A hierarchical analysis of tree growth across eastern US forests

Background/Question/Methods

Forest community composition is known to influence biogeochemical cycling, including the carbon cycle. In order to improve predictions of forest responses to climate change, extensive data on tree growth, mortality and recruitment are necessary. Tree rings provide us with the ability to assess growth responses of trees to their environment over time. To better understand tree growth in temperate forests, we established forest inventory plots in summer 2011 and 2012 at 10 sites across the eastern US and measured growth and mortality in adult trees and saplings. Our current analysis focuses on growth responses of adult trees, detected from tree rings, and utilizes hierarchical bayesian state-space modeling to understand how trees are responding to environmental covariates at multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes.Additionally, we have begun to develop a predictive model for tree growth.

Results/Conclusions

Initial analyses of tree cores indicate that there are site level differences in growth rates between species at all sites, with mid-successional species like Red Oak (Quercus rubra) tending to have the highest growth rates. The relationship between intraspecific growth rates and average temperature across a species' range is more unclear at this point. The most common species tend to show a positive relationship between average temperature and growth rate, however, the relationship of more rare species is not as clear. At the site level, there is evidence for synchrony in responses to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Using these results and growth responses to additional covariates (e.g. elevation, slope, aspect) a simple model of tree growth, which incorporates our observed effects at the individual, plot and site level has been constructed. Future work will incorporate landscape scale effects. This model will improve our understanding of how trees grow in response to their environment, improve our ability to make predictions about growth, and will inform future modeling efforts with the Ecosystem Demography model (ED2).