Urbanization expands the fluctuating difference in gross primary productivity between urban and rural areas from 2000 to 2018 in China.

Climate change Gross primary productivity Growth offset Human activity Urbanization

Journal

The Science of the total environment
ISSN: 1879-1026
Titre abrégé: Sci Total Environ
Pays: Netherlands
ID NLM: 0330500

Informations de publication

Date de publication:
25 Nov 2023
Historique:
received: 21 05 2023
revised: 16 08 2023
accepted: 20 08 2023
pubmed: 24 8 2023
medline: 24 8 2023
entrez: 23 8 2023
Statut: ppublish

Résumé

Urban and rural vegetation are affected by both climate change and human activities, but the role of urbanization in vegetation productivity is unclear given the dual impacts. Here, we delineated urban area (UA) and rural area (RA), quantified the relative impacts of climate change and human activities on gross primary production (GPP) in 34 major cities (MCs) in China from 2000 to 2018, and analyzed the intrinsic impacts of urbanization on GPP. First, we found that the total urban impervious surface coverage (ISC) of the 34 MCs increased by 13.25 % and the mean annual GPP increased by 211 gC m

Identifiants

pubmed: 37611713
pii: S0048-9697(23)05115-X
doi: 10.1016/j.scitotenv.2023.166490
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

166490

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Xiaoyan Liu (X)

Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475001, Henan, China; School of Geography and Environmental Science, Henan University, Kaifeng 475004, China; Dabieshan National Observation and Research Field Station of Forest Ecosystem at Henan, Zhengzhou 450046, China; Xinyang Ecological Research Institute, Xinyang 464000, China.

Yaoping Cui (Y)

Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475001, Henan, China; School of Geography and Environmental Science, Henan University, Kaifeng 475004, China; Dabieshan National Observation and Research Field Station of Forest Ecosystem at Henan, Zhengzhou 450046, China; Xinyang Ecological Research Institute, Xinyang 464000, China. Electronic address: cuiyp@lreis.ac.cn.

Wanlong Li (W)

Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475001, Henan, China; School of Geography and Environmental Science, Henan University, Kaifeng 475004, China.

Mengdi Li (M)

Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475001, Henan, China; School of Geography and Environmental Science, Henan University, Kaifeng 475004, China.

Nan Li (N)

Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475001, Henan, China; School of Geography and Environmental Science, Henan University, Kaifeng 475004, China.

Zhifang Shi (Z)

Key Laboratory of Geospatial Technology for the Middle and Lower Yellow River Regions (Henan University), Ministry of Education, Kaifeng 475001, Henan, China; School of Geography and Environmental Science, Henan University, Kaifeng 475004, China.

Jinwei Dong (J)

Institute of Geographical Sciences and Resources, Chinese Academy of Sciences, Beijing 100101, China.

Xiangming Xiao (X)

Department of Microbiology and Plant Biology, Center for Earth Observation and Modeling, University of Oklahoma, Norman, OK 73019, USA. Electronic address: xiangming.xiao@ou.edu.

Classifications MeSH