Shifting correlations among multiple aspects of weather complicate predicting future demography of a threatened species

• Published in: Ecosphere (Washington, D.C) D.C), 2021-09, Vol.12 (9), p.n/a
• Main Authors: Louthan, Allison M., Walters, Jeffrey R., Terando, Adam J., Garcia, Victoria, Morris, William F.
• Format: Article
• Language: English
• Subjects: Adults; Birds; Climate change; Climate effects; correlation; Demography; directional trend; Ecological effects; Endangered & extinct species; Generalized linear models; Growth rate; Population growth; Precipitation; Rain; Threatened species; Trends; Variables; vital rate; Weather
• ISSN: 2150-8925; 2150-8925
• DOI: 10.1002/ecs2.3740

Most studies of the ecological effects of climate change consider only a limited number of weather drivers that could affect populations, though we know that multiple weather drivers can simultaneously affect population growth rate. Multiple drivers could simultaneously increase/decrease one vital rate, or one may increase a vital rate while another decreases the same vital rate. Considering the impact of multiple weather drivers on vital rates is particularly important in a changing climate, in which correlations among drivers may not be preserved in the future. We used a long‐term dataset on the endangered red‐cockaded woodpecker (Dryobates borealis) to understand how multiple weather drivers jointly affect survival and reproductive vital rates and then assessed the contributions of individual weather drivers to historical trends in vital rates over time. We found that vital rates were often influenced by more than one weather driver and that weather drivers most commonly exerted opposing effects. For instance, some weather drivers increased vital rates over time, while others acted in the opposite direction, decreasing vital rates over time. Importantly, the historical correlations among weather drivers are almost always projected to change in the future climate, such that future trends in vital rates may not match historical trends. For example, we do not find historical trends in adult survival, but changing correlations among weather drivers could generate future trends in this vital rate. Our work provides an example of how multiple weather drivers can control a variety of vital rates and also illustrates how changes in the correlation structure of weather drivers through time might substantially affect future trends in individual and population performance.