Search Results (1,324)

The Rio Grande Rise (RGR) is the largest oceanic plateau in the South Atlantic and represents a key natural laboratory for understanding oceanic plateau formation, deep-sea circulation, ecosystem functioning, and ferromanganese crust development. This study presents a critical synthesis of current scientific knowledge on the RGR, integrating geological, geophysical, oceanographic, biological, and geochemical evidence published over the last two decades. Geophysical data reveal a complex tectono-magmatic evolution involving Late Cretaceous plume-related volcanism, crustal thickening, rifting, and subsequent subsidence. The structural framework of the plateau is dominated by the Cruzeiro do Sul Rift, which plays a central role in controlling sedimentation, magmatism, and seawater circulation. Oceanographic studies demonstrate that the interaction between the southern branch of the South Equatorial Current and the complex topography of the RGR generates intense internal tides and bottom currents, strongly influencing sediment transport and benthic habitats. Biological investigations indicate that the RGR hosts diverse deep-sea communities, including sponge grounds, cold-water corals, and associated fauna, whose distribution is tightly linked to geomorphology and hydrodynamics. Ferromanganese crusts occurring on the plateau preserve valuable geochemical records of oceanographic and redox conditions, although their spatial distribution, thickness, and metal budgets remain incompletely constrained. Despite major advances, significant knowledge gaps persist regarding crustal structure, sedimentary evolution, ecosystem functioning, and mineral formation processes. This review highlights these uncertainties and outlines research priorities necessary to improve understanding of oceanic plateaus and deep-sea systems in the South Atlantic. Full article

Quercus pyrenaica (Willd.), a sub-Mediterranean oak, is expected to experience substantial distribution shifts under climate change, with some populations in Portugal at risk. Beyond climate-driven pressures, long-standing anthropogenic pressures have likely contributed to the species’ current vulnerability. This work aims to characterize the current status of closed-canopy Q. pyrenaica forests by providing a spatio-temporal assessment of forest fragmentation and its recent evolution. Using multispectral bands from Sentinel-2 time-series data, vegetation indices, embedding vectors generated by Google’s AlphaEarth foundational model, and topographic variables, we applied a machine learning Random Forest classifier to map Q. pyrenaica forests in 2019 and 2024 and to analyze their spatial configuration patterns. The findings indicate robust predictive performance (spatial cross-validation OA of 95.1%, Kappa of 83.7%, and F1 of 86.9%) and reveal the prominent role of AlphaEarth embedding features in the RF classifier, suggesting that these features are well-suited for classifying forest habitats of conservation importance. Quercus pyrenaica occurs predominantly at mid-elevations (~820 m a.s.l.), on gentle slopes (~9°), topographically neutral terrain, and northwestern-facing aspects, consistently across both years. Between 2019 and 2024, the Q. pyrenaica forest area showed an increasing signal. However, the results point to a landscape in an initial phase of forest recovery, constrained by land-use legacies, with cover increasing predominantly through the sprawl of small, geometrically complex, and poorly connected patches. Together, these results provide a baseline to track recent changes in Q. pyrenaica distribution and fragmentation, highlighting a contrast between apparent area expansion and declining overall structural integrity. In the future, patch connectivity and full recovery of secondary succession should be a priority for policymakers and forest owners. Full article

