Cropland abandonment has become increasingly significant in mountainous regions, with its ecological effects attracting extensive attention. According to previous studies, cropland abandonment improves vegetation recovery and certain ecosystem service functions. However, spatial heterogeneity driven by variations in natural environmental conditions may lead to substantial differences in its ecological effects across regions. Despite this, the understanding of long-term dynamics of soil conservation under complex geomorphic conditions remains scarce. Taking the karst region of Southwest China as the study area, this study used the 2000–2023 China Land Cover Dataset (CLCD) to identify cropland-abandonment onset during 2000–2020. The land-use trajectory-tracking method was employed in this study to identify cropland abandonment processes, and the InVEST model was used to simulate soil retention functions. Subsequently, comparisons were made between abandoned and non-abandoned cropland, so as to evaluate spatial heterogeneity and temporal instability in soil conservation under different geomorphic backgrounds. The results show that: (1) From 2000 to 2020, the annual newly abandoned cropland area fluctuated between 273,227.49 and 2,584,205.28 ha, while the annual abandonment rate ranged from 0.889% to 8.415%; both reached their minima in 2018 and maxima in 2020. Spatially, abandonment is concentrated in the mountainous and hilly areas of Guizhou, eastern Yunnan, and northwestern Guangxi; (2) During the study period, the regional average soil retention decreased from 11.48 to 8.32 t·km-2·a-1, with an overall decline of about 27.5%. The area with the lowest values increased from 9.4% to 26.9%; (3) Between 2001 and 2018, soil conservation in abandoned cropland was generally higher than in non-abandoned cropland, with values ranging from 3.66 to 15.47 t·km-2·a-1. However, in 2019–2020, this trend reversed, with negative values (−1.20 and −0.33 t·km-2·a-1, respectively); (4) There are significant variations in the effects of abandonment depending on geomorphic contexts. In low-altitude alluvial-proluvial land (LAAP), was the highest (6.83 t·km-2·a-1), whereas mid-high altitude high-relief terrain (MHHRT) exhibited negative effects (−1.10 t·km-2·a-1). These findings indicate that the soil conservation effects of cropland abandonment in the Southwest China karst regions are highly dependent on geomorphic conditions and are temporally unstable, and the increase in abandoned cropland does not necessarily align with increased ecological benefits. This study contributes to a deeper understanding of the variability of ecological effects across complex geomorphic settings and provides scientific references for ecological restoration and land-use optimization in karst regions.
Forest degradation assessments are constrained by single-dimensional indicators (e.g., NDVI) that fail to simultaneously capture functional degradation (biomass loss) and structural degradation (landscape fragmentation), while type-specific management responses remain poorly operationalized. To address this gap, we developed a Composite Degradation Index (CDI) integrating biomass dynamics (Biomass Slope) and a forest fragmentation index (FFI). The CDI was applied at a 30 m spatial resolution using MODIS NDVI/EVI, SRTM DEM, and land-use data from 2000 to 2020 across coniferous, broad-leaved, and mixed forests across the Qinghai-Tibet Plateau (QTP) to quantify degradation severity, identify nonlinear response thresholds, and project fragmentation trends under CMIP6 scenarios using natural breaks classification. Random Forest, XGBoost, and SHAP analysis disentangled the relative contributions of climatic factors, topography, and human activities. The CDI improved assessment accuracy by 22% relative to NDVI. Coniferous forests exhibited strong sensitivity to warming (5.2% per +1 °C), with 27% of degradation indirectly linked to permafrost thaw. Broad-leaved forests responded most strongly to precipitation variability (3.8% per +10%), reflecting hydraulic stress and habitat connectivity loss. Mixed forests showed the highest anthropogenic degradation (35% contribution), highlighting ecotonal fragmentation. Under SSP5-8.5, severe fragmentation is projected to reach 21.73% by 2060; moderate mitigation delays extreme fragmentation by 1.6 years. The CDI provides a transferable framework for “threshold diagnosis–attribution–zoning intervention” in the QTP and analogous vulnerable ecosystems. Based on type-specific response thresholds, we propose three management strategies: (i) permafrost monitoring and thermal buffering for coniferous forests; (ii) hydrological connectivity conservation for broad-leaved forests; and (iii) anthropogenic disturbance buffers for mixed forests. This study demonstrates that composite indicators can bridge environmental monitoring and sustainability decision-making, directly contributing to SDG 13 and SDG 15.
