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Operating wind-power projects often includes protecting volant wildlife. One method for doing this uses an automated system to detect, identify (through use of artificial intelligence; AI), track animals (targets) and curtail turbines when risk of a collision is high. However, assessments of the effectiveness, in terms of identification accuracy and subsequent turbine curtailment of such systems are lacking. Over 1 year, we assessed such an automated system installed at a wind project in California, USA to determine its identification accuracy and rates at which "virtual” curtailments were ordered (without slowing turbines), for eagles (intended targets) and non-eagle targets. The system correctly identified 77% of eagles and 85% of non-eagles. Curtailment orders occurred 6 times more frequently for non-eagle targets (5,439) than for eagle targets (850). Greater abundance of common ravens that were misidentified as eagles influenced the effectiveness of the system by greatly increasing unintended curtailment orders. The balance between costs (price of the IdentiFlight system, reduced energy generation, turbine wear and maintenance) and benefits (reduced collisions between intended target species and turbines) may depend upon the biological setting, speed at which operators can curtail turbines, and the objectives of the operator when considering the IdentiFlight system.

Abstract A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat‐specific behaviors. Here we use behavioral change point analysis to identify behavioral states of golden eagles (Aquila chrysaetos) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation‐relevant habitat associations. We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short‐distance movement behaviors characterized by low AGL (state 1 AGL = 14 m (median); state 2 AGL = 11 m) and two associated with longer‐distance movement behaviors and characterized by higher AGL (state 3 AGL = 108 m; state 4 AGL = 450 m). Behaviors such as perching and low‐altitude hunting were associated with short‐distance movements in updraft‐poor environments, at higher elevations, and over steeper and more north‐facing terrain. In contrast, medium‐distance movements such as hunting and transiting were over gentle and south‐facing slopes. Long‐distance transiting occurred over the desert habitats that generate the best updraft. This information can guide management of this species, and our approach provides a template for behavior‐specific habitat associations for other species of management concern.

Abstract Movements by animals can serve different functions and occur over a variety of spatial and temporal scales. Routine movement types, such as residency (localized movements) and migration, have been well studied. However, nonroutine movement types, such as dispersal, prospecting, and nomadism, are less well understood. Documenting these rarely detected events requires tracking large numbers of individuals across all age classes. We studied >500 golden eagles (Aquila chrysaetos) tracked by telemetry over a 10‐year period in western North America, of which 160 engaged in nonroutine, long‐distance (>300 km) movements. We identified spatial and temporal correlates of those movements at both small and large scales, and we quantified movement timing and direction. We further tested which age and sex classes of eagles were more likely to engage in these movements. Our analysis of 88,093 daily tracks suggested that distances traveled by eagles were responsive to the updraft potential of the spatial and temporal landscape they encountered. Tracks covered longer distances at locations and times of higher updraft potential, and older birds traveled farther than younger birds. By contrast, after decomposing daily tracks into 563 nonroutine, long‐distance movements measured at a multiday scale, only the duration of travel was responsive to environmental conditions encountered by eagles. Multiday trips that were longer were those initiated in open and warm landscapes and those that ended in mountainous regions. Finally, long‐distance movements were more frequently made in seasons other than winter, in north–south directions, and by young birds. We documented clear correlates of nonroutine, long‐distance movements by golden eagles at small, local scales but found little evidence of such correlates at larger, regional scales. Most long‐distance movements we documented fit patterns associated with traditional definitions of prospecting and nomadism but not migration. Our study is the first to describe these movement types by golden eagles, and as such provides a foundation for subsequent study into the movement ecology of other species.

Abstract Prolonged drought due to climate change has negatively impacted amphibians in southern California, U.S.A. Due to the severity and length of the current drought, agencies and researchers had growing concern for the persistence of the arroyo toad (Anaxyrus californicus), an endangered endemic amphibian in this region. Range‐wide surveys for this species had not been conducted for at least 20 years. In 2017–2020, we conducted collaborative surveys for arroyo toads at historical locations. We surveyed 88 of the 115 total sites having historical records and confirmed that the arroyo toad is currently extant in at least 61 of 88 sites and 20 of 25 historically occupied watersheds. We did not detect toads at almost a third of the surveyed sites but did detect toads at 18 of 19 specific sites delineated in the 1999 Recovery Plan to meet one of four downlisting criteria. Arroyo toads are estimated to live 7–8 years, making populations susceptible to prolonged drought. Drought is estimated to increase in frequency and duration with climate change. Mitigation strategies for drought impacts, invasive aquatic species, altered flow regimes, and other anthropogenic effects could be the most beneficial strategies for toad conservation and may also provide simultaneous benefits to several other native species that share the same habitat.