Coastal cities are located at the critical interface of land–sea interaction, and scientifically assessing their ecological importance is essential for identifying conservation priority areas. Existing assessments focus primarily on static function while neglecting dynamic system processes and resilience characteristics. To address this limitation, this study developed an innovative “State-Interaction-Resilience” (SIR) assessment framework. It integrates ecosystem services (state), ecological connectivity and network supply-demand relationships (interaction), and social-ecological system adaptive capacity (resilience) and incorporates differentiated weighting based on the unique “sea–land gradient” pattern of coastal zones. Using Dongying City in the Yellow River Delta as a case study, the results show the following: (1) The SIR framework evaluation results demonstrate balanced and significant positive correlations with all dimensional indicators (r = 0.3~0.8), showing greater comprehensiveness and scientific validity than traditional evaluation methods, with 81% spatial agreement between identified extremely important areas and existing protected areas. (2) From 2000 to 2020, the overall ecological importance of Dongying City showed an upward trend, with the proportion of extremely important areas significantly increasing from 6.03% to 10.24%, while maintaining a stable spatial gradient pattern of “high along the coast, low inland”. (3) The improvement in ecological importance in coastal core areas mainly resulted from state improvement and resilience enhancement driven by restoration projects such as “aquaculture retreat and wetland restoration”, while inland areas were constrained by both habitat fragmentation and ecological supply-demand mismatch. This study confirms that the SIR framework can accurately capture the spatial heterogeneity of coastal zones. The proposed “core protection-corridor restoration-function enhancement” hierarchical and zonal spatial governance strategy provides scientific evidence and actionable spatial guidance for coastal territorial spatial planning, ecological protection redline optimization, and targeted ecological restoration. Full article

Under the combined pressures of urbanization and tourism development, terraced agricultural heritage sites are increasingly threatened by the degradation of traditional landscapes, the weakening of living cultural practices, and mismatches between the supply and demand of cultural ecosystem services (CESs). As a representative type of Globally Important Agricultural Heritage Systems (GIAHSs), the rice terrace landscapes of southern China have formed an integrated system of forests, villages, terraces, and water networks, embodying multiple values related to production, ecology, landscape, and culture. To support the coordination of heritage conservation, tourism development, and the transformation of cultural value, this study takes the core area of the Longji Terraced Fields as a case study and develops an improved SolVES–IPA collaborative assessment framework from the perspective of tourist perception. Four CES categories are examined: recreational value, aesthetic value, historical and cultural value, and educational value. The results show that (1) the four CES categories exhibit significant spatial differentiation. Recreational and aesthetic values are mainly concentrated in high-altitude viewing spaces, whereas historical, cultural, and educational values depend more heavily on traditional architectural spaces and interpretive nodes. (2) Clear supply–demand mismatches exist across CES categories. Recreational value is constrained by limited activity diversity; aesthetic value is limited by inadequate architectural harmony; historical and cultural value is primarily restricted by insufficient continuity of living traditions; and educational value is constrained by incomplete interpretive content and single presentation formats. (3) CES optimization in the Longji Terraced Fields should adopt both type-specific and hierarchical intervention strategies, including priority optimization for high-value units with critical shortcomings, near-term improvement for high-value units with general shortcomings, functional enhancement for medium-value units with critical shortcomings, progressive optimization for medium-value units with general shortcomings, and potential cultivation of low-value units. Based on these findings, this study proposes several optimization directions, including strengthening participatory experiences, promoting the coordinated renewal of the architectural landscape, creating multisensory cultural display spaces, and establishing a multidimensional interpretation network. The improved SolVES–IPA collaborative assessment framework developed in this study integrates CES spatial identification, supply–demand diagnosis, and optimization priority setting, providing a methodological reference and practical support for enhancing cultural services and promoting the coordinated development of heritage conservation and cultural tourism in the Longji Terraced Fields and similar agricultural heritage sites. Full article

Net primary productivity (NPP) is a critical indicator of carbon sequestration and biomass accumulation in terrestrial ecosystems, directly reflecting ecosystem carbon sink capacity. Existing NPP studies have primarily emphasized climate-driven interannual variability. Spatially explicit analyses that jointly quantify multi-factor driving mechanisms, thresholds, and land-use transition risks remain limited. Here, we develop an integrated multi-method analytical workflow (DRIBS) that integrates Distributional Response, Informative Boundary constraints, and Spatial Interpretability Optimization, and apply it to the Jiziwan region in the Yellow River Basin, one of China’s major ecological restoration hotspot regions. From 2000 to 2020, the annual increasing rate of NPP was 5.80 gC·m⁻²·yr⁻¹, and 78% of the area showed a significant increasing trend. Among them, grasslands and croplands in the eastern and western parts exhibited strong fluctuations and low long-term stability. Evapotranspiration (ET) and fractional vegetation cover (FVC) were the dominant drivers of NPP spatial heterogeneity, and precipitation around ~220 mm marked a critical water-stress threshold. Population density and nighttime lights showed a non-linear “ecological adaptation window”, implying both disturbance and management potential. Land-use transitions exhibited divergent risk signatures: grassland/cropland-to-forest transitions produced stable enhancement (priority restoration zones), whereas cropland/unused-to-urban transitions were associated with degradation risk (urgent management). Overall, DRIBS provides an interpretable “change-mechanism-threshold-risk” assessment to support carbon-sink regulation and restoration prioritization in arid and semi-arid regions. Full article

