Context: Wildlife surveys are limited by the capacity to collect data over the spatial extent of a population, which is challenging and costly for species of large geographic distribution in remote regions. Multi-level habitat selection models can limit the surveying extent and become tools for conservation management by identifying key areas and habitats. Objectives: We studied habitat selection of the threatened Eastern North American population of golden eagles (Aquila chrysaetos) with a multi-level approach over the population’s distribution to identify key habitats and zones of interest. Methods: Using tracking data of 30 adults and 276 nest coordinates, we modelled habitat selection at three levels: landscape, foraging and nesting. Results: At the landscape level, eagles selected topographical features (i.e., terrain ruggedness, elevation) more strongly than land cover features (forest cover, distance to water; mean difference: 0.98, CI: 0.37), suggesting that topographical features, facilitating flight and movement through the landscape, are more important than land cover, indicative of hunting opportunities. We also found that home range size was 50% smaller and relative probability of selection at all three levels was ~ 25% higher in the polar regions than boreal regions. It suggests that eagles in polar regions travel shorter foraging distances and habitat characteristic is more suitable. Conclusion: Using multi-level models, we identified key habitat characteristics for a threatened population over a large spatial scale. We also identifying areas of interest to target for a variety of life cycle needs.
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Maynard et al. (2022) studied this question.
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