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Lead poisoning is an important global conservation problem for many species of wildlife, especially raptors. Despite the increasing number of individual studies and regional reviews of lead poisoning of raptors, it has been over a decade since this information has been compiled into a comprehensive global review. Here, we summarize the state of knowledge of lead poisoning of raptors, we review developments in manufacturing of non-lead ammunition, the use of which can reduce the most pervasive source of lead these birds encounter, and we compile data on voluntary and regulatory mitigation options and their associated sociological context. We support our literature review with case studies of mitigation actions, largely provided by the conservation practitioners who study or manage these efforts. Our review illustrates the growing awareness and understanding of lead exposure of raptors, and it shows that the science underpinning this understanding has expanded considerably in recent years. We also show that the political and social appetite for managing lead ammunition appears to vary substantially across administrative regions, countries, and continents. Improved understanding of the drivers of this variation could support more effective mitigation of lead exposure of wildlife. This review also shows that mitigation strategies are likely to be most effective when they are outcome driven, consider behavioural theory, local cultures, and environmental conditions, effectively monitor participation, compliance, and levels of raptor exposure, and support both environmental and human health.
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Bird populations are declining globally. Wind and solar energy can reduce emissions of fossil fuels that drive anthropogenic climate change, yet renewable-energy production represents a potential threat to bird species. Surveys to assess potential effects at renewable-energy facilities are exclusively local, and the geographic extent encompassed by birds killed at these facilities is largely unknown, which creates challenges for minimizing and mitigating the population-level and cumulative effects of these fatalities. We performed geospatial analyses of stable hydrogen isotope data obtained from feathers of 871 individuals of 24 bird species found dead at solar- and wind-energy facilities in California (USA). Most species had individuals with a mix of origins, ranging from 23% to 98% nonlocal. Mean minimum distances to areas of likely origin for nonlocal individuals were as close as 97 to >1250 km, and these minimum distances were larger for species found at solar-energy facilities in deserts than at wind-energy facilities in grasslands (Cohen's d = 6.5). Fatalities were drawn from an estimated 30-100% of species' desingated ranges, and this percentage was significantly smaller for species with large ranges found at wind facilities (Pearson's r = -0.67). Temporal patterns in the geographic origin of fatalities suggested that migratory movements and nonmigratory movements, such as dispersal and nomadism, influence exposure to fatality risk for these birds. Our results illustrate the power of using stable isotope data to assess the geographic extent of renewable-energy fatalities on birds. As the buildout of renewable-energy facilities continues, accurate assessment of the geographic footprint of wildlife fatalities can be used to inform compensatory mitigation for their population-level and cumulative effects.
Extensión geográfica de las poblaciones de aves afectadas por desarrollos de energía renovable Resumen Las poblaciones mundiales de aves están en declive. Las energías solar y eólica pueden reducir las emisiones de combustibles fósiles que causan el cambio climático, aunque la producción de energías renovables representa una amenaza potencial para las aves. Los censos para evaluar los efectos potenciales en los centros de energía renovable son exclusivamente locales y se sabe poco sobre la extensión geográfica representada por las aves que mueren en estas instalaciones, lo que plantea obstáculos para mitigar los efectos acumulativos y de nivel poblacional de estas muertes. Realizamos análisis geoespaciales con datos del isótopo de hidrógeno estable obtenido de las plumas de 871 ejemplares de 24 especies de aves que fueron hallados muertos en los centros de energía solar y eólica en California, EE.UU. La mayoría de las especies contó con ejemplares de orígenes mixtos, con un rango del 23% al 98% no local. La media de la distancia mínima a las áreas de probable origen de los ejemplares no locales varía entre los 97 hasta > 1,250 km. Estas distancias mínimas fueron mayores para las especies encontradas en los centros de energía solar situadas en desiertos que para las especies encontradas en los centros de energía eólica localizadas en pastizales (d de Cohen = 6.5). Las muertes representan un 30100% de la extensión de las especies. Este porcentaje fue significativamente menor para las especies con extensiones amplias encontradas en instalaciones eólicas (r de Pearson = 0.67). Los patrones temporales en el origen geográfico de las muertes sugieren que los movimientos migratorios y no migratorios, como la dispersión y el nomadismo, influyen en la exposición de estas aves al riesgo de muerte. Nuestros resultados demuestran la utilidad de los isótopos estables para evaluar el alcance geográfico de las muertes de aves asociadas a energías renovables. Con el progresivo aumento de instalaciones de energía renovable, una evaluación precisa de la huella geográfica de la mortandad de fauna salvaje podrá guiar la mitigación compensatoria de sus efectos acumulativos y de nivel poblacional.