Biodiversity is declining globally principally because of land degradation and more because of climate change. Its effective conservation is vital for species and habitats, but also to maintain the related ecosystem services they provide for human well-being. In this context, evaluating the ability of Protected Areas (PAs) to cover species distribution under current and future environmental conditions is highly valuable. Considering the distributions of 1692 species of plants in the cross-border region of Grand Genève, located between France and Switzerland, the effectiveness of existing PAs in preserving plant diversity through local hotspots and priority areas for rare and vulnerable species was evaluated. The results show that PAs are moderately effective in conserving plant diversity, but are not expected to lose effectiveness in future conditions because important areas for plant diversity conservation will remain at similar locations. To address this gap, a spatial conservation network combining hotspots and priority areas was identified to cover 30% of the study area. It captures a significantly higher proportion of species distributions under both current and future conditions, and covers a greater representation of rare and ecologically important habitats, such as subalpine meadows and wetlands. The proposed solution aims to inform local stakeholders about areas of high ecological value that could be used to identify the Blue-Green Infrastructure, supporting the expansion of PAs and the improvement of conservation strategies in the face of environmental change. Full article

This study develops a framework to capture spatiotemporal population dynamics and assess future earthquake exposure risk, using Hubei Province as a case study. Future population changes at the county level were projected under different shared socioeconomic pathways (SSPs). These projections were then integrated with NPP-VIIRS nighttime light data and the normalized difference vegetation index (NDVI) to simulate the spatiotemporal dynamics of the population from 2020 to 2070 at a 500 m grid resolution. Combined with seismic hazard zoning, the evolution of population exposure risk under different pathways was assessed. The results indicate the following: 1. Different SSPs profoundly influence future population exposure patterns. Under the SSP3 (regional rivalry) pathway, population growth is the fastest with the strongest agglomeration effect and significantly elevated exposure levels. 2. The refined spatiotemporal population model can more realistically reveal the heterogeneity and evolutionary trajectory of population distribution, providing a high-precision data foundation for exposure analysis and effectively enhancing the scientific rigor of risk assessment. 3. Population exposure risk under various pathways exhibits distinct spatiotemporal dynamics, and monitoring its evolution under different scenarios helps identify high-risk counties that require priority attention. This study is expected to provide precise scientific evidence for implementing differentiated disaster prevention and mitigation strategies and territorial spatial resilience planning in Hubei Province, while it demonstrates the forward-looking value of combining long-term scenario simulations with refined exposure assessments. Full article

