环境科学
营养物
垃圾箱
植物凋落物
生物地球化学循环
热带和亚热带湿润阔叶林
生态系统
溪流
亚热带
水文学(农业)
生态学
农学
生物
计算机科学
计算机网络
工程类
岩土工程
作者
Yuchen Zheng,Siying Chen,Yan Peng,Zemin Zhao,Chaoxiang Yuan,Ji Yuan,Nannan An,Xiangyin Ni,Fuzhong Wu,Kai Yue
出处
期刊:Water
[Multidisciplinary Digital Publishing Institute]
日期:2025-06-19
卷期号:17 (12): 1828-1828
摘要
Headwater streams serve as a crucial link between forest and downstream aquatic ecosystems and also act as crucial agents in carbon (C) and nutrient storage and flux. These aquatic systems play a pivotal role in regulating biogeochemical cycles. Plant litter is an important contributor of nutrients to headwater streams, having significant impacts on downstream ecosystems. However, current research predominantly focuses on the dynamics of plant litter C and nutrients such as nitrogen and phosphorus, and we know little about those of nutrients such as sodium (Na). In this study, we conducted a comprehensive evaluation of the annual dynamics of plant litter Na storage within a subtropical headwater stream. This study took place over a period of one year, from March 2021 to February 2022. Our results showed that (1) the average annual concentration and storage of litter Na was 538.6 mg/kg and 2957.6 mg/m2, respectively, and litter Na storage exhibited a declining trend from stream source to mouth, while demonstrating significantly higher values during the rainy season compared to the dry season; (2) plant litter type had significant impacts on Na concentration and storage, with leaf, twig, and fine woody debris accounting for the majority of litter Na storage; and (3) hydrological (precipitation, discharge) and physicochemical (water temperature, flow velocity, pH, dissolved oxygen, alkalinity) factors jointly affected Na storage patterns. Overall, the results of this study clearly reveal the dynamic characteristics of Na storage in plant litter in a subtropical forest headwater stream, which contributes to a more comprehensive understanding of the role of headwater streams in nutrient cycling and the dynamic changes of nutrients along with hydrological processes. This research will enhance our predictive understanding of nutrient cycling at the watershed scale.
科研通智能强力驱动
Strongly Powered by AbleSci AI