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Conservación de los Recursos Naturales , Energía Renovable , Animales , Aves , Isótopos , VientoRESUMEN
Wildlife conservation strategies focused on one season or population segment may fail to adequately protect populations, especially when a species' habitat preferences vary among seasons, age-classes, geographic regions, or other factors. Conservation of golden eagles (Aquila chrysaetos) is an example of such a complex scenario, in which the distribution, habitat use, and migratory strategies of this species of conservation concern vary by age-class, reproductive status, region, and season. Nonetheless, research aimed at mapping priority use areas to inform management of golden eagles in western North America has typically focused on territory-holding adults during the breeding period, largely to the exclusion of other seasons and life-history groups. To support population-wide conservation planning across the full annual cycle for golden eagles, we developed a distribution model for individuals in a season not typically evaluated-winter-and in an area of the interior western U.S. that is a high priority for conservation of the species. We used a large GPS-telemetry dataset and library of environmental variables to develop a machine-learning model to predict spatial variation in the relative intensity of use by golden eagles during winter in Wyoming, USA, and surrounding ecoregions. Based on a rigorous series of evaluations including cross-validation, withheld and independent data, our winter-season model accurately predicted spatial variation in intensity of use by multiple age- and life-history groups of eagles not associated with nesting territories (i.e., all age classes of long-distance migrants, and resident non-adults and adult "floaters", and movements of adult territory holders and their offspring outside their breeding territories). Important predictors in the model were wind and uplift (40.2% contribution), vegetation and landcover (27.9%), topography (14%), climate and weather (9.4%), and ecoregion (8.7%). Predicted areas of high-use winter habitat had relatively low spatial overlap with nesting habitat, suggesting a conservation strategy targeting high-use areas for one season would capture as much as half and as little as one quarter of high-use areas for the other season. The majority of predicted high-use habitat (top 10% quantile) occurred on private lands (55%); lands managed by states and the Bureau of Land Management (BLM) had a lower amount (33%), but higher concentration of high-use habitat than expected for their area (1.5-1.6x). These results will enable those involved in conservation and management of golden eagles in our study region to incorporate spatial prioritization of wintering habitat into their existing regulatory processes, land-use planning tasks, and conservation actions.
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Águilas , Propilaminas , Sulfuros , Humanos , Animales , Estaciones del Año , Conservación de los Recursos Naturales/métodos , América del NorteRESUMEN
Increased interest in renewable energy has fostered development of wind and solar energy facilities globally. However, energy development sometimes has negative environmental impacts, such as wildlife fatalities. Efforts by regional land managers to balance energy potential while minimizing fatality risk currently rely on datasets that are aggregated at continental, but not regional scales, that focus on single species, or that implement meta-analyses that inappropriately use inferential statistics. We compiled and summarized fatality data from 87 reports for solar and wind facilities in the Mojave and Sonoran Deserts region of southern California within the Desert Renewable Energy Conservation Plan area. Our goal was to evaluate potential temporal and guild-specific patterns in fatalities, especially for priority species of conservation concern. We also aimed to provide a perspective on approaches interpreting these types of data, given inherent limitations in how they were collected. Mourning doves (Zenaida macroura), Chukar (Alectoris chukar) and California Quail (Callipepla californica), and passerines (Passeriformes), accounted for the most commonly reported fatalities. However, our aggregated count data were derived from raw, uncorrected totals, and thus reflect an absolute minimum number of fatalities for the monitored period. Additionally, patterns in the raw data suggested that many species commonly documented as fatalities (e.g., waterbirds and other nocturnal migrants, bats) are rarely counted during typical pre-construction use surveys. This may explain the more commonly observed mismatch between pre-construction risk assessment and actual fatalities. Our work may serve to guide design of future scientific research to address temporal and spatial patterns in fatalities and to apply rigorous guild-specific survey methodologies to estimate populations at risk from renewable energy development.
