Unfolding the effectiveness of ecological restoration programs in combating land degradation: Achievements, causes, and implications.

Degraded dryland Ecological restoration Land degradation Non-linear ecosystem dynamics Soil erosion

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:
15 Dec 2020
Historique:
received: 25 04 2020
revised: 05 08 2020
accepted: 05 08 2020
pubmed: 23 8 2020
medline: 23 8 2020
entrez: 23 8 2020
Statut: ppublish

Résumé

Land degradation is one of the most serious environmental problems worldwide. To combat land degradation, China has implemented a series of ecological restoration programs (ERPs). This study selected the northern dryland of China as a case study to examine the efficiency of ERPs, and the response of soil loss to afforestation efforts and climatic conditions was discussed using the principles from the ecological theory of non-linear ecosystem dynamics. Owing to the combined impacts of declining wind speed and rapid vegetation restoration, the soil erosion for the entire region was substantially reduced from 1990 to 2015. However, the rainfall fluctuated considerably, particularly for the period from the late 1990s to early 2000s. Several drought events to some extent inhibited vegetation growth and further offset afforestation efforts, resulting in degradations in vegetation structure and soil retention function, which have been aggravating soil erosion since 2005. In certain representative sandstorm areas, limited increase in rainfall was not enough to promote vegetation growth, and therefore the vegetation cover did not present increasing trends and, in some cases, even declined significantly. The responses in terms of land degradation to climatic conditions and afforestation efforts behaved in a non-linear dynamic manner, providing essential insights into appropriate timings, climate-induced windows of opportunity, and risk in recovering and sustaining ecosystems, and eventually moving towards the land degradation neutrality (LDN) target. The climate-induced windows of opportunity and risk are critical in identifying the time for starting human interventions to mitigate and halt land degradation. Meanwhile, effective investment actions should be taken according to existing environmental conditions and critical thresholds, to achieve LDN at minimum risk and cost.

Identifiants

pubmed: 32827896
pii: S0048-9697(20)35081-6
doi: 10.1016/j.scitotenv.2020.141552
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

141552

Informations de copyright

Copyright © 2020 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

Chong Jiang (C)

Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, PR China; Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, PR China; School of Earth and Environmental Sciences, The University of Queensland, Brisbane 4072, Australia.

Haiyan Zhang (H)

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

Lingling Zhao (L)

Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, PR China; Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, PR China. Electronic address: linglingzhao@foxmail.com.

Zhiyuan Yang (Z)

Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia.

Xinchi Wang (X)

School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China.

Long Yang (L)

Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, PR China; Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, PR China.

Meili Wen (M)

Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, PR China; Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, PR China.

Shoubao Geng (S)

Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, PR China; Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, PR China.

Qiao Zeng (Q)

Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, PR China; Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, PR China.

Jun Wang (J)

Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangzhou 510070, PR China; Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangzhou 510070, PR China.

Classifications MeSH