Geology topics

Jennifer D McCabe

Publications and source records attributed to Jennifer D McCabe.

3 recordsLinked to original sources

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↗

USGS2021

Flight altitudes of raptors in southern Africa highlight vulnerability of threatened species to wind turbines

Energy infrastructure, particularly for wind power, is rapidly expanding in Africa, creating the potential for conflict with at-risk wildlife populations. Raptor populations are especially susceptible to negative impacts of fatalities from wind energy because individuals tend to be long-lived and reproduce slowly. A major determinant of risk of collision between flying birds and wind turbines is the altitude above ground at which a bird flies. We examine 18,710 observations of flying raptors recorded in southern Africa and we evaluate, for 49 species, the frequency with which they were observed to fly at the general height of a wind turbine rotor-swept zone (50–150 m). Threatened species, especially vultures, were more likely to be observed at turbine height than were other species, suggesting that these raptors are most likely to be affected by wind power development across southern Africa. Our results highlight that threatened raptor species, particularly vultures, might be especially impacted by expanded wind energy infrastructure across southern Africa.

Frontiers in Ecology and Evolution↗

USGS2021

Eagle fatalities are reduced by automated curtailment of wind turbines

Collision‐caused fatalities of animals at wind power facilities create a ‘green versus green’ conflict between wildlife conservation and renewable energy. These fatalities can be mitigated via informed curtailment whereby turbines are slowed or stopped when wildlife are considered at increased risk of collision. Automated monitoring systems could improve efficacy of informed curtailment, yet such technology is undertested. We test the efficacy of an automated curtailment system—a camera system that detects flying objects, classifies them and decides whether to curtail individual turbines to avoid potential collision—in reducing counts of fatalities of eagles, at Top of the World Windpower Facility (hereafter, the treatment site) in Wyoming, USA. We perform a before–after–control–impact study, comparing the number of eagle fatalities observed at the treatment site with those at a nearby (15 km) control site without automated curtailment, both before and after the implementation of automated curtailment at the treatment site. After correcting for carcass detection probability and scaling fatality estimates to turbine‐years, we estimate that the number of fatalities at the treatment site declined by 63% (95% CI = 59%–66%) between before and after periods while increasing at the control site by 113% (51%–218%). In total, there was an 82% (75%–89%) reduction in the fatality rate at the treatment site relative to the control site. Synthesis and applications . Automated curtailment of wind turbine operation substantially reduced eagle fatalities. This technology therefore has the potential to lessen the conflict between wind energy and raptor conservation. Although automated curtailment reduced fatalities, they were not fully eliminated. Therefore, automated curtailment, as implemented here, is not a panacea and its efficacy could be improved if considered in conjunction with other mitigation actions.

Wyoming↗