Agent-Based Inference for Animal Movement and Selection

Authored by Mevin B. Hooten, Devin S. Johnson, Ephraim M. Hanks, John H. Lowry

Date Published: 2010-12

DOI: 10.1007/s13253-010-0038-2

Sponsors: Oceans and Human Health Initiative (NOAA) United States Geological Survey (USGS)

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

Abstract

Contemporary ecologists often find themselves with an overwhelming amount of data to analyze. For example, it is now possible to collect nearly continuous spatiotemporal data on animal locations via global positioning systems and other satellite telemetry technology. In addition, there is a wealth of readily available environmental data via geographic information systems and remote sensing. We present a modeling framework that utilizes these forms of data and builds on previous research pertaining to the quantitative analysis of animal movement. This approach provides additional insight into the environmental drivers of residence and movement as well as resource selection while accommodating path uncertainty. The methods are demonstrated in an application involving mule deer movement in the La Sal Range, Utah, USA. Supplemental materials for this article are available online.

Tags

Agent-based model Individual-based model models ecology systems Bayesian model Change of support Continuous model Hierarchical Habitat selection Chain monte-carlo Estimating site occupancy Mule deer Telemetry