Assessing Assisted Natural Regeneration as a Cost‐Efficient Mitigation for Climate Change and Biodiversity Loss in China

Abstract Global deforestation results in climate change and biodiversity loss. Assisted natural regeneration (ANR) emerges as a promising approach to achieving global forest restoration targets, yet its potential and benefits for climate and biodiversity in China remain underexplored. Here, we assessed ANR potential across China and modeled spatial prioritization strategies targeting climate mitigation, biodiversity conservation, and cost savings, individually and in combination, as well as strategies considering spatial constraints from current forest restoration projects and fragmentation mitigation. From 1995 to 2015, 3.40 million hectares of land naturally regenerated into forests, with an additional 5.11 million hectares identified as potential regeneration areas, which could contribute to 12.41% of China's restoration goal in 2035. Spatial prioritization revealed limited overlap among the three single‐objective ANR strategies, while a multi‐objective optimization strategy emerged as the most effective solution to achieve synergies among goals. The top 30% of prioritized areas under the multi‐objective strategy could sequester 46.54 gigatons of CO 2 , reduce extinction risks of forest‐dependent species by 40.64%, and lower implementation costs by 31.55% compared to monoculture tree plantations. Our findings highlight that strategic spatial prioritization of ANR could mitigate climate change and biodiversity loss in a cost‐efficient manner and have the potential to reinforce current forest restoration projects.

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Publication Details

Journal
Earth s Future
Published
2025-03-01
DOI
https://doi.org/10.1029/2024ef005257
Citations
3
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
3.32

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article

Assessing Assisted Natural Regeneration as a Cost‐Efficient Mitigation for Climate Change and Biodiversity Loss in China

Dianfeng Liu, Marie‐Josée Fortin, Mingli Qiu, Zhaomin Tong et al.
3 citations
Earth s Future
Land Use and Ecosystem Services
3.32
article

Assessing Assisted Natural Regeneration as a Cost‐Efficient Mitigation for Climate Change and Biodiversity Loss in China

Dianfeng Liu, Marie‐Josée Fortin, Mingli Qiu, Zhaomin Tong, Yang Zhao, Jianhua He, Jun‐Long Huang
article en
3 citations

Abstract

Abstract Global deforestation results in climate change and biodiversity loss. Assisted natural regeneration (ANR) emerges as a promising approach to achieving global forest restoration targets, yet its potential and benefits for climate and biodiversity in China remain underexplored. Here, we assessed ANR potential across China and modeled spatial prioritization strategies targeting climate mitigation, biodiversity conservation, and cost savings, individually and in combination, as well as strategies considering spatial constraints from current forest restoration projects and fragmentation mitigation. From 1995 to 2015, 3.40 million hectares of land naturally regenerated into forests, with an additional 5.11 million hectares identified as potential regeneration areas, which could contribute to 12.41% of China's restoration goal in 2035. Spatial prioritization revealed limited overlap among the three single‐objective ANR strategies, while a multi‐objective optimization strategy emerged as the most effective solution to achieve synergies among goals. The top 30% of prioritized areas under the multi‐objective strategy could sequester 46.54 gigatons of CO 2 , reduce extinction risks of forest‐dependent species by 40.64%, and lower implementation costs by 31.55% compared to monoculture tree plantations. Our findings highlight that strategic spatial prioritization of ANR could mitigate climate change and biodiversity loss in a cost‐efficient manner and have the potential to reinforce current forest restoration projects.

Earth s FutureVol. 13(3)
Chongqing University (CN), University of Toronto (CA), Ministry of Natural Resources (CN), Wuhan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 9%
Land Use and Ecosystem Services
3.32
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