Search Results (866)

Vaccinium mandarinorum Diels, a wild blueberry species distributed in the south of the Yangtze River in China, holds significant ecological and commercial value. Understanding its potential distribution and response to climate change is crucial for effective resource utilization and scientific introduction. By using the Maximum Entropy (MaxEnt) model, we evaluated V. mandarinorum’s potential distribution under current (1970–2000) and future climate change scenarios (2041–2060, 2061–2080, and 2081–2100) based on 216 modern distribution records and seven bioclimatic variables. The results showed that the MaxEnt model could effectively simulate the historical distribution and suitability degree of V. mandarinorum. The top two major environmental variables were precipitation of the driest quarter and annual precipitation, considering their contribution rates of 61.3% and 23.4%, respectively. Currently, the high suitability areas were mainly concentrated in central and northern Jiangxi province, central and southern Zhejiang province, southern Anhui province, central and northern Fujian province, and the border areas of Hunan and Guangxi provinces, covering 21.5% of the total suitable area. Future projections indicate that habitat will shift to higher latitudes and altitudes and that habitat quality will decline. Strategies are required to protect current V. mandarinorum populations and their habitats. The study results could provide an important theoretical reference for the optimization of planting distribution and ensure the sustainable production of the blueberry industry. Full article

Cheirotonus jansoni (Jordan, 1898), a beetle species of ecological and ornamental significance, is predominantly found in southern China. With limited dispersal ability, it is classified as a Class 2 protected species in China. In this study, the widely employed maximum entropy (MaxEnt) model and the ensemble Biomod2 model were applied to simulate C. jansoni habitat suitability in China under current environmental conditions based on available distribution data and multiple environmental variables. The optimized MaxEnt model demonstrated improved accuracy and robust predictive capabilities, making it the preferred choice for simulating dynamic changes in potentially suitable habitats for C. jansoni under future climate scenarios. Protection gaps were further identified through analyses of the overlap between nature reserves and highly suitable areas for C. jansoni. The established models indicated that this species primarily resides in southeastern mountainous regions of China below 2000 m, with a preferred altitude of 1000–2000 m. Future climate scenarios suggest a reduction in the overall suitable habitat for C. jansoni with an increase in temperature, underscoring the urgent need for enhanced conservation efforts for this beetle species. Full article

As the global shift from fossil fuels to the Paris Agreement has accelerated, wind energy has become a key alternative to hydroelectric power. However, existing research often needs to improve in integrating diverse environmental, economic, and climate-related variables when modeling wind energy potential, particularly under future climate change scenarios. Addressing these gaps, this study employs the maximum entropy (MaxEnt) method, a robust and innovative tool for spatial modeling, to identify optimal wind farm sites in Türkiye. This research advances site selection methodologies and enhances predictive accuracy by leveraging a comprehensive dataset and incorporating climate change scenarios. The results indicate that 89% of the current licensed projects will maintain compliance in the future, while 8% will see a decrease in compliance. Furthermore, the wind energy potential in Türkiye is expected to increase because of climate change. These results confirm the suitability of existing project locations and identify new high-potential areas for sustainable wind energy development. This study provides policymakers, investors, and developers actionable insights to optimize wind energy integration into the national energy portfolio, supporting global climate goals by accelerating the adoption of renewable energy sources. Full article

Global warming and landscape fragmentation significantly affect the spatial distribution pattern of bamboo forests. This study used high-resolution data and an optimized MaxEnt model to predict the distribution of Phyllostachys edulis in China under current and future climatic conditions in three climate scenarios (SSP126, SSP370, SSP585), and analyzed its land use landscape fragmentation using landscape indices. The results indicate that Phyllostachys edulis currently has potentially suitable habitats majorly distributed in East China, Southwest China, and Central South China. The precipitation of the driest month (BIO14) and the precipitation seasonality (BIO15) are the key environmental factors affecting the distribution of Phyllostachys edulis. In the next three scenarios, the adaptive distribution area of Phyllostachys edulis is generally expanding. With an increase in CO₂ concentration, the adaptive distribution of Phyllostachys edulis in the 2050s migrates towards the southeast direction, and in the 2070s, the suitable habitat of Phyllostachys edulis migrates northward. In the suitable habitat area of Phyllostachys edulis, cropland and forests are the main land use types. With the passage of time, the proportion of forest area in the landscape pattern of the high-suitability area for Phyllostachys edulis continues to increase. Under SSP370 and SSP585 scenarios, the cropland in the Phyllostachys edulis high-suitability area gradually becomes fragmented, leading to a decrease in the distribution of cropland. In addition, it is expected that the landscape of high-suitability areas will become more fragmented and the quality of the landscape will decline in the future. This research provides a scientific basis for understanding the response of Phyllostachys edulis to climate change, and also provides theoretical guidance and data support for the management and planning of bamboo forest ecosystems, which will help in managing bamboo forest resources rationally and balancing carbon sequestration and biodiversity conservation. Full article

