Search Results (266)

Climate change accelerates biodiversity loss, threatening ecosystems worldwide. Using predictive models, such as the maximum entropy model (Maxent), allows us to identify changes in species distribution and guide conservation strategies. This study aims to model the current and future distribution of Anthemis pedunculata subsp. Atlantica and Anthemis pedunculata subsp. pedunculata in Mediterranean regions through MaxEnt modeling with bioclimatic predictors. Using the MaxEnt algorithm, we combine bioclimatic variables and 49 occurrence locations of Anthemis pedunculata subsp. pedunculata and 13 occurrence locations of Anthemis pedunculata subsp. atlantica. The future distribution of the species is projected using MIROC6 model simulations under emission scenario SSP5-8.5 for 2030 and 2050. The current model predicted approximately 99,330,066 ha as a suitable habitat for Anthemis pedunculata subsp. pedunculata. Projections for the future range exhibited a gradual increase in the suitable area in 2030 by 144,365,562 ha and 2050 by 147,335,265 ha. The current model predicted approximately 201,179,880 ha as a suitable habitat for Anthemis pedunculata subsp. atlantica. Projections for the future range exhibited a gradual enhancement of the suitable area in 2030 by 213,898,608 ha and 2050 by 229,357,062. Our results provide further evidence of the negative impact of climate change on these endemic species and emphasize the importance of their conservation. This study provides information that could strengthen the protection of these species and identify potential protection areas. Full article

Bidens pilosa L. is a cosmopolitan and invasive weed that strongly impacts agricultural systems in tropical regions. In Veracruz, Mexico, its presence extends mainly across mid-elevation zones where coffee, maize, and sugarcane are cultivated. This study characterized the bioclimatic and edaphic determinants of B. pilosa distribution using 581 georeferenced occurrences combined with 19 bioclimatic variables, elevation, and soil data. A Maxent model revealed the highest habitat suitability (0.65–1.0) in the central mountainous region between 800 and 1500 m.a.s.l., particularly under temperate–humid climates (Cfa, Cfb) and Acrisol–Leptosol soils. Principal component and redundancy analyses showed that annual precipitation (BIO12), precipitation of the driest month (BIO14), and temperature seasonality (BIO4) explained 74.7% of the total environmental variance. Cluster analysis identified four distinct ecological groups, confirming broad ecological plasticity. These findings indicate that B. pilosa is not randomly distributed but structured along climatic and soil gradients, with precipitation and elevation as major determinants of its ecological niche. Understanding these relationships provides a quantitative framework for predicting its expansion under future climate scenarios and for designing targeted management strategies in tropical agroecosystems. Full article

Systematic biodiversity and ecosystem service (ES) conservation is vital for ecological sustainability and human well-being. This study combines MaxEnt, Zonation, InVEST, and MSPA models to identify Conservation Priority Areas (CPAs) in the Wujiang River Basin (WJRB), integrating biodiversity hotspots, ESs, and landscape connectivity. Results reveal CPAs span 1.13 × 10⁴ km² (primarily downstream), but existing natural reserves (NRs) cover only 24.86% of these critical zones, leaving over 75% unprotected in this region. Current NRs occupy 0.62 × 10⁴ km², with 5.82% of the basin (mainly upstream) available for targeted expansion. Spatial analysis reveals mismatches, such as some NRs protecting low-value ecological areas, resulting in imbalanced coverage. Expanding NRs across the board is less effective than adjusting protection scope or management strategies in areas of spatial mismatch, based on identified CPAs. This can involve establishing new reserves and appropriately relaxing land-use restrictions to allow compatible activities within them. New conservation planning should prioritize large, interconnected CPA regions to enhance landscape coherence. Simultaneously, integrating ecological compensation mechanisms can align protection goals with local livelihood improvements, fostering community engagement. This approach addresses critical gaps and enhances conservation efficiency by strategically directing resources toward high-value, vulnerable ecosystems. The methodology offers a replicable framework for balancing ecological preservation and human needs in river basin management. Full article

