Geology topics

Andrea Contina

Publications and source records attributed to Andrea Contina.

3 recordsLinked to original sources

USGS2025

Dynamic environments generate geographic fluctuations in population structure of an inland shorebird

Species distributions depend on fine-scale ecological processes and population growth trajectories and are influenced by climate and weather changes. However, the characterization of inter-population dynamics underlying the geographic distributions of migratory organisms remains challenging. We adopted a stable isotope approach to investigate the dynamic population geography of a terrestrial migratory bird across multiple generations. We found that the age-specific geographic source of Mountain Plovers sampled during winter shifted over four years across a latitudinal gradient. Moreover, our results show that differential effects of climate on the probability of occurrence at the wintering ground could be a driver of population turnover in a migratory species adapted to extreme environmental stochasticity (i.e., drought occurrence). We propose a framework for the identification of spatial and temporal climate and weather components and respective effects on population composition and recruitment into migratory wintering populations. Our approach is useful to reveal population compositional shifts through hydrogen stable isotope analysis while accounting for cumulative drought effects.

Ecosphere↗

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↗

USGS2024

Asynchronous movement patterns between breeding and stopover locations in a long-distance migratory songbird

The species-specific migratory patterns and strategies of many songbirds remain unknown or understudied, as research in animal ecology is biased toward the breeding period, with the fewest studies on the migratory period across taxa. Identifying large-scale spatiotemporal migratory patterns is challenging, as individuals within a species may vary in their migratory behavior and strategies. The Yellow Warbler ( Setophaga petechia ) is a Nearctic-Neotropical migrant that is relatively well studied during the breeding season, but its species-wide migratory patterns remain understudied. Our aim in studying Yellow Warbler movement ecology was to characterize temporal migration patterns during fall migration. We sought to determine the temporal migration pattern among breeding locations, as determined by the hydrogen stable isotope values in feather samples collected at disjunct (~2000 km) stopover sites in the Gulf of Maine (n = 50) and the Gulf of Mexico (n = 150). We used a similarity matrix to group individuals into a geographic cluster by breeding location, which was then used as the response variable in a modeling analysis. Our results provide evidence that Yellow Warblers exhibit an asynchronous, type 1 temporal migration pattern with southern breeding populations initiating migration prior to northern populations. Using hydrogen isotopes, we identified the temporal migration patterns between geographic clusters, representing an individual’s breeding location, and stopover sites along the Gulf of Maine and Gulf of Mexico, which fills a gap in understanding Yellow Warbler migration ecology.

Avian Conservation and Ecology↗