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With the increase in global temperature, the global change situation dominated by climate warming is becoming more and more serious. Climate change will cause differences in the suitable areas of species in different periods. Ginkgo biloba L., a rare and endangered wild plant protected at the national level in China, is the oldest relict plant in the world. Because of severe climate change, only China's wild Ginkgo biloba has been preserved, yet China's wild Ginkgo biloba population is facing extinction risk. Ginkgo biloba has rich ornamental value, application value, economic value, medicinal value and ecological value. Not only can it produce economic and ecological benefits, but it can also produce huge social benefits. Based on the data of Ginkgo biloba sample distribution, bioclimatic variables and soil variables, this paper uses the MaxEnt model to simulate Ginkgo biloba suitable area under current and future different climate scenarios, and analyzes the changes in the potential suitable area of Ginkgo biloba in the future through ArcGIS 10.6. The results are as follows: (1) the results simulated by the MaxEnt model are AUC > 0.9, showing that the simulation results have a high accuracy; (2) the min temperature of the coldest month, precipitation of the wettest month, elevation, and temperature seasonality are the main environmental variables affecting the change in the Ginkgo biloba suitable area; (3) under future climate scenarios, the suitable area of Ginkgo biloba is predicted to expand in the future, covering most of the south and some northeast regions, and moderate temperature and precipitation changes under climate change are conducive for the growth of Ginkgo biloba; and (4) in the future, the distribution center of the suitable area will move to the northeast. According to the conclusions in this paper, it is expected to provide theoretical reference for cultivation and management, sustainable utilization and solution of ecological environment problems of Ginkgo biloba. [ABSTRACT FROM AUTHOR]

Simple Summary: Identifying the risk regions of human–wildlife conflict is a pertinent topic in current human–wildlife conflict research. Most of the existing studies obtained their wildlife incident information through field surveys to identify risk regions. However, field surveys require a lot of personnel, time, and money. Therefore, they are generally used for meso- and microscale studies as they are difficult to apply to macroscale explorations. In this paper, we attempted to expand the data sources of wildlife incident information to enable macroscale wildlife incident risk region identification more efficiently and at a lower cost. We chose wild boar incidents in China as an example and used web crawling technology to obtain reports of wild boar incidents from internet databases. We then extracted the spatial location information of wild boar incidents from the reports. Subsequently, a system of environmental variables was constructed. Finally, the Maxent model, which provides predictions with higher accuracy and requires less location information, was applied to identify the risk regions of wild boar incidents in China. We observed that approximately 12.18% of China was at a high-risk level, mainly on the eastern side of the Huhuanyong Line. The risk of wild boar incidents was related to the climate, landscape, and topography as well as human disturbance. Variables such as the annual precipitation, GDP index, mean annual temperature, distance from forestland, distance from cultivated land, and elevation strongly influenced the risk of wild boar incidents. The objectives of this study were to identify the risk regions of wild boar incidents in China and to draw a risk map. Risk maps can be used to plan the prioritization of preventive measures, increasing management effectiveness from both a short- and a long-term perspective. We used a web crawler (web information access technology) to obtain reports of wild boar incidents from China's largest search engine (Baidu) and obtained 196 valid geographic locations of wild boar incidents from the reports. Subsequently, a system of environmental variables—with climate, topography, landscape, and human disturbance as the main variable types—was constructed, based on human–land-system thinking. Finally, the Maxent model was applied to predict the risk space of wild boar incidents in China by integrating the geographic location information for wild boar incidents with the environmental variables. We observed that the types of environmental variables that contributed to wild boar incidents were in the descending order of climate (40.5%) > human disturbance (25.2%) > landscape (24.4%) > topography (9.8%). Among the 14 environmental variables, annual precipitation, the GDP index, and the mean annual temperature were the main environmental variables. The distance from woodland, distance from cultivated land, and elevation were the secondary environmental variables. The response curves of the environmental variables demonstrated that the highest probability of wild boar incidents occurred when the annual average temperature was 16 °C, the annual precipitation was 800 mm, and the altitudes were 150 m and 1800 m. The probability of wild boar incidents decreased with an increase in the distance from cultivated and forested land, and increased sharply and then levelled off with an increase in the GDP index. Approximately 12.18% of China was identified as being at a high risk of wild boar incidents, mainly on the eastern side of the Huhuanyong Line. [ABSTRACT FROM AUTHOR]

Grasshoppers can greatly interfere with agriculture and husbandry, and they will breed and grow rapidly in suitable habitats. Therefore, it is necessary to extract the distribution of the grasshopper potential habitat (GPH), analyze the spatial-temporal characteristics of the GPH, and detect the different effects of key environmental factors in the meadow and typical steppe. To achieve the goal, this study took the two steppe types of Xilingol (the Inner Mongolia Autonomous Region of China) as the research object and coupled them with the MaxEnt and multisource remote sensing data to establish a model. First, the environmental factors, including meteorological, vegetation, topographic, and soil factors, that affect the developmental stages of grasshoppers were obtained. Secondly, the GPH associated with meadow and typical steppes from 2018 to 2022 were extracted based on the MaxEnt model. Then, the spatial-temporal characteristics of the GPHs were analyzed. Finally, the effects of the habitat factors in two steppe types were explored. The results demonstrated that the most suitable and moderately suitable areas were distributed mainly in the southern part of the meadow steppe and the eastern and southern parts of the typical steppe. Additionally, most areas in the town of Gaorihan, Honggeergaole, Jirengaole, as well as the border of Wulanhalage and Haoretugaole became more suitable for grasshoppers from 2018 to 2022. This paper also found that the soil temperature in the egg stage, the vegetation type, the soil type, and the precipitation amount in the nymph stage were significant factors both in the meadow and typical steppes. The slope and precipitation in the egg stage played more important roles in the typical steppe, whereas the aspect had a greater contribution to the meadow steppe. These findings can provide a methodical guide for grasshopper control and management and for further ensuring the security of agriculture and husbandry. [ABSTRACT FROM AUTHOR]

As one of the common mulberry tree species, Morus notabilis C. K. Schneid plays a significant role in various industries such as silkworm rearing, papermaking, and medicine due to its valuable mulberry leaves, fruits, and wood. This study utilizes the maximum entropy (MaxEnt) model to predict the potential distribution of M. notabilis in China under future environmental changes. By integrating the relative percentage contribution score of environmental factors with jackknife test analysis, important variables influencing the distribution of M. notabilis were identified along with their optimal values. The results indicate that Annual Precipitation (bio12), Precipitation of Driest Month (bio14), Min Temperature of Coldest Month (bio6), Temperature Annual Range (bio5–bio6) (bio7), Precipitation of Warmest Quarter (bio18), and Precipitation of Coldest Quarter (bio19) are the primary environmental variables affecting its potential distribution. Currently, M. notabilis exhibits high suitability over an area spanning 11,568 km2, while medium suitability covers 34,244 km2. Both current and future suitable areas for M. notabilis are predominantly concentrated in Sichuan, Yunnan, and Guizhou provinces, as well as Chongqing city in southwest China. Under the SSP5-8.5 scenario representing high greenhouse gas concentrations by 2050s and 2090s, there is an increase in high suitability area by 2952 km2 and 3440 km2, with growth rates reaching 25.52% and 29.74%, respectively. Notably, these two scenarios exhibit substantial expansion in suitable habitats for this species compared to others analyzed within this study period. [ABSTRACT FROM AUTHOR]

