Identification of potential forest thinning locations to mitigate water deficits in drylands DOI
Chenxu Wang, Yanxu Liu, Yaosheng Zhang

et al.

Land Degradation and Development, Journal Year: 2023, Volume and Issue: 35(4), P. 1437 - 1448

Published: Dec. 9, 2023

Abstract Appropriate forest thinning measures can mitigate the conflicting relationship between past excessive afforestation and current increasing regional water deficiency in dryland ecosystems. However, since blind intervention landscapes may incur additional economic costs cause loss of ecosystem services, drylands mostly exists scientific discussions is seldom implemented reality. In this study, we propose an advanced technical route to predict spatial arrangement potential locations under different policy scenarios. Taking Shanxi Province China as a case simulated eight scenarios for stakeholders assess benefits after future. The results show that deficit 533 million m 3 could potentially be mitigated by means thinning. Under scenarios, thinned area ranged from 1142.91 1195.47 km 2 , which would result soil 1.77–3.02 /year carbon sequestration 3.15–3.24 t/year. Considering both conservation food security help minimize direct capacity maintain sustainable landscape pattern. method used decision support tool identify resulting consequences scarcity conditions making adaptive optimization decisions.

Language: Английский

Ecological Restoration and Zonal Management of Degraded Grassland Based on Cost–Benefit Analysis: A Case Study in Qinghai, China DOI Open Access
Ziyao Wang, Feng Li, Donglin Xie

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(24), P. 11123 - 11123

Published: Dec. 18, 2024

The Qinghai–Tibetan Plateau (QTP) has the largest area of natural grassland in China, and continuous degradation poses a serious threat to regional ecological security sustainable resource management. It is essential comprehensively evaluate cost–benefit differences drivers across various zones enhance management practices. This study presents zonal framework for restoration degraded grasslands based on analysis, specifically applied Qinghai Northeastern QTP. results indicate: (1) Although overall NDVI shows an upward trend, some areas still exhibit significant degradation. (2) Cost–benefit analysis can divide into four types Ecological Management Zones (EMZs): high-cost–high-benefit zone, high-cost–low-benefit low-cost–low-benefit low-cost–high-benefit zone. (3) driving factors show different EMZs. Based these research findings, differentiated spatial planning strategies were developed each EMZ. not only provides scientific methodology but also offers important insights resources QTP other ecologically sensitive areas.

Language: Английский

Citations

0

Identification of potential forest thinning locations to mitigate water deficits in drylands DOI
Chenxu Wang, Yanxu Liu, Yaosheng Zhang

et al.

Land Degradation and Development, Journal Year: 2023, Volume and Issue: 35(4), P. 1437 - 1448

Published: Dec. 9, 2023

Abstract Appropriate forest thinning measures can mitigate the conflicting relationship between past excessive afforestation and current increasing regional water deficiency in dryland ecosystems. However, since blind intervention landscapes may incur additional economic costs cause loss of ecosystem services, drylands mostly exists scientific discussions is seldom implemented reality. In this study, we propose an advanced technical route to predict spatial arrangement potential locations under different policy scenarios. Taking Shanxi Province China as a case simulated eight scenarios for stakeholders assess benefits after future. The results show that deficit 533 million m 3 could potentially be mitigated by means thinning. Under scenarios, thinned area ranged from 1142.91 1195.47 km 2 , which would result soil 1.77–3.02 /year carbon sequestration 3.15–3.24 t/year. Considering both conservation food security help minimize direct capacity maintain sustainable landscape pattern. method used decision support tool identify resulting consequences scarcity conditions making adaptive optimization decisions.

Language: Английский

Citations

0