollen avoidance. They both rely on knowing when, where and how much pollen is, and is expected to be, in the air. Many medications work best if taken before symptoms occur. Advance knowledge of pollen allows allergy sufferers to change plans in order to minimize their exposure to pollen. </p>
<p>My colleagues and I are pulling together what we know about how plant biology and meteorology affect the amount of pollen in the air, along with pollen count numbers, to build a reliable pollen forecast. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="magnified view of pollen grains" src="https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=445&fit=crop&dpr=1 600w, https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=445&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=445&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=559&fit=crop&dpr=1 754w, https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=559&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/414211/original/file-20210802-24-1jmlm3j.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=559&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A view of pollen from various plants, magnified 586 times under the microscope.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/pollen-high-powered-photomicrographic-magnification-are-news-photo/179796938">BSIP/Universal Images Group via Getty Images</a></span>
</figcaption>
</figure>
<h2>Counting pollen grain by grain</h2>
<p>Allergic symptoms tend to be more severe the higher the concentration of airborne pollen. The amount of pollen in the air is constantly changing, so it would be ideal to monitor pollen in populated areas at regular frequent intervals. In the U.S., <a href="https://pollen.aaaai.org/#/">the National Allergy Bureau</a> collects, processes and distributes daily pollen concentrations from stations around the country. </p>
<p>Unfortunately, there are fewer than 90 active stations. Of these, many do not count on weekends or outside of the main pollen season. Part of the reason is that these are volunteer-run stations, and pollen monitoring requires significant time and resources.</p>
<p>Pollen is collected using a machine that sucks in air and traps pollen on sticky tape. A trained technician then processes, identifies and counts the tiny pollen grains under a microscope. During the height of pollen season, it may take a few hours for a technician to count the day’s pollen. Automated pollen monitoring systems do exist and would greatly reduce the need for human resources. But for now, these systems are either extremely expensive or have not been evaluated for accuracy.</p>
<h2>Building a forecasting model</h2>
<p>Pollen that causes allergic reactions is from <a href="http://sweetgum.nybg.org/science/glossary/glossary-details/?irn=2953">anemophilous or wind-pollinated plants</a>. Pollen grains contain the <a href="http://pollen.utulsa.edu/whatispollen.html">male sperm from the plant</a>, an essential component of plant reproduction. Anemophilous plants produce a lot of pollen because they rely on the whims of the wind to carry it to reach the female counterparts of their species to reproduce and grow new plants. The amount of pollen in the air has been rising because <a href="https://doi.org/10.1073/pnas.2013284118">climate change is lengthening the pollen season</a> and increasing how much pollen gets produced. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="backlit pollen wafts in the air around a flowering tree branch" src="https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=399&fit=crop&dpr=1 600w, https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=399&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=399&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=501&fit=crop&dpr=1 754w, https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=501&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/414212/original/file-20210802-26-18kit17.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=501&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Certain weather conditions make it more likely to be a heavy pollen day.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/photo/pollen-like-snow-royalty-free-image/91821142">Alkimson/iStock via Getty Images Plus</a></span>
</figcaption>
</figure>
<p>Since we have access to only a limited amount of pollen count data, my colleagues and I leverage what we know about the environment to estimate the amount of pollen in the air. Generally warm, sunny, dry and windy days are correlated with high airborne pollen concentrations, and rainy and humid days with low concentrations. </p>
<p>Plants depend on water and sunlight to grow. The timing of precipitation, temperature and solar radiation can affect a plant’s development and its readiness to flower. Once the plant is ready to flower, environmental variables can determine when pollen is released, how far it travels and how long it remains in the air. </p>
<p>The <a href="https://doi.org/10.1016/j.scitotenv.2021.145590">pollen model my colleagues and I have developed</a> uses these known relationships between meteorology and pollen to estimate airborne pollen. We also include satellite images of vegetation in the model because satellites can detect greening and provide an estimate of the beginning of spring.</p>
<p>Our model can forecast pollen 1 to 14 days in advance for locations where there are pollen stations. But due to the sparsity of pollen stations, we are working on extending the model to forecast in locations with no pollen counts. In those places we use nearby pollen station data, along with localized meteorology, to estimate the pollen. </p>
<p>Although pollen reporting and forecasts do exist in the popular media, <a href="https://doi.org/10.1186/1710-1492-8-S1-A11">their pollen reports differ from observations</a>, and their forecasts are limited only to categories of trees, grasses and weeds. Our forecast can predict for specific pollen types because our model includes information about how each plant type interacts differently with the environment.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="woman checks her phone against backdrop of windows at night" src="https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/414213/original/file-20210802-18-11a1ai0.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Checking the pollen forecast could help you plan when to take allergy medication and how much time you’d spend outside.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/photo/young-businesswoman-checking-smartphone-in-the-royalty-free-image/969436696">Klaus Vedfelt/DigitalVision via Getty Images</a></span>
</figcaption>
</figure>
<h2>A fine-tuned forecast in your pocket</h2>
<p>We are collaborating with medical professionals and health scientists to understand the pollen levels associated with increasing severity of allergic symptoms. Our plan is to tailor the forecast to allow patients to better manage their symptoms.</p>
<p>So far, we can accurately forecast for four of the most abundant pollen types in the U.S. only in locations with pollen stations. We are seeking funding to expand to other pollen types and other locations, and we are working on creating a platform to automate the data processing and run the forecast.</p>
<p>Ultimately, we want to provide a forecast every day during pollen season to give allergy sufferers the information they need to manage their symptoms. <a href="https://doi.org/10.1016/j.rmed.2005.05.012">Allergies are often undertreated</a> and <a href="https://doi.org/10.1111/crj.12015">knowledge about self-care is limited</a>, so a reliable pollen forecast that is easy to access – for example via an app on your phone – along with education on allergy management, could really help allergy sufferers.</p>
<p>[<em>You’re smart and curious about the world. So are The Conversation’s authors and editors.</em> <a href="https://theconversation.com/us/newsletters/the-daily-3?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=youresmart">You can read us daily by subscribing to our newsletter</a>.]</p><img src="https://counter.theconversation.com/content/162073/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Fiona Lo does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>Scientists are building a pollen forecasting model using meteorology, botany, pollen count numbers and satellite imagery to help people plan ahead.Fiona Lo, Postdoctoral Researcher in Environmental and Occupational Health Sciences, University of WashingtonLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1610682021-05-24T12:11:39Z2021-05-24T12:11:39Z578,555 people have died from COVID-19 in the US, or maybe it’s 912,345 – here’s why it’s hard to count<figure><img src="https://images.theconversation.com/files/402197/original/file-20210521-13-4t19hq.jpg?ixlib=rb-1.1.0&rect=1034%2C0%2C4716%2C2940&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">A November 2020 memorial in Washington, D.C. consisted of thousands of flags, each planted to remember someone who died of COVID-19.</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/on-the-eve-of-the-2020-presidential-election-the-last-of-news-photo/1283614255">Andrew Lichtenstein/Corbis via Getty Images</a></span></figcaption></figure><p>When the Institute for Health Metrics and Evaluation at the University of Washington released its <a href="http://www.healthdata.org/special-analysis/estimation-excess-mortality-due-covid-19-and-scalars-reported-covid-19-deaths">estimate that COVID-19 had killed 912,345 people</a> in the U.S. by May 6, 2021, many were shocked. That’s 60% higher than the <a href="http://www.healthdata.org/special-analysis/estimation-excess-mortality-due-covid-19-and-scalars-reported-covid-19-deaths">578,555 coronavirus-related deaths</a> officially reported to the U.S. Centers for Disease Control and Prevention over this same period.</p>
<p>How can <a href="https://nymag.com/intelligencer/2021/05/have-over-343-000-more-americans-died-from-covid.html">two estimates differ so widely</a>? It’s not like the Institute for Health Metrics and Evaluation researchers stumbled upon a morgue of more than 300,000 dead people who hadn’t been tracked elsewhere.</p>
<p>Here’s what goes into some of the various counts of COVID-19 pandemic deaths and how <a href="https://scholar.google.com/citations?user=kWGF578AAAAJ&hl=en&oi=ao">I as a statistician</a> think about their differences.</p>
<h2>Tracking deaths</h2>
<p>When someone dies, a medical professional records the immediate cause and up to three underlying conditions that “initiated the events resulting in death” on the <a href="https://www.cdc.gov/nchs/data/dvs/death11-03final-acc.pdf">death certificate</a>. Death certificate information is transmitted to the <a href="https://www.cdc.gov/nchs/nvss/index.htm">National Vital Statistics System</a> for a variety of public health uses, including tabulating the <a href="https://www.cdc.gov/nchs/nvss/leading-causes-of-death.htm">leading causes of death</a> in the U.S. </p>
<p>But death certificate information may not reflect the actual number of COVID-19 deaths. A COVID-19 diagnosis could have been missed by health care workers, or the disease could have gone unrecorded on a death certificate. There’s always going to be some error in the data. </p>
<p>One way to think about this is:</p>
<p>OBSERVED COUNT = TRUE COUNT + ERROR</p>
<p>That is, we want to know the real number of COVID-19 deaths in the U.S., the “true count.” But because the real world is messy, we’ll never know that true count and can only approximate it. The unknown true count combines with unknown errors to give us the observed count – for instance, the tally from all the nation’s death certificates.</p>
<p>If the predominant error is that some COVID-19-related deaths were missed – perhaps due to a lack of testing earlier in the pandemic – then the observed count would be an underestimate of the true count. However, there could be additional types of errors as well, and those may cause the observed count to deviate further or in other ways from the true count.</p>
<h2>Calculating ‘all cause’ excess mortality</h2>
<p>One way around this dilemma is to focus on how many deaths were recorded over and above the number expected by epidemiologists and statisticians had the pandemic not happened. This count is called “all cause” excess mortality. It’s based on historical data.</p>
<p><a href="https://doi.org/10.1111/1740-9713.01485">Estimates from this type of analysis</a> suggest that the reported number of COVID-19 deaths <a href="https://theconversation.com/279-700-extra-deaths-in-the-us-so-far-in-this-pandemic-year-147887">may be an underestimate</a>. Many more people died during the pandemic than normally would have during that time period. And it’s a higher number than how many people died of COVID-19 according to death certificate counts.</p>
<p><iframe id="Wb0re" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/Wb0re/1/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<p>For example, the estimated number of deaths above what was expected in 2020 was almost 412,000 people, while the number of deaths the CDC attributed to COVID‐19 as of Jan. 6, 2021 was 356,000.</p>
<p>This type of analysis cannot conclude that the excess deaths are due to COVID-19 itself, only that the aggregate impact of the pandemic resulted in more deaths than would have been expected in its absence.</p>
<h2>Reconsidering the number of expected deaths</h2>
<p>So if by May 2021 there were 578,555 reported COVID-19-related deaths and perhaps as many as <a href="https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm">663,000 excess deaths according to CDC data</a>, how did the Institute for Health Metrics and Evaluation come up with the figure 912,345?</p>
<p>Their analysis seeks to determine the true number of COVID-19 deaths by estimating other effects due to the pandemic. IHME then uses its estimates of those effects to adjust the observed COVID-19 death count. </p>
<p>Some factors they considered would likely contribute to more deaths: health care that was delayed or deferred; mental health disorders that were untreated; increased alcohol use and opioid use during the pandemic. They also considered factors that would likely cut down on deaths: decreased numbers of injuries; reduced transmission of diseases that weren’t COVID-19.</p>
<p>They then used these estimates to adjust the expected number of deaths in an effort to better quantify the number of deaths attributable to COVID-19. In effect, they were applying these pandemic-specific “errors” to the excess death estimates that were based on pre-pandemic historical trends.</p>
<p>Ideally, this type of analysis should result in excess mortality being a better measure of the number of deaths that can be attributed to COVID-19. It depends, though, on having sufficient detailed data available and requires certain assumptions about that data.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="masked people stand outside in a socially distanced way" src="https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=413&fit=crop&dpr=1 600w, https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=413&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=413&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=519&fit=crop&dpr=1 754w, https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=519&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/402198/original/file-20210521-21-yrpa8b.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=519&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Attendees at an April 2021 ceremony to memorialize people who died of COVID-19.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/at-the-reading-hospital-in-west-reading-pa-thursday-evening-news-photo/1311683124">Ben Hasty/MediaNews Group/Reading Eagle via Getty Images</a></span>
</figcaption>
</figure>
<h2>So which number is right?</h2>
<p>Such a simple question is actually quite hard to answer for many reasons.</p>
<p>One is that each number is the answer to a different question. The number of “all cause” excess deaths quantifies how many people died from any cause above what we would have expected if the death rate during the pandemic had followed pre-pandemic patterns. The Institute for Health Metrics and Evaluation number is an estimate of the total number of deaths that can be attributed to COVID-19. Both are useful for understanding the impact of the pandemic.</p>
<p>Yet, even two estimates of the total number of COVID-19 deaths are going to differ because the estimates could be based on different methodologies, different sources of data and different assumptions. That’s not necessarily a problem. It may be that the results turn out to be relatively consistent, suggesting the conclusions don’t depend on the assumptions. Alternatively, if the results are very different, that can help researchers understand the problem better.</p>
<p>However, even small differences between studies can, unfortunately, sow distrust in science for some people. But it’s all part of the <a href="https://theconversation.com/science-can-seem-like-madness-but-theres-always-method-4013">scientific method</a> in which studies get reviewed by researchers’ peers, <a href="https://theconversation.com/scientific-theories-arent-mere-conjecture-to-survive-they-must-work-73040">questioned and dissected, and then revised</a> as a result. Science is an iterative process in which gut instinct and guesses get refined into theories and then may be subsequently refined into facts and knowledge.</p>
<p>In this case, the Institute for Health Metrics and Evaluation study provides some evidence of what researchers like me suspected: The number of excess deaths in the U.S., while larger than the number of deaths attributed to COVID-19, may also be an undercount of the true number of COVID-19 deaths. It is also consistent with a <a href="https://www.nytimes.com/live/2021/05/21/world/covid-vaccine-coronavirus-mask#who-covid-deaths-excess">World Health Organization analysis</a> that concludes the number of COVID-19 deaths in some countries could be two to three times greater than the number recorded. But no single study offers definitive proof, just one more piece of evidence on the path to better understanding the deadly impact of this pandemic.</p>
<p>[<em>The Conversation’s science, health and technology editors pick their favorite stories.</em> <a href="https://theconversation.com/us/newsletters/science-editors-picks-71/?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=science-favorite">Weekly on Wednesdays</a>.]</p><img src="https://counter.theconversation.com/content/161068/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Ronald D. Fricker Jr. does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>Record-keepers have a pretty good sense of how many people have died. But figuring out the cause of those deaths is a lot trickier – and that’s why reasonable modelers can disagree.Ronald D. Fricker Jr., Professor of Statistics and Senior Associate Dean, Virginia TechLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1608472021-05-14T12:46:06Z2021-05-14T12:46:06ZHalston: The glittering rise – and spectacular fall – of a fashion icon<figure><img src="https://images.theconversation.com/files/400633/original/file-20210513-14-q4ux54.jpg?ixlib=rb-1.1.0&rect=0%2C8%2C2973%2C2124&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Halston with the Halstonettes – a group of models who were part of his entourage – at the Metropolitan Museum of Art in New York City in 1980.</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/halston-and-halstonettes-during-diana-vreelands-costume-news-photo/105451563?adppopup=true">Ron Galella/Ron Galella Collection via Getty Images</a></span></figcaption></figure><p>Walk into any department store, and you’ll get a sense of the powerful brands built by high-end American designers: <a href="https://www.latimes.com/archives/la-xpm-1992-02-23-tm-4945-story.html">Calvin Klein</a>, <a href="https://www.forbes.com/sites/briansolomon/2014/02/04/michael-kors-is-fashions-newest-billionaire/">Michael Kors</a>, <a href="https://www.britannica.com/biography/Ralph-Lauren">Ralph Lauren</a>, <a href="https://jwa.org/encyclopedia/article/karan-donna">Donna Karan</a>. They created veritable fashion empires by leveraging their names to create lower-priced lines and sign profitable licensing agreements.</p>
<p>But before them all, there was <a href="https://www.vanityfair.com/news/1991/09/halston-life-story">Roy Halston Frowick</a> – better known by the singular appellation Halston. </p>
<p>The subject of <a href="https://www.imdb.com/title/tt9569546/">an eponymous Netflix miniseries</a> starring Ewan McGregor, Halston became one of the earliest American designers to extend his brand to multiple price points. In doing so, he made designs that were normally out of reach for everyday Americans available to the masses.</p>
<p>But as <a href="https://scholar.google.nl/citations?user=Vzju6pwAAAAJ&hl=en">fashion</a> <a href="https://jfgordon.net/about.html">historians</a>, we’ll often tell Halston’s story as a cautionary one. Though he made style seem effortless, his relationship with the fashion industry was anything but uncomplicated.</p>
<h2>Attuned to the mood</h2>
<p>A born-and-bred Midwesterner, Halston found early success in hat design working as a custom milliner for <a href="https://style.time.com/2012/09/12/happy-111th-birthday-bergdorf-goodman-a-brief-history-in-numbers/">Bergdorf Goodman</a>. Halston soon became known as a trendsetter, and, in a notable triumph for the young designer, first lady Jacqueline Kennedy <a href="https://www.cnn.com/videos/fashion/2019/08/20/cnn-films-halston-jackie-kennedy-pillbox-hat-ron-3.cnn">wore one of Halston’s signature pillbox hats</a> at her husband’s inauguration. </p>
<figure class="align-center ">
<img alt="Jackie Kennedy rides in a car alongside John F. Kennedy." src="https://images.theconversation.com/files/400402/original/file-20210512-24-1w3vonk.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/400402/original/file-20210512-24-1w3vonk.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=403&fit=crop&dpr=1 600w, https://images.theconversation.com/files/400402/original/file-20210512-24-1w3vonk.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=403&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/400402/original/file-20210512-24-1w3vonk.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=403&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/400402/original/file-20210512-24-1w3vonk.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=506&fit=crop&dpr=1 754w, https://images.theconversation.com/files/400402/original/file-20210512-24-1w3vonk.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=506&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/400402/original/file-20210512-24-1w3vonk.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=506&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption">First lady Jacqueline Kennedy donned one of Halston’s iconic pillbox hats on Inauguration Day in 1961.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/washington-dc-married-couple-us-president-john-f-kennedy-news-photo/514704760?adppopup=true">Bettmann/Getty Images</a></span>
</figcaption>
</figure>
<p>Later in the 1960s, Halston made the foray into dress design. His success was equal parts talent and serendipity, and he once described his approach as “<a href="https://www.proquest.com/wwd/docview/1445680315/EC61F7898B0F45E9PQ/1?accountid=10906&imgSeq=1">editing the mood of what’s happening</a>.”</p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="A mannequin dressed in a tan Halston shirtdress." src="https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=840&fit=crop&dpr=1 600w, https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=840&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=840&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1055&fit=crop&dpr=1 754w, https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1055&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/400405/original/file-20210512-19-1jh3dfh.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1055&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A tan Ultrasuede Halston shirtdress from 1972.</span>
<span class="attribution"><a class="source" href="https://upload.wikimedia.org/wikipedia/commons/6/6c/Halston_shirt_dress.jpg">Museum at FIT/Wikimedia Commons</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<p>Although overt simplicity may seem incongruous with grandeur, Halston garments were both understated and luxurious.</p>
<p>Halston’s body-skimming <a href="https://www.1stdibs.com/fashion/clothing/evening-dresses/rare-halston-hand-painted-caftan/id-v_210060/">silk chiffon caftans</a>, <a href="http://d6vrtzdlbankn.cloudfront.net/wp-content/uploads/2017/04/12-Halston-Original-Iman-jersey-dress-spring-1976-584x1024.jpeg">jersey wraparound dresses</a> and <a href="https://www.nytimes.com/1971/12/09/archives/halstons-revival-of-sweater-girl.html">long cashmere sweaters</a> were often constructed using just one piece of fabric. They covered the body fully, but through careful manipulation of the fabric – wrapping, draping and twisting – Halston’s pieces were sensuous and flattering. </p>
<p><a href="https://www.nytimes.com/1977/02/26/archives/ultra-demand-for-versatile-ultrasuede.html">Halston was even able to turn Ultrasuede</a> – a soft, synthetic, machine-washable faux suede – into a status symbol, molding it into elegant shirtdresses and coats. These became popular despite – or maybe because of – their utter plainness. His garments were fitting for the 1970s, <a href="https://www.bloomberg.com/opinion/articles/2020-09-16/how-1970s-oil-prices-stagflation-changed-the-u-s-economy">when a shaky economy</a> made flagrant displays of wealth unseemly.</p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="A red dress on a mannequin." src="https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=902&fit=crop&dpr=1 600w, https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=902&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=902&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1134&fit=crop&dpr=1 754w, https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1134&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/400631/original/file-20210513-17-1pwngsf.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1134&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A silk Halston evening dress, designed in the mid-1970s.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/evening-dress-ca-1976-silk-jersey-by-halston-news-photo/150057792?adppopup=true">Chicago History Museum/Getty Images</a></span>
</figcaption>
</figure>
<p>Yet the designer’s social life was the opposite of understated. In fact, the image of fashion design as a glamorous and exciting profession owes much to Halston. During his heyday, he was at “the top of the fashion show-biz heap,” as Women’s Wear Daily publisher John Fairchild <a href="https://books.google.com/books/about/Chic_Savages.html?id=qezxAAAAMAAJ">once wrote</a>. </p>
<p>At the legendary <a href="https://www.gq-magazine.co.uk/culture/article/studio-54">Studio 54</a>, he mingled with Bianca Jagger and Andy Warhol. The world-famous disco club became both a showroom for Halston’s designs and a stage for the man himself, and Halston was often accompanied by an entourage of beautiful women known as “<a href="https://exhibitions.fitnyc.edu/blog-ysl-halston/the-halstonettes/">the Halstonettes</a>.”</p>
<h2>Halston the businessman</h2>
<p>As his stature grew, Halston always looked for ways to expand his fashion empire.</p>
<p>Early in his career, he experimented with what’s known as “<a href="https://link.springer.com/chapter/10.1057%2F9781137492265_5">brand diffusion</a>” – which is companies’ use of the same brand name on items at varying price points. </p>