Simple Summary: Grasshoppers are among the most dangerous agricultural pests of China. However, the monitoring, prediction and control of grasshoppers are complex and difficult. Therefore, it is crucial to detect the key factors affecting the spatial distribution of grasshopper occurrence, understand the role of the environmental factors in grasshopper occurrence, and study whether different laws exist between different grass types. Here we conduct a species–environmental matching model integrated by Maxent model and remote sensing data to identify the spatial distribution of grasshopper occurrence in Inner Mongolia of China, analyze the related environmental variables and detect the most relevant environmental factors for grasshopper occurrence both in typical steppe and meadow steppe. Grasshoppers mainly threaten natural grassland vegetation and crops. Therefore, it is of great significance to understand the relationship between environmental factors and grasshopper occurrence. This paper studies the spatial distribution and key factors of grasshopper occurrence in two grass types by integrating a machine learning model (Maxent) and remote sensing data within the major grasshopper occurrence areas of Inner Mongolia, China. The modelling results demonstrate that the typical steppe has larger suitable area and more proportion for grasshopper living than meadow steppe. The soil type, above biomass, altitude and temperature mainly determine the grasshopper occurrence in typical steppe and meadow steppe. However, the contribution of these factors in the two grass types is significantly different. In addition, related vegetation and meteorological factors affect the different growing stages of grasshoppers between the two grass types. This study clearly defines the different effects of key environmental factors (meteorology, vegetation, soil and topography) for grasshopper occurrence in typical steppe and meadow steppe. It also provides a methodology to guide early warning and precautions for grasshopper pest prevention. The findings of this study will be helpful for future management measures, to ensure grass ecological environment security and the sustainable development of grassland. [ABSTRACT FROM AUTHOR]

Citrus medica L. var. sarcodactylis Swingle (Rutaceae: Citrus) is one of the traditional bulk Chinese medicinal materials in China with the effects of bacteriostasis, anti-inflammatory, anti-oxidation, anti-cancer cells, regulating the immun. In our paper, MaxEnt and ArcGIS were applied to simulate the suitable areas of C. medica L. var. sarcodactylis in China from the perspectives of bioclimate, soil, topographic factors and human activities Results showed that 1) temperature annual range (Bio7), annual precipitation (Bio12), human footprint (Hf), elevation (El) and precipitation seasonality (Bio15) were identified as the dominant environmental variables related to the distribution of C. medica L. var. sarcodactylis. The area of the total, most, moderately and poorly suitable habitat of C. medica L. var. sarcodactylis in China were 177.36×104 km², 22.27×104 km², 51.96×104 km² and 103.13×104 km² respectively. The range of the most suitable habitat was the narrowest, which was located in the middle east of Sichuan, western Chongqing in the upstream of the Yangtze River Basin, southern Guizhou and western Guangxi in the upstream of the Pearl River Basin, central and southern Yunnan and Southeast Tibet in the Middle-Lower reaches of the Southwest River Basin and western Taiwan. [ABSTRACT FROM AUTHOR]

Plague, a highly infectious disease caused by Yersinia pestis, has killed millions of people in history and is still active in the natural foci of the world nowadays. Understanding the spatiotemporal patterns of plague outbreaks in history is critically important, as it may help facilitate the prevention and control for potential future outbreaks. This study's objective was to estimate the effect of the topography, vegetation, climate, and other environmental factors on the Y. pestis ecological niche. A maximum entropy algorithm spatially modelled plague occurrence data from 2004--2018 and the environmental variables to evaluate the contribution of the variables to the distribution of Y. pestis. Our results found that the average minimum temperature in September (--8 °C to +5 °C) and the sheep population density (250 sheep per km2) were influential in characterising the niche. The rim of Qinghai Lake showed more favourable conditions for Y. pestis presence than other areas within the study area. Identifying various factors will assist any future modelling efforts. Our suitability map identifies hotspots and will help public health officials in resource allocation in their quest to abate future plague outbreaks. [ABSTRACT FROM AUTHOR]

Climate change is one of the biggest challenges to the world at present. Tomato is also suffered from devastating yield loss due to climate change. The domesticated tomato (Solanum lycopersicum) is presumed to be originated from the wild tomato (S. pimpinellifolium). In this study, we compared the climate data of S. pimpinellifollium with the domesticated tomato, predicted the suitable regions of S. pimpinellifollium in China using MaxEnt model and assessed their tolerance to drought stress. We found that the predicted suitable regions of wild tomato are highly consistent with the current cultivated regions of domesticated tomato, suggesting that the habitat demand of domesticated tomato descended largely from its ancestor, hence the habitat information of wild tomato could provide a reference for tomato cultivation. We further predicted suitable regions of wild tomato in the future in China. Finally, we found that while average drought tolerance between wild and domesticated tomato accessions shows no difference, tolerance levels among wild tomato accessions exhibit higher variation, which could be used for future breeding to improve drought resistance. To summarize, our study shows that suitable regions of wild tomato provide insights into domesticated tomato cultivation in China. [ABSTRACT FROM AUTHOR]

Ambrosia trifida is an invasive alien plant species, which has very high reproductive and environmental adaptability. Through strong resource acquisition ability and allelopathy, it could inhibit the growth and reproduction of surrounding plants and destroy the stability of an invasive ecosystem. It is very important to predict the change of suitable distribution area of A. trifida with climate change before implementing scientific control measures. Based on 106 A. trifida distribution data and 14 points of environmental data, the optimal parameter combination (RM = 0.1, FC = LQ) was obtained using the MaxEnt (version 3.4.1) model optimized by Kuenm package, and thus the potential suitable areas of A. trifida in Northeast China under three different climate scenarios (RCP2.6, RCP4.5, RCP8.5) with different emission intensities in the future (2050, 2070) were predicted. The changes of A. trifida suitable area in Northeast China under three climate scenarios were compared, and the relationship between the change of suitable area and emission intensity was analyzed. In general, the suitable area of A. trifida in Northeast China will expand gradually in the future, and the area of its highly suitable area will also increase with the increasing emission intensity, which is unfavorable to the control of A. trifida. [ABSTRACT FROM AUTHOR]

Simple Summary: Carposina coreana Kim is the most serious pest of Cornus officinalis. In recent years, its damage to C. officinalis has become increasingly serious, causing enormous economic losses in China. Here, the maximum entropy (MaxEnt) model was used to predict the distribution of C. coreana under current climate scenarios and future climate scenarios in China with ArcGIS software. Suitable areas for C. coreana under the current climate scenarios were mainly distributed in central China, and the highly suitable areas were distributed in southern Shaanxi, southwestern Henan, and northwestern Hubei. Under future climate scenarios, the boundaries of the suitable areas for C. coreana tended to shift to northern China. Given the predictive results of this study, we can clearly see the future diffusion trend of C. coreana in China, which has important theoretical significance for the control of this pest in China. Carposina coreana is an important pest of Cornus officinalis, distributed in China, Korea, and Japan. In recent years, its damage to C. officinalis has become increasingly serious, causing enormous economic losses in China. This study and prediction of current and future suitable habitats for C. coreana in China can provide an important reference for the monitoring, early warning, prevention, and control of the pest. In this study, the potential distributions of C. coreana in China under current climate and future climate models were predicted using the maximum entropy (MaxEnt) model with ArcGIS software. The distribution point data of C. coreana were screened using the buffer screening method. Nineteen environmental variables were screened using the knife-cut method and variable correlation analysis. The parameters of the MaxEnt model were optimized using the kuenm package in R software. The MaxEnt model, combined with key environmental variables, was used to predict the distribution range of the suitable area for C. coreana under the current (1971–2000) and four future scenarios. The buffer screening method screened data from 41 distribution points that could be used for modeling. The main factors affecting the distribution of C. coreana were precipitation in the driest month (Bio14), precipitation in the warmest quarter (Bio18), precipitation in the coldest quarter (Bio19), the standard deviation of seasonal variation of temperature (Bio4), minimum temperature in the coldest month (Bio6), and average temperature in the coldest quarter (Bio11). The feature class (FC) after the kuenm package optimization was a Q-quadratic T-threshold combination, and the regularization multiplier (RM) was 0.8. The suitable areas for C. coreana under the current climate model were mainly distributed in central China, and the highly suitable areas were distributed in southern Shaanxi, southwestern Henan, and northwestern Hubei. The lowest temperature in the coldest month (Bio6), the average temperature in the coldest quarter (Bio11), and the precipitation in the warmest quarter (Bio18) all had good predictive ability. In future climate scenarios, the boundary of the suitable area for C. coreana in China is expected to shift northward, and thus, most of the future climate scenarios would shift northward. [ABSTRACT FROM AUTHOR]

