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Evaluating the Potential of Legumes to Mitigate N2O Emissions From Permanent Grassland Using Process‐Based Models

تقييم إمكانات البقوليات للتخفيف من انبعاثات أكسيدالنيتروز من المراعي الدائمة باستخدام النماذج القائمةعلى العمليات
Authors: Mark A. Liebig; Pete Smith; Robert M. Rees; Russell McAuliffe; Jean-François Soussana; Nina Buchmann; Nuala Fitton; +18 Authors

Evaluating the Potential of Legumes to Mitigate N2O Emissions From Permanent Grassland Using Process‐Based Models

Abstract

AbstractA potential strategy for mitigating nitrous oxide (N2O) emissions from permanent grasslands is the partial substitution of fertilizer nitrogen (Nfert) with symbiotically fixed nitrogen (Nsymb) from legumes. The input of Nsymb reduces the energy costs of producing fertilizer and provides a supply of nitrogen (N) for plants that is more synchronous to plant demand than occasional fertilizer applications. Legumes have been promoted as a potential N2O mitigation strategy for grasslands, but evidence to support their efficacy is limited, partly due to the difficulty in conducting experiments across the large range of potential combinations of legume proportions and fertilizer N inputs. These experimental constraints can be overcome by biogeochemical models that can vary legume‐fertilizer combinations and subsequently aid the design of targeted experiments. Using two variants each of two biogeochemical models (APSIM and DayCent), we tested the N2O mitigation potential and productivity of full factorial combinations of legume proportions and fertilizer rates for five temperate grassland sites across the globe. Both models showed that replacing fertilizer with legumes reduced N2O emissions without reducing productivity across a broad range of legume‐fertilizer combinations. Although the models were consistent with the relative changes of N2O emissions compared to the baseline scenario (200 kg N ha−1 yr−1; no legumes), they predicted different levels of absolute N2O emissions and thus also of absolute N2O emission reductions; both were greater in DayCent than in APSIM. We recommend confirming these results with experimental studies assessing the effect of clover proportions in the range 30–50% and ≤150 kg N ha−1 yr−1 input as these were identified as best‐bet climate smart agricultural practices.

Countries
Germany, United Kingdom, Australia, Italy, Italy, Germany, Switzerland, France
Keywords

Atmospheric Science, 550, Adaptation to Climate Change in Agriculture, Economics, QH301 Biology, legumes, Macroeconomics, Organic chemistry, 630, Agricultural and Biological Sciences, Nutritional Strategies for Ruminant Health and Production, Fertilizer, Environmental Science(all), SDG 13 - Climate Action, General Environmental Science, Productivity, Global and Planetary Change, GE, Nitrous oxide, Ecology, greenhouse gas mitigation, Life Sciences, Grassland, Legume, Chemistry, NE/M016900/1, Environmental chemistry, NE/K002589/1, GE Environmental Sciences, 571, Supplementary Information, biological nitrogen fixation; greenhouse gas mitigation; legumes, 330, Nitrogen, [SDE.MCG]Environmental Sciences/Global Changes, Soil Science, Biogeochemical cycle, Greenhouse gas, Environmental science, models, QH301, Environmental Chemistry, SDG 2 - Zero Hunger, Biology, Ecology, Evolution, Behavior and Systematics, info:eu-repo/classification/ddc/550, Soil Fertility, ddc:550, biological nitrogen fixation, Agronomy, Earth sciences, [SDE.MCG] Environmental Sciences/Global Changes, FOS: Biological sciences, Other, BB/N013484/1, Soil Carbon Dynamics and Nutrient Cycling in Ecosystems, Nutrient Limitation, Agronomy and Crop Science

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    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Average
Top 10%
Green
hybrid