Search Results (289)

Sicyos angulatus L. is a rapidly spreading invasive alien vine that threatens natural and agricultural ecosystems globally. We collected occurrence data from 4886 sites and applied the maximum entropy (MaxEnt) model to assess current and future habitat suitability for S. angulatus. Future climate conditions were represented by low and high greenhouse gas concentrations under representative concentration pathways (i.e., RCP2.6 and RCP8.5, respectively). The MaxEnt model accurately predicted the distribution of S. angulatus, and the area under the receiver operating characteristic curve in the receiver operating characteristic test reached 0.921. Among the 19 climatic variables investigated, the best predictors for the distribution of S. angulatus were the precipitation in the driest month (with a contribution of 37.4%), annual precipitation (26.8%), average annual temperature (18.1%), and temperature seasonality (14.9%). Currently, the most suitable areas cover the central and eastern United States, parts of southern Europe, most Japanese islands, the majority of the Korean Peninsula, and eastern China, with a total area of 180.3 × 10⁴ km² (1.2% of the Earth’s land area). During the 2050s and 2090s under RCP2.6 and RCP8.5, the most suitable regions worldwide are projected to expand by factors of 1.0 and 2.2, respectively. In particular, suitable areas might expand to higher-latitude regions and encompass previously unsuitable areas, such as Liaoning Province in Northeast China. These findings may aid in the surveillance and management of S. angulatus’ invasion globally. Full article

Climate change significantly alters vegetation distribution patterns in arid regions, while ecological water conveyance serves as a critical intervention to modify these patterns by augmenting water availability. As a keystone species in Central Asia’s water-stressed ecosystems, Populus euphratica plays a pivotal role in maintaining arid ecosystem stability, making the investigation of its habitat suitability under combined climate change and ecological water conveyance imperative. This study selected 12 variables associated with the spatial distribution of P. euphratica, including bioclimate, groundwater resources, available water storage capacity, elevation, distance to rivers, and stocking rate. Using the maximum entropy (MaxEnt) model, we projected habitat distributions of P. euphratica across the Tarim River Basin with three scenarios: no climate change, climate change, and ecological water conveyance. The study indicated that (1) distance to rivers has the significant effect on the distribution of P. euphratica; (2) although climate change is expected to reduce the habitat suitable for P. euphratica, the implementation of ecological water conveyance is expected to lead to an expansion of its habitat; (3) the implementation of ecological water conveyance is expected to cause the habitat suitable for P. euphratica to shift toward the southeast, suggesting that this initiative has increased groundwater resources in the southeastern part of the watershed. These findings provide a scientific foundation for protecting P. euphratica and formulating effective ecological water conveyance strategies. Full article

The Chinese sturgeon (Acipenser sinensis), a critically endangered anadromous fish species, spends over 90% of its life cycle in marine habitats, yet research on its marine ecology and habitat requirements is limited due to sparse data. To address this, we integrated satellite remote sensing with ecological modeling to assess spatiotemporal dynamics in marine habitat suitability across China’s continental shelf (2003–2020). Nine key habitat factors were derived from multi-source remote sensing data and inverted transparency algorithms. Species occurrence data were coupled with the Maximum Entropy (MaxEnt) model to evaluate habitat preferences and seasonal shifts. Results revealed distinct environmental preferences: shallow depths (≤20 m), sea surface and bottom temperature (10–30 °C and 10–25 °C), salinity (10–35‰), transparency (0.40–3.00 m), eastward and northward seawater velocity (−0.20–0.15 m/s and −0.20–0.20 m/s), moderate productivity (1000–3000 mg/m²), and zooplankton carbon (0.20–6.00 g/m²). Habitat factor importance varied seasonally—salinity, depth, and net primary productivity dominated in spring; bottom temperature and productivity in summer/autumn; salinity and transparency in winter. Spatially, high-suitability areas peaked in autumn (70% total suitable habitat), concentrating near the Yangtze Estuary, northern Jiangsu coast, and Zhoushan Archipelago. This study emphasizes the need to prioritize these areas for protection and inform proliferation and release schemes for Chinese sturgeon. It also demonstrates the efficacy of remote sensing for mapping essential habitats of migratory megafauna in complex coastal ecosystems and provides actionable insights for targeted conservation strategies. Full article