Changes in climate and environmental conditions have aggravated the severity and unpredictability of plant survival and growth. Cunninghamia lanceolata (Lamb.) Hook. is an economically important timber tree. Exploring its potential distribution and dynamic changes and identifying the leading environmental variables affecting it will help to adjust the planting range reasonably according to the habits and climate change, thus contributing to its survival and growth. Based on the MaxEnt model and ArcGIS tool, climate, soil, terrain, human activities, variable environment layers, and 395 C. lanceolata distribution points were used to simulate and analyze the geographical distribution characteristics of C. lanceolata in the current and future periods (the 2050s and 2070s) under RCP2.6, RCP4.5, RCP6.0, and RCP8.5. The results showed that C. lanceolata was suitable to grow in a subtropical monsoon climate with warm, humid, abundant rainfall and a relatively gentle topography. Additionally, using percent contribution, permutation importance, and the knife-cutting test, we noted that the annual precipitation (Bio12), human activities (Hfp), minimum temperature of the coldest month (Bio6), mean temperature of the coldest quarter (Bio11), precipitation of coldest quarter (Bio19), annual temperature range (Bio7), and elevation were the leading environmental factors affecting the geographical distribution of C. lanceolata. Among them, it should be noted that the impact of human activities was negatively correlated with suitable habitat areas of C. lanceolata and led to the degeneration of suitable habitats and fragmentized distribution. In addition, predictions have shown that the areas of habitats under other scenarios will be characterized by an increasing and then decreasing trend by the 2050s and 2070s, except for the RCP2.6 scenario, under which the suitable habitats area of C. lanceolata will increase continuously. The core distributional shifts showed that the suitable habitats of C. lanceolata will gradually shift and migrate to high-latitude areas due to global warming. This study focused on the characteristics of suitable habitats of C. lanceolata under different climatic scenarios using more environmental factors and scenarios than before, aiming to provide a theoretical basis and guidance for the management and utilization of forest resources, the planning of suitable planting areas, and germplasm protection. [ABSTRACT FROM AUTHOR]

In recent decades, ecological niche models (ENMs) have been widely used to predict suitable habitats for species. However, for invasive organisms, the prediction accuracy is unclear. In this study, we employed the most widely used maximum entropy (MaxEnt) model and ensemble model (EM) Biomod2 and verified the practical effectiveness of the ENM in predicting the distribution areas of invasive insects based on the true occurrence of Hyphantria cunea in China. The results showed that when only limited data of invasive areas were used, the two ENMs could not effectively predict the distribution of suitable habitats of H. cunea, although the use of global data can greatly improve the prediction accuracy of ENMs. When analyzing the same data, Biomod2's prediction accuracy was significantly better than that of MaxEnt. For long‐term predictions, the area of suitable habitat predicted by the ENMs was much greater than the occurrence area; for short‐term predictions, the accuracy of the predicted area was significantly improved. Under the current conditions, the area of suitable habitat for H. cunea in China is 118 × 104 km2, of which 59.32% is moderately or highly suitable habitat. Future climate change could significantly increase the suitable habitat area of H. cunea in China, and the predicted area of suitable habitats in all climate scenarios exceeded 355 × 104 km2, accounting for 36.98% of the total land area in China. This study demonstrates the use of ENMs to study invasive insects and provides a reference for the management of H. cunea in China. [ABSTRACT FROM AUTHOR]

Grasshoppers have profound effects on both grassland ecosystems and livestock production. Despite commendable efforts made by China in grasshopper control, completely eradicating or preventing them still remains a distant prospect. This study aims to analyze the ecological distribution and patterns of grasshopper occurrences in order to provide more accurate monitoring techniques and preventive measures. By considering four types of environmental determinants—meteorology, vegetation, soil, and topography—we systematically identified 18 key influencing factors. These factors encompass various developmental stages of grasshoppers, including variables such as temperature, precipitation, vegetation coverage, vegetation type, soil moisture, soil salinity, soil type, and terrain characteristics. The MaxEnt model is employed in this study to comprehensively capture complex ecological interactions. Omission curves, Receiver Operating Characteristic curves (ROC curves), and the Area Under the Curve (AUC values) demonstrate the robustness and high accuracy of the MaxEnt model. Our research results indicate that meteorological factors are the primary influencing factors for the distribution of grasshoppers, surpassing the effects of vegetation, soil, and terrain. Precipitation and vegetation type emerge as key factors shaping their distributional patterns. Integrating the Sen-MK trend method, our findings identify the epicenter of damage primarily within the central, southern, and northeastern regions, notably affecting locales such as New Barag East County and the Ewenki Autonomous Banner. While their impact in 2012 was particularly severe, temporal trends indicate a decreasing risk of grasshoppers in specific regions, with escalated activity observed in other areas. The empirical insights from this study lay a solid foundation for the development of monitoring and control strategies concerning grasshoppers. Furthermore, the derived theoretical framework serves as a valuable foundation for future research endeavors addressing grasshopper infestations. [ABSTRACT FROM AUTHOR]

Simple Summary: The critically endangered Siberian crane (Grus leucogeranus) relies on Poyang Lake's wetlands in China for wintering. Rapid changes in these wetlands, driven by climate shifts and human activities, affect habitat and food availability for these birds. Our study investigated Poyang Lake's hydrological dynamics over the past two decades and assessed the impact of related variables on crane populations. Employing advanced modeling, we predicted how varying water levels influence suitable habitats for Siberian cranes. Our findings revealed that a summer-inundated area exerted a notable influence on population fluctuations in crane species in the natural habitats of Poyang Lake. The scarcity of food, resulting from summer floods, compels cranes to adapt by exploring alternative food sources and new foraging grounds, including artificial habitats. During the dry season, the size of the inundated area primarily impacts the food availability for Siberian cranes, thereby influencing both their population size and distribution pattern, and a moderate water level of 8–10 m provides the highest amount of good habitat. Persistent winter droughts exacerbate the unsuitability of habitats, and the shortage of food in natural habitats may become a recurring occurrence in the future. This study emphasizes the importance of managing both natural and artificial habitats to support Siberian crane conservation amid environmental changes. To assess the Siberian crane (Grus leucogeranus)'s response to changing water levels and habitat quality at Poyang Lake, we analyzed the lake's hydrological trends over the past two decades with the Mann-Kendall and Sen slope methods. Additionally, we explored the link between the crane population size and hydrological conditions at the lake from 2011 to 2019. Meanwhile, five environmental factors, including habitat type, distance from shallow lakes, human footprint index, elevation and normalized vegetation index were selected, and the distribution patterns of suitable habitats for the Siberian crane under 10 water level gradients with intervals of about 1 m (5.3–14.2 m) were simulated by using an improved habitat suitability index model that determines the weights of evaluating factors based on the MaxEnt model. The results showed that the overall trend of the inundated area in Poyang Lake was shrinking in the last 20 years, with a significant increase in the area of exposed floodland during the early wintering period (Z = −2.26). The prolonged drought resulting from this will force vegetation succession, thereby diminishing the food resources for cranes in their natural habitat. The mean inundated area in June demonstrated a significant negative correlation with the population of Siberian cranes in natural habitats (r = −0.75, p = 0.02). Shortage of the Siberian crane-preferred Vallisneria tuber due to June flooding was the primary driver of the crane's altered foraging strategy and habitat shift. In years with relatively normal June inundation, indicating abundant Vallisneria resources, the relationship between the inundated area during the dry season and the crane population fit well, with a quadratic curve (R2 = 0.92, p = 0.02). The dry season's inundated area primarily affected the crane population and distribution pattern by influencing the availability of food resources, and both excessive and insufficient inundation areas were unfavorable for crane survival. The modeling results for habitat suitability indicated that as the water level decreased, the trend of the area of good habitat for the Siberian crane showed an inverted bell shape, peaking at a water level of 8.8 m, with optimal conditions occurring between 8 and 10 m. The combined effects of climate and human activities have made the shortage of food resources in Poyang Lake the new normal. The degradation of natural habitats has led to a decline in the quality of Siberian crane habitats, and artificial habitats can only be used as refuges to a certain extent. Thus, formulating strategies to restore natural habitats and enhance the management of artificial habitats is crucial for the conservation efforts of Siberian cranes. [ABSTRACT FROM AUTHOR]

