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Adam E. Duerr

Publications and source records attributed to Adam E. Duerr.

At least 19 recordsLinked to original sources
USGS2024

Efficacy of non-lead ammunition distribution programs to offset fatalities of golden eagles in southeast Wyoming

Golden eagles ( Aquila chrysaetos ) face many anthropogenic risks including illegal shooting, electrocution, collision with wind turbines and vehicles, and lead poisoning. Minimizing or offsetting eagle deaths resulting from human-caused sources is often viewed as an important management objective. Despite understanding the leading anthropogenic sources of eagle fatalities, existing scientific research supports few practical solutions to mitigate these causes of death. We implemented a non-lead ammunition distribution program in southeast Wyoming, USA, and evaluated its effectiveness as a compensatory mitigation action to offset incidental take (i.e., fatalities) of golden eagles at wind energy facilities. In 2020 and 2022, we distributed non-lead ammunition to 699 hunters with big-game tags specific to our >400,000-ha study area. These hunters harvested 296 pronghorn ( Antilocapra americana ), 14 deer ( Odocoileus spp.), and 33 elk ( Cervus canadensis ) in the study area, which accounted for 6.9% and 6.5% of the harvest in these hunt units in 2020 and 2022, respectively. We used road surveys in 2020 to estimate a density of 0.036 (95% CI = 0.018–0.058) golden eagles/km 2 during the big game hunting season in our study area. Model output suggests that our non-lead ammunition distribution program offset the fatality of 3.84 (95% CI = 1.06–23.72) eagles over the course of these 2 hunting seasons. Our work illustrates the potential usefulness of non-lead ammunition distribution programs as an action to mitigate eagle fatalities caused by wind facilities or other anthropogenic causes of death.

Wyoming↗
USGS2024

Abundance of Long-billed Curlews on military lands in the Columbia Basin

Long-billed Curlews ( Numenius americanus ) are declining throughout North America, and the loss of grassland breeding habitat is one of the primary threats to the species. Intermountain West, in particular, has been identified as the most important region in North America for breeding curlews. Nevertheless, the density and abundance of Long-billed Curlews in this region is not well understood. Lands managed for military training can provide habitat for wildlife species of conservation concern, and increasingly these lands are becoming relevant to sustaining biodiversity. We conducted point count surveys of Long-billed Curlews on Department of Defense lands in the Columbia Basin near Boardman, Oregon, USA during two consecutive breeding seasons. We used multinomial-Poisson mixture models to estimate detection probability and density of curlews and to investigate environmental correlates of those metrics. Mean detection probability at a distance of 400 m was 0.45 and 0.61 in 2015 and 2016, respectively. In 2015, the clarity of skies increased detection probability, but in 2016, none of the variables we measured influenced detection probability. Mean predicted density was 3.3 (95% confidence interval: 2.4–4.7) and 1.8 (1.2–2.7) curlews/km² in 2015 and 2016, respectively. In both years, curlew density was higher in lower-elevation or topographically smoother areas. Estimated abundance of curlews in the study area was 639 (456–912) and 350 (237–520) birds in 2015 and 2016, respectively. The number of curlews appeared to fluctuate across the two years of our study, a demographic trend that may have been influenced by a wildfire in our study area in June 2015. The results of our study indicate that federal grasslands, including areas where military operations are conducted, can provide conservation benefit to breeding Long-billed Curlews.

Oregon↗
USGS2023

Variation in flight characteristics associated with entry by eagles into rotor-swept zones of wind turbines

Automated curtailment of wind turbines can reduce fatality rates of wildlife, but the resulting increased number of curtailments can reduce power generation. Tailoring curtailment criteria for each individual turbine could reduce unnecessary curtailment, yet it is unknown whether the risk to wildlife varies among turbines. We demonstrate turbine-specific variation in the speed, altitude, approach angle, and distance metrics associated with entry by eagles into rotor-swept zones. Our results thus illustrate the potential value of turbine-specific curtailment criteria to reduce fatality rates of wildlife at wind energy facilities.