Sweet cherry (Prunus avium L.), a temperate fruit species highly sensitive to thermal and hydric stress, faces increasing cultivation challenges in semi-arid regions such as Fez-Meknes (Morocco) due to climate change. This study aims to identify ecologically suitable zones for sweet cherry cultivation by modeling its current potential distribution using the MaxEnt (Maximum Entropy) approach. A total of 1151 georeferenced occurrence records were collected through field surveys and validated with satellite imagery. Nineteen bioclimatic variables from the WorldClim database were initially considered, and a subset with low multicollinearity (|r| < 0.7) was retained for analysis. Model performance, evaluated using the area under the ROC curve (AUC), yielded a high mean value of 0.960 ± 0.014, indicating excellent predictive accuracy. Elevation, annual precipitation (BIO12), and precipitation seasonality (BIO15) emerged as key drivers of the species’ distribution, as confirmed by both Jackknife and SPCPI analyses. Spatial prediction maps highlighted high-suitability zones in the provinces of Ifrane, El Hajeb, Azrou, and Sefrou, aligning with known agro-climatic production areas. In contrast, lower suitability was observed in more arid or heat-prone provinces such as Boulemane and Midelt. These findings provide a robust bioclimatic framework for agroecological planning, supporting adaptive varietal zoning and long-term planning for climate-resilient horticulture. Full article

Understanding alpine plants’ survival and reproduction is crucial for their conservation in climate change. This study, based on 273 valid distribution points, utilizes the MaxEnt model to predict the potential habitat and distribution dynamics of Kobresia pygmaea under both current and future climate scenarios (SSP126, SSP245, SSP370, SSP585), while clarifying the key factors that influence its distribution. The study indicates that elevation (3527.99–6054.54 m) is the dominant factor influencing its distribution. The current suitable habitat is primarily concentrated in southern and central Tibet, northwestern Sichuan, and southern Qinghai on the Tibetan Plateau, with a total area of 1.13 × 10⁵ km², of which high- and moderate-suitability areas account for 1.76 × 10⁴ km² and 3.2 × 10⁴ km², respectively. Under future climate scenarios (2050s–2070s), the overall distribution pattern remains concentrated on the Tibetan Plateau, but the suitable area exhibits a trend of initial expansion followed by contraction. By the 2050s, the total suitable area increases across all scenarios, with the most pronounced expansion under SSP126. By the 2070s, however, the total suitable area decreases under high-emission scenarios, declining by 9.50% under SSP370 and 6.76% under SSP585, respectively. The reduction in high-suitability areas is more severe, with a maximum decline of 58.75% under SSP3-7.0. Dynamic change analysis shows that approximately 70% of the current high-suitability areas remain stable by the 2050s, with range expansion occurring under low-emission scenarios toward southeastern Tibet, northwestern Sichuan, and southern Golog in Qinghai. In contrast, habitat contraction intensifies by the 2070s, particularly under the SSP5-8.5 scenario, where the reduced area reaches 1.6 times the current high-suitability extent. Centroid shift analysis indicates that the distribution center of suitable habitats migrates northward or northeastward, with a maximum displacement of 206.51 km under the SSP1-2.6 scenario by the 2050s. The results suggest that short-term climate warming may alleviate low-temperature constraints, facilitating the upward and poleward expansion of Kobresia pygmaea into higher-elevation areas. However, prolonged and intensified warming will likely lead to degradation of core habitats, posing a significant threat to its long-term persistence. This study provides a scientific basis for the conservation of alpine ecosystems on the Tibetan Plateau and for developing adaptive management strategies under climate change. Full article

Pine wilt disease (PWD), caused by the invasive nematode Bursaphelenchus xylophilus, poses a growing threat to East Asian coniferous forests, which is further exacerbated by climate change. While studies have successfully applied Maximum Entropy (MaxEnt) models to map the potential spread of PWD, they have primarily focused on broad spatial scales and climatic factors. This highlights the need for fine-scale, integrative modeling approaches that also account for environmental and anthropogenic factors. Therefore, we applied the MaxEnt model combined with change vector analysis to evaluate the spatial risk and potential future spread of PWD in Andong-si, Republic of Korea, under the SSP1-2.6 climate scenario. We integrated forest structure, soil conditions, topography, climate variables, and anthropogenic factors to generate high-resolution risk maps and identify the most influential environmental drivers. Notably, we demonstrated that historical infection proximity and isothermality strongly influence habitat suitability. We also, for the first time, projected an eastward shift of high-risk areas in Andong-si under future climate conditions. These findings provide timely insights for designing proactive surveillance networks, implementing risk-based monitoring, and developing climate-resilient management strategies. Our integrative modeling framework offers decision-support tools that can enhance early detection and targeted interventions against invasive forest pests under environmental change. Full article

