Search Results (2,168)

Climate change and aging infrastructure are undermining the resilience of urban flood management systems, reducing their reliability and increasing the likelihood of systemic failure that may culminate in regime shifts. This study develops a conceptual and practitioner-oriented screening framework based on a quantitative mathematical model to examine facility-level resilience and identify threshold conditions that may trigger regime transitions under external disturbances and varying pre-disturbance facility conditions. The framework adopts the composite sigmoid function (CSF) to capture nonlinear performance trajectories of infrastructure systems. Building on this model, this study extends its application by developing a parameterization scheme directly linked to four resilience dimensions: robustness, redundancy, rapidity, and resourcefulness (4Rs), which can be derived from field investigations or expert surveys. The normalized 4R scores are mapped to the CSF parameters, thereby converting static resilience assessment results into degradation and recovery curves. To search for threshold conditions, a parametric analysis was conducted by systematically varying the 4R values across their defined ranges. Rather than indicating a single universal threshold value, the results revealed critical threshold regions formed by specific combinations of the 4R dimensions. Lower robustness reduced the initial performance buffer, and low redundancy accelerated and extended performance degradation, while insufficient rapidity and resourcefulness delayed or limited recovery, increasing the likelihood of transition into an alternative degraded regime. For example, even when R1 and R2 were set to relatively high normalized values of 0.90, and R3 was set to its maximum value of 1.00, full recovery could not be achieved when R4 decreased below approximately 0.20. An illustrative application was conducted using preliminary 4R assessment results for flood-control facilities in three districts of Seoul, Korea. The model-derived trajectories were qualitatively compared with reported historical vulnerability patterns. While this comparison was intended as a contextual assessment rather than an event-specific empirical validation, our framework supports comparative, scenario-based screening of potentially vulnerable facilities for preliminary maintenance and investment prioritization. Full article

Urban climate risks, particularly extreme heat and flooding, increasingly threaten public infrastructure in rapidly urbanizing regions. Public schools represent critical community assets, yet their spatial planning often overlooks the role of natural capital in mitigating environmental risks. This study examines the intersection of natural capital and urban design through a case study of public schools in the Mount Vernon District of Fairfax County, Virginia. Using cartographic modeling and spatial analysis, the study assesses school-site exposure to urban heat island effects and localized flood risks by integrating geospatial data on land cover, surface temperature, and hydrological conditions. Results indicate that all analyzed school sites exhibit notable vulnerability to both heat exposure and flooding. The findings highlight the importance of incorporating natural capital—such as expanded tree canopy, green infrastructure, and permeable surfaces—into school site planning to enhance climate resilience and environmental quality. Full article

Effective conservation of the Near Threatened (NT) black-necked crane (Grus nigricollis) requires standardized frameworks for organizing multi-scale biodiversity data. This study proposes the Essential Biodiversity Variables (EBV) system as an optimal structure for archiving and sharing biodiversity data such as Habitat Suitability Index (HSI). Developed by the Group on Earth Observations Biodiversity Observation Network (GEO BON), the EBV framework is an emerging system offering a robust solution for standardizing data exchange. Based on 483,592 valid location records of 106 black-necked cranes using satellite telemetry, we apply species distribution models and demonstrate how the multi-dimensional EBV architecture accommodates distinct life-stage preferences: breeding sites favor mid-elevations modulated by temperature; migration staging relies on precipitation regimes; and wintering grounds are driven by moisture availability and the avoidance of human-modified landscapes. The EBV NetCDF (Network Common Data Form) format functions as a self-describing hypercube that captures spatial, temporal, and life-stage dimensions while ensuring metadata transparency. This integration facilitates critical applications, including the identification of priority conservation areas and climate vulnerability assessments, thereby bridging the gap between species-specific modeling and global biodiversity monitoring standards. Full article