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Quirópteros , Energía Solar , Animales , Animales Salvajes , Conservación de los Recursos Naturales/métodos , Energía Renovable , VientoRESUMEN
Human actions, both legal and illegal, affect wildlife in many ways. Inaccurate diagnosis of cause of death undermines law enforcement, management, threat assessment, and mitigation. We found 410 dead birds collected along 196 km of power lines in four western USA states during 2019-2022. We necropsied these carcasses to test conventional wisdom suggesting that electrocution is the leading cause of death of birds at electrical infrastructure. Of 175 birds with a known cause of death, 66% died from gunshot. Both raptors and corvids were more likely to die from gunshot than from other causes, along both transmission and distribution lines. Past mitigation to reduce avian deaths along power lines has focused almost exclusively on reducing electrocutions or collisions. Our work suggests that, although electrocution and collision remain important, addressing illegal shooting now may have greater relevance for avian conservation.
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Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised (n = 6), semi-supervised (n = 1), and unsupervised (n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors (Gymnogyps californianus). Unsupervised K-means and EM (expectation-maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: -0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.
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Renewable energy production can kill individual birds, but little is known about how it affects avian populations. We assessed the vulnerability of populations for 23 priority bird species killed at wind and solar facilities in California, USA. Bayesian hierarchical models suggested that 48% of these species were vulnerable to population-level effects from added fatalities caused by renewables and other sources. Effects of renewables extended far beyond the location of energy production to impact bird populations in distant regions across continental migration networks. Populations of species associated with grasslands where turbines were located were most vulnerable to wind. Populations of nocturnal migrant species were most vulnerable to solar, despite not typically being associated with deserts where the solar facilities we evaluated were located. Our findings indicate that addressing declines of North American bird populations requires consideration of the effects of renewables and other anthropogenic threats on both nearby and distant populations of vulnerable species.
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Habitat loss is the most prevalent threat to biodiversity in North America. One of the most threatened landscapes in the United States is the sagebrush (Artemisia spp.) ecosystem, much of which has been fragmented or converted to non-native grasslands via the cheatgrass-fire cycle. Like many sagebrush obligates, greater sage-grouse (Centrocercus urophasianus) depend upon sagebrush for food and cover and are affected by changes to this ecosystem. We investigated habitat selection by 28 male greater sage-grouse during each of 3 years after a 113,000-ha wildfire in a sagebrush steppe ecosystem in Idaho and Oregon. During the study period, seeding and herbicide treatments were applied for habitat restoration. We evaluated sage-grouse responses to vegetation and post-fire restoration treatments. Throughout the 3 years post-fire, sage-grouse avoided areas with high exotic annual grass cover but selected strongly for recovering sagebrush and moderately strongly for perennial grasses. By the third year post-fire, they preferred high-density sagebrush, especially in winter when sagebrush is the primary component of the sage-grouse diet. Sage-grouse preferred forb habitat immediately post-fire, especially in summer, but this selection preference was less strong in later years. They also selected areas that were intensively treated with herbicide and seeded with sagebrush, grasses, and forbs, although these responses varied with time since treatment. Wildfire can have severe consequences for sagebrush-obligate species due to loss of large sagebrush plants used for food and for protection from predators and thermal extremes. Our results show that management efforts, including herbicide application and seeding of plants, directed at controlling exotic annual grasses after a wildfire can positively affect habitat selection by sage-grouse.