This study characterizes Phoradendron nervosum, a hemiparasitic mistletoe species prevalent in Ecuador, using morphological, molecular, and ecological modeling approaches. Morphological analysis revealed that P. nervosum possesses green-yellowish cylindrical stems, lanceolate leaves with entire margins, and berry-like fruits with mucilaginous pulp. DNA sequencing of the internal transcribed spacer (ITS) region confirmed a 99.43% identity with P. nervosum (GenBank: AH009776.2), supporting the taxonomic classification. A maximum entropy (MaxEnt version 3.4.4) model was developed using 36 occurrence points and 19 bioclimatic variables to assess potential distribution across the Tumbaco region in Ecuador. Key environmental factors influencing the species’ distribution were precipitation during the warmest quarter (BIO_18), temperature seasonality (BIO_4), and mean diurnal temperature range (BIO_2). The model showed good predictive performance (AUC = 0.736), identifying areas with high suitability for P. nervosum, particularly in habitats with adequate water availability and thermal stability. Findings suggest that this mistletoe parasitizes both native and exotic tree species, potentially impacting biodiversity and forest health. This research provides a baseline for monitoring mistletoe spread under climate change scenarios and emphasizes the need for management strategies in agroforestry systems where host trees are vulnerable. Full article

Trachypteris picta (Pallas, 1773) is a significant pest that can cause serious damage to poplars and willows. To assess the impact of climate change on the suitable habitats of T. picta, this study conducted a comparative analysis of its global suitable habitats using climatic factors, global land use type, and global vegetation from different periods, in combination with the maximum entropy (MaxEnt) model. The results indicate that the annual mean temperature (Bio01), mean temperature of the coldest quarter (Bio11), precipitation of the coldest quarter (Bio19), and isothermality (Bio03) are the four most important climate variables determining the distribution of T. picta. Under the current climate conditions, the highly suitable areas are primarily located in southern Europe, covering an area of 2.22 × 10⁶ km². Under future climate scenarios, the suitable habitat for T. picta is expected to expand and shift towards higher latitudes. In the 2050s, the SSP5-8.5 scenario has the largest suitable area compared to other scenarios, while the SSP2-4.5 scenario has the largest suitable area in the 2090s. In addition, the centroids of the total suitable areas are expected to shift toward higher latitudes under future climate conditions. The results of this study provide valuable data for the monitoring, control, and management of this pest. Full article

Habitat fragmentation restricts the movement of large mammals across broad landscapes, leading to isolation of individuals or groups, reduced interaction with other species, and limited access to vital resources in surrounding habitats. In this study, we aimed to determine the wildlife ecological corridors for five large mammals (Ursus arctos, Cervus elaphus, Capreolus capreolus, Sus scrofa, and Canis lupus) between Kastamonu Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. In the field studies, we used the transect, indirect observation, and camera-trap methods to collect presence data. Maximum Entropy (MaxEnt) (v. 3.4.1) software was used to create habitat suitability models of the target species, which are based on the presence-only data approach. The results indicated that AUC values varied between 0.808 and 0.835, with water sources, stand type, and slope contributing most significantly to model performance. In order to determine wildlife ecological corridors, resistance surface maps were created using the species distribution models (SDMs), and bottleneck areas were determined. The Circuit Theory approach was used to model the connections between ecological corridors. As a result of this study, we developed connectivity models for five large mammals based on Circuit Theory, identified priority wildlife ecological corridors, and evaluated critical connection points between two protected areas, Ilgaz Mountain Wildlife Refuge and Gavurdağı Wildlife Refuge. These findings highlight the essential role of ecological corridors in sustaining landscape-level connectivity and supporting the long-term conservation of wide-ranging species. Full article

