Simulating elephant movements in response to veterinary fencing
An application of predictive modeling to optimize land-use planning in support of southern African wildlife conservation and rural livestock keeping.
[NEW!] Watch my 2024 talk about the modeling and simulation process HERE!
An application of predictive modeling to optimize land-use planning in support of southern African wildlife conservation and rural livestock keeping.
[NEW!] Watch my 2024 talk about the modeling and simulation process HERE!
Veterinary fencing crisscrosses much of southern Africa, protecting livestock from contracting diseases like foot and mouth from wild populations, but negatively impacting wildlife by preventing wild mammals from migrating seasonally to access grazing, water and other resources. As part of the Beyond Fences Initiative, this project uses advanced computer modeling, drawing on existing datasets from radio-collared animals, to investigate how elephants and other mammals currently move about southern Africa's KAZA TFCA. We particularly focus on how elephant movement patterns might change if alternative approaches to livestock disease management less dependent upon fencing were adopted. By simulating migrations using real-world tracking data, potential scenarios for integrative, sustainable land-use management become easier to understand and evaluate.
As ecotourism revenues now rival those of livestock in much of the KAZA region, conservation of large herbivores that shape ecosystems and draw tourists is crucial. In keeping with the One Health theme of both Cornell Atkinson and the Cornell Wildlife Health Center, this project will highlight the sustainable benefits of optimizing land-use planning at the interface of wildlife, livestock, and human health and livelihoods. The simulations used for this project are built using the framework of the abmAnimalMovement R package. I've extended this code into a separate package (abmAME) to address a few key needs:
Learn more about the KAZA elephant fencing project at the GitHub landing page. Funding source: Cornell Atkinson postdoctoral fellowship Further reading:
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