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The longicorn beetle Monochamus saltuarius (Coleoptera; Cerambycidae) is an insect vector that transmits the pine wood nematode Bursaphelenchus xylophilus, a serious issue in pine forests in China, Japan, and South Korea. Dastarcus helophoroides and Scleroderma guani are effective in controlling M. saltuarius. However, the application of these parasites for the direct control of vector insects requires detailed analyses of the suitability of the selected natural enemies in potential pest areas, particularly under climate change. Based on species distribution records as well as the current and projected climate change trends up to 2050, we utilized an optimized Maxent algorithm to predict the potential distribution patterns of M. saltuarius and its natural enemies in China. Furthermore, we estimated Schoener's D to quantify the overlap in adaptability between M. saltuarius and its natural enemies. The potentially suitable areas predicted under the current climate conditions were concentrated mainly in northeast and north China. Additional suitable areas were detected in central, eastern, northwestern, and southwestern China. Under future climate conditions, the suitable range of M. saltuarius gradually shifted southward, with a tendency to expand into high-altitude and colder regions, such as Sichuan, Qinghai, and Tibet. The potential distribution of the natural enemies D. helophoroides and S. guani continued to expand under climate change. A comparison of the appropriate habitats of M. saltuarius and natural enemy insects indicated that D. helophoroides is more suitable for initial biological control in north, northeast, and central China as well as certain northwest and coastal regions. S. guani could be prioritized for nationwide release, while joint control using both species may be effective in Liaoning, Hebei, and Tianjin provinces. These analyses demonstrate that future climate change is likely to exert adverse effects on the potential distribution of M. saltuarius but is favorable for the potential distributions of natural enemies. This study offers important insights into the effective control of M. saltuarius and provides an experimental basis for the utilization of natural enemies according to the characteristics of different regions. [ABSTRACT FROM AUTHOR]

The Alligator Gar (Atractosteus spatula) is a very dangerous species that has an extremely destructive impact on the ecological environment in aquatic areas. As a kind of ornamental fish, it is spreading rapidly all over the world. In order to avoid or delay the spread of Alligator Gar in China, it is urgent to further monitor and clarify its distribution range within the country. In this study, a maximum entropy model (MaxEnt) and geographical information system (ArcGIS) were used to identify suitable regions under climate change scenarios in China, and the significance of environmental factors that shape this species' distribution were evaluated. According to the geographical distribution data of Alligator Gar and selected environmental variables, the potential habitat area of Chinese Alligator Gar under four climate scenarios in the present (2000s) and future (2050s and 2070s) was predicted. (1) The main environmental variables affecting the potential geographical distribution of Alligator Gar are temperature factor variables (the mean temperature of the warmest quarter and the mean temperature of the coldest quarter), precipitation factor variables (precipitation in the driest month and in the driest quarter), and altitude. (2) Under the current climate conditions, the suitable breeding areas of Alligator Gar are mainly concentrated in the Guangxi Zhuang Autonomous Region, Guangdong Province, and Hainan Province. Under the four future climate scenarios, the distribution area of the total suitable area of Alligator Gar will gradually decrease, and the suitable area of Alligator Gar will spread to high latitudes. [ABSTRACT FROM AUTHOR]

During the past two decades discussions on urban shrinkage have been increasing in intensity, mainly due to the irresistible trends of migration, economic transformation, and the so-called "siphon effect" of large and mega cities. Yet, very few studies have tried to understand urban shrinkage from the perspective of local microscopic unit evolution. This study develops a novel model for simultaneous simulation of expansion and shrinkage (MSSES) of urban built-up areas. Starting from a microscopic basis, our MSSES can simulate both the processes and the states that lead to spatial expansion or shrinkage. A MaxEnt model is further used to investigate the driving factors of microspatial changes and compute the probabilities of shrinkage (or expansion) of urban built-up areas. Finally, it simulates the explicit layout of the spatial distribution of shrinkage (or expansion) patches with the help of a sorting cellular automata (CA) model. The validity of MSSES is verified using multisourced data from the Wuhan agglomeration, China. We show that (1) MSSES can more accurately simulate urban expansion or shrinkage than the currently widely used neighborhood-based Logistic-CA (NL-CA) and (2) MSSES has advantage in solving the commonly seen problem of "diffusion-coalescence," especially for the simulation of outlying expansion. Against the context of the Wuhan metropolitan area, we also found that overall the shrinkage trend is slowing down significantly, presenting three types of shrinkage at city-scale: remote shrinkage, peripheral shrinkage, and international shrinkage. Our study has contributions to the body of knowledge as well as practical implications for urban management and improving the sustainable development of urban areas in both China and abroad. The city we live in may be experiencing a situation where expansion and shrinkage are happening simultaneously. Hence, the simulation and prediction of temporal and spatial changes in urban expansion and shrinkage hold great importance in formulating urban policies. In this study, we propose a model capable of simultaneously predicting urban growth and shrinkage, and apply this model to the urban morphological changes in the Wuhan metropolitan area from 2000 to 2035. The simulation results demonstrate the effectiveness of this model in predicting the locations of urban expansion and contraction in advance. Furthermore, we discovered that the overall shrinkage trend is projected to significantly decelerate in the future. These findings offer support for intervention in urban planning, guiding the development of urban spaces and advancing the scientific aspects of urban planning. [ABSTRACT FROM AUTHOR]

Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126‐2090s scenario and the highest under the SSP585‐2090s scenario. [ABSTRACT FROM AUTHOR]