<p>His high-end line was Halston Ltd., a made-to-order, ready-to-wear business. Located on New York City’s Madison Avenue, it catered to an exclusive list of private clientele that included film and television stars like Lauren Bacall, Greta Garbo, Liza Minelli and Elizabeth Taylor. </p>
<p>Meanwhile, the Halston Originals boutique sold dresses to department stores across the country, <a href="https://www.newspapers.com/newspage/383974238/">with prices ranging from US$150 to over $1,000</a>. And with Halston International, the designer created “component” knit pieces – not outfits, but singular garments, turtlenecks, sweater sets, shirts and coats – that consumers could mix and match to their delight.</p>
<figure class="align-center ">
<img alt="Halston kisses Bianca Jagger on the cheek behind her birthday cake." src="https://images.theconversation.com/files/400630/original/file-20210513-13-15t5sum.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/400630/original/file-20210513-13-15t5sum.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=454&fit=crop&dpr=1 600w, https://images.theconversation.com/files/400630/original/file-20210513-13-15t5sum.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=454&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/400630/original/file-20210513-13-15t5sum.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=454&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/400630/original/file-20210513-13-15t5sum.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=570&fit=crop&dpr=1 754w, https://images.theconversation.com/files/400630/original/file-20210513-13-15t5sum.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=570&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/400630/original/file-20210513-13-15t5sum.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=570&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption">Bianca Jagger and Halston during Jagger’s birthday party at Studio 54.</span>
<span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/bianca-jagger-and-designer-halston-attend-the-birthday-news-photo/156188908?adppopup=true">Ron Galella/Ron Galella Collection via Getty Images</a></span>
</figcaption>
</figure>
<p>After the business conglomerate Norton Simon Inc. acquired the Halston businesses in 1973, Halston remained lead designer of his many collections. He worked at a frenetic pace, creating all of the uniforms for the winter and summer 1976 U.S. Olympic athletes and making costumes for Martha Graham’s ballet production “<a href="https://www.gettyimages.ie/detail/news-photo/ballet-dancer-rudolph-nureyev-welcomes-choreographer-martha-news-photo/583900365?adppopup=true">Lucifer</a>.” Products bearing his name included perfumes, luggage, home linens, coats, rainwear and even wigs. By 1983, Halston Enterprises was generating an estimated <a href="https://www.proquest.com/wwd/docview/1445680315/EC61F7898B0F45E9PQ/1">$150 million in annual sales</a>.</p>
<p>Perhaps emboldened by his success or motivated by his heartland roots, Halston signed with JCPenney in 1983 for the creation of an exclusive line that was, as he put it, “<a href="https://www.proquest.com/wwd/docview/1445680315/EC61F7898B0F45E9PQ/1">for the American people</a>.” </p>
<p>With items priced from $24 to $200, the “III line” marked a new era in fashion and retailing. </p>
<figure class="align-right ">
<img alt="A man looks at two stylishly dressed women walking by." src="https://images.theconversation.com/files/400611/original/file-20210513-19-1ikpmp9.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/400611/original/file-20210513-19-1ikpmp9.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=887&fit=crop&dpr=1 600w, https://images.theconversation.com/files/400611/original/file-20210513-19-1ikpmp9.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=887&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/400611/original/file-20210513-19-1ikpmp9.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=887&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/400611/original/file-20210513-19-1ikpmp9.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1115&fit=crop&dpr=1 754w, https://images.theconversation.com/files/400611/original/file-20210513-19-1ikpmp9.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1115&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/400611/original/file-20210513-19-1ikpmp9.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1115&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption">The Halston III line for JCPenney was the first by a high-end American fashion designer licensing his name.</span>
<span class="attribution"><a class="source" href="https://www.flickr.com/photos/barbiescanner/38453218924/in/photostream/">barbiescanner/flickr</a></span>
</figcaption>
</figure>
<p>While high-end fashion designer <a href="https://www.latimes.com/obituaries/story/2020-12-29/pierre-cardin-dead">Pierre Cardin</a> pioneered this form of licensing in Europe, the project of pairing a high-fashion designer with a mass merchandiser best known for selling Levi’s, hardware and household goods was unusual in the United States. While Halston contended it was <a href="https://www.proquest.com/wwd/docview/1445680315/EC61F7898B0F45E9PQ/1">immensely successful</a>, claiming it generated $1 billion in sales, JCPenney’s executives were less enthusiastic. By the mid-1980s, industry insiders were suggesting that <a href="https://www.nytimes.com/1985/09/05/business/a-slow-start-for-an-upscale-penney-s.html">the garments were not selling as well as expected</a>. </p>
<p>The JCPenney’s deal ultimately proved to be damaging for Halston. Wary high-end retailers, including his early employer, Bergdorf Goodman, were fearful that the prestige of the Halston name was sullied by its presence on the racks of a mass-market merchandiser. Bergdorf Goodman eventually dropped his line altogether. </p>
<p>Meanwhile, Halston’s growing reputation of excessive spending and erratic behavior increasingly left his brand to the decisions of businessmen and creative control to other parties. Halston was relegated to the sidelines, and <a href="https://www.nytimes.com/1987/03/15/magazine/no-headline-650887.html">his corporate deals effectively cost him the right to his own name</a>. </p>
<p>In 1988, Halston was diagnosed with AIDS. He lived out of the public eye until his death in 1990.</p>
<h2>Others follow Halston’s lead</h2>
<p>Despite its eventual failure, Halston’s pairing with JCPenney was truly ahead of its time. </p>
<p>Citing the importance of creating practical, easy-care leisurewear for working women and young mothers, Halston tried to offer a fashionable wardrobe at reasonable prices that nearly everyone could afford.</p>
<p>Contemporaries such as <a href="https://www.harpersbazaar.com/fashion/trends/a23741794/anne-klein-shopbazaar-50-years-exhibit/">Anne Klein</a>, Calvin Klein, Ralph Lauren and <a href="https://www.nytimes.com/2021/05/13/style/Kenzo-Auction.html">Kenzo Takada</a> would immediately try out similar diffusion lines. All pulled it off without suffering the extraordinary professional cost that Halston endured. </p>
<p>These designers’ corporate and creative decisions were arguably more tightly controlled than Halston’s devil-may-care diffusion. Acquisitions of these companies by larger conglomerates occurred much later than Halston’s, often decades into the brand’s existence. Perhaps this gave additional time for these brands to arrive at a more singular vision. </p>
<p>Maintaining a consistent direction over such a diverse array of lines proved unfeasible for Halston, and something was lost along the way: the cachet and the allure that made a Halston a Halston. </p>
<p>Halston’s successes and ultimate downfall have provided a cautious inspiration. Isaac Mizrahi’s 2003 <a href="https://www.racked.com/2016/3/10/11183334/isaac-mizrahi-target-qvc">collaboration with Target</a> – 20 years after Halston’s pairing with JCPenney – became a boon for both parties.</p>
<p>It was not, however, without trepidation. In 2019, <a href="https://www.nytimes.com/2019/08/28/style/youve-heard-of-the-drop-target-had-it-first.html">Mizrahi reminisced that the partnership</a> “was a very scary thing. Halston was my idol … and he had failed.” </p>
<p>[<em>Get the best of The Conversation, every weekend.</em> <a href="https://theconversation.com/us/newsletters/weekly-highlights-61?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=weeklybest">Sign up for our weekly newsletter</a>.]</p>
<p>Relationships between designers and retailers are now commonplace in a climate where the most fashionable and visible of women freely mix and match mass market and luxury items, and designers <a href="https://www.eonline.com/photos/17507/best-designer-collaborations-of-all-time">deftly jump between discount retail and the runway</a>. </p>
<p>Halston’s brand lives on, but resuscitating it has been a long process. <a href="https://www.nytimes.com/2011/09/04/fashion/the-men-and-women-who-would-be-halston.html">Fashion heavyweights</a> Kevan Hall and Marios Schwab, as well as style figures Rachel Zoe and Sarah Jessica Parker, have lent their creativity and business acumen to the brand, with limited success.</p>
<p>With the release of Netflix’s “Halston,” a new revival is at hand: not of the line, but of the personality that for a comparatively brief – but glittering – moment, ruled the fashion world with devastating simplicity.</p><img src="https://counter.theconversation.com/content/160847/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.</span></em></p>The subject of a new Netflix miniseries, Halston once ruled over New York’s fashion world. But the designer with a devil-may-care approach to his business dealings attempted too much, too quickly.Jennifer Gordon, Lecturer of Apparel, Events and Hospitality Management, Iowa State UniversitySara Marcketti, Professor of Apparel, Events, and Hospitality Management, Iowa State UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1558342021-03-02T13:24:07Z2021-03-02T13:24:07ZThe Texas blackouts showed how climate extremes threaten energy systems across the US<figure><img src="https://images.theconversation.com/files/387079/original/file-20210301-19-11yngph.jpg?ixlib=rb-1.1.0&rect=43%2C7%2C4749%2C2924&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Electric service trucks line up after a snow storm in Fort Worth, Texas, on Feb. 16, 2021.</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/pike-electric-service-trucks-line-up-after-a-snow-storm-on-news-photo/1231205567?adppopup=true">Ron Jenkins/Getty Images</a></span></figcaption></figure><p>Pundits and politicians have been quick to point fingers over the <a href="https://www.wsj.com/articles/texas-power-grid-was-minutes-from-collapse-during-freeze-operator-says-11614202063">debacle in Texas</a> that left millions without power or clean water during February’s deep freeze. Many have blamed the state’s <a href="https://www.nytimes.com/2021/02/21/us/texas-electricity-ercot-blackouts.html">deregulated electricity market</a>, arguing that Texas prioritized cheap power over reliability.</p>
<p>But climate extremes are wreaking increasing havoc on energy systems across the U.S., regardless of local politics or the particulars of regional grids. For example, conservatives argued that <a href="https://thehill.com/homenews/news/539038-texas-lawmakers-tweets-mocking-california-power-outages-resurface-amid-winter-storm">over-regulation caused widespread outages in California</a> amid extreme heat and wildfires in the summer of 2020.</p>
<p>As an <a href="https://engineering.purdue.edu/LASCI">engineering professor</a> studying <a href="https://scholar.google.com/citations?user=I5tDhsoAAAAJ&hl=en">infrastructure resilience under climate change</a>, I worry about the rising risk of <a href="https://doi.org/10.1016/j.ress.2018.03.015">climate-triggered outages nationwide</a>. In my view, the events in Texas offer three important lessons for energy planners across the U.S. </p>
<figure>
<iframe width="440" height="260" src="https://www.youtube.com/embed/ANGcms9OQd8?wmode=transparent&start=0" frameborder="0" allowfullscreen=""></iframe>
<figcaption><span class="caption">Extreme weather poses a growing threat to power systems across the U.S.</span></figcaption>
</figure>
<h2>Not enough attention to climate extremes</h2>
<p>Experts widely agree that the Electric Reliability Council of Texas, or <a href="http://www.ercot.com/">ERCOT</a>, the nonprofit corporation that manages the power grid for most of the state, failed to anticipate <a href="https://www.economist.com/united-states/2021/02/17/the-freeze-in-texas-exposes-americas-infrastructural-failings">how sharply demand would spike</a> prior to the February cold wave. ERCOT has a record of lacking capacity to meet winter demand surges. The state grid <a href="https://www.statesman.com/article/20110411/NEWS/304119704">nearly collapsed during a 2011 winter storm</a> and experienced another <a href="https://www.statesman.com/article/20140107/BUSINESS/301079651">close call</a> in 2014, narrowly avoiding rolling blackouts.</p>
<p>But grid operators elsewhere have also <a href="https://doi.org/10.1038/s41598-020-67695-y">underestimated how climate extremes can influence electricity demand</a>. I see many similarities between <a href="https://www.theguardian.com/environment/2021/feb/19/power-outages-texas-california-climate-crisis">California’s summer 2020 power crisis</a> and recent events in Texas.</p>
<p>In both cases, extreme weather caused an unexpected increase in demand and reduced generation capacity at the same time. Because energy operators did not foresee these effects, they had to <a href="https://www.texastribune.org/2021/02/18/texas-power-outages-ercot/">resort to rolling blackouts</a> to avert even bigger disasters.</p>
<p><div data-react-class="Tweet" data-react-props="{"tweetId":"1294479825910943746"}"></div></p>
<p>In studies I have conducted in my research lab and in collaboration with <a href="https://scholar.google.de/citations?user=mU4l0vIAAAAJ&hl=en">hydroclimatologist Rohini Kumar</a>, we have found that energy planners in many parts of the U.S. <a href="https://doi.org/10.1038/s41467-020-15393-8">substantially underestimate</a> how sensitive electricity demand is to climate factors. This tendency has significant implications for the <a href="https://doi.org/10.1111/risa.13192">security and reliability of the power systems</a>. </p>
<p>For example, in a study published in April 2020 we analyzed the use of artificial intelligence models for energy forecasting that <a href="https://doi.org/10.1038/s41467-020-15393-8">accounted for the role of humidity</a> in addition to air temperature. We found that such models could make forecasts of energy demand for air conditioning on hot days significantly more accurate across the U.S. More accurate demand forecasts help energy planners understand how much power they will need to meet peak demand during weather extremes.</p>
<p>Grid operators can prepare more effectively for the effects of climate change on both supply and demand by using forecasting models and software that academic researchers have already developed. Many of these new solutions have been <a href="https://doi.org/10.1038/s41467-020-15393-8">published in open-access journals</a>.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="Graphic showing demand increases in Minneapolis, Madison, Chicago, Cleveland, Columbus and Indianapolis." src="https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=323&fit=crop&dpr=1 600w, https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=323&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=323&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=406&fit=crop&dpr=1 754w, https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=406&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/387070/original/file-20210301-12-1p5e53w.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=406&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Results published in the journal Climactic Change from a model that predicts how much summertime electricity and water use in Midwest cities could increase due to climate change between 2030 and 2052. These projections only consider climate effects, not other factors such as population growth or technological shifts.</span>
<span class="attribution"><a class="source" href="https://www.purdue.edu/uns/images/2020/nateghi-cities.jpg">Greg Simmons/Purdue University</a>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<h2>Water, electricity and natural gas are connected</h2>
<p>Electricity, water and natural gas are essential resources, and it’s hard to have any of them without the others. For example, drilling for natural gas consumes electricity and water. Many power plants burn natural gas to generate electricity. And transporting water and gas requires electricity to pump them through pipelines.</p>
<p>Because of these tight connections, outages in one system are bound to ripple through the others and create a cascade of service disruptions. For example, during the Texas cold wave, pumps used to extract gas in West Texas <a href="https://www.texastribune.org/2021/02/16/natural-gas-power-storm/">could not operate</a> because of electricity outages. This cut state gas field production in half, which in turn strained gas-fired electricity production. Power failures also <a href="https://www.texastribune.org/2021/02/20/texas-power-water-outages/">hampered water pumping and treatment</a>, potentially allowing bacteria to <a href="https://www.inquirer.com/weather/texas-power-outages-safe-drinking-water-20210219.html">seep into water supplies</a>. </p>
<p>In a collaborative project connecting researchers at <a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832688&HistoricalAwards=false">Purdue University</a>, the <a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832711">University of Southern California</a>, and the <a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=1832683">University of California-Santa Cruz</a>, we are analyzing ways to prevent this kind of cascading outage. One promising strategy is to install distributed generation sources, such as solar panels or small wind turbines with batteries, at critical interconnection points between energy, water and natural gas systems.</p>
<p>For their part, consumers also need to understand these connections. Taking a hot shower or running a dishwasher consumes water, along with electricity or gas to heat it. These crunch points often cause trouble during crises. For instance, recent advisories urging Texans to boil their water before using it put extra pressure on already-scarce energy supplies.</p>
<p>Our research shows that utilities need to pay more attention to connections between <a href="https://doi.org/10.1016/j.apenergy.2019.114419">natural gas and electricity</a>, and between <a href="https://doi.org/10.1016/j.apenergy.2019.113466">water and electricity</a>. By doing so, planners can see more accurately how climate conditions will affect demand, particularly <a href="https://doi.org/10.1007/s10584-020-02669-7">under climate change</a>. Rampant gas shortages and electricity and water outages in Texas are a sign that infrastructure operators need to understand more clearly how tightly related these resources are, not only during normal operation but also during crises that can disrupt all of them at once. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="People bundled in blankets sit on chairs in a furniture showroom." src="https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/387076/original/file-20210301-15-u2h27p.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">People with no power at their homes rest inside a Gallery Furniture store in Houston after the owner opened the business as a shelter on Feb. 16, 2021.</span>
<span class="attribution"><a class="source" href="https://newsroom.ap.org/detail/WinterWeatherTexasPowerFailures/7fb328d93ba34b48a68c84cfca9fb3a4/photo?Query=winter%20weather%20blackouts&mediaType=photo&sortBy=arrivaldatetime:desc&dateRange=Anytime&totalCount=222&currentItemNo=43">AP Photo/David J. Phillip</a></span>
</figcaption>
</figure>
<h2>The future will be different</h2>
<p>Some commentaries on the Texas disaster have called it a “<a href="https://www.investopedia.com/terms/b/blackswan.asp">black swan event</a>” that could never have been predicted – or even worse, <a href="https://www.forbes.com/sites/davidblackmon/2021/02/20/a-dangerous-narrative-emerges-in-the-wake-of-texas-power-blackouts/?sh=cc2f06e3ab21">a “meteor strike</a>.” In fact, the state published a <a href="http://tdem.wpengine.com/wp-content/uploads/2019/08/txHazMitPlan.pdf">hazard mitigation plan</a> in 2018 that clearly warned of the potential for severe winter weather to cause widespread outages. And it noted that such events would be far more disruptive in Texas than in other regions that experience harsher winters. </p>
<p>In a 2016 study, several colleagues and I warned that current grid reliability metrics and standards across the U.S. <a href="https://doi.org/10.1111/risa.12401">were inadequate</a>, especially with respect to climate risks. We concluded that those standards “fail to provide a sufficient incentive structure for the utilities to adequately ensure high levels of reliability for end‐users, particularly during large‐scale climate events.” </p>
<p>As I see it, a dominant paradigm of “faster, better, cheaper” in energy planning is placing increasing pressure on our nation’s aging infrastructure. I believe it is time for energy planners to be more proactive and make smart investments in measures that will help power systems handle extreme weather events.</p>
<p>Key steps should include leveraging <a href="http://dx.doi.org/10.1109/ACCESS.2018.2792680">predictive analytics</a> to inform disaster planning; accounting for <a href="https://doi.org/10.1038/s41598-020-72207-z">climate uncertainty</a> in infrastructure management; upgrading reliability standards for power transmission and distribution systems; and diversifying the mix of fuels that all states use to generate electricity. Without such steps, frequent disruptions of critical services could become the new norm, with <a href="https://theconversation.com/whats-behind-15-000-electricity-bills-in-texas-155822">high costs</a> and heavy impacts – especially on the <a href="https://www.nytimes.com/2021/02/16/climate/texas-blackout-storm-minorities.html">most vulnerable Americans</a>.</p>
<p>[<em>Deep knowledge, daily.</em> <a href="https://theconversation.com/us/newsletters/the-daily-3?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=deepknowledge">Sign up for The Conversation’s newsletter</a>.]</p><img src="https://counter.theconversation.com/content/155834/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Roshanak (Roshi) Nateghi receives funding from the National Science Foundation. </span></em></p>There will be more weather-driven disasters like February’s deep freeze in Texas, and energy planners aren’t prepared.Roshanak (Roshi) Nateghi, Associate Professor of Industrial Engineering, Purdue UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1424682020-07-15T12:11:54Z2020-07-15T12:11:54ZHow effective does a COVID-19 coronavirus vaccine need to be to stop the pandemic? A new study has answers<figure><img src="https://images.theconversation.com/files/347445/original/file-20200714-139992-fu6jl.jpg?ixlib=rb-1.1.0&rect=1751%2C0%2C4281%2C2481&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">The lower the vaccine's effectiveness, the more likely social distancing in some form may still be necessary.</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/photo/corona-virus-and-research-royalty-free-image/1213444268">Gopixa via Getty Images</a></span></figcaption></figure><p>The U.S. is pinning its hopes on a COVID-19 coronavirus vaccine, but will a vaccine alone be enough to stop the pandemic and allow life to return to normal?</p>
<p>The answer depends on a how “good” the vaccine ends up being.</p>
<p>In <a href="https://www.ajpmonline.org/article/S0749-3797(20)30284-1/fulltext">a study</a> published July 15 in the American Journal of Preventive Medicine, my colleagues and I used a computer simulation of every person in the country to show how effective a vaccine would have to be and how many people would have to get vaccinated to end the pandemic. We found that a coronavirus vaccine’s effectiveness may have to be higher than 70% or even 80% before Americans can safely stop relying social distancing. By comparison, the measles vaccine has an efficacy of 95%-98%, and the flu vaccine is 20%-60%.</p>
<p>That doesn’t mean a vaccine that offers less protection would be useless, but it would mean social distancing in some form may still be necessary.</p>
<h2>What is vaccine ‘effectiveness’ anyway?</h2>
<p>Some political leaders have suggested that society will return to normal soon, especially if a vaccine becomes available by the <a href="https://www.sciencenews.org/article/coronavirus-covid-19-vaccine-clinical-trials-speed-safety">end of the year or early in 2021</a>. Some <a href="https://www.statnews.com/2020/07/14/moderna-covid19-vaccine-first-data-show-spurs-immune-response/">vaccines are currently in early-stage trials</a>, but that timeline would still be very optimistic. </p>
<p>However, it is important to remember that a vaccine is like many other products: What matters is not just that the product is available but also how effective it is. Take clothing for example. If you are going to a formal dinner, underwear alone may partially cover you but probably not well enough for the occasion. This doesn’t mean underwear is useless.</p>
<p>Similarly, different vaccines may offer different levels of protection. Scientists talk about this as the <a href="https://www.cdc.gov/csels/dsepd/ss1978/lesson3/section6.html">vaccine’s efficacy</a> or effectiveness. If 100 people who haven’t been exposed to the virus are given a vaccine that has an efficacy of 80%, that means that on average 80 of them would not get infected. </p>
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<p>The difference between efficacy and effectiveness is that the former applies when vaccination is given under controlled circumstances, like a clinical trial, and the latter is under “real-world” conditions. Typically, a vaccine’s effectiveness tends to be lower than its efficacy.</p>
<h2>Computer simulations show what could happen</h2>
<p>Since COVID-19 coronavirus vaccines are still under development, now is the time to set vaccine efficacy levels to aim for, as well as to manage expectations. Running computer simulations is really the only way to ethically do this. </p>
<p>For the study, our PHICOR team at the <a href="https://sph.cuny.edu/">City University of New York</a> Graduate School of Public Health and Health Policy, working with scientists from the <a href="https://www.bcm.edu/education/national-school-of-tropical-medicine">National School of Tropical Medicine</a> at the Baylor College of Medicine, developed a computer simulation model of the entire United States and its population interacting with each other. Using that model, we were able to introduce the COVID-19 virus into this virtual population in different ways and have it spread from person to person in various pandemic scenarios. Each simulated person who gets infected has probabilities of being hospitalized, placed on a ventilator or dying based on the severity of the problems just as in the real world. </p>
<p>Experiments using this simulated population can represent the different vaccines and what is likely to happen if different proportions of the population are vaccinated at different times during the pandemic. The results show how vaccines with different levels of efficacy would affect the pandemic and can be used to estimate the impact on things such as number of people who get infected, health outcomes and costs. In this case, we assumed that only one vaccination would be required. </p>
