Search Results (2,023)

In contemporary spatial planning, territorial resilience is rapidly gaining relevance, referring to a territory’s capacity to withstand, adapt to, recover from, and transform in response to environmental, social, and economic pressures. However, several constraints limit its operationalisation in planning. A key element to addressing this gap is to investigate where and which interventions are most urgently needed to tackle the impact of hazards on territories. This can be achieved by understanding and localising the vulnerabilities of territorial systems, thereby enabling the definition of appropriate mitigation and adaptation measures. This paper presents the application of R3C-GeoResilience, an open-source GIS tool and its methodological framework, which allows mapping territorial vulnerabilities across different geographical contexts and spatial scales. The methodology is applied to the Italian case of the Union of Bassa Romagna (UBR), aiming to build capacity for local practitioners to implement resilience thinking in decision-making processes. Findings underscore the potential of R3C-GeoResilience to enhance evidence-based planning and policymaking, supporting adaptive and transformative strategies to address territorial vulnerabilities. The application of the research demonstrates the replicability and adaptability of the methodological framework for integrating participatory vulnerability mapping into local governance and urban planning strategies, thereby enhancing the resilience of territories. Full article

With the global energy transition and decarbonization goals, tower-type solar thermal power generation is increasingly important for dispatchable clean energy due to its high efficiency, thermal storage capacity, and regulation performance. However, current research focuses on ideal conditions, ignoring real geographical constraints on heliostat layout and environmental impacts on receiver performance. More practical scene modeling and performance evaluation methods are urgently needed. To address these issues, we propose a heliostat field simulation algorithm based on heat loss mechanisms and real site characteristics. The algorithm includes optical performance evaluation (cosine efficiency, shading, truncation, atmospheric transmittance) and heat loss mechanisms (radiation, convection, conduction) for realistic net heat output estimation. Experiments revealed the following: (1) higher central towers improve optical efficiency by increasing solar elevation angle; (2) radiation losses dominate at high power and tower height, while convection losses dominate at low power and tower height. Using the Economic-Integrated Score (EIS) optimization algorithm, we achieved optimal tower and receiver configuration with 40.22% average improvement over other configurations (maximum 3.9× improvement). This provides a scientific design basis for improving tower-type solar thermal systems’ adaptability and economy in different geographical environments. Full article

Ochetobius elongatus, a critically endangered (CR) fish species of the Yangtze River Basin in China, has experienced a severe decline in its wild population. Understanding its mechanisms of phenotypic variation is essential for developing effective conservation and restoration strategies. Using geometric morphometrics based on 14 landmarks, we examined the phenotypic difference among five populations from the mainstem, the tributary, and the river-connected lakes of the middle Yangtze River. The results showed that significant phenotypic divergence was detected between river and lake populations. River individuals exhibited a more elongated body, smaller head, inferior mouth position, larger operculum, and narrower caudal peduncle, whereas lake individuals showed a deeper body, and anterior shift in the origin of pelvic fin. The first canonical variable effectively distinguished river and lake populations, with the accuracy of both original and cross-validation classification exceeding 90%, indicating that habitat heterogeneity was the primary driver of phenotypic differentiation. No significant correlation was found between morphological distance and geographical distance. Water temperature, flow velocity, water depth, and food abundance significantly influenced phenotypic variation, but their individual effects were limited, which suggested that environmental shaping of morphology depended more on synergistic effects. Our findings provide important insights into the adaptive evolution of this critically endangered species and offer a scientific basis for conservation efforts. Full article

Mountain regions are increasingly affected by the interplay of climate change, infrastructure stress, and evolving socio-ecological systems, intensifying pressure on both water and energy systems. This systematic review investigates how recent scientific literature addresses the management and integration of water and energy systems in mountainous contexts. Following PRISMA guidelines, 88 peer-reviewed studies from 2022 to 2025 were selected through structured database queries and thematic screening. Two key imbalances emerge. First, a geographical imbalance is evident: while the majority of studies come from Asia, Europe shows a strong record of applied efforts, the Americas are moderately represented, and research from Africa remains scarce. Second, a thematic imbalance: water management research is conceptually and methodologically mature, while energy-focused studies remain limited in number and scope. Efforts toward integrated water–energy management are emerging but are mostly confined to pilot projects or modelling exercises, often lacking systemic framing and institutional support. From these findings, three priority directions are identified: advancing adaptive co-design approaches that link water supply, energy storage, ecological flows, and human demand; harmonizing methods, metrics and cross-regional benchmarks to enhance comparability and transferability; strengthening social and institutional pathways to foster resilient, adaptive water–energy systems in mountain environments. Full article

