Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained.Quantitative assessment of ecosystem services and complex interactions can contribut...Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained.Quantitative assessment of ecosystem services and complex interactions can contribute positively to the achievement of the Sustainable Development Goals(SDGs)for urban agglomerations.However,studies on the future contribution of multi-scenario ecosystem services to the SDGS are lacking.We pronovel integrated modeling framework that integrates the CLUES,InVEST,SOM,and GWR approaches to address the complex relationship between ecosystem services over a long“past-present-future”time series.We construct a novel ecosystem service bundle-based approach for measuring urban agglomerations progress towards achieving ecologically relevant sustainable development goals at multiple scales.In the future scenario,the water yield(WY),habitat quality(HQ),and soil conservation(SC)show similar spatial patterns,with comparable spatial grids,while carbon stock(CS)remains predominantly unchanged and the ecological protection scenario(EPS)improves more significantly.The high-synergy regions are mainly distributed in bundle 4,and most of the trade-off regions appear in bundles 1 and 2.Over the last 30 years,all but the water-related SDGs are declining in bundle 1 of the two urban agglomerations,which are 15%higher in the Guangxi Beibu Gulf(GBG)than in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA).From 2020 to 2035,the three scenarios demonstrate that the optimization of the SDGs progresses most effectively under the future ecological protection scenario(EPS).In particular,bundles 3 and 4 are significantly improved.This critical new knowledge can be used in sustainable ecosystem management and decision-making in urban agglomerations.展开更多
Understanding intricate interactions between natural–social factors and ecosystem service synergies and trade-offs(ESS/EST)can be valuable for promoting the sustainable development of multiple ecosystem services(ESs)...Understanding intricate interactions between natural–social factors and ecosystem service synergies and trade-offs(ESS/EST)can be valuable for promoting the sustainable development of multiple ecosystem services(ESs).Taking Beijing as the study area,this study was conducted from the perspective of ecosystem service bundles(ESBs).First,based on the identification of key ecological risks,the supply of 5 ESs was quantified.Then,3 ESBs were identified through the cluster analysis of the ESs.We explored the synergies and trade-offs between ES pairs in different ESBs and quantified their strengths.By further exploring the influence of natural–social factors on ESS/EST,we developed targeted management policies in different ESBs to improve management efficiency.At the township scale,Beijing is divided into 3 ESBs.Marked differences in the ESS/EST were found among each bundle,indicating the necessity of zonal management.The results showed that landscape composition was the dominant factor affecting ESS in ESB3 and EST in ESB2,human activities had the greatest influence on ESS in ESB2,while biophysical indicators had the highest degree of contribution to ESS and EST in ESB1 and EST in ESB3.These results support the formulation of sustainable management strategies.The results of the study emphasize the importance of considering ESS/EST and their natural–social factors in different ESBs when formulating effective policies,which can provide useful guidance for sustainable urban planning and development and can be further applied to metropolitan areas around the world.展开更多
Interactions among ecosystem services(ESs)are spatially heterogeneous,shaped by both stable(unidirectional)and unstable(context-dependent)influences of socio-economic development and climate change.These complexities ...Interactions among ecosystem services(ESs)are spatially heterogeneous,shaped by both stable(unidirectional)and unstable(context-dependent)influences of socio-economic development and climate change.These complexities pose significant challenges for spatially adaptive ecosystem management.Ecosystem service bundles(ESBs),as recurring combinations of ESs,offer a valuable framework to capture such interactions.Here,we proposed an integrated analytical framework that combines K-means clustering,the geographical detector(GD)model,and geographically and temporally weighted regression(GTWR)models to evaluate how socio-economic and climatic drivers influence ESBs across space and time.Using Hanshui River Basin(HRB)in central China as a case study,we quantified ES dynamics from 2000 to 2020,identified ESBs and stable and unstable effects of multiple drivers.The results showed that carbon sequestration(CS),water yield(WY),and aesthetic landscape(AL)increased by 32.80%,9.00%,and 7.34%,respectively,while