Pub Date : 2025-06-13DOI: 10.1016/j.geosus.2025.100326
Xianlei Fan , Yangjian Zhang , Jing Zhang , Edith Bai
Although Vegetation Restoration Programs (VRPs) on the Loess Plateau, China, have significantly improved the region’s ecological condition, their impact on the local economy and agriculture remain unclear. Here we used the difference-in-differences analysis to quantify the effects of the VRPs on population, economic, and agricultural aspects. Results suggest that the implementation of the VRPs increased mean county-based Gross Domestic Product by 148 % and per capita grain production by 30 %, but decreased rural labor resources by 11 %. VRPs promoted the transfer of population to the secondary industry and increased the income of local farmers. We predict that grain production will likely start to decline when the restoration area exceeds approximately 55 % of the total county area in the future. Our study suggests that while VRPs on the Loess Plateau are economically sustainable, their expansion beyond a certain threshold could jeopardize agriculture.
{"title":"Agricultural and socioeconomic effects of vegetation restoration on the Loess Plateau, China","authors":"Xianlei Fan , Yangjian Zhang , Jing Zhang , Edith Bai","doi":"10.1016/j.geosus.2025.100326","DOIUrl":"10.1016/j.geosus.2025.100326","url":null,"abstract":"<div><div>Although Vegetation Restoration Programs (VRPs) on the Loess Plateau, China, have significantly improved the region’s ecological condition, their impact on the local economy and agriculture remain unclear. Here we used the difference-in-differences analysis to quantify the effects of the VRPs on population, economic, and agricultural aspects. Results suggest that the implementation of the VRPs increased mean county-based Gross Domestic Product by 148 % and per capita grain production by 30 %, but decreased rural labor resources by 11 %. VRPs promoted the transfer of population to the secondary industry and increased the income of local farmers. We predict that grain production will likely start to decline when the restoration area exceeds approximately 55 % of the total county area in the future. Our study suggests that while VRPs on the Loess Plateau are economically sustainable, their expansion beyond a certain threshold could jeopardize agriculture.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 5","pages":"Article 100326"},"PeriodicalIF":8.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-13DOI: 10.1016/j.geosus.2025.100327
Peifang Leng , Zhipin Ai , Fadong Li
Water is an indispensable resource for agricultural production. However, its value in agriculture remains largely unknown. This oversight results in agriculture water value being seldom integrated into water pricing, thereby restricting the information available for water allocation decisions. In this study, we estimated irrigation water value over the last 30 years on the north slope of the Tianshan Mountains, where agriculture is largely dependent on irrigation water supply. Using a data-parsimonious biophysical framework with a function of crop growth and water-demanding dynamics, we estimate the additional net economic benefit of irrigated agriculture relative to rainfed conditions for three major crops at the county level. Our results reveal that mean irrigation water values were 0.27, 0.32, and 0.16 USD m–3 for cotton, maize, and wheat, respectively, which were 2.0 − 3.2 times higher than global estimates. The value of irrigation water significantly increased over time, primarily driven by rising crop prices and improved water use efficiency. Our findings indicate that farmers in arid regions with water limitations may favor crops with high irrigation water use efficiency. Wheat is suggested to be spatially reallocated in light of the economic benefit, given its relatively low output price and water use efficiency. Irrigation water value was more sensitive to precipitation than air temperature by lowering crop prices and narrowing the gap between rain-fed and irrigated yields. The inclusion of irrigation water value in planning could lead to more efficient use of water resources and support decisions regarding irrigation investments, water use rights, and, ultimately, food sustainability.