The rapid rise of e-commerce is intensifying pressure on last-mile delivery networks, making the strategic placement of parcel lockers an urgent urban challenge. In this work, we adapt multilayer two-mode Social Network Analysis to the parcel-locker siting problem, modeling city-scale systems as bipartite networks linking spatially resolved demand zones to locker locations using only open-source demographic and geographic data. We introduce two new Social Network Analysis metrics, Dual centrality and Coverage centrality, designed to identify both structurally critical and highly accessible lockers within the network. Applying our framework to Milan, Rome, and Naples, we find that conventional coverage-based strategies successfully maximize immediate service reach, but tend to prioritize redundant hubs. In contrast, Dual centrality reveals a distinct set of lockers whose presence is essential for maintaining overall connectivity and resilience, often acting as hidden bridges between user communities. Comparative analysis with state-of-the-art multi-criteria optimization baselines confirms that our network-centric metrics deliver complementary, and in some cases better, guidance for robust locker placement. Our results show that a network-analytic lens yields actionable guidance for resilient last-mile locker siting. The method is reproducible from open data (potential-access weights) and plug-in compatible with observed assignments. Importantly, the path-based results (Coverage centrality) are adjacency-driven and thus largely insensitive to volumetric weights. Full article

In the Red List of Threatened Species, released by International Union for Conservation of Nature (IUCN), Paphiopedilum helenae has been classified as an endangered species. It exhibits exceptional decorative value and germplasm resource potential. To elucidate the ecological adaptation of this species and the characteristics of its rhizosphere microbiome, bacterial 16S rRNA and fungal ITS sequences of three wild populations of P. helenae were investigated using Illumina high-throughput sequencing technology and the microbial community structures and diversities were systematically compared. These three populations were spanned across distinct geographical locations in Longzhou County, Guangxi. The results showed that the bacterial community in the rhizosphere soil of P. helenae comprised 31 phyla, primarily including Actinobacteriota, Proteobacteria, Chloroflexi and Acidobacteriota. On the other hand, the fungal community consisted of 10 phyla, dominated by Ascomycota and Basidiomycota. There were significant differences in the diversity of rhizosphere microbes across different populations of P. helenae. The LG population had the highest bacterial richness (Chao index: 2912.71 ± 131.73; p < 0.05) and diversity (Shannon index: 6.40 ± 0.06; p < 0.01), while the MQ population had the lowest diversity (Shannon index: 3.47 ± 0.24; p < 0.01) of fungi. The degree of variation in fungal β-diversity was significantly higher than that of bacteria. Soil organic matter (SOM) and available nitrogen (AN) contents were the core factors shaping the microbial communities in the rhizosphere soil of P. helenae, which jointly explained 49.87% and 16.39% of variations in the bacterial and fungal communities. Furthermore, population-specific enrichment of functionally significant microorganisms was evident. Population MQ was enriched with plant growth-promoting and stress-resistant fungi, such as Geminibasidium, Trichoderma, etc. Population LG was enriched with oligotrophic bacteria (e.g., Patescibacteria), while population SL exhibited an overwhelming dominance of Ascomycota (93.25%) and enrichment of pathogenic fungal genus Nigrospora. This research revealed the variations in the functional adaptation strategy of P. helenae and the microbial communities in the rhizosphere soils across different geographical locations. This suggests that microbial community imbalance in rhizosphere soil may be one of the factors leading to the endangerment of this plant species. The study proposed a differentiated protection strategy for endangered plant species based on microbial resources. The results provide a theoretical basis for development of a “microorganism-assisted protection” strategy for ecological restoration and sustainable utilization of endangered orchid plants. Full article

Mountain settlements represent culturally rich but environmentally fragile landscapes, shaped by enduring processes of ecological adaptation and human resilience. In western Sichuan, Jiarong Tibetan villages, with their distinctive integration of defensive stone towers and settlements, embody this coupling of culture and the environment. We hypothesize that settlement cores in these villages were shaped by natural environmental factors, with subsequent expansion reinforced by the cultural significance of towers. To test this, we applied a micro-scale spatial–environmental framework to four sample villages in Suopo Township, Danba County. High-resolution World Imagery (Esri, 0.5–1 m, 2022–2023) was classified via a Random Forest algorithm to generate detailed land-use maps, and a 100 × 100 m fishnet grid extracted topographic metrics (elevation, slope, aspect) and accessibility measures (distances to streams, roads, towers). Geographically weighted regression (GWR) was then used to examine how slope, elevation, aspect, proximity to water and roads, and tower distribution affect settlement patterns. The results show built-up density peaks on southeast-facing slopes of 15–30°, at altitudes of 2600–2800 m, and within 50–500 m of streams, co-locating with historic watchtower sites. Based on these findings, we propose four zoning strategies—a Core Protected Zone, a Construction And Development Zone, an Ecological Conservation Zone, and an Industry Development Zone—to balance preservation with growth. The resulting policy recommendations offer actionable guidance for sustaining traditional settlements in complex mountain environments. Full article

