Search Results (5,579)

Functional trait plasticity enables invasive plant species to establish and persist across diverse environmental conditions. Following the extensive habitat disturbance caused by the 2010 floods in Khyber Pakhtunkhwa, Verbesina encelioides rapidly spread into disturbed and natural habitats. This study evaluated the phenotypic plasticity and biomass allocation traits of Verbesina encelioides across five contrasting habitats (i.e., cropland, roadside, riverside, urban, and abandoned land). Habitat differences were assessed using analysis of variance with Tukey’s HSD post hoc test, while multivariate analysis was used to examine relationships among functional traits, environmental variables, and habitats. Log-transformed data were used for linear regression analyses to satisfy normality assumptions. Plant functional traits varied significantly among habitats, demonstrating substantial phenotypic plasticity. Riverside vegetation had high functional trait plasticity followed by abandoned habitats. In contrast, riverside populations had fewer branches (14.3 ± 1.4), leaves (184.7 ± 10), lower leaf area (5360 ± 77 cm²), and reduced inflorescence biomass (8.61 ± 2.1 g) than abandoned-land populations. Cropland plants were taller (106 ± 3 cm) with heavier seeds (0.30 ± 0.04 g; p < 0.05), whereas roadside plants had smaller leaves (6.1 ± 0.3 cm) but produced more flowers (38.4 ± 6.2; p < 0.001). Biomass allocation remained relatively stable across habitats (p > 0.05), with greater investment in aboveground than belowground structures. Soil texture, organic matter, temperature, and precipitation were the principal environmental variables associated with trait variation, indicating that local environmental conditions strongly influence plant performance (p < 0.05). PCA revealed that seed traits dominated the first axis and were associated with cropland and riversides. Redundancy analysis indicated that soil properties (sand, silt, pH, EC) and climatic factors (precipitation, temperature) significantly influenced trait distribution. Hierarchical cluster analysis shows that riverside was distinct from other clusters both in functional traits and environmental variables. Inter-trait correlation revealed a significant relationship between leaf and seed traits. Overall, these findings reveal that V. encelioides adjusts its growth and reproductive traits according to habitat conditions. Greater seed weight in croplands may enhance seedling establishment under competitive conditions, whereas increased flower production in disturbed roadside habitats may promote dispersal and reproductive success of the plant. The strong functional trait plasticity of V. encelioides across different habitats highlights its potential to persist under habitat disturbance and changing environmental conditions, therefore posing risk to native plant communities and ecosystem structure. These findings support the need for habitat-based monitoring, protection of native flora and restoration of disturbed areas as part of sustainable land and biodiversity management. Full article

The timberline region of the Western Himalaya is a crucial ecological transition area highly sensitive to climate changes, which significantly influence vegetation patterns, soil formation, and carbon dynamics. This study aimed to investigate the spatial and altitudinal changes in soil organic carbon (SOC) across different topographic orientations and to evaluate machine-learning models for spatial SOC prediction in the timberline ecotone (2100–3300 m) of the Kedarnath Wildlife Sanctuary. Through systematic random sampling across 100 m elevation bands, composite soil samples were collected from three aspects (North-East, South-West, and North-West) at two depths (0–15 cm and 15–30 cm) and analyzed alongside topographic, spectral, and climatic covariates. Results indicated that SOC trends varied significantly by aspect; the North-East aspect exhibited a considerable increase in SOC with elevation, while the North-West and South-West sides responded differently. Furthermore, Digital Soil Mapping using the Random Forest (RF) model outperformed Support Vector Machine and XGBoost, explaining 62% of surface and 74% of subsurface SOC variability. In conclusion, aspect-induced microclimatic gradients play a major role in controlling soil characteristics near the Himalayan timberline, and machine-learning models like RF can successfully capture these complex spatial patterns. Consequently, it is recommended that the established baseline SOC maps be utilized as reference points for future climate-change monitoring, carbon accounting, and directing conservation strategies in high-altitude forests. Full article