{"title":"The value of water in agriculture over the past 30 years on the north slope of the Tianshan Mountains","authors":"Peifang Leng , Zhipin Ai , Fadong Li","doi":"10.1016/j.geosus.2025.100327","DOIUrl":"10.1016/j.geosus.2025.100327","url":null,"abstract":"<div><div>Water is an indispensable resource for agricultural production. However, its value in agriculture remains largely unknown. This oversight results in agriculture water value being seldom integrated into water pricing, thereby restricting the information available for water allocation decisions. In this study, we estimated irrigation water value over the last 30 years on the north slope of the Tianshan Mountains, where agriculture is largely dependent on irrigation water supply. Using a data-parsimonious biophysical framework with a function of crop growth and water-demanding dynamics, we estimate the additional net economic benefit of irrigated agriculture relative to rainfed conditions for three major crops at the county level. Our results reveal that mean irrigation water values were 0.27, 0.32, and 0.16 USD m<sup>–3</sup> for cotton, maize, and wheat, respectively, which were 2.0 − 3.2 times higher than global estimates. The value of irrigation water significantly increased over time, primarily driven by rising crop prices and improved water use efficiency. Our findings indicate that farmers in arid regions with water limitations may favor crops with high irrigation water use efficiency. Wheat is suggested to be spatially reallocated in light of the economic benefit, given its relatively low output price and water use efficiency. Irrigation water value was more sensitive to precipitation than air temperature by lowering crop prices and narrowing the gap between rain-fed and irrigated yields. The inclusion of irrigation water value in planning could lead to more efficient use of water resources and support decisions regarding irrigation investments, water use rights, and, ultimately, food sustainability.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 5","pages":"Article 100327"},"PeriodicalIF":8.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-11DOI: 10.1016/j.geosus.2025.100325
Hua Liu , Shiliang Liu , Fangfang Wang , Yifei Zhao , Yuhong Dong , Lam-Son Phan Tran
Ecological restoration is considered an important way to mitigate ecosystem degradation and improve regional nature’s contributions to people (NCPs). Ecological planning is a prerequisite for ecological restoration and the prevention of future ecological risks. However, few studies have focused on integrating ecological plans within the framework of Sustainable Development Goals (SDGs) and shared socioeconomic pathways (SSPs). In this study, taking the Qinghai‒Xizang Plateau (QXP) as a case, we assessed ecological restoration priorities based on NCPs under various SDGs and SSP scenarios. Specifically, the land use demand was predicted using system dynamics (SD) and cellular automata (CA) models between 2030 and 2060 under SDG-SSP scenarios. In addition, habitat maintenance (NCP1), climate regulation (NCP4), and water quantity regulation (NCP6) were assessed based on the predicted land use. Finally, priority areas for ecological restoration were identified using a zonation model. The results indicated that the grassland, forest, and cultivated areas will increase in the SDGs and SSPs scenarios, respectively. The high-value NCP areas are mainly located in the southeast part of the QXP, accounting for 45.16 % of the study area. In addition, the ecological restoration area involves grassland, cultivated and bare land. In the single-objective scenario, NCP1, NCP4, and NCP6 can be improved by 30.29 %, 28.75 % and 25.63 %, respectively, through the restoration of 15.33 % of the priority areas identified in 2015. When shifting to a multi-objective cooperative optimum, NCP1, NCP4 and NCP6 can be improved 35.79 % by restoring 54.96 % of the priority areas. This study provides insight into how SDGs and SSPs can contribute to ecological restoration for mitigating ecosystem degradation under SDG-SSP scenarios.