Rapid urban expansion and the growing spatial requirements of utility-scale photovoltaic (PV) deployment compete for the same category of land—flat, accessible, and high-insolation terrain—yet the scale, trajectory, and planning-sensitivity of this conflict remain poorly characterised at the regional level. This study quantifies the spatiotemporal competition between urban construction land and PV-suitable land in the Yangtze River Delta (YRD) from 2000 to 2020 and projects its evolution to 2030 under three development scenarios. Built-up areas were extracted for three epochs using a Random Forest (RF) classifier on the Google Earth Engine (GEE) platform, achieving overall accuracies of 87.7–94.5% and Kappa coefficients of 0.718–0.739. PV site suitability was evaluated through a hybrid Multi-Criteria Decision Analysis (MCDA) framework combining Boolean exclusion constraints with an Analytic Hierarchy Process (AHP)-based Weighted Linear Combination model; the weight structure was validated by a Consistency Ratio of 0.006, and a One-At-a-Time sensitivity analysis confirmed spatial robustness across threshold scenarios. Spatial overlay analysis reveals that the cumulative area of PV-suitable land occupied by urban built-up uses grew from 15,862 km² in 2000 to 23,872 km² in 2020, representing an incremental loss of 8010 km² over two decades. Future conflict was projected using the PLUS model, calibrated on 2010–2020 observed expansion and validated against the 2020 classified map (OA = 93.99%, Kappa = 0.91). Under the Business-as-Usual (BAU) scenario, 33,368 km² of currently open PV-suitable land faces urban encroachment by 2030; the Ecological Conservation Priority (ECP) scenario reduces this figure to approximately 30,767 km², while the Economic Development (ED) scenario yields a near-identical outcome to BAU, indicating that development velocity alone does not determine the spatial extent of conflict—the allocation of growth does. These findings provide a quantitative basis for designating energy-strategic reserve zones within national spatial planning frameworks and demonstrate that targeted spatial governance, applied at high-pressure locations, can substantially slow the erosion of the region’s solar energy land base. Full article

The dominant agri-food system’s well-documented failures—biodiversity loss, deepening rural inequalities, and the erosion of small-scale farming livelihoods—have elevated SSE initiatives and social innovation in the agri-food sector and bioeconomy from a niche policy concern to a structural priority. This paper examines how SSE arrangements drive meaningful transformation in agri-food chains while advancing sustainable development at local and regional scales. Through a narrative review of interdisciplinary peer-reviewed literature and key institutional sources, the paper synthesizes evidence that SSE initiatives generate transformation through three interconnected mechanisms: (a) the reconfiguration of governance structures; (b) the deepening of producer–consumer relationships through spatial proximity and relational transparency; and (c) the more equitable redistribution of value across agri-food territories. These findings suggest that place-based SSE models occupy a central—rather than peripheral—role in sustainability transitions and local development. The paper presents a structured analytical framework linking SSE practices to agri-food chain transformation and develops nine concrete policy implications for scaling and sustaining SSE innovations through coordinated collaboration among public, private, and social economy stakeholders. The findings contribute to a sharper understanding of the conditions under which SSE-driven models can foster sustainable, socially inclusive, and community-oriented agri-food systems and of why the solidarity dimension, rather than organisational form alone, is the decisive criterion for identifying genuinely transformative initiatives. Full article

This article presents a comprehensive assessment of sediment contamination in the Irtysh River within the industrial zone of the city of Ust-Kamenogorsk, using the Specific Combinatorial Sediment Pollution Index (SCSPI). This study includes a set of priority chemical elements characteristic of the region’s technogenic load (Be, Cu, Zn, As, Se, Cd, Te, Hg, Pb), taking into account their hazard class, persistence in bottom sediments, and ability to accumulate in fine-grained (pelitic) fractions. The assessment was carried out based on the calculation of the frequency index of background exceedance (S_α) and the exceedance multiplicity index (S_β), relative to the effective local background value, followed by the determination of the partial pollution indices (Ki) and the integral SCSPI indicator. It was established that, for most elements, the frequency of exceedance ranges from 75% to 100%, indicating widespread surpassing of the effective local background. The partial indices vary within 4–7 points, with cadmium and zinc making the greatest contribution to the formation of integrated pollution due to the presence of local accumulation zones. Correlation analysis showed that the proportion of the pelitic fraction (<0.01 mm) is most strongly associated with the accumulation of Cd (r = 0.67) and Se (r = 0.66), indicating the preferential accumulation of these elements in fine-grained sediments. Principal component analysis revealed stable geochemical associations among the elements. For the <2.0 mm fraction, the first three principal components explain 73.57% of the total variance, with PC1 mainly associated with Pb, Se, and Cd. For the <0.2 mm fraction, the first three components explain 72.44% of the total variance, and PC1 is characterized by high loadings of Zn, Cd, As, and Se, reflecting the strengthening of the technogenic association in fine-grained material. The SCSPI values across the studied cross-sections range from 5.0 to 5.6, corresponding to a moderately polluted state of bottom sediments (Classes 3a–3b). The spatial distribution of the index reflects the combined influence of technogenic sources and hydrodynamic processes responsible for the redistribution of fine-grained material. The obtained results confirm the applicability of the Specific Combinatorial Sediment Pollution Index (SCSPI) for an integrated assessment of the ecological condition of bottom sediments and for identifying zones of increased technogenic load. A comprehensive approach to the analysis of bottom sediment pollution is proposed, enabling a more accurate identification of spatial distribution patterns of contaminants and their accumulation zones. This provides a scientific basis for the development of adaptive strategies for monitoring and management of aquatic ecosystems. This study is of significant practical importance for advancing sustainable environmental management and the rational use of natural resources under increasing anthropogenic impact. Full article

