Multivariate Analysis of Climate Change, Agricultural Inputs, Cropping Diversity, and Environmental Covariates on Future Wheat, Barley, and Canola Yield in Canadian Prairies, a Case Study.

The majority of Canada’s grain and oilseed production occurs in the Canadian Prairies, where variability in growing season precipitation and temperature affects crop yield. This study assessed wheat (Triticum aestivum L.), canola (Brassica napus L.) and barley (Hordeum vulgare L.) yield simulated with the Environmental Policy Integrated Climate (EPIC) model for historical weather (1971-2000) and future climate scenarios (2041-2070) in the context of input management and crop diversity at the Scott Experimental Farm, Scott, Saskatchewan. In this study, variation due to climate change in future projected yield of wheat, canola and barley in the Canadian Prairies was partitioned between input, 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 reduced and lowest under organic inputs. The combination of input and diversity accounted for about one third of variation in future wheat yield and about 10 % for barley. In general, cropping diversity did not affect crop yield under future climate scenarios. Most of the variability in yield was correlated with GSP in May, June, and July and GDD in April, May, June, August and September.  Future growing season maximum and minimum temperatures increased by 1.06 and 2.03°C, respectively, and 11% in future GSP compared to historical weather. This study shows the importance of input management with respect to yield, in particular with respect to tillage, which will allow producers to adapt to increases in maximum temperature due to climate change.  Furthermore analyses which include GSP and GDD as covariates with the effect of input on yield simulations are important tools in analyses of climate change.