Coastline erosion and flooding pose serious threats to coastal settlements, particularly in rapidly urbanising regions where climate change is exacerbating these hazards. This study aims to assess the spatial vulnerability to erosion and flooding across the 664.42 km2 Durban coastline using complementary geospatial techniques. The Digital Shoreline Analysis System (DSAS) and Analytical Hierarchy Process (AHP), supported by field observations, were used. The results show that approximately 41% of the coastline is highly susceptible to erosion. The flood vulnerability assessment applied eight (8) physical and three (3) socioeconomic criteria, and a consistency ratio of 0.08. Approximately 369.00 km2 (56%) and 214.65 km2 (32%) of the coastal area are moderately and highly vulnerable to flooding, respectively, while 6.71 km2 (1.01%) is very highly vulnerable, with critical hotspots concentrated in low-lying coastal areas. Low-vulnerability areas accounted for 74.06 km2 (11.15%). However, there was a strong spatial overlap between high erosion and flood risk in Umlazi, Durban Bay, the Umgeni, and the uMkomazi estuaries, which were among the areas affected by the April 2022 floods. In these areas, shoreline retreat and encroachment of informal settlements have diminished the natural protective features of coastal dunes, wetlands, and beach width, exposing the population to hazard impacts. These findings highlight the urgent need for stricter implementation of the Integrated Coastal Management Act to address the interconnected risk of erosion and flood hazards in the area. These findings are particularly useful to disaster managers and coastal engineers in supporting spatial decision-making to enhance the resilience and sustainable planning of coastal communities in the area.
Managing agricultural landscapes requires solutions that promote sustainability and resilience. Given the complexity of these systems, decision-making must consider multiple criteria. The participation of different stakeholders, combining knowledge and experience, strengthens efforts to achieve Sustainable Development. This study examines the use of a participatory model in agricultural landscape management, employing multicriteria decision analysis (MCDA) as an evaluation framework. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied to conduct the MCDA. Two scenarios were analysed: sustainable technological solutions for olive groves (SUSTAINOLIVE project) and measures to mitigate flood and erosion risks. Questionnaire responses were used to evaluate and prioritize alternatives (FLOOD RISK project). Four criteria were included in the questionnaires: environmental relevance, urgency of implementation, feasibility, and implementation cost. In both cases, TOPSIS results were robust, and the prioritized alternatives were stable (1st alternative maintained the rank in 55% of the TOPSIS solutions in the SUSTAINOLIVE project and in 80% of the TOPSIS solutions in the FLOOD RISK project). TOPSIS methodology supports informed and transparent decision-making for sustainable agroecosystem management. Results indicate that varying the criteria weights significantly influences the prioritization of alternatives, and that when the stakeholders assign weights through agreement, the prioritization distribution of alternative is more heterogenous, highlighting the importance of stakeholder active engagement and open future research lines to detect barriers or windows of opportunity for implementing the management solution.
