95th ESA Annual Meeting (August 1 -- 6, 2010)

OOS 35-9 - Modeled effect of warming on ecosystem carbon and water dynamics within grassland/old-field ecosystems along a moisture gradient

Wednesday, August 4, 2010: 4:20 PM
317-318, David L Lawrence Convention Center
Jana L. Heisler-White1, Jack Morgan2, William Parton3, John Blair4, Nona R. Chiariello5, Jeffrey S. Dukes6, Philip A. Fay7, Christopher Field8, Susanne S. Hoeppner6, Mark Hovenden9, Alan Knapp10, Yiqi Luo11, Shuli Niu12, Elise Pendall13 and Vidya Suseela14, (1)TriHydro, Inc, Laramie, WY, (2)Rangeland Resources Research Unit, USDA-ARS, Fort Collins, CO, (3)Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO, (4)Division of Biology, Kansas State University, Manhattan, KS, (5)Jasper Ridge Biological Preserve, Stanford University, Stanford, CA, (6)Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN, (7)Grassland, Soil & Water Research Laboratory, USDA, Agricultural Research Service, Temple, TX, (8)Stanford Woods Institute for the Environment, Stanford University, Stanford, CA, (9)Biological Sciences, School of Natural Sciences, University of Tasmania, Hobart, TAS, Australia, (10)Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO, (11)Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, (12)Department of Botany and Microbiology, University of Oklahoma, Norman, OK, (13)Botany, University of Wyoming, Laramie, WY, (14)School of Agricultural, Forest, and Environmental Sciences, Clemson University, Clemson, SC
Background/Question/Methods As a consequence of steadily increasing concentrations of greenhouse gases in Earth’s atmosphere, average world-wide surface temperature is expected to increase 1.5-6.4°C by the end of the 21st Century.  Results from manipulative field experiments and ecosystem modeling indicate that plants and soils will be influenced by these changes, however, a robust conceptual framework for understanding both the direct and indirect effects of warming on terrestrial ecosystems is currently lacking.  The goal of this project will be to use a terrestrial ecosystem model (DAYCENT) plus site weather and ecosystem data to explore the impacts of global warming on carbon and water dynamics within grassland and old field ecosystems.  This multi-site modeling exercise focuses on herbaceous plant communities along a mean annual precipitation gradient, and includes the Jasper Ridge Global Change Experiment, the Prairie Heating and CO2 Enrichment Experiment, the Oklahoma Global Climate Change Experiment, the Konza Prairie Warming Experiment, the Boston Area Climate Experiment, and the T-FACE experiment in the Qinghai-Tibet grassland.  We have chosen these sites because of their similar field experimental manipulations of temperature, which strengthens direct comparisons between experimental and modeling results.
The guiding research questions for this multi-site modeling exercise include:
1)      How does warming influence individual components of the ecosystem water budget (i.e. transpiration, runoff, evaporation, and infiltration) and subsequently soil moisture dynamics?
2)      How are net ecosystem productivity (NEP), net primary productivity (NPP), and soil respiration (Rh) affected by warming?  Does the magnitude of these impacts vary in some predictable way across the precipitation gradient?
3)      How do intra- and inter- annual variability in precipitation influence ecosystem carbon dynamics in response to warming?

In characterizing ecosystem responses along a dry to wet precipitation gradient, a primary interest is to focus on water as a “common denominator” or indirect effect of global warming across ecosystems where its relative degree of limitation varies.  However, we also know that temperature has important, more direct effects on the kinetics of C dynamics.  Our goal is to characterize these direct and indirect (water-induced) effects of temperature on C dynamics across a precipitation gradient represented in the warming experiments, and to use that knowledge to develop new constructs that will enhance our ability to predict how climate change will affect C cycling.