Journal
CANADIAN JOURNAL OF SOIL SCIENCE
Volume 97, Issue 2, Pages 300-318Publisher
CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cjss-2016-0075
Keywords
climate change; model bias; agricultural inputs; cropping diversity; growing season precipitation; growing degree days; recursive partitioning analysis
Categories
Funding
- National Science Foundation (NSF)
- US Department of Energy (DOE)
- National Oceanic and Atmospheric Administration (NOAA)
- US Environmental Protection Agency Office of Research and Development (EPA)
- Agriculture and Agri-Food Canada under Growing Forward 2
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Canada's grain and oilseed production in the Canadian Prairies may be affected by climate change, but the impact of input and diversity has not been assessed relative to projected variability in precipitation and temperature. This study assessed wheat, canola, and barley yields simulated with the environmental policy integrated climate model for historical weather and future climate scenarios in the context of agricultural inputs and cropping diversity at Scott, SK, Canada. Variation of future yield was explored with recursive partitioning in multivariate analyses of inputs, cropping diversity, future growing season precipitation (GSP), and growing degree days (GDD). Agricultural inputs significantly affected wheat yield but not barley or canola. Wheat yield was highest under the reduced input level and lowest under the organic input level. The combination of input and diversity accounted for about one-third of variation in future wheat yield and approximately 10% for barley yield. Most of the variability in yield was correlated with GSP in May-July and GDD in April-June and August-September. Future growing season maximum and minimum temperatures increased by 1.06 and 2.03 degrees C, respectively, and 11% in future GSP. This study showed how input management and reduced tillage maintained or improved yield, in the context of increased temperature due to climate change.
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