In forested regions, rights-of-way for power lines modify local environmental conditions, creating three vegetation zones: the corridor, forest edge and adjacent forest. Because corridors undergo regular vegetation maintenance to prevent tree growth, their effects on vegetation functional diversity remain poorly understood. We surveyed the abundance and cover of forbs, shrubs and trees at 18 sites spanning a 750 km north–south climatic gradient in Québec, Canada. For each vegetation stratum and position relative to the right-of-way, we calculated functional diversity metrics (functional richness, divergence, evenness, and dispersion) and the Shannon Weaver index using plant functional traits reflecting ecological strategies, pollinator habitat suitability, and ecosystem functioning. Linear mixed-effects models assessed the effect of position relative to the right-of-way, corridor characteristics, edaphic variables, and climate on each diversity index.Position relative to the right-of-way was the principal driver of vegetation functional diversity, significantly influencing 8 of the 15 models; the strongest model explained 52% of variation, and the median marginal R2 was 0.33. In contrast, corridor characteristics had fewer effects. Shrub functional diversity was consistently lower in corridors than at forest edges and adjacent forests, while forest edges were similar to adjacent forests. Responses of forb communities were mainly influenced by climatic conditions interacting with position, whereas tree functional diversity showed few responses. Overall, power line rights-of-way primarily altered the functional diversity of understory vegetation, whereas forest edges retained functionally diverse communities comparable to those in adjacent forests. These findings advance understanding of vegetation responses to right-of-way management across broad environmental gradients.
Tourism economic resilience (TER) refers to the ability of a tourism economic system to remain stable, recover, and adapt to a new equilibrium after external shocks. Meanwhile, TER has been affected by multiple factors. However, in ecologically fragile regions, it remains unclear whether TER is mainly shaped by ecological conditions alone or by a multidimensional synergistic driving pattern under the relative dominance of the ecological environment. The practical question requires precise identification through scientific methods, so as to better coordinate the relationship between tourism development and ecological protection. Hence, this study constructs a TER evaluation indicator system, including resistance ability, recovery ability, reconstruction ability, and update ability, to evaluate the spatiotemporal characteristics of TER in Jiziwan, China, and identify the dominant drivers for TER by utilizing partial order theory (POT) and Hasse diagram technique (HDT). The results indicated the following: (1) TER showed an overall upward trend from 2010 to 2023, and the spatial characteristics decreased from the centre to the periphery. (2) Comparative analysis of the three periods reveals that the ecological environment was the relatively dominant driver of TER in all periods. (3) In the future, we should strengthen ecological protection and promote the development of green tourism, especially in cities such as YL, YA, and SZ. This study fills the research gap by applying POT and HDT in the tourism field, and provides theoretical and policy support for the green transformation of tourism industry and regional ecological environment protection in Jiziwan.
Assessing progress in climate change adaptation remains challenging, particularly in human settlements and human security where adaptation outcomes involve interactions among infrastructure systems, governance mechanisms, and social vulnerability. Existing adaptation monitoring approaches often emphasize institutional outputs and infrastructure measures while providing limited insight into how these interventions translate into resilience at the household and community levels. This study develops a multidimensional indicator framework for assessing climate change adaptation in the context of human settlements and human security in Thailand. The framework was developed through a review of adaptation literature and global adaptation frameworks, analysis of Thailand’s National Adaptation Plan, and consultations with relevant government agencies and experts. The findings identify five interrelated dimensions of adaptation: urban planning, infrastructure quantity and quality, disaster preparedness and risk reduction mechanisms, social protection and resilience mechanisms, and quality of life and household resilience. The proposed indicators represent different stages of the adaptation results chain, encompassing process, output, and outcome measures across these dimensions. The framework integrates institutional adaptation mechanisms with household-level dimensions of adaptive capacity, including housing security, economic resilience, and social protection coverage. The study demonstrates how multidimensional and context-sensitive adaptation indicators can be operationalized within existing governance and administrative systems, providing a practical link between global adaptation priorities and national implementation in developing-country contexts. The proposed framework provides an operational basis for monitoring adaptation progress and supporting national adaptation governance in Thailand while offering a context-sensitive approach that may inform adaptation monitoring in other developing-country settings.