Background/Objectives: The COVID-19 (Coronavirus Disease, 2019) pandemic affected all countries in a variety of ways, and forced policymakers to adapt national health infrastructure. In this context, the strategic adaptation and policy evolution of small island states are understudied. Therefore, the objective of this study was to quantitatively analyse the relationship between confirmed COVID-19 cases and health policy decisions in Northern Cyprus. We also examined the shifting management strategies employed during the pandemic using a replicable statistical analysis framework. Methods: In this mixed-methods study, we used systematic thematic analysis to categorise official policy decisions from March 2020 to December 2022. Yearly linear regression models using SPSS and Python correlated the monthly number of decisions with the number of confirmed COVID-19 cases. The analyses included R² values, p-values, and visualisations with 95% confidence intervals. Results: The findings of this study highlight a three-phase strategic period. In 2020, the results (R² = 0.03, p = 0.63) showed no significant relationship, indicating initial uncertainty. The results (R² = 0.60, p = 0.003) indicate a strong negative correlation in 2021, which reflects the consistency of the proactive suppression strategies adopted. Conversely, for 2022, the results (R² = 0.79, p < 0.001) show a strong positive correlation representing the shift to a reactive mitigation strategy, in which the government responded based on case peaks. Conclusions: This study’s primary finding is that strategic agility was key to managing the pandemic. For small island states in particular, the effectiveness of geographic advantages like border control depends on a coherent strategy that transcends initial uncertainty. Our data-driven framework provides a tool for analysing this strategic evolution and guiding responses to future pandemics. Full article

The instance segmentation of power distribution equipment in infrared images is a prerequisite for determining its overheating fault, which is crucial for urban power grids. Due to the specific characteristics of power distribution equipment, the objects are generally characterized by small scale and complex structure. Existing methods typically use a backbone network to extract features from infrared images. However, the inherent down-sampling operations lead to information loss of objects. The content regions of small-scale objects are compressed, and the edge regions of complex-structured objects are fragmented. In this paper, (1) the first unmanned aerial vehicle-based infrared dataset PDI for power distribution inspection is constructed with 16,596 images, 126,570 instances, and 7 categories of power equipment. It has the advantages of large data volume, rich geographic scenarios, and diverse object patterns, as well as challenges of distribution imbalance, category imbalance, and scale imbalance of objects. (2) A reconstruction error (RE)-guided instance segmentation framework, coupled with an object reconstruction decoder (ORD) and a difference feature enhancement (DFE) module, is proposed. The former reconstructs the objects, where the reconstruction result indicates the position and degree of information loss of the objects. Therefore, the difference map between the reconstruction result and the input image effectively replays the object features. The latter adaptively compensates for object features by global fusion between the difference features and backbone features, thereby enhancing the spatial representation of objects. Extensive experiments on the constructed and publicly available datasets demonstrate the strong generalization, superiority, and versatility of the proposed framework. Full article

This study examined the habitat suitability of Kentucky bluegrass (Poa pratensis L.) in Iran’s Fars province, a region characterized by diverse climatic conditions and significant ecological challenges. Utilizing a multi-technique approach that included species distribution models (SDMs) based on machine learning algorithms, geographic information systems (GIS), and remote sensing, we analyzed environmental factors such as climate variables, soil properties, and water availability to understand their influence on habitat suitability. The results indicated that Kentucky bluegrass shows a strong preference for areas near water sources, and its distribution is significantly affected by soil salinity and texture. Among the models tested, Random Forest (RF) and Support Vector Machines (SVMs) demonstrated the highest predictive accuracy. Based on the RF model, the most suitable habitats were identified in the counties of Sepidan, Beyza, Bavanat, Pasargad, and Abadeh. At the same time, areas with lower suitability included Eqlid, Marvdasht, Zarghan, and Arsanjan. Although this study primarily focused on current distribution patterns, the findings provide important insights into the ecological preferences and adaptive capacities of Kentucky bluegrass. These insights are essential for the development of targeted conservation strategies in transitional climate zones. Future studies are recommended to explore the species’ response to future climate scenarios, enhancing its resilience against global climate change. Full article

