Tropical forests contain > 50% of the world’s known species (Heywood 1995), 55% of global forest biomass (Pan et al. 2011), and exchange more carbon (C), water and energy with the atmosphere than any other ecosystem type (e.g., Saugier et al. 2001). Despite their importance, there is more uncertainty associated with predictions of how tropical forests will respond to warming than for any other biome (Randerson et al. 2009). This uncertainty is of global concern due to the large quantity of C cycled by these forests and the high potential for biodiversity loss. Given the importance of tropical forests, decision makers and land managers around the globe need increased predictive capacity regarding how tropical forests will respond to climatic change.
Here we propose a set of workshops designed to bring together modelers and empiricists to evaluate and compare predictions of tropical forest response to increased temperature at a variety of temporal and spatial scales. First, we will model and critically evaluate the responses of a range of tropical forest sites to increased temperature using a selection of models that operate at multiple scales and specialize in different processes. Results will greatly help constrain expected tropical forest responses and will be used to generate hypotheses for a future tropical forest warming experiment in Puerto Rico. Second, we will develop strategies and proposals with the goal of linking three finer-scale models to a larger, global-scale model in order to improve the predictive capacity of the global-scale model. Instead of collecting new data or focusing on a single model, these workshops will build upon current knowledge to amass existing datasets and take advantage of a suite of models. Exceptional scientists in the appropriate fields have agreed to participate in these meetings. The Powell Center is the perfect venue for this endeavor due to its focus on facilitating data synthesis and cross-disciplinary scientific communication. The US Forest Service and INTERFACE (a NSF Research Coordination Network) also strongly support the meetings.
Principal Investigator(s):
Sasha C Reed (Canyonlands Field Station, SBSC)
Tana Wood (U.S. Forest Service)
Molly Cavaleri (Michigan Tech)
Participant(s):
Shinichi Asao (Colorado State University)
Bill Bauerle (Colorado State University)
Deborah Clark (University of Missouri)
Adam Coble (Michigan Tech)
Shelley Crausbay (Colorado State University)
Rosie Fisher (National Center for Atmospheric Research (NCAR))
Ariel E Lugo (U.S. Department of Agriculture)
Yadvinder Malhi (University of Oxford)
Patrick Martin (Colorado State University)
Richard Norby (Oak Ridge National Laboratory)
Bill Parton (Colorado State University)
Wilfred M Post (Oak Ridge National Laboratory)
Peter B. Reich (University of Minnesota)
Michael Ryan (Colorado State University)
Bill Smith (University of Minnesota)
Peter E. Thornton (Climate Change Science Institute)
Maria Uriarte (Columbia University)
Anthony P. Walker (Oak Ridge National Laboratory)
Xiaojuan Yang (Climate Change Science Institute)
- Source: USGS Sciencebase (id: 5266a3c4e4b0992695a7fbfd)
- Overview
Tropical forests contain > 50% of the world’s known species (Heywood 1995), 55% of global forest biomass (Pan et al. 2011), and exchange more carbon (C), water and energy with the atmosphere than any other ecosystem type (e.g., Saugier et al. 2001). Despite their importance, there is more uncertainty associated with predictions of how tropical forests will respond to warming than for any other biome (Randerson et al. 2009). This uncertainty is of global concern due to the large quantity of C cycled by these forests and the high potential for biodiversity loss. Given the importance of tropical forests, decision makers and land managers around the globe need increased predictive capacity regarding how tropical forests will respond to climatic change.
Here we propose a set of workshops designed to bring together modelers and empiricists to evaluate and compare predictions of tropical forest response to increased temperature at a variety of temporal and spatial scales. First, we will model and critically evaluate the responses of a range of tropical forest sites to increased temperature using a selection of models that operate at multiple scales and specialize in different processes. Results will greatly help constrain expected tropical forest responses and will be used to generate hypotheses for a future tropical forest warming experiment in Puerto Rico. Second, we will develop strategies and proposals with the goal of linking three finer-scale models to a larger, global-scale model in order to improve the predictive capacity of the global-scale model. Instead of collecting new data or focusing on a single model, these workshops will build upon current knowledge to amass existing datasets and take advantage of a suite of models. Exceptional scientists in the appropriate fields have agreed to participate in these meetings. The Powell Center is the perfect venue for this endeavor due to its focus on facilitating data synthesis and cross-disciplinary scientific communication. The US Forest Service and INTERFACE (a NSF Research Coordination Network) also strongly support the meetings.
Principal Investigator(s):
Sasha C Reed (Canyonlands Field Station, SBSC)
Tana Wood (U.S. Forest Service)
Molly Cavaleri (Michigan Tech)Participant(s):
Shinichi Asao (Colorado State University)
Bill Bauerle (Colorado State University)
Deborah Clark (University of Missouri)
Adam Coble (Michigan Tech)
Shelley Crausbay (Colorado State University)
Rosie Fisher (National Center for Atmospheric Research (NCAR))
Ariel E Lugo (U.S. Department of Agriculture)
Yadvinder Malhi (University of Oxford)
Patrick Martin (Colorado State University)
Richard Norby (Oak Ridge National Laboratory)
Bill Parton (Colorado State University)
Wilfred M Post (Oak Ridge National Laboratory)
Peter B. Reich (University of Minnesota)
Michael Ryan (Colorado State University)
Bill Smith (University of Minnesota)
Peter E. Thornton (Climate Change Science Institute)
Maria Uriarte (Columbia University)
Anthony P. Walker (Oak Ridge National Laboratory)
Xiaojuan Yang (Climate Change Science Institute)- Source: USGS Sciencebase (id: 5266a3c4e4b0992695a7fbfd)
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