Identifying factors associated with cultivated land non-agriculturalization (CLN) is essential for food security and sustainable development, yet most existing studies neglect spatiotemporal non-stationarity and scale dependence, limiting both theoretical understanding and policy precision. To address this gap, this study develops an integrated "spatiotemporal–scale–mechanism" analytical framework and applies it to Yunnan Province, China, a region characterized by pronounced topographical and ecological heterogeneity. Using complete annual panel data for 2000–2022, we fitted one unified Geographically and Temporally Weighted Regression model at each of two nested administrative scales—prefecture and county—and summarized the resulting location- and year-specific coefficients across three development periods. Three principal findings emerge: (1) CLN exhibits marked spatiotemporal non-stationarity, with driver magnitude and direction varying across both space and time; (2) a clear scalar shift in driver dominance is confirmed — macroeconomic factors dominate at the prefecture scale while biophysical endowments prevail at the county scale, providing empirical evidence for the ecological fallacy; and (3) cross-scale analysis documents a governance transition from scale conflict toward scale coordination, reflected in declining spatial mismatches and expanding 'oasis within hotspot' patterns. These findings demonstrate that CLN governance cannot be adequately informed by stationary or single-scale analyses. More effective cultivated-land protection requires multiscale, adaptive, and spatially differentiated strategies that account for both macro-level development pressures and locally specific environmental constraints, while recognizing that the identified relationships are associational rather than causal.
Human activities have significantly increased carbon dioxide (CO2) emissions, exacerbating global warming. Therefore, accurately estimating anthropogenic emissions is crucial for developing effective emission reduction policies. This study focuses on evaluate the impact of land cover (LC) and topography (DEM) on inverted CO2 fluxes using a new developed regional Carbon Assimilation System (RCAS). Our primary aim is to assess the extent to which LC and DEM influence CO2 flux inversion in Shenzhen, a rapidly urbanizing coastal city. To achieve this, we analyzed the forward simulations of meteorological variables (wind speed/direction, relative humidity, temperature, and pressure) alongside CO2 concentration simulations. Following this, we evaluated the posterior CO2 concentration estimates with the CO2 flux from the inversion system. The findings demonstrate that new LC and DEM data led to a mean bias reduction from -1.08 ppm to -0.88 ppm, representing a 0.2 ppm improvement, and a slight decrease in standard deviation values from 5.59 ppm to 5.57 ppm in the posterior CO2 concentration simulation. These results underscore the critical importance of accurate LC and DEM data in enhancing CO2 flux inversion accuracy, providing valuable insights for improving regional-scale carbon monitoring systems.
Cropland abandonment has become a widespread land-use transition under global socioeconomic transformation, with critical effects on regional ecosystem structure, service functions, and environmental sustainability. However, existing studies remain limited in explaining the long-term dynamics and nonlinear driving factors through which cropland abandonment affects water-related ecosystem services in humid regions. This study focuses on the Lingnan region, a typical humid area in southern China. Using the 30 m-resolution China Land Cover Dataset from 2000 to 2023 and a land-use trajectory-tracking method, this study identified the spatiotemporal patterns of cropland abandonment, coupled the InVEST water yield module with a Random Forest model to quantify changes in InVEST-simulated water yield, and identified underlying driving factors. According to the results, (1) abandoned cropland ranged from 8.90 × 104 to 7.23 × 105 ha, with a mean abandonment rate of 2.13%. Spatially, it exhibited a dispersed mosaic pattern with regional clustering, mainly distributed in low- and moderate-slope areas and gradually expanding toward more complex terrain conditions; (2) more than 92% of abandoned patches showed increased simulated water yield depth, with a multi-year mean of 769.87 mm, while localized decreases occurred on steep slopes where soil erosion may weaken the hydrological response; (3) climatic factors served as the dominant driving factors of simulated water yield changes, with annual precipitation contributing the most to model explanation (0.536), and all key variables exhibited nonlinear responses, indicating complex interactions between climatic conditions, terrain characteristics, and vegetation recovery processes. These findings provide quantitative evidence to better understand how cropland abandonment reshapes water-related ecosystem services in humid regions and support spatial governance strategies that coordinate food security, ecological protection, and environmental sustainability amid rapid urbanization.
