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Activity Number: 692
Type: Contributed
Date/Time: Thursday, August 4, 2016 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #320762 View Presentation
Title: A Spatio-Temporal Model for Ecological Colonizations
Author(s): Perry Williams* and Mevin Hooten and Jamie N. Womble and George G. Esslinger and Michael R. Bower
Companies: Colorado State University and Colorado State University and National Park Service and U.S. Geological Survey Alaska Science Center and National Park Service
Keywords: diffusion ; optimal monitoring ; population trends
Abstract:

Methods for inferring the dynamics of population spread through time are important for many ecological applications including the reintroduction of extirpated species and invasive species management. Spatio-temporal statistical models provide a framework to understand the dynamics of population spread. Sea otters (Enhydra lutris) were first detected in Glacier Bay in 1993 and have increased in both abundance and distribution since then; abundance estimates have increased from 5 otters to >8,000 otters. We developed a Bayesian hierarchical spatio-temporal model and fit it to aerial survey data to better understand the ecological processes governing changes in sea otter abundance and distribution in Glacier Bay. We used a process model motivated by partial differential equations to model sea otter spatio-temporal dynamics. Understanding the processes governing the population expansion provides a template for developing an optimal, dynamic monitoring framework that can be used to monitor abundance and distribution of a spreading population. We consider optimizing future monitoring efforts based on minimizing a design criterion associated with process prediction uncertainty.


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