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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #252665

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

Author
item HEISLER-WHITE, JANA - University Of Wyoming
item Morgan, Jack
item PARTON, WILLIAM - Colorado State University
item BLAIR, JOHN - Kansas State University
item CHIARIELLO, NONA - Stanford University
item DUKES, JEFFREY - Purdue University
item Fay, Philip
item FIELD, CHRISTOPHER - Carnegie Institute - Washington
item HOEPPNER, SUSANNE - Purdue University
item HOVENDEN, MARK - University Of Tasmania
item KNAPP, ALAN - Colorado State University
item LUO, YIQI - University Of Oklahoma
item NIU, SHULI - University Of Oklahoma
item PENDALL, ELISE - University Of Wyoming
item SUSEELA, VIDYA - Purdue University
item WANG, SHIPING - Chinese Academy Of Sciences

Submitted to: Ecological Society of America Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 5/11/2010
Publication Date: 8/1/2010
Citation: Heisler-White, J., Morgan, J.A., Parton, W., Blair, J., Chiariello, N., Dukes, J., Fay, P.A., Field, C., Hoeppner, S., Hovenden, M., Knapp, A., Luo, Y., Niu, S., Pendall, E., Suseela, V., Wang, S. 2010. Modeled effect of warming on ecosystem carbon and water dynamics within grassland/old-field ecosystems along a moisture gradient. In: Proceedings of the Ecological Society of America Abstracts, August 1-6, 2010, Pittsburgh, Pennsylvania. OOS 35-9.

Interpretive Summary:

Technical Abstract: 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, the T-FACE experiment in the Qinghai-Tibet grassland, and the TasFACE Global Change Experiment. 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.