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Slager, D. L.

Publications and source records attributed to Slager, D. L..

5 recordsLinked to original sources

Population-level migration modeling of North American birds through data integration with BirdFlow

BackgroundAccurate information on population-level movements of migratory animals is essential for understanding migration and for designing effective conservation strategies in a changing world. Yet such information remains scarce for most migratory species due to the effort and expense needed to collect data across their full distribution ranges. BirdFlow is a probabilistic modeling framework that infers population-level movements from weekly species distribution maps produced by the participatory science project eBird. However, BirdFlow models have only been tuned for a handful of species using high-resolution individual tracking data, which is not available for most migratory species. MethodsHere, we introduce a general tuning and evaluation framework for BirdFlow that enables the first large-scale integration of distributional and individual-level data to infer animal movement across continents and hundreds of migratory species, eliminating reliance on any single individual-tracking data source. By generalizing the BirdFlow model parametrization, we enable tuning and validation using multiple complementary data sources, including GPS tracks, banding recoveries, and radio telemetry data from the Motus Wildlife Tracking System. We investigate the efficacy of this approach by (1) investigating predictive performance compared to null models; (2) validating the biological plausibility of BirdFlow models by comparing movement properties such as route straightness, number of stopovers, and migration speed between model-generated routes and real movement tracks; and (3) comparing the performance of models tuned on species-specific movement data to models tuned using hyperparameters transferred from other species. ResultsOur results show that BirdFlow models produced by the new tuning framework achieve biologically realistic performance, even for prediction horizons of thousands of kilometers and several months. When species-specific data are unavailable, models can still be tuned using data from other phylogenetically adjacent species to achieve improved performance. ConclusionsBy integrating eBird Status & Trends abundance surfaces with data from banding recaptures, radio telemetry, and GPS tracking, we scale BirdFlow model to 153 North American migratory species, representing the first collection of continental-scale population-level movement and forecasting models. Species-specific tuning improves population-level movement forecasts, while taxonomically informed hyperparameter transfer supports the modeling of data-limited species. Overall, our work offers a foundation for more accurate predictions across hundreds of species for research in ecology and conservation, disease surveillance, aviation, and public outreach.

ecology↗

Active learnings impact on student course performance in STEM varies by type and intensity

We updated a recent meta-analysis of active learnings impact on student achievement in undergraduate STEM courses by following the same protocol to evaluate studies published from 2010-2017. We screened 1659 papers, coded 1294, and found 210 that met five pre-established inclusion criteria and six pre-established criteria for methodological quality. After further dropping 76 studies with no exam scores data, 134 of these studies contained data on student performance on identical or equivalent exams. We found that on average, active learnings effect size on exam scores was 0.519 {+/-} 0.049, meaning that when students are in active learning classes, they perform roughly half a standard deviation higher on an identical exam. Funnel plots and sensitivity analyses indicated that these results were not due to sampling bias. Active learning had a positive impact on student outcomes regardless of class size, course level, or STEM discipline, though there was heterogeneity in the effects. All of these results are very similar when compared to earlier meta-analyses, however increased resolution in the studies analyzed here revealed two novel results. First, student performance was significantly better in courses that employed high-intensity active learning, defined as students being on task at least two-thirds of class time, versus lower-intensities. Additionally, there was significant heterogeneity in efficacy across different types of active learning employed. These results suggest that most, if not all types of active learning are effective, and that when innovating in their classes, instructors should continually work to increase active learning intensity. We urge caution in interpreting the results on active learning types, however, and propose a preliminary framework for making more-sophisticated and reliable analyses of variation in course design. Finally, the evidence presented here for active learnings impact on student outcomes creates a strong foundation for faculty professional development and administration.

scientific communication and education↗

Seasonal and directional dispersal behavior in an ongoing dove invasion

The dispersal behavior that underlies range expansions can be difficult to study. Eurasian Collared-Doves have staged independent northwestward invasions across both Europe and North America, reaching carrying capacity in Europe but continuing to increase exponentially in the Americas, where their dispersal behavior remains enigmatic. I used citizen science observations to investigate Eurasian Collared-Dove dispersal behavior along the North American Pacific coast, a natural barrier to land-bird dispersal. Using coastal and pelagic observations, I assessed the seasonality and directionality of dispersal and its prevalence across years. Dispersal flights peaked in spring, like in Europe, and were north-biased, consistent with northwestward initial colonization. A non-significant trend of increasing dispersal across years may reflect evolution of dispersal via spatial sorting and selection. These results inform management of this invasive dove, raise new questions about evolutionary mechanisms behind the invasion, and exemplify using citizen science to study dispersal behavior, a longstanding challenge in ecology.

ecology↗

Cryptic and extensive hybridization between ancient lineages of American crows

Most species and therefore most hybrid zones have historically been described using phenotypic characters. However, both speciation and hybridization can occur with negligible morphological differentiation. The Northwestern Crow (Corvus caurinus) and American Crow (Corvus brachyrhynchos) are sister taxonomic species with a continuous distribution that lack reliable traditional characters for identification. In this first population genomic study of Northwestern and American crows, we use genomic SNPs (nuDNA) and mtDNA to investigate whether these crows are genetically differentiated and the extent to which they may hybridize. We found that American and Northwestern crows have distinct evolutionary histories, supported by two nuDNA ancestry clusters and two 1.1%-divergent mtDNA clades dating to the late Pleistocene, when glacial advances may have isolated crow populations in separate refugia. We document extensive hybridization, with geographic overlap of mtDNA clades and admixture of nuDNA across >1,400 km of western Washington and western British Columbia. This broad hybrid zone consists of late-generation hybrids and backcrosses, not recent (e.g., F1) hybrids. Nuclear DNA and mtDNA clines were both centered in southwestern British Columbia, farther north than previously postulated. The mtDNA cline was narrower than the nuDNA cline, consistent with Haldanes rule but not sex-biased dispersal. Overall, our results suggest a history of reticulate evolution in American and Northwestern crows, consistent with potentially recurring neutral expansion(s) from Pleistocene glacial refugia followed by lineage fusion(s). However, we do not rule out a contributing role for more recent potential drivers of hybridization, such as expansion into human-modified habitats.

evolutionary biology↗

A Migratory Divide In The Painted Bunting (Passerina ciris)

Divergence in migratory behavior is a potential mechanism of lineage divergence in sympatric populations and a key life history trait used in the identification of demographically independent units for conservation purposes. In the Painted Bunting (Passerina ciris), a North American songbird, populations on the Atlantic coast and interior southern United States are known to be allopatric during the breeding season, but efforts to map connectivity with wintering ranges in Mexico, Florida, and the Caribbean have been largely inconclusive. Using genomic and morphological data from natural history specimens and banded birds, we found evidence of three genetically differentiated populations with distinct wintering ranges and molt-migration phenologies. In addition to confirming that the Atlantic coast population remains allopatric throughout the annual cycle, we identified an unexpected migratory divide within the interior breeding range. Populations breeding in the Lower Mississippi River Valley winter on the Yucatan Peninsula, and are parapatric with other interior populations that winter in mainland Mexico and Central America. Across the interior breeding range, genetic ancestry is also associated with variation in wing length; suggesting that selective pressures may be promoting morphological divergence in populations with different migration strategies.

zoology↗