Predicting Soil Test Phosphorus Concentrations Across Ontario to Aid in Management Strategies for the Great Lakes

Phosphorus is crucial for optimal plant growth and agricultural productivity, but excessive runoff of phosphorus can harm aquatic ecosystems, affecting tourism, fishing, and water quality in communities. Soil test phosphorus (STP) is a laboratory measurement that is correlated with total phosphorus (TP) and total water extractable phosphorus (tWEP) in the soil, making it a good proxy for phosphorus vulnerable to runoff. This study integrated Southern Ontario soil data from diverse sources to model STP using the machine learning tool Cubist at (i) a regional scale and (ii) a local field scale. The findings show that the local field scale models perform better, indicating STP’s location-specific nature. Improved regional scale modelling of STP is possible with readily available field-scale soil data and updated regional soil property information. Better understanding phosphorus in soils and runoff events can mitigate its adverse impacts on water quality and ecosystems, benefiting both local and regional contexts.