Animal movement models with mechanistic selection functions

Abstract

A suite of statistical methods are used to study animal movement. Most of these methods treat animal telemetry data in one of three ways: as discrete processes, as continuous processes, or as point processes. We briefly review each of these approaches and then focus in on the latter. In the context of point processes, so-called resource selection analyses are among the most common way to statistically treat animal telemetry data. However, most resource selection analyses provide inference based on approximations of point process models. The forms of these models have been limited to a few types of specifications that provide inference about relative resource use and, less commonly, probability of use. For more general spatio-temporal point process models, the most common type of analysis often proceeds with a data augmentation approach that is used to create a binary data set that can be analyzed with conditional logistic regression. We show that the conditional logistic regression likelihood can be generalized to accommodate a variety of alternative specifications related to resource selection. We then provide an example of a case where a spatio-temporal point process model coincides with that implied by a mechanistic model for movement expressed as a partial differential equation derived from first principles of movement. We demonstrate that inference from this form of point process model is intuitive (and could be useful for management and conservation) by analyzing a set of telemetry data from a mountain lion in Colorado, USA, to understand the effects of spatially explicit environmental conditions on movement behavior of this species.

Diffusion modeling reveals effects of multiple release sites and human activity on a recolonizing apex predator

“…3 & 4 ). Given the relationship between motility in the ecological diffusion model, population spread rates, and specific forms of resource selection functions [ 64 ], it is possible that preliminary investigations of individual animal movement—either in the reintroduction area or a similar area—could be used to optimize a reintroduction strategy in terms of the initial locations and densities of released individuals. Nonetheless, these inferences regarding improved translocation strategies are largely based on mathematical theory underlying diffusion models, so further study is needed to determine how they may apply to translocation and reintroduction efforts in practice.…”

Diffusion modeling reveals effects of multiple release sites and human activity on a recolonizing apex predator

“…In fact, our results provided evidence of this: The sea otter population spread quickly over areas with high motility, then settled at high abundance in areas with low motility, which included areas with limited or no commercial fishing (Figure & 4). Given the relationship between motility in the ecological diffusion model, population spread rates, and specific forms of resource selection functions (Hooten et al, 2020), it is possible that preliminary investigations of individual animal movement-either in the reintroduction area or a similar area-could be used to optimize a reintroduction strategy in terms of the initial locations and densities of released individuals. Nonetheless, these inferences regarding improved translocation strategies are largely based on mathematical theory underlying diffusion models, so further study is needed to determine how they may apply to translocation and reintroduction efforts in practice.…”

Towns and Trails Drive Carnivore Connectivity using a Step Selection Approach

“…Emerging techniques in the field of movement ecology offer new opportunities to develop stronger links between movement behavior and estimates of connectivity (e.g. Hooten et al 2020).…”

“…Movement models and step selection analyses offer a complementary approach for estimating connectivity either from model predictions (Buderman et al 2018, Hooten et al 2020) or from simulated paths (Palmer et al 2011, Quaglietta and Porto 2019, Zeller et al 2020). Step selection analyses are a subset of spatial point-process models that are increasingly used to estimate relative selection of resources (Fortin et al 2005), to understand the effects of human activity on animal movement behaviour (e.g.…”

“…Movement models and step selection analyses offer a complementary approach for estimating connectivity either from model predictions (Buderman et al 2018, Hooten et al 2020 or from simulated paths (Palmer et al 2011, Zeller et al 2020…”