Predicting the spatial distribution of wintering golden eagles to inform full annual cycle conservation in western North America.

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.

Effects of Selection for Mass-Independent Maximal Metabolic Rate on Food Consumption.

Metabolic rates potentially regulate the pace of important physiological and life-history traits. Natural selection has shaped the evolution of metabolic rates and the physiology that supports them, including digestibility and the rate of food consumption. Understanding the relationship between metabolic rates and energy internalization is central to understanding how resources are allocated among competing physiological functions. We investigated how artificial selection on mass-independent basal metabolic rate (BMR) and mass-independent aerobic maximal metabolic rate (MMR) affected food consumption and apparent digestibility in mice. Evolved changes in mass-corrected BMR-but not mass-corrected MMR-corresponded with changes in food consumption. This result is consistent with previous work showing that BMR constitutes a large portion of an animal's daily energy budget and thus that BMR might provide a better indicator of daily food requirements than MMR. In contrast, digestive efficiencies did not differ among selection treatments and did not evolve in these mice. This study provides insights into how evolution of metabolic rates may affect food consumption and overall energy use.

Modeling spatial variation in density of golden eagle nest sites in the western United States.

In order to contribute to conservation planning efforts for golden eagles (Aquila chrysaetos) in the western U.S., we developed nest site models using >6,500 nest site locations throughout a >3,483,000 km2 area of the western U.S. We developed models for twelve discrete modeling regions, and estimated relative density of nest sites for each region. Cross-validation showed that, in general, models accurately estimated relative nest site densities within regions and sub-regions. Areas estimated to have the highest densities of breeding golden eagles had from 132-2,660 times greater densities compared to the lowest density areas. Observed nest site densities were very similar to those reported from published studies. Large extents of each modeling region consisted of low predicted nest site density, while a small percentage of each modeling region contained disproportionately high nest site density. For example, we estimated that areas with relative nest density values <0.3 represented from 62.8-97.8% ([Formula: see text] = 82.5%) of each modeling area, and those areas contained from 14.7-30.0% ([Formula: see text] = 22.1%) of the nest sites. In contrast, areas with relative nest density values >0.5 represented from 1.0-12.8% ([Formula: see text] = 6.3%) of modeling areas, and those areas contained from 47.7-66.9% ([Formula: see text] = 57.3%) of the nest sites. Our findings have direct application to: 1) large-scale conservation planning efforts, 2) risk analyses for land-use proposals such as recreational trails or wind power development, and 3) identifying mitigation areas to offset the impacts of human disturbance.

Speeding up Growth: Selection for Mass-Independent Maximal Metabolic Rate Alters Growth Rates.

Investigations into relationships between life-history traits, such as growth rate and energy metabolism, typically focus on basal metabolic rate (BMR). In contrast, investigators rarely examine maximal metabolic rate (MMR) as a relevant metric of energy metabolism, even though it indicates the maximal capacity to metabolize energy aerobically, and hence it might also be important in trade-offs. We studied the relationship between energy metabolism and growth in mice (Mus musculus domesticus Linnaeus) selected for high mass-independent metabolic rates. Selection for high mass-independent MMR increased maximal growth rate, increased body mass at 20 weeks of age, and generally altered growth patterns in both male and female mice. In contrast, there was little evidence that the correlated response in mass-adjusted BMR altered growth patterns. The relationship between mass-adjusted MMR and growth rate indicates that MMR is an important mediator of life histories. Studies investigating associations between energy metabolism and life histories should consider MMR because it is potentially as important in understanding life history as BMR.

Selection for increased mass-independent maximal metabolic rate suppresses innate but not adaptive immune function.

Both appropriate metabolic rates and sufficient immune function are essential for survival. Consequently, eco-immunologists have hypothesized that animals may experience trade-offs between metabolic rates and immune function. Previous work has focused on how basal metabolic rate (BMR) may trade-off with immune function, but maximal metabolic rate (MMR), the upper limit to aerobic activity, might also trade-off with immune function. We used mice artificially selected for high mass-independent MMR to test for trade-offs with immune function. We assessed (i) innate immune function by quantifying cytokine production in response to injection with lipopolysaccharide and (ii) adaptive immune function by measuring antibody production in response to injection with keyhole limpet haemocyanin. Selection for high mass-independent MMR suppressed innate immune function, but not adaptive immune function. However, analyses at the individual level also indicate a negative correlation between MMR and adaptive immune function. By contrast BMR did not affect immune function. Evolutionarily, natural selection may favour increasing MMR to enhance aerobic performance and endurance, but the benefits of high MMR may be offset by impaired immune function. This result could be important in understanding the selective factors acting on the evolution of metabolic rates.

Estimating Raptor Nesting Success: Old and New Approaches.

Studies of nesting success can be valuable in assessing the status of raptor populations, but differing monitoring protocols can present unique challenges when comparing populations of different species across time or geographic areas. We used large datasets from long-term studies of 3 raptor species to compare estimates of apparent nest success (ANS, the ratio of successful to total number of nesting attempts), Mayfield nesting success, and the logistic-exposure model of nest survival. Golden eagles (Aquila chrysaetos), prairie falcons (Falco mexicanus), and American kestrels (F. sparverius) differ in their breeding biology and the methods often used to monitor their reproduction. Mayfield and logistic-exposure models generated similar estimates of nesting success with similar levels of precision. Apparent nest success overestimated nesting success and was particularly sensitive to inclusion of nesting attempts discovered late in the nesting season. Thus, the ANS estimator is inappropriate when exact point estimates are required, especially when most raptor pairs cannot be located before or soon after laying eggs. However, ANS may be sufficient to assess long-term trends of species in which nesting attempts are highly detectable.