Lagos, Nigeria (population c.18.3–25 million), occupies a position of compound exposure at the intersection of accelerating climate hazards, recurring displacement and urban fragility, and governance constraints that have amplified rather than mitigated disaster risk. Conventional single-hazard planning paradigms have been demonstrably insufficient to address the structural drivers of this vulnerability, which emerge from the interaction among biophysical exposure, colonial spatial legacies, post-independence governance deficits, and inequities within the global climate finance architecture. This article employs a structured, systematic literature review of 74 peer-reviewed, institutional and policy sources, conducted through a transparent three-stage protocol involving keyword-based Boolean searches of Scopus, Web of Science, Google Scholar, and the African Journals OnLine (AJOL) database, title–abstract screening, full-text eligibility assessment against pre-specified criteria, and thematic synthesis using a combined deductive–inductive coding framework, reported in accordance with the PRISMA 2020 guidelines. Thematic analysis yields four principal findings: Lagos’s flood and displacement cycles are products of structurally produced vulnerability; compound climate–displacement dynamics are systematically underestimated by single-hazard frameworks; nature-based solutions, community-led upgrading, and participatory governance show measurable effectiveness under enabling governance conditions; and transformative resilience approaches are constrained by political economy and land tenure dynamics. An original Integrated Urban Resilience Framework (IURF) incorporating five pillars is proposed and conceptually benchmarked against twelve comparable Global South frameworks. Post-disaster urban futures in rapidly urbanising megacities require technically rigorous, politically grounded, and ecologically integrated planning frameworks. The IURF offers a replicable conceptual scaffold for cities facing compound climate–displacement risk, subject to future empirical testing. Potential applications of the framework for state planning agencies, multilateral and bilateral funders, community organisations, and comparable West African coastal cities are specified, and the limitations of the review are set out in full. Full article

The resilience of electricity networks to extreme weather is an essential component of sustainable energy systems, as power interruptions can affect essential services, economic activities, public safety, and the integration of renewable energy sources. However, this assessment can be challenging due to the inherent differences and complexities between weather and grid data. To address this issue, we developed a data pipeline to acquire, prepare, and integrate power grid outage records, meteorological measurements, and lightning strike data into a unified relational database. The framework was applied to the Italian power grid, with detailed regional analyses conducted for Piedmont and Campania. The results show that, for more than 90% of the matched weather-related failures, at least one relevant weather condition was identified in the integrated datasets. Rainfall showed the most widespread association with failures throughout the year, while lightning was particularly relevant during summer and snowfall during colder months. The proposed framework provides a reproducible basis for monitoring weather-related infrastructure vulnerability and can support evidence-based maintenance prioritization, climate adaptation, and resilience-oriented grid planning. By facilitating the identification of regional risk patterns, the approach contributes to the development of more reliable and sustainable electricity infrastructure. Full article

Sudan faces riverine flooding along the Blue Nile and chronic drought across Darfur–Kordofan, yet no national assessment integrates both hazards with social vulnerability to support sustainable and climate-resilient development. This study develops a Societal Impact Index (SII) for Sudan’s eighteen states using a terrain-based flood-susceptibility surface, a drought-frequency indicator (SPEI-12), and thirteen social-vulnerability indicators. These are combined into four weighted pillars following the Intergovernmental Panel on Climate Change (IPCC) risk architecture and validated against independent humanitarian-needs assessments, with convergent checks based on displacement and malnutrition. An unsupervised machine-learning audit, combining k-means clustering with principal component analysis, tests whether the data’s structure supports the composite ranking. The audit shows that the five High-impact states follow two distinct pathways: hazard-and-exposure dominance in Al Qadarif and Al Jazirah, and sensitivity dominance in the remaining three Darfur states. This distinction enables risk-reduction and infrastructure measures to be tailored to the dominant pathway in each state. The first two principal components correlate only weakly with the SII ($r=0.02$ and $r=0.36$), indicating that the ranking reflects the assigned weights as well as the data structure. Each score is exactly decomposed into pillar contributions, improving transparency, while a prototype scenario tool illustrates practical use. Flood-exposed population increased by 7.4 percent between 2017 and 2020, highlighting the need for continuous updating. The reproducible, open-data framework can support equitable resource allocation, sustainable infrastructure planning, long-term vulnerability reduction, and future disaster-resilience digital twins in data-scarce Sahelian settings. Full article

Climate change has increased the vulnerability of coffee farming by affecting the environmental conditions that sustain production. The objective of this study was to analyze how climate change vulnerability has been assessed in coffee farming systems through a systematic review of the scientific literature. The methodology consisted of a systematic search in the Dimensions database using the terms vulnerability, climate change, and coffee. A total of 49 articles were analyzed according to four analytical axes: (1) chronology and institutional origin, (2) study subjects and spatial location, (3) theoretical and methodological approaches, and (4) temporal scale. The results show an increase in research beginning in 2020, led mainly by institutions from the United States and Brazil, which together accounted for 28.8% of the total studies. A high diversity of study subjects was identified, grouped into seven categories and 18 thematic areas, with coffee farmers, households, and production systems being the most prominent, mainly located in Brazil and Nicaragua. Assessments based on the Intergovernmental Panel on Climate Change (IPCC) framework predominated, particularly those using composite indices, climate suitability models, and hybrid approaches combining biophysical and socio-economic variables. The current vulnerability was the dominant temporal scale. The review highlights substantial methodological diversity, spatial concentration of studies, and limited incorporation of prospective scenarios. Full article

