Search Results (2,731)

Global water management faces a critical challenge: whilst scholarly consensus recognises that multiple, interacting drivers fundamentally shape water availability and management capacity, operational governance frameworks fail to systematically incorporate this understanding. This disconnect is particularly acute in public good contexts where incomplete knowledge, diverse stakeholder values, and statutory planning mandates create distinct challenges. Using Australia’s Murray–Darling Basin as a pilot case, this research develops and demonstrates a rapid, policy-relevant heuristic for identifying, prioritising, and incorporating drivers of change in complex socio-ecological water systems. Through structured participatory deliberation with 70 experts spanning research, policy, industry, and community sectors across three sequential workshops and 15 semi-structured interviews, we systematically identified key drivers across environmental, governance, economic, social, and legacy dimensions. A risk and sensitivity assessment framework enabled prioritisation based on impact, vulnerability, and urgency. Climate change, drought, water quality events, and cumulative impacts emerged as the highest-priority future drivers, with climate change acting as a threat multiplier, whilst governance drivers show declining relative significance. Using these methodological innovations, we synthesise the I-PLAN heuristic: five interdependent dimensions (Integrative Knowledge, Prioritisation for Management, Linkages between Drivers, Adaptive Agendas, and Normative Collaboration) that provide water planners with a transferable, operational tool for driver identification and bridging to planning and management in data-sparse contexts. Full article

Socio-ecological systems in basin regions characterized by diverse cultural traditions and hierarchical village spatial structure are undergoing profound transformation driven by multifunctional demands and spatial restructuring. This study develops an analytical framework encompassing economic production, socio-cultural functions, and ecological potential to examine the spatial differentiation and socio-ecological coupling mechanisms within the Yilong Lake Basin, Yunnan Province. Through the entropy weighting method and a coupling coordination model, the framework evaluates the “lake–mountain–village” gradient of spatial differentiation. The results indicate that: (1) the overall coordination level of multifunctional systems in the region remains relatively low, exhibiting a decreasing trend from lakeshore to the mountain periphery; (2) village-level dependencies of spatial functions can be summarized into three coupling categories—associated with institutional embedding, self-organization, and value mismatch—revealing distinct socio-ecological interaction patterns; and (3) three coupling categories correspond to three differentiated governance pathways, namely coupling optimization, functional transition, and conflict mitigation. The study advances theoretical and methodological insights into the spatial differentiation and evolution of complex village systems, highlighting the nonlinear coexistence of interdependence and constraint among economic, social, and ecological functions. It further provides practical guidance for coordinated governance and sustainable spatial planning in similar rural and basin environments worldwide. Full article

Sustainability in the agri-food sector has become a cornerstone of global efforts to combat climate change, ensure food security through climate-smart agriculture, and strengthen economic resilience. Sustainability reporting within agri-food systems has gained increasing regulatory significance with the introduction of mandatory frameworks such as the Turkish Sustainability Reporting Standards (TSRSs). This article searches for the sustainability reports of agri-business firms listed in BIST in Turkey. Although TSRS reporting is not yet mandatory for the agribusiness sector, this study examines the first TSRS-aligned sustainability reports published by eight agri-food companies, excluding the retail sector. The analysis assesses how effectively these reports address sector-specific environmental and social challenges defined in the GRI 13 Agriculture, Aquaculture and Fishing Sector Standard and their alignment with the United Nations Sustainable Development Goals (SDGs). Using a structured content analysis approach, disclosure patterns were examined at both thematic and company levels. The findings indicate that TSRS-aligned reports place strong emphasis on environmental and climate-related disclosures, particularly emissions, climate adaptation and resilience, water management, and waste. In contrast, agro-ecological and land-based impacts—such as soil health, pesticide use, and ecosystem conversion—are weakly addressed. Economic disclosures are predominantly framed around climate-related financial risks and supply chain traceability, while social reporting focuses mainly on occupational health and safety, employment practices, and food safety, with limited attention to labor and equity issues across the broader value chain. Company-level results reveal marked heterogeneity, with internationally active firms demonstrating deeper alignment with GRI 13 requirements. From an SDG alignment perspective, high levels of coverage are observed across all companies for SDG 13 (Climate Action), SDG 12 (Responsible Consumption and Production), and SDG 6 (Clean Water and Sanitation). By contrast, SDGs critical to agro-ecological integrity and social equity—namely SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 10 (Reduced Inequalities), and SDG 15 (Life on Land)—are weakly represented or entirely absent. Overall, the results suggest that while TSRS-aligned reporting enhances transparency in climate-related domains, it achieves only selective alignment with the SDG agenda. This underscores the need for a stronger integration of sector-specific sustainability priorities into mandatory sustainability reporting frameworks. Full article

