Because of the slow pace of terrestrial ecosystem processes, including the slow generation time, growth rate, and decomposition rate of trees, the impact of changing climate and disturbance on forests plays out over hundreds of years. For this reason, terrestrial ecosystem models are used to anticipate the centennial scale projections of forest response to environmental change. Current terrestrial ecosystem model predictions vary widely and results have large statistical uncertainties. Furthermore, testing and calibration of these models relies on short term (sub-daily to decadal) data that fail to capture longer term trends and infrequent extreme events. The capacity of ecosystem models for scientific inference and long-term prediction would be greatly improved if uncertainties can be reduced through rigorous testing against observational data. PalEON is an interdisciplinary team of paleoecologists, statisticians, and modelers that have partnered to rigorously synthesize longer term paleoecological data and incorporate into ecosystem models to provide a deeper understanding of past dynamics and to use this knowledge to improve long-term forecasting capabilities.
Funds are provided to address four objectives and associated research questions: 1) Validation: How well do ecosystem models simulate decadal-to-centennial dynamics when confronted with past climate change, and what limits model accuracy? 2) Initialization: How sensitive are ecosystem models to initialization state and equilibrium assumptions? Do data-constrained simulations of centennial-scale dynamics improve 20thcentury simulations? 3) Inference: Was the terrestrial biosphere a carbon sink or source during the Little Ice Age and Medieval Climate Anomaly? and 4) Improvement: How can parameters and processes responsible for data-model divergences be improved? The data synthesis will include wide range of ecosystems, encompasses past climate variations that were large enough to affect tree growth rates, disturbance regimes, and forest demography, and leverages available paleodata. The synthesis will include 1) fossil pollen and Public Land Survey data to reconstruct forest composition, 2) sedimentary charcoal, stand-age and firescar indicators of past disturbance regimes, 3) tree-ring records of tree growth rates, and 4) multiple paleoclimatic proxies and paleoclimatic simulations. Bayesian hierarchical statistical models will be used to reconstruct key ecological variables and their associated uncertainty estimates. A standardized model intercomparison involving 13 ecosystem modeling groups will be used to evaluate the robustness of the modeling approach.
Three areas will be emphasized for PalEON's broader impacts. Community Building: The PalEON research community has doubled over the past 10 months, with more than 60 participants now. It is anticipated to nearly another doubling over the next five years, and the funds will allow the ongoing community-building via annual large meetings and task-oriented workshops. Interdisciplinary Training and Mentoring: A new generation of researchers will be trained to naturally conceptualize large spatial and temporal scales and to approach ecological forecasting as an integrative activity spanning data collection to model prediction. Eight postdocs and seven graduate students will be involved in proposed PalEON research, with multiple opportunities for cross-training. Additionally, the PalEON Summer Short Course provides an intensive cross-training experience for young scientists in all areas encompassed by PalEON. The 2012 course will be followed by courses in 2014 and 2016. Building Scientific Infrastructure: All PalEON datasets will be made publicly available upon publication, as will our new data-assimilation methods and model intercomparison protocols. Tools will be developed for optimal site selection (given the goal of reducing the integrated prediction uncertainty about past vegetation and climate over space and time) and will distribute a publicly available webtool version that will be linked directly to the Neotoma Paleoecology Database.
