The abundances of animals vary from year to year, sometimes quite dramatically, and these changes are often attributed to differences in weather patterns. However, it is often difficult to understand the many ways that seasonal changes in rainfall and temperature influence the reproduction, survival and movement patterns of organisms. This study uses grassland birds to understand the effect of weather patterns on populations directly and indirectly, through their effects on vegetation, food availability and predators. By focusing on migratory birds, this work explores the effects of weather pattern on populations at both the local and continental scale. Through the development of novel statistical tools to process multiple types of data, the project will generate insights critical to forecasting population declines and will provide a template that can be used in other systems. Because >96% of North America's tallgrass prairies have been converted, the project's findings and implications will be used to promote the long-term health of Great Plains ecosystems. This project will cross-train students in statistical and biological methods, engage local stake-holders and promote the appreciation of grassland ecosystems though public outreach opportunities.

This study will identify the key climatic drivers of population fluctuations in highly mobile animals by combining detailed, population studies with long-term community data in an integrative population modeling framework. This study will test predictions of multiple alternative drivers of local breeding-season abundance by identifying the direct physiological responses to weather by several bird species, including the Grasshopper Sparrows, Dickcissels, and Eastern Meadowlarks, and by examining the interactions between rainfall, fire, and grazing on plant, prey, and predator communities on these populations. This project explores the issue of scale, by using stable isotopes in feathers and geolocator data to examine the links between climate in non-breeding areas and breeding abundance in subsequent years. Finally, this study develops cutting-edge statistical methods that are needed to integrate disparate datasets and reconcile climate-population linkages at multiple scales. This work will be informed by and build upon four decades of data collected through the Long-Term Ecological Research program at Konza Prairie, Kansas.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Environmental Biology (DEB)
Type
Standard Grant (Standard)
Application #
1754491
Program Officer
Betsy Von Holle
Project Start
Project End
Budget Start
2018-08-01
Budget End
2022-07-31
Support Year
Fiscal Year
2017
Total Cost
$609,318
Indirect Cost
Name
Kansas State University
Department
Type
DUNS #
City
Manhattan
State
KS
Country
United States
Zip Code
66506