Thursday, August 6, 2009: 10:30 AM
San Miguel, Albuquerque Convention Center
Erica A.H. Smithwick1, Robert E. Keane2, Donald McKenzie3, Carol Miller4, Martin Simard5, Daniel M. Kashian6, Rachel Loehman2 and Donald A. Falk7, (1)Department of Geography, The Pennsylvania State University, University Park, PA, (2)Fire Sciences Lab, USDA Forest Service, Rocky Mountain Research Station, Missoula, MT, (3)Pacific Wildland Fire Sciences Lab, US Forest Service, Seattle, WA, (4)Aldo Leopold Wilderness Research Institute, USDA Forest Service, Rocky Mountain Research Station, Missoula, MT, (5)University of Wisconsin- Madison, Madison, WI, (6)Department of Biological Sciences, Wayne State University, Detroit, MI, (7)School of Natural Resources and the Environment, University of Arizona, Tucson, AZ
Background/Question/Methods Complex ecosystem dynamics emerge from the reciprocal interactions of disturbance, climate, and vegetation, and can have dramatic effects on ecosystem biogeochemistry. Ecosystem models can be used to forecast altered ecosystem biogeochemistry and function in complex systems, but it remains a challenge to unravel emergent behaviors that result from modeled spatially-interactive processes or modeled interactions of multiple disturbances. As a result, feedbacks of disturbance, climate, and vegetation on ecosystem biogeochemistry are a challenge in complex landscapes. A new modeling approach is needed that explores the extent to which disturbance, climate, and vegetation interact and the degree to which these interactions produce ecological “surprises.” We use the FIRE-BGC model in the central plateau of Yellowstone National Park to determine the extent to which climate would need to change to fundamentally alter ecosystem biogeochemistry, i.e., carbon storage and nitrogen cycling. Results/Conclusions
Predictions of future temperature and precipitation in Yellowstone varied considerably among IPCC models and these models on average overestimated temperature in the current period (1971-2000) by 1.5 degrees C compared to historical data. Moreover, average future temperature increases (2021-2100) varied between 2.5 and 4.3 degrees C depending on CO2 emissions scenario . Therefore, model approaches that simulate probability distributions of future climate scenarios are likely to be more helpful than raw IPCC data for complex landscapes. Our work also shows that earlier concepts that related disturbance to ecosystem biogeochemistry are powerful for guiding understanding of single disturbances, but are less helpful for understanding the consequences of multiple, interacting, non-linear processes. Specifically, we found that changes in ecosystem biogeochemistry are due to extreme climate events that alter fire-beetle interactions, rather than direct effects of climate or single disturbances. Finally, we conclude that heuristic modeling is critical to understand complex landscape biogeochemistry in the face of uncertainty in disturbance-climate interactions.