soil retention(SR)and food supply(FS)declined by 8.38%and 5.36%.Five distinct ESBs were identified,namely ecologically fragile bundle(EFB),agricultural production bundle(APB),water supply bundle(WSB),forest ecological bundle(FEB),and ecological conservation bundle(ECB).Among these,FEB expanded to more than 35.75%of the HRB,and APB exhibited the sharpest decline(-28.64%).Land use intensity(LUI)was the primary driver of the spatial heterogeneity of ESBs,while synergistic and nonlinear interactions among multiple factors increasingly amplified their effects over time.Notably,annual precipitation(AP)emerged as the only stable basin-scale driver,consistently enhancing ES performance,while gross domestic product(GDP)and normalized difference vegetation index(NDVI)had stable yet spatially differentiated effects across bundles.Our findings highlight the significance of distinguishing stable/unstable driver effects on ES dynamics to inform regionally adaptive ecosystem governance.The proposed framework provides valuable insights into ES interactions,identify spatial priorities,and support policy interventions that balance ecological conservation with socio-economic development.展开更多
The degradation of ecosystem structure and function on the Qinghai-Tibet Plateau is the result of a combination of natural and anthropogenic factors,with landscape change driven by global change and human activities b...The degradation of ecosystem structure and function on the Qinghai-Tibet Plateau is the result of a combination of natural and anthropogenic factors,with landscape change driven by global change and human activities being one of the major ecological challenges facing the region.This study analyzed the spatiotemporal characteristics of ecosystem services(ESs)and landscape patterns in eastern Qinghai province(EQHP)from 2000 to 2018using multisource datasets and landscape indices.Three ecosystem service bundles(ESBs)were identified using the self-organizing map(SOM),and changes in ecosystem structure and function were analyzed through bundle-landscaped spatial combinations.The study also explored the interactions between ESs and natural and human factors using redundancy analysis(RDA).We revealed an increase in total ecosystem service in the EQHP from 1.59 in 2000 to 1.69 in 2018,with a significant change in landscape patterns driven by the conversion of unused land to grassland in the southwest.Forestland,grassland,and unused land were identified as important to the supply of ESs.In comparison to human activities,natural environmental factors were found to have a stronger impact on changes in ESs,with vegetation,meteorology,soil texture,and landscape composition being the main driving factors.However,the role of driving factors within different ESBs varied significantly.Exploring the response of ecosystem services to changes in landscape patterns can provide valuable insights for achieving sustainable ecological management and contribute to ecological restoration efforts.展开更多
基金National Natural Science Foundation of China,No.U21A2022,No.U1901219,No.42071393,No.42101369。
文摘Ecosystem services in urban agglomerations are the environmental conditions under which human survival and development are sustained.Quantitative assessment of ecosystem services and complex interactions can contribute positively to the achievement of the Sustainable Development Goals(SDGs)for urban agglomerations.However,studies on the future contribution of multi-scenario ecosystem services to the SDGS are lacking.We pronovel integrated modeling framework that integrates the CLUES,InVEST,SOM,and GWR approaches to address the complex relationship between ecosystem services over a long“past-present-future”time series.We construct a novel ecosystem service bundle-based approach for measuring urban agglomerations progress towards achieving ecologically relevant sustainable development goals at multiple scales.In the future scenario,the water yield(WY),habitat quality(HQ),and soil conservation(SC)show similar spatial patterns,with comparable spatial grids,while carbon stock(CS)remains predominantly unchanged and the ecological protection scenario(EPS)improves more significantly.The high-synergy regions are mainly distributed in bundle 4,and most of the trade-off regions appear in bundles 1 and 2.Over the last 30 years,all but the water-related SDGs are declining in bundle 1 of the two urban agglomerations,which are 15%higher in the Guangxi Beibu Gulf(GBG)than in the Guangdong-Hong Kong-Macao Greater Bay Area(GBA).From 2020 to 2035,the three scenarios demonstrate that the optimization of the SDGs progresses most effectively under the future ecological protection scenario(EPS).In particular,bundles 3 and 4 are significantly improved.This critical new knowledge can be used in sustainable ecosystem management and decision-making in urban agglomerations.