Under the dual backdrop of the Healthy China strategy and the concept of sustainable development, optimizing the spatial layout of primary healthcare facilities is important for fairly distributing healthcare resources and strengthening the resilience of the public health system in a sustainable way. This study introduces an innovative 3D spatial resilience evaluation framework, covering transmission (service accessibility), diversity (facility type matching), and stability (supply demand balance). Unlike traditional accessibility studies, the concept of “resilience” here highlights a system’s ability to adapt to sudden public health events through spatial reorganization, contrasting sharply with vulnerable systems that lack resilience. Method-wise, the study uses an improved Gaussian two-step floating catchment area method (Ga2SFCA) to measure spatial accessibility, applies a geographically weighted regression model (GWR) to analyze spatial heterogeneity factors, combines network analysis tools to assess service coverage efficiency, and uses spatial overlay analysis to identify areas with supply demand imbalances. Harbin is located in northeastern China and is the capital of Heilongjiang Province. Since Harbin is a typical central city in the northeast region, with a large population and clear regional differences, it was chosen as the case study. The case study in Harbin’s main urban area shows clear spatial differences in medical accessibility. Daoli, Nangang, and Xiangfang form a highly accessible cluster, while Songbei and Daowai show clear service gaps. The GWR model reveals that population density and facility density are key factors driving differences in service accessibility. LISA cluster analysis identifies two typical hot spots with supply demand imbalances: northern Xiangfang and southern Songbei. Finally, based on these findings, recommendations are made to increase appropriate-level medical facilities, offering useful insights for fine-tuning the spatial layout of basic healthcare facilities in similar large cities. Full article

The highly fatal rabbit hemorrhagic disease (RHD) that first emerged in 1984 in China has spread worldwide and affects both domestic and wild rabbits. The disease was originally caused by RHD virus (Lagovirus europaeus, L.europaeus) of GI.1 genotype, but over the years, two further pathogenic forms, known as the antigenic and genetic variant RHDVa (GI.1a) and RHDV2 (genotype GI.2), have been identified. RHD was first reported in Poland in 1988, when two RHDV strains were isolated, currently classified as GI.1c, while RHDVa and RHDV2 emerged in 2003 and 2016, respectively. In this study, using virological and molecular methods, we characterized five new RHDV strains belonging to GI.1 (RHDV)/GI.1a (RHDVa) and GI.2 (RHDV2) genotypes isolated in Poland in 2020–2022, in domestic rabbits from backyard farm and companion animals. We showed that two strains of L. europaeus (NRU 2020 and LIB 2020) from 2020 in the phylogenies of nonstructural proteins (NSP) and structural capsid protein (SP-VP60) clustered in a homogeneous GI.1a variant group. We stated that three strains of L. europaeus from 2020 to 2022 (KOB 2020, ZWO 2021, WAE 2022) in the VP60 phylogeny were positioned in the GI.2 (RHDV2) genotype, while in the NSP phylogeny, they are genetically related to recombinants with the GI.3/GI.2 genotype. Unexpectedly, in two RHD cases identified in the same small geographical area of south-eastern Poland (Libusza and Kobylanka), the close coexistence of RHDVa (LIB2020) and RHDV2 (KOB2020) strains capable of causing independent infections at the same time was found. This leads to the conclusion that the close natural coexistence of RHDV strains belonging to different genotypes does not necessarily have to directly lead to the emergence of new genetic or antigenic variants, which confirms the distinctness of both genetic forms and indicates different evolutionary paths leading to the best possible adaptation to the host. Full article

Eyespots are functionally complex and highly variable elements of butterfly wing patterns. The Meadow Brown, Maniola jurtina, is a classic model species studied for variation in eyespots as an index of evolutionary divergence and adaptation. However, the role of fine-scale ecogeographic conditions on eyespot variation remains poorly understood. In this study, we examined hindwing eyespot number, distribution, and combination patterns in male M. jurtina across climatically and topographically diverse north-western Balkans. Compared to the species average, males in this region displayed greater spottiness and phenotypic diversity. While the typical two-spot phenotype was dominant and stable, in some populations, three-spotted and even four-spotted males occurred at similar frequencies. Rare six-spotted individuals were recorded only at mountain localities above 1200 m. Geographic and climatic factors together influenced this variation: higher altitudes and cooler, thermally stable environments promoted increased eyespot number and greater phenotypic plasticity than warmer, more variable environments. This pattern contrasts with large-scale latitudinal trends previously described for the species, emphasizing the importance of local climatic heterogeneity. Our findings suggest the north-western Balkans as a possible transitional zone where environmental complexity promotes elevated eyespot variability, contributing to the understanding of adaptive morphological plasticity in M. jurtina. Full article