Extreme wildfires are becoming increasingly frequent and severe across many regions worldwide, driven by climate change, land-use transitions, and long-standing fire-suppression legacies. In this context, Nature-based Solutions (NbSs)—defined as actions that work with ecological processes to address societal challenges while providing biodiversity and socio-economic benefits—offer a promising yet underdeveloped pathway for enhancing wildfire resilience. This Special Issue brings together eleven contributions spanning empirical ecology, landscape configuration, simulation modelling, spatial optimisation, ecosystem service analysis, governance assessment, and community-based innovation. Collectively, these studies demonstrate that restoring ecological fire regimes, promoting multifunctional landscapes, and integrating advanced decision support tools can substantially reduce wildfire hazard while sustaining ecosystem functions. They also reveal significant governance barriers, including fragmented policies, limited investment in prevention, and challenges in incorporating social demands into territorial planning. By synthesising these insights, this editorial identifies several strategic priorities for advancing NbSs in fire-prone landscapes: mainstreaming prevention within governance frameworks, strengthening the science–practice interface, investing in long-term socio-ecological monitoring, managing trade-offs transparently, and empowering local communities. Together, the findings highlight that effective NbSs emerge from the alignment of ecological, technological, institutional, and social dimensions, offering a coherent pathway toward more resilient, biodiverse, and fire-adaptive landscapes. Full article

Promoting green industrial development and enhancing high-quality employment are crucial for advancing county-level economic growth and achieving shared prosperity. This study analyzes the spatiotemporal evolution trends of green industrial development and high-quality employment using panel data from 20 mountainous counties (cities and districts) in Zhejiang Province from 2010 to 2023. It employs panel models to investigate the effects and mechanisms through which green industrial development fosters high-quality employment. The results indicate that, during the study period, both green industry development and high-quality employment exhibited uneven progress across the 20 mountainous counties (cities and districts) in Zhejiang. Mechanism analysis revealed that green industrial development significantly promotes high-quality employment through two pathways: industrial structure upgrading and technological progress. The heterogeneity analysis indicates that the impact of green industrial development on high-quality employment varies significantly across different industrial structures, with counties dominated by the tertiary sector showing more substantial promotion effects. The threshold regression analysis reveals a dual-threshold effect of technological progress in promoting high-quality employment through green industrial development, presenting an approximately J-shaped nonlinear relationship. The research findings provide significant support for the sustainable development of the ecological environment and society by addressing current imbalances between ecological preservation and economic or social growth. Full article

This research aimed to conduct a bibliometric review on Acrocomia aculeata (Jacq.) Lodd. ex Mart., popularly known as “macaúba”, a palm tree of the Arecaceae family with great potential to promote sustainable practices. The review focused on the applications associated with the oil, pulp, and almonds of the fruit, products that can be used in industries such as food, cosmetics, and bioenergy, contributing to the development of more ecological production chains with less environmental impact. Data were collected from the Scopus, Web of Science, and ScienceDirect databases for publications related to phytochemical and bioactive aspects, while only Web of Science was used for data on energy aspects. The documents found were analyzed in the VOSviewer software (version 1.6.20), allowing the creation of bibliometric networks (clusters) and tables on scientific production. The analyses included authors, co-authors, countries, institutions, journal sources, and keywords. For phytochemical and bioactive aspects, the search resulted in 1026 articles, of which 261 were selected after applying the exclusion criteria. For energy aspects, 99 publications were found. Based on the data, it was possible to analyze the existing research on A. aculeata, identifying the state of the research and possible gaps in studies related to this oilseed. The results highlight the importance of macaúba as a sustainable alternative for diversifying agricultural and bioindustrial products, promoting the bioeconomy and contributing to the mitigation of environmental impacts. In addition, the research allowed us to identify the universities and researchers most dedicated to this species, their main results and the areas that still require investment to advance research. Thus, A. aculeata emerges as a relevant option to strengthen sustainable practices in key sectors, integrating economic, social, and environmental benefits. Full article