Ibis↗
USGS2022

A review of supervised learning methods for classifying animal behavioural states from environmental features

Accurately predicting behavioural modes of animals in response to environmental features is important for ecology and conservation. Supervised learning (SL) methods are increasingly common in animal movement ecology for classifying behavioural modes. However, few examples exist of applying SL to classify polytomous animal behaviour from environmental features especially in the context of millions of animal observations. We review SL methods (weighted k -nearest neighbours; neural nets; random forests; and boosted classification trees with XGBoost) for classifying polytomous animal behaviour from environmental predictors. We also describe tuning parameter selection and assessment strategies, approaches for visualizing relationships between predictors and class outputs, and computational considerations. We demonstrate these methods by predicting three categories of risk to bald eagles from colliding with wind turbines using, as predictors, 12 environmental state features associated with 1.7 million GPS telemetry data points from 57 eagles. Of the SL methods we considered, XGBoost yielded the most accurate model with 86.2% classification accuracy and pairwise-averaged area under the ROC curve of 90.6. Computational time of XGBoost scaled better to large data than any other SL method. We also show how SHAP values integrated in the R package ( xgboost ) facilitate investigation of variable relationships and importance. For big data applications, XGBoost appears to provide superior classification accuracy and computational efficiency. Our results suggest XGBoost should be considered as an early modelling option in situations where the intent is to classify millions of animal behaviour observations from environmental predictors and to understand relationships between those predictors and movement behaviours. We also offer a tutorial to assist researchers in implementing this method.

Methods in Ecology and Evolution↗
USGS2022

Flight characteristics forecast entry by eagles into rotor-swept zones of wind turbines

Operators of wind power facilities can mitigate wildlife mortality by slowing or stopping wind turbines (hereafter ‘curtail’) when birds are at an increased risk of collision. Some facility operators curtail when individual birds have flight characteristics (e.g. altitude, distance or relative bearing of a bird's flight path) that exceed some threshold value, but thresholds currently in use have not been empirically evaluated. Overly restrictive thresholds can cause turbine curtailment for birds that never enter rotor-swept zones, thereby resulting in excess power loss. We evaluated the probability that birds, specifically eagles, entered the rotor-swept zone (hereafter ‘entry probability’) in response to their flight characteristics. We used an automated monitoring system to classify individuals as eagles or non-eagles and record flight paths of purported eagles at a wind facility in Wyoming, USA. We used logistic regression with occupancy dynamics and a distance-dependent colonization process to model entry probability. As a result, this model allowed entry probability to decrease with horizontal distance to the nearest turbine. The probability of entry varied with distance to the nearest turbine and approached zero when that distance was more than 202 m. Entry probability peaked when eagles flew 89 m above ground, corresponding to hub heights of turbines (80 m), and decreased to near-zero at altitudes of 189 m or more. Entry probabilities were greatest when flight paths were near the rotor-swept zone and when eagles flew slowly toward the nearest turbine. Compass bearing of a flight path was not associated with entry probability. Our model accurately forecasted entry probability in Wyoming (area under the curve (AUC) = 0.96) and was transferable to another facility in California, USA (AUC = 0.97); therefore, our results may be applicable across a variety of settings. Curtailment criteria can be based on flight path characteristics to forecast entry into rotor-swept zones. The use of distance and altitude thresholds when making curtailment decisions is justified. However, this analysis suggests alteration of the time to collision threshold, with curtailment initiated at greater distances as the speed of the bird decreases. Our novel modelling method and our results can inform curtailment criteria in any situation where curtailment decisions are made in real-time.

Wyoming↗
USGS2022

Age-specific survival rates, causes of death, and allowable take of golden eagles in the western United States

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.

western United States↗
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 ( &lt; "> < 50 m) and wind conditions are known at facility scale ( &lt; "> < 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 &gt; "> > 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

