OOS 47-9
Decomposing vegetation dynamics in ecosystem-model simulations and comparison with paleoecological observations

Wednesday, August 12, 2015: 4:20 PM
314, Baltimore Convention Center
Yao Liu, School of Natural Resources and the Environment, University of Arizona, Tucson, AZ
Christine R Rollinson, Earth and Environment, Boston University, Boston, MA
Michael Dietze, Earth and Environment, Boston University, Boston, MA
Benjamin Poulter, Biosphere, NASA GSFC, Greenbelt, MD
Tristan Quaife, Department of Meteorology, University of Reading, Reading, United Kingdom
Ann Raiho, Biological Sciences, University of Notre Dame
Dan M. Ricciuto, Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN
Kevin Schaefer, University of Colorado - Boulder, National Snow & Ice Data Center, Boulder, CO
Joerg Steinkamp, Biodiversity and Climate Research Centre, Senckenberg Gesellschaft für Naturforschung, Frankfurt, Germany
David J.P. Moore, School of Natural Resources and the Environment, University of Arizona, Tucson, AZ

Current ecosystems will likely undergo major composition shifts in response to changing climate and disturbance regimes. Forecasts of changes in plant distribution and abundance depend on an understanding of long-term vegetation dynamics, which is under-constrained in current terrestrial biosphere models. We ask the question: what are the most relevant ecological processes that control vegetation dynamics over multi-decadal to multi-centennial timescales. To address this, we 1) simulated vegetation changes at 6 sites in the northeastern United States over the past 1160 years using 7 terrestrial biosphere models (CLM4.5, CLM4.5-DGVM, ED2, LINKAGES, LPJ-GUESS, LPJ-wsl, and JULES) driven by common paleoclimatic drivers, 2) for each model, calculated the biomass growth and turnover rates (as well as establishment and mortality rates where appropriate) of the plant functional types (PFTs), 3) partitioned the calculated rates of growth and turnover/mortality into three major factors (climate, competition, and disturbance) and estimated the relative effect of each factor, and 4) estimated the growth and turnover rates from paleo-data (reconstructions of paleovegetation composition, paleoclimate, and fire) by assuming growth is similar for stands of a given composition.


First, we examined the effects of climate, competition, and disturbance on plant growth and turnover estimated from the simulations against plant-community theories (bioclimatic-niche limits, differential growth and mortality due to niche difference, temporal partitioning and storage effect, and disturbance). We found that vegetation composition in all models were sensitive to differential growth rates of PFTs under different climates. For models that incorporate bioclimatic envelopes, abrupt changes in composition were observed, because when the bioclimatic limit was crossed, a full mortality was often invoked. Temporal variability of climate had minor effects on community composition. Fire was important in determining the ecosystem composition, though fire regimes in some models didn’t vary significantly across climatic conditions and vegetation compositions (i.e. the vegetation to fire feedback is weak). Second, we found that vegetation-composition changes in the simulations were driven to a much greater degree by growth rate as opposed to by turnover/mortality, when compared with those in paleoecological records. In sum, our study suggest 1) we can use paleodata to better constrain the niche differences (limits and growth responses), and 2) dynamic turnover, fire, and possibly temporal partition are important processes controlling long-term vegetation dynamics, but not well implemented in contemporary ecosystem models.