Biophysical Controls of Ecosystem‐Scale Methane Fluxes From a Subtropical Estuarine Mangrove: Multiscale, Nonlinearity, Asynchrony and Causality

环境科学 红树林 大气科学 生态系统 台风 气候学 生态学 生物 地质学
作者
Jiangong Liu,Alex Valach,Dennis Baldocchi,Derrick Y.F. Lai
出处
期刊:Global Biogeochemical Cycles [Wiley]
卷期号:36 (6) 被引量:5
标识
DOI:10.1029/2021gb007179
摘要

Abstract Mangroves are complex ecosystems subject to periodic and irregular changes in meteorology, tides, water quality and biological factors. Methane dynamics in mangroves and their dependence on biogeochemical controls across scales are poorly characterized using traditional parametric statistics. We measured the ecosystem‐scale methane flux (F CH4 ) using an eddy covariance system in a subtropical estuarine mangrove for two years. A combination of nonparametric statistical approaches, including singular spectrum analysis and information theory, was used to isolate multiscale F CH4 variations and explore their variability and dominant controls at different time scales. F CH4 exhibited the largest variability at the diel scale (57%), followed by seasonal (25%) and multiday (18%) scales. Mutual information metrics suggested that variation in F CH4 was dominantly coupled to plant activities through synchronous processes at the diel scale. Moreover, fluctuations in atmospheric turbulence and soil temperature dominated multiday variation in F CH4 through asynchronous processes. Seasonally, soil temperature and water salinity were dominant variables leading to changes in F CH4 with a time lag of 12 and 17 days, respectively. Weak links between F CH4 and tidal heights were found across all the studied time scales. Transfer entropy metrics indicated that a super typhoon event substantially weakened causal links between biophysical variables and F CH4 by causing severe defoliation and disturbing the soil microbial community. The typhoon also temporarily decoupled the causal link between F CH4 and temperature. These findings call for the inclusion of the properties of scale emergence, nonlinearity, asynchrony and causality for comprehensively understanding and accurately predicting the interactions between mangrove F CH4 and its biophysical controls.
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