B12C:
Quantifying Uncertainties and Merging Observations, Experiments, and Models for Improving Estimation, Mapping, and Forecasting of Terrestrial Ecosystem Dynamics II

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Session ID#: 15457

Session Description:
Terrestrial Biosphere Models (TBMs) are crucial tools in global carbon cycle studies, but the ecosystem processes they represent are many and complex, therefore being among the greatest uncertainty sources in future climate projections. Evaluating and improving these important TBM processes requires both data from ecosystem scale experiments (e.g. CO2 and temperature manipulation) and specific statistical methods to incorporate that data into the models (e.g. Bayesian data assimilation). Both of these aspects are important and can rarely be separated from each other as the experimental data determines the appropriate mathematical approach.

This session focuses on novel insights into TBM processes gained from both experimentals and the numerical techniques used to assimilate the data in to the models. We encourage submissions that address the challenge of improving model representation of ecosystems through both experimental data and advanced numerical methods, although studies focusing on just experiments or mathematical methods are also welcomed.

Primary Convener:  Cove Sturtevant, National Ecological Observatory Network, Battelle, Boulder, United States
Conveners:  Toni Viskari1, John L Campbell2 and Michael Dietze1, (1)Boston University, Boston, MA, United States(2)US Forest Service, Northern Research Station, Durham, United States
Chairs:  Toni Viskari, Boston University, Boston, MA, United States, Ankur R Desai, University of Wisconsin Madison, Atmospheric and Oceanic Sciences, Madison, WI, United States, Ruth D. Yanai, SUNY College of Environmental Science and Forestry, Syracuse, NY, United States and Chabbi Abad, INRA Institut National de la Recherche Agronomique, Paris Cedex 07, France
OSPA Liaison:  Cove Sturtevant, National Ecological Observatory Network, Battelle, Boulder, United States
Index Terms:

0430 Computational methods and data processing [BIOGEOSCIENCES]
0439 Ecosystems, structure and dynamics [BIOGEOSCIENCES]
0452 Instruments and techniques [BIOGEOSCIENCES]
0466 Modeling [BIOGEOSCIENCES]

Abstracts Submitted to this Session:

On the nature of prediction in ecology (Invited) (125468)
Michael Dietze, Boston University, Boston, MA, United States
Evaluating Productivity Predictions Under Elevated CO2 Conditions: Multi-Model Benchmarking Across FACE Experiments (186792)
Elizabeth Cowdery and Michael Dietze, Boston University, Boston, MA, United States
Moving across scales: Challenges and opportunities in upscaling carbon fluxes (Invited) (118727)
Kusum J. Naithani, University of Arkansas, Department of Biological Sciences, Fayetteville, AR, United States
Accounting for "Ecoclimate Teleconnections" that structure ecological responses to disturbance and climate, from local to global scales (192267)
Scott R Saleska1, Elizabeth Garcia2, Scott C Stark3, Juan Camilo Villegas4, David D Breshears5, Abigail L. S. Swann6, David JP Moore5, Darin Law5, David Minor7 and Jason P Field5, (1)University of Arizona, Department of Ecology & Evolutionary Biology, Tucson, AZ, United States, (2)University of Washington Seattle Campus, Seattle, WA, United States, (3)Michigan State University, Department of Forestry, East Lansing, MI, United States, (4)Universidad de Antioquia, Antioquia, Medellín, Colombia, (5)University of Arizona, School of Natural Resources and the Environment, Tucson, AZ, United States, (6)University of Washington, Department of Atmospheric and Climate Science and Department of Biology, Seattle, United States, (7)Michigan State University, East Lansing, MI, United States
Combining Ecosystem Observations, Manipulations and the Data Assimilation Research Testbed to Provide New Insights into Community Land Model Performance (185412)
Andrew M Fox, NASA Goddard Space Flight Center, Greenbelt, United States, Timothy Hoar, National Center for Atmospheric Research, Boulder, CO, United States, Marcy E Litvak, University of New Mexico, Department of Biology, Albuquerque, United States and David JP Moore, University of Arizona, School of Natural Resources and the Environment, Tucson, AZ, United States
Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation (143123)
Istem Fer, Boston University, Earth and Environment, Boston, MA, United States, Ryan Kelly, Neptune and Company, Lakewood, CO, United States, Travis Andrews, Lehigh U., Bethlehem, PA, United States, Michael Dietze, Boston University, Boston, MA, United States and Andrew D Richardson, School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA; Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA, Cambridge, United States
Quantifying the impacts of parametric uncertainty at FLUXNET sites in the ACME land model (Invited) (194673)
Daniel M Ricciuto, Oak Ridge National Laboratory, Climate Change Science Institute, Oak Ridge, TN, United States, Khachik Sargsyan, Sandia National Laboratories, Albuquerque, NM, United States and Peter E Thornton, Oak Ridge National Laboratory, Environmental Sciences Division, Oak Ridge, United States
From Small Forest Inventory Plots to Regional Biomass Estimates: Dealing with Uncertainty from Inventory Sampling by Focusing on Trees Instead of Biomass (194678)
Bradley Tomasek1, Erin M Schliep2, Alan E. Gelfand1 and James S Clark3, (1)Duke University, Durham, NC, United States, (2)University of Missouri Columbia, Columbia, United States, (3)Duke University, Nicholas School of Environment, Department of Statistical Science, Durham, NC, United States

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