James is a Ph.D. student with the Caesar Kleberg Wildlife Research Institute. He is originally from Albany, NY and received his Associate’s degree from Chattanooga State CC in Chattanooga, TN, and his Bachelor’s degree in Wildlife Science (minor in Applied Statistics) from SUNY College of Environmental Science and Forestry in Syracuse, NY. He has worked for the NYS Department of Environmental Conservation Big Game Unit and worked alongside the U.S. Forest Service while serving as an AmeriCorps member in Chattahoochee National Forest in GA. Before moving to Texas, he completed his Master’s degree at Mississippi State University, where he studied conservation threats to the endangered Eastern Massasauga rattlesnake. In addition to his current work with ocelots, James’ broader research interests include population ecology, GIS & geospatial techniques, capture-recapture, climate change, and endangered species conservation. In his free time, James enjoys backpacking, wakeboarding/snowboarding, and music.
Texas A&M University-Kingsville
Major Advisor: Lisanne S. Petracca, Ph.D.
Applying Spatially Explicit Genetic Capture-Recapture for Ocelot Density Estimation
Robust and accurate estimates of population parameters are crucial for effectively managing endangered species. Estimates of abundance and density are needed to monitor populations over time, make comparisons among sites, and assess extinction risk. While analytical advancements such as spatially explicit capture-recapture (SECR) models have generally improved our ability to estimate abundance, there is still a need to identify the most effective methods for monitoring elusive, low abundance populations over time. We will use SECR to answer questions related to the last remaining populations of the federally listed ocelot (Leopardus pardalis) in the United States while evaluating efficacy of field and analytic techniques. First, we will use simulations to determine the ideal detector array design under multiple movement strategies, giving researchers insight into how to design trap arrays when movement models are known and unknown. We will utilize camera traps and scat detection dogs to estimate ocelot and bobcat (Lynx rufus) densities for the South Texas ocelot populations. This effort will provide the first multi-site estimate of abundance and allow for the evaluation of camera trap versus scat detection dog methodologies. We will then extrapolate potential density to a region-wide scale using remotely sensed landscape characteristics. Finally, we will use a combined Integrated Population Model-Population Viability Analysis to jointly estimate parameters of Texas ocelot populations and predict future population size and extinction risk under climate and landcover change scenarios. An IPM-PVA will give us insights into the dynamics of ocelot populations through the end of the 21st century and beyond.
welderwildlife.org 