Statistical ecology is a new scientific discipline that has grown rapidly in response to changes in the global environment. The Conversation Africa’s energy and environment editor Ozayr Patel asked Sanet Hugo, from the Centre for Statistics in Ecology, the Environment and Conservation, how this has affected African scientists.
What is statistical ecology?
Statistical methods have been used for more than a century to analyse the environment, wildlife and species. But ecological data today have reached unprecedented levels of detail, complexity and size.
Scientific “big data” spur new developments in statistics and computing power. Ecological big data isn’t as massive as that of astrophysics and genetics, but there are aspects of it that need specialised methods to manage the statistics.
What are the roots of statistical ecology?
Statistical ecology emerged as a link between cutting-edge statistical methods and sophisticated ecological questions. It’s developed rapidly over the past decade, responding to the urgent need to look at what’s driving environmental changes like climate change and habitat destruction.
It’s a particularly productive field in Africa and could enable researchers on the continent to become leaders in globally relevant research. It can also position them to really tackle real-world issues.
Statistical ecology also provides tools to track environmental changes that affect biodiversity and human livelihoods. This supports sustainable infrastructure and agricultural policies.
Who are statistical ecologists?
In the past decade there’s been a flood of opportunities for ecologists. As these increase, though, so does the workload. Mathematically inclined ecologists and statisticians shoulder much of the work burden.
They are scarce in Africa.
The problem is that ecologists need better undergraduate training in statistics. Ecologists really need advanced statistical training and computer programming abilities.
Statistical ecology is able to provide confident, evidence-based solutions to those who make decisions about conservation. At the moment such material is often bypassed when urgent conservation policies are developed. This is particularly true in Africa.
If the field is to advance, more people with diverse talents in programming, statistics and ecology must be nurtured. There also needs to be work around plugging the communication gap that exists between scientists from different fields. A similar gap exists between scientists and policymakers.
How can capacity be increased?
The good news is that these problems can be solved. In fact, many solutions have already been set in motion.
Institutional change is crucial. It’s a long-term project, of course, that needs financial and administrative input.
New courses are needed and ecologists really need better undergraduate statistical training. And postgraduate students and professionals could also benefit from advanced statistics courses. More generally, science students need better mathematics education in school.
Collaboration is key. There must be stronger ties between researchers, university departments and non-academic institutions.
There’s been quite a bit of progress internationally. Research institutions like the Centre for Research into Ecological and Environmental Modelling and the Centre for Statistical Ecology and Environmental Statistics have been set up. There is also a scientific conference dedicated to the discipline. But options are more limited in Africa.
Where to find statistical ecologists
The Centre for Statistics in Ecology, the Environment and Conservation spans the departments of biology and statistics at the University of Cape Town. It collaborates with institutions locally and abroad. These include the Endangered Wildlife Trust and the South African National Biodiversity Institute.
African researchers shouldn’t be deterred from embracing statistical ecology just because their institutions are slow to change. Many higher education institutions promote free web-based seminars and courses. There’s additional support too from online educational, scientific and programming communities. These are part of a global drive to promote accessible, open-source educational resources and computer programmes.
These are short-term solutions that can’t replace investment in formal institutions. But it’s still encouraging that the scientific community, policymakers and the public are spontaneously sharing knowledge.
This may raise the awareness needed to speed up institutional reform. The communication gap between statistical science, ecology, policymakers, the public and other scientific fields might soon be a thing of the past.