Statistical ecology software development
Effective wildlife management and conservation requires user-friendly software that makes state-of-the-art statistical tools accessible to natural resource managers and conservation practitioners. A key pillar of my research is developing computationally-efficient and accessible software to understand the ecological and anthropogenic drivers of species distributions, population dynamics, and biodiversity patterns.
I am the lead author and maintainer of the spOccupancy R package, which fits spatially explicit single-species, multi-species, and integrated Bayesian occupancy models (Doser et al. 2022A MEE), with an emphasis on making these complex statistical models accessible to ecologists and conservation practitioners that may lack extensive training in spatial statistics. With collaborators across the world, I am actively using spOccupancy to inform effective conservation and management approaches for birds, mammals, bats, and crickets. I recently incorporated new functionality to fit spatially varying coefficients models in spOccupancy, and used simulations and a case study on spatially-varying forest bird trends across the eastern U.S. to provide a series of guidelines and recommendations on the use of these models to understand context dependency in species-environment relationships (Doser et al. 2023).
Additionally, I am developing an R package spAbundance that will provide user-friendly approaches to efficiently fit spatially explicit single-species and multi-species abundance-based generalized linear models, N-mixture models, and distance sampling models. spAbundance will allow for robust modeling of multi-species abundance patterns, providing crucial insight into the patterns that determine population dynamics and ecological communities.