Future shortages of minerals essential for green technologies have driven the search for new supply sources. In this context, deep-sea mining (DSM) has emerged as an innovative alternative for accessing strategic metals such as manganese and cobalt, among others, through the exploitation of deposits including polymetallic nodules, ferromanganese crusts, and seafloor massive sulfides. However, while DSM could help meet the growing demand for minerals, it also presents significant challenges and opportunities. This study compiles and analyzes scientific publications on DSM to assess its potential effects. It reviews the main environmental impacts and, in addition, proposes a systematic classification of them. It also addresses the social and economic effects associated with this activity, considering human dynamics and the factors that shape its long-term viability. The results indicate that, although DSM may offer advantages over terrestrial mining, it still lacks a robust framework to mitigate impacts and anticipate future consequences. Unlike previous reviews focused on partial dimensions of sustainability, this work integrates environmental, social, and economic dimensions through a systematic impact classification. Critical challenges remain in ecological understanding, environmental monitoring, and long-term socio-economic assessment, alongside an international governance framework that is still nascent, reinforcing the need for interdisciplinary research. Full article

Understanding regional disparities in Chinese modernization is essential for achieving coordinated and sustainable development. This study develops a multi-dimensional evaluation framework, integrating grey relational analysis, entropy weighting, and TOPSIS to assess provincial modernization across China from 2018 to 2023. The framework operationalizes Chinese-style modernization through five dimensions: population quality, economic strength, social development, ecological sustainability, innovation and governance, capturing both material and institutional aspects of development. Using K-Means clustering, kernel density estimation, and convergence analysis, the study examines spatial and temporal patterns of modernization. Results reveal pronounced regional heterogeneity: eastern provinces lead in overall modernization but display internal volatility, central provinces exhibit gradual convergence, and western provinces face widening disparities. Intra-regional analysis highlights uneven development even within geographic clusters, reflecting differential access to resources, governance capacity, and innovation infrastructure. These findings are interpreted through modernization theory, linking observed patterns to governance models, regional development trajectories, and policy coordination. The proposed framework offers a rigorous, data-driven tool for monitoring modernization progress, diagnosing regional bottlenecks, and informing targeted policy interventions. This study demonstrates the methodological value of integrating grey system theory with multi-criteria decision-making and clustering analysis, providing both theoretical insights and practical guidance for advancing balanced and sustainable Chinese-style modernization. Full article

The concept of sustainable development has emerged as a global consensus, forged in response to environmental constraints and critical reflection on conventional growth-oriented paradigms. It now serves as the overarching framework for addressing climate, ecological, and socio-economic crises. In the period after the adoption of the Sustainable Development Goals (SDGs) in 2016, there was an observable trend of increased integration of these objectives into the strategic frameworks of national and subnational entities. However, global assessments have indicated a divergence between the progress achieved and the trajectory delineated by the SDGs. The Earth system is demonstrating signs of decreased resilience, with widening inequalities and the emergence of multiple crises, thereby hindering the implementation of the 2030 Agenda for Sustainable Development. As the 2030 deadline approaches, a fundamental question arises for global development governance: what should be the future of the SDGs beyond 2030? While insufficient progress has prompted debates over the adequacy of the SDG framework, fundamentally revising or replacing the SDGs would risk undermining a hard-won international consensus forged through decades of negotiation and institutional investment. Based on a comprehensive review of the historical evolution of the sustainable development concept, this study argues that the SDGs represent a rare and fragile achievement in global governance. While insufficient progress has sparked debates about their effectiveness, fundamentally revising or replacing the SDGs would jeopardize the hard-won international consensus forged through decades of negotiations and institutional investments. This study further analyzes the latest progress on the SDGs and identifies emerging risks, aiming to explore how to accelerate and optimize sustainable development pathways within the existing SDG framework rather than propose a new global goal system. Based on both global experience and practice in China, four interconnected strategic priorities—namely, economic reform, social equity, environmental justice, and technology sharing—are proposed as a comprehensive framework to accelerate SDG implementation and guide the transformation of development pathways towards a more just, low-carbon, and resilient future. Full article

