Structural ecology is the main focus of the lab.
Social movement in complex landscapes
We are attempting to create a unified modeling framework that describes how socially-moving groups (flocks, herds, swarms, etc.) navigate complex physical landscapes. The challenge is that models of social movement tend to be physics-based simulation models, whereas models of landscape movement tend to be choice-based statistical models suitable to fitting to data. Specific projects include:
- The SPRSF (“social-physical resource selection function”) for combined modeling of social and physical influences on animal movements.
- Elephants in Etosha National Park, Namibia.
The role of island biogeography in conservation
Past work has examined how models of biogeography can potentially play a very useful role in conservation. Specifically, spatially explicit metapopulation models can be used to evaluate fragmented landscapes at many scales and make recommendations for protection and habitat restoration efforts. However, at the heart of such models are rather naive assumptions assumptions about animal dispersal
Automated identification for ecology and conservation
One of our research areas is automated ‘technical’ ID systems: systems for identifying species from images of specific parts, such as bees from their wings or trees from their leaves. As good as modern deep learning networks are at being robust to noise, disambiguating closely related species often depends on very subtle differences, and so it is still important to get good consistent images, both for training, testing, and ultimately deployable systems. This can be a challenge. We suspect that there might be relatively simple hardware accessories that would improve the process dramatically. Here are two cases:
Identifying bees from wing images
Bees are identified from preserved specimens under a microscope. Obtaining a clear image of a bee’s wing is a challenge: generally the wing is detached from the body and sandwiched under a cover slip, which is fiddly and time-consuming. The resulting images often have glare spots, which are noise for the ID algorithm. So the design challenge is this: is there a specially shaped platform (in microscope terms, a ‘stage’) that would allow a high-quality image of a bee wing (or really any kind of insect wing) to be taken quickly without detachment?