SNUEI

Identifying dominant environmental predictors of freshwater wetland methane fluxes across diurnal to seasonal time scales

2021 · Global Change Biology

저자

Sara Knox, Sheel Bansal, Gavin McNicol, Karina V. R. Schäfer, Cove Sturtevant, Masahito Ueyama, Alex C. Valach, Dennis Baldocchi, Kyle Delwiche, Ankur Rashmikant Desai, Eugenie Susanne Euskirchen, Jinxun Liu, Annalea Lohila, Avni Malhotra, Lulie Melling, W. J. Riley, Benjamin R. K. Runkle, Jessica Turner, Rodrigo Vargas, Qing Zhu, Tuula Aalto, Etienne Fluet‐Chouinard, Mathias Goeckede, Joe R. Melton, Oliver Sonnentag 외 34명

연구주제

Peatlands and Wetlands Ecology

NTIS 과학기술표준분류

에너지/자원만에너지·환경·원자력 확장

지원 과제·AI 키워드로 잡을 근거가 없어 분류하지 않았다.

AI 연구 키워드·방법

freshwater wetland water table depth 습지 메탄 배출

에디 공분산법 기계학습

키워드 (OpenAlex)

methane flux freshwater wetlands methane emissions water table depth air temperature soil temperature atmospheric pressure diurnal variation

초록

Abstract While wetlands are the largest natural source of methane (CH 4 ) to the atmosphere, they represent a large source of uncertainty in the global CH 4 budget due to the complex biogeochemical controls on CH 4 dynamics. Here we present, to our knowledge, the first multi‐site synthesis of how predictors of CH 4 fluxes (FCH4) in freshwater wetlands vary across wetland types at diel, multiday (synoptic), and seasonal time scales. We used several statistical approaches (correlation analysis, generalized additive modeling, mutual information, and random forests) in a wavelet‐based multi‐resolution framework to assess the importance of environmental predictors, nonlinearities and lags on FCH4 across 23 eddy covariance sites. Seasonally, soil and air temperature were dominant predictors of FCH4 at sites with smaller seasonal variation in water table depth (WTD). In contrast, WTD was the do…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

연도과제부처사업수행기관NTIS 분류(1순위)
2021서울대학교 스마트시티 글로벌 융합 혁신인재양성 교육연구단교육부4단계두뇌한국21사업(R&D)서울대학–

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교수 1

류영렬

연구주제 1

Peatlands and Wetlands Ecology

키워드 1

습지 메탄 배출

방법 2

기계학습 · 에디 공분산법