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Grazing intensity significantly changes the C : N : P stoichiometry in grassland ecosystems

131

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37

References

2019

Year

Abstract

Abstract Aim Livestock grazing can alter carbon (C), nitrogen (N) and phosphorus (P) cycles, thereby affecting the C : N : P stoichiometry in grasslands. In this study, we aimed to examine mechanisms underlying the impacts of grazing on grassland C : N : P stoichiometry, focusing on belowground processes and their linkages with aboveground vegetation properties. Location Global. Time period 1900–2018. Major taxa studied Grassland ecosystems. Methods We conducted a meta‐analysis based on 129 published studies to synthesize the effects of grazing on the C : N : P stoichiometry of leaves, stems, litter, roots, microbial biomass, and soil in grassland ecosystems. Results Grazing significantly affected the C, N and P pools, and then the C : N : P stoichiometry in grassland ecosystems. Grazing effects on C : N : P stoichiometry varied strongly with grazing intensity. Specifically, heavy grazing decreased all C : N : P stoichiometry except litter N : P and root C : N ratios, while light and moderate grazing caused less negative or positive effects. Grazing effects on litter C : N ratio were negatively correlated with grazing effects on soil C : N ratios under light and moderate grazing, but this relationship was positive under heavy grazing. In contrast, grazing effects on root C : P and soil C : P were positively correlated under light and moderate grazing but negatively correlated under heavy grazing. Importantly, grazing significantly decreased the soil N pool by 10.0% but increased the soil P pool by 3.6%, indicating differential mechanisms for grazing impact on N and P cycles in grasslands. Main conclusions Our results strongly suggest that grazing intensity regulates the biogeochemical cycles of C, N and P in grassland ecosystems by affecting plant nutrient use efficiency and soil physicochemical processes. Therefore, incorporating grazing intensity into Earth system models may improve predictions of climate–grassland feedbacks in the Anthropocene.

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