Phyllostachys edulis (Moso bamboo) is a subtropical bamboo species endemic to China and holds substantial economic and ecological value. Ongoing climate change is reshaping the geographic distribution of its suitable habitats. To reveal these climate-driven dynamics, we calibrated the maximum entropy (MaxEnt) species distribution model using the ENMeval R package version 4.5.2 and evaluated model robustness via spatially independent block cross-validation. We identified nine critical environmental predictors to model spatiotemporal variations in suitable habitats for Moso bamboo, examining both present-day climate and four future periods under four Shared Socioeconomic Pathway (SSP) scenarios. Model performance was optimized at regularization multiplier (RM) of 1.5 with the feature class combination LQHPT, yielding a spatial validation AUC of 0.9104 and robust predictive capacity. Environmental controls were dominated by mean temperature of the coldest quarter (bio11, 63.9% relative contribution) and precipitation of the driest quarter (bio17, 31.2%), while soil clay and organic carbon content modulated suitability at local scales. Under current conditions, the total suitable habitat area encompasses approximately 218.88 × 10⁴ km², with the majority distributed throughout the subtropical zone of southeastern China. Under nearly all future scenarios, high-suitability habitats showed a general contracting trend of 20.94%–95.29% relative to the current baseline, while moderate-suitability habitats exhibited a fluctuating expansion trend, reaching a peak increase of 47.90% in the 2030s under SSP585, but contracted by 18.65% in the 2090s. Meanwhile, habitat centroids underwent small-scale oscillatory shifts in multiple directions and remained entirely within Hunan Province across all periods. MESS analysis confirmed that 90.60%–99.82% of China’s land area fell within climate-analogous ranges, indicating low extrapolation risk for core habitat projections. Core climate refugia with high cross-scenario stability were primarily concentrated in the traditional bamboo-producing regions of southeastern China. This study provides a scientific basis for the sustainable management of Moso bamboo resources, biodiversity conservation, and ecological risk prevention in the context of ongoing climate change. Full article

Protected areas increasingly reshape land use rules, resource accessibility, and livelihood opportunities for adjacent communities. However, household livelihood resilience under protected-area land use restrictions is rarely explained by a single factor; rather, it is better understood through the combined configurations of spatial constraint intensity, natural-capital dependence, social capital, and alternative livelihood capacity. Taking households in five sampled Yi, Qiang, and Hui villages around the Giant Panda National Park in China as empirical cases, this study examines the configurational relationships through which land use restrictions are associated with household livelihood resilience. Based on survey data from 200 households in five sampled Yi, Qiang, and Hui villages, supplemented by participatory rural appraisal and semi-structured interviews, we apply fuzzy-set qualitative comparative analysis to identify configurations associated with both high and low livelihood resilience. The results identify two robust high-resilience pathways: an opportunity conversion pathway characterized by weak spatial constraints and strong alternative livelihood capacity, and a dual-capacity support pathway in which social capital and alternative livelihood capacity jointly support livelihood resilience under natural-capital dependence. A third, less robust configuration is interpreted as a supplementary low-exposure livelihood stability configuration rather than active adaptive resilience. The analysis of low livelihood resilience further identifies a constraint-dependent vulnerability pathway characterized by strong spatial constraints, high natural-capital dependence, and the absence of alternative livelihood capacity. These pathways are closely associated with community-specific spatial locations and livelihood traditions. Rather than treating ethnicity as an intrinsic causal factor, this study interprets it as a socially embedded expression of spatial location, livelihood traditions, and informal institutional resources. The findings further suggest that the role of social capital depends not only on its volume but also on whether it can be converted into governance and livelihood-support functions. This study contributes to protected-area livelihood research by clarifying the configurational relationships through which land use restrictions are associated with household livelihood resilience, and it provides implications for differentiated governance and sustainable land management in national park regions. Full article