Climate change has dramatic impacts on the growth and the geographical distribution of tea (Camellia sinensis L.). Assessing the potential distribution of tea will help decision makers to formulate appropriate adaptation measures to use the altered climatic resources and avoid the damage from climate hazards. The objective in this study is to model the current and future distribution of tea species based on the four SSPs scenarios using the MaxEnt model in China. For the modeling procedure, tea growth records in 410 sites and 9 climate variables were used in this paper. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the performance of the model. The AUC value was over 0.9 in this study, showing the excellent simulation result of the model. In relation to the current distribution, areas of 82.01 × 104 km2 (8.51% of total land area in China), 115.97 × 104 km2 (12.03% of total land area in China), and 67.14 × 104 km2 (6.97% of total land area in China) were recognized as Marginal, Medium, and Optimal climate suitable habitats for tea over China. Compared to the current distribution, most of the Optimal suitability areas in southeast China would be lost in four scenarios. The area of Marginal and Medium suitable habitats would expand in SSP370 and SSP585, especially in 2041–2061 and 2081–2100. The suitable area of tea would expand northwards and westwards, suggesting that additional new suitable habitats could be created for tea production with the future climate change, especially in Shandong, Henan, Guizhou, and Yunnan Provinces. This research would provide vital scientific understanding for policy making on tea production, tea garden site chosen and adopyion of adaptation methods in the future. [ABSTRACT FROM AUTHOR]

Simple Summary: Cicadella viridis is a polyphagous pest that feeds on plant sap. During its feeding or oviposition periods, C. viridis can cause significant economic losses to fruit trees, willows, and rice crops. This study utilized the maximum entropy (MaxEnt) model in species distribution modeling to predict the potential suitable distribution of C. viridis in China. The results indicate that climate change has had a significant impact on the geographic distribution of the leafhopper, particularly by reducing the high and moderate suitability zones (except for the RCP8.5 scenario in the 2090s). Furthermore, an analysis of several key environmental variables revealed that temperature and precipitation may be important influencing factors in the selection of suitable habitats for the leafhopper. This study provides important guidance for the future development of effective monitoring and control methods for C. viridis. Cicadella viridis (Hemiptera: Cicadellidae) is an omnivorous leafhopper that feeds on plant sap. It significantly reduces the yield of agricultural and forestry crops while feeding or ovipositing on the host plant. In recent years, the rapid expansion of C. viridis has posed a serious threat to agricultural and forestry crops. To study the impact of climate change on the geographical distribution of the leafhopper, the maximum entropy (MaxEnt) model and ArcGIS software, combined with 253 geographic distribution records of the pest and 24 environmental variables, were used, for the first time, to predict the potential distribution of C. viridis in China under conditions of climatic change. The results showed that the currently suitable areas for C. viridis are 29.06–43° N, 65.25–85.15° E, and 93.45–128.85° E, with an estimated area of 11,231,423.79 km2, i.e., 11.66% of China. The Loess Plateau, the North China Plain, and the Shandong Peninsula are the main suitable areas. The potential distribution of the leafhopper for the high and medium suitability areas decreased under each climate scenario (except RCP8.5 in the 2090s). Several key variables that have the most significant effect on the distribution of C. viridis were identified, including the mean annual temperature (Bio1), the standard deviation of temperature seasonality (Bio4), the minimum temperature of the coldest month (Bio6), and the precipitation of the coldest quarter (Bio19). Our research provides important guidance for developing effective monitoring and pest control methods for C. viridis, given the predicted challenges of altered pest dynamics related to future climate change. [ABSTRACT FROM AUTHOR]

In the context of global change, land cover change is significantly influenced by human activities. However, there is limited knowledge about the potential economic and ecological benefits that land cover change on the Ruoergai Plateau will bring by 2035, considering the existing development plans. In our study, the CLUMondo model was improved by integrating the MaxEnt model and Boltzmann entropy and used to predict the structure and intensity of land change in China's Ruoergai Plateau. The results show that the model integrated with MaxEnt and Boltzmann entropy is the most accurate in four contrasting experiments that have a Kappa of 0.773. The predicted results show that with the increase in the demand for ecological benefits, the total area of the water area shows a clear increasing trend. With 0.25% GDP growth, the water area is about 178 km2. With 2.5% GEP growth, the water area is about 202 km2. The latter is 24 km2 more than the former, an increase of about 13.6%. With the increase in the demand for economic benefits, the total area of construction land shows a clear increasing trend. Grassland, forest, and cropland are partly converted into construction land, because of the higher economic benefits of construction land. At the same time, the density of construction land will increase. With 12.6% GDP growth, the high-density construction area is about 399 km2. With 126.1% GEP growth, the water area is about 761 km2. High-density construction land increased by 90.7% (about 362 km2). In the low elevation area near the mountains of Ruoergai County, a new concentration of construction land will appear. The simulation results are of great significance for guiding ecological protection and urban construction in Ruoergai. [ABSTRACT FROM AUTHOR]

Simple Summary: Sclerodermus sichuanensis is a natural enemy of the longicorn beetle and has biological control value, and its habitat area was studied. In this work, we simulated the current distribution of S. sichuanensis in China using the Maxent model and ArcGIS software and predicted its distribution in different future periods. The results showed that the Mean Diurnal Range (bio2), Min Temperature of Coldest Month (bio6), Precision of Warmest Quarter (bio18), and Max Temperature of Warmest Month (bio5) were the key environmental variables affecting the distribution of S. sichuanensis. Southwest China, represented by Sichuan, Chongqing, Guizhou, and part of North China, are the main concentrations of the current high suitability areas of S. sichuanensis. The moderately suitable areas are concentrated in South China and Central China. Most of the high and middle appropriate areas belong to subtropical monsoon climate and temperate monsoon climate. In one of the future periods, the suitable area will be significantly expanded to North and Northwest China, with a total area increase of 81,295 km2. This study provides an essential reference for future research on S. sichuanensis and the application of forestry pest control. Sclerodermus sichuanensis is the natural enemy of the longicorn beetle due to its strong attack ability and high parasitic rate. Its good resistance and fecundity make it have significant biological control value. The Maxent model and ArcGIS software were used to simulate the current distribution of S. sichuanensis in China by combining the known distribution information and environmental variables and predict the suitable area of the 2050s (2041–2060) and 2090s (2081–2000) under three climate scenarios (SSP1-2.6, SSP2-4.5. and SSP5-8.5). The results showed that the Mean Diurnal Range (bio2), Min Temperature of the Coldest Month (bio6), Precipitation of the Warmest Quarter (bio18), and Max Temperature of the Warmest Month (bio5) were the key environmental variables affecting the distribution of S. sichuanensis. Southwest China and part of North China are the main concentrations of the current high-suitability areas of S. sichuanensis. The moderately suitable areas are concentrated in South China and Central China. Under the SSP5-8.5 scenario, the suitable area predicted in the 2050s will expand significantly to North China and Northwest China, with a total increase of 81,295 km2. This work provides an essential reference for future research on S. sichuanensis and the application of forestry pest control. [ABSTRACT FROM AUTHOR]

Background: Cryptosporidiosis is a zoonotic intestinal infectious disease caused by Cryptosporidium spp., and its transmission is highly influenced by climate factors. In the present study, the potential spatial distribution of Cryptosporidium in China was predicted based on ecological niche models for cryptosporidiosis epidemic risk warning and prevention and control. Methods: The applicability of existing Cryptosporidium presence points in ENM analysis was investigated based on data from monitoring sites in 2011–2019. Cryptosporidium occurrence data for China and neighboring countries were extracted and used to construct the ENMs, namely Maxent, Bioclim, Domain, and Garp. Models were evaluated based on Receiver Operating Characteristic curve, Kappa, and True Skill Statistic coefficients. The best model was constructed using Cryptosporidium data and climate variables during 1986‒2010, and used to analyze the effects of climate factors on Cryptosporidium distribution. The climate variables for the period 2011‒2100 were projected to the simulation results to predict the ecological adaptability and potential distribution of Cryptosporidium in future in China. Results: The Maxent model (AUC = 0.95, maximum Kappa = 0.91, maximum TSS = 1.00) fit better than the other three models and was thus considered the best ENM for predicting Cryptosporidium habitat suitability. The major suitable habitats for human-derived Cryptosporidium in China were located in some high-population density areas, especially in the middle and lower reaches of the Yangtze River, the lower reaches of the Yellow River, and the Huai and the Pearl River Basins (cloglog value of habitat suitability > 0.9). Under future climate change, non-suitable habitats for Cryptosporidium will shrink, while highly suitable habitats will expand significantly (χ2 = 76.641, P < 0.01; χ2 = 86.836, P < 0.01), and the main changes will likely be concentrated in the northeastern, southwestern, and northwestern regions. Conclusions: The Maxent model is applicable in prediction of Cryptosporidium habitat suitability and can achieve excellent simulation results. These results suggest a current high risk of transmission and significant pressure for cryptosporidiosis prevention and control in China. Against a future climate change background, Cryptosporidium may gain more suitable habitats within China. Constructing a national surveillance network could facilitate further elucidation of the epidemiological trends and transmission patterns of cryptosporidiosis, and mitigate the associated epidemic and outbreak risks. [ABSTRACT FROM AUTHOR]