Disaster-prone mountainous regions face complex human–environment conflicts resulting from the combined influences of natural disaster threats, ecosystem conservation, and resource development. This study takes Mentougou District as the research area, leveraging landscape character identification methods to develop a multidimensional evaluation framework integrating safety, ecology, and landscape aspects, providing a foundation for zoning and management decisions. Four characteristic elements—elevation, geomorphology, vegetation type, and land cover type—were extracted during the landscape character identification phase. Two-step clustering and eCognition multi-scale segmentation were used to identify 12 landscape character types (LCTs) and delineate Landscape Character Areas (LCAs). The MaxEnt model was applied during the evaluation phase to assess debris flow susceptibility. At the same time, AHP and ArcGIS spatial overlay methods were used to evaluate ecological resilience and landscape resource quality. The three-dimensional evaluation results for the 12 LCAs were clustered and manually interpreted, resulting in four levels of protection and development areas. Management strategies were proposed from three perspectives: debris flow disaster prevention, ecosystem conservation, and landscape resource development. This method provides a pathway to balance human–environment conflicts in disaster-prone mountainous regions, promoting scientific zoning management and sustainable development in vast mountainous areas. Full article

Magnolia officinalis Rehder & E.H. Wilson is a deciduous tree in the Magnoliaceae family with extensive medicinal uses in China and Japan, being used to treat symptoms such as indigestion, insomnia, and anxiety. In this study, we used the MaxEnt model to (1) simulate the suitable spatial distribution areas of M. officinalis in China in the current and future periods (2050s and 2090s) and, (2) identify the key environmental variables affecting its spatial distributions by comparing the changes in the center of mass of the suitable areas under the current and projected future climate. The research results show that the current distribution range of M. officinalis is mainly between east longitude 102.2° to 122.2° and north latitude 23.7° to 33.9°, and it is located in the subtropical region of China. In the future, only the high-suitability area under scenario SSP1-2.6 and the low-suitability area under scenario SSP5-8.5 decreased in the 2050s, while the area increased under all other conditions. In the 2050s, the high- and medium-suitability areas under the SSP5-8.5 scenario increased the most, by 54.76% and 20.90%, respectively. Most of the key bio-climatic variables affecting the spatial distributions of M. officinalis are related to temperature and precipitation, and soil, terrain, chemical, and human variables that are also key environmental variables affecting the spatial distributions of M. officinalis. Currently, the suitable spatial distribution centroid of M. officinalis is at (111.71° E, 28.52° N), but it will change in the future climate; although, it will still be located in Hunan Province. This study predicts the spatial distribution areas that are favorable for the cultivation of M. officinalis with the intention of offering an objectively informed identification of suitable areas for the current and future development of this tree crop’s industry. Full article