Cultural ecosystem services (CES) represent fundamental expressions of human-environment interactions. A comprehensive assessment of CES supply and demand offers a robust scientific foundation for optimizing the transformation of ecosystem service values to improve human well-being. This study integrates multi-source datasets and employs Maximum Entropy (MaxEnt) modeling with the ArcGIS platform to analyze the spatial distribution of CES supply and demand in Hunan Province, a typical mountain tourism regions in China. Furthermore, geographical detector methods were used to identify and quantify the driving factors influencing these spatial patterns. The findings reveal that: (1) Both CES supply and demand demonstrate pronounced spatial heterogeneity. High-demand areas are predominantly concentrated around prominent scenic locations, forming a “multi-core, clustered” pattern, whereas high-supply areas are primarily located in urban centers, water systems, and mountainous regions, exhibiting a gradient decline along transportation corridors and river networks. (2) According to the CES supply-demand pattern, Hunan Province can be classified into demand, coordination, and enhancement zones. Coordination zones dominate (45–70%), followed by demand zones (20–30%), while enhancement zones account for the smallest proportion (5–20%). (3) Urbanization intensity and land use emerged as the primary drivers of CES supply-demand alignment, followed by vegetation cover, distance to water bodies, and population density. (4) The explanatory power of two-factor interactions across all eight CES categories surpasses that of any individual factor, highlighting the critical role of synergistic multi-factorial influences in shaping the spatial pattern of CES. This study provides a systematic analysis of the categories and driving factors underlying the spatial alignment between CES supply and demand in Hunan Province. The findings offer a scientific foundation for the preservation of ecological and cultural values and the optimization of spatial patterns in mountain tourist areas, while also serving as a valuable reference for the large-scale quantitative assessment of cultural ecosystem services. Full article

Urban agglomerations in plateau regions often face severe landscape fragmentation and cross-boundary ecological pressures, highlighting the need for coordinated eco-logical planning for sustainable urban development. We coupled species–landscape interactions and multi-ecological services to construct sustainable ecological security patterns (ESPs) and establish a collaborative optimization framework. Specifically, we integrated MaxEnt-derived habit suitability with InVEST-based ecosystem services to identify ecological sources (ESs) and analysis the environmental impacts on species distribution. Based on this, we built a multi-factor resistance surface and employed circuit theory to extract ecological corridors (ECs) and critical nodes (pinch points and barrier points). Then, we quantitatively compared two simulated scenarios (barrier points restoration and stepping stone augmentation) to assess the spatial priority of ecological nodes. We identified 48 ESs (26,410.48 km², mainly distributed in Chuxiong, Yuxi, Honghe, and Kunming), 115 ECs (2670.02 km, with a west-dense and east-sparse spatial pattern), 43 pinch points, and 39 barrier points. Scenario simulation shows that repairing 39 barrier nodes increases network connectivity by an average of 33.52% and global network efficiency by 19.44%, whereas adding steeping stones yields improvements of 20.09% and 5.56%, respectively, indicating that barrier-node restoration produces larger contribution in both connectivity and efficiency at the global scale. Leveraging EN construction and scenario simulation, we developed an ESP-based sustainable framework for collaborative optimization in plateau urban agglomerations. The framework specifies agglomeration-specific coordination pathways, which are expected to provide a transferable blueprint for biodiversity conservation, ecosystem optimization, and sustainable development. Full article

Climate change threatens Tetraclinis articulata, a Mediterranean plant endangered by habitat loss, logging, and aridification. This study used the MaxEnt model to analyze factors affecting its distribution under current and future climate scenarios (SSP1-2.6 to SSP5-8.5) for 2040–2100, highlighting its vulnerability to drought and urgent conservation needs. Results showed that: (a) the model demonstrated excellent predictive power with an AUC of 0.92; (b) the highly suitable habitat for T. articulata is projected to expand by 6.5%–6.7% (5.24–5.38 million km²) by 2100 under SSPs 2-4.5, 3-7.0, and 5-8.5, compared to current conditions (6.1%, 4.92 million km²); (c) the centroid of suitable habitats shifts from northwest Algeria (1.394° N, 33.538° E) to various locations under future climate scenarios: west Morocco (SSP1-2.6, −3.429° S, 33.588° E), east Tunisia (SSP2-4.5, 11.091° N, 32.501° E), northwest Morocco (SSP3-7.0, −1.947° S, 34.098° E), and southwest Morocco (SSP5-8.5, −2.985° S, 34.707° E); (d) key environmental variables influencing T. articulata distribution include annual precipitation (bio12, 41.7%), mean annual temperature (bio1, 27.9%), and precipitation during the driest month (bio14, 16.1%). This study concluded that climate change significantly influenced the distribution of T. articulata in the Mediterranean, highlighting the urgent need for conservation strategies to mitigate the risk of local extinction driven by both anthropogenic activities and climate impacts. Full article

