关键词：
Climate change
Modeling
Agricultural inputs and cropping diversity
Soil organic carbon
Microbial respiration
摘要：
Climate change, agricultural inputs, cropping diversity, and environment have seldom been combined in analyses of soil organic carbon (SOC), and soil C respired through microbial respiration (MR). This modeling study assessed SOC and MR simulated with the Environmental Policy Integrated Climate (EPIC) model for historical weather (1971-2000) and future climate scenarios (2041-2070) for the Alternative Cropping Systems (ACS) study research site in Saskatchewan, Canada. Nineteen years of field and crop management information from the 1994-2013 ACS study were used to validate and provide parameters to the EPIC model for analyses of climate change scenarios. The ACS study consisted of three levels of agricultural inputs [organic (ORG), reduced (RED), and high (HI)] and three levels of cropping diversity [low (LOW), diversified annual grains (DAG), and diversified annuals and perennials (DAP)]. Changes in future SOC and MR under climate change were explored with ANOVA and recursive partitioning in multivariate analyses of inputs, diversity, growing season precipitation (GSP), growing degree days (GDD), annual average maximum, minimum temperatures, cumulative annual precipitation, and terrain attributes (TA). Under climate change, SOC decreased by 1.3% (from 132.3 to 130.6 Mg ha(-1)) of original stocks in the 0-90 cm. Microbial respiration was affected by climate change and increased by 17% (from L92 to 2.25 Mg C ha(-1) y(-1)) due to an increase in annual maximum and minimum temperatures. The increase in annual maximum and minimum temperature was correlated with 32 and 42% of variation in SOC respectively. Monthly growing season GDD was correlated with 14% of variation of SOC in an analysis independent of annual data. Annual precipitation did not affect SOC, though May GSP accounted for 16% of total variation in SOC, while June temperature accounted for 9% of variation in MR. The combination of input and diversity was correlated with 3 and 7% of variation in SOC and MR, r
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