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Lead poisoning occurs worldwide in populations of predatory birds, but exposure rates and population impacts are known only from regional studies. We evaluated the lead exposure of 1210 bald and golden eagles from 38 US states across North America, including 620 live eagles. We detected unexpectedly high frequencies of lead poisoning of eagles, both chronic (46 to 47% of bald and golden eagles, as measured in bone) and acute (27 to 33% of bald eagles and 7 to 35% of golden eagles, as measured in liver, blood, and feathers). Frequency of lead poisoning was influenced by age and, for bald eagles, by region and season. Continent-wide demographic modeling suggests that poisoning at this level suppresses population growth rates for bald eagles by 3.8% (95% confidence interval: 2.5%, 5.4%) and for golden eagles by 0.8% (0.7%, 0.9%). Lead poisoning is an underappreciated but important constraint on continent-wide populations of these iconic protected species.
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Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.We apply a framework for using K-means clustering to classify bird behavior using points from short time interval GPS tracks. K-means clustering is a well-known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K-means clustering to six focal variables derived from GPS data collected at 1-11 s intervals from free-flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life-stage- and age-related variation in behavior.After filtering for data quality, the K-means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non-moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.The K-means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short-interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high-dimensional movement data, it provides insight into small-scale variation in behavior that would not be possible with many other analytical approaches.
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In the United States, the Bald and Golden Eagle Protection Act prohibits take of golden eagles (Aquila chrysaetos) unless authorized by permit, and stipulates that all permitted take must be sustainable. Golden eagles are unintentionally killed in conjunction with many lawful activities (e.g., electrocution on power poles, collision with wind turbines). Managers who issue permits for incidental take of golden eagles must determine allowable take levels and manage permitted take accordingly. To aid managers in making these decisions in the western United States, we used an integrated population model to obtain estimates of golden eagle vital rates and population size, and then used those estimates in a prescribed take level (PTL) model to estimate the allowable take level. Estimated mean annual survival rates for golden eagles ranged from 0.70 (95% credible interval = 0.66-0.74) for first-year birds to 0.90 (0.88-0.91) for adults. Models suggested a high proportion of adult female golden eagles attempted to breed and breeding pairs fledged a mean of 0.53 (0.39-0.72) young annually. Population size in the coterminous western United States has averaged ~31,800 individuals for several decades, with λ = 1.0 (0.96-1.05). The PTL model estimated a median allowable take limit of ~2227 (708-4182) individuals annually given a management objective of maintaining a stable population. We estimate that take averaged 2572 out of 4373 (59%) deaths annually, based on a representative sample of transmitter-tagged golden eagles. For the subset of golden eagles that were recovered and a cause of death determined, anthropogenic mortality accounted for an average of 74% of deaths after their first year; leading forms of take over all age classes were shooting (~670 per year), collisions (~611), electrocutions (~506), and poisoning (~427). Although observed take overlapped the credible interval of our allowable take estimate and the population overall has been stable, our findings indicate that additional take, unless mitigated for, may not be sustainable. Our analysis demonstrates the utility of the joint application of integrated population and prescribed take level models to management of incidental take of a protected species.
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Águilas , Factores de Edad , Animales , Causas de Muerte , Femenino , Humanos , Propilaminas , Sulfuros , Tasa de Supervivencia , Estados UnidosRESUMEN
There is increasing pressure on wind energy facilities to manage or mitigate for wildlife collisions. However, little information exists regarding spatial and temporal variation in collision rates, meaning that mitigation is most often a blanket prescription. To address this knowledge gap, we evaluated variation among turbines and months in an aspect of collision risk-probability of entry by an eagle into a rotor-swept zone (hereafter, "probability of entry"). We examined 10,222 eagle flight paths identified and recorded by an automated bird monitoring system at a wind energy facility in Wyoming, USA. Probabilities of entry per turbine-month combination were 4.03 times greater in some months than others, ranging 0.15 to 0.62. The overall probability of entry for the riskiest turbine (i.e., the one with the greatest probability of entry) was 2.39 times greater than the least-risky turbine. Our methodology describes large variation across turbines and months in the probability of entry. If subsequently combined with information on other sources of variation (i.e., weather, topography), this approach can identify risky versus safe situations for eagles under which cost of management, curtailment prescriptions, and collision risk can be simultaneously minimized.
