OOS 50-9 - Assimilation of tree-ring and repeat census data to model interactions between climate and past forest dynamics

Friday, August 11, 2017: 10:50 AM
Portland Blrm 256, Oregon Convention Center
Malcolm S. Itter Jr., Forestry, Michigan State University, East Lansing, MI, John B. Bradford, Southwest Biological Science Center, U.S. Geological Survey, Flagstaff, AZ, Anthony W. D'Amato, The Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, VT, Margaret E. K. Evans, Laboratory of Tree Ring Research, University of Arizona, Tucson, AZ, Andrew O. Finley, Forestry and Geography, Michigan State University, East Lansing, MI, Jane R. Foster, Department of Forest Resources, University of Minnesota, St. Paul, MN and Brian J. Palik, Northern Research Station, USDA Forest Service, Grand Rapids, MN
Background/Question/Methods

The frequency of extreme climate events (e.g., droughts) is expected to change over the next century. Managing forest ecosystems in the face of changing climatic conditions requires we understand interactions between climate and forest dynamics—changes in forest composition, density, size, age, and spatial structure over time. The role of forest dynamics in shaping forest responses to climate extremes is particularly important given forest dynamics can be modified through forest management. Analyses focused on modeling interactions between climate and forest dynamics face a data challenge. Tree rings provide sufficiently long records to model climate effects on growth, but provide little to no information on past forest dynamics. Repeat forest census data—periodic measurements of fixed sample plots—provide detailed measurements of forest growth, mortality, composition, and structure over time, but are rarely of sufficient length or resolution to understand forest responses to climate. We nested a stand-level growth and yield model within a Bayesian state space framework to assimilate tree-ring and repeat forest census data to model forest growth and mortality as a function of climate and forest dynamics. The state space model was applied to data from a long-term red pine thinning experiment in northern Minnesota.

Results/Conclusions

Forest growth and mortality varied over time in relation to forest development. Focusing on the effects of forest dynamics alone, mean mortality (basal area [BA] loss/acre/year) was greatest during the stem exclusion phase of development. Mean forest productivity (BA growth/acre/year) was greatest near the end of the stem exclusion phase as individual trees differentiated in canopy position. Climate data were converted to climatic water deficit, reflecting the interaction between temperature, precipitation, and soil water-holding capacity. Climatic water deficit was associated with reduced tree growth and increased mortality, on average, over the study period (1912-2012). Considering the interactive effects of climate and forest dynamics, climatic water deficit had the greatest effect on growth and mortality during the stem exclusion phase when density and inter-tree competition were high and during the transition to old-growth phase when a number of large diameter trees dominated the forest canopy. Results indicate red pine sensitivity to climatic water deficit may be increased by moderate-intensity thinning treatments that reduce stand density and maintain a uniform distribution of mid-sized canopy trees. Current work is focused on testing the effectiveness of different thinning strategies to reduce red pine sensitivity to climatic water deficit.