Identifying conservation priority areas and predicting the climate change impact on the future habitats of endangered Nepenthes khasiana Hook.f. utilizing ecological niche modelling

Developing strategies for effective species conservation is necessary to counter the ever-fluctuating environmental conditions with increasing anthropogenic activities. Studies have proven Ecological Niche Modelling (ENM) as an effective tool for sustainable conservation. Nepenthes khasiana Hook.f. is an endangered pitcher plant facing a constant decline in population due to anthropogenic activities. This study aimed to locate the most suitable areas for re-establishing the species in natural habitats using Maximum Entropy (MaxEnt) modelling, and to forecast the effects of current and future climate conditions on its distribution throughout Northeast India. The potential suitable areas in future climate under three Representative Concentration Pathway (RCP) scenarios and in the current climate were predicted utilizing the 30 occurrence data, bioclimatic predictors, and variables from BCC-CSM1.1 model and WorldClim respectively. The results of the current study showed significant relationships among annual precipitation, precipitation in the driest month, seasonality of precipitation, annual range iso-thermality of temperature, mean diurnal range [Mean of monthly (max temp - min temp)], and the distribution of the analysed species. The optimum model performance was represented by the AUC value of 0.972 ± 0.007. The model predicted 10.70% of the NE Indian region as climatically suitable, which will expand under RCP4.5 and RCP6.0, reaching 15.35%, and 12.64%, respectively. However, this may degrade significantly under RCP8.5, reducing to 8.14%. Based on the analysis of modelling results it was found that the Nokrek belt and the Khasi hills as highly suitable regions for the reintroduction of the species. The study revalidated ENM as an effective means to identify new populations and predict the influence of climate change on the future habitat which can benefit the concurrent species management strategies.     

Predicting impacts of climate change on habitat connectivity of Kalopanax septemlobus in South Korea

Understanding the drivers of habitat distribution patterns and assessing habitat connectivity are crucial for conservation in the face of climate change. In this study, we examined a sparsely distributed tree species, Kalopanax septemlobus (Araliaceae), which has been heavily disturbed by human use in temperate forests of South Korea. We used maximum entropy distribution modeling (MaxEnt) to identify the climatic and topographic factors driving the distribution of the species. Then, we constructed habitat models under current and projected climate conditions for the year 2050 and evaluated changes in the extent and connectivity of the K. septemlobus habitat. Annual mean temperature and terrain slope were the two most important predictors of species distribution. Our models predicted the range shift of K. septemlobus toward higher elevations under medium-low and high emissions scenarios for 2050, with dramatic reductions in suitable habitat (51% and 85%, respectively). In addition, connectivity analysis indicated that climate change is expected to reduce future levels of habitat connectivity. Even under the Representative Construction Pathway (RCP) 4.5 medium-low warming scenario, the projected climate conditions will decrease habitat connectivity by 78%. Overall, suitable habitats for K. septemlobus populations will likely become more isolated depending on the severity of global warming. The approach presented here can be used to efficiently assess species and habitat vulnerability to climate change.     

A distribution model for Glossina brevipalpis and Glossina austeni in Southern Mozambique,Eswatini and South Africa for enhanced area-wide integrated pest management approaches

BackgroundGlossina austeni and Glossina brevipalpis (Diptera: Glossinidae) are the sole cyclical vectors of African trypanosomes in South Africa, Eswatini and southern Mozambique. These populations represent the southernmost distribution of tsetse flies on the African continent. Accurate knowledge of infested areas is a prerequisite to develop and implement efficient and cost-effective control strategies, and distribution models may reduce large-scale, extensive entomological surveys that are time consuming and expensive. The objective was to develop a MaxEnt species distribution model and habitat suitability maps for the southern tsetse belt of South Africa, Eswatini and southern Mozambique.Methodology/Principal findingsThe present study used existing entomological survey data of G. austeni and G. brevipalpis to develop a MaxEnt species distribution model and habitat suitability maps. Distribution models and a checkerboard analysis indicated an overlapping presence of the two species and the most suitable habitat for both species were protected areas and the coastal strip in KwaZulu-Natal Province, South Africa and Maputo Province, Mozambique. The predicted presence extents, to a small degree, into communal farming areas adjacent to the protected areas and coastline, especially in the Matutuíne District of Mozambique. The quality of the MaxEnt model was assessed using an independent data set and indicated good performance with high predictive power (AUC > 0.80 for both species).Conclusions/SignificanceThe models indicated that cattle density, land surface temperature and protected areas, in relation with vegetation are the main factors contributing to the distribution of the two tsetse species in the area. Changes in the climate, agricultural practices and land-use have had a significant and rapid impact on tsetse abundance in the area. The model predicted low habitat suitability in the Gaza and Inhambane Provinces of Mozambique, i.e., the area north of the Matutuíne District. This might indicate that the southern tsetse population is isolated from the main tsetse belt in the north of Mozambique. The updated distribution models will be useful for planning tsetse and trypanosomosis interventions in the area.     

