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1.
Science ; 375(6582): 779-782, 2022 02 18.
Article in English | MEDLINE | ID: mdl-35175813

ABSTRACT

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.

2.
Ecol Appl ; 32(3): e2544, 2022 04.
Article in English | MEDLINE | ID: mdl-35080801

ABSTRACT

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.


Subject(s)
Eagles , Age Factors , Animals , Cause of Death , Female , Humans , Propylamines , Sulfides , Survival Rate , United States
3.
PLoS One ; 16(4): e0246134, 2021.
Article in English | MEDLINE | ID: mdl-33826627

ABSTRACT

Raptors, including eagles, are geographically widespread and sit atop the food chain, thereby serving an important role in maintaining ecosystem balance. After facing population declines associated with exposure to organochlorine insecticides such as dichlorodiphenyltrichloroethane (DDT), bald eagles (Haliaeetus leucocephalus) have recovered from the brink of extinction. However, both bald and golden eagles (Aquila chrysaetos) are exposed to a variety of other toxic compounds in the environment that could have population impacts. Few studies have focused on anticoagulant rodenticide (AR) exposure in eagles. Therefore, the purpose of this study was to determine the types of ARs that eagles are exposed to in the USA and better define the extent of toxicosis (i.e., fatal illness due to compound exposure). Diagnostic case records from bald and golden eagles submitted to the Southeastern Cooperative Wildlife Disease Study (University of Georgia) 2014 through 2018 were reviewed. Overall, 303 eagles were examined, and the livers from 116 bald eagles and 17 golden eagles were tested for ARs. The percentage of AR exposure (i.e., detectable levels but not associated with mortality) in eagles was high; ARs were detected in 109 (82%) eagles, including 96 (83%) bald eagles and 13 (77%) golden eagles. Anticoagulant rodenticide toxicosis was determined to be the cause of mortality in 12 (4%) of the 303 eagles examined, including 11 bald eagles and 1 golden eagle. Six different AR compounds were detected in these eagles, with brodifacoum and bromadiolone most frequently detected (81% and 25% of eagles tested, respectively). These results suggest that some ARs, most notably brodifacoum, are widespread in the environment and are commonly consumed by eagles. This highlights the need for research to understand the pathways of AR exposure in eagles, which may help inform policy and regulatory actions to mitigate AR exposure risk.


Subject(s)
4-Hydroxycoumarins/adverse effects , Anticoagulants/adverse effects , Bird Diseases , Eagles/metabolism , Rodenticides/adverse effects , Animals , Bird Diseases/chemically induced , Bird Diseases/metabolism , Bird Diseases/pathology , Ecosystem , Liver/metabolism , Liver/pathology , United States
4.
PLoS One ; 11(8): e0159271, 2016.
Article in English | MEDLINE | ID: mdl-27556735

ABSTRACT

Increasing development across the western United States (USA) elevates concerns about effects on wildlife resources; the golden eagle (Aquila chrysaetos) is of special concern in this regard. Knowledge of golden eagle abundance and distribution across the western USA must be improved to help identify and conserve areas of major importance to the species. We used distance sampling and visual mark-recapture procedures to estimate golden eagle abundance from aerial line-transect surveys conducted across four Bird Conservation Regions in the western USA between 15 August and 15 September in 2006-2010, 2012, and 2013. To assess golden eagle-habitat relationships at this scale, we modeled counts of golden eagles seen during surveys in 2006-2010, adjusted for probability of detection, and used land cover and other environmental factors as predictor variables within 20-km2 sampling units randomly selected from survey transects. We found evidence of positive relationships between intensity of use by golden eagles and elevation, solar radiation, and mean wind speed, and of negative relationships with the proportion of landscape classified as forest or as developed. The model accurately predicted habitat use observed during surveys conducted in 2012 and 2013. We used the model to construct a map predicting intensity of use by golden eagles during late summer across our ~2 million-km2 study area. The map can be used to help prioritize landscapes for conservation efforts, identify areas where mitigation efforts may be most effective, and identify regions for additional research and monitoring. In addition, our map can be used to develop region-specific (e.g., state-level) density estimates based on the latest information on golden eagle abundance from a late-summer survey and aid designation of geographic management units for the species.


Subject(s)
Eagles , Models, Theoretical , Seasons , Algorithms , Animals , Animals, Wild , Conservation of Natural Resources , Ecosystem , Geography , Population Dynamics , United States
5.
PLoS One ; 10(7): e0130978, 2015.
Article in English | MEDLINE | ID: mdl-26134412

ABSTRACT

Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80th quantile, 6.3). In this case, the increased precision in the fatality prediction lowered the level of authorized take, and thus lowered the required amount of compensatory mitigation.


Subject(s)
Conservation of Natural Resources/statistics & numerical data , Eagles/physiology , Energy-Generating Resources/ethics , Mortality/trends , Animals , Bayes Theorem , Risk , Uncertainty , Wind
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