Golden eagles (Aquila chrysaetos) are of increasing conservation concern in western North America. Effective conservation measures for this wide-ranging, federally protected raptor species require monitoring frameworks that accommodate strong inference on the status of breeding populations across vast landscapes. We used a broad-scale sampling design to identify relationships between landscape conditions, detection rates, and site occupancy by territorial pairs of golden eagles in coastal southern California, United States. In 2016 and 2017, we surveyed 175 territory-sized sample sites (13.9-km2 randomly selected grid cells) up to four times each year and detected a pair of eagles at least once in 22 (12.6%) sites. The probability of detecting pairs of eagles varied substantially between years and declined with increasing amounts of forest cover at survey sites, which obscured observations of eagles during ground-based surveys. After accounting for variable detection, the mean estimate of expected site occupancy by eagle pairs was 0.156 (SE = 0.081). Site-level estimates of occupancy were greatest (>0.30) at sample sites with more rugged terrain conditions,

Abstract Background Management requires a robust understanding of between- and within-species genetic variability, however such data are still lacking in many species. For example, although multiple population genetics studies of the peregrine falcon (Falco peregrinus) have been conducted, no similar studies have been done of the closely-related prairie falcon (F. mexicanus) and it is unclear how much genetic variation and population structure exists across the species’ range. Furthermore, the phylogenetic relationship of F. mexicanus relative to other falcon species is contested. We utilized a genomics approach (i.e., genome sequencing and assembly followed by single nucleotide polymorphism genotyping) to rapidly address these gaps in knowledge. Results We sequenced the genome of a single female prairie falcon and generated a 1.17 Gb (gigabases) draft genome assembly. We generated maximum likelihood phylogenetic trees using complete mitochondrial genomes as well as nuclear protein-coding genes. This process provided evidence that F. mexicanus is an outgroup to the clade that includes the peregrine falcon and members of the subgenus Hierofalco. We annotated > 16,000 genes and almost 600,000 high-quality single nucleotide polymorphisms (SNPs) in the nuclear genome, providing the raw material for a SNP assay design featuring > 140 gene-associated markers and a molecular-sexing marker. We subsequently genotyped ~ 100 individuals from California (including the San Francisco East Bay Area, Pinnacles National Park and the Mojave Desert) and Idaho (Snake River Birds of Prey National Conservation Area). We tested for population structure and found evidence that individuals sampled in California and Idaho represent a single panmictic population. Conclusions Our study illustrates how genomic resources can rapidly shed light on genetic variability in understudied species and resolve phylogenetic relationships. Furthermore, we found evidence of a single, randomly mating population of prairie falcons across our sampling locations. Prairie falcons are highly mobile and relatively rare long-distance dispersal events may promote gene flow throughout the range. As such, California’s prairie falcons might be managed as a single population, indicating that management actions undertaken to benefit the species at the local level have the potential to influence the species as a whole.

Operating wind-power projects often includes protecting volant wildlife. One method for doing this uses an automated system to detect, identify (through use of artificial intelligence; AI), track animals (targets) and curtail turbines when risk of a collision is high. However, assessments of the effectiveness, in terms of identification accuracy and subsequent turbine curtailment of such systems are lacking. Over 1 year, we assessed such an automated system installed at a wind project in California, USA to determine its identification accuracy and rates at which "virtual" curtailments were ordered (without slowing turbines), for eagles (intended targets) and non-eagle targets. The system correctly identified 77% of eagles and 85% of non-eagles. Curtailment orders occurred 6 times more frequently for non-eagle targets (5,439) than for eagle targets (850). Greater abundance of common ravens that were misidentified as eagles influenced the effectiveness of the system by greatly increasing unintended curtailment orders. The balance between costs (price of the IdentiFlight system, reduced energy generation, turbine wear and maintenance) and benefits (reduced collisions between intended target species and turbines) may depend upon the biological setting, speed at which operators can curtail turbines, and the objectives of the operator when considering the IdentiFlight system.