Sustainable Urban Drainage Systems (SUDSs) are essential for stormwater management in urban areas, with varying hydrological, social, ecological, and economic benefits. Nevertheless, choosing the SUDS most appropriate for public spaces poses a challenge when balancing details/specifications against community decisions, primarily social implications and perceptions. Building on the SUDS design pillar of the amenity, this study outlines a three-phase methodological framework for selecting SUDS based on social facilitation. The first phase introduces the application of the Partial Least Squares Structural Equation Modeling (PLS-SEM) and Classificatory Expectation–Maximization (CEM) techniques by modeling complex social interdependencies to find critical components related to urban planning. A Likert scale survey was also conducted with 440 urban dwellers in Tunja (Colombia), which identified three dimensions: Residential Satisfaction (RS), Resilience and Adaptation to Climate Change (RACC), and Community Participation (CP). In the second phase, the factors identified above were transformed into eight operational criteria, which were weighted using the Analytic Hierarchy Process (AHP) with the collaboration of 35 international experts in SUDS planning and implementation. In the third phase, these weighted criteria were used to evaluate and classify 13 types of SUDSs based on the experts’ assessments of their sub-criteria. The results deliver a clear message: cities must concentrate on solutions that will guarantee that water is managed to the best of their ability, not just safely, and that also enhance climate resilience, energy efficiency, and the ways in which public space is used. Among those options considered, infiltration ponds, green roofs, rain gardens, wetlands, and the like were the best-performing options, providing real and concrete uses in promoting a more resilient and sustainable urban water system. The methodology was also used in a real case in Tunja, Colombia. In its results, this approach proved not only pragmatic but also useful for all concerned, showing that the socio-cultural dimensions can be truly integrated into planning SUDSs and ensuring success. Full article

The successful attainment of the Sustainable Development Goals (SDGs) necessitates robust monitoring frameworks capable of tracking progress toward tangible outcomes while capturing dynamic sustainability trajectories. However, existing SDG evaluation methods suffer from three critical limitations: (1) misalignment between global targets and national priorities, which undermines contextual relevance; (2) fragmented assessments that neglect holistic integration of social, economic, and ecological dimensions, thereby obscuring systemic interdependencies; and (3) insufficient longitudinal analysis, which restricts insights into temporal patterns of sustainable development and hinders adaptive policymaking. To address these gaps, we employed China’s 31 provinces as a case study and constructed an SDG indicator framework comprising 178 metrics—harmonizing global SDG benchmarks with China’s national development priorities. Using official statistics and open-source data spanning 2006–2021, we evaluate longitudinal SDG scores for all 17 goals (SDGs 1–17). Additionally, we developed a composite SDG index that considers the coupling coordination degree of the social–economic–ecological system and evaluated the index value under different economic region settings. Finally, we developed a two-threshold model to analyze the dynamic evolution of SDG conditions, incorporating temporal sustainability (long-term development resilience) and action urgency (short-term policy intervention needs) as dual evaluation dimensions. This model was applied to conduct a longitudinal analysis (2006–2021) across all 31 Chinese provinces, enabling a granular assessment of regional SDG trajectories while capturing both systemic trends and acute challenges over time. The results indicate that China’s social SDG performance improved substantially over the 2006–2021 period, achieving a cumulative increase of 126.53%, whereas progress in ecological SDGs was comparatively modest, with a cumulative growth of only 23.93%. Over the same period, the average composite SDG score across China’s 31 provinces increased markedly from 0.502 to 0.714, reflecting a strengthened systemic alignment between regional development trajectories and national sustainability objectives. Further analysis shows that all provinces attained a status of “temporal sustainability with low action urgency” throughout the study period, highlighting China’s overall progress in sustainable development. Nevertheless, pronounced regional disparities persist: eastern provinces developed earlier and have consistently maintained leading positions; central and northeastern regions exhibit broadly comparable development levels; and western regions, despite severe early-stage lagging, have demonstrated accelerated growth in later years. Our study holds substantial significance by integrating multi-dimensional indicators—spanning ecological, economic, and social dimensions—to deliver a holistic, longitudinal perspective on sustainable development. Full article

The identification of supplementary cultivated land as a reserve resource is of great significance for ensuring implementation of the new mechanism of land occupation and compensation balance in China. Using Jiangsu Province as a case study, here, we use a “multi-period land use change patterns–multi-scenario land use simulation–cultivation suitability evaluation–identification of supplementary cultivated land” framework to explore identification of supplementary cultivated land. A single land use dynamic index and a land use transfer matrix were used to analyze land use pattern changes in Jiangsu Province and showed that the area of cultivated land in Jiangsu Province decreased significantly, mainly by being converted into land used for buildings, and waters and conservancy facilities. A Markov-FLUS model was used to simulate and predict land use quantity and spatial distribution under four scenarios: an inertial development scenario, a cultivated land protection scenario, an economic development priority scenario, and an ecological protection priority scenario. Sixteen factor indicators were selected from the four dimensions of natural land quality, social economy, management, and the ecological condition of the land, and the degree of suitability of cultivated land in Jiangsu was evaluated by multi-factor stepwise correction. The southern and central parts of Jiangsu had higher suitability, while the northern part had lower suitability. By superimposing these data on current land use data from 2023, the plots of land that were converted to or from cultivated land were identified. Combined with the suitability degree, the potential three major categories and eight types of sources for supplementary cultivated land, totaling 29,015.92 km², were identified, along with their distribution. A time sequence arrangement for these sources was initially set up. Corresponding management suggestions were proposed based on the adaptability of different supplementary cultivated land sources, with the aim of providing scientific references for the acquisition of supplementary cultivated land sources in the implementation of the national and local government’s farmland balance management. Full article

