OOS 46-8 - Integrating biodiversity estimation into the EPIC model

Friday, August 12, 2011: 10:30 AM
16B, Austin Convention Center
Ritvik Sahajpal1, Timothy D. Meehan2, R. Cesar Izaurralde3, David Manowitz4, Xuesong Zhang3, Claudio Gratton5, Ben P. Werling6 and Douglas A. Landis7, (1)Geography, University of Maryland College Park, (2)The Nature Conservancy, Boulder, CO, (3)Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, MD, (4)Pacific Northwest National Laboratory, (5)Department of Entomology, University of Wisconsin - Madison, Madison, WI, (6)Entomology, Michigan State University, East Lansing, MI, (7)Center for Integrated Plant Systems Lab, Michigan State University, East Lansing, MI
Background/Question/Methods

Biofuels are widely considered to be a part of the solution to high oil prices. While the United States already leads the world in biofuel production, the Energy Independence and Security Act of 2007, prescribes a 5-fold increase in biofuel production by 2022. Consequently, production of biofuels in the U.S. in the near future is set to increase. This has been aided by the availability of additional cropland for cultivation because of the decrease in the maximum acreage enrolled in the Conservation Reserve Program. U.S. government subsidies on corn-based ethanol production are also encouraging farmers to shift from cultivating food crops to corn.

The simplification of agroecosystems, through expansion of agricultural land supporting a single crop type is an important cause behind the decline in farmland biodiversity. As a result, ecosystem services associated with biodiversity, like nutrient recycling, microclimate regulation and natural pest control, have also deteriorated. Beyond their ecological importance, these ecosystem services provide other tangible benefits. For instance, the suppression of pest populations in crops by natural enemies reduces yield loss and the need for excessive use of pesticides. 

Results/Conclusions

Our work incorporates biodiversity estimation into modeling approaches so that these factors can be assessed and compared for different scenarios at varying locations and scales.

The model used is the Environmental Policy Integrated Climate (EPIC) model. EPIC is a biophysical biogeochemical model which uses soil, terrain, weather and crop management data to simulate plant productivity, greenhouse-gas emissions, C and nutrient cycling and soil erosion. EPIC has been modified to assess yield losses due to pest pressure resulting from simplified agroecosystems. Results from applying the modified EPIC model to a nine county regionally intensive modeling area in south-west Michigan are presented. It is expected that estimating the impact of biodiversity loss in a biofuel-dominated agricultural landscapes will offer the opportunity to optimize crop types and locations so that the provision of ecosystem services is maximized.

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