{"title":"Ecological restoration priority on the Qinghai‒Xizang Plateau based on the nature’s contributions to people under SDGs-SSPs scenarios","authors":"Hua Liu , Shiliang Liu , Fangfang Wang , Yifei Zhao , Yuhong Dong , Lam-Son Phan Tran","doi":"10.1016/j.geosus.2025.100325","DOIUrl":"10.1016/j.geosus.2025.100325","url":null,"abstract":"<div><div>Ecological restoration is considered an important way to mitigate ecosystem degradation and improve regional nature’s contributions to people (NCPs). Ecological planning is a prerequisite for ecological restoration and the prevention of future ecological risks. However, few studies have focused on integrating ecological plans within the framework of Sustainable Development Goals (SDGs) and shared socioeconomic pathways (SSPs). In this study, taking the Qinghai‒Xizang Plateau (QXP) as a case, we assessed ecological restoration priorities based on NCPs under various SDGs and SSP scenarios. Specifically, the land use demand was predicted using system dynamics (SD) and cellular automata (CA) models between 2030 and 2060 under SDG-SSP scenarios. In addition, habitat maintenance (NCP1), climate regulation (NCP4), and water quantity regulation (NCP6) were assessed based on the predicted land use. Finally, priority areas for ecological restoration were identified using a zonation model. The results indicated that the grassland, forest, and cultivated areas will increase in the SDGs and SSPs scenarios, respectively. The high-value NCP areas are mainly located in the southeast part of the QXP, accounting for 45.16 % of the study area. In addition, the ecological restoration area involves grassland, cultivated and bare land. In the single-objective scenario, NCP1, NCP4, and NCP6 can be improved by 30.29 %, 28.75 % and 25.63 %, respectively, through the restoration of 15.33 % of the priority areas identified in 2015. When shifting to a multi-objective cooperative optimum, NCP1, NCP4 and NCP6 can be improved 35.79 % by restoring 54.96 % of the priority areas. This study provides insight into how SDGs and SSPs can contribute to ecological restoration for mitigating ecosystem degradation under SDG-SSP scenarios.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 5","pages":"Article 100325"},"PeriodicalIF":8.0,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144563483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study examines the impact of urbanization on the Surface Urban Heat Island (SUHI) effect in the Bangkok Metropolitan Region (BMR) over a 36-year period, utilizing advanced machine learning techniques to assess changes in land use and land cover (LULC). The research addresses three key questions: (1) How have changes in LULC influenced the dynamics of the urban heat island (UHI) effect in the BMR? (2) What roles do green and blue infrastructure play in mitigating urban heat? (3) How effectively can machine learning models classify LULC changes and provide insights to support sustainable urban planning? The findings reveal a strong correlation between urban growth and increased land surface temperatures (LST), with parks and water bodies exhibiting lower LSTs, emphasizing the importance of green and blue infrastructure in mitigating urban heat. The SUHI effect, initially measured at 3 °C from 1988 to 1991, peaked at 4.8 °C between 2012 and 2019 before slightly declining to 4.1 °C in recent years due to urban greening initiatives. However, ongoing urban development continues to diminish green spaces and water bodies, underscoring the urgent need for sustainable urban planning. Economic factors, including the 1997 Asian Financial Crisis and land tax laws introduced in 2019, influenced land use patterns, further exacerbating the SUHI effect. The research highlights the necessity of integrated urban management and sustainable land use policies to enhance climate resilience in rapidly urbanizing regions like the BMR.
{"title":"A 36-year geospatial analysis of urbanization dynamics and surface urban heat island effect: Case study of the Bangkok Metropolitan Region","authors":"Nattapong Puttanapong , Nithima Nuengjumnong , JoJinda SaeJung , Sitthisak Moukomla","doi":"10.1016/j.geosus.2025.100322","DOIUrl":"10.1016/j.geosus.2025.100322","url":null,"abstract":"<div><div>This study examines the impact of urbanization on the Surface Urban Heat Island (SUHI) effect in the Bangkok Metropolitan Region (BMR) over a 36-year period, utilizing advanced machine learning techniques to assess changes in land use and land cover (LULC). The research addresses three key questions: (1) How have changes in LULC influenced the dynamics of the urban heat island (UHI) effect in the BMR? (2) What roles do green and blue infrastructure play in mitigating urban heat? (3) How effectively can machine learning models classify LULC changes and provide insights to support sustainable urban planning? The findings reveal a strong correlation between urban growth and increased land surface temperatures (LST), with parks and water bodies exhibiting lower LSTs, emphasizing the importance of green and blue infrastructure in mitigating urban heat. The SUHI effect, initially measured at 3 °C from 1988 to 1991, peaked at 4.8 °C between 2012 and 2019 before slightly declining to 4.1 °C in recent years due to urban greening initiatives. However, ongoing urban development continues to diminish green spaces and water bodies, underscoring the urgent need for sustainable urban planning. Economic factors, including the 1997 Asian Financial Crisis and land tax laws introduced in 2019, influenced land use patterns, further exacerbating the SUHI effect. The research highlights the necessity of integrated urban management and sustainable land use policies to enhance climate resilience in rapidly urbanizing regions like the BMR.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 4","pages":"Article 100322"},"PeriodicalIF":8.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-09DOI: 10.1016/j.geosus.2025.100323
