Assessing the Scale Effects of Dynamics and Socio-Ecological Drivers of Ecosystem Service Interactions in the Lishui River Basin, China DOI Open Access

Suping Zeng,

Chunqian Jiang,

Yanfeng Bai

et al.

Sustainability, Journal Year: 2024, Volume and Issue: 16(20), P. 8990 - 8990

Published: Oct. 17, 2024

Grasping how scale influences the interactions among ecosystem services (ESs) is vital for sustainable management of multiple ESs at regional level. However, it currently unclear whether actual ES and their driving mechanisms are consistent across different spatial temporal scales. Therefore, using Lishui River Basin China as a case study, we analyzed distribution five key three scales (grid, sub-watershed, county) from 2010 to 2020. We also innovatively used Pearson correlation analysis, Self-organizing Mapping (SOM), random forest analysis assess dynamic trends trade-offs/synergies ESs, service bundles (ESBs), main socio-ecological drivers spatiotemporal The findings showed that (1) varied with land use types, high-value areas mainly in western northern mountainous regions lower values eastern part. Temporally, significant improvements were observed soil conservation (SC, 3028.23–5023.75 t/hm2) water yield (WY, 558.79–969.56 mm), while carbon sequestration (CS) habitat quality (HQ) declined (2) trade-offs synergies exhibited enhanced larger scales, being predominant relationship. These relationships remained relatively stable over time, pairs related nitrogen export (NE). (3) ESBs At grid scale, frequent ESB flows transformations observed, use/land cover (LULC) drivers. other climate (especially temperature) topography dominant. Ecosystem focused on city or downstream east basin, aligning urban expansion trends. insights will offer valuable guidance decision-making regarding hierarchical strategies resource allocation ESs.

Language: Английский

Spatiotemporal heterogeneity of ecosystem service interactions and their determining thresholds across distinct climate zones in the temperate desert steppe of northern China DOI Creative Commons
Xin Li, Xiangdong Li, Xiaoqian Li

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113099 - 113099

Published: Jan. 1, 2025

Language: Английский

Citations

1
Spatiotemporal Differentiation and Its Attribution of the Ecosystem Service Trade-Off/Synergy in the Yellow River Basin DOI Creative Commons
Huiying Sun, Zhenhua Di,

Piling Sun

et al.

Land, Journal Year: 2024, Volume and Issue: 13(3), P. 369 - 369

Published: March 14, 2024

Clarifying the spatio-temporal patterns of ecosystem services trade-off/synergy relationships (ESTSs) and their attribution in Yellow River Basin is crucial to constructing ecological civilization China. This study first analyzed change (ESs) including water yield, soil conservation, carbon sequestration, habitat quality during 2000–2020 based on InVEST RUSLE models. Then, spatial autocorrelation methods were used quantify differentiation ESTSs, Geo-detector method was employed identify contributions driving factors associated with natural, social-economic, regional policy aspects ESTSs. Finally, random forest analysis variance validate reasonability major obtained by Geo-detector. The main findings include: (1) In 2000–2020, increased, sequestration decreased. ESs had a pattern high east low west. (2) Overall, there synergistic between four Ess. distribution expansion synergy zone trade-off occupied majority. zones tended be concentrated northwest southeast area. contrast, more scattered than zone, mainly focused east-central southwestern parts Basin. (3) both showed that natural strong explanatory power which NDVI key driver. Both results interactions exerted most significant influence followed interaction socio-economic factors.

Language: Английский

Citations

7
Interactions between ecosystem services and their causal relationships with driving factors: A case study of the Tarim River Basin, China DOI Creative Commons

Rongqin Yang,

Zhenxia Mu, Rui Gao

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 169, P. 112810 - 112810

Published: Nov. 15, 2024

Language: Английский

Citations

6
Spatiotemporal heterogeneity management: Optimizing the critical role of ecosystem services in achieving Sustainable Development Goals DOI Creative Commons

Lingli Zuo,

Guohua Liu,

Junyan Zhao

et al.

Geography and sustainability, Journal Year: 2024, Volume and Issue: 6(1), P. 100211 - 100211

Published: Aug. 6, 2024

Ecosystems play a pivotal role in advancing Sustainable Development Goals (SDGs) by providing indispensable and resilient ecosystem services (ESs). However, the limited analysis of spatiotemporal heterogeneity often restricts recognition ESs' roles attaining SDGs landscape planning. We selected 183 counties Sichuan Province as study area mapped 10 7 ESs from 2000 to 2020. used correlation analysis, principal component Geographically Temporally Weighted Regression model, self-organizing maps reveal impacts bundle on develop spatial planning management strategies. The results showed that (1) was improved all counties, with SDG 1 (No Poverty) 3 (Good Health Well-being) exhibiting poor performance. Western demonstrated stronger performance environment-related Province, while Basin better progress socio-economic-related SDGs; (2) habitat quality, carbon sequestration, air pollution removal, soil retention significantly influenced development 9 (3) supporting, regulating, provisioning service bundles have persistent stable effects SDG1, SDG8, SDG11, SDG13, SDG15. These findings substantiate need for integrated multiple facilitate regional achievement geographically intricate areas.

