Geology topics

Brian Millsap

Publications and source records attributed to Brian Millsap.

3 recordsLinked to original sources

USGS2023

A 37 K SNP array for the management and conservation of Golden Eagles (Aquila chrysaetos)

We describe the development of a custom 37 K Affymetrix Axiom myDesign single nucleotide polymorphism (SNP) array for a culturally and ecologically important apex predator, the golden eagle ( Aquila chrysaetos ). Using this SNP array, we performed population genomic analysis on 154 individuals of known natal localities and detected three genetic clusters that we designated as Taiga/High Arctic, Great Basin, and Rocky Mountains/Great Plains. Each of these clusters appears to display clinal variation within these geographic regions. After determining genetic structure, we performed an assignment test of 32 individuals, five of which were siblings of individuals used in the assessment of genetic structure, three had associated telemetry data, and the remaining individuals were of unknown natal locations. Using this array, four siblings were correctly assigned to the same geographic region as their sibling and the genetic assignment of the radio telemetered birds agreed with the expected movement patterns displayed by these individuals. For the remaining individuals, we were able to assign all but five individuals to one of the three genetic clusters. Our genetic assignments illustrates the utility of this SNP array to accurately assign most individuals to predesignated geographical regions. While further compiling genetic and other data types, we can increase the power of this tool for identifying those breeding populations that may need assistance due to anthropogenic stressors that negatively impact their population viability. The use of this genetic resource will help substantiate decisions by multiple conservation groups that seek to preserve the natural population structure of the golden eagle.

Conservation Genetics↗

USGS2022

Estimating allowable take for an increasing bald eagle population in the United States

Effectively managing take of wildlife resulting from human activities poses a major challenge for applied conservation. Demographic data essential to decisions regarding take are often expensive to collect and are either not available or based on limited studies for many species. Therefore, modeling approaches that efficiently integrate available information are important to improving the scientific basis for sustainable take thresholds. We used the prescribed take level (PTL) framework to estimate allowable take for bald eagles ( Haliaeetus leucocephalus ) in the conterminous United States. We developed an integrated population model (IPM) that incorporates multiple sources of information and then use the model output as the scientific basis for components of the PTL framework. Our IPM is structured to identify key parameters needed for the PTL and to quantify uncertainties in those parameters at the scale at which the United States Fish and Wildlife Service manages take. Our IPM indicated that mean survival of birds >1 year old was high and precise (0.91, 95% CI = 0.90–0.92), whereas mean survival of first-year eagles was lower and more variable (0.69, 95% CI = 0.62–0.78). We assumed that density dependence influenced recruitment by affecting the probability of breeding, which was highly imprecise and estimated to have declined from approximately 0.988 (95% CI = 0.985–0.993) to 0.66 (95% CI = 0.34–0.99) between 1994 and 2018. We sampled values from the posterior distributions of the IPM for use in the PTL and estimated that allowable take (e.g., permitted take for energy development, incidental collisions with human made structures, or removal of nests for development) ranged from approximately 12,000 to 20,000 individual eagles depending on risk tolerance and form of density dependence at the scale of the conterminous United States excluding the Southwest. Model-based thresholds for allowable take can be inaccurate if the assumptions of the underlying framework are not met, if the influence of permitted take is under-estimated, or if undetected population declines occur from other sources. Continued monitoring and use of the IPM and PTL frameworks to identify key uncertainties in bald eagle population dynamics and management of allowable take can mitigate this potential bias, especially where improved information could reduce the risk of permitting non-sustainable take.

Journal of Wildlife Management↗

USGS2016

Genetic structure and viability selection in the golden eagle (Aquila chrysaetos), a vagile raptor with a Holarctic distribution

Molecular markers can reveal interesting aspects of organismal ecology and evolution, especially when surveyed in rare or elusive species. Herein, we provide a preliminary assessment of golden eagle ( Aquila chrysaetos ) population structure in North America using novel single nucleotide polymorphisms (SNPs). These SNPs included one molecular sexing marker, two mitochondrial markers, 85 putatively neutral markers that were derived from noncoding regions within large intergenic intervals, and 74 putatively nonneutral markers found in or very near protein-coding genes. We genotyped 523 eagle samples at these 162 SNPs and quantified genotyping error rates and variability at each marker. Our samples corresponded to 344 individual golden eagles as assessed by unique multilocus genotypes. Observed heterozygosity of known adults was significantly higher than of chicks, as was the number of heterozygous loci, indicating that mean zygosity measured across all 159 autosomal markers was an indicator of fitness as it is associated with eagle survival to adulthood. Finally, we used chick samples of known provenance to test for population differentiation across portions of North America and found pronounced structure among geographic sampling sites. These data indicate that cryptic genetic population structure is likely widespread in the golden eagle gene pool, and that extensive field sampling and genotyping will be required to more clearly delineate management units within North America and elsewhere.

Conservation Genetics↗