Endophytic bacteria play an important role in the growth, stress tolerance, and metabolic function of salt-tolerant peanuts, yet their community assembly across different saline–alkali soils and plant organs remains poorly characterized. In this study, the V3–V4 variable region of the endophytic bacteria 16S rRNA gene in three organs (roots, leaves, and pods) of high-oleic-acid peanut variety Huayu9118 from three saline–alkali locations (Xinjiang, Jilin, and Shandong, China) was analyzed by high-throughput sequencing. A total of 1,360,313 effective sequences yielded 19,449 amplicon sequence variants (ASVs), with Proteobacteria (45.86–84.62%), Bacteroidota (6.52–13.90%), and Actinobacteriota (3.97–10.87%) dominating all samples. Niche strongly influenced microbial diversity: the roots exhibited the highest level of richness (Chao 1/ACE indices), while the leaves showed the greatest diversity (Shannon/Simpson indices) in XJ samples. Significant compositional differences were observed between aerial (leaves) and underground (roots/pods) organs. Geographic location also markedly shaped endophytic communities, with stronger effects in roots and pods than in leaves—a pattern supported by PCoA combined with ANOSIM (R (roots) = 1, R (pods) = 0.874, R (leaves) = 0.336, respectively, p < 0.001). Saline–alkali adaptation led to a marked enrichment of Novosphingobium in roots and pods and of Halomonas in leaves compared to non-saline–alkali-grown peanuts. Furthermore, the endophytic communities within the same organ type varied significantly across the three saline–alkali sites. Redundancy analysis (RDA) identified the key environmental factors shaping bacterial community composition in the root samples from each location: available phosphorus (AP) and sulfate (SO₄²⁻) were the strongest predictors in XJ; available potassium (AK) and chloride (Cl⁻) in DY; and hydrolyzed nitrogen (HN), pH, soil organic matter (SOM), and bicarbonate (HCO₃⁻) in JL. These findings demonstrate that niches and geographical conditions determined the composition and relative abundance of endophytic bacteria in salt-tolerant peanuts, providing new insights into microbial ecological adaptation in saline–alkali ecosystems. Full article

China’s rural revitalization strategy has entered a new stage of development, in which optimizing the layout of rural settlements constitutes both a critical component and an urgent task for promoting integrated urban–rural development. Important ecological function areas play a vital role in maintaining ecological security; however, research focusing on the evaluation and optimization of rural settlement suitability within these regions remains limited, thereby constraining their sustainable development. Accordingly, this paper selects Shiyan City, situated within the core water source area of China’s South-to-North Water Diversion Project, as a case study. From an ecological perspective, a suitability evaluation system for rural settlements is developed, specifically tailored to important ecological function areas. This system integrates ecological factors including geological hazards, vegetation coverage, soil and water conservation, and soil erosion. Utilizing GIS spatial analysis and the minimum cumulative resistance model, the study assesses the suitability of rural settlements within these important ecological function areas. Furthermore, it proposes corresponding optimization types and strategies for rural settlements in such areas. The findings indicate the following: (1) The rural settlements in the study area demonstrate a “large dispersed settlements and small clustered settlements” distribution pattern, exhibiting an overall high-density agglomeration, though their internal layout remains fragmented and disordered due to geographical and ecological constraints. (2) The spatial comprehensive resistance values in the study area exhibit significant heterogeneity, with a general pattern of lower values in the north and higher values in the south. The region was categorized into five suitability levels: high yield, highly suitable, generally suitable, less suitable and unsuitable. The highly suitable areas, despite their limited spatial extent, support the highest density of rural settlements. In contrast, unsuitable areas occupy a substantially larger proportion of the territory, reaching 46.83%. These areas are strongly constrained by topographic and ecological factors, limiting their potential for development, and the spatial layout of villages requires further optimization, with emphasis placed on ecological conservation and adaptive sustainability. (3) Rural settlements are categorized into four optimized types: Urban–rural integration settlements, primarily located in high yield areas, are incorporated into urban development plans after optimization. Adjusted and improved settlements, mainly in highly suitable areas, enhance service quality and stimulate economic vitality post-optimization. Relocation and renovation settlements, including those in generally suitable and less suitable areas, achieve concentrated living and improved ecological livability after optimization. Restricted development settlements, predominantly in unsuitable areas, focus on ecological conservation and regional ecological security post-optimization. This study integrates ecological function protection factors with spatial optimization zoning for rural settlements in the study area, providing scientific reference for enhancing residential safety and ecological security for rural residents in important ecological function areas. Full article