Weilong Li , Meng Zhang , Mengyao Han
Photovoltaics play an essential role in supporting the unprecedented growth of renewable energy transition as well as facing a series of trade risks due to complex international dynamics and intermittent trade disruptions. By combining complex network modeling and shock propagation analysis, the spatial-temporal evolution of photovoltaic supply chains worldwide was depicted, and the potential trade risks under different scenarios were elucidated in this study. The results show that the trade patterns of photovoltaic supply chains have evolved significantly, particularly characterized by the rise of China, Malaysia, Vietnam, and Thailand. The complexity of photovoltaic supply chains increases significantly with the addition of more nodes and edges in the networks. The vulnerability of critical photovoltaic supply chains tends to intensify with the increasing concentration of global supply chains in a geographic sense. The interruption of trade ties between China and Vietnam may lead to the most drastic impact on photovoltaic supply chains, followed by trade disruptions between Southeast Asia and North America. By unveiling the spatial-temporal network evolution and potential trade disruption of global photovoltaic supply chains, it is practical to propose rational and feasible strategies that consider the geographical diversification and international cooperation of photovoltaic supply chains worldwide.
{"title":"Geographical linkage and trade disruption within global photovoltaic supply chains","authors":"Weilong Li , Meng Zhang , Mengyao Han","doi":"10.1016/j.geosus.2025.100323","DOIUrl":"10.1016/j.geosus.2025.100323","url":null,"abstract":"<div><div>Photovoltaics play an essential role in supporting the unprecedented growth of renewable energy transition as well as facing a series of trade risks due to complex international dynamics and intermittent trade disruptions. By combining complex network modeling and shock propagation analysis, the spatial-temporal evolution of photovoltaic supply chains worldwide was depicted, and the potential trade risks under different scenarios were elucidated in this study. The results show that the trade patterns of photovoltaic supply chains have evolved significantly, particularly characterized by the rise of China, Malaysia, Vietnam, and Thailand. The complexity of photovoltaic supply chains increases significantly with the addition of more nodes and edges in the networks. The vulnerability of critical photovoltaic supply chains tends to intensify with the increasing concentration of global supply chains in a geographic sense. The interruption of trade ties between China and Vietnam may lead to the most drastic impact on photovoltaic supply chains, followed by trade disruptions between Southeast Asia and North America. By unveiling the spatial-temporal network evolution and potential trade disruption of global photovoltaic supply chains, it is practical to propose rational and feasible strategies that consider the geographical diversification and international cooperation of photovoltaic supply chains worldwide.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 5","pages":"Article 100323"},"PeriodicalIF":8.0,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144631855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01DOI: 10.1016/j.geosus.2025.100321
Wenwu Zhao , Zizhao Ni , Caichun Yin , Yanxu Liu , Paulo Pereira
Amid ongoing global environmental change and the critical pursuit of sustainable development, human–environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships, underscoring an urgent need for innovative research frameworks. Integrated geography synthesizes physical geography, human geography, and geographic information science, providing key frameworks for understanding complex human–environment systems. This editorial proposes an emerging research framework for integrated geography—“Composite driving–System evolution–Coupling mechanism–Synergistic regulation (CSCS)”—based on key issues such as climate change, biodiversity loss, resource scarcity, and social–ecological interactions, which have been highlighted in both recent critical literature on human–environment systems and UN assessment reports. The framework starts with diverse composite driving forces, extends to the evolution of human–environment system structures, processes, and functions that these drivers induce, explores couplings within human–environment systems, and calls for regulation aimed at sustainable development in synergies. Major research frontiers include understanding the cascading “evolution–coupling” effects of shocks; measuring system resilience, thresholds, and safe and just operating space boundaries; clarifying linkage mechanisms across scales; and achieving synergistic outcomes for multi-objective sustainability. This framework will help promote the interdisciplinary integration and development of integrated geography, and provide geographical solutions for the global sustainable development agenda.
