The Ecological Time Machine: Towards an Understanding of Vegetation-Climate Relationships Across Scales

Anthropogenic climate change is threatening terrestrial ecosystems globally, with consequences for biodiversity, the provisioning of ecosystem services, and global biogeochemical cycling. Understanding the relationship between vegetation and climate is imperative for anticipating and mitigating the potential effects of global change on vegetation. Because of the long lifespans and slow demography of terrestrial vegetation, the climate-vegetation relationship must be examined over time scales relevant to long-lived vegetation. Additionally, accessible and equitable education is essential for the long-term sustainability of ecological research. In this dissertation, I investigate the climate-vegetation relationship across observational and long-term (centennial) time scales. I use a variety of methods, primarily mechanistic and statistical modeling, and data sources, including vegetation trait observations, tree ring chronologies, historical and contemporary vegetation inventories, and paleoecological reconstructions. In my dissertation, I also highlight opportunities for improving undergraduate education in ecology. In Chapter 2, I conduct a meta-analysis of functional traits in trees and lianas, two woody vegetation life forms common in the global tropics. I find that differences in hydraulic functional traits between life forms lead to different vulnerabilities to climate change, and conclude that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100. In Chapter 3, I investigate the availability and accessibility of ecological forecasting education. I find that there are persistent gaps in the topics taught at the undergraduate level and in where ecological forecasting courses are taught. This work serves as a baseline from which the ecological forecasting community can build towards more equitable and accessible educational opportunities. In Chapter 4, I quantify the vegetation-climate relationship over the last 2,000 years, to understand the extent to which vegetation was in equilibrium with climate. I find that while vegetation often was in equilibrium with climate, that were instances of abrupt vegetation change even when climate was stable. In Chapter 5, I use complementary historical and contemporary vegetation surveys to show the consequences of assuming that observations from one time period capture the full vegetation-environment relationship. I find that species distribution models fit to historical vegetation records are unable to predict the widespread conversion of savanna to forest between time periods. Finally, in Chapter 6, I use a forest ecosystem model and 50 years of aboveground biomass reconstructions as a case study for how model-data fusion can be used for ecological hypothesis testing. Specifically, I find that the strong climatic limitations to tree growth in the process model are inconsistent with our observations, highlighting an opportunity to update ecological hypotheses about climate-tree growth relationships.