Urban expansion leads to changes in land use, and the resulting habitat fragmentation increases the risk of species extinction. Therefore, strategies to connect fragmented habitats for wildlife conservation are required, but past research has focused mainly on large mammals and specific species, and there has been a lack of research on habitat connectivity in Korea. In the present study, we sought to design an ecological network for the conservation of endangered forest wildlife (leopard cat, yellow-throated marten, and Siberian flying squirrel) in Pyeongchang, Gangwon State, Korea. The InVEST habitat quality and MaxEnt models were used to predict forest areas with excellent habitat quality and a high probability of the occurrence of endangered wildlife. We then used Linkage Mapper to identify corridors and bottlenecks that connect fragmented habitats within the study area. The quality of these corridors and the environmental features of the pinch points were also analyzed. The results showed that the area outside of Pyeongchang is the most likely area for endangered forest wildlife habitats and occurrence. A total of seven core areas were identified, and 12 corridors connecting the core areas were identified. The highest quality corridors were those connecting forest areas outside of Pyeongchang because they had a high habitat quality with alternative paths of least resistance. We also identified sections with high pinch points in all corridors, and these points tended to have high elevation, a southern aspect, a long distance from agricultural land and water bodies, low traffic density, and low building density. ANOVA revealed that the environmental variables associated with high pinch points, least-cost paths, and Pyeongchang in general exhibited statistically significant differences. These results demonstrate that the proposed conservation planning model can be applied to multiple species using a corridor-integrated mapping approach and produces quantitative figures for the targeted improvement of ecological connectivity in forests according to local characteristics, including biodiversity. As such, this approach can be utilized as the basis for the selection and management of protected forest areas and for environmental impact assessment. However, because this study had data limitations, field surveys and the monitoring of target species are needed. Once these limitations are addressed, a quantitative conservation plan can be established based on the ecological characteristics of endangered forest wildlife. Full article

Cultivation is advocated as a solution for the sustainable exploitation of medicinal plants. Understanding environmental factors influencing plant species distribution will eliminate the indiscriminate introduction of medicinal plants to inappropriate cultivation regions. This study investigated environmental conditions for the distribution of Artemisia afra and mapped out potential areas for its cultivation in South Africa. Soil samples were collected for analysis in the Free State Province in South Africa. To identify suitable environmental conditions for the natural distribution of A. afra, the South African National Botanical Institute database and physically collected Global Positioning System points were used in a maximum entropy model. Monthly long-term average interpolated weather surfaces were used to estimate the effect of climate change on future climate suitability for A. afra distribution. Sixty-one percent of soil samples from different A. afra populations were clay loam soils with a slightly acidic to neutral pH. The carbon source utilization, Shannon Weaver Index, and species richness were positively correlated with one group of fourteen soil samples, and species evenness was positively correlated with the second group, consisting of four samples. Climate change will only affect the distribution of A. afra in the very long term. The current study provides critical information for identifying suitable cultivation areas for A. afra while supporting conservation efforts from an ecological point of view. Full article

Invasive alien species often undergo shifts in their ecological niches when they establish themselves in environments that differ from their native habitats. Leptocybe invasa Fisher et LaSalle (Hymenoptera: Eulophidae), specifically, has caused huge economic losses to Eucalyptus trees in Australia. The global spread of eucalyptus cultivation has allowed L. invasa to threaten plantations beyond its native habitat. It is, therefore, urgent to implement effective control measures to mitigate the impact of this pest. The optimized MaxEnt model was used to predict the potential global distribution of L. invasa based on occurrence data and environmental variables. The centroid shift, overlap, unfilling, and expansion (COUE) framework was employed to evaluate niche dynamics during the global invasion process by comparing the ecological niches of L. invasa in both native regions and regions affected by invasions (hereafter referred to as “invaded”). The results indicated that the distribution of L. invasa is primarily influenced by temperature, precipitation, and the human influence index variables. Its ecological niche was shown to have considerably expanded from native to invaded regions. Under future climate scenarios, the potential geographical distribution of L. invasa is projected to be concentrated primarily in East Asia, Southeast Asia, Western Europe, and Southern Oceania. In the future, the potentially suitable areas for the establishment of L. invasa are expected to further expand. This study provides a unified framework for exploring the niche dynamics of invasive alien species globally. Emphasizing early warning and control in uninvaded areas is crucial for minimizing L. invasa ecological and economic threats. Full article