Language: Английский

Citations

4
Assessment of ecological asset quality and its drivers in Agro-pastoral Ecotone of China DOI Creative Commons

Wenmin Liu,

Zhiyuan Cheng,

Jie Li

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113072 - 113072

Published: Jan. 1, 2025

Language: Английский

Citations

0
Integrating Spatial–Temporal Heterogeneity and Driving Mechanisms of Ecosystem Services Into Spatial Management Across Urban Hierarchies: A Case of the Yangtze River Economic Belt, China DOI Open Access

Qiaoling Luo,

Junfang Zhou,

Mingxing Liu

et al.

Land Degradation and Development, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 28, 2025

ABSTRACT Effective management of ecosystem services (ESs) is critical for sustainable regional development. Multi‐scale ESs assessments provide valuable insights spatial management. However, limited attention has been given to the spatial–temporal heterogeneity and driving mechanisms across urban hierarchies their integration into Therefore, taking Yangtze River Economic Belt in China as a case study, we assessed service values (ESVs) five from 2000 2020. Results showed that area ratios variation ESVs trends were typically S‐shaped small cities super cities. High‐value clusters decreased, low‐value ESV linear increase intensified. Human activities predominantly impacted lower hierarchy, whereas terrain conditions significantly higher hierarchy. Furthermore, novel framework was proposed integrate management, emphasizing multi‐scale ESs. This study effective strategies support region‐specific

Language: Английский

Citations

0
Evaluating ecosystem services under various trajectories and land use/land cover changes in a densely populated area, Iran DOI
Bahman Veisi Nabikandi, Farzin Shahbazi, Asim Biswas

et al.

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)

Published: April 10, 2025

Language: Английский

Citations

0
Spatio-Temporal Dynamics and Drivers of Ecosystem Service Bundles in the Altay Region: Implications for Sustainable Land Management DOI Creative Commons
Suyan Yi, Hongwei Wang, Ling Xie

et al.

Land, Journal Year: 2024, Volume and Issue: 13(6), P. 805 - 805

Published: June 6, 2024

Understanding the dynamics of ecosystem services (ESs) in arid landscapes and socio-ecological systems is crucial for sustainable development human well-being. This study uses Invest model to quantify spatio-temporal changes four key ecosystems Altay from 1990 2020: water yield (water yield), carbon stock (carbon stock), soil retention (soil retention), habitat quality (habitat quality). The trade-offs/synergies between different ESs were investigated via Spearman’s correlation analysis. Ecosystem service bundles (ESBs) mapped using self-organizing mapping (SOM), drivers ES relationships ESBs revealed through redundancy results showed that increased by 33.7% 1.2%, while decreased 3.5% 1.24%, respectively. spatial distribution pattern had a clear zonal pattern, with northern mountainous areas higher than southern desert areas. six pairs ESs, general, mainly low trade-off high synergistic relationships, trade-offs stock, quality, decreasing trend over time. Four types distinguished, compositional differences within each ESB determined interactions landscape types. There are complex non-linear years. Before 2010, ecological factors influencing ESBs, whereas social environmental combined drive allocations after 2010. Additionally, this found implementation conservation measures, such as reforestation land management practices, positively influenced provision region. These findings underscore importance integrating efforts into use planning decision-making processes ensure delivery landscapes.

Language: Английский

Citations

2
Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China DOI Creative Commons
Yaobin Liu,

Nan Huang,

Chenghao Liu

et al.

Frontiers in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 12

Published: Feb. 22, 2024

Clarifying the driving mechanisms of spatial and temporal changes in regulating ecosystem service value (RESV) is an important part realizing goal sustainable development. Existing studies have focused on specific factors, ignoring complex interactions between factors their regional differences. In this regard, RESV its different zones (core area, fringe peripheral area) were explored Poyang Lake Area, China. The results showed that spatially distribution characteristics area > core while lakes influenced provision services, showing per unit was higher gradually declined with increase distance from lakes, presenting decreasing trend area. From 2000 to 2020, study lost 70.5988 billion CNY for RESV, which most affected. Further analysis mechanism areas found there are differences paths factors: Population density mainly affects precipitation GDP land

Language: Английский

Citations

1
Spatiotemporal changes and driving factors of ecosystem services between karst and non-karst World Heritage sites in Southwest China DOI Creative Commons
Yue Chen, Rong Li, Kangning Xiong

et al.

Heritage Science, Journal Year: 2024, Volume and Issue: 12(1)

Published: Aug. 2, 2024

Abstract Understanding the spatiotemporal variation and drivers of ecosystem services is fundamental to optimal management sustainable development World Heritage (WH) sites. Although WH sites face multiple natural anthropogenic threats, our understanding their still limited, especially for karst In this study, we assessed habitat quality (HQ), carbon storage (CS), soil retention (SR), water conservation (WC), combined service (CES) non-karst in Southwest China from 2000 2020 using InVEST model. We also trade-offs/synergies among spatial overlay method, identified driving factors geographical detector structural equation models. The results showed that exhibited high variation. particular, there were higher values property zone than buffer zone, an increasing trend SR but a decreasing HQ CES over time. Compared sites, had significantly lower HQ, CS, SR, CES, heterogeneity WC, CES. Weak trade-offs dominated with proportion weak synergies strong synergies. provision was primarily influenced by (e.g., landscape division index normalized difference vegetation index), followed distance road population density). Overall, these findings may have important implications decision-making aimed at protecting outstanding universal value, authenticity, integrity different attributes.

Language: Английский

Citations

1