Geology topics

Robert Sargent

Publications and source records attributed to Robert Sargent.

4 recordsLinked to original sources

USGS2024

Key breeding habitats of threatened golden eagles across Eastern Canada identified using a multi-level, multi-scale habitat selection approach

Context In a conservation context, identifying key habitats suitable for reproduction, foraging, or survival is a useful tool, yet challenging for species with large geographic distributions and/or living in remote regions. Objectives The objective of this study is to identify selected habitats at multiple levels and scales of the threatened eastern North American population of golden eagles ( Aquila chrysaetos ). We studied habitat selection at three levels: landscape (second order of selection), foraging (third order of selection), and nesting (fourth order of selection). Methods Using tracking data from 30 adults and 366 nest coordinates spanning over a 1.5 million km 2 area in remote boreal and Arctic regions, we modelled the three levels of habitat selection with resource selection functions using seven environmental features (aerial, topographical, and land cover). We then calculated the relative probability of selection in the study area to identify regions with higher probabilities of selection. Results Eagles selected more for terrain ruggedness index and relative elevation than land cover (i.e., forest cover, distance to water; mean difference in relative selection strength: 1.2 [0.71; 1.69], 95% CI) at all three levels. We also found that the relative probability of selection at all three levels was ~ 25% higher in the Arctic than in the boreal regions. Eagles breeding in the Arctic travelled shorter foraging distances with greater access to habitat with a high probability of selection than boreal eagles. Conclusion Here we found which aerial and topographical features were important for several of the eagles’ life cycle needs. We also identified important areas to monitor and preserve this threatened population. The next step is to quantify the quality of habitat by linking our multi-level, multi-scale approach to population demography and performance such as reproductive success.

Landscape Ecology↗

USGS2023

Winter distribution of golden eagles in the Eastern USA

Golden Eagles ( Aquila chrysaetos ) have a Holarctic distribution, but some details of that overall distribution are poorly understood, including parts of the range in eastern North America. Recent studies in the region suggest that Golden Eagles may be more widely distributed than previously recognized. For species specific conservation efforts to be effective, an understanding of the distribution of the species is essential. Thus, the goal of this study was to map the winter distribution of Golden Eagles in the eastern half of the USA. To accomplish this, we reviewed and compiled 11,981 Golden Eagle records from eight data sources, including literature and ornithology records, community science data, survey data, and telemetry data. We found that Golden Eagles were observed in winter in each of the 31 states that lie completely east of the 100th meridian and in 1244 of the 2045 counties (61%) in those states. The proportion of counties with records varied by physiographic province, with higher proportions in physiographic provinces with more rugged terrain and greater forest cover. Our study shows that Golden Eagles are more widely distributed during winter in eastern USA states than was previously recognized. This work provides an important foundation for future management and research at a time when threats to this species are expanding rapidly on the landscape.

Journal of Raptor Research↗

USGS2022

Interannual consistency of migration phenology is season- and breeding region-specific in North American Golden Eagles

Interannual consistency (an indicator of the strength of adjustments) in migration phenology of Golden Eagles ( Aquila chrysaetos ) in North America is most strongly associated with the breeding region, the season, and with late-season temperature on breeding and wintering grounds. Consistency was greatest in boreal spring migration and the breeding regions of eastern Canada. Using multi-year GPS tracks of 83 adults breeding in 3 spatially distant regions (Alaska, northeast Canada, and southeast Canada), we quantified the interannual consistency of migration phenology and wintering latitude within and among individuals tracked across multiple years and the repeatability ( r ) by breeding regions and seasons. By comparing regions and seasons, we found that consistency was highest ( r > 0.85) for boreal spring migration in eastern Canada while Alaska had the lowest value ( r < 0.15). Because seasonal consistency of migration phenology was only detected in eastern Canada, we conclude that seasonal features are not a primary constraint. While regional differences in consistency were not related to differences in migratory distances, they could be the result of genetic or habitat differences. We also found that temperatures warmer than the decadal average at the region of departure delayed the start of boreal spring migration by ~10 days and advanced boreal autumn migration by ~20 days. These results suggest that warmer temperatures would reduce residence time on breeding grounds, contrary to expectations and trends found in other studies. Wide variations in migratory strategies across a species distribution can add to the list of challenges for conservation but may give migrants the capacity to acclimate to environmental changes.

Ornithology↗

USGS2021

Resource selection functions based on hierarchical generalized additive models provide new insights into individual animal variation and species distribution

Habitat selection studies are designed to generate predictions of species distributions or inference regarding general habitat associations and individual variation in habitat use. Such studies frequently involve either individually indexed locations gathered across limited spatial extents and analyzed using resource selection functions (RSFs) or spatially extensive locational data without individual resolution typically analyzed using species distribution models. Both analytical methodologies have certain desirable features, but analyses that combine individual- and population-level inference with flexible non-linear functions may provide improved predictions while accounting for individual variation. Here, we describe how RSFs can be fit using hierarchical generalized additive models (HGAMs) using widely available software, providing a means to explore individual variation in habitat associations and to generate species distribution maps. We used GPS tracking data from golden eagles Aquila chrysaetos from across eastern North America with four environmental predictors to generate monthly distribution models. We considered three model structures that assumed different amounts of individual variation in the functional relationship between predictors and habitat use and used k -fold cross-validation to compare model performance. Models accounting for individual variability in shape and smoothness of functional responses performed best. Eagles exhibited the least amount of individual variation in response to land cover variables during winter months, with most individuals more closely adhering to the population-level trend. During the summer months, eagles exhibited more substantial individual variation in shape and smoothness of the functional relationships, suggesting some need to account for individual variation in eagle habitat use for both inferential and predictive purposes, during this time of year. Because they allow users to blend flexible functions with random effects structures and are well-supported by a variety of software platforms, we believe that HGAMs provide a useful addition to the suite of analyses used for modeling habitat associations or predicting species distributions.

Ecography↗