基金supported by the Key Project of the State Forestry and Grassland Administration of China(2023132050)the Major Project of Teaching Reform of Beijing Forestry University 2023 (BJFU2023JYZD002)
文摘Understanding intricate interactions between natural–social factors and ecosystem service synergies and trade-offs(ESS/EST)can be valuable for promoting the sustainable development of multiple ecosystem services(ESs).Taking Beijing as the study area,this study was conducted from the perspective of ecosystem service bundles(ESBs).First,based on the identification of key ecological risks,the supply of 5 ESs was quantified.Then,3 ESBs were identified through the cluster analysis of the ESs.We explored the synergies and trade-offs between ES pairs in different ESBs and quantified their strengths.By further exploring the influence of natural–social factors on ESS/EST,we developed targeted management policies in different ESBs to improve management efficiency.At the township scale,Beijing is divided into 3 ESBs.Marked differences in the ESS/EST were found among each bundle,indicating the necessity of zonal management.The results showed that landscape composition was the dominant factor affecting ESS in ESB3 and EST in ESB2,human activities had the greatest influence on ESS in ESB2,while biophysical indicators had the highest degree of contribution to ESS and EST in ESB1 and EST in ESB3.These results support the formulation of sustainable management strategies.The results of the study emphasize the importance of considering ESS/EST and their natural–social factors in different ESBs when formulating effective policies,which can provide useful guidance for sustainable urban planning and development and can be further applied to metropolitan areas around the world.
基金Under the auspices of National Natural Science Foundation of China(No.42171414)。
文摘Interactions among ecosystem services(ESs)are spatially heterogeneous,shaped by both stable(unidirectional)and unstable(context-dependent)influences of socio-economic development and climate change.These complexities pose significant challenges for spatially adaptive ecosystem management.Ecosystem service bundles(ESBs),as recurring combinations of ESs,offer a valuable framework to capture such interactions.Here,we proposed an integrated analytical framework that combines K-means clustering,the geographical detector(GD)model,and geographically and temporally weighted regression(GTWR)models to evaluate how socio-economic and climatic drivers influence ESBs across space and time.Using Hanshui River Basin(HRB)in central China as a case study,we quantified ES dynamics from 2000 to 2020,identified ESBs and stable and unstable effects of multiple drivers.The results showed that carbon sequestration(CS),water yield(WY),and aesthetic landscape(AL)increased by 32.80%,9.00%,and 7.34%,respectively,while soil retention(SR)and food supply(FS)declined by 8.38%and 5.36%.Five distinct ESBs were identified,namely ecologically fragile bundle(EFB),agricultural production bundle(APB),water supply bundle(WSB),forest ecological bundle(FEB),and ecological conservation bundle(ECB).Among these,FEB expanded to more than 35.75%of the HRB,and APB exhibited the sharpest decline(-28.64%).Land use intensity(LUI)was the primary driver of the spatial heterogeneity of ESBs,while synergistic and nonlinear interactions among multiple factors increasingly amplified their effects over time.Notably,annual precipitation(AP)emerged as the only stable basin-scale driver,consistently enhancing ES performance,while gross domestic product(GDP)and normalized difference vegetation index(NDVI)had stable yet spatially differentiated effects across bundles.Our findings highlight the significance of distinguishing stable/unstable driver effects on ES dynamics to inform regionally adaptive ecosystem governance.The proposed framework provides valuable insights into ES interactions,identify spatial priorities,and support policy interventions that balance ecological conservation with socio-economic development.
基金The Second Tibetan Plateau Scientific Expedition and Research Program,No.2019QZKK0405The Chinese Academy of Sciences+1 种基金Strategic Pilot Science and Technology Project(Class A),No.XDA2002040201The Fundamental Research Funds for the Central Universities,CHD,No.300102352201。
文摘The degradation of ecosystem structure and function on the Qinghai-Tibet Plateau is the result of a combination of natural and anthropogenic factors,with landscape change driven by global change and human activities being one of the major ecological challenges facing the region.This study analyzed the spatiotemporal characteristics of ecosystem services(ESs)and landscape patterns in eastern Qinghai province(EQHP)from 2000 to 2018using multisource datasets and landscape indices.Three ecosystem service bundles(ESBs)were identified using the self-organizing map(SOM),and changes in ecosystem structure and function were analyzed through bundle-landscaped spatial combinations.The study also explored the interactions between ESs and natural and human factors using redundancy analysis(RDA).We revealed an increase in total ecosystem service in the EQHP from 1.59 in 2000 to 1.69 in 2018,with a significant change in landscape patterns driven by the conversion of unused land to grassland in the southwest.Forestland,grassland,and unused land were identified as important to the supply of ESs.In comparison to human activities,natural environmental factors were found to have a stronger impact on changes in ESs,with vegetation,meteorology,soil texture,and landscape composition being the main driving factors.However,the role of driving factors within different ESBs varied significantly.Exploring the response of ecosystem services to changes in landscape patterns can provide valuable insights for achieving sustainable ecological management and contribute to ecological restoration efforts.
