Quantifies nutrient runoff impacts from various grassland management practices, indicating significant ecological implications.
Grasslands encompass nearly 40% of the terrestrial earth’s surface, yet their contribution to N and P runoff and to adverse impacts such as accelerated eutrophication has not been systematically evaluated. To address this need, we utilized 1 412 site-years of data from 41 studies in the MANAGE database to quantify annual nutrient loads in runoff from grasslands in the Continental US and Canada. We performed cursory evaluations for several potential factors (i.e., ecoregion, grassland type, land use/grazing management, fertilizer type) and conducted more in-depth generalized linear mixed model (GLMM) analyses related to land use/grazing management. Noteworthy results include: 1) Ecoregion had a significant impact on mean annual N and P loads with the exception of particulate P, and the highest loads typically occurred in the Southeastern USA Plains; 2) Improved Pasture and Improved Pasture (Overseeded) had higher mean annual dissolved and total N and P loads than native sites; 3) While Improved Pasture (Overseeded) had lower fertilizer rates as well as increased nutrient uptake potential due to the presence of cover crops, which were expected to reduce N and P runoff relative to Improved pasture (without overseeding), this expectation held true for N runoff but not for total P runoff; 4) Mean annual particulate N and P loads occurred in the following order: Continuously Grazed (Heavy Intensity) > Continuously Grazing (Light-Moderate Intensity) ≈ Rotationally Grazed > Ungrazed ≈ Hayed ; and 5) Organic only fertilization produced the highest dissolved and total N and P loads, likely due to high animal manure application rates as such occurs on waste application fields. These general results, presented for the first time in a compilation across North American ecoregions, provide insights into climatic, land use, and management impacts of nutrient runoff losses, and highlight potential uses of MANAGE for subsequent, in-depth analyses to guide programmatic, policy, and management decision-making.
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Harmel et al. (2026) studied this question.
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