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United States Department of Agriculture

Agricultural Research Service

Research Project: ADVANCING SUSTAINABLE AND RESILIENT CROPPING SYSTEMS FOR THE SHORT GROWING SEASONS AND COLD, WET SOILS OF THE UPPER MIDWEST

Location: Soil Management Research

Title: Modeling carbon sequestration potential in Mollisols under climate change scenarios

Authors
item Jaradat, Abdullah
item Starr, Jon

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: July 24, 2013
Publication Date: N/A

Technical Abstract: Carbon sequestration in agricultural soils, besides its importance in mitigating global climate change, impacts and will be impacted by provisioning, regulating and supporting agroecosystem services. The objectives of this study were to (1) provide an improved understanding of the role of projected climate change and its interaction with land use and management practices on carbon sequestration, and (2) develop prediction models to scale up carbon sequestration from plot to watershed level and predict future impacts on agroecosystem services. We used 8-year data on soils, cropping systems, crop rotations, and the climate to calibrate and validate a simulation model and to predict carbon sequestration in the top 1-m of the soil profile in response to historical (A0) and future rainfall, temperature and carbon dioxide data based on the A1B, A2 and B1 climate change scenarios of the IPCC under current and alternative management practices in the Upper Midwest of the US. Fifty year-simulation runs for each of the A0 and climate change scenarios were based on 16 combinations of two major Mollisols under conventional and organic cropping systems and subjected to a combination of five crop rotations with increasing complexity and the inclusion of a perennial forage crop, and tillage and fertilizer application treatments. Simulated data were used in developing 320 prediction and validation partial least squares (PLS) models for soil carbon as influenced by crop biomass and grain yield, nitrate- and ammonium-nitrogen in soil, and cumulative runoff and soil erosion. Total variance in soil carbon sequestration was partitioned into its components using a mixed multivariate model. Secondary statistics derived from the PLS analyses were used in further statistical analyses to quantify carbon sequestration potential of both soil series in response to climate change scenarios, management practices, and as mediated by the agroecosystem services. The PLS models predicted carbon sequestration with large (R2>0.95), intermediate (R2 0.6-0.7) and small (R2 0.3-0.45) certainties (i.e., model fit) based on A0, A1B, and both A2 and B1 global climate change scenarios, respectively. The variability in carbon sequestration potential increased over time and was inversely related to the model fit. Although there were significant differences in carbon sequestration potential between A1B, A2 and B1, the largest differences were predicted between each of these climate change scenarios and A0. The impact of agroecosystem services on carbon sequestration was positive, negative or neutral depending on the climate change scenario and its interaction with other factors and management practices. The largest portion of variation in soil carbon within each climate change scenario was attributed to differences between soil series and followed in decreasing order by differences between cropping systems, crop rotations, and tillage practices. Significant and positive effect of a perennial forage crop on soil carbon is anticipated by the fourth year of its inclusion in a crop rotation that includes a small grain crop in addition to corn and soybean. Results of this study were used to scale-up predictions to a watershed level and may assist producers in developing and adopting innovative crop rotations and management practices to address and manage soil conservation implications of climate change. This research conducted by NCSCRL is part of a larger initiative called the Chippewa 10% Project, with several partners, that is designed to achieve water quality goals through predictive modeling, outreach to farmers, market development for perennial crops and livestock on the land and monitoring for actual impacts in area streams and soils.

Last Modified: 4/23/2014