As China’s first systematic assessment of high-risk Amaranthaceae invaders, this study addresses a critical knowledge gap identified in the National Invasive Species Inventory, in which four invasive Amaranthaceae species (Dysphania ambrosioides, Celosia argentea, Amaranthus palmeri, and Amaranthus spinosus) are prioritized due to CNY 2.6 billion annual ecosystem damages in China. By coupling multi-species comparative analysis with a parameter-optimized Maximum Entropy (MaxEnt) model integrating climate, soil, and topographical variables in China under Shared Socioeconomic Pathways (SSP) 126/245/585 scenarios, we reveal divergent expansion mechanisms (e.g., 247 km faster northward shift in A. palmeri than D. ambrosioides) that redefine invasion corridors in the North China Plain. Under current conditions, the suitable habitats of these species span from 92° E to 129° E and 18° N to 49° N, with high-risk zones concentrated in central and southern China, including the Yunnan–Guizhou–Sichuan region and the North China Plain. Temperature variables (Bio: Bioclimatic Variables; Bio6, Bio11) were the primary contributors based on permutation importance (e.g., Bio11 explained 56.4% for C. argentea), while altitude (e.g., 27.3% for A. palmeri) and UV-B (e.g., 16.2% for A. palmeri) exerted lower influence. Model validation confirmed high accuracy (mean area under the curve (AUC) > 0.86 and true skill statistic (TSS) > 0.6). By the 2090s, all species showed net habitat expansion overall, although D. ambrosioides exhibited net total contractions during mid-century under the SSP126/245 scenarios, C. argentea experienced reduced total suitability during the 2050s–2070s despite high-suitability growth, and A. palmeri and A. spinosus expanded significantly in both total and highly suitable habitat. All species shifted their distribution centroids northward, aligning with warming trends. Overall, these findings highlight the critical role of temperature in driving range dynamics and underscore the need for latitude-specific monitoring strategies to mitigate invasion risks, providing a scientific basis for adaptive management under global climate change. Full article

Understanding the geographic distribution of mammal species is essential for informed conservation planning, maintaining local ecosystem stability, and addressing research gaps, particularly in data-deficient regions. This study investigated the distribution and richness of 20 mammal species within Nyerere National Park (NNP), a large and understudied protected area in Southern Tanzania. We applied species distribution models (SDMs) using presence data collected through ground surveys between 2022 and 2024, combined with environmental variables derived from remote sensing, including land surface temperature, vegetation indices, soil moisture, elevation, and proximity to water sources and human infrastructure. Models were constructed using the Maximum Entropy (MaxEnt) algorithm, and performance was evaluated using the Area Under the Curve (AUC) metric, yielding high accuracy ranging from 0.81 to 0.97. Temperature (32.3%) and vegetation indices (23.4%) emerged as the most influential predictors of species distributions, followed by elevation (21.7%) and proximity to water (14.5%). Species richness, estimated using a stacked SDM approach, was highest in the northern and riparian zones of the park, identifying potential biodiversity hotspots. This study presents the first fine-scale SDMs for mammal species in Nyerere National Park, offering a valuable ecological baseline to support conservation planning and promote sustainable ecotourism development in Tanzania’s southern protected areas. Full article

This study aimed to predict the potential habitats of Luciola unmunsana using a species distribution model (SDM). Luciola unmunsana is an endemic species that lives only in South Korea, and because its females do not have genus wings and are less fluid, it is difficult to collect, so research related to its distribution and restoration is relatively understudied. Therefore, this study predicted the potential habitats of Luciola unmunsana across South Korea using the single model Maximum Entropy (MaxEnt) and a multi-model ensemble model to prepare basic data necessary for a conservation and habitat restoration plan for the species. A total of 39 points of occurrence were built based on public data and prior research from the Jeonbuk Green Environment Support Center (JGESC), the Global Biodiversity Information Facility (GBIF), and the National Institute of Biological Resources (NIBR). Among the input variables, climate variables were based on the shared socioeconomic pathway (SSP) scenario-based ecological climate index, while nonclimate variables were based on topography, land cover maps, and the Enhanced Vegetation Index (EVI). The main findings of this study are summarized below. First, in predicting Luciola unmunsana potential habitats, the EVI, water network analysis, land cover, and annual precipitation (Bio12) were identified as good predictors in both models. Accordingly, areas with high vegetation activity in their forests, adjacent to water resources, and stable humidity were predicted as potential habitats. Second, by overlaying the predicted potential habitats and highly significant variables, we found that areas with high vegetation vigor within their forests, proximity to water systems, and relatively high annual precipitation, which can maintain stable humidity, are potential habitats for Luciola unmunsana. Third, literature surveys used to predict potential habitat sites, including Geumsan-gun, Chungcheongnam-do, Yeongam-gun, Jeollabuk-do, Mudeungsan Mountain, Gwangju-si, Korea, and Gijang-gun, Busan-si, Korea, confirmed the occurrence of Luciola unmunsana. This study is significant in that it is the first to develop a regional SDM for Luciola unmunsana, whose population is declining due to urbanization. In addition, by applying various environmental variables that reflect ecological characteristics, it contributes to more accurate predictions of the potential habitats of this species. The predicted results can be used as basic data for the future conservation of Luciola unmunsana and the establishment of habitat restoration strategies. Full article