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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.
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Anticoagulant rodenticides (ARs) used to control mammalian pest populations cause secondary exposure of predatory species throughout much of the world. It is important to understand the drivers of non-target AR exposure patterns as context for assessing long-term effects and developing effective mitigation for these toxicants. In Australia, however, little is known about exposure and effects of ARs on predators. We detected AR residues in 74% of 50 opportunistically collected carcasses of the Tasmanian wedge-tailed eagle (Aquila audax fleayi), an endangered apex predator. In 22% of birds tested, or 31% of those exposed, liver concentrations of second generation ARs (SGARs) were >0.1 mg/kg ww. Eagles were exposed to flocoumafen, a toxicant only available from agricultural suppliers, at an exceptionally high rate (40% of birds tested). Liver SGAR concentrations were positively associated with the proportion of agricultural habitat and human population density in the area around where each eagle died. The high exposure rate in a species not known to regularly prey upon synanthropic rodents supports the hypothesis that apex predators are vulnerable to SGARs. Our results indicate that AR exposure constitutes a previously unrecognized threat to Tasmanian wedge-tailed eagles and highlight the importance of efforts to address non-target AR exposure in Australia.
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Rodenticidas , Animales , Anticoagulantes/análisis , Australia , Ecosistema , Monitoreo del Ambiente , Rodenticidas/análisis , Rodenticidas/toxicidadRESUMEN
Scavenging is an important function within ecosystems where scavengers remove organic matter, reduce disease, stabilize food webs, and generally make ecosystems more resilient to environmental changes. Global change (i.e., changing climate and increasing human impact) is currently influencing scavenger communities. Thus, understanding what promotes species richness in scavenger communities can help prioritize management actions. Using a long-term dataset from camera traps deployed with animal carcasses as bait along a 1881 km latitudinal gradient in the Appalachian Mountains of eastern USA, we investigated the relative impact of climate and humans on the species richness and diversity of vertebrate scavengers. Our most supported models for both mammalian and avian scavengers included climatic, but not human, variables. The richness of mammalian and avian scavengers detected was highest during relatively warm (5-10°C) and dry (100-150 mm precipitation) winters, when food was likely limited and both reliance on and detection of carrion was high. The diversity of mammalian and avian scavengers detected was highest under drier conditions. We then used these results to project the future species richness of scavengers that would be detected within our sampling area and under the climate scenario of 2070 (emissions level RCP8.5). Our predictions suggest up to 80% and 67% reductions, respectively, in the richness of avian and mammalian scavengers that would be detected at baited sites. Climate-induced shifts in behavior (i.e., reduction in scavenging, even if present) at this scale could have cascading implications for ecosystem function, resilience, and human health. Further, our study highlights the importance of conducting studies of scavenger community dynamics within ecosystems across wide spatial gradients within temperate environments. More broadly, these findings build upon our understanding of the impacts of climate-induced adjustments in behavior that can likely have negative impacts on systems at a large scale.
