Enhancing ecosystem services and socio-ecological system coupling coordination through LULC optimization

生态学 生态系统 生态系统服务 联轴节(管道) 环境资源管理 环境科学 生物 工程类 机械工程
作者
Shunjie Xin,Ning Chen,Zhongguo Li
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:179: 114160-114160 被引量:1
标识
DOI:10.1016/j.ecolind.2025.114160
摘要

In the context of global urbanization and the degradation of ecosystem services, optimizing land use and land cover (LULC) emerges as a pivotal Nature-based Solution for the effective management of human-influenced landscapes. This methodology is essential for enhancing ecosystem functions and fostering sustainable development. By analyzing LULC data spanning from 2000 to 2020, in conjunction with 20 driving factors within the Lanzhou-Xining urban agglomeration, we devised a technical framework consisting of “historical coupling state identification, multi-scenario simulation, and ecological effect evaluation.” Utilizing this framework, we optimized LULC projections for the year 2060 across three scenarios: Low-Coupling, Natural-Development, and High-Coupling. Our findings reveal that, subsequent to LULC optimization in the High-Coupling scenario, a significant increase in ecosystem services is observed. Specifically, the forest area expands by 90,238 ha, and water bodies increase by 1840 ha, while unused land diminishes by 387,637 ha. This optimization yields a 19.12 % elevation in water yield, achieving 205.54 cubic meters, a 10.52 % enhancement in soil retention to 297.92 tons per hectare, and a 7.0 % augmentation in carbon storage to 85.95 kg of carbon per hectare, effectively reversing ecological degradation. Furthermore, it improves the coupling coordination of the social-ecological system by 0.1649 from 2020 to 2060, demonstrating synergistic effects extending from the core area to adjacent regions. This research elucidates the mechanism underlying “LULC optimization–ecological function enhancement-system coupling synergy” and provides a spatial regulation framework for resource-dependent and ecologically vulnerable areas.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
楠楠完成签到,获得积分10
刚刚
科研通AI6.4应助wuti采纳,获得10
2秒前
pzy完成签到,获得积分10
2秒前
科研通AI2S应助beepppp采纳,获得10
2秒前
2秒前
脑洞疼应助贾硕士采纳,获得10
3秒前
ineout发布了新的文献求助10
3秒前
3秒前
杭三问发布了新的文献求助10
3秒前
孙翠婷关注了科研通微信公众号
4秒前
4秒前
羊子关注了科研通微信公众号
4秒前
5秒前
phi发布了新的文献求助10
7秒前
铭铭子发布了新的文献求助10
7秒前
JamesPei应助Jamie2采纳,获得10
8秒前
完美世界应助Bonnie采纳,获得10
9秒前
9秒前
江二毛发布了新的文献求助10
9秒前
苏苏发布了新的文献求助10
9秒前
10秒前
青梧完成签到,获得积分10
10秒前
11秒前
12秒前
12秒前
Sus完成签到,获得积分10
13秒前
贾硕士发布了新的文献求助10
13秒前
芒草lx发布了新的文献求助10
14秒前
刘小飞完成签到,获得积分10
14秒前
李健的小迷弟应助苏苏采纳,获得10
15秒前
Bonnie发布了新的文献求助10
15秒前
龙猫嗯啊应助赵雪采纳,获得10
16秒前
张欢馨应助赵雪采纳,获得10
16秒前
16秒前
九点睡关注了科研通微信公众号
19秒前
19秒前
丘比特应助ineout采纳,获得10
20秒前
21秒前
22秒前
xc发布了新的文献求助10
24秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Reducing Compassion Fatigue, Secondary Traumatic Stress and Burnout 600
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Mammalian Synthetic Biology 500
Auslegungsgeschichte 500
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7638193
求助须知:如何正确求助?哪些是违规求助? 9211518
关于积分的说明 19758981
捐赠科研通 7205200
什么是DOI,文献DOI怎么找? 3275818
关于科研通互助平台的介绍 2437416
邀请新用户注册赠送积分活动 2273004