The Larimichthys crocea represents a critically important economic marine species in China’s East Yellow Sea. However, its populations have experienced significant decline due to overexploitation. Despite implemented conservation measures—including stock enhancement, spawning ground protection, and seasonal fishing moratoria—the recovery of yellow croaker resources remains markedly slow. To address this, our study employed the Maximum Entropy (MaxEnt) model to evaluate and characterize the habitat selection patterns of Larimichthys crocea, thereby providing a theoretical foundation for scientifically informed stock enhancement and resource recovery strategies. Species occurrence data were compiled from field surveys conducted during April and November (2019–2023), supplemented with records from the GBIF database and peer-reviewed literature. Concurrent environmental variables, including primary productivity, current velocity, depth, temperature, salinity, silicate, nitrate, phosphate, and pH, were obtained from the Copernicus and NOAA databases. After rigorous screening, 136 distribution points (April) and 369 points (November) were retained for analysis. The model performance was robust, with an AUC (Area Under the Curve) value of 0.935 for April (2019–2023) and 0.905 for November (2019–2023), indicating excellent predictive accuracy (AUC > 0.9). April (2019–2023): Nitrate, salinity, phosphate, and silicate were identified as the primary environmental factors influencing habitat suitability. November (2019–2023): Silicate, salinity, nitrate, and primary productivity emerged as the dominant drivers. Spatially, Larimichthys crocea exhibited high-density distributions in offshore regions of Zhejiang and Jiangsu, particularly near the Yangtze River estuary. Populations were also associated with island-reef systems, forming continuous distributions along Zhejiang’s offshore waters. In Jiangsu, aggregations were concentrated between Nantong and Yancheng. This study delineates habitat suitability zones for Larimichthys crocea, offering a scientific basis for optimizing stock enhancement programs, designing targeted conservation measures, and establishing marine protected areas. Our findings enable policymakers to develop sustainable fisheries management strategies, ensuring the long-term viability of this ecologically and economically vital species. Full article

Due to its ecological functions, huge economic benefits, and excellent nutritional and physiological activities, Lentinula edodes is a very popular edible fungus in Asia, especially in China. Changes in the distribution and population of wild L. edodes play an important role in conservation, variety improvements, and breeding. This investigation detected wild L. edodes in 28 provinces and municipalities in China, encompassing approximately 300 regions and natural reserves. MaxEnt analysis of 53 effective distribution locations indicated that host plants, Bio19 (precipitation in the coldest quarter), Bio10 (mean temperature of the warmest quarter), and Bio17 (precipitation in the driest quarter) made the most critical contributions to this model. The areas of suitable and highly suitable habitats were 55.386 × 10⁴ km² and 88.493 × 10⁴ km², respectively. Under four climate change scenarios, the L. edodes distribution was predicted to decrease and the suitable habitat area shifted to the north and west of China. The decrease in highly suitable habitat area ranged from 21.155% in the 2070s under the ssp1-2.6 scenario to 90.522% in the 2050s under the ssp3-7.5 scenario. This sharp reduction in habitat areas suggests that we should take measures to prevent the deterioration of the environment and climate and thus to ensure the survival of L. edodes. Full article

Species distribution models were built for three short-palped crane fly species of the genus Dicranomyia: Dicranomyia affinis, Dicranomyia chorea, and Dicranomyia mitis. The main objective of this study was to assess potential habitat suitability in undersampled regions and explore differences in environmental space. Dicranomyia affinis was historically considered a variety of Dicranomyia mitis due to their morphological similarity. In contrast, Dicranomyia chorea is a widespread species. The biology and ecology of these species remain poorly understood. Models were developed using Maxent, a widely used tool. Our results indicate that Dicranomyia affinis and Dicranomyia chorea share highly similar predicted habitat suitability, with high suitability across the Mediterranean, Central, and Northern Europe, moderate suitability in Eastern Europe, and low suitability in Central Asia. In contrast, Dicranomyia mitis is predicted to have greater habitat suitability in Eastern Europe and Scandinavia, with lower suitability in Mediterranean regions. Analysis of variable importance revealed possible ecological differences between the species. While climatic factors primarily influenced the models for Dicranomyia affinis and Dicranomyia chorea, Dicranomyia mitis was more strongly influenced by the variable pH. These findings may provide insights into potential distributions in undersampled areas and improve our understanding of the species’ ecology. Full article