Influence of anthropogenic subsidies on movements of common ravens

Anthropogenic subsidies can benefit populations of generalist predators such as common ravens (ravens; Corvus corax ), which in turn may depress populations of many types of species at lower-trophic levels, including desert tortoises (Gopherus agassizii ) or greater sage-grouse (Centrocercus urophasianus). Management of subsidized ravens often has targeted local breeding populations that are presumed to affect species of concern and ignored “urban” populations of ravens. However, little is known about how ravens move, especially in response to the presence of anthropogenic subsidies. Therefore, subsidized ravens from distant populations that are not managed may influence local prey. To better understand this issue, we deployed global positioning system – global system for mobile communications transmitters to track movements of 19 ravens from September to December 2020 relative to 2 land cover types that provide subsidies: developed areas and cultivated crops. On average, ravens moved 41.5 km (±30.5) per day, although daily movement distances ranged from 0.13– 206.1 km. Raven movement among cover types during the non-breeding season varied widely, with 100% of individuals each using land cover types that provide subsidy and other types at least once in the season. On 100% of days ravens used areas that did not provide subsidy, on 86.7% of days they used developed areas, and on 20.5% of days they used cultivated crops. Although on some days a raven would stay exclusively in areas that did not provide subsidy, there were no days in which a single raven ever stayed exclusively in developed or cultivated crops. Ravens moved shorter distances on days when they used subsidies more frequently. Further, time spent in developed areas and cultivated crops increased when ravens roosted closer to them, although this effect was greater for developed areas than for cultivated crops. Individual ravens were not associated exclusively with either of the subsidy-providing landscapes we considered, but instead all birds used both subsidized and other landscapes. Our research suggests that management of ravens during the non-breeding season and possibly during the breeding season, intended to reduce risk of predation on desert tortoises, will be most effective if conducted on a broad scale because of distances the birds travel and the lack of separation between putative “urban” and “natural” populations of ravens.

California↗
USGS2021

Eagles enter rotor-swept zones of wind turbines at rates that vary per turbine

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.

Wyoming↗
USGS2020

Assessing population-level consequences of anthropogenic stressors for terrestrial wildlife

Human activity influences wildlife. However, the ecological and conservation significances of these influences are difficult to predict and depend on their population‐level consequences. This difficulty arises partly because of information gaps, and partly because the data on stressors are usually collected in a count‐based manner (e.g., number of dead animals) that is difficult to translate into rate‐based estimates important to infer population‐level consequences (e.g., changes in mortality or population growth rates). However, ongoing methodological developments can provide information to make this transition. Here, we synthesize tools from multiple fields of study to propose an overarching, spatially explicit framework to assess population‐level consequences of anthropogenic stressors on terrestrial wildlife. A key component of this process is using ecological information from affected animals to upscale from count‐based field data on individuals to rate‐based demographic inference. The five steps to this framework are (1) framing the problem to identify species, populations, and assessment parameters; (2) field‐based measurement of the effect of the stressor on individuals; (3) characterizing the location and size of the populations of interest; (4) demographic modeling for those populations; and (5) assessing the significance of stressor‐induced changes in demographic rates. The tools required for each of these steps are well developed, and some have been used in conjunction with each other, but the entire group has not previously been unified together as we do in this framework. We detail these steps and then illustrate their application for two species affected by different anthropogenic stressors. In our examples, we use stable hydrogen isotope data to infer a catchment area describing the geographic origins of affected individuals, as the basis to estimate population size for that area. These examples reveal unexpectedly greater potential risks from stressors for the more common and widely distributed species. This work illustrates key strengths of the framework but also important areas for subsequent theoretical and technical development to make it still more broadly applicable.

Ecosphere↗
USGS2020

Learning from real-world experience to understand renewable energy impacts to wildlife

The project team sought to use real-world data to understand adverse effects to wildlife of renewable energy production that is critical to meeting California’s climate and clean energy goals. The project had three main components. First, a systematic literature review studied 20 peer-reviewed publications and 612 reports from other nonreviewed sources from 231 wind and solar facilities in North America. Within California, 50 percent of facilities collected pre- and post-construction data, 30 percent had experimental study designs, and fewer than 7 percent estimated detection probability during habitat use surveys. Mitigation at wind power plants focused on repowering to reduce risk to soaring birds and at solar facilities emphasized wildlife deterrence and compensatory mitigation. Second, the authors developed a best-practices approach to employ environmental isotopes (for example, hydrogen obtained from animal tissue) and rescaling functions (a statistical approach to modeling the relationship between variables) to assign individual birds or bats to their place of origin. The team applied this approach to feathers from 411 individuals of 12 species killed at wind facilities and 515 individuals of 19 species killed at solar facilities. From 24 percent to 100 percent (mean +/- SD = 49 percent +/- 33 percent) and 25 percent to 100 percent (73 percent +/- 25 percent) of birds grew feathers at a location outside the collection site at wind and solar facilities, respectively. Third, the authors constructed Bayesian integrated population models (probability models) for 29 focal species affected by wind or solar energy generation in California. Species predominantly local in origin generally had lower population growth rates than did species that were predominantly nonlocal in origin. These patterns illustrate the complex linkages between behavioral ecology, vulnerability to mortality, and population-level impacts to wildlife from fatalities at renewable energy facilities. This project benefits the renewable energy sector by providing a framework and specific tools for understanding environmental impacts of renewable energy generation.

