Shucheng Li , Kaiwei Li , Tongrui Zhang , Shiming Tang , Zhe Zhang , Hongyang Chen , Ke Jin
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引用次数: 0
Abstract
Soil nitrogen (N) in grassland ecosystem is highly sensitive to grazing, thus understanding the responses of soil N retention to grazing is critical to maintaining grassland ecosystem function. Here, we quantified the effects of grazing on total and available soil N retention under different management regimes (in terms of grazing intensity and duration) and environmental factors (temperature, precipitation, and ecosystem N abundance) using 2785 paired observations from 179 publications, and found that grazing (particularly moderate-to-heavy grazing) reduced total and available N retention worldwide. Additionally, grazing is associated with more soil N loss from long-term grazing (> 4 years), warmer (mean annual temperature ≥ 5°C), drier (mean annual precipitation ≤ 300 mm), or relatively N-sufficient (initial N content ≥2 g kg−1 soil) grasslands, implying the importance of climatic and environmental factors in regulating N loss. Similarly, interactive effects of grazing with mean annual temperature, mean annual precipitation, duration and initial N content on soil total N were observed. More importantly, our results emphasize the grazing effect on soil N was best explained by the response ratios of plant belowground biomass. Our study provides global insights that will aid sustainable grazing management, and more research is needed to explore the regulatory role of grazing intensity and nutrient supplementation on global grassland N retention.
期刊介绍:
Agriculture, Ecosystems and Environment publishes scientific articles dealing with the interface between agroecosystems and the natural environment, specifically how agriculture influences the environment and how changes in that environment impact agroecosystems. Preference is given to papers from experimental and observational research at the field, system or landscape level, from studies that enhance our understanding of processes using data-based biophysical modelling, and papers that bridge scientific disciplines and integrate knowledge. All papers should be placed in an international or wide comparative context.