Statistically efficient integration of animal tracking data into ecological theory and evidence-based conservation

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Animal movement is a key behavioural process that governs how individuals, populations, and species interact with each other and the environment, and is a core component of conservation science. Spurred by advances in tracking technologies, movement ecology has expanded from a niche topic to one of the fastest growing fields in ecology. Problematically, however, statistical techniques for analyzing these new and challenging datasets have lagged behind. This can limit the ability for tracking data to reliably inform species conservation. My long-term objective is to support the statistically efficient integration of animal tracking data into ecological theory and evidence-based conservation. Over the next 5 years, I will build toward this goal by tackling three key challenges. Challenge (i): Accurate estimation of latent variables estimated from animal paths. HQP in my lab will leverage established modelling and simulation methods to develop novel estimators of path-derived latent variables (e.g., habitat time budgets, road crossing rates, etc.). Software implementations of these estimators will be made freely available to the scientific community. Using pre-existing tracking datasets HQP will apply these tools to achieve accurate estimates for mitigating human-wildlife conflict. Challenge (ii): Encounter distribution estimation. Existing work on modelling inter-individual encounters has focused primarily on relating animal movement and encounter rates, while no research directly links individual movement with the spatial locations of encounter events in the environment. HQP will bridge this gap by introducing a new theoretical distribution, deriving this distribution, and implementing its estimator in open-access software. This estimator will then be integrated with the tools from challenge (i) to build an analytical framework for answering questions on animal-vehicle interactions. Challenge (iii): Macro-ecology and global conservation. I have assembled an extensive empirical animal tracking dataset, consisting of ~1300 individuals from 76 globally distributed species. By pairing these data with robust analytical tools, my trainees and I will evaluate four key questions aimed at understanding how animals are responding to anthropogenic impacts globally: a) the allometric scaling of movement speeds; b) an evaluation of the effects of anthropogenic disturbance on circadian rhythms; c) an evaluation of the evolution of periodic behaviour; and d) an evaluation of the evolutionary constraints on the phenotypic plasticity of animal movement. A diverse group of HQP, including at least 3 PhD, 3 MSc, and 4 UG will be trained as part of this project. The lab's research and training activities will help position Canada at the forefront of the rapidly growing field of movement ecology. Findings will have direct application for government agencies and NGOs charged with protecting and restoring Canada's culturally and ecologically important species.