Extreme heterogeneity of population response to climatic variation and the limits of prediction. (13th March 2019)

• Record Type: Journal Article
• Authors: Nice, Chris C.; Forister, Matthew L.; Harrison, Joshua G.; Gompert, Zachariah; Fordyce, James A.; Thorne, James H.; Waetjen, David P.; Shapiro, Arthur M.
• Is Part Of: Global change biology. Volume 25:Number 6(2019)
• Page Start: 2127
• Page End: 2136
• Publication Date: 2019-03-13
• Subjects: Bayesian hierarchical model -- climate change -- long‐term data -- monitoring -- weather; Climatic changes -- Environmental aspects -- Periodicals; Troposphere -- Environmental aspects -- Periodicals; Biodiversity conservation -- Periodicals; Eutrophication -- Periodicals; 551.5
• DOI: 10.1111/gcb.14593
• Languages: English
• ISSNs: 1354-1013

Abstract

Abstract: Certain general facets of biotic response to climate change, such as shifts in phenology and geographic distribution, are well characterized; however, it is not clear whether the observed similarity of responses across taxa will extend to variation in other population‐level processes. We examined population response to climatic variation using long‐term incidence data (collected over 42 years) encompassing 149 butterfly species and considerable habitat diversity (10 sites along an elevational gradient from sea level to over 2, 700 m in California). Population responses were characterized by extreme heterogeneity that was not attributable to differences in species composition among sites. These results indicate that habitat heterogeneity might be a buffer against climate change and highlight important questions about mechanisms maintaining interpopulation differences in responses to weather. Despite overall heterogeneity of response, population dynamics were accurately predicted by our model for many species at each site. However, the overall correlation between observed and predicted incidence in a cross validation analysis was moderate (Pearson's r = 0.23, SE 0.01), and 97% of observed data fell within the predicted 95% credible intervals. Prediction was most successful for more abundant species as well as for sites with lower annual turnover. Population‐level heterogeneity in response to climate variation and the limits of our predictive power highlight the challenges for a future of increasing climatic variability. Abstract : Analyses of 42 years of butterfly observations at 10 sites along a transect in northern California from sea level to above tree‐line (top panel) revealed extreme heterogeneity in responses to inter‐annual variation in a variety of weather variables such as Spring Pecipitation (middle panel). Our model's predictive ability declined for sites with higher year‐to‐year species turnover (bottom panel) and for rarer species (not shown). These results highlight challenges for a future of increasing climatic variability.