Impact of Climate Change on Potential Distribution of Chinese Caterpillar Fungus (Ophiocordyceps sinensis) in Nepal Himalaya

Climate change has already impacted ecosystems and species and substantial impacts of climate change in the future are expected. Species distribution modeling is widely used to map the current potential distribution of species as well as to model the impact of future climate change on distribution of species. Mapping current distribution is useful for conservation planning and understanding the change in distribution impacted by climate change is important for mitigation of future biodiversity losses. However, the current distribution of Chinese caterpillar fungus, a flagship species of the Himalaya with very high economic value, is unknown. Nor do we know the potential changes in suitable habitat of Chinese caterpillar fungus caused by future climate change. We used MaxEnt modeling to predict current distribution and changes in the future distributions of Chinese caterpillar fungus in three future climate change trajectories based on representative concentration pathways (RCPs: RCP 2.6, RCP 4.5, and RCP 6.0) in three different time periods (2030, 2050, and 2070) using species occurrence points, bioclimatic variables, and altitude. About 6.02% (8,989 km²) area of the Nepal Himalaya is suitable for Chinese caterpillar fungus habitat. Our model showed that across all future climate change trajectories over three different time periods, the area of predicted suitable habitat of Chinese caterpillar fungus would expand, with 0.11–4.87% expansion over current suitable habitat. Depending upon the representative concentration pathways, we observed both increase and decrease in average elevation of the suitable habitat range of the species.     

Alpine marmot (Marmota marmota) distribution evolution under climate change: The use of species distribution models at a local scale in the western Pyrenees massif (France)

The Alpine marmot (Marmota marmota) is a social mammal living in mountainous grassland areas and has the particularity to hibernate in winter. Recent studies on a population in the French Alps found that climate change is affecting Alpine marmot population dynamics and might impact their overall distribution in the future. Using Species Distribution Models (SDMs), the effect of climate change on Alpine marmot's future distribution was investigated at a local scale, in the western part of the Pyrenean massif (New-Aquitaine region, France). This scale was chosen as an appropriate action scale for the conservation strategy for the species. Three climatic scenarios were used (RCP 2.6, RCP 4.5, and RCP 8.5) over three future 30-year periods (2021–2050, 2040–2070, 2071–2100) to predict the short- to long-term potential distribution of the target species. The results are consistent with naturalistic knowledge of the species´ ecological needs in terms of variable importance and response type. Mean maximum temperature in winter, standard-deviation of daily temperature in winter, along with the median rainfall amount in summer were the three most important climatic variables. Predictions under the two most pessimistic climate scenarios showed potential large habitat loss. In the long term, for RCP 4.5, an estimated habitat loss of 18% was predicted. In the case of RCP 8.5, a higher impact was predicted, with a 54% habitat loss. Our results show that high impact due to climate change can be expected at a long term. In addition, if winter climatic conditions are important for marmot survival through hibernation, drought in summer might be one of the drivers of future population dynamic and distribution. Our findings can be applied for other species living in grassland mountainous environments and for which access to food resources in summer is essential, facilitating the conservation of target areas.     

Climate and pH Predict the Potential Range of the Invasive Apple Snail (Pomacea insularum) in the Southeastern United States

Predicting the potential range of invasive species is essential for risk assessment, monitoring, and management, and it can also inform us about a species’ overall potential invasiveness. However, modeling the distribution of invasive species that have not reached their equilibrium distribution can be problematic for many predictive approaches. We apply the modeling approach of maximum entropy (MaxEnt) that is effective with incomplete, presence-only datasets to predict the distribution of the invasive island apple snail, Pomacea insularum. This freshwater snail is native to South America and has been spreading in the USA over the last decade from its initial introductions in Texas and Florida. It has now been documented throughout eight southeastern states. The snail’s extensive consumption of aquatic vegetation and ability to accumulate and transmit algal toxins through the food web heighten concerns about its spread. Our model shows that under current climate conditions the snail should remain mostly confined to the coastal plain of the southeastern USA where it is limited by minimum temperature in the coldest month and precipitation in the warmest quarter. Furthermore, low pH waters (pH <5.5) are detrimental to the snail’s survival and persistence. Of particular note are low-pH blackwater swamps, especially Okefenokee Swamp in southern Georgia (with a pH below 4 in many areas), which are predicted to preclude the snail’s establishment even though many of these areas are well matched climatically. Our results elucidate the factors that affect the regional distribution of P. insularum, while simultaneously presenting a spatial basis for the prediction of its future spread. Furthermore, the model for this species exemplifies that combining climatic and habitat variables is a powerful way to model distributions of invasive species.     

