Prof. David Borchers
I'm a statistician at the University of St Andrews, specialising in the developing statistical methods to solve problems in ecology: mostly methods of estimating wildlife population abudance, distribution and population trajectories over time.
See links above for more on my Research, PhD Students, and Publications. There are also a few Images and Videos relating to my research.
Postgraduate study in Statistical Ecology?
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We have an MSc in Statistical Ecology that started in 2020.
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Some Projects and Collaborators
I and colleageus are working with the Global Snow Leopard and Ecosystem Protection Programme, The Snow Leopard Trust, and snow leopard range countries to complete the first range-wide assessment of snow leopard populations, using spatial capture-recapture methods.
I and colleageus are working with the IUCN Section on Small Apes, Rainforest Connection, Aarhus University, Association Anoulak and the University of Auckland to develop customised hardware and software for effecient acoustic spatial capture-recapture methods to survey gibbons and other vocalising species.
I hold an associate position at the University of Cape Town and collaborate with various members of the Statistics in Ecology, Environment and Conservation research group there.
Some Recent Research
Acoustic Spatial Capture-Recapture Methods:
I am working with Rachel Fewster, Ben Stevenson and Paul van Dam-Bates, to develop spatial capture-reapture methods for situations in which capture histories are not known. This situation occurs quite often with acoustic surveys because it is often impossible to identify individuals when they are heard and not seen. With Erica Ye and Yuheng Wang, I am also looking into integrating AI methods for species identification from acoustic surveys, with spatial capture-recapture methods, while Filippo Franchini and I are developing methods for acoustic surveys of gibbons from mobile survey platforms.
Optimal Designs for Spatial Capture-Recapture Surveys:
In this work, led by Ian Durbach, we develop methods for placing detectors in a spatial capture-recapture surveys, allowing for spatially-varying density and detectability, in a way that optimise the precision of resulting density estimates.
The image above shows optimal designs under various assumptions about distribution and detectability. (As you move from left to right, animals become more selective about their habitat, and this changes what the most efficient design is.)