<h2>What will it take to stop the pandemic?</h2>
<p>Typically, in an epidemic or pandemic, as more people are exposed to the virus, the number of new infections per day steadily increases until it reaches a peak and begins to drop. Of course, how long this takes depends upon how the virus and the response to it may evolve over time. </p>
<p>To stop the pandemic, the number of new infections per day needs to drop to zero, or at least to a very low number, as quickly as possible. </p>
<p>If the COVID-19 pandemic was just beginning and the population infected was close to 0%, the simulations show that vaccine efficacy would have to be at least 60% to stop the coronavirus if the entire population was vaccinated. Given the number of susceptible people who couldn’t be vaccinated because of age or health problems and the number who would refuse to be vaccinated, that’s probably impossible.</p>
<p><iframe id="CdU85" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/CdU85/4/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<p>If only 75% of the population gets vaccinated, the vaccine efficacy would have to be around 70%. If only 60% of people get vaccinated, the threshold goes even higher, to around 80%. It’s all about making sure the virus can’t find more people to infect. </p>
<p>Those numbers assume that a person infected with the virus <a href="https://www.cdc.gov/coronavirus/2019-ncov/hcp/planning-scenarios.html#box">infects 2.5 other people on average</a>. If the virus is more contagious, the vaccine has to be more efficient.</p>
<p>Now, the further along the pandemic is, the less the height of the peak can be reduced. It’s like climbing a mountain – you are already at a certain height. Plus, it is harder to shut a pandemic down when there are more infectious people running around. </p>
<p>So, when 5% of the population has already been infected with the virus, the best that you can do is reduce the peak by around 85%. The difference between 0% and 5% can add up to millions of infections. So far, <a href="https://www.cdc.gov/coronavirus/2019-ncov/cases-updates/cases-in-us.html">about 1%</a> of the U.S. population has been confirmed to have been infected, but officials estimate the actual percentage is much higher.</p>
<p><iframe id="wVx7n" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/wVx7n/4/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<p><iframe id="oSh3H" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/oSh3H/3/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<h2>How many people get vaccinated is crucial</h2>
<p>Based on these findings, a vaccine with an efficacy as low as 60% could still stop the pandemic and allow society to return to normal. However, most if not all of the population would have to be vaccinated. </p>
<p>This seems unlikely, given polls showing that <a href="https://www.reuters.com/article/us-health-coronavirus-vaccine-poll-exclu/exclusive-a-quarter-of-americans-are-hesitant-about-a-coronavirus-vaccine-reuters-ipsos-poll-idUSKBN22X19G">only about three-quarters</a> <a href="https://www.washingtonpost.com/health/7-in-10-americans-would-be-likely-to-get-a-coronavirus-vaccine-a-post-abc-poll-finds/2020/06/01/4d1f8f68-a429-11ea-bb20-ebf0921f3bbd_story.html">of Americans say</a> they would get a coronavirus vaccine if assured that it was safe. </p>
<p>With fewer people protected, a vaccine would have to have an efficacy of at least 80% to be able to stop the pandemic by itself, meaning social distancing could be completely relaxed. This can provide a target to aim for when developing COVID-19 coronavirus vaccines. </p>
<p>Again, all of this doesn’t mean that a vaccine with a lower efficacy would not be useful. It would mean that social distancing and mask-wearing likely would have to continue until the pandemic runs its course or a vaccine that is actually “good enough” arrives.</p><img src="https://counter.theconversation.com/content/142468/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Bruce Y. Lee received funding from the City University of New York’s (CUNY) Graduate School of Public Health and Health Policy, the National Institutes of General Medical Sciences (NIGMS), the Agency for Healthcare Research and Quality (AHRQ), the U.S. Agency for International Development (USAID), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development </span></em></p>A vaccine that’s 70% effective might not be good enough if too few people are willing to be vaccinated, new research shows.Bruce Y. Lee, Professor of Health Policy and Management, City University of New YorkLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1383992020-06-02T12:14:08Z2020-06-02T12:14:08ZCoronavirus deaths in San Francisco vs. New York: What causes such big differences in cities’ tolls?<figure><img src="https://images.theconversation.com/files/338900/original/file-20200601-95049-15lyhu.jpg?ixlib=rb-1.1.0&rect=6%2C64%2C2038%2C1293&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Nurses and other health care workers in New York mourned colleagues who have died during the outbreak of the novel coronavirus.</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/nurses-and-healthcare-workers-mourn-and-remember-their-news-photo/1209599224">Johannes Eisele/AFP/Getty Images</a></span></figcaption></figure><p>San Francisco and New York City both reported their first COVID-19 cases during the first week of March. On March 16, <a href="https://www.youtube.com/watch?v=_VwHUvVyO_M">San Francisco announced</a> it was ordering residents to stay home to avoid spreading the coronavirus, and <a href="https://coronavirus.health.ny.gov/new-york-state-pause">New York did the same</a> less than a week later. But by the end of May, while San Francisco had attributed <a href="https://data.sfgov.org/stories/s/San-Francisco-CxOVID-19-Data-and-Reports/fjki-2fab">43 deaths</a> to COVID-19, New York City’s death count was <a href="https://www1.nyc.gov/site/doh/covid/covid-19-data.page">over 20,000</a>.</p>
<p>What explains the stark difference in COVID-19-related deaths between these two cities? Is the delay in the stay-at-home order responsible? What about city-specific measures taken to mitigate COVID-19 before the order? Is something else going on? </p>
<p>The divergent trajectories of San Francisco and New York City, while especially striking, are not unique. <a href="https://www.nytimes.com/2020/05/03/world/asia/coronavirus-spread-where-why.html#click=https://t.co/HawqDHbUzw">Worldwide</a>, COVID-19 is having highly variable effects. <a href="https://coronavirus.jhu.edu/us-map">Within the U.S.</a>, infections, hospitalizations and deaths have skyrocketed in nearly all major cities in the Northeast while remaining fairly low in some other metropolitan centers, such as Houston, Phoenix and San Diego. </p>
<p>How cities and states <a href="https://github.com/COVID19StatePolicy/SocialDistancing">implemented</a> public health interventions, such as school closures and stay-at-home orders, has varied widely. Comparing these interventions, whether they worked and for whom, can provide insights about the disease and help improve future policy decisions. But accurate comparisons aren’t simple.</p>
<p>The range of COVID-19 interventions implemented across the U.S. and worldwide <a href="http://doi.org/10.1111/1471-0528.15199">was not random</a>, making them difficult to compare. Among other things, population density, household sizes, public transportation use and hospital capacity may have contributed to the differences in COVID-19 deaths in San Francisco and New York City. These sorts of differences complicate analyses of the effectiveness of responses to the COVID-19 pandemic. </p>
<p><iframe id="tDnGg" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/tDnGg/13/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<p>As <a href="https://theconversation.com/profiles/laura-b-balzer-1062379">a biostatistician</a> and <a href="https://theconversation.com/profiles/brian-w-whitcomb-1073405">an epidemiologist</a>, we use statistical methods to sort out causes and effects by controlling for the differences between communities. With COVID-19, we’ve often seen comparisons that don’t adjust for these differences. The following experiment shows why that can be a problem.</p>
<h2>City simulations reveal a paradox</h2>
<p>To illustrate the dangers of comparisons that fail to adjust for differences, we set up a simple <a href="https://github.com/LauraBalzer/Simulated_paradox">computer simulation</a> with only three hypothetical variables: city size, timing of stay-at-home orders and cumulative COVID-19 deaths by May 15. </p>
<p>For 300 simulated cities, we plotted COVID-19 deaths by the delay time, defined as the number of days between March 1 and the order being issued. Among cities of comparable size, delays in implementing stay-at-home orders are associated with more COVID-19 deaths – specifically, 40-63 more deaths are expected for each 10-day delay. The hypothetical policy recommendation from this analysis would be for immediate implementation of stay-at-home orders. </p>
<figure class="align-center ">
<img alt="" src="https://images.theconversation.com/files/339024/original/file-20200601-95032-dqjcsq.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/339024/original/file-20200601-95032-dqjcsq.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=671&fit=crop&dpr=1 600w, https://images.theconversation.com/files/339024/original/file-20200601-95032-dqjcsq.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=671&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/339024/original/file-20200601-95032-dqjcsq.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=671&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/339024/original/file-20200601-95032-dqjcsq.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=843&fit=crop&dpr=1 754w, https://images.theconversation.com/files/339024/original/file-20200601-95032-dqjcsq.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=843&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/339024/original/file-20200601-95032-dqjcsq.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=843&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption"></span>
<span class="attribution"><span class="source">Laura Balzer/Github</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>Now consider a plot of the same 300 simulated cities that doesn’t take city size into consideration. The relationship between delays and deaths is reversed: Earlier implementation in this simulation is strongly associated with more deaths, and later implementation with fewer deaths. This apparent <a href="https://en.wikipedia.org/wiki/Simpson%27s_paradox">paradox</a> occurs because of the causal relationships between city size, delays and COVID-19 deaths. Strong connections or associations between two variables don’t guarantee that one variable causes another. <a href="https://en.wikipedia.org/wiki/Correlation_does_not_imply_causation">Correlation does not imply causation</a>. </p>
<p>Failing to properly address these relationships can create misperceptions with dramatic implications for policymakers. In these simulations, the analysis that fails to consider city size would lead to an erroneous policy recommendation to delay or never implement stay-at-home orders. </p>
<figure class="align-center ">
<img alt="" src="https://images.theconversation.com/files/339023/original/file-20200601-95013-rpyp2y.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/339023/original/file-20200601-95013-rpyp2y.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=590&fit=crop&dpr=1 600w, https://images.theconversation.com/files/339023/original/file-20200601-95013-rpyp2y.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=590&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/339023/original/file-20200601-95013-rpyp2y.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=590&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/339023/original/file-20200601-95013-rpyp2y.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=742&fit=crop&dpr=1 754w, https://images.theconversation.com/files/339023/original/file-20200601-95013-rpyp2y.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=742&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/339023/original/file-20200601-95013-rpyp2y.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=742&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption"></span>
<span class="attribution"><span class="source">Laura Balzer/Github</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<h2>It gets more complicated</h2>
<p>Of course, causal inference in real life is more complicated than in a computer simulation with only three variables. </p>
<p>In addition to confounding factors like community size, substantial evidence suggests that public health interventions do not protect all people equally. </p>
<p>In San Francisco, stark disparities have emerged. For example, comprehensive testing of the Mission District revealed 95% of people testing positive were <a href="https://www.sfgate.com/news/editorspicks/article/90-of-people-who-tested-positive-for-COVID-19-in-15247476.php">Hispanic</a>. Factors like socioeconomic status, race and ethnicity, and many others, <a href="https://theconversation.com/is-your-neighborhood-raising-your-coronavirus-risk-redlining-decades-ago-set-communities-up-for-greater-danger-138256">vary widely among communities</a> and can impact COVID-19 infection and death rates. Differences among community residents makes appropriate interpretation of comparisons, such as between San Francisco and New York, even more difficult.</p>
<h2>So how do we effectively learn in the current environment?</h2>
<p>While especially pressing now, the analytic challenges posed by COVID-19 are not new. Public health experts have long used data from nonrandomized studies – even in the midst of epidemics. During the Cholera outbreak in London in 1849, <a href="https://www.ph.ucla.edu/epi/snow/snowcricketarticle.html">John Snow</a>, famed in epidemiologic circles, used available data, simple tools and careful consideration to identify a water pump as a source of disease spread. Evidence-based decisions require both data and appropriate methods to analyze data.</p>
<p>Cities and communities worldwide vary in important ways that can complicate public health research. The rigorous application of <a href="http://doi.org/10.1097/EDE.0000000000000078">causal inference methods</a> that can take into account differences between populations is necessary to guide policy and to avoid misinformed conclusions. </p>
<p>[<em>You need to understand the coronavirus pandemic, and we can help.</em> <a href="https://theconversation.com/us/newsletters?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=upper-coronavirus-help">Read The Conversation’s newsletter</a>.]</p><img src="https://counter.theconversation.com/content/138399/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.</span></em></p>Why one city suffers significantly more deaths than another isn’t always obvious. A simple experiment shows how failing to consider certain factors can point policy makers in the wrong direction.Laura B. Balzer, Assistant Professor of Biostatistics & Director of the UMass Causality Lab, UMass AmherstBrian W. Whitcomb, Associate Professor of Epidemiology, UMass AmherstLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1357972020-04-15T12:12:56Z2020-04-15T12:12:56ZLack of data makes predicting COVID-19’s spread difficult but models are still vital<figure><img src="https://images.theconversation.com/files/327778/original/file-20200414-117573-16iea84.jpg?ixlib=rb-1.1.0&rect=78%2C1224%2C5659%2C2606&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Public health authorities rely on models to make decisions but how accurate are they?</span> <span class="attribution"><a class="source" href="https://www.gettyimages.com/detail/news-photo/white-house-coronavirus-response-coordinator-deborah-birx-news-photo/1209192140?adppopup=true">Sarah Silbiger/Getty Images</a></span></figcaption></figure><p><em>Editor’s note: The question everyone in the world wants answered is how far the new coronavirus will spread and when the pandemic will begin to ebb. To know that, epidemiologists, public health authorities and policymakers rely on models.</em></p>
<p><em>Models are not meant to predict the future perfectly – yet they’re still useful. Biomedical mathematician <a href="https://www.researchgate.net/profile/Lester_Caudill">Lester Caudill</a>, who is currently teaching a class focused on COVID-19 and modeling, explains the limitations of models and how to better understand them.</em></p>
<h2>What are infectious disease models?</h2>
<p>Mathematical models of how infections spread are simplified versions of reality. They are designed to mimic the main features of real-world disease spread well enough to make predictions which can, at least partly, be trusted enough to make decisions. The COVID-19 model predictions reported in the media come from mathematical models that have been converted into computer simulations. For example, a model might use a variety of real world data to predict a date (or range of dates) for a city’s peak number of cases.</p>
<h2>Why is modeling the spread of COVID-19 challenging?</h2>
<p>In order for a model’s predictions to be trustworthy, the model must accurately reflect how the infection progresses in real life. To do this, modelers typically use data from prior outbreaks of the same infection, both to create their model, and to make sure its predictions match what people already know to be true.</p>
<p>This works well for infections like influenza, because scientists have decades of data that help them understand how flu outbreaks progress through different types of communities. Influenza models are used each year to make decisions regarding vaccine formulations and other flu-season preparations. </p>
<p>By contrast, modeling the current COVID-19 outbreak is much more challenging, simply because researchers know very little about the disease. What are all the different ways it can be transferred between people? How long does it live on door knobs or Amazon boxes? How much time passes from the moment the virus enters a person’s body until that person is able to transmit it to someone else? These, and many other questions, are important to incorporate into a reliable model of COVID-19 infections. Yet people simply do not know the answers yet, because the world is in the midst of the first appearance of this disease, ever.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/327775/original/file-20200414-117567-1bkxl64.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Disease models are built on assumptions and historical data collected from other diseases. Having relatively little epidemiological data on COVID-19 adds uncertainty to models of how it will spread.</span>
<span class="attribution"><a class="source" href="http://www.apimages.com/metadata/Index/Virus-Outbreak-Predicting-the-Outcome/96a4f368626f4779ad1f3f2f4c6442cd/2/0">AP Photo/Jon Elswick</a></span>
</figcaption>
</figure>
<h2>Why do different models have different predictions?</h2>
<p>The best modelers can do is assume some things about COVID-19, and create models that are based on these assumptions. Some current COVID-19 models assume that the virus behaves like influenza, so they use influenza data in their models. Other COVID-19 models assume that the virus behaves like SARS-CoV, the virus that caused the SARS epidemic in 2003.</p>
<p>Other models may make other assumptions about COVID-19, but they must all assume something, in order to make up for information that they need, but that simply does not yet exist. These different assumptions are likely to lead to very different COVID-19 model predictions.</p>
<h2>How can people make sense of the different – sometimes conflicting – model predictions?</h2>
<p>This question gets at, perhaps, the most important thing to know about mathematical model predictions: They are only useful if you understand the assumptions that the model is based on.</p>
<p>Ideally, model predictions like, “We expect 80,000 COVID-related deaths in the U.S.” would read more like, “Assuming that COVID-19 behaves similar to SARS, we expect 80,000 COVID-related deaths in the U.S.” This helps place the model’s prediction into context, and helps remind everyone that model predictions are not, necessarily, glimpses into an inevitable future. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=251&fit=crop&dpr=1 600w, https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=251&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=251&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=315&fit=crop&dpr=1 754w, https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=315&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/327748/original/file-20200414-117573-15hs7n9.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=315&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">An oft-cited model from Institute for Health Metrics and Evaluation at the University of Washington has a wide range of projections for deaths from COVID-19. They vary based on different underlying assumptions and how they change, such as the effect of social distancing or widespread testing.</span>
<span class="attribution"><a class="source" href="https://covid19.healthdata.org/projections">Institute for Health Metrics and Evaluation at the University of Washington</a></span>
</figcaption>
</figure>
<p>It may also be useful to use predictions from different models to establish reasonable ranges, rather than exact numbers. For instance, a model that assumes COVID-19 behaves like influenza might predict 50,000 deaths in the U.S. Rather than trying to decide which prediction to believe – which is an impossible task – it may be more useful to conclude that there will be between 50,000 and 80,000 deaths in the U.S.</p>
<h2>Why do the same models seem to predict different outcomes today than they did yesterday?</h2>
<p>As COVID-19 data becomes available – and there are many good people working tirelessly to gather data and make it available – modelers are incorporating it so that, each day, their models are based a little more on actual COVID-19 information, and a little less on assumptions about the disease. You can see this process unfold in the news, where the major predictive COVID-19 models provide almost daily revisions to their prior estimates of case numbers and deaths.</p>
<h2>Can a model that’s (probably) not accurate at predicting the future still be useful?</h2>
<p>While models of infections can provide insights into what the future might hold, they are far more valuable when they help answer, “How can policies alter that future?” </p>
<p>For instance, a baseline model for predicting the future number of COVID-19 cases might be adapted to incorporate the effects of, say, a stay-at-home order. By running model simulations with the order, and comparing to model simulations without the order, public health authorities may learn something about how effective the order is expected to be. That can be especially useful when comparing the associated costs, not only in terms of disease burden, but in economic terms, as well.</p>
<p>One step further, this same model could be used to predict the consequences of ending the order on, say, June 10 – the current target date for the stay-at-home order in Virginia – and compare them to model predictions for ending the order on, say, May 31 or June 30. Here, as in many other settings, models prove to be most useful when they’re used to generate different scenarios which are compared to each other. This is different than comparing model predictions to reality.</p>
<p>[<em>Get our best science, health and technology stories.</em> <a href="https://theconversation.com/us/newsletters/science-editors-picks-71/??utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=science-best">Sign up for The Conversation’s science newsletter</a>.]</p><img src="https://counter.theconversation.com/content/135797/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Lester Caudill does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>Why is there such a wide difference in projections for how much COVID-19 will spread? An expert in disease modeling explains what models can and cannot do.Lester Caudill, Professor of Mathematics, University of RichmondLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1247472019-10-08T23:09:58Z2019-10-08T23:09:58ZFast evolution explains the tiny stature of extinct ‘Hobbit’ from Flores Island<figure><img src="https://images.theconversation.com/files/296079/original/file-20191008-128665-1ubc795.jpg?ixlib=rb-1.1.0&rect=245%2C131%2C4685%2C3506&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">An Indonesian island was home to _H. Floresiensis_ – but how did the dwarfed human species evolve?</span> <span class="attribution"><a class="source" href="https://www.shutterstock.com/image-photo/koka-beach-one-beaches-sikka-regency-1243898557">areza taqwim/Shutterstock.com</a></span></figcaption></figure><p>It’s not every day that scientists discover a new human species. </p>
<p>But that’s just what happened back in 2004, when archaeologists uncovered some very well-preserved fossil remains in the Liang Bua cave on Flores Island, Indonesia. The diminutive size of this new human species, <a href="https://www.nature.com/news/the-discovery-of-homo-floresiensis-tales-of-the-hobbit-1.16197"><em>Homo floresiensis</em></a>, earned it the nickname “Hobbit.” </p>
<p>Shockingly, researchers believed it had survived until the end of the last Ice Age, some 18,000 years ago. That was much later than Neanderthals lived, later than any human species other than our own.</p>
<p>Almost immediately, interpretations of this Hobbit skeleton met with fierce criticism from both anthropologists and evolutionary biologists. The poor Hobbit was accused of being an example not of a small new human species, but an abnormal <em>Homo sapiens</em>, bearing any of a variety <a href="https://doi.org/10.1002/ajpa.20655">of growth and</a> <a href="https://doi.org/10.1098/rspb.2007.1488">hormonal conditions</a>. The Hobbit, many scientists decided, had no place among the giants of the human evolutionary record.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/295885/original/file-20191007-52202-lzkp34.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">An artist’s interpretation of how <em>H. floresiensis</em> looked in life.</span>
<span class="attribution"><a class="source" href="https://www.flickr.com/photos/timevanson/7283199410">Tim Evanson/Flickr</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<p>Yet she – yes, the Hobbit was later found to be a female – had her revenge. This tiny, small-brained creature stood just a bit more than three feet tall and had a brain as big as a chimp. But her place in the human ancestral line was cemented when researchers uncovered another tiny individual in Flores. This second, much older discovery debunked the idea that the Hobbit was a unique, abnormal <em>Homo sapiens</em>.</p>
<p>After 15 years of <a href="https://theconversation.com/the-hobbit-took-our-breath-away-now-its-the-new-normal-60784">intense research</a>, anthropologists now confidently date the Liang Bua individual to have lived between 60,000 and 90,000 years ago. Her much older cousins in Flores lived 700,000 years ago. This long reign testifies to the success of this tiny human species, no matter how small-statured and small-brained they were. </p>
<p>And this year anthropologists found a new dwarfed human species, christened <a href="https://doi.org/10.1038/s41586-019-1067-9"><em>Homo luzonensis</em></a>, in the Philippines.</p>
