Geographic origins and population genetics of bats killed at wind-energy facilities.

An unanticipated impact of wind-energy development has been large-scale mortality of insectivorous bats. In eastern North America, where mortality rates are among the highest in the world, the hoary bat (Lasiurus cinereus) and the eastern red bat (L. borealis) comprise the majority of turbine-associated bat mortality. Both species are migratory tree bats with widespread distributions; however, little is known regarding the geographic origins of bats killed at wind-energy facilities or the diversity and population structure of affected species. We addressed these unknowns by measuring stable hydrogen isotope ratios (δ2 H) and conducting population genetic analyses of bats killed at wind-energy facilities in the central Appalachian Mountains (USA) to determine the summering origins, effective size, structure, and temporal stability of populations. Our results indicate that ~1% of hoary bat mortalities and ~57% of red bat mortalities derive from non-local sources, with no relationship between the proportion of non-local bats and sex, location of mortality, or month of mortality. Additionally, our data indicate that hoary bats in our sample consist of an unstructured population with a small effective size (Ne ) and either a stable or declining history. Red bats also showed no evidence of population genetic structure, but in contrast to hoary bats, the diversity contained in our red bat samples is consistent with a much larger Ne that reflects a demographic expansion after a bottleneck. These results suggest that the impacts of mortality associated with intensive wind-energy development may affect bat species dissimilarly, with red bats potentially better able to absorb sustained mortality than hoary bats because of their larger Ne . Our results provide important baseline data and also illustrate the utility of stable isotopes and population genetics for monitoring bat populations affected by wind-energy development.

Cell-Type Composition Affects Adipose Gene Expression Associations With Cardiometabolic Traits.

Understanding differences in adipose gene expression between individuals with different levels of clinical traits may reveal the genes and mechanisms leading to cardiometabolic diseases. However, adipose is a heterogeneous tissue. To account for cell-type heterogeneity, we estimated cell-type proportions in 859 subcutaneous adipose tissue samples with bulk RNA sequencing (RNA-seq) using a reference single-nuclear RNA-seq data set. Cell-type proportions were associated with cardiometabolic traits; for example, higher macrophage and adipocyte proportions were associated with higher and lower BMI, respectively. We evaluated cell-type proportions and BMI as covariates in tests of association between >25,000 gene expression levels and 22 cardiometabolic traits. For >95% of genes, the optimal, or best-fit, models included BMI as a covariate, and for 79% of associations, the optimal models also included cell type. After adjusting for the optimal covariates, we identified 2,664 significant associations (P ≤ 2e-6) for 1,252 genes and 14 traits. Among genes proposed to affect cardiometabolic traits based on colocalized genome-wide association study and adipose expression quantitative trait locus signals, 25 showed a corresponding association between trait and gene expression levels. Overall, these results suggest the importance of modeling cell-type proportion when identifying gene expression associations with cardiometabolic traits.

Dispersal and Land Cover Contribute to Pseudorabies Virus Exposure in Invasive Wild Pigs.

We investigated the landscape epidemiology of a globally distributed mammal, the wild pig (Sus scrofa), in Florida (U.S.), where it is considered an invasive species and reservoir to pathogens that impact the health of people, domestic animals, and wildlife. Specifically, we tested the hypothesis that two commonly cited factors in disease transmission, connectivity among populations and abundant resources, would increase the likelihood of exposure to both pseudorabies virus (PrV) and Brucella spp. (bacterial agent of brucellosis) in wild pigs across the Kissimmee Valley of Florida. Using DNA from 348 wild pigs and sera from 320 individuals at 24 sites, we employed population genetic techniques to infer individual dispersal, and an Akaike information criterion framework to compare candidate logistic regression models that incorporated both dispersal and land cover composition. Our findings suggested that recent dispersal conferred higher odds of exposure to PrV, but not Brucella spp., among wild pigs throughout the Kissimmee Valley region. Odds of exposure also increased in association with agriculture and open canopy pine, prairie, and scrub habitats, likely because of highly localized resources within those land cover types. Because the effect of open canopy on PrV exposure reversed when agricultural cover was available, we suggest that small-scale resource distribution may be more important than overall resource abundance. Our results underscore the importance of studying and managing disease dynamics through multiple processes and spatial scales, particularly for non-native pathogens that threaten wildlife conservation, economy, and public health.

Stable hydrogen isotopes record the summering grounds of eastern red bats (Lasiurus borealis).

Bats face numerous threats associated with global environmental change, including the rapid expansion of wind-energy facilities, emerging infectious disease, and habitat loss. An understanding of the movement and migration patterns of these highly dispersive animals would help reveal how spatially localized the impacts from these threats are likely to be on bat populations, thus aiding in their conservation. Stable hydrogen isotope ratios (δ (2)H) can be used to infer regions where bats have foraged during the summer molt season, thus allowing an assessment of summering location and distance of movement of bats sampled during other times of year. However, a major impediment to the application of δ (2)H for inference of bat movements is that the relationship between δ (2)H of bat hair and precipitation tends to be species specific and is still unknown for some key species of conservation concern. We addressed this issue by using geo-referenced museum specimens to calibrate the relationship between δ (2)H of hair (δ (2)Hhair) and long-term δ (2)H of growing-season precipitation (δ (2)HGSprecip) at the site of collection for eastern red bats (Lasiurus borealis), one of the main species of bats experiencing large numbers of fatalities at wind-energy facilities in North America. Based on comparison of δ (2)Hhair and δ (2)HGSprecip values for males we estimated a period of molt of June 14-August 7. Within this period, male and female red bats exhibited a significant positive relationship between δ (2)Hhair and δ (2)HGSprecip. These results establish the relationship between δ (2)Hhair and δ (2)HGSprecip for red bats, which is necessary for the use of δ (2)Hhair to infer the movement and migration patterns of this important species. These results provide a critical resource to conservation biologists working to assess the impacts of environmental change on bat populations.

Genomic Resources Notes accepted 1 October 2013-30 November 2013.

This article documents the public availability of (i) genomic sequence data and 43 microsatellite loci for the bat species, Lasiurus borealis and Lasiurus cinereus, and (ii) complete mitochondrial and partial nuclear genomes for two jack species, Caranx ignobilis, Caranx melampygus.