High-altitude Andean páramo ecosystems are critical socio-ecological assets that provide key regulating and supporting services, yet they remain highly vulnerable to climate change and anthropogenic pressures. Understanding these services requires frameworks that integrate biophysical capacity with social valuation and demographic accessibility. In this study, we mapped and assessed belowground and aboveground carbon storage and species habitat provision across the altitudinal gradient (3160–4400 m.a.s.l.) of Cajas National Park (PNC), Ecuador, using a spatially explicit socio-ecological approach. Carbon stocks were modeled following The Intergovernmental Panel on Climate Change (IPCC) 2019 Refined Guidelines, combining reference soil organic carbon (SOC) stocks with aboveground biomass coefficients. Habitat provision was modeled through a multi-factor suitability index integrating Normalized Difference Vegetation Index (NDVI), elevation, water bodies, and interpolated climate surfaces. Biophysical supplies were weighted via a Delphi-based expert consultation and integrated with demographic census data (173,672 inhabitants in four adjacent parishes) to estimate actual service capture and effective benefits. Total carbon stocks in PNC were estimated at 1.49 million Mg C, with volcanic Andisols acting as the primary reservoir (97.5% of the total stock). Habitat suitability was highly heterogeneous, with critical refuge patches clustered around the park’s lacustric network and stable microclimatic zones. Socio-ecological mapping revealed that the eastern boundary of the park represents the highest hotspot of effective benefit capture, directly supplying vital water regulation and cultural services to the peri-urban populations of Sayausí and Baños. These results demonstrate the utility of integrating standard IPCC guidelines with the ECOSER protocol, offering a repeatable and transparent framework to guide spatial conservation planning and sustainable land-use zoning in vulnerable high-altitude protected areas. Full article

Vulnerable coastal urban margins face overlapping pressures from erosion, climate change, and plastic-waste accumulation. This study presents a screening-level numerical assessment of a hollow modular unit made of a recycled polyethylene terephthalate (PET)–concrete composite, proposed for coastal slope protection and stabilisation in Chucuito, Callao, Peru. A limit-equilibrium baseline indicates that the unprotected slope is marginal to unstable under the site’s seismic demand, motivating the evaluation of a surface-protection concept through a parallel, one-way finite element analysis–computational fluid dynamics (FEA–CFD) framework applied at three slope angles (60°, 53°, 45°). The FEA structural-response screening indicates consistent trends across configurations under an equivalent impact load and the adopted basal restraint. For the hydraulic comparison, inlet velocities of 3, 5 and 7 m/s were anchored to the site-specific Delft3D inundation modelling (site maximum 5 m/s), with a conservative 10 m/s upper bound; relative to a rip-rap reference, the hollow configuration suggests midpoint run-up velocity reductions of approximately 52% at θ = 53° under the conservative scenario and ≈57% at 3 and 5 m/s, falling to ≈25% at 7 m/s with overlapping ranges and the simulated free surface exceeding the crest. The CFD free-surface elevations show order-of-magnitude consistency with an indicative EurOtop-based run-up benchmark used as a consistency check rather than as hydraulic validation. Independent of this hydraulic comparison, the hollow geometry saves ≈ 62% of the material volume relative to an equivalent solid concrete block, valorises ≈ 793 post-consumer PET bottles per unit at a 10% dosage, and suggests a 42–58% embodied-CO₂ reduction relative to the same solid-concrete reference, driven mainly by the hollow geometry rather than by the PET substitution itself. The results are internally consistent but not experimentally validated and are intended as a comparative baseline to guide subsequent experimental and field studies, in line with Sustainable Development Goals (SDG) 11, 12 and 13. Full article