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Ecosistema , Cadena Alimentaria , Animales , Región de los Apalaches , Biodiversidad , Humanos , América del Norte , VertebradosRESUMEN
Increasing global energy demand is fostering the development of renewable energy as an alternative to fossil fuels. However, renewable energy facilities may adversely affect wildlife. Facility siting guidelines recommend or require project developers complete pre- and postconstruction wildlife surveys to predict risk and estimate effects of proposed projects. Despite this, there are no published studies that have quantified the types of surveys used or how survey types are standardized within and across facilities. We evaluated 628 peer-reviewed publications, unpublished reports, and citations, and we analyzed data from 525 of these sources (203 facilities: 193 wind and 10 solar) in the United States and Canada to determine the frequency of pre- and postconstruction surveys and whether that frequency changed over time; frequency of studies explicitly designed to allow before-after or impact-control analyses; and what types of survey data were collected during pre- and postconstruction periods and how those data types were standardized across periods and among facilities. Within our data set, postconstruction monitoring for wildlife fatalities and habitat use was a standard practice (n = 446 reports), but preconstruction estimation of baseline wildlife habitat use and mortality was less frequently reported (n = 84). Only 22% (n = 45) of the 203 facilities provided data from both pre- and postconstruction, and 29% (n = 59) had experimental study designs. Of 108 facilities at which habitat-use surveys were conducted, only 3% estimated of detection probability. Thus, the available data generally preclude comparison of biological data across construction periods and among facilities. Use of experimental study designs and following similar field protocols would improve the knowledge of how renewable energy affects wildlife. Article Impact Statement Many surveys at wind and solar facilities provide limited information on wildlife use and fatality rates.
Limitaciones, Falta de Estandarización y las Mejores Prácticas Recomendadas en Estudios de los Efectos de las Energías Renovables sobre las Aves y los Murciélagos Resumen La creciente demanda global por energía está fomentando el desarrollo de energías renovables como una alternativa a los combustibles fósiles. Sin embargo, las instalaciones de energías renovables pueden afectar de manera adversa a la fauna. Las pautas para la ubicación de dichas instalaciones recomiendan o requieren que los desarrolladores de los proyectos realicen censos previa y posteriormente a la construcción de las instalaciones para pronosticar el riesgo y estimar los efectos de los proyectos propuestos. A pesar de esto, no existen estudios publicados que hayan cuantificado los tipos de censo usados o cómo los tipos de censo están estandarizados para las instalaciones en específico y en general. Evaluamos 628 publicaciones revisadas por pares, reportes sin publicar y referencias y analizamos los datos de 525 de estas fuentes (203 instalaciones: 193 de energía eólica y 10 de energía solar) en los Estados Unidos y Canadá para determinar la frecuencia de los censos previos y posteriores a la construcción y si dicha frecuencia cambió con el tiempo; para determinar la frecuencia de los estudios diseñados explícitamente para permitir los análisis antes-y-después o de control-impacto; y para determinar cuáles tipos de datos fueron recolectados previa y posteriormente a la construcción y cómo aquellos tipos de datos estuvieron estandarizados a través de los periodos y entre las instalaciones. Dentro de nuestro conjunto de datos, el monitoreo posterior a la construcción de las fatalidades faunísticas y el uso de hábitat fue una práctica común (n = 446 reportes), pero la estimación previa a la construcción de la línea base del uso de hábitat por la fauna y la mortalidad estuvo reportada con menor frecuencia (n = 84). Sólo el 22% (n = 45) de las 203 instalaciones proporcionaron datos de los censos previos y posteriores a la construcción y el 29% (n = 59) contó con diseño de estudios experimentales. De las 108 instalaciones en las que se realizaron censos de uso de hábitat, sólo el 3% incluyó la estimación de la probabilidad de detección. Por lo tanto, los datos disponibles generalmente impiden la comparación de los datos biológicos durante los periodos de construcción y entre las instalaciones. El uso del diseño de estudios experimentales y el seguimiento de protocolos de campo similares mejoraría el conocimiento sobre cómo las energías renovables afectan a la fauna.
