Identification of human remains using Rapid DNA analysis.

Rapid identification of human remains following mass casualty events is essential to bring closure to family members and friends of the victims. Unfortunately, disaster victim identification, missing persons identification, and forensic casework analysis are often complicated by sample degradation due to exposure to harsh environmental conditions. Following a mass disaster, forensic laboratories may be overwhelmed by the number of dissociated portions that require identification and reassociation or compromised by the event itself. The interval between the disaster and receipt of victim samples at a laboratory is critical in that sample quality deteriorates as the postmortem interval increases. When bodies decompose due to delay in collection, transport, and sample processing, DNA becomes progressively fragmented, adversely impacting identification. We have previously developed a fully automated, field-forward Rapid DNA identification system that produces STR profiles (also referred to as DNA IDs or DNA fingerprints) from buccal and crime scene samples. The system performs all sample processing and data interpretation in less than 2 h. Here, we present results on Rapid DNA identification performed on several tissue types (including buccal, muscle, liver, brain, tooth, and bone) from exposed human bodies placed above ground or stored in a morgue/cooler, two scenarios commonly encountered following mass disasters. We demonstrate that for exposed remains, buccal swabs are the sample of choice for up to 11 days exposure and bone and tooth samples generated excellent DNA IDs for the 1-year duration of the study. For refrigerated remains, all sample types generated excellent DNA IDs for the 3-month testing period.

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.

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.

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.

Alternative workflows for identifying transnational missing persons.

Mass migration and migrant death at the U.S. southern border highlight the disconnectedness of the systems for transnational decedent identifications. Death investigation cases in Texas face delays and barriers at all stages of an investigation. Additionally, fragmentation of DNA databases exacerbate challenges in comparing genetic samples from unidentified human remains (UHR) and families of the missing. We sought to pilot alternative workflows for processing UHR and family reference samples (FRS) for the identification of probable migrant decedents. Primarily using Rapid DNA, but also accredited non-CODIS DNA laboratories, the piloted approaches were conducted in parallel to existing medicolegal workflows under the relevant case jurisdictional guidance. Our data show that Rapid DNA is a valid path for anthropology laboratories to support identification hypotheses and that accredited non-CODIS forensic and genetic laboratories also can support families to identify remains, especially when families reside outside of the United States.

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.

Developmental Validation of the ANDE 6C System for Rapid DNA Analysis of Forensic Casework and DVI Samples.

A developmental validation was performed to demonstrate reliability, reproducibility, and robustness of the ANDE Rapid DNA Identification System for processing of crime scene and disaster victim identification (DVI) samples. A total of 1705 samples were evaluated, including blood, oral epithelial samples from drinking containers, samples on FTA and untreated paper, semen, bone, and soft tissues. This study was conducted to address the FBI's Quality Assurance Standards on developmental validation and to accumulate data from a sufficient number of unique donors and sample types to meet NDIS submission requirements for acceptance of the ANDE Expert System for casework use. To date, no Expert System has been approved for such samples, but the results of this study demonstrated that the automated Expert System performs similarly to conventional laboratory data analysis. Furthermore, Rapid DNA analysis demonstrated accuracy, precision, resolution, concordance, and reproducibility that were comparable to conventional processing along with appropriate species specificity, limit of detection, performance in the presence of inhibitors. No lane-to-lane or run-to-run contamination was observed, and the system correctly identified the presence of mixtures. Taken together, the ANDE instrument, I-Chip consumable, FlexPlex chemistry (a 27-locus STR assay compatible with all widely used global loci, including the CODIS core 20 loci), and automated Expert System successfully processed and interpreted more than 1200 unique samples with over 99.99% concordant CODIS alleles. This extensive developmental validation data provides support for broad use of the system by agencies and accredited forensic laboratories in single-source suspect-evidence comparisons, local database searches, and DVI.

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.