<p>So why did tiny humans wind up living on these islands? For us biogeographers and <a href="https://scholar.google.com/citations?user=gE-4C2cAAAAJ&hl=en&oi=ao">evolutionary</a> <a href="https://scholar.google.com/citations?user=scYHGuQAAAAJ&hl=en&oi=ao">biologists</a>, the answer was right in front of us: <a href="https://www.pbs.org/wgbh/nova/article/gigantism-and-dwarfism-islands/">the island rule</a>.</p>
<h2>Island life and body size</h2>
<p>Zoologist J. Bristol Foster <a href="https://doi.org/10.1038/202234a0">originally proposed</a> the island rule in 1964. </p>
<p>He’d noted that when a large-bodied species settles onto an island, it will tend to evolve to shrink in size – all the way to the point of leaving dwarf descendants. At the same time, the opposite will happen. Small-bodied species will evolve to be larger, producing gigantic daughter species.</p>
<p>There are spectacular cases of this island rule in action across the world. Think of pygmy elephants and mammoths from <a href="https://doi.org/10.1023/A:1025577414005">Mediterranean</a> and Baja California islands, hippos that would barely outweigh a donkey in Cyprus, deer as tall as a pet dog in Crete, rats as big as a cow in the Caribbean and insects as long as a human hand in New Zealand.</p>
<p>Biologists have proposed various mechanisms that could be responsible for this evolutionary trend. A good motive might be the absence of natural predators on islands. A number of species, most notably elephants and hippos, fend predators off by virtue of their size, an expensive strategy when no killer is lurking in the dark. Also, on islands the scarce resource supply might favor smaller body size because smaller individuals can live with less.</p>
<p>Or it could be that smaller individuals with no predators just produce more offspring, which implies females start delivering earlier and at smaller size, investing less in growth and more in reproduction. This possibility is a likely explanation for <a href="https://doi.org/10.1073/pnas.0708024105">how contemporary human pygmies evolved</a>. </p>
<p>All of these options will eventually lead to changes in the genetic architecture that underlies body-size variation.</p>
<p>So, we asked, could the island rule be an explanation for small size of <em>Homo floresiensis</em> and <em>Homo luzonensis</em>? We thought probably yes.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=420&fit=crop&dpr=1 600w, https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=420&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=420&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=528&fit=crop&dpr=1 754w, https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=528&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/296081/original/file-20191008-128681-801yeu.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=528&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Excavations in 2009 at Liang Bua cave, where <em>Homo floresiensis</em> was found.</span>
<span class="attribution"><a class="source" href="http://www.apimages.com/metadata/Index/Indonesia-Hobbit/2a6835d986064cf095696d86e3e700e6/1/0">AP Photo/Achmad Ibrahim</a></span>
</figcaption>
</figure>
<h2>Modeling generations on the island</h2>
<p>The Hobbit’s most likely ancestor is <em>Homo erectus</em>, a species more than twice its size in terms of its brain and overall bulk. Based on the geological history of Flores and the oldest known fossils of <em>Homo floresiensis</em>, it seems the evolution of the new species must have occurred in less than about 300,000 years.</p>
<p>As evolutionary biologists, we are acquainted with the idea that Darwinian evolution is a slow and gradual process that takes place over very long timescales. Could such drastic change in body size happen this fast?</p>
<p>So our interdisciplinary research team developed a <a href="https://theconversation.com/simulating-evolution-how-close-do-computer-models-come-to-reality-57538">computer model</a> to try to answer this basic question. It’s like a computer game that simulates body size evolution under biologically and ecologically realistic scenarios.</p>
<p>In our model, individuals colonize the island, grow to their adult body size according to how much food is available, give birth to a number of young and die. The basic rule of the game is that individuals that are closer to the “optimum” body size for the island in that moment will leave more descendants. Offspring inherit genes for large or small body size.</p>
<p>Generation after generation, new mutations may appear in the population and shift body size toward either higher or lower values. Occasionally, new individuals might even invade the island and mix with the residents. Another basic rule is that the initial small population cannot grow above the number the island’s resources might sustain.</p>
<p>Our colleagues, Earth systems scientists <a href="https://scholar.google.com/citations?user=kSDahsoAAAAJ&hl=en&oi=ao">Neil Edwards</a> and <a href="https://scholar.google.com/citations?user=1gais1MAAAAJ&hl=en">Phil Holden</a>, used paleoclimatic data to tweak our model. Hotter and wetter times can support more people on the island, and would influence optimum body size at any given moment.</p>
<p>We started our simulations assuming that large-bodied <em>Homo erectus</em> arrived at the island and then evolved into a smaller species there. Since we just don’t know the exact numbers our model should crank through, we based them on estimates obtained from current human populations.</p>
<p>Because of this uncertainty, we ran our model thousands of times, each time using a random combination of all the parameters. Ultimately we were able to build a statistical distribution of how long it took for <em>Homo erectus</em> to become as small as <em>Homo floresiensis</em>.</p>
<p><iframe id="bx726" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/bx726/3/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<h2>A new species, in the blink of an evolutionary eye</h2>
<p>After running 10,000 simulations, we were surprised to discover that <a href="http://dx.doi.org/10.1098/rsbl.2019.0481">in less than 350 generations, the process was complete</a>. Thinking in terms of years, assuming a young female delivers a first baby at the average age of 15, that translates to about 10,000 years.</p>
<p>That may seem long for you and me. But from an evolutionary perspective, that’s the blink of an eye – a little more than a thousandth of <em>Homo</em> evolutionary history.</p>
<p>Of course we do not expect that all the features that make <em>Homo floresiensis</em> as unique as it is evolved that fast and at the same time. Yet, our simulation still shows, 300,000 years is far more than enough time for a new human species to arise.</p>
<p>Our work supports the idea that fast evolution is quite plausible under a realistic set of ecological parameters, and that natural selection may be a powerful force influencing body size on islands. And if <em>Homo floresiensis</em> is indeed a product of the island rule, she shows – yet again – that we humans tend to obey the same overall rules driving evolution in many other mammals.</p>
<p>[ <em>You’re smart and curious about the world. So are The Conversation’s authors and editors.</em> <a href="https://theconversation.com/us/newsletters?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=youresmart">You can read us daily by subscribing to our newsletter</a>. ]</p><img src="https://counter.theconversation.com/content/124747/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>José Alexandre Felizola Diniz-Filho receives funding from CNPq and CAPES. </span></em></p><p class="fine-print"><em><span>Pasquale Raia does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>New research models how the Homo floresiensis species could have evolved its small size remarkably quickly while living on an isolated island.José Alexandre Felizola Diniz-Filho, Professor of Ecology and Evolution, Universidade Federal de Goias (UFG)Pasquale Raia, Associate Professor of Paleontology and Paleoecology, University of Naples Federico IILicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1213582019-08-23T12:26:24Z2019-08-23T12:26:24ZBargain-hunting robocars could spell the end for downtown parking – cities need to plan ahead now<figure><img src="https://images.theconversation.com/files/288962/original/file-20190821-170941-22yp12.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">What does a future full of AVs mean for all the spaces reserved for downtown parking?</span> <span class="attribution"><a class="source" href="https://unsplash.com/photos/WxZ5RWm-AEg">Kris Cros/Unsplash</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span></figcaption></figure><p>Imagine a scene from the near-future: You get dropped off downtown by a driverless car. You slam the door and head into your office or appointment. But then where does the autonomous vehicle go? </p>
<p>It’s a question that cities would be wise to consider now. Self-driving cars may be on the roads within the next decade or two. </p>
<p>Automakers and specialized startups alike are aggressively <a href="https://www.audi-mediacenter.com/en/on-autopilot-into-the-future-the-audi-vision-of-autonomous-driving-9305/the-new-audi-a8-conditional-automated-at-level-3-9307">developing</a> automated vehicles (AVs), while government agencies <a href="https://www.transportation.gov/av/3">explore ways to reduce regulatory barriers</a>. Ride-hailing companies such as <a href="https://techcrunch.com/2019/05/07/waymo-and-lyft-partner-to-scale-self-driving-robotaxi-service-in-phoenix/">Lyft</a> and <a href="https://www.theverge.com/2019/6/12/18662626/uber-volvo-self-driving-car-safety-autonomous-factory-level">Uber</a> plan to operate some AVs, but others could become private robotaxis that drop owners off wherever they like and pick them up later.</p>
<p>Without policies to encourage sharing, it’s possible there could be many private AVs on the road. <a href="https://scholar.google.com/citations?user=79Ml-9YAAAAJ&hl=en&oi=sra">We are civil</a> <a href="https://scholar.google.com/citations?user=yReyGAwAAAAJ&hl=en">and environmental engineers</a> who collaborated with <a href="https://scholar.google.com/citations?user=0LqbCKAAAAAJ&hl=en">Chris Hendrickson</a>, director of Carnegie Mellon’s <a href="https://traffic21.heinz.cmu.edu/">Traffic21 Institute</a>, to <a href="https://engrxiv.org/9hqs7">examine the potential effects</a> of private AVs on cities.</p>
<p>Using Seattle as a case study, our analysis suggests that one of the biggest effects of AV technology may be on parking, as AVs leave expensive downtown spots behind in favor of cheaper parking outside the city center.</p>
<h2>Parking has a big footprint – and brings big bucks</h2>
<p>Parking takes up a lot of land in cities. </p>
<p>Researchers at UCLA estimated that about <a href="https://doi.org/10.1177/0739456X9701700102">5% to 8% of urban land</a> is devoted to curb parking. They estimated that the <a href="https://doi.org/10.1061/(ASCE)0733-9488(2005)131:4(233)">parking coverage</a> – the ratio of parking area to total land area - in downtown Los Angeles and Houston are about 81% and 57%, respectively.</p>
<p><a href="https://www.mba.org/2018-press-releases/july/riha-releases-new-report-quantified-parking-comprehensive-parking-inventories-for-five-major-us-cities">A 2018 parking study</a> done by the Mortgage Bankers Association found that Seattle’s parking density of 29 parking stalls per acre of land is twice its population density of 13 people per acre.</p>
<p>Because driverless cars could park outside urban cores to avoid the higher parking charges downtown, they might considerably affect urban land use.</p>
<p>And there are potentially big fiscal consequences. Many cities gather a substantial amount of money from parking-related activities, with the 25 largest cities, collectively, generating <a href="https://www.governing.com/gov-data/gov-how-autonomous-vehicles-could-effect-city-budgets.html">US$1.5 billion</a> in total revenue from parking fees and taxes in 2016. </p>
<p>In Seattle, for instance, annual revenues from parking meters total about <a href="http://www.seattle.gov/financedepartment/documents/2017-09-28RevenueupdateforCouncil.pdf">$37 million</a>. In addition, Seattle also collects <a href="http://www.seattle.gov/financedepartment/documents/2017-09-28RevenueupdateforCouncil.pdf">$39 million</a> and <a href="https://www.governing.com/gov-data/gov-how-autonomous-vehicles-could-effect-city-budgets.html">$21 million</a> in annual revenues from commercial parking lot taxes and parking fines, respectively. </p>
<p>Lower demand for parking could mean <a href="http://www.seattle.gov/financedepartment/documents/2019adoptedand2020endorsed-budgetbook-final.pdf">these funds</a> – traditionally used for city operations including education, cultural resources and libraries – will need to be replaced through other sources of revenue.</p>
<h2>Simulating a city with driverless cars</h2>
<p>To gauge the potential effects of private AVs on parking, we used Seattle as a case study because data on all its off-street parking lots is available. We looked at factors including energy use, emissions, parking revenue and vehicle miles traveled (VMT), a key statistic used by traffic engineers to measure travel demand.</p>
<p>Our team obtained data from the <a href="https://www.psrc.org/parking-inventory">Puget Sound Region Council</a> on the daily occupancy and parking prices of all paid off-street parking garages and lots in downtown Seattle. We went on to identify areas outside of the downtown area with many unrestricted parking spaces, where vehicles can currently park free of charge during the day.</p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=577&fit=crop&dpr=1 600w, https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=577&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=577&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=725&fit=crop&dpr=1 754w, https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=725&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/287929/original/file-20190813-9389-1e9bcnj.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=725&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">The model assumed AVs would rather travel long distances for free parking (green) than park in a paid parking lot (red), since this minimizes cost to the user.</span>
<span class="attribution"><a class="source" href="http://dx.doi.org/10.1061/(ASCE)UP.1943-5444.0000488">Harper et al (2018)</a>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>Then we modeled privately owned AVs searching for cheaper parking, where each vehicle makes parking decisions based on availability and total cost, including both parking fees and all operational costs of the round trip to the parking space. Each AV’s objective is to minimize cost. An AV would not become frustrated sitting in congestion or cruising to find an open curb space, whereas a human driver would.</p>
<p>We varied the operating costs of AVs per mile across a range of values, to understand how future changes either in improved technology or imposed per mile taxes might affect the results. </p>
<h2>More miles traveled, fewer parking garages?</h2>
<p>We considered a range of possible adoption rates for private AVs, from a point when few high-income early adopters have AVs to total market penetration.</p>
<p><iframe id="AIAx6" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/AIAx6/1/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<p>At low penetration rates – where anywhere from 5 to 50 percent of all cars traditionally parked downtown become automated – AVs are usually able to obtain their choice of parking space. In most cases, these are in free parking zones closest to where they drop passengers off downtown.</p>
<p>As more AVs come online, these free parking spaces closest to the downtown area fill up and cars must travel longer distances to obtain cheap parking. As market penetration rates rise, each vehicle would travel additional round trip miles in its quest for inexpensive parking.</p>
<p>With lower numbers of AVs on the road, this would have negligible impacts on the overall total miles traveled by cars in the Seattle region. But if all private cars parking downtown were AVs, the total daily miles traveled by cars in Seattle would increase by about 2.5%, with each AV traveling an additional 8.5 miles each day on average. That change, even if it sounds small, could cause congestion along heavily traveled routes depending on the time day and the mix of human-driven vehicles on the road.</p>
<p>Our simulation shows that there is enough free parking just outside downtown Seattle that AVs would no longer choose to park in downtown lots. At current prices it’s more economical to travel for free parking than to park in a paid lot. </p>
<p>Some private AV owners may rent out their car during the day as a ride-hailing service, but for others it might make financial sense to send their car home during the day and have it pick them up later. That would further increase overall vehicle miles traveled.</p>
<p><img width="100%" src="https://media.giphy.com/media/LrExHi8d0ApbT9fiB6/giphy.gif"></p>
<h2>No more parking downtown?</h2>
<p>As AVs leave downtown, parking lot revenues could decline to the point where owning a parking lot or garage would no longer be economically viable. This presents both challenges and opportunities for cities. Cities could lose a substantial amount of annual parking revenue in a future with more AVs.</p>
<p>We see a few ways that cities could strategically adapt parking requirements to prepare for additional travel by self-driving cars.</p>
<p>For example, cities could implement congestion pricing: a fee or tax paid by users to enter the urban core of the city. They could encourage more public and active transportation, like biking and walking. They could also change the rules for parking in areas where it’s now unrestricted and free, or try a combination of these options.</p>
<p>Cities could experiment with what’s called a scaled VMT tax: a fee for an AV to enter a downtown zone based on the number of miles it’s already traveled that day. This option might discourage an increase in housing sprawl with AVs and reduce the number of people using AVs to get downtown. In addition, encouraging AVs to be powered by electricity rather than gasoline would reduce the environmental impact of any additional travel.</p>
<p>Much of the land devoted to parking lots in today’s cities could be converted to parks, housing or commercial spaces, and reducing curb parking could allow for wider bike lanes or sidewalks. To take advantage of changing parking demand, cities could build adaptable parking garages that can be <a href="https://www.citylab.com/design/2013/11/its-time-design-parking-garages-car-less-future/7583/">converted to other uses</a> if they’re no longer needed. Garages with flat floors and exterior ramps, rather than interior ramps, can more easily be converted to commercial uses or housing.</p>
<p>Cities would need to look for other sources of revenues to supplement the money lost from parking taxes, revenues and tickets. Some of these resources may be recovered through VMT and congestion fees, or by replacing underutilized parking structures with new denser uses. </p>
<p>While robotaxis are not here yet, preparing now for changes in downtown parking and infrastructure could help cities respond when privately owned AVs start to hit the streets.</p>
<p>[ <em>Deep knowledge, daily.</em> <a href="https://theconversation.com/us/newsletters?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=deepknowledge">Sign up for The Conversation’s newsletter</a>. ]</p><img src="https://counter.theconversation.com/content/121358/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Corey Harper is a Presidential Postdoctoral Fellow at Carnegie Mellon University and is supported by funding from the University's Provost's office and the Department of Civil and Environmental Engineering. Corey has received funding from the United States Department of Transportation and the National Academies of Science, Engineering, and Medicine.</span></em></p><p class="fine-print"><em><span>Constantine Samaras receives research funding from the National Science Foundation, the U.S. Department of Energy, the U.S. Department of Transportation, and Argonne National Laboratory. He is also an Adjunct Senior Researcher with the non-profit, non-partisan RAND Corporation. The opinions expressed here do not necessarily represent those of any organization.</span></em></p>Self-driving cars may someday drop off their owners downtown and then leave to find free parking. What would that mean for cities of the future?Corey Harper, Postdoctoral Research Associate in Civil and Environmental Engineering, Carnegie Mellon UniversityConstantine Samaras, Associate Professor of Civil and Environmental Engineering, Carnegie Mellon UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1207132019-08-22T12:36:20Z2019-08-22T12:36:20ZHow to have an all-renewable electric grid<figure><img src="https://images.theconversation.com/files/288821/original/file-20190820-170918-byvgq7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">An all-renewable grid will mean more electricity and more transmission lines.</span> <span class="attribution"><a class="source" href="https://www.flickr.com/photos/russloar/5465756669/in/photolist-9jZr2X-rayW2s-7Lmmva-9BmmE-88BUgW-5BTA2H-9jZket-d3pPFh-9wT8yW-4XpiM5-asvKSC-7TqXLx-9F3EdH-9F3E7g-qnNgoo-8QVfKg-9F6zq1-ckWJKJ-efxxtW-efxuuQ-dZy8v4-efrKT2-efxueN-qGXzbG-2fqPxsM-rDXhfi-oL7Sqo-2dQFtBS-3jiKb4-rnoMWE-fAdqiF-gu2RGv-9F3E9c-pkRxxf-5sbANR-6tKAVf-YWbpgZ-rmywWW-6tFs7H-rmxBF5-bXTNnm-8QVfhK-efrM4X-efxvbs-A3DKB4-efrLe2-efxuKy-efrLFp-asi1MA-9EHwbd">Russ Allison Loar/flickr</a>, <a class="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">CC BY-NC-ND</a></span></figcaption></figure><p>The main solution to <a href="https://www.ipcc.ch/sr15/">climate change</a> is well known – stop burning fossil fuels. How to do this is more complicated, but as a scholar who does energy modeling, I and others see the outlines of a post-fossil-fuel future: We <a href="https://www.vox.com/2016/9/19/12938086/electrify-everything">make electricity with renewable sources and electrify almost everything</a>.</p>
<p>That means running vehicles and trains on electricity, heating buildings with electric <a href="https://www.energy.gov/energysaver/heat-and-cool/heat-pump-systems">heat pumps</a>, electrifying <a href="https://www.sciencedirect.com/science/article/abs/pii/S0360544216310295">industrial applications</a> such as steel production and using renewable electricity to make <a href="https://www.irena.org/-/media/Files/IRENA/Agency/Publication/2018/Sep/IRENA_Hydrogen_from_renewable_power_2018.pdf">hydrogen</a> (similar to natural gas) for other requirements. So the focus is on powering the electric grid with renewable sources. </p>
<p>There is debate, though, about whether fully renewable electricity systems are <a href="https://www.sciencedirect.com/science/article/pii/S1364032118303897">feasible</a> and <a href="https://theconversation.com/energy-wonks-have-a-meltdown-over-the-us-going-100-percent-renewable-why-79834">how quickly</a> the transition can be made. Here I argue that feasibility is clear, so only the transition question is relevant.</p>
<h2>Known technologies</h2>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=450&fit=crop&dpr=1 600w, https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=450&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=450&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=565&fit=crop&dpr=1 754w, https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=565&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/288415/original/file-20190817-192219-whjdwg.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=565&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A wind farm in Texas, which got about 15% of its electricity from wind in 2017.</span>
<span class="attribution"><a class="source" href="https://www.flickr.com/photos/daxis/34747221193/in/photolist-81dHwJ-UWuAhz-f1qfX3-31V78q-nBdg3W-V5JKbR-VYYxAA-8ryqGa-7fZ4Ci-VT1q9V-4VwfAj-88p6fa-9VQz4t-ckV5yu-24Bo8mz-7ytxLh-nAYv9w-dshNQX-UYjp7B-a88FEB-8aswuY-cYdUX-6fCjqF-92JMUR-91C5Hz-URxC5s-arxhZk-smfxkm-nTED7a-6bPPJi-2dduhan-TT9MRp-dh31UX-cYdUZ-oHoFMJ-5s4Dj2-64x9Ue-66j9JG-8ZxQWs-qqvgYD-dD7or7-c192Mb-MeE5hL-enkWDp-XzBhuu-5paeoT-dnHhMz-4y4EBQ-25ut64V-dvnLf">Draxis/flickr</a>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>My research focuses on the <a href="https://scholar.google.com/scholar?hl=en&as_sdt=0%2C22&q=timmons+david+renewable+energy&btnG=">economics of renewable energy</a>. To demonstrate feasibility and estimate cost of renewable electricity systems, researchers use computer models that calculate potential production from different technologies at each point in time, based on changing weather conditions. A model reveals which combination of electricity sources and energy storage systems has the lowest cost while always meeting demand. </p>
<p><a href="https://www.sciencedirect.com/science/article/abs/pii/S0360544219304967">Many studies</a> demonstrate that fully renewable electric grids are feasible in the <a href="https://www.pnas.org/content/112/49/15060.short">United States</a>, <a href="https://www.sciencedirect.com/science/article/pii/S1876610218310221">Europe</a>, <a href="https://www.sciencedirect.com/science/article/pii/S0301421513002164">Australia</a> and elsewhere. My colleagues and I recently completed a small-scale study on the island-nation of <a href="https://doi.org/10.1016/j.enpol.2019.110895">Mauritius</a>. <a href="https://theconversation.com/jamaica-leads-in-richard-branson-backed-plan-for-a-caribbean-climate-revolution-105478">Islands are attractive</a> places for initial renewable transitions because of their small scale, relative simplicity and dependence on imported fuels.</p>
<p>There are a number of <a href="http://www.ase.tufts.edu/gdae/education_materials/modules/RenewableEnergyEcon.pdf">ways to make renewable electricity</a>: hydro, wind, solar photovoltaics, geothermal and burning various forms of biomass (plant matter), besides <a href="https://www.sciencedirect.com/science/article/pii/S0301421516300702">improving efficiency</a> to use less energy. These are mature technologies with known costs. </p>
<p>Other possibilities include <a href="https://learning.media.mit.edu/seed/wave%20energy.html">wave, tidal</a> and <a href="https://www.seia.org/initiatives/concentrating-solar-power">concentrating solar power</a>, where reflectors focus solar rays to produce power. While these may be used in the future, the need to address climate change is urgent, and in my estimation, the mature technologies suffice. </p>
<p>Opinions on <a href="https://www.bostonglobe.com/opinion/2019/07/29/the-false-promise-nuclear-power/kS8rzs8f7MAONgXL1fWOGK/story.html">nuclear energy</a> run strong, which is another conversation. But models show that the United States does not need nuclear energy to retire fossil fuels. </p>
<h2>The grid of the future</h2>
<p>Renewable energy systems are location-specific: The best system depends on a location’s resources (is it windy?), its temporal pattern (how often is it not windy?) and availability of complementary sources (is there hydropower for backup?). Despite this location sensitivity, studies in disparate places are finding similar results. </p>
<p>Having a diversity of renewable sources can reduce costs. In particular, solar and wind are <a href="https://www.sciencedirect.com/science/article/pii/S0306261916300575">complementary</a> if the sunny season is not the windy season; models find that a combination of both is typically less expensive than either alone. </p>