To ensure food security in Xinjiang, scientifically conducting land suitability evaluation is of significant importance. This paper takes an arid and ecologically fragile region of southern Xinjiang—Qiemu County—as an example. Based on the optimized Maximum Entropy (MaxEnt) model, 14 multi-source environmental variables including climate, soil, hydrology, and topography are integrated. The ENMeval package is used to optimize the model parameters, and Spearman’s rank correlation analysis is employed to screen key variables. The spatial distribution of land suitability and the dominant factors are systematically assessed. The results show that the model AUC values for the mountainous and plain areas are 0.987 and 0.940, respectively, indicating high accuracy. In the plain area, land suitability is primarily influenced by the soil sand content, while in the mountainous region, the annual accumulated temperature plays a leading role. The highly suitable areas are mainly distributed in the northern plains and parts of the southern mountains. This study clarifies the suitable areas for land development and environmental thresholds, providing a scientific basis for the development of land resources in arid regions and the implementation of the “store grain in the land” strategy. Full article

The impact of climate change on the distribution of Cinnamomum malabatrum (Laurales—Lauraceae), a culturally and ecologically important species in the Malabar region of Western Ghats, India, was studied using a MaxEnt machine learning algorithm. The findings are rooted in extensive field data and advanced modeling techniques. The predicted range shifts and contraction of suitable habitats for the species indicate significant challenges ahead, especially in the Malabar midlands and coastal plains—areas of high endemicity. The proposed conservation strategies provide a comprehensive framework that encompasses the protection of sacred groves, sustainable land-use policies, afforestation, and community conservation strategies within protected areas. This study serves as a clarion call for concerted action and collaboration among researchers, policymakers, local communities, and conservation practitioners to preserve the delicate balance of the ecosystem in the face of environmental change. Full article

A key challenge is how to effectively conserve habitats and biodiversity amid widespread habitat fragmentation and loss caused by global urbanization. Despite growing attention to this issue, knowledge of the seasonal dynamics of habitats remains limited, and conservation gaps are still inadequately identified. This study proposes a novel integrated framework, “Habitat Suitability–Risk–Quality”, to improve the assessment of the seasonal bird habitat quality and to identify priority conservation habitats in urban landscapes. The framework was implemented in Wuhan, China, a critical stopover site along the East Asian–Australasian Flyway. It combines the Maximum Entropy (MaxEnt) model to predict the seasonal habitat suitability, the Habitat Risk Assessment (HRA) model to quantify habitat sensitivity to multiple anthropogenic threats, and a refined Habitat Quality (HQ) model to evaluate the seasonal habitat quality. K-means clustering was then applied to group habitats based on seasonal quality dynamics, enabling the identification of priority areas and the development of differentiated conservation strategies. The results show significant seasonal variation in habitat suitability and quality. Wetlands provided the highest-quality habitats in autumn and winter, grasslands exhibited moderate seasonal quality, and forests showed the least seasonal fluctuation. The spatial analysis revealed that high-quality wetland habitats form an ecological belt along the urban–suburban fringe. Four habitat clusters with distinct seasonal characteristics were then identified. However, spatial mismatches were found between existing protected areas and habitats of high ecological value. Notably, Cluster 1 maintained high habitat quality year round, spanning 99.38 km², yet only 46.51% of its area is currently protected. The remaining 53.16 km², mostly situated in urban–suburban transitional zones, remain unprotected. This study provides valuable insights for identifying priority habitats and developing season-specific conservation strategies in rapidly urbanizing regions, thereby supporting the sustainable management of urban biodiversity and the development of resilient ecological systems. Full article

