Lagged Wetland CH 4 Flux Response in a Historically Wet Year-Reference-Cited by-同舟云学术

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Lagged Wetland CH 4 Flux Response in a Historically Wet Year

Published:2021-11 Issue:11 Volume:126 Page:
ISSN:2169-8953
Container-title:Journal of Geophysical Research: Biogeosciences
language:en
Short-container-title:JGR Biogeosciences

Author:

Turner J.¹^ORCID,Desai A. R.²^ORCID,Thom J.³,Wickland K. P.⁴^ORCID

Affiliation:

1. Freshwater and Marine Sciences University of Wisconsin‐Madison Madison WI USA

2. Department of Atmospheric & Oceanic Sciences University of Wisconsin‐Madison Madison WI USA

3. Space Science and Engineering Center University of Wisconsin‐Madison Madison WI USA

4. United States Geological Survey Water Resources Mission Area Boulder CO USA

Funder

National Science Foundation

Publisher

American Geophysical Union (AGU)

Subject

Paleontology,Atmospheric Science,Soil Science,Water Science and Technology,Ecology,Aquatic Science,Forestry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021JG006458

Reference56 articles.

1. Long-term water table manipulations alter peatland gaseous carbon fluxes in Northern Michigan

2. Methane emissions from wetlands: biogeochemical, microbial, and modeling perspectives from local to global scales

3. Critical inundation level for methane emissions from wetlands

4. Assessing diel variation of CH4 flux from rice paddies through temperature patterns

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Empirical Dynamic Modeling Reveals Complexity of Methane Fluxes in a Temperate Salt Marsh;Journal of Geophysical Research: Biogeosciences;2024-02

2. On the Relationship Between Aquatic CO2 Concentration and Ecosystem Fluxes in Some of the World’s Key Wetland Types;Wetlands;2023-12-05

3. Drivers of Decadal Carbon Fluxes Across Temperate Ecosystems;Journal of Geophysical Research: Biogeosciences;2022-12

4. Scaling Land‐Atmosphere Interactions: Special or Fundamental?;Journal of Geophysical Research: Biogeosciences;2022-10

5. Causality guided machine learning model on wetland CH4 emissions across global wetlands;Agricultural and Forest Meteorology;2022-09

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