Municipal solid waste (MSW) generation is a global problem affecting the environment and public health. The current landfill’s useful life is reaching its end, making new site selection a priority to guarantee proper MSW management. This research evaluated the suitability of the metropolitan area of the municipalities of Chihuahua, Aldama, and Aquiles Serdan, using Spatial Decision Support Systems (SDSS) integrated with Multi-criteria Decision-making (MCDM) and hierarchical analysis, and Geographic Information Systems (GIS) to determine potential sites for new Metropolitan landfill development in a semi-arid region. Results showed that 44.7% of the areas studied present a high suitability level, while 29.52% corresponds to a very high suitability level. These areas are located mainly in the north and center zones of the Chihuahua and Aldama municipalities, with some isolated areas in Aquiles Serdan. The key selection criteria were airport distance, land slope, and proximity to the intermunicipal boundary, which enabled the identification of sites with lower environmental impact and greater technical and economic feasibility. This study demonstrates that SDSS and GIS are efficient tools for identifying potential landfill sites. The results highlight the importance of integrating technical, environmental, and social criteria into MSW management planning to achieve sustainable, efficient management in the region. Full article

The dynamism of adventure tourism necessitates the precise identification of areas with suitable natural, infrastructural, and service capacities for hosting activities. The aim of this study is to assess the multi-scenario spatial suitability for the sustainable development of adventure tourism camps using a Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach. The datasets used included topographic, climatic, environmental, accessibility, natural and cultural attraction, and service infrastructure indicators. The relevant criteria were first standardized, and their weights were determined using the Analytic Hierarchy Process (AHP). Subsequently, the layers were integrated through a Weighted Linear Combination (WLC) model. Four scenarios were designed for sensitivity analysis: the first scenario with balanced weight distribution (S_bal), the second prioritizing accessibility (S_acc), the third focusing on natural attractions (S_att), and the fourth emphasizing services (S_serv). The results indicated that approximately 21% and 9% of Chaharmahal and Bakhtiari province have high and very high potential for adventure activities, respectively, which were selected as initial options for the multi-scenario analysis. In the balanced (S_bal) scenario, 31% and 13% of the area of these options fell into high and very high suitability classes, respectively. The Service-Based Scenario (S_serv) increased the share of high and very high suitability areas to 34% and 19%, while Accessibility-Based Scenario (S_acc) reduced these classes to 27% and 10%. In the Attraction-Based Scenario (S_att), the areas in the high and very high suitability classes were 30% and 12%, respectively. The findings demonstrate that altering the priority of components can significantly change the spatial pattern of suitability, and sustainable planning of adventure tourism activities should be conducted based on management objectives and regional capacities. The proposed framework is generalizable to other regions and can serve as a basis for decision-making in balanced development, optimal infrastructure allocation, and sustainable management of adventure tourism. Full article