California↗
USGS2019

Relevance of individual and environmental drivers of movement of Golden Eagles

An animal's movement is expected to be governed by an interplay between goals determined by its internal state and energetic costs associated with navigating through the external environment. Understanding this ecological process is challenging when an animal moves in two dimensions and even more difficult for birds that move in a third dimension. To understand the dynamic interaction between the internal state of an animal and the variable external environment, we evaluated hypotheses explaining association of different covariates of movement and the trade‐offs birds face as they make behavioural decisions in a fluctuating landscape. We used ~870 000 GPS telemetry data points collected from 68 Golden Eagles Aquila chrysaetos to test demographic, diel, topographic and meteorological hypotheses to determine (1) the probability that these birds would be in motion and (2), once in motion, their flight speed. A complex and sometimes interacting set of potential internal and external factors determined movement behaviour. There was good evidence that reproductive state, manifested as age, sex and seasonal effects, had a significant influence on the probability of being in motion and, to a lesser extent, on speed of motion. Likewise, movement responses to the external environment were often unexpectedly strong. These responses, to northness of slope, strength of orographic updraft and intensity of solar radiation, were regionally and temporally variable. In contrast to previous work showing the role of a single environmental factor in determining movement decisions, our analyses support the hypothesis that multiple factors simultaneously interact to influence animal movement. In particular they highlighted how movement is influenced by the interaction between the individual's internal reproductive state and the external environment, and that, of the environmental factors, topographic influences are often more relevant than meteorological influences in determining patterns of flight behaviour. Further disentangling of how these internal and externals states jointly affect movement will provide additional insights into the energetic costs of movement and benefits associated with achieving process‐driven goals.

California↗
USGS2019

Topographic drivers of flight altitude over large spatial and temporal scales

Bird movements vary spatially and temporally, but the primary drivers that explain such variation can be difficult to identify. For example, it is well known that the availability of updraft influences soaring flight and that topography interacts with weather to produce these updrafts. However, the influences of topography on flight are not well understood. We determined how topographic characteristics influenced flight altitude above ground level (AGL) of a large soaring bird, the Golden Eagle (Aquila chrysaetos), over several regions within the State of California, USA. Primary drivers of flight AGL, those to which eagles showed the same response at all spatial scales, were topographic roughness, ground elevation and the east-west component of aspect (eastness). Each of these is related to formation of thermal updrafts. Secondary drivers, those to which eagles showed region-specific patterns, included topographic position, percent slope, and the north-south component of aspect (northness). In contrast to primary drivers, these secondary drivers were related to formation of both thermal and orographic updrafts. Overall, drivers of flight altitudes that were related to thermal updrafts showed different levels of complexity due to spatial and temporal variation of those drivers than did flight altitudes related to orographic updrafts.