Biotope mapping provides an essential spatial framework for biodiversity conservation, ecosystem management, and sustainable landscape planning. However, a standardized and transferable GIS-based methodological framework for biotope identification and mapping is still lacking in Türkiye, limiting the systematic integration of biodiversity considerations into spatial planning processes. This study develops an integrated GIS-based biotope mapping framework for Çınarcık District, Yalova Province, Türkiye, integrating Digital Elevation Model (DEM), CORINE Land Cover 2018, Forest Management Plans, stand characteristics, vegetation, floristic, and hydrological data through spatial analyses. Additionally, 30 national and 15 international studies were systematically reviewed to identify the common indicators, data sources, and methodological components used in biotope mapping and to establish the proposed GIS-based framework. The proposed approach identified four main biotope groups (forest, aquatic, agricultural, and urban). Based on ecological similarity and growing environment characteristics, 12 sub-biotope types were identified within the forest biotopes. Forest biotopes were the dominant ecological units, mainly characterized by broadleaved communities dominated by Fagus orientalis, Castanea sativa, Tilia tomentosa, and Quercus petraea. A total of 72 forest stand types were identified, with Fagus orientalis-dominated forests in plateau environments representing the largest sub-biotope type (36.40%). The proposed framework provides a repeatable and transferable, inventory-based methodology that can serve as a preliminary decision-support tool for biodiversity assessment, conservation planning, and sustainable landscape management in forested landscapes with similar ecological characteristics, pending future field-based validation. Full article

Sebastes schlegelii is a commercially significant species in the northern Yellow Sea. Recently, Sebastes schlegelii has shown a reduced stock density and a shift toward smaller body sizes in the northern Yellow Sea area off Liaoning Province. To comprehend the population dynamics and to formulate management tactics, we established a mathematical formula describing the length–weight relationship, as well as the corresponding growth equations for the body length and body weight. The biomass of Sebastes schlegelii in the northern Yellow Sea area off Liaoning Province was evaluated using biological survey data from 2019 to 2022. The findings reveal that the length–weight formula is expressed as W = 4.98 × 10⁻⁵L^2.8878 (R² = 0.9108), with L_∞ = 407.6 mm, W_∞ = 1717.04 g, K = 0.21 a⁻¹, and t₀ = −0.65 a. The critical age was 3.34 years, and the stock biomass was 13,141.35 tonnes. The current exploitation rate of this resource is below the maximum yield, indicating sustainable utilization. A fishing closure period from April to June is considered suitable. A minimum landing size of 240.48 mm is recommended for Sebastes schlegelii. Full article

Páramo ecosystems are among the most biodiverse and hydrologically critical landscapes on Earth, yet their long-term sustainability is increasingly threatened by climate-driven wildfires. Vegetation Cover Fires (VCFs) in these high-altitude environments degrade carbon stocks, disrupt freshwater regulation, and undermine biodiversity conservation goals central to the UN Sustainable Development Goals (SDGs 13, 15, and 6). Between 2001 and 2023, 128 fire events consumed approximately 815 ha in the Sumapaz locality (the world’s largest continuous páramo), representing 64.9% of all fires recorded across Bogotá’s 20 localities. Despite this disproportionate ecological and social impact, no spatially explicit, operational risk management framework has been available for the region, representing a critical sustainability governance gap. This study addresses that gap by proposing an integrated climate-adaptive risk assessment and management strategy based on (i) the Canadian Forest Fire Danger Rating System Fire Weather Index (FWI), derived from ERA5 reanalysis climate data; (ii) spatial and temporal hotspot analysis of MODIS FIRMS active fire detections; and (iii) IDEAM’s multi-component vulnerability and threat scoring protocol. Spatial data were processed using ArcGIS, and FWI sub-indices were computed for each month of the 2001–2023 period. The FWI averaged 0.78 (low danger) across the study period yet peaked at 13.7 in February 2010 (moderate-to-high danger), consistent with the year of highest recorded fire activity (19 events). High- and very high-risk areas (3.70% combined) coincide with slopes >25%, the presence of the invasive and pyrogenic Ulex europaeus, and proximity to populated and agricultural lands. This study concludes with a three-pillar risk management framework—risk knowledge, risk reduction, and disaster management—providing spatially targeted, operationally viable strategies for local and institutional actors that directly support the sustainable conservation of páramo ecosystem services (water supply, carbon sequestration, biodiversity). The framework is designed to be updatable on a monthly basis using freely available ERA5 data, enabling continuous adaptive governance of wildfire risk as a contribution to long-term territorial sustainability. Limitations regarding MODIS detection uncertainty, ERA5 spatial resolution in complex terrain, and the need for probabilistic modeling are explicitly acknowledged. Full article

