土壤碳
化学
热带和亚热带湿润阔叶林
环境化学
垃圾箱
氮气
总有机碳
沉积(地质)
碳纤维
土壤有机质
农学
亚热带
土壤水分
生态学
环境科学
土壤科学
生物
沉积物
材料科学
有机化学
复合数
复合材料
古生物学
作者
Jingqi Chen,Qiufang Zhang,Hui Dai,Jiguang Feng,Quanxin Zeng,Xueqi Sun,Yuanzhen Peng,Wenwei Chen,Biao Zhu,Yuehmin Chen
出处
期刊:Forests
[Multidisciplinary Digital Publishing Institute]
日期:2024-03-28
卷期号:15 (4): 619-619
被引量:5
摘要
Nitrogen (N) deposition rates of terrestrial ecosystems have gradually declined but are still high in some areas. Previous studies have reported that N addition elicits diverse impacts on soil organic carbon (SOC) pools. SOC can be divided into different functional fractions, namely, particulate organic carbon (POC) and mineral-associated organic carbon (MAOC). The responses of these fractions to N addition should be elucidated to better understand the changes in SOC pools. Here, we conducted a N addition experiment (0, 40, and 80 kg N ha−1 yr−1) in a subtropical Castanopsis fabri forest to simulate N deposition. The surface (0−10 cm) SOC fractions, aboveground litter product, fine root (diameter < 2 mm) biomass, soil exchangeable cation content, and soil enzyme activity under different N addition treatments were measured. The results showed the following: (1) N addition showed a positive effect on POC and SOC contents but did not significantly affect MAOC content; (2) POC content was negatively correlated with pH and soil enzyme activity and positively correlated with aboveground litter product, suggesting that POC accumulation was influenced by aboveground litter input and microbial decomposition; (3) a close negative relationship was observed between exchangeable Al3+ and Ca2+ or K+ contents, indicating that there is likely to be a trade-off between the mineral sorption and desorption, thus resulting in an insignificant reaction of MAOC to N addition. Overall, the accumulation of SOC under short-term N addition was found to be primarily driven by POC, and the response of different SOC functional fractions to N addition was inconsistent. By incorporating these nuances into ecosystem models, it is possible to predict SOC dynamics more accurately in response to global change.
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