California↗
USGS2019

Movements of immature bald eagles: Implications for bird aircraft strike hazard

Bald eagle (Haliaeetus leucocephalus) aircraft strikes have increased dramatically over the last 20 years as their populations have recovered to near historic sizes. Their attraction to airfields and their large body size makes them a danger to aircraft and therefore important to airfield wildlife managers. However, their management is complicated by their special protected status and the iconic place they hold in the eyes of the public. To help airfield wildlife managers plan monitoring efforts and make informed management decisions, we studied the movements of 32 bald eagles telemetered as nestlings in the Chesapeake Bay of Virginia, USA. Managers often need to know when fledged eagles are most likely to move enough to encounter airfields near nests. As fledglings aged they moved progressively farther from the nest and spent more time away from the nest. Twenty-eight days after fledging, eagles spent most of the day (81±10%, 95% confidence interval) near the nest (<500 m) and only 7±7% of the daytime away from the nest (>1 km). By day 53 fledglings ventured beyond 2.5 km from the nest and spent 30 ± 15% the day >1 km away from their nest. However, distances moved were influenced by proximity of the nest to water, the quality and salinity of that water, and human population density. Eagles left their natal areas and generally migrated out of the Chesapeake Bay 60.5 ± 7.7 days (4 August) after fledging and returned to the Chesapeake Bay approximately 225 days later (March-April). Eighty-four percent (27 of 32) of the eagles that we tracked encountered 164 airfields across the east coast with 91% of those airfields located within 10 km of the Chesapeake Bay. Encounters with airfields outside the Chesapeake Bay occurred mainly during the first 1.5 years of life, peaking in late fall and early spring. Eagles were recorded on Chesapeake Bay airfields during each year, but encounters peaked in April of the first year of the bird’s life. This month coincides with the height of reported strikes of eagles by aircraft in the region. Our results suggest that eagles fledging from the Chesapeake Bay are not only an issue for airports near the Chesapeake Bay, but for airports across the east coast. Given the continued growth of the population, this issue is likely to continue and grow in significance.

Virginia↗
USGS2019

Roost- and perch-site selection by Golden Eagles (Aquila chrysaetos) in eastern North America

Birds select critical resources to meet needs that vary in response to spatial, temporal, and individual variation. As an example, perch or roost sites may be at locations that provide protection from predators, mobbing, or inclement weather. Applied to large, soaring predators, this theory suggests that they may select perch and roost sites near food resources or at sites where environmental updrafts develop. To test these theories, we characterized selection of nonflight locations throughout the annual cycle for Golden Eagles ( Aquila chrysaetos ) in eastern North America. We determined factors associated with selection of perching (daytime) and roosting (nighttime) sites by eagles by comparing land cover and topographic characteristics of GPS telemetry locations for eagles (used) with random (available) locations. We separately assessed selection for perch and roost sites during each of 4 seasons (winter, summer, and spring and fall migration). Golden Eagles showed different selection patterns for perching by season and age. Throughout the year, eagles selected perch sites on steep slopes. The direction these slopes faced differed among seasons, with eagles selecting south-facing slopes in summer and east-facing slopes during migration. Adults showed greater preferences for broadleaf forests in summer and for ridges in fall. Patterns of perch-site use were consistent with selection for sites that provide thermal protection and access to thermal updrafts. We found few patterns of selection for roosting sites. Our analysis provides insight into decision-making by a longdistance migrant across its annual cycle and throughout its geographic range, and thus into how resource selection changes seasonally.

Wilson Journal of Ornithology↗
USGS2018

State‐space modelling of the flight behaviour of a soaring bird provides new insights to migratory strategies

Characterising the spatiotemporal variation of animal behaviour can elucidate the way individuals interact with their environment and allocate energy. Increasing sophistication of tracking technologies paired with novel analytical approaches allows the characterisation of movement dynamics even when an individual is not directly observable. In this study, high‐resolution movement data collected via global positioning system (GPS) tracking in three dimensions were paired with topographical information and used in a Bayesian state‐space model to describe the flight modes of migrating golden eagles ( Aquila chrysaetos ) in eastern North America. Our model identified five functional behavioural states, two of which were previously undescribed variations on thermal soaring. The other states comprised gliding, perching and orographic soaring. States were discriminated by movement features in the horizontal (step length and turning angle) and vertical (change in altitude) planes and by the association with ridgelines promoting wind deflection. Tracked eagles spent 2%, 31%, 38%, 9% and 20% of their daytime in directed thermal soaring, gliding, convoluted thermal soaring, perching and orographic soaring, respectively. The analysis of the relative occurrence of these flight modes highlighted yearly, seasonal, age, individual and sex differences in flight strategy and performance. Particularly, less energy‐efficient orographic soaring was more frequent in autumn, when thermals were less available. Adult birds were also better at optimising energy efficiency than subadults. Our approach represents the first example of a state‐space model for bird flight mode using altitude data in conjunction with horizontal locations and is applicable to other flying organisms where similar data are available. The ability to describe animal movements in a three‐dimensional habitat is critical to advance our understanding of the functional processes driving animals’ decisions.

Functional Ecology↗