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Results for “Avian Conservation and Ecology”

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USGS2022

Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights

Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles ( Aquila chrysaetos ) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale ( < "> < 50 m) and wind conditions are known at facility scale ( < "> < 3 km). For a given set of atmospheric conditions, the model simulates movements of thousands of orographic soaring eagles to produce a density map quantifying the relative probability of eagle presence. We validated the simulated tracks with GPS telemetry data showing four directional tracks made by golden eagles transiting through the area in 2019 and 2020. For each eagle track, validation was performed using the ratio of the model-simulated eagle presence likelihood with uniform eagle presence and the presence computed using directed random-walk movements. We found that the predictive performance of the model was significantly better (likelihood ratio > "> > 1) for low-altitude movements than high-altitude movements that can involve thermal-soaring. We employed the model to produce seasonal presence maps for migrating golden eagles. We found significant turbine-level variations in eagle presence between northerly and southerly migration routes through the study area. Overall, the proposed model offers a generalizable, probabilistic, and predictive tool to assist wind energy developers, ecologists, wildlife managers, and industry consultants in estimating the potential for conflict between soaring birds and wind turbines, thereby reducing the need for site-specific data on golden eagle movements.

Wyoming↗

USGS2022

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter datasets versus pseudo-absence locations during migratory periods, and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and post-breeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations, when compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings, and thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach for integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Ecological Applications↗

USGS1999

Le Conte's sparrows breeding in Conservation Reserve Program fields: precipitation and patterns of population change

The climate of the North American Great Plains is highly dynamic, with great year-to-year variability in precipitation and periodic, often extreme, wet and dry cycles (Bragg 1995). Drought is a major force of ecological disturbance on the Great Plains and has played a key role in directing the evolution of the grassland biota of this region (Knopf and Samson 1997). Although grassland birds may differ in their responses to enviromenental variations (Rotenberry and Wiens 1991), climatic variability and concomitant unpredictability of resources strongly influence populations of grassland birds across space and time (Wiens 1974, 1986; Cody 1985). Not surprisingly, breeding bird populations on the Great Plains are highly dynamic, exhibiting considerable annual variation in composition, abundance, and distribution (Johnson and Grier 1988, George et al. 1992, Zimmerman 1992, Igl and Johnson 1997). Recently, interest in grassland birds has increased with the recognition that many species are declining both continentally (Droege and Sauer 1994) and globally (Goriup 1988). Identification of the specific factors associated with grassland bird declines in North America, however, remains largely enigmatic (Herkert 1997), and it is complicated by the considerable annual fluctuations in grassland bird distribution and abundance (Igl and Johnson 1997). Although there is evidence that land-use changes on the breeding grounds may have contributed to grassland bird declines (e.g., Igl and Johnson 1997), there also is an indication that long-term drought conditions may have influenced recent population changes of some breeding birds on the Great Plains (Droege and Sauer 1989, Peterjohn and Sauer 1993, Bethke and Nudds 1995, Igl and Johnson 1997). Le Conte's Sparrow (Ammodramus leconteii) is a secretive grassland bird that breeds in central and southern Canada and the northcentral United States (Murray 1969). It winters primarily in the southern United States (Peterson 1980, 1990). Like populations of many grassland breeding birds in North America (Fretwell 1986, Igl and Johnson 1997), Le Conte's Sparrow populations exhibit numerical highs and lows depending on local moisture conditions (Peabody 1901, Stewart 1975, Knapton 1979, Zimmer 1979, Madden 1996). This observation, however, is based largely on anecdotal evidence or short-term observations. Long-term studies of Le Conte's Sparrow populations are limited. Le Conte's Sparrow is poorly represented on the North American Breeding Bird Survey (BBS) because of small sample sizes, poor coverage in the northern portion of its breeding range, and the species' furtive behavior (Sauer et al. 1995). Moreover, dramatic fluctuations in Le Conte's Sparrow abundance tend to obscure the species' long-term population trends on the BBS (Sauer et al. 1995). In this paper we examine long-term population changes of Le Conte's Sparrows breeding in perennial grassland fields enrolled in the Conservation Reserve Program (CRP) on the northern Great Plains. We discuss patterns of population change of Le Conte's Sparrows associated with changes in precipitation and moisture conditions.

Studies in Avian Biology↗