{"title":"Research framework for integrated geography: Composite driving–system evolution–coupling mechanism–synergistic regulation","authors":"Wenwu Zhao , Zizhao Ni , Caichun Yin , Yanxu Liu , Paulo Pereira","doi":"10.1016/j.geosus.2025.100321","DOIUrl":"10.1016/j.geosus.2025.100321","url":null,"abstract":"<div><div>Amid ongoing global environmental change and the critical pursuit of sustainable development, human–environment systems are exhibiting increasingly complex dynamic evolutions and spatial relationships, underscoring an urgent need for innovative research frameworks. Integrated geography synthesizes physical geography, human geography, and geographic information science, providing key frameworks for understanding complex human–environment systems. This editorial proposes an emerging research framework for integrated geography—“Composite driving–System evolution–Coupling mechanism–Synergistic regulation (CSCS)”—based on key issues such as climate change, biodiversity loss, resource scarcity, and social–ecological interactions, which have been highlighted in both recent critical literature on human–environment systems and UN assessment reports. The framework starts with diverse composite driving forces, extends to the evolution of human–environment system structures, processes, and functions that these drivers induce, explores couplings within human–environment systems, and calls for regulation aimed at sustainable development in synergies. Major research frontiers include understanding the cascading “evolution–coupling” effects of shocks; measuring system resilience, thresholds, and safe and just operating space boundaries; clarifying linkage mechanisms across scales; and achieving synergistic outcomes for multi-objective sustainability. This framework will help promote the interdisciplinary integration and development of integrated geography, and provide geographical solutions for the global sustainable development agenda.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 3","pages":"Article 100321"},"PeriodicalIF":8.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144306948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-28DOI: 10.1016/j.geosus.2025.100318
Xiao Chen , Song Leng , Zhaowu Yu , Ranhao Sun
Elderly individuals disproportionately face heat exposure risk compared to other demographic groups, with projected amplification in the future. The vast disparities between Global North and South countries necessitate a comprehensive understanding of the underlying factors influencing future heat exposure vulnerabilities. Here, we use factor decomposition method to quantify the contribution of climate change, population, and aging to heat exposure risk under four shared socioeconomic pathways (SSP) (SSP126, SSP245, SSP370, SSP585) from 2000 to 2100 at 20-year intervals. Results demonstrate a projected global escalation in heat exposure risk by 16 and 76 times under SSP126 and SSP585, respectively, with the North generally suffering lower risk than the South. Climate change emerges as a pivotal driver of future heat exposure risk in the North while aging notably influences the South. Despite climate change is projected to reduce heat exposure risk by up to 10 % in the North under SSP1-2.6 by the end of the 21st century, aging remains a critical risk factor.