The Berca–Arbănași region of Buzău County (Romania) is of exceptional geochemical interest due to diapiric structures, active mud volcanoes, and historical subsurface hydrocarbon deposits. This study presents the first comprehensive geochemical assessment of surface soils from the Berca–Arbănași Subcarpathian zone, based on the analysis of 27 soil samples collected along three north–south transects and the determination of 12 potentially toxic elements (As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, V, Zn) using aqua regia digestion and ICP-MS. The local geochemical background was calculated using the iterative median ± 2MAD method. Twelve pollution and ecological risk indices were computed: the Pollution Index (PI), Contamination Factor (CF), Geoaccumulation Index (Igeo), Enrichment Factor (EF), Pollution Load Index (PLI), Modified Degree of Contamination (mCd), Nemerow Integrated Pollution Index (PINemerow), Ecological Risk Factor (E_rⁱ), Ecological Risk Index (RI), Mean Effect Range-Median Quotient (MERMQ), Degree of contamination (Cdeg), and the V/Ni petroleum origin indicator. Results show that 66.7% of samples are classified as polluted (PLI ≥ 1; mean = 1.102), with moderate enrichment in Cd, Cu, Hg, Pb, and Zn, attributable to diffuse anthropogenic sources. The ecological risk index (RI) remains low across all samples (mean = 35.96; all < 150), indicating that, despite moderate pollution, ecological risk is currently low. The V/Ni ratio (0.391–0.884, mean = 0.608) is below 1.0 for all samples, indicating a lithogenic (not petroleum) origin of vanadium and nickel and confirming a negligible geochemical impact of mud volcanoes and hydrocarbon extraction activities in the area at the sampled locations. The study establishes baseline geochemical reference values for the Berca–Arbănași area and provides data for sustainable land management, environmental monitoring, and evidence-based policymaking. These results directly support the objectives of the EU Soil Strategy 2030 and align with the United Nations Sustainable Development Goals on food security (SDG 2), good health and well-being (SDG 3), and life on land (SDG 15). Full article

Land-use change affects regional carbon accounting through ecological conversion and the concentration of energy-intensive economic activity. We combined 30 m China Land Cover Dataset maps for 2010, 2015, 2020, and 2025 with provincial socioeconomic and energy statistics to quantify land-use transitions and carbon emissions across nine Yellow River Basin provinces. Construction-land-associated emissions were decomposed using the logarithmic mean Divisia index, factors associated with land expansion were examined using random-forest models, and three 2030 scenarios were evaluated. Construction land expanded by 38.87% from 2010 to 2025, with 71.33% of new construction land converted from cropland and 17.75% from grassland. Net land-use carbon emissions increased by 69.82%, from 1139.06 to 1934.33 million t C. Economic-output density contributed 1144.84 million t C to the increase in construction-land-associated emissions, compared with 576.11 million t C from land expansion, whereas declining energy intensity offset 922.72 million t C. Projected 2030 emissions ranged from 2124.72 million t C under ecological protection to 2866.55 million t C under urban expansion. Construction-land expansion was substantial, but economic-output density made the larger positive contribution to historical emission growth. The projected 2030 estimates depended on the combined trajectories of construction-land demand, economic growth, and energy intensity. These findings highlight the importance of coordinating land-use planning, economic development, and energy-efficiency improvement for sustainable low-carbon transitions. Full article

Soil health is central to sustainable agriculture, but remains challenging to assess in diversified agroecosystems such as permaculture. Soil condition reflects the interaction of physical, chemical, and biological properties, but practical assessment commonly relies on a limited set of informative indicators. In this study, a PCA-weighted Soil Health Index (SHI) was constructed from five surface soil indicators: organic carbon, total nitrogen, microbial biomass (PLFA), bulk density, and gravimetric water content. The first principal component explained 75.30% of the total variance. The analysis used 84 observations collected between 2019 and 2021 from permaculture and conventional farming systems across nine locations in Germany and Luxembourg, encompassing different land use types and two soil depths. Permaculture plots showed higher SHI values overall than conventional plots, with the same trend observed across all nine locations, although land use imbalance limited fully matched comparisons. To avoid circular prediction of the PCA-derived target, the five surface variables used directly to construct the SHI were excluded from the predictive feature set. Machine learning models were evaluated using grouped validation in which entire locations were held out from model training. The best-performing full-profile Ridge model achieved an out-of-fold $R^2$ of 0.710, an MAE of 0.159, and an RMSE of 0.214. Out-of-fold SHAP analysis indicated that magnesium, zinc, soil pH, subsoil bulk density, and copper made the largest model-specific contributions to SHI estimation. These findings demonstrate that PCA-based soil health assessment can distinguish systematic differences between studied farming systems and that a leakage-aware, interpretable modeling framework can provide moderate predictive performance across held-out locations. The results should be interpreted as internal evidence from a small multi-location dataset rather than as externally validated or causal estimates of management effects. Full article