Planting suitability determines the distribution and yield of crops in a given region which can be greatly affected by climate change. In recent years, many studies have shown that carbon dioxide fertilization effects increase the productivity of temperate deciduous fruit trees under a changing climate, but the potential risks to fruit tree planting caused by a reduction in suitable planting areas are rarely reported. In this study, Maxent was first used to investigate the spatial distribution of five Pyrus species in China, and the consistency between the actual production area and the modeled climatically suitable area under the current climatic conditions were determined. In addition, based on Coupled Model Intercomparison Project Phase 6, three climate models were used to simulate the change in suitable area and the migration trend for different species under different emission scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5). The results showed that the suitable area for pear was highly consistent with the actual main production area under current climate conditions. The potential planting areas of P. ussuriensis showed a downward trend under all emission paths from 2020 to 2100; other species showed a trend of increasing first and then decreasing or slowing down and this growth effect was the most obvious in 2020–2040. Except for P. pashia, other species showed a migration trend toward a high latitude, and the trend was more prominent under the high emission path. Our results emphasize the response difference between species to climate change, and the method of consistency analysis between suitable planting area and actual production regions cannot only evaluate the potential planting risk but also provide a reasonable idea for the accuracy test of the modeled results. This work has certain guiding and reference significance for the protection of pear germplasm resources and the prediction of yield. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, in order to understand the distribution and optimal living environment of Quasipaa spinosa in China, we made predictions about the impacts of different environmental climates on its habitat. Our results show that our model is highly reliable. The mountainous areas in southern China with sufficient water supply are the main suitable areas for this species. The future reduction in emission concentration will be friendly to the ecological environment in the suitable areas of this species, better protecting the reproduction of its natural population. Quasipaa spinosa is a large cold-water frog unique to China, with great ecological and economic value. In recent years, due to the impact of human activities on the climate, its habitat has been destroyed, resulting in a sharp decline in natural population resources. Based on the existing distribution records of Q. spinosa, this study uses the optimized MaxEnt model and ArcGis 10.2 software to screen out 10 factors such as climate and altitude to predict its future potential distribution area because of climate change. The results show that when the parameters are FC = LQHP and RM = 3, the MaxEnt model is optimal and AUC values are greater than 0.95. The precipitation of the driest month (bio14), temperature seasonality (bio4), elevation (ele), isothermality (bio3), and the minimum temperature of coldest month (bio6) were the main environmental factors affecting the potential range of the Q. spinosa. At present, high-suitability areas are mainly in the Hunan, Fujian, Jiangxi, Chongqing, Guizhou, Anhui, and Sichuan provinces of China. In the future, the potential distribution area of Q. spinosa may gradually extend to the northwest and north. The low-concentration emissions scenario in the future can increase the area of suitable habitat for Q. spinosa and slow down the reduction in the amount of high-suitability areas to a certain extent. In conclusion, the habitat of Q. spinosa is mainly distributed in southern China. Because of global climate change, the high-altitude mountainous areas in southern China with abundant water resources may be the main potential habitat area of Q. spinosa. Predicting the changes in the distribution patterns of Q. spinosa can better help us understand the biogeography of Q. spinosa and develop conservation strategies to minimize the impacts of climate change. [ABSTRACT FROM AUTHOR]

The Asian elephant (Elephas maximus Linnaeus) is a globally endangered species, an internationally protected species, and a first-class protected animal in China. However, future climate change and human activities exacerbate the instability of its habitat range, leading to a possible reduction in the range. By using multi-source remote sensing data and products, as well as climate change models, including ASTER GDEM v3, Landsat8 OLI image and ClimateAP, we examined the effects of ecological factors related to climate and natural and anthropogenic influences on the distribution of Asian elephants in Sipsongpanna. Multiyear elephant field tracking data were used with a MaxEnt species distribution model and the climate model. First, the distribution of Asian elephants in potentially suitable areas in Sipsongpanna was simulated under current climatic conditions without considering human activities. The predicted distribution was verified by existing Asian elephant migration trajectories. Subsequently, the distribution of potentially suitable areas for Asian elephants in Sipsongpanna was simulated under two climate change scenarios (RCP4.5, RCP8.5) in three periods (2025, 2055, and 2085). The changes in potentially suitable areas for Asian elephants in Sipsongpanna were analyzed under multiple climate change scenarios for the current (2017) and different future periods by considering the effects of human activities. The results show the following: (1) under anthropogenic interference (AI), the optimal MaxEnt model has a high prediction accuracy with the area under the curve (AUC) of 0.913. The feature combination (FC) includes linear, quadratic, and threshold features, and the regularization multiplier (RM) is 2.1. (2) Jackknife analyses of the non-anthropogenic interference (NAI) and anthropogenic interference (AI) scenarios indicate that topography (altitude (Alt)), temperature (mean warmest month temperature (MWMT)), and precipitation (mean annual precipitation (MAP)) are the top three factors influencing the distribution of Asian elephants. (3) The total area suitable for Asian elephants under current climate conditions and AI accounts for 46.35% of the total area. Areas of high suitability (occurrence probability >0.5) are located in Jinghong City in central Sipsongpanna and Mengla County in southeastern Sipsongpanna. Among them, the minimum habitat range and ecological corridors are mainly located in Mengman Town, Mohan Town, Mengla Town, Mengban Township, Dadugang Township, and Mengwang Township. (4) The change in potentially suitable areas for Asian elephants between current and future conditions is small under AI and large under undisturbed conditions. [ABSTRACT FROM AUTHOR]

Habitat fragmentation is considered a major threat to biodiversity worldwide. Two endangered species, the blood pheasant (Ithaginis cruentus) and the blue eared pheasant (Crossoptilon auritum), co-exist in a fragmented forest in the Qilian Mountains. However, how their habitats react to the fragmenting landscape remains unclear. Therefore, we carried out a field survey in the core habitat of the two species in Qilian Mountains National Park and used the MaxEnt Model to predict their potential distribution and to assess the protection efficiency. Then, we utilized a modified within-patch fragmentation categorizing model to identify how their functional fragmentations differentiated. The results showed that the habitat utilization of the two pheasant species was significantly different, with a potential distribution area of 18,281 km2 for the blood pheasant and 43,223 km2 for the blue eared pheasant. The habitat of the blue eared pheasant is highly fragmented with 27.7% categorized as 'Interior' and 49.3% as 'Edge', while the habitat of the blood pheasant is more severe with 2.1% categorized as 'Interior' and 50.4% as 'Edge'. Analysis shows that large areas of habitat for the two pheasants remain unprotected by the Qilian Mountains National Park. The intense grazing and human infrastructure may have a large effect on the currently highly fragmented landscape. Future measurements are needed to alleviate this conflict. [ABSTRACT FROM AUTHOR]