Global food systems must balance productivity with environmental sustainability amid climate change, geopolitical shocks, and unevenly distributed natural resources. This study introduces the Food Supply Sustainability Index (FSSI), a transparent, composite measure of the sustainability of a nation’s food production including international trade, and future climate-driven trade dynamics, with a distance-to-target method. Using FAO and IFPRI data, the FSSI categorises countries into five sustainability classes across three pillars: carbon footprint, soil degradation, and water stress. The results show high-income countries produce food less sustainably, while low-income countries do so more sustainably yet are more vulnerable to climate change and trade disruptions. The FSSI therefore recognises that trade redistributes rather than removes environmental risk, creating a more evenly distributed yet persistent global vulnerability to shocks. Under future climate scenarios, the index identifies that sustainability worsens in poorer regions, especially Sub-Saharan Africa, exposing countries to food insecurity. By combining multiple environmental dimensions into a single metric, the FSSI enables countries to benchmark sustainability performance and identify priority areas for intervention. The FSSI supports policies such as aligning imports with sustainability criteria, diversifying suppliers toward lower-impact origins, and supporting sustainable intensification in low-income settings. The FSSI provides a replicable, policy-relevant tool to assess, compare, and communicate global food system sustainability. Full article

Western Kazakhstan is one of the most climate-vulnerable macro-regions in Central Asia. Intensifying aridification, acute water scarcity, and active land degradation are already undermining its ecosystems and an economy built heavily on oil and gas. Yet investment in the region is still driven by short-term priorities rather than a systematic assessment of actual need. A previous study by the authors identified a significant investment gap for sustainable development in the Aktobe region, and showed that this problem calls for comprehensive, comparative analyses rather than a localized one. This study aims to assess and compare investment needs for sustainable development across the four regions of Western Kazakhstan (Aktobe Atyrau, West Kazakhstan, and Mangystau) for 2021–2024, accounting for sustainability thresholds derived from optimal population density. An improved eco-economic methodology was applied, combining per capita investment need calculations with thresholds indicators of regional vulnerability and adaptive capacity, based on official statistical and sectoral data. The results revealed substantial inter-regional differences in investment needs, driven by differing economic specializations, and pointed to an urgent need for targeted investment in water infrastructure modernization, land degradation prevention, and renewable energy development. A new development paradigm is proposed that integrates sustainability thresholds into investment planning, with region-specific recommendations, offering a reproducible framework for arid regions worldwide. The study’s limitations include its short data coverage period (2021–2024), its reliance on official statistics, and the indirect nature of the population-density threshold. The proposed framework was tested for the hydrocarbon-dependent arid regions of Western Kazakhstan. Full article

Urban disaster resilience has become central to risk governance as climate change, compound hazards, and interdependent urban systems intensify pressures on cities. Publication-based reviews describe visible research outputs but reveal less about how research priorities are formulated and funded. This study examines 26 National Natural Science Foundation of China projects initiated during 2014–2024 and retrieved using three deliberately focused keywords: “urban disaster,” “urban resilience,” and “disaster resilience.” Descriptive statistics, text-assisted coding, temporal analysis, knowledge mapping, and a paradigm matrix were applied across six dimensions: hazard types, urban systems, resilience capacities, research methods, spatial scales, and paradigm orientations. Within this selected corpus, funding activity became concentrated after 2019, while research attention broadened from disaster prevention, risk identification, and vulnerability assessment toward resilience assessment, adaptive governance, community capacity, infrastructure networks, and coupled urban systems. Nevertheless, indicator frameworks, spatial evaluation, and model-based measurement remained dominant. Recovery trajectories, compound hazard interactions, social equity, and cross-system governance received comparatively limited attention. These findings indicate an agenda-level reorientation within the selected NSFC-funded corpus, rather than a universal transformation of Chinese urban disaster research. A more mature resilience agenda requires stronger integration of compound risks, recovery processes, equity, and coupled system governance. Full article

Assessing long-term hydroclimatic variability in central Mexico is essential to understand regional water availability and groundwater recharge for urban centers such as Querétaro. This study developed a multi-century winter–spring precipitation reconstruction for the Sierra Gorda Biosphere Reserve (SGBR) using ring width chronologies of Douglas-fir, Pseudotsuga menziesii (Mirb.) Franco. Standard dendrochronological techniques were applied to develop a 284-year master chronology (1731–2015). Following the accepted Subsample Signal Strength criterion (SSS ≥ 0.85) for chronology reliability, the reconstruction was restricted to the 1744–2015 period, yielding a statistically robust 271-year December–April precipitation record. A bootstrapped ordinary least-squares regression model relating tree-ring indices to instrumental December–April precipitation was calibrated and validated using split-sample cross-validation, explaining 46% of the instrumental precipitation variance (R² = 0.46) and yielding positive verification statistics (RE = 0.38–0.58; CE = 0.37–0.57). Spatial field correlations against gridded climate data (CRU TS4.08) confirmed a broad regional hydroclimatic signal centered over the Sierra Madre Oriental. Continuous wavelet transform (CWT), spectral analysis, superposed epoch analysis (SEA), and wavelet coherence (WTC) revealed significant interannual (2–8 years) and decadal (10–20 years) variability associated with large-scale ocean–atmosphere climate modes, including the El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and Tropical North Atlantic (TNA) index. The pronounced sensitivity of these conifer forests to pre-monsoonal moisture deficits highlights their vulnerability to projected warming and increasing spring evapotranspiration stress. Although the reconstruction is limited to pre-monsoonal (December–April) precipitation, it provides a robust centuries-long baseline for contextualizing regional hydroclimatic variability and supports water-resource management, groundwater conservation, and climate-adaptation strategies in central Mexico. Full article