{"title":"Global aging exacerbates heat exposure risk across diverse socioeconomic pathways","authors":"Xiao Chen , Song Leng , Zhaowu Yu , Ranhao Sun","doi":"10.1016/j.geosus.2025.100318","DOIUrl":"10.1016/j.geosus.2025.100318","url":null,"abstract":"<div><div>Elderly individuals disproportionately face heat exposure risk compared to other demographic groups, with projected amplification in the future. The vast disparities between Global North and South countries necessitate a comprehensive understanding of the underlying factors influencing future heat exposure vulnerabilities. Here, we use factor decomposition method to quantify the contribution of climate change, population, and aging to heat exposure risk under four shared socioeconomic pathways (SSP) (SSP126, SSP245, SSP370, SSP585) from 2000 to 2100 at 20-year intervals. Results demonstrate a projected global escalation in heat exposure risk by 16 and 76 times under SSP126 and SSP585, respectively, with the North generally suffering lower risk than the South. Climate change emerges as a pivotal driver of future heat exposure risk in the North while aging notably influences the South. Despite climate change is projected to reduce heat exposure risk by up to 10 % in the North under SSP1-2.6 by the end of the 21st century, aging remains a critical risk factor.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 5","pages":"Article 100318"},"PeriodicalIF":8.0,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144536172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-27DOI: 10.1016/j.geosus.2025.100320
Hu Yu , Xinyue Hu , Ling Yao
Vegetation restoration (VR) is critical for enhancing the resilience of fragile ecosystems, yet its impact on landscape ecological risk (LER) remains uncertain. The VR project on the Loess Plateau in Shaanxi Province (LPSX) was taken as a case study to address ecological and environmental challenges, including soil erosion and land degradation. This study used multi-source data, including land cover, fractional vegetation cover, and nighttime light. It employed landscape pattern analysis, spatio-temporal correlation analysis, and causality analysis to assess the impacts. This study found a generally positive relationship between VR and the mitigation of LER in LPSX, though spatial and temporal variations exist from 2000 to 2020. Localized VR significantly influenced 17.66 % to 27.03 % of the study area. Positive effects were mainly observed in sandy and gully-hilly regions, showing an upward fluctuating trend that peaked at 21.91 % in 2010. After 2010, negative effects in the Fen-Wei Plain, Qinling Mountains, and Liupan Mountains outweighed the positive effects and continued to expand. Urbanization had a broader impact on LER distribution compared to VR. The findings indicate that future VR projects should focus on the spatial pattern of restoration and its associated eco-social effects to ensure sustainable development.
{"title":"Vegetation restoration reduces landscape ecological risk in the Loess Plateau","authors":"Hu Yu , Xinyue Hu , Ling Yao","doi":"10.1016/j.geosus.2025.100320","DOIUrl":"10.1016/j.geosus.2025.100320","url":null,"abstract":"<div><div>Vegetation restoration (VR) is critical for enhancing the resilience of fragile ecosystems, yet its impact on landscape ecological risk (LER) remains uncertain. The VR project on the Loess Plateau in Shaanxi Province (LPSX) was taken as a case study to address ecological and environmental challenges, including soil erosion and land degradation. This study used multi-source data, including land cover, fractional vegetation cover, and nighttime light. It employed landscape pattern analysis, spatio-temporal correlation analysis, and causality analysis to assess the impacts. This study found a generally positive relationship between VR and the mitigation of LER in LPSX, though spatial and temporal variations exist from 2000 to 2020. Localized VR significantly influenced 17.66 % to 27.03 % of the study area. Positive effects were mainly observed in sandy and gully-hilly regions, showing an upward fluctuating trend that peaked at 21.91 % in 2010. After 2010, negative effects in the Fen-Wei Plain, Qinling Mountains, and Liupan Mountains outweighed the positive effects and continued to expand. Urbanization had a broader impact on LER distribution compared to VR. The findings indicate that future VR projects should focus on the spatial pattern of restoration and its associated eco-social effects to ensure sustainable development.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 5","pages":"Article 100320"},"PeriodicalIF":8.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144298357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-27DOI: 10.1016/j.geosus.2025.100319
Fayong Liu , Xinyu Zou , Yuanyuan Huang
Due to its impact on cereal yields, vegetation growth, animal wellbeing, and human health, considerable attention has been paid to diurnal temperature range, focusing on the temporal dimension of surface air temperature. However, the characteristics of spatial temperature range and its response to climate change remain unclear, despite its importance to various natural and societal activities. Here, we proposed a daily spatial temperature range (DSTR, difference between spatial maximum and minimum temperature, STmax and STmin) indicator to measure the maximum spatial temperature range within a given region over a day. We analyzed the spatiotemporal pattern of DSTR and its trend under climate change at four scales (global, hemispheric, national, and provincial), with the following main results: (1) DSTR was scale dependent, provincial pattern of which were mainly related to sensible and latent heat fluxes. (2) The key regions affecting DSTR and temporal distribution at different scales were mapped out. (3) Under climate change, DSTR significantly decreased globally, hemispherically, and in several Chinese provinces due to the greater warming of STmin than STmax. The influence of latent heat flux and solar shortwave radiation was larger at global/hemispheric scales, while the albedo was a more critical driver at provincial scale. For the first time, we proposed the DSTR indicator and emphasized the importance of exploring spatial temperature heterogeneity. This spatial information is important to optimize relevant societal activities, and the response of DSTR to climate change has further led to the consideration of the relationship between DSTR and extreme events, biodiversity, etc.
