Investigation of Fire and Vegetation Structure Preferences of Golden Eagles in New Jersey Pinelands
Topics: Animal Geographies
, Environment
,
Keywords: fire, prescribed burns, lidar, golden eagle, New Jersey
Session Type: Virtual Poster Abstract
Day: Sunday
Session Start / End Time: 2/27/2022 05:20 PM (Eastern Time (US & Canada)) - 2/27/2022 06:40 PM (Eastern Time (US & Canada))
Room: Virtual 32
Authors:
Lee Nolan,
Timothy A. Warner, West Virginia University
Tricia A. Miller, Conservation Science Global, Inc.
Inga La Puma, Earth Resources Observation and Science (EROS) Center
Jamison F. Conley, West Virginia University
Nicholas S. Skowronski, USDA Forest Service, Northern Research Station
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,
,
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Abstract
Prescribed burns are widely implemented to achieve resource management objectives, including habitat enhancement. Our study assesses the relationships among fire, vegetation structure, and golden eagle preferences and how prescribed fire could enhance their habitat in the New Jersey Pinelands. We recorded golden eagle telemetry locations within the study area and aggregated them to 240 m pixels. We identified three dependent variables: presence of eagles, eagles at flight, and eagles perching. We selected independent variables, centered on the same pixels, that are influenced by prescribed fire and that may influence golden eagle habitat selection: forest type, LIDAR derived canopy bulk density estimates at one-meter increments above ground level, numbers of prescribed burns and total fires, and the number of years since the most recent fire. We employed logistic regression and Poisson point process models to estimate golden eagle habitat selection for each dependent variable for the entire study area and the subset of coniferous forests. Results were weak, with high AIC scores and low deviation explained. However, logistic regression consistently outperformed Poisson point process models, and common trends emerged across all analyses. Golden eagles were more likely to be present in cells with more prescribed burns and less low-level (< 2m AGL) biomass, but longer periods since the most recent fire, suggesting post-fire recovery time influences golden eagle habitat selection. Future analyses may be improved by reducing pixel size, using summarized metrics for dependent variables in each pixel, or incorporating other variables like topography, which influences golden eagle habitat selection elsewhere.
Investigation of Fire and Vegetation Structure Preferences of Golden Eagles in New Jersey Pinelands
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Virtual Poster Abstract
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