Natural resource management under climate change generates interdependent economic, social, and environmental impacts. However, the scientific evidence remains fragmented. This fragmentation limits the design of integrated policies capable of reducing vulnerability and preventing the degradation of natural capital. The objective of this study is to analyze recent scientific literature to assess how natural resource management in the context of climate change simultaneously influences economic stability, social resilience, and environmental sustainability. To this end, a systematic review of literature published in indexed journals on environmental economics, climate change, and natural resource management was conducted, selecting quantitative and mixed-methods studies that examine economic, social, or biophysical impacts associated with environmental degradation, extractive dependence, and adaptation and mitigation strategies. The review integrated research at macroeconomic, microeconomic, and ecological scales, organized using comparative matrices that allowed for the identification of common patterns in indicators of economic loss, emissions, natural capital depreciation, and effects on social welfare. Subsequently, a comparative analysis was conducted to detect relationships between management failures, social vulnerability, and long-term costs, as well as to identify conceptual, methodological, and geographical gaps in the literature. The results show that the degradation of natural resources under climate change produces simultaneous effects on macroeconomic stability, household income, and ecosystem resilience, increasing the costs of inaction when policies are designed sectorally. The evidence synthesized in this review indicates that dependence on extractive activities, limited productive diversification, and institutional weaknesses are frequently associated with greater economic and social vulnerability, particularly in communities dependent on natural resources. The reviewed studies also suggest that adaptation and mitigation strategies that incorporate participatory governance, social capital, and natural capital conservation may contribute to strengthening resilience. However, given the heterogeneity of methodologies, spatial scales, and indicators among the analyzed studies, these findings should be interpreted as evidence of consistent patterns rather than causal relationships. Therefore, integrated approaches that consider economic, social, and environmental dimensions represent a promising direction for sustainable natural resource management under climate change, although further empirical research is required to evaluate their effectiveness across different contexts. Full article

Background: Hospitalization and incarceration are distinct institutional experiences, but both may involve reduced autonomy, externally regulated routines, uncertainty, restricted privacy, and disruption of meaningful social relationships. This systematic review examined shared and setting-specific psychological outcomes and associated factors across the two environments. Methods: PubMed, Scopus, Web of Science and the Cochrane Library were searched from database inception to 30 January 2026. Of 1149 identified records, 22 studies met the eligibility criteria. Methodological quality was assessed using the Mixed Methods Appraisal Tool 2018, and findings were synthesized narratively because substantial clinical and methodological heterogeneity precluded meta-analysis. Results: Ten studies examined incarcerated populations and twelve examined hospitalized populations. Across incarceration studies, reported estimates ranged from 14.9% to 72.6% for depressive symptoms or mood disorders and from 23.3% to 77.8% for anxiety symptoms or disorders. Across hospitalization studies, corresponding estimates ranged from 5.1% to 41.0% and from 5.8% to 60.0%, respectively. These ranges reflect heterogeneous screening instruments, diagnostic procedures, populations, and outcome definitions and were not statistically pooled. In both settings, poorer psychological outcomes were associated with reduced perceived control, disrupted routines, uncertainty, limited social support, and individual vulnerability. Setting-specific factors included prison climate, coping style, shame, and sentence-related circumstances in incarceration, and illness severity, functional impairment, prognostic uncertainty, isolation precautions, and prolonged or repeated admission in hospitalization. Findings concerning exposure duration were inconsistent in both settings. Conclusions: Hospitalization and incarceration should not be regarded as psychologically equivalent. Nevertheless, they may share experiential conditions associated with distress, particularly when autonomy, privacy, predictability, and social connectedness are reduced. Because the evidence was heterogeneous and predominantly observational, causal conclusions and direct quantitative comparisons cannot be made. Full article