Forecasting population dynamics in changing environments

How will populations behave when the environment keeps changing?

Climate change is altering the means, variances, and temporal autocorrelations of the key abiotic factors that underlie species performance. Understanding how these changes will impact species’ long-term fates is a key challenge that must be resolved in order to effectively forecast and mitigate climate change-driven biodiversity loss. Predicting the fates of organisms with simple, short-lived life histories should be relatively straightforward: These species should persist as long as the birth rate is greater than or equal to the death rate across the full range of future climatic conditions. However, many organisms have complex life cycles that span multiple years with individual demographic rates differing by age, size, stage, or sex. These organisms will experience climatic conditions over their lifespans that will range from historic norms to entirely novel conditions. The ability of species with complex, perennial life cycles to persist under climate change will therefore depend on their ability to successfully exploit climatically favorable years and buffer against unfavorable years.

For more than a decade, we’ve collected annual, individual-level demographic data on the long-lived, dioecious plant Valeriana edulis across its broad elevation range near the Rocky Mountain Biological Laboratory. By fusing these long-term data with historic data and field experiments, we are building a demographic forecasting platform that grapples with the complexities of life history and the nature and pace of climate change. This will enable us to not only forecast the future size, composition, sex ratio, and fate of Valeriana populations, but confront these predictions with true out-of-sample observed data in future years. Inspired by this empirical work, we are developing theory to generalize our understanding of how populations behave under changing environmental conditions.

We’re enthusiastically representing population ecology in the Ecological Forecasting Initiative.

Collaborators:

• Kailen Mooney, UC Irvine
• Judy Soule, retired
• Tom Miller, Rice