Modeling spatial variation in density of golden eagle nest sites in the western United States

Abstract

In order to contribute to conservation planning efforts for golden eagles (Aquila chrysaetos) in the western U.S., we developed nest site models using >6,500 nest site locations throughout a >3,483,000 km2 area of the western U.S. We developed models for twelve discrete modeling regions, and estimated relative density of nest sites for each region. Cross-validation showed that, in general, models accurately estimated relative nest site densities within regions and sub-regions. Areas estimated to have the highest densities of breeding golden eagles had from 132–2,660 times greater densities compared to the lowest density areas. Observed nest site densities were very similar to those reported from published studies. Large extents of each modeling region consisted of low predicted nest site density, while a small percentage of each modeling region contained disproportionately high nest site density. For example, we estimated that areas with relative nest density values <0.3 represented from 62.8–97.8% ( = 82.5%) of each modeling area, and those areas contained from 14.7–30.0% ( = 22.1%) of the nest sites. In contrast, areas with relative nest density values >0.5 represented from 1.0–12.8% ( = 6.3%) of modeling areas, and those areas contained from 47.7–66.9% ( = 57.3%) of the nest sites. Our findings have direct application to: 1) large-scale conservation planning efforts, 2) risk analyses for land-use proposals such as recreational trails or wind power development, and 3) identifying mitigation areas to offset the impacts of human disturbance.

A Spatially Explicit Model to Predict the Relative Risk of Golden Eagle Electrocutions in the Northwestern Plains, USA

“…Thus, quantile binning resulted in the highest bins containing a disproportionately large range of the values, while the lower bins more finely differentiated among the smaller predicted values. Similarly, ,20% of the study area had Golden Eagle nest-site density values .1.0 AAF, yet contained .80% of known Golden Eagle nests (Dunk et al 2019a). Although other binning methods might be reasonable and useful, our method of binning model values using quantiles worked very well, based on our evaluation of independent mortality data, which indicated that even small increases in Golden Eagle density (e.g., bin 5 vs. bin 6; Fig.…”

“…Given the model's accurate predictions in the PRECorp service area, we believe the model will be immediately useful to land managers, utilities, and conservationists throughout the Northwestern Plains region. Because we previously developed models of Golden Eagle and power pole density for the majority of ecoregions occupied by Golden Eagles in the western USA (Dunk et al 2019a, the analysis presented here is a case study in only one of many regions where such risk analyses are possible.…”

“…Study Area. We conducted our study within the Northwestern Plains, a 474,170-km 2 region adapted from the Northwestern Great Plains and Northwestern Glaciated Plains Level-III ecoregions defined by the Commission for Environmental Cooperation (2011), with modifications to improve alignment with Golden Eagle habitat (Dunk et al 2019a; Fig. 1).…”

“…We used a predictive model of Golden Eagle relative nest-site density for the Northwestern Plains ecoregion as an index of exposure ( Fig. 2a; Dunk et al 2019a). Using MaxEnt (Phillips et al 2006), Dunk et al (2019a) related Golden Eagle nest locations to environmental covariates (e.g., landcover, topography, climate) at multiple spatial scales and generated predictions of relative nest-site density at a 120-m 3 120-m spatial resolution.…”

“…Using MaxEnt (Phillips et al 2006), Dunk et al (2019a) related Golden Eagle nest locations to environmental covariates (e.g., landcover, topography, climate) at multiple spatial scales and generated predictions of relative nest-site density at a 120-m 3 120-m spatial resolution. Dunk et al (2019a) interpreted their estimated quantity as relative nest density (RND), based on Dudík (2004) and Aarts et al (2012) who noted that models such as MaxEnt represent relative density of the estimated quantity. Relative density alone, however, is equivalent to ranking, where the magnitude of differences between areas of differing RND is unknown.…”