<p>For most technologies, <a href="https://www.lazard.com/perspective/levelized-cost-of-energy-and-levelized-cost-of-storage-2018/">larger scale reduces cost</a>. For example, in the United States, large-scale solar farms can be more than 1,000 times larger than residential rooftop systems and about half the cost. To minimize cost, we build large systems.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/288822/original/file-20190820-170935-1b0ai5w.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Building large-scale renewable energy projects, such as this 550-megawatt solar plant in the Mojave Desert in California, leads to lower costs for energy produced.</span>
<span class="attribution"><a class="source" href="https://www.flickr.com/photos/usinterior/15863210084/in/photolist-qaM6G9-aCisif-qe3E9k-bBfpRi-UnPCMG-qe4YW6-9v4WQw-6FWFQg-qdVDHW-9WrrJA-9wWuGb-qvqRzQ-WFYU9L-e1BeGg-TA62s1-i45ou3-26GEEsU-r7GKg5-dyxMgh-fTR2E9-SdM8xs-pDc6Uq-oN6i68-oN5Sso-Gi4fnV-ZzGf5w-BU8g4R-8F1rdR-fg37Qz-pRtLcX-cCg7Em-5hJGf6-EutxaU-aCirFo-wmY3qQ-RceEbd-e2Qf9U-XTCK6s-bvVhfF-r7Wxz9-9c3qZz-RM7sHx-r7MGKr-JULX3k-XKrTR8-55u3hW-PNyWWK-qe4bor-QXinJ1-p5zHGD">U.S. Department of Interior</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<p>Because solar and wind conditions vary across the landscape, system <a href="https://www.sciencedirect.com/science/article/pii/S187661021830986X">costs fall as a production area grows</a>, so there needs to be a <a href="https://theconversation.com/the-cheapest-way-to-scale-up-wind-and-solar-energy-high-tech-power-lines-53597">robust electric grid</a> to move electricity from places where there is supply to places of demand. We also need more electricity for applications like transportation that currently use fossil fuels. This means the grid must grow.</p>
<p>Studies show that running an electric grid with variable renewable energy will <a href="https://theconversation.com/a-radical-idea-to-get-a-high-renewable-electric-grid-build-way-more-solar-and-wind-than-needed-113635">include not using, or dumping, some energy</a> at times, a strategy that reduces cost compared to always storing surplus energy. </p>
<p>Still, some form of <a href="https://www.sciencedirect.com/science/article/pii/S1364032114008284">electricity storage</a> is needed. Batteries work well for smoothing short-term fluctuations, but for storing energy for many hours or days, <a href="https://www.sciencedirect.com/science/article/pii/S1364032115000106">pumped hydroelectric storage</a> is less expensive. Pumped hydro uses any extra energy in the grid to pump water uphill, and when energy is needed, the water runs back down to generate power in a turbine. The United States has some existing examples and <a href="https://www.sciencedirect.com/science/article/pii/S1364032110003072">many feasible locations</a>. With grid expansion, storage may be located at a distance from users.</p>
<p>Hydroelectricity and biomass power are available on demand, so having these in a renewable electric grid shrinks the energy storage need and reduces cost. Both have environmental effects that must be managed. </p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=606&fit=crop&dpr=1 600w, https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=606&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=606&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=762&fit=crop&dpr=1 754w, https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=762&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/288969/original/file-20190821-170918-1lseqp6.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=762&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption"></span>
<span class="attribution"><a class="source" href="https://www.eia.gov/energyexplained/index.php?page=electricity_in_the_united_states">U.S. Energy Information Administration</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>Hydropower can alter local ecosystems. Burning <a href="https://theconversation.com/the-epa-says-burning-wood-to-generate-power-is-carbon-neutral-is-that-true-95727">biomass emits carbon dioxide</a>, but a study I worked on shows that biomass emissions <a href="https://onlinelibrary.wiley.com/doi/full/10.1111/gcbb.12276">are reversible</a> and are clearly carbon-preferable to fossil-fuel emissions. Sustainability also depends critically on management of biomass fields and forests; the human track record on this <a href="https://www.nytimes.com/2018/11/20/magazine/palm-oil-borneo-climate-catastrophe.html">has not been stellar</a>. </p>
<p>Renewable energy systems require land. A <a href="https://pubs.rsc.org/en/content/articlelanding/2015/ee/c5ee01283j#!divAbstract">U.S. study</a> shows that supplying all electricity from wind, water and solar would need 0.42% of land area, plus 1.6% of land area for space between wind turbines. Biomass energy requires much more land than wind or solar, so biomass must be a small part of the renewable energy solution.</p>
<h2>Real barriers are political and cultural</h2>
<p>A future renewable electricity grid with associated electrification may or may not <a href="https://www.axios.com/wind-solar-energy-grow-challenges-6e07bb69-a291-4935-9458-beb4454678b1.html">reduce energy costs</a>. But avoiding the worst effects of climate change means quitting fossil fuels, whether or not this saves money. Still, the renewable transition will be faster and politically easier if it is less expensive. </p>
<p>In <a href="https://www.sciencedirect.com/science/article/pii/S0301421519304732">Mauritius</a>, our study finds renewable electricity costs to be similar to present costs there, based on current capital costs for renewable energy. <a href="https://www.sciencedirect.com/science/article/pii/S1876610218310221">Some studies</a> also find costs for future renewable electricity to be lower than present fossil-fuel costs, in the likely event that costs fall as we build more renewable energy systems and get better at doing it. </p>
<p><iframe id="Qf3BY" class="tc-infographic-datawrapper" src="https://datawrapper.dwcdn.net/Qf3BY/2/" height="400px" width="100%" style="border: none" frameborder="0"></iframe></p>
<p>And that’s it, from a technical perspective. A combination of renewable sources and energy storage – the specific combination depending on local conditions and preferences – can supply all the electricity needed at an affordable price, and will reduce air pollution to boot. </p>
<p>But government policies are needed to make a transition to renewable energy. Climate change is an external cost – borne by society rather than by energy producers – so market forces alone will not make the transition. Besides putting a price on carbon (perhaps with <a href="https://www.politico.com/agenda/story/2019/07/23/reduce-carbon-emissions-000936">dividends returned to the public</a>), government could make it easier to build the needed infrastructure. And public support is needed: For example, public acceptance of transmission lines to move electricity from the windy Great Plains to city centers is another challenge for an all-renewable grid.</p>
<p>A project on the scale of transforming the energy system will <a href="https://www.americanprogress.org/issues/green/reports/2014/09/18/96404/green-growth/">create jobs</a> – many jobs – which is perhaps the economic measure of most importance to the citizenry. </p>
<p>Research from me and others shows that fully renewable electric grids are feasible with current technology at current prices; barriers to using renewable electricity are more <a href="https://www.sciencedirect.com/science/article/abs/pii/S1364032118303897">political and cultural than technological or economic</a>.</p>
<p>[ <em>Like what you’ve read? Want more?</em> <a href="https://theconversation.com/us/newsletters?utm_source=TCUS&utm_medium=inline-link&utm_campaign=newsletter-text&utm_content=likethis">Sign up for The Conversation’s daily newsletter</a>. ]</p><img src="https://counter.theconversation.com/content/120713/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>David Timmons received funding for the Mauritius study from a Fulbright Program grant sponsored by the Bureau of Educational and Cultural Affairs of the United States Department of State. </span></em></p>We have all the technologies needed to make the electric grid run on renewables and lower pollution. What are they and what are the barriers to adopting them widely?David Timmons, Associate Professor of Economics, UMass BostonLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1165732019-08-15T11:14:55Z2019-08-15T11:14:55ZWhy are so many languages spoken in some places and so few in others?<figure><img src="https://images.theconversation.com/files/287904/original/file-20190813-9404-1feepwk.jpg?ixlib=rb-1.1.0&rect=1357%2C339%2C4944%2C2738&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">What factors contribute to some places having many, while other places have few?</span> <span class="attribution"><a class="source" href="https://www.shutterstock.com/image-vector/icons-people-speech-bubbles-chatting-vector-357391937">VLADGRIN/Shutterstock.com</a></span></figcaption></figure><p>People across the world describe their thoughts and emotions, share experiences and spread ideas through the use of thousands of distinct languages. These languages form a fundamental part of our humanity. They determine whom we communicate with and how we express ourselves.</p>
<p>Despite continually mapping the distribution of languages across the world, scientists have few clear answers about what caused the emergence of thousands of languages. Collectively, <a href="https://glottolog.org/">human beings speak more than 7,000 distinct languages</a>, and these languages are not uniformly distributed across the planet. For example, far more languages are spoken <a href="https://doi.org/10.1371/journal.pone.0107623">in tropical regions than in temperate areas</a>.</p>
<p>But why are there so many languages spoken in some places and so few in others? </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=303&fit=crop&dpr=1 600w, https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=303&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=303&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=381&fit=crop&dpr=1 754w, https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=381&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/287720/original/file-20190812-71917-1flrn2t.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=381&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A grid map of language ranges in North America prior to European contact.</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1098/rspb.2019.0242">Coelho et al. RSPB 2019</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>Our research team has been tackling this longstanding question by exploring <a href="https://doi.org/10.1098/rspb.2019.0242">language diversity patterns on the continent of North America</a>. Prior to European contact, North America was home to speakers of around 400 languages, unevenly spread across the landscape. Some places, such as the West Coast from present-day Vancouver to southern California, had far more languages; other areas, such as northern Canada and the Mississippi delta region, appear to have had fewer languages. We drew on methods from ecology originally developed to study <a href="https://doi.org/10.1111/j.1600-0587.2012.07553.x">patterns of species diversity</a> to investigate these patterns of language diversity.</p>
<h2>Building boundaries</h2>
<p>Many theories have outlined <a href="https://doi.org/10.1525/bio.2013.63.7.6">possible ways the world’s languages might have diversified</a>.</p>
<p>Fundamental to all of these theories is the idea that languages are markers of social boundaries between human groups. People who speak the same language share a common means of communication. And this fact is readily evident both to those who speak the language and those who do not. After just a few words, you can often surmise who is in your group and who is not.</p>
<p>So any factor that might create or weaken the social or physical barriers between groups may also influence the emergence or extinction of languages.</p>
<p>One idea is that physical barriers create boundaries between human groups. When people move to the other side of a large mountain range, for instance, or <a href="https://doi.org/10.1111/j.1466-8238.2011.00744.x">the ocean</a>, it becomes increasingly hard to interact with previously neighboring groups. Over time, if the groups remain isolated, one might expect their languages to diverge. If physical isolation is a critical factor, then we should find a larger number of languages in locations that promote more isolation, such as mountainous regions. </p>
<p>Another possible way group boundaries might form involves how much groups must cooperate in order to survive. Some researchers suggest that more extreme or variable climatic conditions <a href="https://doi.org/10.1098/rsos.171897">can make food harder to obtain</a>. This uncertainty may lead people to build larger social networks in order to share resources in times of need. More frequent contact through the extended social networks could dissolve social boundaries and reduce language diversity. In this case, one would expect <a href="https://doi.org/10.1006/jaar.1996.0015">less language diversity</a> in locations with unstable or extreme climatic conditions.</p>
<p>Perhaps how many people can live in a given location also shapes language diversity. Some environmental and social conditions can support higher densities of people. These greater population densities might lead to increases in language diversity in a number of ways. For example, human groups do not increase infinitely. Maintaining social ties may come at a cost, such that when a group gets too big, it will tend to divide. Therefore, you might expect more distinct human groups to accumulate in locations that can support more people. And with more distinct groups, you’d also expect to see <a href="https://doi.org/10.1111/geb.12563">more languages in these locations</a>.</p>
<h2>No single explanation</h2>
<p>Surprisingly, few of these theories, or many others that researchers have proposed, have been rigorously tested. And the tests that have been done <a href="https://doi.org/10.1525/bio.2013.63.7.6">point to contradictory results</a>. For instance, some studies support the idea that less language diversity is found in locations with unstable and extreme climatic conditions, while others found little or no support for that idea.</p>
<p>The problem has been that researchers have tended to search for one silver bullet, a single factor that would explain patterns of language diversity everywhere. But why expect one factor to accurately summarize thousands of years of human history across the entire globe, or even across a continent? What if the story underlying language diversity in northern Canada is totally different from the story underlying language diversity in California? </p>
<p>Recently, our interdisciplinary research group tried to untangle which factors had the most influence on language diversity in different places. Combining ideas from linguists, ecologists, evolutionary biologists and geographers, we took a unique approach. We used statistical techniques to estimate how the effects of <a href="https://doi.org/10.1098/rspb.2019.0242">environmental and sociocultural factors on language diversity</a> changed from one location to another. In our study, each location was represented by a 300 km² grid cell, as is visible in all our maps.</p>
<p>We found that the most important variables associated with language diversity varied from one part of North America to another.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=290&fit=crop&dpr=1 600w, https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=290&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=290&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=365&fit=crop&dpr=1 754w, https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=365&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/287728/original/file-20190812-71905-v0f88j.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=365&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Language diversification in different regions may have been driven by different factors. In some places, like the areas in pink, temperature variability might have been most important. Other possible factors include population density (gray), precipitation constancy (light blue), topographic complexity (dark blue), carrying capacity with group size limits (green) and climate change velocity (purple).</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1098/rspb.2019.0242">Modified from Coelho et al. RSPB 2019</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>For example, on the West Coast, we found that variability in temperature over time is a key driver linked to language diversity. This result provides some support for the idea that in areas with more stable environmental conditions, human social networks can be smaller and more languages may exist. </p>
<p>However, in the eastern part of the continent, potential population density tends to be the factor most strongly linked to language diversity.</p>
<p>We also found that in some places, such as the high-language-diversity regions on the West Coast, our model could predict the number of languages present very accurately, whereas in other areas, such as the Gulf Coast of the U.S., we have limited understanding of what drove language diversification.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=332&fit=crop&dpr=1 600w, https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=332&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=332&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=417&fit=crop&dpr=1 754w, https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=417&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/287731/original/file-20190812-71913-1abfudf.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=417&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">The model’s ability to predict the number of languages varied from excellent in some places (red) to poor in others (green).</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1098/rspb.2019.0242">Modified from Coelho et al. RSPB 2019</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>Our analytical tools were originally developed to study patterns of species diversity; these approaches are now starting to increase scientists’ understanding of what factors <a href="https://doi.org/10.1371/journal.pone.0158391">shaped human diversity</a>. But our results so far also underscore how much is still unknown about how cultural diversity originated and how it will change into the future.</p><img src="https://counter.theconversation.com/content/116573/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Marco Túlio Pacheco Coelho receives funding from Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
(CAPES, finance code 001). </span></em></p><p class="fine-print"><em><span>Michael Gavin receives funding from the National Science Foundation (grant numbers: 1660465 and 1519987)</span></em></p>Linguists have a lot of largely untested theories. Borrowing a tool from ecology, researchers built a model that didn’t look for one worldwide explanation.Marco Túlio Pacheco Coelho, Ph.D. Student in Ecology, Universidade Federal de Goias (UFG)Michael Gavin, Associate Professor of Human Dimensions of Natural Resources, Colorado State UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/1151052019-04-10T10:47:57Z2019-04-10T10:47:57ZEmpathy is the secret ingredient that makes cooperation – and civilization – possible<figure><img src="https://images.theconversation.com/files/268466/original/file-20190409-2909-1xhbhyt.jpg?ixlib=rb-1.1.0&rect=945%2C338%2C2948%2C2154&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">What goes into all for one and one for all?</span> <span class="attribution"><a class="source" href="https://www.shutterstock.com/image-photo/united-hands-close-up-black-white-333648788?src=f9ZsPuZmwUx5Z9EDJPp8Qg-1-5">Africa Studio/Shutterstock.com</a></span></figcaption></figure><p>Human societies are so prosperous mostly because of how altruistic we are. Unlike other animals, people cooperate even with complete strangers. We share knowledge on Wikipedia, we show up to vote, and we work together to responsibly manage natural resources.</p>
<p>But where do these cooperative skills come from and why don’t our selfish instincts overwhelm them? Using a branch of mathematics called <a href="https://www.nature.com/scitable/knowledge/library/game-theory-evolutionary-stable-strategies-and-the-25953132">evolutionary game theory</a> to explore this feature of human societies, my collaborators <a href="https://scholar.google.com/citations?user=yi-SnYcAAAAJ&hl=en&oi=ao">and I</a> <a href="https://doi.org/10.7554/eLife.44269">found that empathy</a> – a uniquely human capacity to take another person’s perspective – might be responsible for sustaining such extraordinarily high levels of cooperation in modern societies.</p>
<h2>Social rules of cooperation</h2>
<p>For decades scholars have thought that <a href="https://doi.org/10.1257/jep.14.3.137">social norms and reputation</a> can explain much altruistic behavior. Humans are <a href="https://doi.org/10.1073/pnas.1301210110">far more likely</a> to be kind to individuals they see as “good,” than they are to people of “bad” reputation. If everyone agrees that being altruistic toward other cooperators earns you a good reputation, cooperation will persist.</p>
<p>This universal understanding of whom we see as morally good and worthy of cooperation is a form of <a href="https://plato.stanford.edu/entries/social-norms/">social norm</a> – an invisible rule that guides social behavior and promotes cooperation. A common norm in human societies called “stern judging,” for instance, rewards cooperators who refuse to help bad people, but many other norms are possible.</p>
<p>This idea that you help one person and someone else helps you is called the <a href="https://doi.org/10.1038/nature04131">theory of indirect reciprocity</a>. However, it’s been built assuming that people always agree on each others’ reputations as they change over time. Moral reputations were presumed to be fully objective and publicly known. Imagine, for instance, an all-seeing institution monitoring people’s behavior and assigning reputations, like China’s <a href="https://www.forbes.com/sites/bernardmarr/2019/01/21/chinese-social-credit-score-utopian-big-data-bliss-or-black-mirror-on-steroids/#1cd4ebb748b8">social credit system</a>, in which people will be rewarded or sanctioned based on “social scores” calculated by the government.</p>
<p>But in most real-life communities, people often disagree about each others’ reputations. A person who appears good to me might seem like a bad individual from my friend’s perspective. My friend’s judgment might be based on a different social norm or a different observation than mine. This is why reputations in real societies are relative – people have different opinions about what is good or bad.</p>
<p>Using biology-inspired evolutionary models, I set out to investigate what happens in a more realistic setting. Can cooperation evolve when there are disagreements about what is considered good or bad? To answer this question, I first worked with mathematical descriptions of large societies, in which people could choose between various types of cooperative and selfish behaviors based on how beneficial they were. Later I used computer models to simulate social interactions in much smaller societies that more closely resemble human communities.</p>
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<p>The results of my modeling work were not encouraging: Overall, moral relativity made societies less altruistic. Cooperation almost vanished under most social norms. This meant that most of what was known about social norms promoting human cooperation may have been false.</p>
<h2>Evolution of empathy</h2>
<p>To find out what was missing from the dominant theory of altruism, I teamed up with <a href="http://mathbio.sas.upenn.edu/">Joshua Plotkin</a>, <a href="https://scholar.google.com/citations?user=WANIT2oAAAAJ&hl=en&oi=ao">a theoretical biologist</a> at the University of Pennsylvania, and <a href="https://www.alexanderjstewart.org/">Alex Stewart</a> at the University of Houston, both <a href="https://scholar.google.com/citations?user=Z3-RzE0AAAAJ&hl=en&oi=ao">experts in game theoretical approaches</a> to human behavior. We agreed that my pessimistic findings went against our intuition – most people do care about reputations and about the moral value of others’ actions. </p>
<p>But we also knew that humans have a remarkable ability to <a href="https://doi.org/10.1177/2374373517699267">empathetically include other people’s views</a> when deciding that a certain behavior is morally good or bad. On some occasions, for instance, you might be tempted to judge an uncooperative person harshly, when you really shouldn’t if from their own perspective, cooperation was not the right thing to do.</p>
<p>This is when my colleagues and I decided to modify our models to give individuals the capacity for empathy – that is, the ability to make their moral evaluations from the perspective of another person. We also wanted individuals in our model to be able to learn how to be empathetic, simply by observing and copying personality traits of more successful people.</p>
<p>When we incorporated this type of <a href="https://doi.org/10.7554/eLife.44269">empathetic perspective-taking into our equations</a>, cooperation rates skyrocketed; once again we observed altruism winning over selfish behavior. Even initially uncooperative societies in which everyone judged each other based mostly on their own selfish perspectives, eventually discovered empathy – it became socially contagious and spread throughout the population. Empathy made our model societies altruistic again.</p>
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<p>Moral psychologists have long suggested that <a href="https://www.psychologytoday.com/us/blog/wild-connections/201709/cultivating-empathy">empathy can act as social glue</a>, increasing cohesiveness and cooperation of human societies. Empathetic perspective-taking <a href="https://theconversation.com/children-understand-far-more-about-other-minds-than-long-believed-72711">starts developing in infancy</a>, and at least some <a href="https://doi.org/10.1002/icd.740">aspects of empathy are learned</a> from parents and other members of the child’s social network. But how humans evolved empathy in the first place remained a mystery.</p>
<p>It is incredibly difficult to build rigorous theories about concepts of moral psychology as complex as empathy or trust. Our study offers a new way of thinking about empathy, by incorporating it into the well-studied framework of evolutionary game theory. Other moral emotions like guilt and shame can potentially be studied in the same way.</p>
<p>I hope that the link between empathy and human cooperation we discovered can soon be tested experimentally. Perspective-taking skills are most important in communities where many different backgrounds, cultures and norms intersect; this is where different individuals will have diverging views on what actions are morally good or bad. If the effect of empathy is as strong as our theory suggests, there could be ways to use our findings to promote large-scale cooperation in the long term – for instance, by designing nudges, interventions and policies that promote development of perspective-taking skills or at least encourage considering the views of those who are different.</p><img src="https://counter.theconversation.com/content/115105/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Arunas L. Radzvilavicius receives funding from David and Lucile Packard Foundation and the U.S.
