Effects of Crop Inputs, Diversity, Environment and Terrain on Soil Nitrogen and Phosphorus in an 18-Year Study in the Semi-Arid Canadian Prairie

A long-term field experiment was conducted from 1994 to 2013 to assess the role of agricultural inputs and cropping diversity in sustaining crop production and soil quality in the Canadian Prairies at the AAFC Research Farm in Scott, SK. In addition to the effects of input and diversity, this research investigated effects of growing season precipitation (GSP), growing degree days (GDD), and terrain attributes (planar and profile curvature, wetness index, and slope) on soil nitrate-N and labile soil phosphorus (P). The experiment was a four replicate split-plot with main plot treatments consisting of three levels of inputs [organic (ORG), reduced (RED), and high (HI)] and sub-plots comprised of three levels of cropping diversity [low (LOW), diversified annual grains (DAG), and diversified annual perennial (DAP)]. Data were analyzed with machine learning methods such as artificial neural networks, boosted tree, bootstrap forest, followed by the MIXED model procedure, analysis of variance and covariance. Results indicated that input, diversity, environmental covariates and terrain attributes were significantly correlated with soil nitrate-N and soil P. Nitrate-N was highest in HI, followed by RED, and lowest in the ORG systems. Soil P was highest in RED, followed by HI, and lowest in the ORG. Along with input and cropping diversity, monthly GSP and GDD were correlated with soil nitrate-N, while terrain attributes were found important factors which explained variation in soil P. This study shows the importance of input management with respect to soil nitrate-N and soil P, in particular with respect to tillage, which will allow producers to adapt to variability in temperature and precipitation in the future. Terrain attributes, GSP, and GDD should be assessed when analyzing impacts of fixed effects such as agricultural inputs and cropping diversity on soil nitrate-N and soil P, to account for variability due to weather, micro-topography or landforms.