Understanding how local stakeholders perceive forest ecosystem services (FES), particularly when considering sociodemographic factors and forest governance types, can inform sustainable forest use and management. However, such evidence on the ecosystem services provided by forest patches in Western Africa is limited. We conducted 2,621 household surveys across nine forest patches in four Western African countries: Togo, Benin, Nigeria, and Cameroon. Provisioning services were the most perceived forest benefit (83.5%), followed by regulating (12%), cultural services (1.6%), and 2.9% of no benefits. A logistic regression model showed that age group, education level, residency, main occupation, and marital status explain the variation in FES perceptions. However, main occupation and marital status exert a weaker influence on the probability of change in perceptions. The Kruskal-Wallis non-parametric H test revealed significant differences in FES perceptions across sociodemographic factors. While FES were generally considered important, perceptions of their changes over time vary across forests. Moreover, the forest governance type plays a significant role in these perceptions, especially among residents living near community-based forests and family-owned forests. The identified perception gaps between provisioning, regulating, and cultural ecosystem services constitute a governance and policy risk. The findings show that integrating social-ecological contexts, sociodemographic factors and forest governance status together and individually in examining FES perceptions reveals the extent to which the multi-layered mechanisms shape decision-making on sustainable forest management. Ignoring them can hinder the legitimacy and effectiveness of policies aimed at sustainable forest management.
Providing tactical management advice for tropical information limited fisheries can be difficult due to the constraints and assumptions of available approaches and uncertainty in data input streams. This study presents a workflow which combines information limited fisheries approaches together with data input sensitivity analyses in a novel way to develop a range of plausible management scenarios and their respective bioeconomic trade-offs, with uncertainty, to inform decision theory. The study applies the approach to the commercial demersal finfish fishery across the Indonesian archipelago. Estimates of fishing mortality, biomass, forecasted catch, rebuilding times, profit, and nutritional outcomes were calculated at five different management reference points and for the status quo. For some species, estimated biomass was below the biomass associated with the limit reference point, and fishing mortality rates were higher than the fishing mortality rate associated with the target reference point. Under the status quo, the fishery is operating at a financial loss, predominately due to the biomass and current fishing mortality rate of the most targeted species, Lutjanus malabaricus, and its large contribution to the catch. The novel study approach provided a menu of policy considerations and their respective trade-offs that managers can use to make informed decisions that balance biological sustainability with economic and nutritional outcomes.
Carbon neutral territorial planning in mountainous provinces requires more than aggregate carbon balance, it also depends on whether spatially concentrated emission deficits can access usable sequestration surplus within feasible coordination distances. This study develops a cross scale diagnostic framework for Yunnan, China, by coupling built up constrained DMSP-OLS/VIIRS nighttime emission downscaling with InVEST based carbon-storage and annual CO2 equivalent sequestration estimation for 2000 to 2024. Deficit and surplus units were identified using net carbon emission pressure and the ecological support coefficient, while Wasserstein-1 distance and the minimum compensation radius were used to quantify distributional mismatch and spatial accessibility, respectively. The results show that at the grid scale, total surplus exceeds total deficit by approximately 6.2%, but mismatch is tail-dominated: 3,371 deficit cells coexist with 8,342 surplus cells, and the Wasserstein-1 distance reaches 1.54×107kg CO2 yr-1. Most grid deficits are locally compensable, with a median compensation radius of 8.3 km and 98.22% coverage within 30 km. However, at the county scale, coordination demand amplifies sharply. Among 129 counties, 62 are deficit units, and the median compensation radius increases to 85.3 km, with the 95th percentile reaching 171.3 km and the maximum reaching 222.9 km, only 12.9% of deficit counties can be compensated within 50 km. These findings demonstrate that carbon-neutral planning in mountainous provinces is constrained less by aggregate sink insufficiency than by accessibility-limited mobilization of usable sinks. This transferable framework converts source-sink mismatch into actionable coordination thresholds and governance strategies for mountainous eco-barrier regions.