Ulmus glabra Huds. is a mesophilic, montane broadleaf tree with high ecological value, commonly found in temperate riparian and floodplain forests across Türkiye. Its populations in Türkiye have declined due to anthropogenic disturbances and climatic pressures that cause habitat fragmentation and threaten the species’ long-term survival. In this research, we used Maximum Entropy (MaxEnt) to build species distribution models (SDMs) and applied the Restoration Planner (RP) tool to identify and prioritize critical restoration sites under both current and projected climate scenarios (SSP245, SSP370, SSP585). The SDMs highlighted areas of high suitability, primarily along the Black Sea coast. Future projections show that habitat fragmentation and shifts in suitable areas are expected to worsen. To systematically compare restoration options across different future scenarios, we derived and applied four spatial network status indicators using the RP tool. Specifically, we calculated Restoration Pixels (REST_PIX), Average Distance of Restoration Pixels from the Network (AVDIST_RP), Change in Equivalent Connected Area (ΔECA), and Restoration Efficiency (EFFIC) using the RP tool. For the 1 <-> 2 restoration pathways, the highest efficiency (EFFIC = 38.17) was recorded under present climate conditions. However, the largest improvement in connectivity (ΔECA = 60,775.62) was found in the 4 <-> 5 pathway under the SSP585 scenario, though this required substantial restoration effort (REST_PIX = 385). Temporal analysis noted that the restoration action will have most effectiveness between 2040 and 2080, while between 2081 and 2100, increased habitat fragmentation can severely undermine ecological connectivity. The result indicates that incorporation of habitat suitability modeling into restoration planning can help to design cost-effective restoration actions for degraded land. Moreover, the approach used herein provides a reproducible framework for the enhancement of species sustainability and habitat connectivity under varying climate conditions. Full article

Chengiodendron marginatum, an evergreen tree or shrub belonging to the Oleaceae family, represents a critical germplasm resource with considerable potential for novel cultivar breeding. To elucidate the adaptive responses of C. marginatum to climate change and provide strategic guidance for its conservation, this study investigates the changing patterns in its potential suitable habitats under various climate scenarios. We employed an integrated approach combining maximum entropy (Maxent) modeling with GIS spatial analysis, utilizing current occurrence records and paleoclimatic data spanning from the mid-Holocene to future projections (2041–2060 [2050s] and 2061–2080 [2070s]). Climate scenarios SSP126 and SSP585 were selected to represent contrasting emission pathways. The model demonstrated excellent predictive accuracy with an AUC value of 0.942, identifying precipitation-related variables (particularly the precipitation of driest month and annual precipitation) as the primary environmental factors shaping the geographical distribution of C. marginatum. Current suitable habitats encompass approximately 98.38 × 10⁴ km², primarily located in East, Central, and South China, with high-suitability habitats restricted to southern Hainan, Taiwan, and northeastern Guangxi. Since the mid-Holocene, an expansion of suitable habitats occurred despite localized contractions in Southwest China. Future projections revealed moderate habitat reduction under both scenarios, and high-suitability areas decreased substantially. Importantly, under both scenarios, persistent high-suitability habitats were maintained in southern Hainan, Taiwan, and northeastern Guangxi, which are identified as essential climate refugia for the species. These findings provide a basis for understanding the response of the species to climate change and offer valuable guidance for its conservation. Full article

Tamarix boveana Bunge demonstrates strong drought and salinity tolerance, exhibiting significant economic potential and ecological functions. With global warming profoundly altering plant distribution patterns, this study aims to identify key factors influencing its distribution and predict shifts in habitat suitability under future climate scenarios. This study employed the maximum entropy (MaxEnt) model with 186 presences and 36 environmental variables. Results reveal that the current suitable habitat of Tamarix boveana is primarily concentrated along the southern Mediterranean coast and partial western coastal areas, with highly suitable zones comprising 14% of the total suitable range. Dominant environmental factors governing its distribution include isothermality (bio3), annual mean temperature (bio1), soil pH (t_pH_h₂o), and precipitation of the warmest quarter (bio18). Projections under varying carbon emission scenarios indicate a contraction in suitable habitat area, accompanied by pronounced poleward range shifts and habitat fragmentation, particularly under high-emission pathways. This study provides a scientific foundation for the conservation and management of Tamarix boveana, while contributing to climate change impact assessments and biodiversity preservation. Full article