Ephedra sinica Stapf is an important traditional medicinal plant. However, in recent years, due to climate change and human activities, its habitat area and distribution area have been decreasing sharply. In order to provide better protection for E. sinica, it is necessary to study the historical and future potential zoning of E. sinica. The maximum entropy model (MaxEnt) was used to simulate the potential geographical distribution patterns of E. sinica under historical and future climatic conditions simulated using two Shared Socio-economic Pathways. The main results were also analyzed using the jackknife method and ArcGIS. The results showed that: (1) the potential suitable distribution area of E. sinica in China is about 29.18 × 105 km2—high-suitable areas, medium-suitable areas, and low-suitable areas cover 6.38 × 105 km2, 8.62 × 105 km2, 14.18 × 105 km2, respectively—and E. sinica is mainly distributed in Inner Mongolia; (2) precipitation and temperature contribute more to the distribution of E. sinica; (3) under two kinds of SSPs, the total suitable area of E. sinica increased significantly, but the differences between 2021–2040, 2041–2060, 2061–2080, and 2081–2100 are not obvious; (4) the barycentre of E. sinica moves from the historical position to its southwest. The results show that E. sinica can easily adapt to future climates well, and its ecological value will become more important. This study provides scientific guidance for the protection, management, renewal and maintenance of E. sinica. [ABSTRACT FROM AUTHOR]

Association is the basic unit of plant community classification. Exploring the distribution of plant associations can help improve our understanding of biodiversity conservation. Different associations depend on different habitats and studying the association level is important for ecological restoration, regional ecological protection, regulating the ecological balance, and maintaining biodiversity. However, previous studies have only focused on suitable distribution areas for species and not on the distribution of plant associations. Larix gmelinii is a sensitive and abundant species that occurs along the southern margin of the Eurasian boreal forests, and its distribution is closely related to permafrost. In this study, 420 original plots of L. gmelinii forests were investigated. We used a Maxent model and the ArcGIS software to project the potential geographical distribution of L. gmelinii associations in the future (by 2050 and 2070) according to the climate scenarios RCP 2.6, RCP 4.5, and RCP 8.5. We used the multi‐classification logistic regression analysis method to obtain the response of the suitable area change for the L. gmelinii alliance and associations to climate change under different climate scenarios. Results revealed that temperature is the most crucial factor affecting the distribution of L. gmelinii forests and most of its associations under different climate scenarios. Suitable areas for each association type are shrinking by varying degrees, especially due to habitat loss at high altitudes in special terrains. Different L. gmelinii associations should have different management measures based on the site conditions, composition structure, growth, development, and renewal succession trends. Subsequent research should consider data on biological factors to obtain more accurate prediction results. [ABSTRACT FROM AUTHOR]

Simple Summary: How to realize the sustainability of economic development and animal protection is a significant problem faced by Man and the Biosphere reserves. Although there are many theoretical frameworks, there is still a lack of supportive ecological evidence. This study analyzed aspects of the local human population, economic growth, number of tourists, and ticket income data of Huangshan Man and Biosphere Reserve (HMBR) as well as population and distribution changes in the flagship species (Tibetan macaque) in HMBR over a 30 year period. We found that after 30 years of implementing a sustainable development strategy in HMBR, the local economy and the population of Tibetan macaques have increased simultaneously. With economic growth, more funds for protection have been invested, improving the local environment significantly and expanding the existing distribution of the Tibetan macaque population. This study provides strong evidence for the sustainable development of Man and Biosphere reserves. We propose that economic and wildlife population growth and distribution area measures constitute a critical standard for the evaluation of sustainable development. The primary purpose of the Man and the Biosphere Program is the sustainable development of both the economy and nature conservation activities. Although the effectiveness of eco-tourism to reach this goal has been proposed, due to the lack of long-term monitoring data and a model species, there has been no obvious mechanism to evaluate the effectiveness of this policy. This study explored the effectiveness of the sustainable development policy of HMBR based on 30 years data of monitoring the Tibetan macaque, local human population, visitors, and annual ecotourism income in Huangshan by estimating species habitat suitability and the impact of ecotourism. The results showed increases in the income for the local human population, the number of visitors, and annual eco-tourism. Simultaneously, the reserve's Tibetan macaque population size and suitable habitat areas increased. The macaques expanded their habitat to the low-altitude buffer zone (400–800 m), an area with lower eco-tourism disturbance. Scenic spots had a significant negative impact on habitat suitability (the substantially increased contributions of scenic spots from 0.71% to 32.88%). Our results and methods provide a suitable evaluation framework for monitoring the sustainable development and effectiveness of eco-tourism and wildlife conservation in Man and the Biosphere reserves. [ABSTRACT FROM AUTHOR]

Simple Summary: Climate change has always been a noticeable factor in the research of species distribution. In recent decades, the habitats of species have been gradually destroyed due to the changing climate. Thus, in order to predict how climate change will influence the survival and suitable habitats of wild Morchella Dill. ex Pers. species in China, we used a maximum entropy model to simulate the changes in its distribution area from historical periods to future periods. Our results illustrate that precipitation, elevation and temperature are indispensable factors affecting the presence and suitable habitats of wild Morchella species. Furthermore, this research showed us a promising trend that, regardless of which scenario, the suitable area of the species will increase to a certain scale in the near future. Based on these findings, we could explore and design an optimal scheme for the conservation of wild Morchella resources. Morchella is a kind of precious edible, medicinal fungi with a series of important effects, including anti-tumor and anti-oxidation effects. Based on the data of 18 environmental variables and the distribution sites of wild Morchella species, this study used a maximum entropy (MaxEnt) model to predict the changes in the geographic distribution of Morchella species in different historical periods (the Last Glacial Maximum (LGM), Mid Holocene (MH), current, 2050s and 2070s). The results revealed that the area under the curve (AUC) values of the receiver operating characteristic curves of different periods were all relatively high (>0.83), indicating that the results of the maximum entropy model are good. Species distribution modeling showed that the major factors influencing the geographical distribution of Morchella species were the precipitation of the driest quarter (Bio17), elevation, the mean temperature of the coldest quarter (Bio11) and the annual mean temperature (Bio1). The simulation of geographic distribution suggested that the current suitable habitat of Morchella was mainly located in Yunnan, Sichuan, Gansu, Shaanxi, Xinjiang Uygur Autonomous Region (XUAR) and other provinces in China. Compared with current times, the suitable area in Northwest and Northeast China decreased in the LGM and MH periods. As for the future periods, the suitable habitats all increased under the different scenarios compared with those in contemporary times, showing a trend of expansion to Northeast and Northwest China. These results could provide a theoretical basis for the protection, rational exploitation and utilization of wild Morchella resources under scenarios of climate change. [ABSTRACT FROM AUTHOR]

Understanding the impacts and constraints of climate change on the geographical distribution of wild Akebia trifoliata is crucial for its sustainable management and economic development as a medicinal material or fruit. In this study, according to the first‐hand information obtained from field investigation, the distribution and response to climate change of A. trifoliata were studied by the MaxEnt model and ArcGIS. The genetic diversity and population structure of 21 natural populations of A. trifoliata were studied by simple sequence repeat (SSR) markers. The results showed that the most important bioclimatic variable limiting the distribution of A. trifoliata was the Mean Temperature of Coldest Quarter (bio11). Under the scenarios SSP1‐2.6 and SSP2‐4.5, the suitable area of A. trifoliata in the world will remain stable, and the suitable area will increase significantly under the scenarios of SSP3‐7.0 and SSP5‐8.5. Under the current climate scenario, the suitable growth regions of A. trifoliata in China were 79.9–122.7°E and 21.5–37.5°N. Under the four emission scenarios in the future, the geometric center of the suitable distribution regions of Akebia trifoliata in China will move to the north. The clustering results of 21 populations of A. trifoliata analyzed by SSR markers showed that they had a trend of evolution from south to north. [ABSTRACT FROM AUTHOR]