Army Research Office. </span></em></p>Where do the cooperative skills that hold together human societies come from and why don’t our selfish instincts overwhelm them? Evolutionary game theory suggests that empathy is a crucial contributor.Arunas L. Radzvilavicius, Postdoctoral Researcher of Evolutionary Biology, University of PennsylvaniaLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/908222018-01-30T17:31:55Z2018-01-30T17:31:55ZCan scientists learn to make ‘nature forecasts’ just as we forecast the weather?<figure><img src="https://images.theconversation.com/files/203834/original/file-20180129-89550-1iyvfao.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Images created by NASA with satellite data helped the U.S. Department of Agriculture analyze outbreak patterns for southern pine beetles in Alabama, in spring 2016.</span> <span class="attribution"><a class="source" href="https://develop.larc.nasa.gov/2016/spring/AlabamaEco.html">NASA</a></span></figcaption></figure><p>Imagine that spring has finally arrived and you’re planning your weekend. The weather forecast looks great. You could go to the beach – but what if it’s closed because of an algal bloom? Maybe you could go for a hike – will the leaves be out yet? What might be in flower? Will the migratory birds be back? Oh, and you heard last year was bad for ticks – will this spring be better or worse? </p>
<p>We all take weather forecasts for granted, so why isn’t there a ‘nature forecast’ to answer these questions? Enter the new scientific field of <a href="https://press.princeton.edu/titles/11048.html">ecological forecasting</a>. Ecologists have long sought to understand the natural world, but only recently have they begun to think systematically about forecasting.</p>
<p>Much of the current research in ecological forecasting is focused on long-term projections. It considers questions that play out over decades to centuries, such as how species may shift their ranges in response to climate change, or whether forests will continue to take up carbon dioxide from the atmosphere. </p>
<p>However, in a new <a href="https://doi.org/10.1073/pnas.1710231115">article</a> that I co-authored with 18 other scientists from universities, private research institutes and the U.S. Geological Survey, we argue that focusing on near-term forecasts over spans of days, seasons and years will help us better understand, manage and conserve ecosystems. Developing this ability would be a win-win for both science and society.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=420&fit=crop&dpr=1 600w, https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=420&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=420&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=528&fit=crop&dpr=1 754w, https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=528&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/203829/original/file-20180129-89597-14rm65h.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=528&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A ‘red tide’ bloom of <em>Karenia brevis</em>, a toxic microorganism that can cause fish kills and poison humans who eat contaminated shellfish. Scientists use satellite imagery and water sampling to predict harmful algal blooms and other short-term ecological phenomena.</span>
<span class="attribution"><a class="source" href="http://www.noaanews.noaa.gov/stories2010/20101209_habs.html">Chase Fountain/Texas Parks & Wildlife</a></span>
</figcaption>
</figure>
<h2>The benefits of forecasting</h2>
<p>Beyond helping people plan their weekends, ecological forecasts will improve decision-making in agriculture, forestry, fisheries and other industries. They will help private landowners, local governments and state and federal agencies better manage and conserve our land, water and coastlines, for example by warning of events such as pest outbreaks and <a href="https://theconversation.com/nutrient-pollution-voluntary-steps-are-failing-to-shrink-algae-blooms-and-dead-zones-81249">harmful algal blooms</a>. They will improve public health through better forecasts of infectious disease outbreaks and better planning in anticipation of famine, wildfire and other natural disasters. </p>
<p>Ecological forecasts will also deepen our understanding of the world around us, and of how human activities are altering it. Forecasting formalizes the cycle between <a href="https://theconversation.com/scientific-theories-arent-mere-conjecture-to-survive-they-must-work-73040">prediction and testing</a> that is at the heart of the scientific method, and repeats it on a much quicker cycle. It can accelerate the pace of discovery in the environmental sciences at this critical time of rapid environmental change.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=363&fit=crop&dpr=1 600w, https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=363&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=363&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=456&fit=crop&dpr=1 754w, https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=456&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/203672/original/file-20180128-100926-ayhans.jpeg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=456&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Weather forecast skill at the National Oceanic and Atmospheric Administration has improved continually and dramatically since the dawn of numerical weather prediction in the 1950s (100 = perfect score, 0 = random). The increasing accuracy over time has been attributed to more data, faster computers and better tools for bringing data into models every day. The synergy of these factors has steadily advanced our understanding of the atmosphere and improved weather models.</span>
<span class="attribution"><a class="source" href="https://celebrating200years.noaa.gov/foundations/numerical_wx_pred/S1Chart06.html">Adapted from NOAA</a>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<h2>New tools and technology</h2>
<p>Big data is driving many of the advances in ecological forecasting. Today ecologists have orders of magnitude more data compared to just a decade ago, thanks to sustained public funding for basic science and environmental monitoring. This investment has given us better sensors, satellites and organizations such as the <a href="http://www.neonscience.org/">National Ecological Observatory Network</a>, which collects high-quality data from 81 field sites across the United States and Puerto Rico. At the same time, cultural shifts across funding agencies, research networks and journals have made that data more open and available. </p>
<p>Digital technologies make it possible to access this information more quickly than in the past. Field notebooks have given way to tablets and cell networks that can stream new data into supercomputers in real time. Computing advances allow us to build better models and use more sophisticated statistical methods to produce forecasts.</p>
<h2>Technical and social challenges</h2>
<p>So far, though, ecological forecasting has not kept pace with advances in data and technology. In our article, we lay out a road map for accelerating the field by tackling the bottlenecks slowing us down. </p>
<p>Some of these bottlenecks are technical, such as better integrating the streams of data that are now available from many different sources, such as field studies, sensor networks and satellite observations. </p>
<p>Other challenges involve human choices. Ecologists need to spend more time engaged in two-way communication with stakeholders, rather than just pushing out the latest research to decision-makers. And we need better ways to transfer state-of-the-art research from universities to agencies and private industry. </p>
<p>Perhaps most limiting is that ecologists traditionally have not been taught forecasting concepts and methods. But as I have <a href="https://press.princeton.edu/titles/11048.html">written</a>, this situation is changing. There now are summer <a href="https://ecoforecast.wordpress.com/summer-course/">workshops</a> and a growing number of university courses in ecological forecasting. Prediction is leading to <a href="http://dx.doi.org/10.1002/eap.1589">new theories</a> that aim to unify different parts of ecology.</p>
<figure>
<iframe width="440" height="260" src="https://www.youtube.com/embed/2rt1IOXCELM?wmode=transparent&start=0" frameborder="0" allowfullscreen=""></iframe>
<figcaption><span class="caption">With data from the National Ecological Observatory Network (NEON), scientists can compare the health of U.S. ecosystems over time.</span></figcaption>
</figure>
<h2>Ecology’s choice</h2>
<p>At the dawn of numerical weather prediction in the 1950s, scientists at the National Weather Service faced a choice. They could either wait to start forecasting until the underlying research, models and tools improved, or proceed immediately with making forecasts and learn by doing. They chose the second path. It proved harder than expected – but had they waited, they <a href="https://journals.ametsoc.org/doi/pdf/10.1175/1520-0434%281989%29004%3C0286%3AHONWPA%3E2.0.CO%3B2">likely would have failed</a> because they would have missed a critical window when experts and agencies were willing to make major investments in this effort.</p>
<p>Up to now, ecologists have generally adhered to the first, more conservative path. But in this time of rapid environmental change, the societal need and technological capacity for forecasting have never been greater. The forecasts won’t always be right, especially as the field develops, but <a href="https://theconversation.com/failure-in-real-science-is-good-and-different-from-phony-controversies-37217">failure is part of learning</a>. The time for ecologists to start forecasting is now.</p><img src="https://counter.theconversation.com/content/90822/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Michael Dietze receives funding from the National Science Foundation, the National Aeronautics and Space Administration, and the Strategic Environmental Research and Development Program. </span></em></p>Big data open-access publishing and other advances offer ecologists the ability to forecast events like pest outbreaks over days and seasons rather than decades. But scholars need to seize this opportunity.Michael Dietze, Associate Professor of Earth and Environment, Boston UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/863712017-11-02T23:38:41Z2017-11-02T23:38:41ZIt’s mostly mothers who pass on mitochondria – and a new theory says it’s due to the first sexual conflict<figure><img src="https://images.theconversation.com/files/193092/original/file-20171102-26478-lwqk5w.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Is this how we got the sperm and the egg?</span> <span class="attribution"><a class="source" href="https://www.shutterstock.com/image-photo/sperm-egg-1762515">Sebastian Kaulitzki/Shutterstock</a></span></figcaption></figure><p>Evolutionary interests of males and females do not always coincide. This is known as sexual conflict: male innovations that allow them to reproduce more sometimes hurt females, and vice versa.</p>
<p>Male fruit flies, for instance, inject their partners with <a href="http://www.nytimes.com/1995/01/24/science/sex-and-the-fruit-fly-price-of-promiscuity-is-premature-death.html">toxic chemicals</a> during sex. These toxins destroy sperm of the female’s previous mates, improving his own chances for becoming the sole father of her offspring. But the toxins also make female flies sick and reduce their lifespan. Females, in turn, have evolved defenses to counter the chemicals, sometimes at the expense of males’ success. </p>
<p>Biologists believe that sexual conflicts are rooted in the <a href="http://www.cell.com/trends/ecology-evolution/abstract/S0169-5347(02)00004-6">size and number of reproductive cells</a> – eggs and sperm. Males typically produce large numbers of sperm that can fertilize multiple eggs. Females, on the other hand, produce a small number of large reproductive cells, and so invest more energy and resources in each. </p>
<p><a href="http://www.ucl.ac.uk/%7Eucbhpom/people.html">My team</a> of evolutionary biologists at University College London <a href="https://doi.org/10.1186/s12915-017-0437-8">has now identified a different kind of sexual conflict</a>, dating back to the days when the most complex organisms were made of single cells, possibly as far as 1.5 billion years ago. This ancient sexual conflict – before the two sexes even existed – had to do with whose mitochondria would be passed on to offspring.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=544&fit=crop&dpr=1 600w, https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=544&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=544&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=684&fit=crop&dpr=1 754w, https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=684&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/192858/original/file-20171101-19894-1jdkw1c.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=684&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Eukaryotic cells have a nucleus (blue) and numerous mitochondria (green).</span>
<span class="attribution"><a class="source" href="https://www.flickr.com/photos/nihgov/20495441928">Dylan Burnette and Jennifer Lippincott-Schwartz, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health</a>, <a class="license" href="http://creativecommons.org/licenses/by-nc/4.0/">CC BY-NC</a></span>
</figcaption>
</figure>
<h2>Whose mitochondria will be passed on?</h2>
<p>We studied inheritance of genes located in <a href="https://www.livescience.com/50679-mitochondria.html">mitochondria</a> – the structures inside our cells that breathe and produce energy. In many animals and plants, when the egg is fertilized, only the mother’s mitochondrial genes survive, while the father’s mitochondria are lost.</p>
<p>This is not by accident: Females have evolved many mechanisms to recognize a partner’s mitochondria entering the egg. Once detected, an army of enzymes is sent to digest them. Previous research has shown that <a href="https://doi.org/10.1098/rspb.2013.1920">getting rid of male mitochondria</a> is a way to keep descendents’ mitochondrial genes mutation-free. In the long run, inheritance of healthy maternal mitochondria is good news for the offspring.</p>
<figure class="align-right zoomable">
<a href="https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=511&fit=crop&dpr=1 600w, https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=511&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=511&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=642&fit=crop&dpr=1 754w, https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=642&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/192864/original/file-20171101-19845-1rugssj.gif?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=642&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">For the most part mitochondria come from the mother’s line. But there are exceptions.</span>
<span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Mitochondrial_DNA_versus_Nuclear_DNA.gif">University of California Museum of Paleontology and the National Center for Science Education</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<p>But there are many exceptions that remain unexplained. In some species, <a href="https://doi.org/10.1038/hdy.2012.60">paternal mitochondria remain undigested</a>, as if the father had found a way to protect them from being detected. Stranger still, in organisms such as fruit flies and many plants, it is the father that destroys most of his own mitochondria during production of sperm.</p>
<p>If maternal inheritance is as beneficial as previous research shows, why are there so many exceptions?</p>
<h2>Taking the long or the short view</h2>
<p>In our new study, we show that these exceptions arise because of a <a href="https://doi.org/10.1186/s12915-017-0437-8">sexual conflict over the control of mitochondrial inheritance</a>.</p>
<p>Using mathematical modeling, we found that evolution in females tends to focus on long-term effects. Destroying paternal mitochondria makes it easier to weed out harmful mutations in the future, but this effect unfolds over many generations. This strategy works well in females, because the same healthy set of maternal mitochondria is passed down the female line over and over again. </p>
<p>But males don’t have a long evolutionary time horizon to deal with in this case. Since most of their mitochondria are replaced by maternal ones at the start of every generation, evolution cannot detect long-term benefits from males’ mitochondrial genes. Because there’s no long-term link, they can benefit only in the immediate future, and that often means passing on some of their mitochondria right now. Males therefore seek to improve the fitness of their offspring in the short-term, even if the long-term effects are harmful.</p>
<p>It’s these different interests of males and females that can lead to an evolutionary arms race, as selection in the two sexes acts in opposite directions. Evolution in females strives to keep the future generations free of male mitochondria, while males make every effort to get some of theirs into the mix.</p>
<p>“Over and over again, males have come up with ways to subvert female destruction of their mitochondria,” said my co-author, geneticist <a href="http://www.ucl.ac.uk/%7Eucbhpom/">Andrew Pomiankowski</a>. “So females had to develop new ways to block male mitochondria. Our model explains nicely why there are so many different mechanisms used to exclude male mitochondria, and why males sometimes do it themselves.”</p>
<p>It’s all about the control of mitochondrial inheritance – and for males it’s better to be in the driver’s seat to decide how many mitochondria they contribute to the mix than be completely excluded.</p>
<h2>A sexual conflict that led to the sexes</h2>
<p>There is evidence that this conflict dates back to the days when all organisms were made of single cells. Male and female sexes did not exist, because all reproductive cells were of the same size. </p>
<p>“One of the strategies an organism can use to win in this conflict is to simply have more mitochondria than their partner, for example, by increasing the size of their sex cells,” Andrew Pomiankowski said. “Strikingly, this might have been the impetus to evolve two sexes in the first place.” Larger sex cells – the future eggs – garnered an advantage in the battle over mitochondrial inheritance, simply by swamping smaller sex cells – the forerunners of sperm – that had fewer mitochondria to contribute.</p>
<p>Most biologists currently think that <a href="https://doi.org/10.1098/rspb.2002.2161">two sexes evolved through division of labor</a> – a so-called “disruptive selection” theory. Large female sex cells can survive longer but cannot move much, while smaller sperm are fragile but move faster and can find more mating partners.</p>
<p>Our hypothesis on the origin of sexes, if true, adds a new angle to this origins story, tracing it back to an ancient conflict over mitochondrial inheritance. Females may have won this ancient battle by simply producing larger sex cells packed with mitochondria, ensuring that mitochondrial transmission is effectively one-sided (and reaping the long-term fitness benefits). But ultimately, as with all scientific hypotheses, this one will have to stand the test of thorough experimental verification.</p><img src="https://counter.theconversation.com/content/86371/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Arunas L Radzvilavicius receives funding from David and Lucille Packard Foundation.</span></em></p>An ancient sexual conflict over mitochondrial inheritance may be responsible for the evolution of the two sexes as we know them.Arunas L. Radzvilavicius, Postdoctoral Researcher of Evolutionary Biology, University of PennsylvaniaLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/808612017-08-03T01:00:21Z2017-08-03T01:00:21ZSoundscapes in the past: Adding a new dimension to our archaeological picture of ancient cultures<figure><img src="https://images.theconversation.com/files/180405/original/file-20170731-22169-j5elmn.JPG?ixlib=rb-1.1.0&rect=312%2C0%2C2759%2C1811&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">What sounds did the people of Chaco Canyon hear during daily life?</span> <span class="attribution"><span class="source">David E. Witt</span>, <a class="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">CC BY-NC-ND</a></span></figcaption></figure><p>Picture an archaeological site, what comes to mind? Sandstone walls, standing in the desert heat? Stonehenge, watching over a grassy field?</p>
<p>When thinking about archaeological sites, we tend to conceive of them as dead silent – empty ruins left by past cultures. But this isn’t how the people who lived in and used these sites would have experienced them. Residents would have heard others speaking and laughing, babies crying, people working, dogs barking and music such as drumming. These sounds could be heard from close by, and perhaps coming from distant locations as well. </p>
<p>Putting sound back into the archaeological landscape is an important part of understanding how people lived, what they valued, how they shaped their identities and experienced the world and their place in it. This growing field is called acoustic archaeology, or archaeoacoustics. By considering the sounds heard by people moving through the landscape, we’re able to more fully understand their culture, and thus better relate to them as human beings.</p>
<p>We <a href="https://doi.org/10.1016/j.jasrep.2017.05.044">recently modeled an ancient soundscape</a> at the landscape level for the first time. What can our ears tell us about the way the Anasazi, or Ancestral Puebloan, people lived in New Mexico’s Chaco Canyon more than a thousand years ago?</p>
<h2>Modeling ancient sound</h2>
<p><a href="https://uofupress.lib.utah.edu/chacos-northern-prodigies/">Chaco Canyon was the center</a> of <a href="https://sarweb.org/?sar_press_a_history_of_the_ancient_southwest">ancestral Puebloan civilization</a>. It’s famous for its great houses – large, multistoried structures, some the size of football fields – built and used from approximately A.D. 850-1150. Archaeologists have studied how the Ancestral Puebloans <a href="https://uofupress.lib.utah.edu/the-architecture-of-chaco-canyon-new-mexico/">built the structures of Chaco Canyon</a> and <a href="https://sarweb.org/?sar_press_chaco_experience">placed them in relation</a> to each other and <a href="http://www.solsticeproject.org">to astronomical alignments</a>.</p>
<p>To add a new dimension to our understanding of this time and place, we investigated how sounds were experienced at these sites. We wanted to know how a listener would have experienced a sound from a specific distance away from whatever was producing it.</p>
<p>To explore sound physics and its application to archaeology, we first developed an Excel spreadsheet. Our calculations described linear sound profiles, similar to a line-of-sight analysis; this took into account a straight path between the person or instrument making the noise and the person hearing it. However, this approach was limited because the results applied to only one listener standing at a very specific location a set distance away.</p>
<p>Our research truly blossomed when we wondered if we could apply the same sound physics calculations to an entire landscape simultaneously. We turned to a type of computer program called Geographic Information Systems (GIS) that allows us to model the world in three dimensions.</p>
<p>The software package we used, ESRI’s ArcGIS, offers anyone the option to create customized tools, such as the Soundshed Analysis Tool we created, to do calculations or create geographical data and images. The Soundshed Analysis Tool is derived from an <a href="http://www.acousticecology.org/docs/TWS_SPreAD_usersguide.pdf">earlier modeling script</a> “SPreAD-GIS” developed by environmental scientist Sarah Reed to measure the impact of noise on natural environments, such as national forests. That tool was itself adapted from SPreAD, or “the System for the Prediction of Acoustic Detectability,” a method the U.S. Forest Service devised in 1980 to <a href="https://www.cabdirect.org/cabdirect/abstract/19811878509">predict the impact of noise</a> on outdoor recreation. </p>
<p>The Soundshed Analysis Tool requires seven input variables, a study location and elevation data. Variables include the sound source height, frequency of the sound source, sound pressure level of the source, the measurement distance from the source, air temperature, relative humidity and the ambient sound pressure level of the study location. We gathered this information from a variety of sources: open-source elevation data, archaeological research, paleoclimatological research and historical climate data. We also gathered from the relevant literature the decibel levels of crowds, individuals and the conch trumpet instrument ancestral Puebloans used.</p>
<p>Once the input variables are entered, it takes the Soundshed tool less than 10 minutes to crunch through this complex math for every point on the landscape within two miles of the spot where the sound is produced. Our model then creates images that show where and how sound spreads across the landscape. This gives us a way to visualize the sounds people would have experienced as they moved through the landscape, going about their day. </p>
<h2>Who could hear what, where</h2>
<p>We focused on culturally relevant sounds and how they would have spread throughout the Chacoan landscape. These could be the voices of people, the sound of domestic animals like dogs and turkeys, the creation of stone tools or the sound of musical instruments. Within the American Southwest, these instruments include bone flutes, whistles, foot drums, copper bells and conch shell trumpets. </p>
<p>Soundshed maps reveal that a person standing at either of two neighboring great houses, Pueblo Alto and New Alto, located approximately 500 feet from each other, can hear a person shouting or speaking to a group at the other site. The patterns differ between the two maps because the terrain differs slightly between the two locations, and because the structures themselves block sound.</p>
<p>A third map models someone blowing a conch shell trumpet from immediately north of Casa Rinconada, a large ceremonial structure, at dawn on the summer solstice. </p>
<p>The sound spreads throughout the canyon, traveling to a number of mesa top shrines that often marked sacred locations and high points on the landscape. Perhaps audibility influenced the positioning of the shrines so ritual events occurring at Casa Rinconada could be heard? </p>
<p>Investigating how sound interacts with the built environment can reveal details about the importance of ritual. It can show us if sound was considered important by the ancestral Puebloan people, especially if shrines are consistently found in locations where people could hear rituals that were performed at a distance.</p>
<h2>The future of archaeoacoustics</h2>
<p>Our research presents a first step in the archaeoacoustic study of landscapes. Now we hope to expand our research by visiting Chaco Canyon to perform sound studies and record measurements in the field. We also plan to apply our model to other cultures, geographic areas and time periods. </p>
<p>Acoustic studies combined with other archaeological research contribute to a more holistic understanding of past cultures. The field has grown as more researchers expand their multidisciplinary pursuits, combining other fields of study with their archaeological approach. For example, advances in geography, physics, psychology, computer programming and other fields made our acoustic study possible. Previously, the study of archaeoacoustics at the landscape level had been out of reach due to technological limitations and a lack of tools. It is only now that computer processing power has caught up to our dreams. </p>