Soaring birds can balance the energetic costs of movement by switching between flapping, soaring and gliding flight. Accelerometers can allow quantification of flight behavior and thus a context to interpret these energetic costs. However, models to interpret accelerometry data are still being developed, rarely trained with supervised datasets, and difficult to apply. We collected accelerometry data at 140Hz from a trained golden eagle (Aquila chrysaetos) whose flight we recorded with video that we used to characterize behavior. We applied two forms of supervised classifications, random forest (RF) models and K-nearest neighbor (KNN) models. The KNN model was substantially easier to implement than the RF approach but both were highly accurate in classifying basic behaviors such as flapping (85.5% and 83.6% accurate, respectively), soaring (92.8% and 87.6%) and sitting (84.1% and 88.9%) with overall accuracies of 86.6% and 92.3% respectively. More detailed classification schemes, with specific behaviors such as banking and straight flights were well classified only by the KNN model (91.24% accurate; RF = 61.64% accurate). The RF model maintained its accuracy of classifying basic behavior classification accuracy of basic behaviors at sampling frequencies as low as 10Hz, the KNN at sampling frequencies as low as 20Hz. Classification of accelerometer data collected from free ranging birds demonstrated a strong dependence of predicted behavior on the type of classification model used. Our analyses demonstrate the consequence of different approaches to classification of accelerometry data, the potential to optimize classification algorithms with validated flight behaviors to improve classification accuracy, ideal sampling frequencies for different classification algorithms, and a number of ways to improve commonly used analytical techniques and best practices for classification of accelerometry data.

Biologists routinely use molecular markers to identify conservation units, to quantify genetic connectivity, to estimate population sizes, and to identify targets of selection. Many imperiled eagle populations require such efforts and would benefit from enhanced genomic resources. We sequenced, assembled, and annotated the first eagle genome using DNA from a male golden eagle (Aquila chrysaetos) captured in western North America. We constructed genomic libraries that were sequenced using Illumina technology and assembled the high-quality data to a depth of ∼40x coverage. The genome assembly includes 2,552 scaffolds >10 Kb and 415 scaffolds >1.2 Mb. We annotated 16,571 genes that are involved in myriad biological processes, including such disparate traits as beak formation and color vision. We also identified repetitive regions spanning 92 Mb (∼6% of the assembly), including LINES, SINES, LTR-RTs and DNA transposons. The mitochondrial genome encompasses 17,332 bp and is ∼91% identical to the Mountain Hawk-Eagle (Nisaetus nipalensis). Finally, the data reveal that several anonymous microsatellites commonly used for population studies are embedded within protein-coding genes and thus may not have evolved in a neutral fashion. Because the genome sequence includes ∼800,000 novel polymorphisms, markers can now be chosen based on their proximity to functional genes involved in migration, carnivory, and other biological processes.

Predatory and scavenging birds may be exposed to high levels of lead when they ingest shot or bullet fragments embedded in the tissues of animals injured or killed with lead ammunition. Lead poisoning was a contributing factor in the decline of the endangered California condor population in the 1980s, and remains one of the primary factors threatening species recovery. In response to this threat, a ban on the use of lead ammunition for most hunting activities in the range of the condor in California was implemented in 2008. Monitoring of lead exposure in predatory and scavenging birds is essential for assessing the effectiveness of the lead ammunition ban in reducing lead exposure in these species. In this study, we assessed the effectiveness of the regulation in decreasing blood lead concentration in two avian sentinels, golden eagles and turkey vultures, within the condor range in California. We compared blood lead concentration in golden eagles and turkey vultures prior to the lead ammunition ban and one year following implementation of the ban. Lead exposure in both golden eagles and turkey vultures declined significantly post-ban. Our findings provide evidence that hunter compliance with lead ammunition regulations was sufficient to reduce lead exposure in predatory and scavenging birds at our study sites.