Under the combined influence of global climate change and intensified human activities, quantifying ecological compensation (EC) amounts between regions and formulating scientifically sound and rational policies have become critical strategies for addressing the imbalance between economic development and ecological conservation. This study focuses on the Yangtze River Economic Belt (YREB) as the research subject, assesses ecosystem service supply and demand (ESSD) in the years 2000, 2010, and 2020 from the perspective of the water-energy-food nexus (WEF-Nexus), identifies ecosystem service flows (ESF) between supply and demand areas, develops an integrated EC model incorporating ecological, economic, and social dimensions to estimate EC amounts, and ultimately employs the XGBoost-SHAP model to analyze the underlying driving mechanisms. The results indicate the following: (1) From 2000 to 2020, the spatio-temporal variations in the three ESSDs in the YREB were substantial. Additionally, imbalances in ESSDs were observed, predominantly in economically advanced regions. (2) A total of 183 ESFs were identified among cities within the YREB, reflecting relatively active exchanges of ecosystem services (ESs). (3) Over the past two decades, the average annual total EC of the YREB amounted to 46,866.35 million yuan, with EC capital flows occurring in 117 cities. The proportion of water area in each city constitutes the primary driver of the EC amount. The EC model based on the “water-energy-food” ecosystem service flow (WEF-ESF) proposed in this study provides a valuable reference and scientific basis for formulating EC policies among YREB cities. Full article

Urban expansion and its driving factors are frequently analyzed within administrative regions to inform regional urban planning, yet such analyses often fall short at the natural basin scale (referring to the spatial extent defined by hydrological drainage boundaries) due to the scarcity of statistical data. Geographic and socio-economic spatial data can offer more detailed information across various research scales compared to traditional data (such as administrative statistical data, survey-based data, etc.), providing a potential solution to this limitation. Thus, this study took the Indus Basin as an example to reveal its urban expansion patterns and driving mechanism based on natural–economic–social time-series (2000–2020) spatial data, landscape expansion index, and geographical detector model (GDM). Future urban expansion distribution under different scenarios was also projected using Cellular Automata and Markov model (CA-Markov). The results indicated the following: (1) The Indus River Basin experienced rapid urban expansion during 2000–2020 dominated by edge-expansion, with urban expansion intensity showing a continuous increase. (2) Between 2000 and 2010 as well as 2010 and 2020, the dominant factor influencing urban expansion shifted from altitude to population (Pop), while the strongest interacting factors shifted from fine particulate matter (PM_2.5) and altitude to Gross Domestic Product (GDP) and Pop. (3) Future urban expansion probably occupies substantial mountainous area under the normal scenario, while the expansion region shifts towards the central plains to protect more ecological zones under a sustainable development scenario. Findings in this study would deepen the understanding of urban expansion characteristics of the Indus Basin and benefit its future urban planning. Full article

Water functional zoning plays a crucial role in water resource allocation, pollution prevention, and ecological protection. With the increasing intensity of human activities, there is a significant mismatch between current water functional zoning and the economic, social development needs and ecological protection goals. Existing water functional zoning methods mainly rely on expert experience for qualitative judgment, which is highly subjective and inefficient. In response, this paper presents a transferable quantitative feature system and introduces a machine learning-based progressive zoning framework for water functions, validated through a case study of the Yangtze River Basin. The results show that the overall accuracy of the framework is 0.78, which is 4–7% higher compared to traditional single models. In terms of spatial distribution, the transformation of protection and reserved zones in 2020 mainly occurred in the middle and lower reaches, where human activities are frequent, particularly in Sichuan and Jiangxi provinces. The development zones are highly concentrated in the downstream areas, with some regions transitioning into protection or reserved zones, mainly in Hubei and Chongqing provinces. Adjustments to buffer zones are primarily concentrated along inter-provincial boundary areas, such as the junction between Hubei and Anhui provinces. This framework helps managers quickly identify key areas for optimizing water functional zones, providing valuable reference for the precise management of water resources and the formulation of ecological protection strategies in the basin. Full article