Grassland ecosystems cover a high percentage of the terrestrial habitats of Earth and support the livelihood and well-being of at least one-fifth of the human population. Climate change and human activities are causing increasing pressure on arid and semi-arid regions. Land use/cover change significantly affects the function and distribution of grasslands, showing diverse patterns across space and time. The study investigated the spatial distribution of grasslands of Mount Zireia (Peloponnesus, Greece) using MaxEnt modeling based on CMIP6 models (CNRM-CM6 and CCMCC-ESM2) and two Shared Socioeconomic Pathways (SSP 245 and SSP 585) covering the period of 1970–2100. The results from the current (1970–2000) and several future periods (2020–2100) revealed that the MaxEnt model provided highly accurate forecasts. The grassland distribution was found to be significantly impacted by climate change, with impacts varying by period, scenario, and climate model used. In particular, the CNRM-CM6-1 model forecasts a substantial increase in grasslands at higher elevations up to 2100 m asl. The research emphasizes the importance of exploring the combined impacts of climate change and grazing intensity on land use and cover changes in mountainous grasslands. Full article

The demarcation of national park boundaries is crucial for comprehensive planning, effective management, and maintaining the integrity of ecosystems and biodiversity. This research uses the proposed ‘Ailaoshan–Wuliangshan’ National Park (AWNP) in Yunnan Province, China, as the study area and adheres to the principles of systematic conservation planning (SCP). It employs the Marxan 2.43, MaxEnt 3.4.4, and InVEST 3.14.2 models to predict suitable distribution areas for key endangered species within the AWNP, identifies core ecological source areas, priority conservation areas, and conservation gaps, and constructs a double boundary protection framework. The study’s findings indicate that the potentially suitable habitats for the major rare and endangered species, as predicted by the MaxEnt model, are predominantly located in the Ailaoshan and Wuliangshan areas, with a smaller portion distributed in the Konglonghe area. The InVEST model assessment of habitat quality revealed that the total area of the core ecological source areas is 4775.26 km², accounting for 35.34% of the total study area. The Marxan model identified a total area of 1064.22 km² as priority conservation areas, constituting 7.90% of the total study area. Additionally, it revealed conservation gaps of 302.1 km², which represent 2.20% of the total area. Ultimately, by integrating biodiversity conservation and ecosystem services, the boundaries of the AWNP were optimized into a double boundary delineation model: the inner boundary, characterized by rigid control, spans an area of 1076.20 km², while the outer boundary, characterized by elastic management, covers an area of 3056.92 km². Corresponding management recommendations are proposed for the different areas. The double boundary delineation method proposed in this study can, to a certain extent, reconcile the conflict between biodiversity conservation and resource utilization, providing an appropriate reference for the demarcation and dynamic management of national park boundaries in China. Full article

Species distribution modeling (SDM) is a vital tool for ecological and biogeographical research, allowing precise predictions of species distributions based on environmental variables. This study reviews the evolution of SDM techniques from 1985 to 2023, focusing on model development and applications in conservation, climate change adaptation, and invasive species management. We employed a mixed review with bibliometric and systematic element approaches using the Scopus database, analyzing 982 documents from 275 sources. The MaxEnt model emerged as the most frequently used technique, applied in 85% of the studies due to its adaptability and accuracy. Our findings highlight the increasing trend in international collaboration, particularly between China, the United Kingdom, and Brazil. The study reveals a significant annual growth rate of 11.99%, driven by technological advancements and the urgency to address biodiversity loss. Our analysis also shows that while MaxEnt remains dominant, deep learning and other advanced computational techniques are gaining traction, reflecting a shift toward integrating AI in ecological modeling. The results emphasize the importance of global cooperation and the continued evolution of SDM methodologies, projecting further integration of real-time data sources like UAVs and satellite imagery to enhance model precision and applicability in future conservation efforts. Full article