Tenure insecurity among smallholder farmers undermines incentives for long-term soil health restoration investments, thereby limiting agricultural productivity and household food security. This study examines the impacts of land registration on soil health restoration and household food security among smallholder farmers in Malawi. Using representative data from 506 households, the study employs a corrected selectivity endogenous switching regression model to account for selection bias, reverse causality and unobserved heterogeneity. Food security is measured using multiple indicators to capture its multidimensional nature, including the Women’s Dietary Diversity Score (WDDS), Children’s Dietary Diversity Score (CDDS), the Household Food Insecurity Access Scale (HFIAS), and the Household Food Insecurity Experience Scale (HFIES). The results indicate that land registration significantly improves soil health restoration by 9% (p < 0.00) and food security outcomes across indicators, with average treatment effects on the treated (ATT) of 1.02 for WDDS, 0.50 for CDDS, −0.83 for HFIES, and −2.54 for HFIAS, all significant at the 1% level. Furthermore, household and farm characteristics, such as the age of the household head, membership in farmer groups, landholding size, and adoption of sustainable land management practices enhance welfare. The study suggests that scaling up targeted land registration, alongside promoting complementary sustainable land management practices, has the potential to improve soil health restoration and strengthen food security in Malawi’s smallholder farming systems. Full article

Biodiversity conservation schemes in collaboration with agriculture have been criticized in part for their limited ecological effectiveness. In this regard, biosphere reserves are internationally recognized as playing a model role in developing sustainable land use systems. To learn about farmers’ perspectives on insects, the role of biosphere reserves in their farm management, and their experiences with biodiversity measures, we interviewed farmers in the German biosphere reserves (BRs) Schaalsee, Schorfheide-Chorin, Middle Elbe, Bavarian Rhön and Black Forest, thereby drawing on the model function of these reserves for insect conservation. Their perceptions were then assessed by BR staff and insect conservation managers. Juxtaposing the views of farmers and insect conservation stakeholders provides comparative insights from multiple perspectives. Interviewed farmers perceived BR staff as holding substantial regional knowledge, which gives them a reputation as competent intermediaries between biodiversity conservation and agriculture. Although the economic incentives to change farm management are perceived as low, most farmers can be engaged in biodiversity conservation through their intrinsic motivations. Farmers were clustered into four motivational patterns that require targeted communication. Across motivational patterns, farmers identified administrative burdens, farm-level costs, and the limited reliability and flexibility of existing measures as major barriers. To better conserve insects and promote insect conservation measures among farmers, extension services are needed. BR staff and insect conservation managers agreed on most of the farmers’ needs identified through the interviews. Therefore, BR administrations may play a crucial role in insect conservation as they recognize the contribution of agriculture and can engage additional stakeholders beyond the sector. To establish insect conservation in BRs in the long term, regional extension staff for nature conservation and regional support schemes are most needed to provide site-specific, regionally adapted conservation measures. Full article

Ports are progressively evolving from traditional logistics nodes into integrated energy ecosystems, characterised by increasing electrification of maritime and land-based operations, the deployment of renewable energy sources, and the emergence of new and highly variable energy demand profiles. In this context, the main challenge is not only the availability of renewable energy but also the capacity of port energy systems to provide sufficient electrical power, flexibility, and resilience under increasing operational constraints. These issues are particularly relevant in Mediterranean ports, where limited grid capacity, infrastructure constraints, load variability, and interactions with surrounding urban areas strongly influence energy planning strategies. This paper proposes an integrated framework for the development of sustainable port energy hubs based on renewable generation, energy storage, green hydrogen systems, port microgrids, and intelligent energy management strategies (EMS). The main novelty lies in the integration of these energy vectors within a unified framework that explicitly accounts for the specific operational and infrastructure constraints of Mediterranean ports. The proposed approach aims to optimise the interaction between energy production, distribution, storage, and consumption, with particular attention to the role of hydrogen as a long-duration energy storage vector and as an energy carrier for selected port logistics applications. Through a data-driven Port Energy Baseline Assessment (PEBA), port operational characteristics are translated into quantified energy demand and power requirements, providing the basis for power adequacy assessment and the evaluation of alternative transition pathways. An illustrative application to a representative Mediterranean port, characterized by a peak electricity demand of 42 MW, illustrates how the framework quantifies power requirements, assesses power adequacy under infrastructure constraints, and compares alternative transition pathways based on renewable generation, battery storage, and hydrogen. Full article