{"title":"Daily spatial temperature range: Spatiotemporal pattern and climate change response","authors":"Fayong Liu , Xinyu Zou , Yuanyuan Huang","doi":"10.1016/j.geosus.2025.100319","DOIUrl":"10.1016/j.geosus.2025.100319","url":null,"abstract":"<div><div>Due to its impact on cereal yields, vegetation growth, animal wellbeing, and human health, considerable attention has been paid to diurnal temperature range, focusing on the temporal dimension of surface air temperature. However, the characteristics of spatial temperature range and its response to climate change remain unclear, despite its importance to various natural and societal activities. Here, we proposed a daily spatial temperature range (DSTR, difference between spatial maximum and minimum temperature, STmax and STmin) indicator to measure the maximum spatial temperature range within a given region over a day. We analyzed the spatiotemporal pattern of DSTR and its trend under climate change at four scales (global, hemispheric, national, and provincial), with the following main results: (1) DSTR was scale dependent, provincial pattern of which were mainly related to sensible and latent heat fluxes. (2) The key regions affecting DSTR and temporal distribution at different scales were mapped out. (3) Under climate change, DSTR significantly decreased globally, hemispherically, and in several Chinese provinces due to the greater warming of STmin than STmax. The influence of latent heat flux and solar shortwave radiation was larger at global/hemispheric scales, while the albedo was a more critical driver at provincial scale. For the first time, we proposed the DSTR indicator and emphasized the importance of exploring spatial temperature heterogeneity. This spatial information is important to optimize relevant societal activities, and the response of DSTR to climate change has further led to the consideration of the relationship between DSTR and extreme events, biodiversity, etc.</div></div>","PeriodicalId":52374,"journal":{"name":"Geography and Sustainability","volume":"6 5","pages":"Article 100319"},"PeriodicalIF":8.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144330336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-22DOI: 10.1016/j.geosus.2025.100309
Jianguo (Jingle) Wu , Julius Addai , Macharia Consolata , Zening Gao , Erica Martin , Emily Sezate Yasutake , Yucang Wang
Achieving Sustainable Development Goals (SDGs) requires place-based solutions that reconcile global aspirations with local realities. Landscapes and regions represent a pivotal scale domain—large enough to capture cross-boundary ecological and socioeconomic processes, yet sufficiently grounded to enable context-sensitive understanding and governance. Landscape sustainability science offers a robust framework for bridging the global-local divide in SDG implementation. Rooted in the long-standing convergence between ecology and geography—tracing back to Humboldt’s unity of nature—landscape sustainability science advances a spatially explicit, systems-oriented approach guided by the principles of strong sustainability. Here we present the landscape sustainability science framework, structured around the core triad of landscape pattern, ecosystem services, and human wellbeing, and operationalized through dual feedback loops and the analysis–adaptation–assessment cycle. Our assessment shows that landscape sustainability science contributes directly to eight SDGs and indirectly to six others, offering actionable strategies for climate resilience, sustainable land management, and inclusive landscape governance. By helping to spatialize, localize, and operationalize global sustainability targets, landscape sustainability science provides a pragmatic pathway to advance the SDGs in diverse socioecological contexts. If global sustainability is to be achieved, we must think and act like a landscape.
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