This study offers a detailed, field-based evaluation of the interstate elephant corridors in Nagaland, India, identifying eleven corridors that facilitate connectivity between Nagaland and Assam. Employing a multidisciplinary approach that combines field observations, community interviews, spatial mapping, and remote sensing to study corridor integrity, landscape features, and conservation status within a region predominantly managed through community land tenure, as established by Article 371(A) of the Indian Constitution. Multi-temporal analysis of the Normalized Difference Vegetation Index (NDVI) for the years 1994, 2009, and 2024 indicated an initial reduction in vegetation greenness, followed by a notable increase post-2009. Nonetheless, supplementary field and Land Use/Land Cover (LULC) analyses revealed that this greening largely results from the proliferation and maturation of commercial plantations, such as rubber, areca nut, teak and tea, rather than native forest recovery. Consequently, vegetation greenness alone is an unreliable metric for evaluating elephant habitat quality and corridor effectiveness. The examination demonstrates that the corridor network does not exhibit uniform degradation but instead comprises stable, recovering, declining, and severed corridors, reflecting diverse ecological responses to habitat fragmentation, land-use changes, and socio-economic development. These transformations have diminished habitat quality, impaired elephant movement, and escalated human-elephant conflicts. The study underscores the importance of integrating ecological restoration, participatory governance, and sustainable land-use planning tailored to Nagaland’s community-based land tenure for effective long-term corridor conservation. It concludes that elephant corridors should be viewed as dynamic socio-ecological systems requiring both functional connectivity and robust community stewardship to ensure the coexistence of humans and elephants.
Land-use and land-cover change (LUCC) strongly influences terrestrial carbon sequestration and climate mitigation, making accurate future simulation essential for sustainable land management. However, many existing studies separately address LUCC prediction and carbon assessment, with limited use of interpretable multi-scenario frameworks. This study developed an integrated framework combining Random Forest (RF) machine learning, CA–Markov spatial simulation, and the InVEST Carbon Storage and Sequestration model to project LUCC dynamics and associated carbon changes from 2024 to 2050 in metropolitan Prague, Czech Republic. RF-derived transition potentials based on topographic, climatic, and anthropogenic drivers were incorporated into the CA–Markov allocation process to simulate Business-as-Usual, Ecological Optimization, and Urban Growth scenarios. SHAP analysis revealed a class-specific gradient in driver dominance: anthropogenic accessibility factors dominated transitions in six of seven land-cover classes (from 51.0% for water to 75.7% for built-up areas), whereas only hydrologically sensitive flooded vegetation was primarily controlled by elevation and climate. The Ecological Optimization scenario produced the greatest gains in vegetation cover and carbon storage, while the Urban Growth scenario resulted in the largest conversion of agricultural land to built-up areas. InVEST analysis identified persistent high-carbon areas and an overall positive carbon sequestration trend associated with vegetation recovery and forest expansion. The proposed framework provides an interpretable and reproducible approach for linking LUCC dynamics with ecosystem carbon storage and supports sustainable land-use planning and climate mitigation strategies in metropolitan regions.
Human-driven destabilisation of the Earth system threatens ecological thresholds, or irreversible tipping points. Integrated Assessment Models (IAMs) capture ecological limits but miss the lived local socioeconomic and governance realities. To bridge the gap between Earth system science and governance, this study asks: how can global Planetary Boundaries (PBs) be translated into sub-national climate policy actions? Positioned as a methodological framework paper, this study introduces a novel multi-scalar indicator Framework for Integrated Theory, Model, and Strategy Architecture (FIT-MSA). Through the fusion of seven interconnected models, the FIT-MSA framework translates planetary constraints into actionable strategies for India at national and sub-national sustainability metrics. Using network analysis and a computational model, the FIT-MSA shows that targeted mitigation, especially achieving net-zero, serves as an Earth system stabiliser for interlinked biophysical nodes. Evidence shows that these global limits, when scaled down to national indices, highlight vulnerabilities in India's biogeochemical flows and land systems. The Indian power sector assessment suggests that unabated coal use leads to a multi-boundary threat. At the same time, the study shows that decarbonization could have macroeconomic implications and uneven transition capacities among resource-dependent states. The FIT-MSA provides a methodological framework for closing institutional accountability gaps and enables enforcement by mandating redistributive mechanisms and directly linking ecological deficits to laws and agencies. Securing India's long-term climate and economic future requires moving beyond generic pledges to adopt context-specific, binding sustainability metrics and transparent market mechanisms.
