Toward a Comprehensive Socio-Ecological Climate Model for Mato Grosso

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Monday, 5 January 2015
Keith R. Spangler, Brown University, Providence, RI; and A. H. Lynch, C. Neill, M. T. Coe, and T. E. Arbetter

Rising demand for agricultural products has precipitated large-scale deforestation and promoted novel changes in post-clearing agricultural land uses in the Amazon Basin. These shifts exacerbate existing uncertainties about the complex feedbacks between land cover and atmospheric dynamics, which in turn present unique challenges to agricultural decision-making. Of particular interest is Mato Grosso, a Brazilian state in the southeastern region of the Amazon Basin, which has adopted the use of “double cropping” to maintain crop yields while slowing its unprecedented rate of deforestation. This technique, in which two crops (e.g., soybean and corn) are planted successively on a particular plot of land within a growing season, presents many socio-ecological benefits; however, it is unknown how this management practice will affect the regional climate, particularly with respect to inter-annual variability of the amount and timing of precipitation. This creates considerable uncertainty about how regional climate will drive land management and how these land-use decisions will consequently affect the climate system. To address these questions, this study affirms the utility of the Community Land Model (CLM), the terrestrial component of the Community Earth Systems Model (CESM) from NCAR, in simulating the climate and landscape of the region of interest. Daily single-point simulations were first run in forested regions in Mato Grosso where in-situ flux tower validation data were available; these outputs were then compared to simulations from Agro-IBIS, a land model with demonstrated efficacy for southern Brazilian landscapes but not necessarily for Amazonian soy crops. Additional CLM simulations were then run for the duration of the growing season (October through April) over the double-cropped agricultural areas and were validated with crop-yield data. Confirming the accuracy of CLM output in the Amazonian frontier is an important first step in using CESM to determine the sensitivity of, and feedbacks between, novel land-management practices and emerging atmospheric changes in a rapidly evolving landscape. Subsequent research will focus on these effects and investigate the role they play in agrarian decision-making and the feasibility of broader conservation policies.