Statistical Modeling of Agroecosystem Services Under Climate Change.

The impact of three global climate change (GCC) scenarios (A2, A1B, and B1) on annual and cumulative yield and related ecosystem services of successively complex crop rotations (2-4 crops rotated for 2-7 years) applied to two major and three minor soil series within conventional and organic cropping systems, and subjected to tillage and fertility management practices appropriate for each rotation and system (i.e., Factors). In addition, A2 was downscaled to the location level (A2D), and 8-year data derived from a field experiment at Swan Lake Research Farm was used to calibrate the APSIM simulation software program. A 50 year period was then simulated using the same GCC scenarios and actual weather data recorded during the course of the 8-year experiment (SL50). Multivariate statistical analyses of a weighted index (I_w), developed for each cropping system, crop rotation, and soil series under each GCC scenario on the basis of positive (grain and biomass yield, and sequestered soil carbon) ecosystem services (ES) and (dis)services (soil erosion, runoff, and leached nitrate-N; dES) suggested that (1) Cropping systems responded to GCC scenarios in the same manner (A2D<SL50<B1<A2<A1B); however, I_w estimates for organic system were 8-19% lower than their respective estimates for conventional system; (2) Differences in soils’ response to GCC scenarios accounted for 28.7 (p<0.05) and 22.0% (p<0.05) of variation in I_w in conventional and organic systems, respectively; this was followed by the respective values of 12.4 and 8.4% due to interaction between soils and crop rotations; and (3) Prediction profilers were developed for each Factor whereby ES and dES can be employed to maximize I_w and optimize yield response under projected GCC scenarios.