Urban pluvial flooding shows clear temporal accumulation, delayed response, and spatial heterogeneity. Better flood-depth prediction from a spatiotemporal coupling perspective can support urban flood risk identification and refined management. This study develops a spatiotemporal prediction model that integrates a Transformer and graph neural network (GNN). The Transformer module captures temporal dependencies in rainfall processes and flood-depth evolution. The graph attention network (GAT) represents spatial associations constrained by terrain, drainage networks, and neighboring spatial relationships. A fusion attention mechanism then adaptively couples temporal and spatial features. This study uses multi-source data, including hourly meteorological observations, terrain, land cover, drainage networks, and water-system data. It selects the heavy rainfall event caused by Typhoon In-Fa in Huai’an City in July 2021 as a typical case. The study analyzes the temporal evolution of regional average flood depth and the spatial differentiation of inundated grid cells at the municipal scale. The results show three main findings. First, during the typical heavy rainfall event, regional average flood depth follows a continuous process of low-level stability, sustained rise, rapid increase, delayed peak, slow recession at a high level, and rapid recession. The flood peak lags behind the rainfall peak by about 3 h. This result indicates clear accumulation and delayed response in urban pluvial flooding. Second, at the municipal scale, inundated grid cells show a pattern of concentrated distribution in urban built-up areas, secondary distribution in county-level built-up areas, and scattered distribution in non-construction land. Different depth grades also show clear hierarchical differentiation. Mild and moderate inundation covers a wider area. Medium-high inundation concentrates locally. High-grade inundation appears as a small number of nested high-value cells. Third, the spatial differentiation of medium- and high-grade inundated grid cells does not result from low-lying terrain or construction land alone. It forms under the combined effects of low-lying terrain, local relative depressions, and impervious surfaces in construction land. This pattern shows clear built-up-area clustering, grade differentiation, and land-cover correspondence. The results provide methodological support and decision references for urban flood risk identification, grid-based risk management, and emergency dispatch during extreme rainfall. Full article

Biomass is widely recognized as a critical renewable energy source for supporting global decarbonization and energy diversification. However, the financial viability of bioenergy investments depends heavily on how climate policies and sustainable finance mechanisms interact under environmental uncertainty. This study develops a land-constrained bioenergy valuation model to examine the joint effects of carbon pricing, climate finance arrangements, and land-use regulations on the economic sustainability of biomass producers. Environmental and financial policies enter the framework through carbon costs, land-use constraints, and financial intermediation conditions, thereby linking climate regulation to firm-level capital performance. Using a contingent-claim framework, producer equity and financing risks are evaluated to capture the complex effects of market asset volatility on energy investment incentives. The framework is evaluated through a literature-informed baseline calibration and comparative-static numerical analysis; accordingly, the reported results are model-implied comparative-static mechanisms designed to evaluate bioenergy project viability under policy and market uncertainty. The numerical analysis employs a non-region-specific representative benchmark and is intended to identify structural and comparative-static mechanisms rather than to forecast outcomes for a particular geographical market. The results show that higher carbon prices reduce producer viability by increasing operating costs, although this financial strain is partially mitigated by the option-like nature of equity under higher asset volatility. In contrast, improvements in agronomic productivity, greater land availability, and higher biomass market prices enhance investment returns and financing conditions. The findings further indicate that climate policies shape bioenergy deployment not only through physical production costs but also through financial transmission channels and risk-sharing mechanisms. The study contributes to the energy policy and climate finance literature by integrating carbon pricing, land governance, and financial options within a unified analytical framework. The results highlight the importance of policy coordination between renewable energy incentives, sustainable finance management, and carbon regulation to mitigate investment risks in the bioenergy sector. Full article