Danaus genutia, commonly known as the tiger butterfly, is a visually appealing species in the Danaidae family. As it is not currently classified as endangered, it is excluded from key protected species lists at national and local levels, limiting focus on its population and habitat status, which may result in it being overlooked in local butterfly conservation initiatives. Yunnan, characterized by high butterfly diversity, presents an ideal region for studying habitat suitability for D. genutia, which may support the conservation of regional biodiversity. This study employs the MaxEnt ecological niche model, predictions regarding suitable habitat distribution, and trends for D. genutia and identifying primary environmental factors influencing their distribution. The results indicate that the niche model that includes interspecies relationships provides a distribution prediction closely aligned with the observed range of D. genutia. Under current climatic conditions, highly suitable habitats for both D. genutia and its host plant, Cynanchun annularium, are located predominantly in the Yuanjiang River Valley. Optimal conditions occur at average annual temperatures of 19.80–22 °C for D. genutia and 22–24 °C for C. annularium. The distribution range of C. annularium is a vital biological factor limiting D. genutia’s habitat. By 2040, projections under four future climate scenarios indicate a potential increase in the total area of suitable habitats for D. genutia, with a general trend of northward expansion. Full article

Illicium verum Hook. f. (star anise) is a highly important plant in terms of both its edible and medicinal properties and its economic value. The suitable habitat for star anise may undergo alterations in response to climate changes and human activities, which in turn might impact its quality. To ensure the future introduction and protection of star anise, it is crucial to analyze the impacts of climate change on the potential distribution of the species. The approach presented in this study integrates the MaxEnt model and chemical composition analysis to assess the potential distribution patterns of star anise in response to climate change and evaluate the impact of environmental variables on its quality. The results revealed that the soil pH, mean temperature of the coldest quarter, mean diurnal range, precipitation of the warmest quarter and annual precipitation were the main factors affecting the current distribution of I. verum. The current area of suitable habitat is approximately 17.6 × 10⁴ km², accounting for 74% of the total area of Guangxi Province. Under the future climate scenarios, the overall pattern of the potential distribution range shifted northwards, and the SSP3126 scenario showed the most significant increase in the area. By utilizing comprehensive 2D chromatography technologies, 111 volatile compounds present in the 61 batches of star anise were identified. Further analysis via chemometric methods revealed that the components β-bisabolene, caryophyllene, 4-methoxyphenylacetone, cis-β-farnesene, anethole and linalool could serve as potential markers for distinguishing the quality of star anise from different geographical origins. Finally, a stepwise regression model between chemical compositions and environmental variables was established, and based on this, a quality zoning map was subsequently plotted. This study provides valuable scientific insights for resource conservation, planting site selection and quality control for star anise. Full article

Acorus calamus, a perennial emergent herb, is highly valued for its ornamental appeal, water purification ability, and medicinal properties. However, there is a significant contradiction between the rapidly increasing demand for A. calamus and the diminishing wild resources. Understanding its geographical distribution and the influence of global climate change on its geographical distribution is imperative for establishing a theoretical framework for the conservation of natural resources and the expansion of its cultivation. In this study, 266 distribution records of A. calamus and 18 selected key environmental factors were utilized to construct an optimal MaxEnt model via the ENMeval package. We simulated the potential geographical distributions under current conditions and under three different climate scenarios (SSP126, SSP370, and SSP585) in the 2050s, 2070s, and 2090s. Additionally, we employed the jackknife method and response curves to identify the environmental factors with the greatest influence on the distribution of A. calamus, and their response intervals. The results indicate that the regularization multiplier (RM) of 3.5 and the feature combinations (FC) of linear (L), quadratic (Q), hinge (H), and product (P) are the optimal model parameter combinations. With these parameters, the model predictions are highly accurate, and the consistency of the results is significant. The dominant environmental factors and their thresholds affecting the distribution of A. calamus are the precipitation of the wettest month (≥109.87 mm), human footprint (≥5.39), annual precipitation (≥388.56 mm), and mean diurnal range (≤12.83 °C). The primary land use types include rivers and channels, reservoirs and ponds, lakes, urban areas, marshes, other constructed lands, rice fields, forested areas, and shrublands. Under current climate conditions, the suitable geographical distribution of A. calamus in China is clearly located east of the 400 mm precipitation line, with high- and low-suitability areas covering 121.12 × 10⁴ km², and 164.20 × 10⁴ km², respectively. Under future climate conditions, both high- and low- suitability areas are projected to increase significantly, whereas unsuitable areas are expected to decrease, with the centroid of each suitability zone shifting northward. This study provides a theoretical foundation for sustainable utilization, future production planning, and the development of conservation strategies for wild germplasm resources of A. calamus. Full article