Spatial patterns and driving factors of carbon stocks in mangrove forests on Hainan Island, China-Reference-Cited by-同舟云学术

Spatial patterns and driving factors of carbon stocks in mangrove forests on Hainan Island, China

Published:2022-06-02 Issue:9 Volume:31 Page:1692-1706
ISSN:1466-822X
Container-title:Global Ecology and Biogeography
language:en
Short-container-title:Global Ecol. Biogeogr.

Author:

Meng Yuchen¹²³,Gou Ruikun¹²,Bai Jiankun¹⁴,Moreno‐Mateos David⁵⁶⁷,Davis Charles C.⁵,Wan Luoma⁸,Song Shanshan¹,Zhang Hongsheng⁹,Zhu Xiaoshan³,Lin Guanghui¹³

Affiliation:

1. Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling Institute for Global Change Studies, Tsinghua University Beijing China

2. Department of Environmental Systems Science Swiss Federal Institute of Technology in Zurich (ETH Zurich) Zurich Switzerland

3. Institute for Ocean Engineering, Shenzhen International Graduate School Tsinghua University Shenzhen China

4. School of Ecology and Environmental Science Yunnan University Kunming China

5. Department of Organismic and Evolutionary Biology Harvard University Cambridge Massachusetts USA

6. Department of Landscape Architecture Harvard University Cambridge Massachusetts USA

7. Basque Center for Climate Change/Ikerbasque Foundation Leioa Spain

8. Department of Land Surveying and Geo‐Informatics The Hong Kong Polytechnic University Hong Kong China

9. Department of Geography The University of Hong Kong Hong Kong China

Funder

National Key Research and Development Program of China

Publisher

Wiley

Subject

Ecology,Ecology, Evolution, Behavior and Systematics,Global and Planetary Change

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/geb.13549

Reference93 articles.

1. Carbon sequestration in mangrove forests

2. Carbon Cycling and Storage in Mangrove Forests

3. Impact of Global Change on Nutrient Dynamics in Mangrove Forests

4. Mapping the soils of an Argentine Pampas region using structural equation modelling

5. Mapping spatial distribution and biomass of coastal wetland vegetation in Indonesian Papua by combining active and passive remotely sensed data

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