Grant: Discovery Grants Program - Individual

One of humanity's greatest short comings has been a failure to detect and respect ecological limits. This is particularly true of land management and nutrient loading to the environment (11,17). Synthetic nitrogen (N) fertilizer adds 120 million tonnes of N to the environment annually and has effectively doubled the reactive N present on the Earth (16). Only about 50% of N fertilizer used in agriculture is taken up by the crop, while the rest remains in the environment (11). Inefficient N use is a result of numerous pathways of N loss from soil and the role of weather events in triggering N losses. To improve the efficiency of N use we must better account for all sources of N, including the soil, and ensure reactive N does not accumulate during periods of high N loss potential. Increasing N use efficiency is tied to six of the seventeen UN Sustainable Development Goals (1). The Atlantic region is the focus of this research as cropping systems there occur on low fertility soils, require high rates of N fertilizer addition and are in close proximity to vulnerable surface water and groundwater systems. This region is typical of cool, humid agroecosystems which have the highest rates of agricultural N impacts on surrounding ecosystems. This work examines the influence of climate on soil N functions, determines the role of climate in triggering N processes, and evaluates probabilistic estimates of soil N supply/loss as usable and useful information for agricultural producers and/or policy makers The role of dissolved organic N in controlling the availability of N to plants and potential for loss to the environment is poorly understood. We will discover the link between climate triggers (freeze/thaw, dry/wet) and the solubilization of organic N which we hypothesize is the rate limiting step in soil N supply to plants and loss to the environment. This will result in improved estimates of soil N supply. We will use site-specific measures of soil N function and climate to generate probability-based Bayesian predictors of soil N supply/loss. These Bayesian statistical approaches will build on past research and produce tools that will allow producers to integrate current climate information and probability-based, georeferenced estimates of soil N supply to develop site-specific, crop-specific N recommendations, improving N use efficiency and reduced environmental impact. The Bayesian predictors of soil N functions will be used in combination with future climate scenarios to examine the potential impacts of climate change on soil N supply and the potential for soil N loss to the environment. These projects will combine field and laboratory studies to translate science-based measures of soil N status into probabilistic, geo-referenced tools that can be used by agricultural producers and policy makers alike to improve the efficiency of N use in agriculture and the sustainability of agriculture in Canadian cool humid agro-ecosystems.