<p>Modeling tools like this one also offer the added benefit of allowing us to study what people heard at a site in any place or time without the need to travel to those locations. Instead, researchers can apply existing data found through a literature search, or measure the sound levels of noises or musical instruments to use as model inputs. This opens up new areas to be explored and studied.</p>
<p>Sound modeling can help researchers ask questions, and help everyone understand and relate to the ways that other people experienced their world. A sound model opens a new door into our understanding of the past.</p><img src="https://counter.theconversation.com/content/80861/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Kristy Primeau is currently employed by the New York State Department of Environmental Conservation (DEC). DEC data was used in the article "Soundscapes in the Past: Investigating Sound at the Landscape Level". </span></em></p><p class="fine-print"><em><span>David E. Witt is currently employed by the New York State Department of Environmental Conservation (DEC). DEC data was used in the article "Soundscapes in the Past: Investigating Sound at the Landscape Level". David is also currently a member of the Government Affairs Committee of the Society for American Archaeology.</span></em></p>We tend to think of archaeological sites as dead silent – empty ruins left by past cultures. But this isn’t how the people who lived in and used these sites would have experienced them.Kristy E. Primeau, Registered Professional Archaeologist, PhD Candidate, University at Albany, State University of New YorkDavid E. Witt, Research Associate, University at BuffaloLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/754342017-07-16T18:09:27Z2017-07-16T18:09:27ZWhy do human beings speak so many languages?<figure><img src="https://images.theconversation.com/files/178173/original/file-20170713-11780-17ip7zb.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">People currently speak 7,000 languages around the globe.</span> <span class="attribution"><span class="source">Michael Gavin</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span></figcaption></figure><p>The thatched roof held back the sun’s rays, but it could not keep the tropical heat at bay. As everyone at the research workshop headed outside for a break, small groups splintered off to gather in the shade of coconut trees and enjoy a breeze. I wandered from group to group, joining in the discussions. Each time, I noticed that the language of the conversation would change from an indigenous language to something they knew I could understand, Bislama or English. I was amazed by the ease with which the meeting’s participants switched between languages, but I was even more astonished by the number of different indigenous languages.</p>
<p>Thirty people had gathered for the workshop on this island in the South Pacific, and all except for me came from the island, called Makelua, in the nation of Vanuatu. They lived in 16 different communities and spoke 16 distinct languages. </p>
<p>In many cases, you could stand at the edge of one village and see the outskirts of the next community. Yet the residents of each village spoke completely different languages. According to recent work by my colleagues at the <a href="http://www.shh.mpg.de/180082/dlce-research-projects">Max Planck Institute for the Science of Human History</a>, this island, just 100 kilometers long and 20 kilometers wide, is home to speakers of <a href="http://www.soundcomparisons.com/#/en/Malakula/map/one/Lgs_All">perhaps 40 different indigenous languages</a>. Why so many? </p>
<p>We could ask this same question of the entire globe. People don’t speak one universal language, or even a handful. Instead, today our species collectively speaks over <a href="https://www.ethnologue.com/">7,000 distinct languages</a>. </p>
<p>And these languages are not spread randomly across the planet. For example, <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107623">far more languages</a> are found in tropical regions than in the temperate zones. The tropical island of New Guinea is home to over 900 languages. Russia, 20 times larger, has 105 indigenous languages. Even within the tropics, language diversity varies widely. For example, the 250,000 people who live on Vanuatu’s 80 islands speak 110 different languages, but in Bangladesh, a population 600 times greater speaks only 41 languages.</p>
<p>Why is it that humans speak so many languages? And why are they so unevenly spread across the planet? As it turns out, we have few clear answers to these fundamental questions about how humanity communicates.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=491&fit=crop&dpr=1 600w, https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=491&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=491&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=617&fit=crop&dpr=1 754w, https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=617&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/178175/original/file-20170713-9804-1u8y70s.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=617&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Why do some places have many languages, and others only a few?</span>
<span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:Dgernesiais_welcome_sign_St_Peter_Port_Guernsey.jpg">Man vyi</a>, <a class="license" href="http://creativecommons.org/licenses/by-sa/4.0/">CC BY-SA</a></span>
</figcaption>
</figure>
<h2>Some ideas, but little evidence</h2>
<p>Most people can easily brainstorm possible answers to these intriguing questions. They hypothesize that language diversity must be about history, cultural differences, mountains or oceans dividing populations, or old squabbles writ large – “we hated them, so we don’t talk to them.”</p>
<p>The questions also seem like they should be fundamental to many academic disciplines – linguistics, anthropology, human geography. But, starting in 2010, when <a href="https://www.nescent.org/science/awards_summary.php-id=255.html">our diverse team</a> of researchers from six different disciplines and eight different countries began to review what was known, we were shocked that only a dozen previous studies had been done, including one we ourselves completed on <a href="https://doi.org/10.1111/j.1466-8238.2011.00744.x">language diversity in the Pacific</a>.</p>
<p><a href="https://doi.org/10.1525/bio.2013.63.7.6">These prior efforts</a> all examined the degree to which different environmental, social and geographic variables correlated with the number of languages found in a given location. The results varied a lot from one study to another, and no clear patterns emerged. The studies also ran up against many methodological challenges, the biggest of which centered on the old statistical adage – correlation does not equal causation.</p>
<p>We wanted to know the exact steps that led to so many languages forming in certain places and so few in others. But previous work provided few robust theories on the specific processes involved, and the methods used did not get us any closer to understanding the causes of language diversity patterns.</p>
<p>For example, previous studies pointed out that <a href="https://doi.org/10.1371/journal.pone.0107623">at lower latitudes</a> languages are often spoken across smaller areas than at higher latitudes. You can fit more languages into a given area the closer you get to the equator. But this result does not tell us much about the processes that create language diversity. Just because a group of people crosses an imaginary latitudinal line on the map doesn’t mean they’ll automatically divide into two different populations speaking two different languages. Latitude might be correlated with language diversity, but it certainly did not create it. </p>
<h2>Can a simple model predict reality?</h2>
<p>A better way to identify the causes of particular patterns is to simulate the processes we think might be creating them. The closer the model’s products are to the reality we know exists, the greater the chances are that we understand the actual processes at work. </p>
<p>Two members of our group, ecologists <a href="https://scholar.google.com/citations?user=EHbuZpYAAAAJ">Thiago Rangel</a> and <a href="http://viceroy.eeb.uconn.edu/Colwell/">Robert Colwell</a>, had developed this <a href="https://doi.org/10.1098/rstb.2010.0293">simulation modeling technique</a> for their studies of <a href="https://doi.org/10.1086/521315">species diversity patterns</a>. But no one had ever used this approach to study the diversity of human populations.</p>
<p><a href="https://doi.org/10.1111/geb.12563">We decided to explore its potential</a> by first building a simple model to test the degree to which a few basic processes might explain language diversity patterns in just one part of the globe, the continent of Australia. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=396&fit=crop&dpr=1 600w, https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=396&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=396&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=498&fit=crop&dpr=1 754w, https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=498&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/177774/original/file-20170711-14452-167eqee.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=498&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Map of Australia’s 406 languages before contact with Europeans.</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1111/geb.12563">Claire Bowern, Yale University, with support from the National Science Foundation BCS-1423711</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>Our colleague <a href="https://theconversation.com/profiles/claire-bowern-1098">Claire Bowern</a>, a linguist at Yale University, created a map that shows the diversity of aboriginal languages – a total of 406 – found in Australia prior to contact with Europeans. There were far more languages in the north and along the coasts, with relatively few in the desert interior. We wanted to see how closely a model, based on a simple set of processes, could match this geographic pattern of language diversity. </p>
<p>Our simulation model made only three basic assumptions. First, populations will move to fill available spaces where no one else lives.</p>
<p>Second, rainfall will limit the number of people that can live in a place; Our model assumed that people would live in higher densities in areas where it rained more. <a href="http://onlinelibrary.wiley.com/store/10.1111/geb.12563/asset/supinfo/geb12563-sup-0002-suppinfo2.pdf?v=1&s=b92a15ea48c3a0d9f85c9bd2e3731a1162917e89">Annual precipitation varies widely in Australia</a>, from over three meters in the northeastern rainforests to one-tenth of a meter in the Outback. </p>
<p>Third, we assumed that human populations have a maximum size. <a href="http://dx.doi.org/10.1037/1089-2699.12.1.7">Ideal group size</a> is a trade-off between benefits of a larger group (wider selection of potential mates) and <a href="https://doi.org/10.1016/0278-4165(90)90009-3">costs</a> (keeping track of unrelated individuals). In our model, when a population grew larger than a maximum threshold – set randomly based on a global distribution of hunter-gatherer population sizes – it divided into two populations, each speaking a distinct language.</p>
<p>We used this model to simulate language diversity maps for Australia. In each iteration, an initial population sprung up randomly somewhere on the map and began to grow and spread in a random direction. An underlying rainfall map determined the population density, and when the population size hit the predetermined maximum, the group divided. In this way, the simulated human populations grew and divided as they spread to fill up the entire Australian continent.</p>
<p>Our simple model didn’t include any impact from contact among groups, changes in subsistence strategies, the effects of the borrowing of cultural ideas or components of language from nearby groups, or many other potential processes. So, we expected it would fail miserably. </p>
<p>Incredibly, the model produced 407 languages, just one off from the actual number.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=570&fit=crop&dpr=1 600w, https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=570&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=570&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=716&fit=crop&dpr=1 754w, https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=716&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/177760/original/file-20170711-26274-z0c5mn.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=716&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">The simulation model predicts virtually the same number of languages (407) as were observed in reality (406).</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1111/geb.12563">Gavin et al DOI: 10.1111/geb.12563</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>The simulated language maps also show more languages in the north and along the coasts, and less in the dry regions of central Australia, mirroring the geographic patterns in observed language diversity.</p>
<p>And so for the continent of Australia it appears that a small number of factors – limitations rainfall places on population density and limits on group size – might explain both the number of languages and much of the variation in how many languages are spoken in different locations. </p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=430&fit=crop&dpr=1 600w, https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=430&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=430&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=540&fit=crop&dpr=1 754w, https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=540&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/178176/original/file-20170713-5760-cvw5nj.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=540&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">A simulation model based on a few simple processes predicts much of the geographic variation in language diversity in Australia.</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1111/geb.12563">Gavin et al DOI: 10.1111/geb.12563</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<h2>Applying the model elsewhere</h2>
<p>But we suspect that the patterns of language diversity in other places may be shaped by different factors and processes. In other locations, such as Vanuatu, rainfall levels do not vary as widely as in Australia, and population densities may be shaped by other environmental conditions.</p>
<p>In other instances, contact among human groups probably reshaped the landscape of language diversity. For example, the <a href="https://doi.org/10.1126/science.1078208">spread of agricultural groups</a> speaking Indo-European or Bantu languages may have changed the structure of populations and the languages spoken across huge areas of Europe and Africa, respectively.</p>
<p>Undoubtedly, a wide variety of social and environmental factors and processes have contributed to the patterns in language diversity we see across the globe. In some places topography, climate or the density of key natural resources may be more critical; in others the history of warfare, political organization or the subsistence strategies of different groups may play a bigger role in shaping group boundaries and language diversity patterns. What we have established for now is a template for a method that can be used to uncover the different processes at work in each location.</p>
<p>Language diversity has played a key role in shaping the interactions of human groups and the history of our species, and yet we know surprisingly little about the factors shaping this diversity. We hope other scientists will become as fascinated by the geography of language diversity as our research group is and join us in the search for understanding why humans speak so many languages.</p><img src="https://counter.theconversation.com/content/75434/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Funding from the National Evolutionary Synthesis Center, the Max Planck Institute for the Science of Human History, and the National Science Foundation to Michael Gavin (BCS-1660465) and Claire Bowern (BCS-1423711) supported the research discussed in this article.</span></em></p>There’s little research into origins of the geographic patterns of language diversity. A new model exploring processes that shaped Australia’s language diversity provides a template for investigators.Michael Gavin, Associate Professor of Human Dimensions of Natural Resources, Colorado State UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/757422017-05-02T02:35:30Z2017-05-02T02:35:30ZHow to boil down a pile of diverse research papers into one cohesive picture<figure><img src="https://images.theconversation.com/files/167402/original/file-20170501-17304-nalnmm.jpg?ixlib=rb-1.1.0&rect=0%2C58%2C2114%2C1411&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Can an algorithmic method for analyzing published research help zero in on reality?</span> <span class="attribution"><a class="source" href="https://www.shutterstock.com/image-photo/shelves-old-scientific-journals-202908463">Sergei25/Shutterstock.com</a></span></figcaption></figure><p>From social to natural and applied sciences, overall scientific output has been growing worldwide – it <a href="http://blogs.nature.com/news/2014/05/global-scientific-output-doubles-every-nine-years.html">doubles every nine years</a>.</p>
<p>Traditionally, researchers solve a problem by conducting new experiments. With the ever-growing body of scientific literature, though, it is becoming more common to make a discovery based on the vast number of already-published journal articles. Researchers synthesize the findings from previous studies to develop a more complete understanding of a phenomenon. Making sense of this explosion of studies is critical for scientists not only to build on previous work but also to push research fields forward.</p>
<p>My colleagues <a href="http://mitsloan.mit.edu/faculty-and-research/faculty-directory/detail/?id=3547">Hazhir Rahmandad</a> and <a href="https://pwp.gatech.edu/kamran-paynabar/">Kamran Paynabar</a> and I have developed a new, more robust way to pull together all the prior research on a particular topic. In a five-year joint <a href="http://jalali.mit.edu/gma">project</a> between MIT and Georgia Tech, we worked to create a new technique for research aggregation. Our recently published paper in PLOS ONE introduces a flexible method that <a href="http://dx.doi.org/10.1371/journal.pone.0175111">helps synthesize findings from prior studies</a>, even potentially those with diverse methods and diverging results. We call it <a href="https://en.wikipedia.org/wiki/Generalized_model_aggregation">generalized model aggregation</a>, or GMA.</p>
<h2>Pulling it all together</h2>
<p><a href="http://researchguides.ebling.library.wisc.edu/c.php?g=293229&p=1953452">Narrative reviews</a> of the literature have long been a key component of scientific publications. The need for more comprehensive approaches has led to the emergence of two other very useful methods: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3024725/">systematic review and meta-analysis</a>. </p>
<p>In a systematic review, an author finds and critiques all prior studies around a similar research question. The idea is to bring a reader up to speed on the current state of affairs around a particular research topic.</p>
<p>In a meta-analysis, researchers go one step further and synthesize the findings quantitatively. Essentially, it takes a weighted average of the findings of several studies on one topic. Pooling results from multiple studies is meant to generate a more reliable finding than that of any single study. This is crucially helpful when prior studies reported diverging findings and conclusions. And the rise in the publications of meta-analysis has shot up over the last decade, underscoring their importance across research communities.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=354&fit=crop&dpr=1 600w, https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=354&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=354&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=444&fit=crop&dpr=1 754w, https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=444&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/163958/original/image-20170404-5725-g8zkku.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=444&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Publications of meta-analyses are on the rise, based on Web of Science search results for articles that included the term ‘meta-analysis’ in their title.</span>
<span class="attribution"><span class="source">Mohammad S. Jalali</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>Meta-analysis has been helpful in increasing our understanding of many scientific problems. But it has some challenges. <a href="https://us.sagepub.com/en-us/nam/methods-of-meta-analysis/book240589">A typical meta-analysis</a> combines just one explanatory variable (that is, a treatment controlled by the experimenter) and one response variable (for instance, a health outcome). Also, a researcher has to be very careful not to lump apples and oranges together in the meta-analysis. She must be selective and make sure to include only previous work that shared a very similar study design.</p>
<p>Here is where our simple and flexible generalized model aggregation method comes in. Using GMA, the prior studies do not necessarily need to have the same study design or method. They can also have different explanatory variables. As long as they are all answering a similar research question, GMA can synthesize them.</p>
<h2>Pooling findings from across a field</h2>
<p>Consider an example from the health literature. Obesity and nutrition researchers need reliable equations that estimate basal metabolic rate (BMR) – the amount of energy the human body spends at complete rest. Understanding BMR has big implications for real-world questions of weight management.</p>
<p>Researchers often estimate BMR as a function of different attributes: age, height, weight, fat mass and fat-free mass. The challenge is that current publications in research journals <a href="https://doi.org/10.1038/ijo.2012.218">provide over 200 such equations</a> estimated for different samples and age groups. These equations also include different subsets of those attributes.</p>
<p>For example, one of these equations included weight and age, but another included only fat-free mass. Another equation considered the impact of all these attributes, but the sample size was too small to make it reliable. More interestingly, and confusingly, there have been several studies with similar samples and variables but they have reported very different equations to explain the relationships.</p>
<p>So which equations are you going to choose to accurately estimate BMR? How do you ensure that your selected equation is more reliable than the rest? </p>
<p>In order to address these questions, <a href="http://journals.plos.org/plosone/article/file?type=supplementary&id=info:doi/10.1371/journal.pone.0175111.s001">we identified 27 published BMR equations</a> for white males from published studies. Then we used GMA to aggregate them into a single equation, which we called a meta-model.</p>
<p>Through validation tests, we showed that our meta-model is more precise than any of the prior equations for estimating BMR. It also can deal with a logarithmic relationship between two variables – something not captured by any of the original 27 linear equations.</p>
<p>We tested our method by putting it up against more complex situations. What if all the equations we aggregate using GMA are actually off the mark? Would GMA still get close to what is really going on?</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=324&fit=crop&dpr=1 600w, https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=324&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=324&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=407&fit=crop&dpr=1 754w, https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=407&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/164555/original/image-20170408-29386-lwhnmr.PNG?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=407&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">The meta-model (on the right) relies only on reported information from the two incorrect models in the middle – not their observed data or the true data. And it is much closer to reality (on the left) than either incorrect model.</span>
<span class="attribution"><a class="source" href="https://doi.org/10.1371/journal.pone.0175111">Rahmandad et al, DOI: 10.1371/journal.pone.0175111</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>To investigate, we imagined two researchers coming up with two different linear equations to describe what they did not realize is actually a nonlinear phenomenon. The findings of the two researchers are far from reality. But again, our meta-model provided an extremely close estimate of reality – even when aggregating these two incorrect and biased models.</p>
<h2>How GMA gets at the truth</h2>
<p>So how does it all work? There is no magic here. In fact, the <a href="https://en.wikipedia.org/wiki/Generalized_model_aggregation">intuition behind GMA is simple</a>, which lets researchers with no extensive statistical background use it. </p>
<p>Broadly, each previous empirical study is an attempt to estimate an underlying reality. Let’s call this the “true model.” And it is unknown to us; whatever is actually driving the phenomenon under investigation is nature’s secret. The empirical studies report relevant information about the true model, even if they are biased or incomplete. </p>
<p>Generalized model aggregation uses computer simulations to replicate prior studies. This time, though, the simulated studies attempt to estimate a meta-model instead of the true model (that is, reality). </p>
<p>We feed the empirical studies’ reported estimates into the simulation. The flexibility of the GMA allows us to also use any other additional information about the underlying true model, too – such as the relationships among the variables or the quality of empirical studies’ estimates. This extra information helps increase the reliability of GMA estimates.</p>
<p>The GMA algorithm carefully applies the same sample characteristics to each previous study and replicates their same method. Then it compares the outcomes of the simulated studies with the actual results of the empirical studies, trying to find the closest match. Through this matching process, GMA estimates the meta-model.</p>
<p>If the simulated and actual outputs match, the meta-model may be a good representation of the true model – that is, by running a bunch of studies through the GMA algorithm, we are able to tease out a closer approximation of how the phenomenon in question actually works. </p>
<h2>Wide range of applications for GMA</h2>
<p>In our paper, we <a href="http://dx.doi.org/10.1371/journal.pone.0175111">discussed a wide range of examples</a>, from health to climate change and environmental sciences, that can benefit from generalized model aggregation. Using GMA to synthesize prior findings into a coherent meta-model can increase the accuracy of aggregation. </p>
<p>In the current replicability crisis, GMA can help not only identify studies that are reproducible, but also distinguish reliable findings from less robust ones. </p>
