Published June 8, 2023 | Version v1
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Winter range shifts and their associations with species traits are heterogeneous in eastern North American birds

  • 1. University of North Carolina at Asheville
  • 2. United States Department of Agriculture

Description

Many species' distributions are shifting in response to climate change. Many distributional shifts are predictably poleward or higher in elevation, but heterogeneity in the rate and direction of shifts both within and between species appears to be common. We found high heterogeneity in the trajectory of winter range shifts for 65 species of birds across eastern North America and in the different traits and trait interactions associated with these shifts across the spatial scales we examined. We used data from the Christmas Bird Count to quantify the trajectory of winter latitudinal center of abundance range shifts over four decades (1980–2019) for 65 species of songbirds and woodpeckers in North America, both across eastern North America (ENA) as a whole and for the Atlantic (ATL) and Mississippi (MISS) flyways separately. We then used linear models and AICc model selection to test whether species traits could explain variation in range shifts or flyway discrepancies. Across ENA, most species showed northward latitudinal range shifts, but some showed no latitudinal shift while others shifted southwards. Amongst ATL and MISS, we documented both within- and between-species differences in the rate and direction of latitudinal shifts, complicating the results from across ENA. No single trait emerged as a dominant driver of range shift differences at the ENA and flyway scales. Migration strategy interacted with insectivory to explain variation at the largest spatial scale (ENA), whereas frugivory and mean winter latitude explained much of the variation in ATL and MISS, respectively. Exploring heterogeneity in range shifts within and between species, and in the associations between range shifts and life history traits, will help us better understand the mechanisms that mediate differing responses to environmental change and predict which species will be better able to adapt to those changes.

Notes

To calculate the LCA of each species for each year and flyway, we calculated the geographic mean of all CBC circles with that species present that year, weighted by the relative abundance of that species in each circle, using the R package geosphere (Hijmans et al. 2019).

Model selection and assessment of overall variable importance (i.e., the summed Akaike weights (Σwi) of all models that included the variable) were performed using the MuMIn package in R (Barton 2022). The glms and all other numerical analyses described above were performed in R version 4.0.5 (R Core Team 2021).

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Related works

Is source of
10.5061/dryad.4j0zpc8hq (DOI)