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Quirópteros , Animales , Aves , Canadá , Conservación de los Recursos Naturales , Estándares de Referencia , Energía Renovable , VientoRESUMEN
Lead poisoning, mainly through incidental ingestion of lead ammunition in carcasses, is a threat to scavenging and predatory bird species worldwide. In Australia, shooting for animal control is widespread, and a range of native scavenging species are susceptible to lead exposure. However, the prevalence of lead exposure in Australia's scavenging and predatory birds is largely unknown. We evaluated the degree to which the Tasmanian wedge-tailed eagle (Aquila audax fleayi), an endangered Australian raptor and facultative scavenger, showed evidence of lead exposure. We detected lead in 100% of femur and liver tissues of 109 eagle carcasses opportunistically collected throughout Tasmania between 1996 and 2018. Concentrations were elevated in 10% of 106 liver (>6 mg/kg dry wt) and 4% of 108 femur (>10 mg/kg dry wt) samples. We also detected lead in 96% of blood samples taken from 24 live nestlings, with 8% at elevated concentrations (>10 µg/dL). Of the liver samples with elevated lead, 73% had lead207/206 isotope ratios within the published range of lead-based bullets available in Tasmania. These first comprehensive data on lead exposure of an Australian raptor are comparable to those for raptor studies elsewhere that identify lead-based ammunition exposure as a conservation threat. Our findings highlight the importance of further research and efforts to address lead contamination throughout the Tasmanian ecosystem and in other Australian regions. Environ Toxicol Chem 2021;40:219-230. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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Águilas , Animales , Australia , Combinación de Medicamentos , Ecosistema , Glicerol , Plomo , SalicilatosRESUMEN
Anticoagulant rodenticides (ARs) are commonly used to control rodent pests. However, worldwide, their use is associated with secondary and tertiary poisoning of nontarget species, especially predatory and scavenging birds. No medical device can rapidly test for AR exposure of avian wildlife. Prothrombin time (PT) is a useful biomarker for AR exposure, and multiple commercially available point-of-care (POC) devices measure PT of humans, and domestic and companion mammals. We evaluated the potential of one commercially available POC device, the Coag-Sense® PT/INR Monitoring System, to rapidly detect AR exposure of living birds of prey. The Coag-Sense device delivered repeatable PT measurements on avian blood samples collected from four species of raptors trapped during migration (Intraclass Correlation Coefficient > 0.9; overall intra-sample variation CV: 5.7%). However, PT measurements reported by the Coag-Sense system from 81 ferruginous hawk (Buteo regalis) nestlings were not correlated to those measured by a one-stage laboratory avian PT assay (r = - 0.017, p = 0.88). Although precise, the lack of agreement in PT estimates from the Coag-Sense device and the laboratory assay indicates that this device is not suitable for detecting potential AR exposure of birds of prey. The lack of suitability may be related to the use of a mammalian reagent in the clotting reaction, suggesting that the device may perform better in testing mammalian wildlife.
Asunto(s)
Anticoagulantes/metabolismo , Monitoreo del Ambiente , Rapaces/metabolismo , Rodenticidas/metabolismo , Animales , Anticoagulantes/envenenamiento , Aves , Humanos , Hígado , Conducta Predatoria , Rodenticidas/envenenamientoRESUMEN
Viability selection yields adult populations that are more genetically variable than those of juveniles, producing a positive correlation between heterozygosity and survival. Viability selection could be the result of decreased heterozygosity across many loci in inbred individuals and a subsequent decrease in survivorship resulting from the expression of the deleterious alleles. Alternatively, locus-specific differences in genetic variability between adults and juveniles may be driven by forms of balancing selection, including heterozygote advantage, frequency-dependent selection, or selection across temporal and spatial scales. We use a pooled-sequencing approach to compare genome-wide and locus-specific genetic variability between 74 golden eagle (Aquila chrysaetos), 62 imperial eagle (Aquila heliaca), and 69 prairie falcon (Falco mexicanus) juveniles and adults. Although genome-wide genetic variability is comparable between juvenile and adult golden eagles and prairie falcons, imperial eagle adults are significantly more heterozygous than juveniles. This evidence of viability selection may stem from a relatively smaller imperial eagle effective population size and potentially greater genetic load. We additionally identify ~2000 single-nucleotide polymorphisms across the 3 species with extreme differences in heterozygosity between juveniles and adults. Many of these markers are associated with genes implicated in immune function or olfaction. These loci represent potential targets for studies of how heterozygote advantage, frequency-dependent selection, and selection over spatial and temporal scales influence survivorship in avian species. Overall, our genome-wide data extend previous studies that used allozyme or microsatellite markers and indicate that viability selection may be a more common evolutionary phenomenon than often appreciated.