Human activities have accelerated the extinction of species, driving biodiversity loss and ecosystem degradation. Establishing protected areas (PAs) that encompass habitats of endangered species is essential for achieving biodiversity conservation and ecosystem protection goals. This study aimed to identify and prioritize critical conservation areas for the endangered long-tailed goral (Naemorhedus caudatus) in five regions of Gangwon and Gyeongbuk Provinces, South Korea. The MaxEnt model was applied to predict the potential habitat of the species, considering key environmental factors such as topographic, distance-related, vegetation, and land cover variables. The InVEST Habitat Risk Assessment (HRA) model was used to quantitatively assess cumulative risks within the habitat from the impacts of forest development and anthropogenic pressures. Subsequently, the Zonation software was employed for spatial prioritization by integrating the outputs of the models, and core conservation areas (CCAs) with high ecological value were identified through overlap analysis with 1st-grade areas from the Ecological and Nature Map (ENM). Results indicated that suitable habitats for the long-tailed goral were mainly located in forested regions, and areas subjected to multiple stressors faced elevated habitat risk. High-priority areas (HPAs) were primarily forested zones with high habitat suitability. The overlap analysis emphasized the need to implement conservation measures targeting CCAs while also managing additional HPAs outside CCAs, which are not designated as ENM. This study provides a methodological framework and baseline data to support systematic conservation planning for the long-tailed goral, offering practical guidance for future research and policy development. Full article

The Blue Schools initiative integrates the ocean into classroom learning through project-based approaches, cultivating environmental awareness and a deeper sense of responsibility toward marine ecosystems and human–ocean interactions. Although the European Blue School initiative has grown steadily since its launch in 2020, its uneven uptake raises important questions about the territorial factors that influence certification. This study examines the spatial determinants of Blue School certification in Mallorca, Spain, where a bottom-up pilot initiative successfully certified 100 schools. Using Maximum Entropy (MaxEnt) modeling, we estimated the spatial probability of certification based on 16 geospatial variables, including proximity to Blue Economy actors, hydrological networks, transport accessibility, and socio-economic indicators. The model achieved strong predictive performance (AUC = 0.84) and revealed that features such as freshwater ecosystems, traditional economic structures, and sustainable public transport play a greater role in school engagement than coastal proximity alone. The resulting suitability map identifies over 30 high-potential, non-certified schools, offering actionable insights for targeted outreach and educational policy. This research highlights the potential of presence-only modeling to guide the strategic expansion of Blue Schools networks. Full article

As unique geographical entities, island cities boast abundant ecological resources and profound cultural values, serving as critical hubs for maintaining ecosystem services in coastal transition zones. Ensuring the stability of ecosystem services is strategically significant for sustainable urban development, while the construction of Ecosystem Service Networks (ESNs) has emerged as a core strategy to enhance ecological functionality and mitigate systemic risks. Based on current research gaps, this study focuses on three key questions: (1) How to construct a Composite Ecosystem Service Index (CESI) for island cities? (2) How to identify the Ecosystem Service Networks (ESNs) of island-type cities? (3) How to optimize the ecosystem service networks of island cities? This study selects Pingtan Island as a representative case, innovatively integrating the InVEST and MaxEnt models to conduct a comprehensive assessment of ecological and cultural services. By employing Principal Component Analysis (PCA), a Composite Ecosystem Service Index (CESI) was established. The research follows a systematic technical approach to construct and optimize the ESN: landscape connectivity indices were applied to identify ecological source areas based on CESI outcomes; multidimensional resistance factors were integrated into the Minimum Cumulative Resistance (MCR) model to develop the foundational ecological network; gradient buffer zone analysis and circuit theory were sequentially employed to refine the network structure and evaluate ecological efficacy. Key findings reveal: (1) Landscape connectivity analysis scientifically delineated 20 ecologically valuable source areas; (2) The coupled MCR model and circuit theory established a hierarchical ESN comprising 45 corridors (12 Level-1, 14 Level-2, and 19 Level-3), identifying 5.75 km² of ecological pinch points, 7.17 km² of ecological barriers, and 84 critical nodes—primarily concentrated in cultivated areas; (3) Buffer zone gradient analysis confirmed 30 m as the optimal corridor width for multi-scale planning; (4) Circuit theory optimization significantly enhanced network current density (1.653→8.224), demonstrating a leapfrog improvement in ecological service efficiency. The proposed “assessment–construction–optimization” integrated methodology establishes an innovative paradigm for deep integration of ecosystem services with urban spatial planning. These findings provide practical spatial guidance for island city planning, supporting corridor design, conservation prioritization, and targeted restoration, thereby enhancing ecosystem service efficiency, biodiversity protection, and resilience against coastal ecosystem fragmentation. Full article