The future demographic niche of a declining grassland bird fails to shift poleward in response to climate change
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Temperate grasslands and their dependent species are exposed to high variability in weather and climate due to the lack of natural buffers such as forests. Grassland birds are particularly vulnerable to this variability, yet have failed to shift poleward in response to recent climate change like other bird species in North America. However, there have been few studies examining the effect of weather on grassland bird demography and consequent influence of climate change on population persistence and distributional shifts.
The goal of this study was to estimate the vulnerability of Henslow’s Sparrow (Ammodramus henslowii), an obligate grassland bird that has been declining throughout much of its range, to past and future climatic variability.
We conducted a demographic meta-analysis from published studies and quantified the relationship between nest success rates and variability in breeding season climate. We projected the climate-demography relationships spatially, throughout the breeding range, and temporally, from 1981 to 2050. These projections were used to evaluate population dynamics by implementing a spatially explicit population model.
We uncovered a climate-demography linkage for Henslow’s Sparrow with summer precipitation, and to a lesser degree, temperature positively affecting nest success. We found that future climatic conditions—primarily changes in precipitation—will likely contribute to reduced population persistence and a southwestward range contraction.
Future distributional shifts in response to climate change may not always be poleward and assessing projected changes in precipitation is critical for grassland bird conservation and climate change adaptation.
KeywordsClimate change vulnerability assessment Demographic modeling Grassland birds Nest success Poleward shift Precipitation Species distribution modeling
This work was funded by the Northeast Climate Science Center. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Online Appendix 3 of this paper) for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank our scientific advisory board, J. Herkert, S. Hull, D. King, K Koch, M. Knutson, D. Lorenz, R. Renfrew, D. Rugg, D. Sample, S. Skagen, G. White, and T. Will, for their input as we developed our models. We thank W. Thogmartin, two anonymous reviewers, and Associate Editor C. Wilsey for their comments on earlier drafts of this manuscript. We thank N. Schumaker for guidance in developing the spatially explicit population models in HexSim. We thank the University of Wisconsin Madison Department of Forest and Wildlife Ecology for help with publication expenses. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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