降水
中观
环境科学
温室气体
土壤呼吸
一氧化二氮
焊剂(冶金)
强度(物理)
生物量(生态学)
土壤水分
硝酸盐
氮气
草原
土壤碳
大气科学
环境化学
沉积(地质)
化学
二氧化碳
土壤科学
甲烷
碳纤维
呼吸
碳循环
大气(单位)
初级生产
含水量
水文学(农业)
生态系统
气候变化
基质(水族馆)
陆地生态系统
作者
Weifeng Gao,Tianhang Zhao,Xu Yang,Rui He,Jianying Ma,Tianxue Yang,Haiying Cui,Wei Sun
摘要
ABSTRACT Precipitation intensity and nitrogen (N) deposition are projected to increase under global change scenarios, and both are expected to affect greenhouse gas (GHG) fluxes. However, the interactive effects of increasing precipitation intensity and N addition on GHG fluxes are still unknown. To address this gap, a mesocosm simulation experiment was conducted to investigate the individual and combined effects of changing precipitation intensity (with a constant event magnitude of 50 mm) and long‐term N addition on GHG fluxes. The results revealed that precipitation application triggered a pulse effect on GHG fluxes, with increases up to 876% compared to pre‐precipitation levels. The net changes in water‐filled pore spaces (Δ WFPS) affected the temporal dynamics of GHG fluxes. Increasing precipitation intensity suppressed cumulative soil respiration, methane uptake, and nitrous oxide fluxes by directly reducing water availability (WFPS) and indirectly suppressing microbial biomass and substrate availability (dissolved organic carbon (DOC) or nitrate N content (NO 3 − ‐N)). Furthermore, precipitation application altered the magnitude or direction of GHG flux responses to N addition. Changes in precipitation intensity and N addition had interactive effects on the Δ cumulative soil respiration and Δ cumulative N 2 O fluxes, but not on Δ cumulative CH 4 fluxes. Increasing precipitation intensities decreased the Δ DOC content in the unfertilized treatment and increased Δ DOC content in the N addition treatment, thereby interactively affecting Δ cumulative soil respiration. N addition increased the Δ NO 3 − ‐N content, influencing the response of Δ cumulative N 2 O fluxes to increasing precipitation intensities. Our findings highlight that precipitation intensity regulates grassland GHG with N interactions, providing mechanistic insights to refine climate feedback predictions in ecosystems.
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