Regional sustainable development requires integrated assessments that capture ecosystem function, risk exposure, and recovery capacity. Conventional two-dimensional frameworks based on ecosystem services (ESs) and landscape ecological risk (ERI) often overlook the self-regulation potential of ecosystems following disturbance. This study proposes that incorporating RES as a third zoning dimension enables functional differentiation between areas that share similar ES–ERI profiles but differ substantially in recovery capacity, thereby revealing management priorities that a conventional two-dimensional framework cannot detect. This study develops a three-dimensional zoning framework integrating ES, ERI, and ecological resilience (RES) in the main urban area of Ganzhou City, a representative hilly city in southern China. Land-use dynamics from 1990 to 2020 and under four 2050 scenarios were simulated using a coupled PLUS-InVEST approach. Differentiated ecological zones were delineated, and the optimal-parameter geographic detector (OPGD) was applied to examine driving factor interactions. Results indicate that cultivated land and forestland dominated the study area throughout the period. ES supply remained favorable with stage-wise fluctuations, while ERI showed progressive convergence of high-risk patches toward the central basin. RES exhibited a sharp decline in higher-resilience areas during 1990–2000 (91.0%), followed by partial recovery during 2010–2020 (47.3%). The three-dimensional zoning delineated 35.9% of the area as Ecological control zones that may require priority intervention. Driver analysis revealed that DEM, precipitation, and river proximity, along with their interactions, strongly influenced regional ecological patterns. The proposed framework extends conventional ES-ERI assessments and provides spatial guidance for differentiated ecological management in hilly regions. Full article

The use of solar photovoltaic technology is among the most promising approaches to achieving SDG7—Affordable and Clean Energy—which seeks to provide modern, reliable, sustainable, and efficient energy for everyone globally, especially in developing areas with high irradiation, where both energy access and decarbonization are major challenges. South Khorasan Province, Iran, is one of the most highly irradiated regions in the world. However, despite the abundance of solar resources, most previous research in Iran on solar potential has focused on technical potential, with little emphasis on actual energy consumption patterns and economic viability. To the best of our knowledge, this is the first demand-driven assessment at the county level and the first national-scale implementation of the MARCOS (Measurement of Alternatives and Ranking according to Compromise Solution) method for selecting solar energy sites in Iran. A spatially explicit integrated framework based on GIS-MARCOS was established for each of the eleven counties of South Khorasan Province, and five benefits were used as criteria (solar irradiance, population, per capita electrical consumption in residential, industrial, and agricultural sectors). Objective weights were calculated using Shannon’s Entropy. The analysis indicates that residential electricity demand emerges as the most influential factor in the prioritization process. Therefore, the counties of Birjand, Qaenat, and Tabas were identified as top priority counties, while counties with high irradiation levels but low demand (for example, Boshruyeh) received the least priority. These results clearly indicate the need to transition from irradiation-based to demand-based planning to minimize transmission losses and maximize the ability to integrate solar-generated electricity into the electric power grid. This proposed methodology provides a transferable decision-support tool for other high-irradiation, demand-heterogeneous regions around the globe. Full article

Tangyue Village in Huizhou, China, is renowned for its monumental Bao-family archway complex and well-preserved ancestral halls, which host and memorial activities embodying rich clan traditions and regional cultural identity. However, these traditional spaces face contemporary challenges, including functional obsolescence, high energy consumption, and limited sustainability. Focusing on the memorial spaces of Tangyue Village, this study explores low-carbon design strategies for their renewal by developing a comprehensive research framework that integrates multi-stakeholder demand analysis, weighting evaluation, case-based design, and performance verification. Initially, user needs were identified through semi-structured interviews and behavioral observations, followed by the application of the Fuzzy Kano (FKANO) model to classify and filter these requirements. Subsequently, a multi-level evaluation system was established, encompassing low-carbon performance, spatial functionality, cultural continuity, and community participation. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach combined with the entropy weight method was then employed to determine the relative importance of each indicator. The results indicate that the organization of memorial spaces, the application of low-carbon materials, rainwater harvesting, and spatial accessibility represent key design priorities. Space syntax simulations conducted via DepthmapX further demonstrate that the optimized design significantly improves spatial accessibility, permeability, and vitality while enhancing the overall low-carbon performance. Ultimately, this study proposes practical low-carbon renewal strategies for memorial spaces in traditional settlements, offering a systematic approach that balances cultural heritage preservation with environmental sustainability. Full article