The maximum entropy (MaxEnt) model for predicting the potential suitable habitat of species has been commonly employed in many ecological and biological applications by using presence-only occurrence records along with associated environmental factors. Parnassia wightiana, a perennial herb, is a cold-adapted plant distributed across three diversity hotspots in China, including the Hengduan Range, Central China and the Lingnan region. The MaxEnt model was used to simulate the historic, current and future distribution trends of P. wightiana, as well as to analyse its distribution pattern in each historical period and explore the causes of species distribution changes. The results of our analysis indicated that annual precipitation, annual temperature range and mean temperature of the warmest quarter were the key bioclimatic variables affecting the distribution of P. wightiana. Most temperate species retracted into smaller refugial areas during glacial periods and experienced range expansion during interglacial periods. Possible refugia of the species were inferred to be located in the Hengduan Range and Qinling Regions. [ABSTRACT FROM AUTHOR]

Chinese alfalfa (Medicago sativa) is one of the most widely planted species in China. It has considerable economic potential and plays an important role in soil and water conservation. In order to conduct scientific cultivation of Chinese alfalfa, we collected 100 occurrence records from herbarium and publications and 19 climatic variables from BIOCLIM to simulate potential suitable habitat and identified the key climatic factors of Chinese alfalfa by MaxEnt and GIS software. The result shows that the MaxEnt model performed well, with an average test AUC value of 0.86 with 10-fold cross validation. The potential distribution of Chinese alfalfa is mainly in arid and semi-arid areas of north and northwest China, about 15.2% (1.46 million km2) of China's total land area, and the highly suitable area is Loess Hilly region and Xinjiang. The main climatic factors affecting the distribution of this species is hydrological-related factors (PDM, PS, AP, PDQ and PCQ), which explained 58.6% of the variation, and the climatic factors limiting the southern, northern, northwestern and Tibetan plateau boundaries were PDM, AMT, AP and MTCM, respectively. The climatic thresholds of the core area of Chinese alfalfa are 0.0–14.0 mm of PDM, 23.8–108.2% of PS, 3.9–15.5 °C of AMT, 14.0–664.0 mm of AP, 1.0–47.0 mm of PDQ, 2.0–51.0 mm of PCQ. The results improve our understanding of limiting climatic factors for Chinese alfalfa and suggest a priority management measures for areas with corresponding limiting climatic factor. [ABSTRACT FROM AUTHOR]

Haloxylon ammodendron, an excellent tree species for sand fixation and afforestation in the desert areas of western China, is threatened by climate change and anthropogenic activities. The suitable habitat of this species is shrinking at a remarkable rate, although conservation measures have been implemented. Cistanche deserticola is an entirely parasitic herb that occurs in deserts, is a source of "desert ginseng" worldwide, and has extremely high medicinal value. Little is known about using niche models to simulate habitat suitability and evaluate important environmental variables related to parasitic species. In this study, we modeled the current suitable habitat of H. ammodendron and C. deserticola by MaxEnt based on occurrence record data of the distributions of these two species in China. We grouped H. ammodendron and C. deserticola into three groups according to the characteristics of parasitic species and modeled them with environmental factors. The results showed that bioclimate was the most important environmental parameter affecting the H. ammodendron and C. deserticola distribution. Precipitations, such as annual precipitation, precipitation seasonality, and precipitation in the driest quarter, were identified as the most critical parameters. The slope, diurnal temperature range, water vapor pressure, ground‐frost frequency, and solar radiation also substantially contributed to the distribution of the two species. The proportions of the most suitable areas for Groups 1, 2, and 3 were 1.2%, 1.3%, and 1.7%, respectively, in China. When combined with cultural geography, five hot spot conservation areas were determined within the distribution of H. ammodendron and C. deserticola. The comprehensive analysis indicated that by using MaxEnt to model the suitable habitat of parasitic species, we further improved the accuracy of the prediction and coupled the error of the distribution of a single species. This study provides a useful reference for the protection of H. ammodendron forests and the management of C. deserticola plantations. [ABSTRACT FROM AUTHOR]

In this study, we investigated suitable habitats for the endangered tree fern, Sphaeropteris lepifera (J. Sm. ex Hook.) R.M. Tryon, based on fieldwork, ecological niche modeling, and regression approaches. We combined these data with the characterization of spore germination and gametophytic development in the laboratory to assess the reasons why S. lepifera is endangered and to propose a conservation strategy that focuses on suitable sites for reintroduction and accounts for the ecology and biphasic life cycle of the species. Our methods represent an integration of process- and correlation-based approaches to understanding the distributional patterns of this species, and this combined approach, while uncommonly applied, is a more robust strategy than either approach used in isolation. Our ecological niche models indicated that cold temperature extremes, temperature stability over long- and short-terms, and the seasonality of precipitation were among the most important abiotic environmental factors affecting the distribution of S. lepifera among the variables that we measured. Moreover, distribution of this fern species is also strongly influenced by the timing of development of male and female gametes. Additionally, we observed that slope aspect, specifically south-facing slopes, facilitates more incoming sunlight for mature trees, and simultaneously, provides greater, much-needed shade for fiddleheads on account of the canopy being denser. We believe that our study can provide important guidance on the restoration of S. lepifera in the wild. Specifically, potential restoration areas can be screened for the specific environmental factors that we infer to have a critical impact on the survival of the species. [ABSTRACT FROM AUTHOR]

Simple Summary: The red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is an invasive pest, and it has spread rapidly all over the world. In this study, based on the distribution data and environmental factor data of S. invicta, the optimized MaxEnt model was used to predict the suitable areas of S. invicta growth in China under current and future climatic conditions. The results show that the potential suitable area of S. invicta growth in the current climate is 81.37 × 104 km2 in size and is mainly located in the south and southeast of China. The total suitable area of S. invicta growth is expected to increase in the future climate change scenario, and the suitable area is likely to spread to higher latitudes. The red imported fire ant, Solenopsis invicta (Hymenoptera: Formicidae), is an invasive pest, and it has spread rapidly all over the world. Predicting the suitable area of S. invicta growth in China will provide a reference that will allow for its invasion to be curbed. In this study, based on the 354 geographical distribution records of S. invicta, combined with 24 environmental factors, the suitable areas of S. invicta growth in China under current (2000s) and future (2030s and 2050s) climate scenarios (SSPs1-2.5s, SSPs2-3.5s and SSPs5-8.5s) were predicted by using the optimized MaxEnt model and geo-detector model. An iterative algorithm and knife-cut test were used to evaluate the important environmental factors that restrict the suitable area under the current climatic conditions. This study also used the response curve to determine the appropriate value of environmental factors to further predict the change and the center of gravity transfer of the suitable area under climate change. The optimized MaxEnt model has high prediction accuracy, and the working curve area (AUC) of the subjects is 0.974. Under climatic conditions, the suitable area is 81.37 × 104 km2 in size and is mainly located in the south and southeast of China. The main environmental factors affecting the suitable area are temperature (Bio1, Bio6, and Bio9), precipitation (Bio12 and Bio14) and NDVI. In future climate change scenarios, the total suitable area will spread to higher latitudes. This distribution will provide an important theoretical basis for relevant departments to rapidly prevent and control the invasion of S. invicta. [ABSTRACT FROM AUTHOR]