<p>We reported <a href="http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0175111#pone.0175111.s001">all the steps of our analysis</a> for further replication. A recipe for using GMA and its codes, along with instructions, is also <a href="http://jalali.mit.edu/gma">publicly available</a>.</p>
<p>We hope that GMA can extend the reach of current research synthesis efforts to many new problems. GMA can help us understand the bigger picture of phenomena by aggregating their parts. Consider a puzzle with its pieces scattered about; the overall picture is revealed only when the pieces have been put together.</p><img src="https://counter.theconversation.com/content/75742/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Mohammad S. Jalali does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.</span></em></p>Researchers need to be able to draw conclusions based on previously published studies in their field. A new aggregation method synthesizes prior findings and may help reveal more of the big picture.Mohammad S. Jalali, Research Faculty, MIT Sloan School of ManagementLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/686412016-11-16T13:26:50Z2016-11-16T13:26:50ZRed, yellow, pink and green: How the world’s languages name the rainbow<figure><img src="https://images.theconversation.com/files/146234/original/image-20161116-13506-10ayrig.jpg?ixlib=rb-1.1.0&rect=307%2C71%2C3877%2C2628&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">How many colors in your language's rainbow?</span> <span class="attribution"><a class="source" href="http://www.shutterstock.com/pic-130215719.html">Eye image via www.shutterstock.com.</a></span></figcaption></figure><p>It is striking that English color words come from many sources. Some of the more exotic ones, like “vermilion” and “chartreuse,” were borrowed from French, and are named after the color of a particular item (a type of mercury and a liquor, respectively). But even our words “black” and “white” didn’t originate as color terms. “Black” comes from a word meaning “burnt,” and “white” comes from a word meaning “shining.” </p>
<p>Color words vary a lot across the world. Most languages have between two and 11 basic color words. English, for example, has the full set of 11 basic colors: black, white, red, green, yellow, blue, pink, gray, brown, orange and purple. In a 1999 survey by linguists <a href="http://www1.icsi.berkeley.edu/%7Ekay/">Paul Kay</a> and <a href="http://terralingua.org/">Luisa Maffi</a>, languages were <a href="http://wals.info/feature/133A#2/22.3/153.7">roughly equally distributed</a> between the basic color categories that they tracked.</p>
<p>In languages with fewer terms than this – such as the Alaskan language Yup'ik with its five terms – the range of a word expands. For example, for languages without a separate word for “orange,” hues that we’d call “orange” in English might be named by the same color that English speakers would call “red” or “yellow.” We can think of these terms as a system that together cover the visible spectrum, but where individual terms are centered on various parts of that spectrum.</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=600&fit=crop&dpr=1 600w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=600&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=600&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=754&fit=crop&dpr=1 754w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=754&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/146097/original/image-20161115-31138-1hotkg5.png?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=754&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Illustration of a color system with 20 hues.</span>
<span class="attribution"><a class="source" href="https://commons.wikimedia.org/wiki/File:MunsellColorWheel.svg">Thenoizz</a>, <a class="license" href="http://creativecommons.org/licenses/by/4.0/">CC BY</a></span>
</figcaption>
</figure>
<p>Does that mean that speakers of languages with fewer words for colors see less color? No, just as English speakers can see the difference between the “blue” of the sky and the “blue” of an M&M. Moreover, if language words limited our perception of color, words wouldn’t be able to change; speakers would not be able to add new distinctions. </p>
<p>My colleague <a href="http://hannahhaynie.com/">Hannah Haynie</a> and <a href="http://campuspress.yale.edu/clairebowern">I</a> were interested in how color terms might change over time, and in particular, in how color terms might change as a system. That is, do the words change independently, or does change in one word trigger a change in others? <a href="http://doi.org/10.1073/pnas.1613666113">In our research, recently published in the journal PNAS</a>, we used a computer modeling technique more common in biology than linguistics to investigate typical patterns and rates of color term change. Contrary to previous assumptions, what we found suggests that color words aren’t unique in how they evolve in language.</p>
<h2>Questioning common conceptions on colors</h2>
<p>Previous work (such as by anthropological linguists <a href="http://www.ucpress.edu/op.php?isbn=9780520076358">Brent Berlin and Paul Kay</a>) has suggested that the order in which new color terms are added to a language is largely fixed. Speakers begin with two terms – one covering “black” and dark hues, the other covering “white” and light hues. There are plenty of languages with only two color terms, but in all cases, one of the color terms is centered on “black” and the other on “white.”</p>
<p>When a language has three terms, the third is one is almost always centered on hues that English speakers would call “red.” There are no languages with three color terms where the named colors are centered on black, white and light green, for example. If a language has four color terms, they will be black, white, red and either yellow or green. In the next stage, both yellow and green are present, while the next color terms to be added are blue and brown (in that order). Cognitive scientists and linguists such as <a href="http://lclab.berkeley.edu/papers/tics2-published.pdf">Terry Regier</a> have argued that these particular parts of the color spectrum are most noticeable for people.</p>
<p>Berlin and Kay also hypothesized that language speakers don’t lose color terms. For example, once a language has a distinction between “red-like” hues (such as blood) and “yellow-like” ones (such as bananas), they wouldn’t collapse the distinction and go back to calling them all by the same color name again.</p>
<p>This would make color words quite different from other areas of language change, where words come and go. For example, words can <a href="http://dx.doi.org/10.1016/B0-08-044854-2/01105-6">change their meaning</a> when they are used metaphorically, but over time the metaphoric meaning becomes basic. They can broaden or narrow their meanings; for example, English “starve” used to mean “die” (generally), not “die of hunger,” as it primarily means now. “Starve” has also acquired metaphorical meanings.</p>
<p>That there’s something unique about the stability of color concepts is an assumption we wanted to investigate. We were also interested in patterns of color naming and where color terms come from. And we wanted to look at the rates of change – that is, if color terms are added, do speakers tend to add lots of them? Or are the additions more independent, with color terms added one at a time?</p>
<figure class="align-center zoomable">
<a href="https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=400&fit=crop&dpr=1 600w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=400&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=400&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=503&fit=crop&dpr=1 754w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=503&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/146236/original/image-20161116-13506-15zf4h7.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=503&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Everyone sees them all, but languages divide them into different color terms.</span>
<span class="attribution"><a class="source" href="http://www.shutterstock.com/pic.mhtml?id=300363659&src=lb-29877982">Colors image via www.shutterstock.com.</a></span>
</figcaption>
</figure>
<h2>Modeling how a language tree grew</h2>
<p>We tested these ideas using color words in Australian Aboriginal languages. We worked with Australian languages (rather than European or other languages) for several reasons. Color demarcations vary in Indo-European, but the number of colors in each language is pretty similar; the ranges differ but the number of colors don’t vary very much. Russian has two terms that cover the hues that English speakers call “blue,” but Indo-European languages have many terms.</p>
<p>In contrast, Australian languages are a lot more variable, ranging from systems like Darkinyung’s, with just two terms (<em>mining</em> for “black” and <em>barag</em> for “white”), to languages like Kaytetye, where there are at least eight colors, or Bidyara with six. That variation gave us more points of data. Also, there are simply a lot of languages in Australia: Of the more than 400 spoken at the time of European settlement, we had color data for 189 languages of the Pama-Nyungan family, from the <a href="http://pamanyungan.net/chirila">Chirila</a> <a href="https://scholarspace.manoa.hawaii.edu/bitstream/handle/10125/24685/bowern.pdf">database</a> of Australian languages.</p>
<p>In order to answer these questions, we used techniques originally developed in biology. Phylogenetic methods use computers to study the remote past. In brief, we use probability theory, combined with a family tree of languages, to make a model of what the history of the color words might have been.</p>
<p>First, we construct a tree that shows how languages are related to one another. The <a href="https://en.wikipedia.org/wiki/Pama_nyungan">contemporary Pama-Nyungan languages</a> are all descended from a single ancestor language. Over 6,000 years, Proto-Pama-Nyungan split into different dialects, and those dialects turned into different languages: about 300 of them at the time of the European settlement of Australia. Linguists usually show those splits on a family tree diagram. </p>
<figure class="align-left zoomable">
<a href="https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=1000&fit=clip"><img alt="" src="https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=237&fit=clip" srcset="https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=842&fit=crop&dpr=1 600w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=842&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=842&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=1059&fit=crop&dpr=1 754w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=1059&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/145959/original/image-20161115-30749-1mlxf6a.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=1059&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px"></a>
<figcaption>
<span class="caption">Family tree of Australian languages with their color terms and reconstructions of color systems for major subgroups.</span>
<span class="attribution"><span class="source">Haynie and Bowern (2016): Figure 3</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span>
</figcaption>
</figure>
<p>Then, we build a model for that tree of how different features (in this case, color terms) are gained or lost, and how quickly those features might change. This is a complicated problem; we estimate likely reconstructions, evaluate that model for how well it fits our hypotheses, tweak the model parameters a bit to produce a different set of results, score that model, and so on. We repeat this many times (millions of times, usually) and then take a random sample of our estimates. This method is due originally to evolutionary biologists <a href="http://www.evolution.reading.ac.uk/">Mark Pagel and Andrew Meade</a>.</p>
<p>Estimates that are very consistent (like reconstructing terms for “black,” “white” and “red”) are highly likely to be good reconstructions. Other forms were consistently reconstructed as absent (for instance, “blue” from many parts of the tree). A third set of forms were more variable, such as “yellow” and “green” in some parts of the tree; in that case, we have some evidence they were present, but it’s unclear. </p>
<p>Our results supported some of the previous findings, but questioned others. In general, our findings backed up Berlin and Kay’s ideas about the sequential adding of terms, in the order they proposed. For the most part, our color data showed that Australian languages also show the patterns of color term naming that have been proposed elsewhere in the world; if there are three named colors, they will be black, white and red (not, for example, black, white and purple). But we show that it is most likely that Australian languages have lost color terms, as well as gained them. This contradicts 40 years of assumptions of how color terms change – and makes color words look a lot more like other words. </p>
<p>We also looked at where the color words themselves came from. Some were old in the family, and seemed to go back as color terms. Others relate to the environment (like <em>tyimpa</em> for “black” in Yandruwandha, which is related to a word which means “ashes” in other languages) or to other color words (compare Yolŋu <em>miku</em> for “red,” which also sometimes means simply “colored”). So Australian languages show similar sources of color terms to languages elsewhere in the world: color words change when people draw analogies with items in their environment.</p>
<p>Our research shows the potential for using language change to study areas of science that have previously been more closely examined by fields such as psychology. Psychologists and psycholinguists have described how constraints from our vision systems lead to particular areas of the color spectrum being named. We show that these constraints apply to color loss as well as gain. Just as it’s a lot easier to see a chameleon when it moves, language change makes it possible to see how words are working.</p><img src="https://counter.theconversation.com/content/68641/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>Claire Bowern receives funding from the National Science Foundation and the Australian Research Council. She is Vice-President of the Endangered Language Fund. </span></em></p>New research investigates how people sequentially add new color terms to languages over time – and the results hold surprises about assumptions linguists have made for 40 years.Claire Bowern, Associate Professor of Linguistics, Yale UniversityLicensed as Creative Commons – attribution, no derivatives.tag:theconversation.com,2011:article/609952016-06-16T18:01:20Z2016-06-16T18:01:20ZDisrupting pro-ISIS online ‘ecosystems’ could help thwart real-world terrorism<figure><img src="https://images.theconversation.com/files/126867/original/image-20160616-19932-1k1aa25.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=496&fit=clip" /><figcaption><span class="caption">Schematic diagram of an aggregate made up of linked users, with the mathematical equation that describes this online pro-ISIS ecology.</span> <span class="attribution"><span class="source">Neil Johnson</span>, <a class="license" href="http://creativecommons.org/licenses/by-nd/4.0/">CC BY-ND</a></span></figcaption></figure><p>Supporters of the Islamic State, or ISIS, around the world gather online, becoming members of virtual communities in much the same way any of us might join online groups focused on some common interest. The videos, audio messages, letters, chatter and know-how that they then share are much more sinister than typical online hobbies, though. They <a href="https://www.whitehouse.gov/blog/2016/06/12/president-obama-tragic-shooting-orlando">may ultimately inspire terrorist acts</a> by individuals who have no prior history of extremism, no formal cell membership, no direct links to leadership.</p>
<p>How does this online support for ISIS manage to not just survive but thrive – even in the face of plenty of online anti-ISIS opposition?</p>
<p>The importance and urgency of this question couldn’t be greater, particularly given the uncertainties surrounding recent terrorist <a href="http://www.nytimes.com/2015/07/22/us/chattanooga-gunman-mohammod-abdulazeez.html?_r=0">attacks</a> by <a href="https://en.wikipedia.org/wiki/List_of_terrorist_incidents_linked_to_ISIL">“inspired” individuals</a> in the United States, as in <a href="http://www.nytimes.com/2015/12/07/us/politics/president-obama-terrorism-threat-speech-oval-office.html">San Bernardino</a> and <a href="https://theconversation.com/us/topics/orlando-shooting-2016">Orlando</a>.</p>
<p>My colleagues and I at the University of Miami’s <a href="http://www.as.miami.edu/research/research-news/connecting-the-dots-and-finding-the-patterns-in-big-data-.html">Complexity Initiative</a> decided to tackle this question of what makes pro-ISIS online support tick. <a href="http://science.sciencemag.org/content/352/6292/1459">By intensively analyzing online data</a> we’ve been collecting continuously since 2014, our goal was to decode the online “ecology” of ISIS supporters. Could we even go a step further and use what we learned to make accurate predictions about real-world attacks?</p>
<h2>Online fieldwork: hunting out the data</h2>
<p>The key challenge we faced as researchers was how to obtain the data. Many social media sites quickly shut down any pro-ISIS activity, meaning we found negligible amounts of pro-ISIS activity on Facebook, for instance. </p>
<p>But when we looked at other social media sites around the world, we found that some were slower to shut down pro-ISIS activity – probably because finding such aggregates and shutting them down requires significant amounts of resources and time. We assembled a multi-disciplinary team with expertise across languages.</p>
<p>After many dead ends, we found that the social media site <a href="https://vk.com">VKontakte</a> was ideal for our pro-ISIS analysis. It is the most popular online social networking service within central Europe and has more than 350 million users worldwide. Being based physically in Russia, it has a high concentration of users of Chechen origin in the Caucasus region, near ISIS’ main area of influence in the Levant. And ISIS is known to have spread significant amounts of propaganda <a href="http://linkis.com/dmFgu">among the Russian-speaking population</a>.</p>
<p>We started off by manually identifying relevant pro-ISIS narratives using hashtags in multiple languages – for example, expressions of support or positive references to particular ISIS actions. Then we’d trace them to the underlying online “aggregates.” An aggregate is an ad hoc virtual community that anyone can create on social media sites – imagine a group on Facebook focused on a particular sports team. Users can become members if they’re fans, and then share significant information and material about that team.</p>
<p>The same applies for pro-ISIS aggregates, but now in support of ISIS rather than a sports team. To be included on our pro-ISIS list, an aggregate had to explicitly express its support for ISIS, publish ISIS-related news or propaganda and call for jihad in the name of ISIS.</p>
<p>We then developed software Application Programming Interfaces (APIs) that expanded our list of aggregates by means of automated searches on hashtags or relevant words. For example, we might have initially found an aggregate called ILiveForISIS manually. We’d scour ILiveForISIS for keywords and content that the APIs could then use to search and uncover new aggregates. </p>
<p>When the APIs eventually started turning up ILiveForISIS together with other pro-ISIS aggregates already on our list, we would know that we were reaching closure. At that stage, while not perfect, we were confident that we had captured a high proportion of what actually existed online.</p>
<p>Eventually we found 196 pro-ISIS aggregates involving 108,086 individual followers between January 1 and August 31, 2015. Membership ebbed and flowed each day; on the most active day, the total number of follower links reached 134,857.</p>
<p>This process of data collection, analysis and modeling provided us with a living road map of online pro-ISIS activity. Next, we needed to develop a mathematical theory for pro-ISIS online support that was in good quantitative agreement with the raw online data. </p>
<h2>An online ecosystem of pro-ISIS sentiment</h2>
<p><a href="http://science.sciencemag.org/content/352/6292/1459">Our research revealed an ultrafast ecology of self-organized aggregates</a> that share operational information and propaganda, and whose rapid evolution drives the online support.</p>
<p>During a typical period of a few weeks, aggregates would appear and disappear sporadically, with their total number changing relatively slowly. Over a particular set of months, however, we found that the rate at which new aggregates appeared started to increase very rapidly – in technical terms, it diverged. Its peak coincided almost exactly with the unexpected onset of real-world attacks on Kobane in Syria by ISIS fighters.</p>
<p>Curiously, we had found a similar divergence in the rate at which new aggregates appeared just before the onset of another unexpected burst of events (this time, non-ISIS civil unrest events) in Brazil in 2013. This suggested to us that an explosion in the rate at which new aggregates appear in the online world can act as an indicator of conditions being right for a burst of attacks in the real world.</p>
<figure class="align-center ">
<img alt="" src="https://images.theconversation.com/files/126837/original/image-20160616-19949-qfbhi8.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&fit=clip" srcset="https://images.theconversation.com/files/126837/original/image-20160616-19949-qfbhi8.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=600&h=387&fit=crop&dpr=1 600w, https://images.theconversation.com/files/126837/original/image-20160616-19949-qfbhi8.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=600&h=387&fit=crop&dpr=2 1200w, https://images.theconversation.com/files/126837/original/image-20160616-19949-qfbhi8.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=600&h=387&fit=crop&dpr=3 1800w, https://images.theconversation.com/files/126837/original/image-20160616-19949-qfbhi8.jpg?ixlib=rb-1.1.0&q=45&auto=format&w=754&h=486&fit=crop&dpr=1 754w, https://images.theconversation.com/files/126837/original/image-20160616-19949-qfbhi8.jpg?ixlib=rb-1.1.0&q=30&auto=format&w=754&h=486&fit=crop&dpr=2 1508w, https://images.theconversation.com/files/126837/original/image-20160616-19949-qfbhi8.jpg?ixlib=rb-1.1.0&q=15&auto=format&w=754&h=486&fit=crop&dpr=3 2262w" sizes="(min-width: 1466px) 754px, (max-width: 599px) 100vw, (min-width: 600px) 600px, 237px">
<figcaption>
<span class="caption">Example of the aggregate size (i.e., number of members of an aggregate) as time increases, for three example aggregates. Below is the equation we derived that describes these aggregate dynamics.</span>
</figcaption>
</figure>
<p>We also found that the evolution of this aggregate ecosystem follows a rather precise mathematical form. As the size – the number of members – of each aggregate evolved over time, it produced a familiar shark-fin shape. It’s the same shark-fin shape we find in the natural sciences when groups of interacting objects (particles, animals) follow a <a href="http://dx.doi.org/10.1016/j.cub.2006.02.042">process of coalescence and fragmentation</a>.</p>
<p>In other words, these groups of ISIS supporters come together (coalescence) and break up (fragmentation) like fish in schools or birds in a flock might. There’s one difference, though. When they break up, they fragment completely because some external, anti-ISIS entity or online moderator has shut them down. That’s why you see the abrupt drop-off like the edge of a shark fin.</p>
<h2>From math model to real-world disruption</h2>
<p>These pro-ISIS aggregates are leaderless, self-organized entities that change rapidly over time. But now that we’ve identified a rather precise mathematical equation that describes their evolution, we can start to think about how to intervene.</p>
<p>To start, the main implication of our work is that once you identify the aggregates, you have your hand on the pulse of the entire organization. Instead of having to sift through millions of internet users and tracking specific individuals, an anti-ISIS agency can simply follow the relatively small number of aggregates to gauge what is happening in terms of hard-core global ISIS support.</p>
<p>As these ISIS supporters coalesce over time into aggregates, anti-ISIS agencies have an opportunity to step in and break up small aggregates before they develop into larger, potentially powerful ones. One concern is that if anti-ISIS agencies – be they <a href="http://www.bbc.com/news/world-europe-33220037">government-based</a>, private hackers or online moderators – aren’t active enough in their countermeasures, pro-ISIS support could quickly grow from a number of smaller aggregates into one superaggregate.</p>
<p>Our model also warns that if aggregate shutdown rates drop below a certain critical value, any piece of pro-ISIS material will then be able to spread globally across the internet. A low shutdown rate allows an aggregate time to internally develop ideas, content and plans. Then when it’s eventually shut down and the members scatter, they take this content with them to the new aggregates they eventually join.</p>
<p>Our analysis of the data suggests that the rate of creation of aggregates proliferates in a specific mathematical way preceding bursts of real-world attacks. This means monitoring such proliferation can help predict when conditions are favorable for future real-world attacks. If anti-ISIS trackers are on the lookout, a big online surge can therefore be an early warning that could be used along with additional intelligence to thwart a planned terrorist action.</p>
<p>But perhaps most importantly in light of the massacre in Orlando, our research also suggests that any online “lone wolf” actor will truly be alone only for short periods of time. Since we observed that people with serious interest in ISIS online tend to coalesce into these aggregate groups, any such lone wolf was likely either recently in an aggregate or will soon be in one.</p>
<p>As for the future, even if pro-ISIS support moves onto the <a href="https://theconversation.com/securing-web-browsing-protecting-the-tor-network-56840">dark net</a> where open access is not possible, or if a new entity beyond ISIS emerges, our results should still be relevant. The mechanism we’ve identified and theory we’ve developed appear to capture a basic process of human online behavior. Going forward, it can be used to help describe not only pro-ISIS online activity, but also that of any future extremist group or organization.</p><img src="https://counter.theconversation.com/content/60995/count.gif" alt="The Conversation" width="1" height="1" />
<p class="fine-print"><em><span>This research was carried out by members of the new Complexity Initiative in the College of Arts and Sciences at the University of Miami. Neil Johnson received partial support for preliminary work from Intelligence Advanced Research Projects Activity (IARPA) under grant D12PC00285 and recent funding under National Science Foundation (NSF) grant CNS1500250 and Air Force (AFOSR) grant 16RT0367.</span></em></p>A new mathematical model of ISIS supporters’ online behavior provides insights into how cyberactivity relates to real-world attacks.Neil Johnson, Professor of Physics, University of MiamiLicensed as Creative Commons – attribution, no derivatives.