Geology topics

Thomas J. Prebyl

Publications and source records attributed to Thomas J. Prebyl.

3 recordsLinked to original sources

USGS2024

Using remote sensing to identify habitat for wintering Henslow's Sparrows (Centronyx henslowii)

The Henslow's Sparrow ( Centronyx henslowii ) is a grassland bird species that overwinters in the southeastern United States and is a species of conservation concern due to population declines primarily caused by habitat loss. Henslow's Sparrows often overwinter in marginal habitats, such as powerline rights-of-way (ROWs), clear cuts, and field edges that provide some of their desired habitat characteristics, such as low-to-no tree cover and a diverse herbaceous understory. Using remote sensing methods, we evaluated the habitat characteristics of Henslow's Sparrow–occupied ROWs in southeastern Georgia. We calculated 22 satellite imagery metrics from Sentinel 2-L2 10 m resolution imagery, including single-pixel variables (e.g., Enhanced Vegetation Index, EVI) as well as “image texture” metrics that represent spatial heterogeneity. Using Random Forest models, we evaluated whether satellite imagery metrics could be used to discriminate between Henslow's Sparrow used areas (delineated from telemetry data) and surrounding available areas. Satellite imagery metrics were successful in predicting habitat characteristics in the ROWs (as evaluated by out-of-bag error and 3 goodness-of-fit tests), with image texture metrics performing better than single-pixel metrics. Image texture metrics were 9 of the top 10 most important predictors of habitat use in the best performing model that had a 500 m available buffer around use areas (out-of-bag error rate 21.21%). The most important image texture metric, cluster shade, was positively correlated with tree cover; Henslow's Sparrows were more likely to use areas with intermediate levels of cluster shade. From our results, we concluded that image texture metrics derived from 10 m satellite imagery could be used to predict sites that have suitable overwintering habitat for Henslow's Sparrows, but only at coarse resolutions and broader extents (hundreds of meters to kilometers). Therefore, this tool could be used to identify other ROWs (and possibly non-ROWs) with habitat that may support this and other declining grassland species.

Georgia↗

USGS2023

Dynamic spatiotemporal modeling of a habitat-defining plant species to support wildlife management at regional scales

Sagebrush ( Artemisia spp.) ecosystems provide critical habitat for the Greater sage-grouse ( Centrocercus urophasianus ), a species of conservation concern. Thus, future loss of sagebrush habitat because of land use change and global climate change is of concern. Here, we use a dynamic additive spatiotemporal model to estimate the effects of climate on sagebrush cover dynamics at 32 sage-grouse management (core) areas in Wyoming. We use the fitted models to quantify the sensitivity of each management area to precipitation and temperature, and to make probabilistic projections of sagebrush cover from present to 2100 under three climate change scenarios. Global circulation models predict an increase in temperature and no change in precipitation for Wyoming. Sensitivity to climate varied among management areas, but the most common response (70% of management areas) was a positive effect of temperature on sagebrush performance. The combination of positive sensitivity to temperature and the predicted increase in temperature under all climate change scenarios resulted in projections of increased sagebrush cover for most management areas. We characterized management areas as “optimal” or “suboptimal” based on the percentage of grid cells in each management area with sagebrush cover exceeding a nesting habitat target value. Only 18% of management areas are projected to switch from being currently optimal to suboptimal in the future. Thirty-five percent of management areas are projected to switch from being suboptimal to optimal. The most common outcome (47%) was for currently suboptimal management areas to remain suboptimal, even though average cover tended to increase in those areas. The direct effects of climate change appear to favor sagebrush performance in the future for most sage-grouse core areas in Wyoming. Our approach is broadly applicable to quantitative climate change assessments where remotely sensed estimates of habitat-defining vegetation are available.

Wyoming↗

USGS2016

Using GPS telemetry to determine roadways most susceptible to deer-vehicle collisions

More than 1 million wildlife-vehicle collisions occur annually in the United States. The majority of these accidents involve white-tailed deer (Odocoileus virginianus) and result in >US $4.6 billion in damage and >200 human fatalities. Prior research has used collision locations to assess sitespecific as well as landscape features that contribute to risk of deer-vehicle collisions. As an alternative approach, we calculated road-crossing locations from 25 GPS-instrumented white-tailed deer near Madison, Georgia (n=154,131 hourly locations). We identified crossing locations by creating movement paths between subsequent GPS points and then intersecting the paths with road locations. Using AIC model selection, we determined whether 10 local and landscape variables were successful at identifying areas where higher frequencies of deer crossings were likely to occur. Our findings indicate that traffic volume, distance to riparian areas, and the amount of forested area influenced the frequency of road crossings. Roadways that were predominately located in wooded landscapes and 200–300 m from riparian areas were crossed frequently. Additionally, we found that areas of low traffic volume (e.g., county roads) had the highest frequencies of deer crossings. Analyses utilizing only records of deer-vehicle collision locations cannot separate the relative contribution of deer crossing rates and traffic volume. Increased frequency of road crossings by deer in low-traffic, forested areas may lead to a greater risk of deer-vehicle collision than suggested by evaluations of deer-vehicle collision frequency alone.

Georgia↗