Infrastructure-induced residual spaces the leftover lands beneath metro viaducts, along highway and railway edges, under flyovers, and between built elements constitute a distinct and underexamined category of urban leftover space. Unlike residual land defined by value deficiency or planning status, these spaces originate within transport and mobility systems, which impose specific spatial constraints, environmental degradation, and governance complexities that conventional revitalisation frameworks do not adequately address. This study conducts a systematic literature review of 131 peer-reviewed articles, retrieved using the terms "leftover space" and "residual space", to examine how such spaces have been addressed through nature-based solutions (NBS). Five dominant typologies are identified metro viaduct, highway edge, railway edge, under-flyover, and in-between infrastructure spaces each associated with recurring NBS-oriented revitalisation strategies that reflect varying degrees of ecological intervention, social engagement, and governance involvement. By aligning these typologies with corresponding NBS strategies across policy, implementation, funding, and long-term management, the study develops a preliminary typology–strategy framework to support evidence-based planning and landscape-led regeneration. The findings offer a structured basis for integrating residual urban spaces into sustainable and resilient urban systems.
Endangered freshwater fishes are highly vulnerable to climate change, yet conservation prioritization often relies on single metrics that may not fully capture compounded risks associated with climatic and land-use stressors. Here, we assessed climate vulnerability in 19 freshwater fish species legally designated as endangered in South Korea using a multi-indicator framework that integrates recurrent climatic exposure and ecological threshold sensitivity. Habitat suitability was projected using multi-algorithm ensemble species distribution models under four Shared Socioeconomic Pathways for the 2050s and 2080s. Recurrent severe exposure was defined as a loss of ≥80% of currently suitable habitat in at least four of the eight scenario–time projections. Ecological sensitivity was quantified using Threshold Indicator Taxa Analysis (TITAN) along thermal and land-use gradients. Nine species met the recurrent-exposure criterion, whereas four met the ecological-sensitivity criterion. TITAN revealed pronounced nonlinear responses to temperature and anthropogenic land use, including negative responses even at low levels of urbanization and positive responses associated with high forest cover. All four species meeting the ecological-sensitivity criterion also experienced recurrent severe exposure and were assigned to Tier 1, whereas five additional species met the exposure criterion alone. Two Tier 1 species were endemic to South Korea, highlighting the global conservation significance of projected habitat losses for these taxa. These findings show that projected habitat loss alone may not fully characterize ecological risk and underscore the value of integrating climatic exposure with ecological threshold responses.
Environmental and sustainability indicators are essential tools for translating complex ecosystem processes into actionable information for assessment and management. Marine food webs capture key dimensions of ecosystem structure, functioning, and resilience, yet their operational use as indicators remains limited and uneven. This review evaluates the current capacity of food-web indicators to support sustainability-oriented environmental assessment across European seas, with particular attention to ecologically vulnerable systems such as the Black Sea. A two-tiered synthesis was applied: Tier 1 maps food-web indicator applications in peer-reviewed literature (Stream A, n = 11, used as a structured mapping corpus) and operational grey literature including (Stream B, n = 13); Tier 2 screens broader food-web literature for methodological and conceptual capacity. Stream A reveals a strong reliance on structural indicators and lower-trophic components, while indicators addressing energy flow, trophic balance, and ecosystem service relevance are applied less consistently. Significant geographic disparities are evident, with well-monitored regions dominating indicator development and semi-enclosed seas remaining underrepresented. For the Black Sea, underrepresentation reflects a structural governance and capacity gap: EU member states Romania and Bulgaria reported no Descriptor 4 assessment data in the 2018 reporting cycle despite available monitoring infrastructure. Overall, current limitations arise primarily from gaps in standardisation, implementation feasibility, and governance alignment rather than from insufficient scientific knowledge. Addressing these gaps requires a prioritised set of cross-trophic indicators for harmonised deployment, targeted capacity-building in data-limited regions, and faster translation of methodologically ready approaches into operational assessment frameworks.
