Geology topics

Kristen Ruegg

Publications and source records attributed to Kristen Ruegg.

4 recordsLinked to original sources

USGS2025

Challenges and opportunities for data integration to improve estimation of migratory connectivity

Understanding migratory connectivity, or the linkage of populations between seasons, is critical for effective conservation and management of migratory wildlife. A growing number of tools are available for understanding where migratory individuals and populations occur throughout the annual cycle. Integration of the diverse measures of migratory movements can help elucidate migratory connectivity patterns with methodology that accounts for differences in sampling design, directionality, effort, precision and bias inherent to each data type. The R package MigConnectivity was developed to estimate population-specific connectivity and the range-wide strength of those connections. New functions allow users to integrate intrinsic markers, tracking and long-distance reencounter data, collected from the same or different individuals, to estimate population-specific transition probabilities (estTransition) and the range-wide strength of those transition probabilities (estStrength). We used simulation and real-world case studies to explore the challenges and limitations of data integration based on data from three migratory bird species, Painted Bunting ( Passerina ciris ), Yellow Warbler ( Setophaga petechia ) and Bald Eagle ( Haliaeetus leucocephalus ), two of which had bidirectional data. We found data integration is useful for quantifying migratory connectivity, as single data sources are less likely to be available across the species range. Furthermore, accurate strength estimates can be obtained from either breeding-to-nonbreeding or nonbreeding-to-breeding data. For bidirectional data, integration can lead to more accurate estimates when data are available from all regions in at least one season. The ability to conduct combined analyses that account for the unique limitations and biases of each data type is a promising possibility for overcoming the challenge of range-wide coverage that has been hard to achieve using single data types. The best-case scenario for data integration is to have data from all regions, especially if the question is range-wide or data are bidirectional. Multiple data types on animal movements are becoming increasingly available and integration of these growing datasets will lead to a better understanding of the full annual cycle of migratory animals.

Methods in Ecology and Evolution↗

USGS2023

Utilizing high-resolution genetic markers to track population-level exposure of migratory birds to renewable energy development

With new motivation to increase the proportion of energy demands met by zero-carbon sources, there is a greater focus on efforts to assess and mitigate the impacts of renewable energy development on sensitive ecosystems and wildlife, of which birds are of particular interest. One challenge for researchers, due in part to a lack of appropriate tools, has been estimating the effects from such development on individual breeding populations of migratory birds. To help address this, we utilize a newly developed, high-resolution genetic tagging method to rapidly identify the breeding population of origin of carcasses recovered from renewable energy facilities and combine them with maps of genetic variation across geographic space (called ‘genoscapes’) for five species of migratory birds known to be exposed to energy development, to assess the extent of population-level effects on migratory birds. We demonstrate that most avian remains collected were from the largest populations of a given species. In contrast, those remains from smaller, declining populations made up a smaller percentage of the total number of birds assayed. Results suggest that application of this genetic tagging method can successfully define population-level exposure to renewable energy development and may be a powerful tool to inform future siting and mitigation activities associated with renewable energy programs.

PLOS Sustainability and Transformation↗

USGS2022

Genetic assignment of fisheries bycatch reveals disproportionate mortality among Alaska Northern Fulmar breeding colonies

Global fisheries kill millions of seabirds annually through bycatch, but little is known about population-level impacts, particularly in species that form metapopulations. U.S. North Pacific groundfish fisheries catch thousands of Northern Fulmars ( Fulmarus glacialis rodgersii ) each year, making fulmars the most frequently caught seabird in federally managed U.S. fisheries. Here, we used genetic stock identification to assign 1,536 fulmars sampled as bycatch to one of four Alaska breeding colonies and quantified the similarity of bycatch locations at sea among colonies. We found disproportionately high bycatch from the Pribilof Islands (6% of metapopulation, 23% of bycatch), and disproportionately low bycatch from Chagulak Island (34% of metapopulation, 14% of bycatch). Overlap between fisheries and colony-specific foraging areas diverge more during the summer breeding season, leading to greater differences in bycatch susceptibility. Contemporary and historical gene flow likely contributes to low genetic differentiation among colonies (F ST = 0.003–0.01), yet these values may not represent present connectivity. Our findings illustrate how genetic stock identification can link at-sea threats to colonies and inform management to reduce bycatch from impacted colonies.

Alaska↗

USGS2021

Linking climate niches across seasons to assess population vulnerability in a migratory bird

Global loss of biodiversity has placed new urgency on the need to understand factors regulating species response to rapid environmental change. While specialists are often less resilient to rapid environmental change than generalists, species-level analyses may obscure the extent of specialization when locally adapted populations vary in climate tolerances. Until recently, quantification of the degree of climate specialization in migratory birds below the species level was hindered by a lack of genomic and tracking information, but recent technological advances have helped to overcome these barriers. Here we take a genome-wide genetic approach to mapping population-specific migratory routes and quantifying niche breadth within genetically distinct populations of a migratory bird, the willow flycatcher ( Empidonax traillii ), which exhibits variation in the severity of population declines across its breeding range. While our sample size is restricted to the number of genetically distinct populations within the species, our results support the idea that locally adapted populations of the willow flycatcher with narrow climatic niches across seasons are already federally listed as endangered or in steep decline, while populations with broader climatic niches have remained stable in recent decades. Overall, this work highlights the value of quantifying niche breadth within genetically distinct groups across time and space when attempting to understand the factors that facilitate or constrain the response of locally adapted populations to rapid environmental change.

Global Change Biology↗