Using MaxEnt modeling to predict the potential distribution of the endemic plant Rosa arabica Crép. in Egypt

Climate change poses negative impacts on plant species, particularly for those of restricted ecology and distribution range. Rosa arabica Crép., an exclusive endemic species to Saint Catherine Protectorate in Egypt, has severely declined and become critically endangered in the last years. In this paper, we applied the maximum-entropy algorithm (MaxEnt) to predict the current and future potential distribution of this species in order to provide a basis for its protection and conservation. In total, 32 field-based occurrence points and 22 environmental variables (19 bioclimatic and three topographic) were used to model the potential distribution area under current and two future representative concentration pathways (RCP2.6 and RCP8.5) for the years 2050 and 2070. Annual temperature, annual precipitation and elevation were the key factors for the distribution of R. arabica. The response curves showed that this species prefers habitats with an annual temperature of 8.05–15.4 °C, annual precipitation of 36 to 120 mm and elevation range of 1571 to 2273 m a.s.l. Most of the potential current suitable conditions were located at the middle northern region of Saint Catherine. Prediction models under two future climate change scenarios displayed habitat range shifts through the disappearance of R. arabica in sites below 1500 m a.s.l., an altitudinal range contraction at 1500–2000 m and possible expansions towards higher elevation sites (2000–2500 m a.s.l.). Our findings can be used to define the high priority areas for reintroduction or for protection against the expected climate change impacts and future modifications.     

基于生态位模型的外来入侵种克氏原螯虾在中国的适生区预测

克氏原螯虾在20世纪初作为重要的水产品引入中国,但因其繁殖能力强、生长迅速、适应性强、喜掘洞穴,对农作物、池埂及农田水利有一定破坏作用,降低入侵地区当地物种多样性,对当地生态系统造成严重危害。因此,研究未来气候情景下克氏原螯虾适生区的变化,可为其监控和管理措施提供关键信息,有效预防和控制其蔓延。本研究基于克氏原螯虾的分布点,应用最大熵(MaxEnt)模型和规则集遗传算法(GARP)模型模拟了当前气候条件下克氏原螯虾在中国的潜在适生区,并预测了2041—2060年和2061—2080年克氏原螯虾在4种气候变化情景下(RCP 2.6、RCP 4.5、RCP 6.0、RCP 8.5)的分布,采用ROC曲线对预测结果进行检验和评价。结果表明: 在当前气候条件下克氏原螯虾集中分布在上海、江苏、浙江、安徽等长江沿岸地区;最冷季平均温度、最冷月最低温度对克氏原螯虾分布影响最大,其次是温度季节性变化、最暖月最高温度和最干月降水量。在未来气候情景下,2061—2080年克氏原螯虾的适生区面积有不同程度的变化,在RCP 2.6和RCP 4.5情景下总适生面积增加,但在RCP 8.5情景下呈先增后减趋势,而在RCP 6.0情景下无明显变化;克氏原螯虾适生区在空间分布上不仅有纬度方向上的扩散,也有向海拔较高地区迁移的趋势。     

伯乐树潜在地理分布时空格局模拟

以伯乐树(Bretschneidera sinensis Hemsl.)为研究对象,基于现有的151个伯乐树居群分布点及12个气候变量,运用MaxEnt模型和GIS技术,模拟末次盛冰期、全新世中期、当前、未来(RCP 2.6、RCP 4.5、RCP 6.0和RCP 8.5)气候情景下的伯乐树潜在地理分布格局;采用受试者工作特征曲线(ROC)下的面积(AUC值),评价模拟的精度;综合分析测试增益、气候变量贡献率及置换重要值,探讨制约伯乐树地理分布的主导气候变量;基于分布面积比(N a)、生境变化程度(N e),比较伯乐树在不同气候情景下的地理分布动态。ROC曲线结果显示,7种不同气候情景下的训练集与测试集AUC值均大于0.99,表明模型模拟精度极高。测试增益、气候变量贡献率及置换重要值显示,昼夜温差月均值、等温性和最干季度降水量是伯乐树潜在地理分布的限制因子。不同气候情景下伯乐树地理分布动态暗示,金佛山、大瑶山可能是伯乐树冰期多个微型避难所;末次盛冰期以来,伯乐树地理分布经历了扩张过程;未来不同气候情景下,其地理分布范围可能会发生不同程度(25%~47%)的收缩,其中RCP 8.5情境下,伯乐树居群生境破碎化最为严重。开展伯乐树资源调查、收集和遗传管理的国际合作,在气候适宜地区建立迁地保育林,是有效防止伯乐树遗传资源丢失的重要措施。     

Assessing the climate change effects on the distribution pattern of the Azerbaijan Mountain Newt (Neurergus crocatus)

Climate change is a grave danger for humans and a looming threat to Earth's biodiversity in the twenty-first century. Assessing the vulnerability of species to climate change is critical for practical conservation efforts. Due to their limited dispersal ability, amphibians are one of the most vulnerable groups of vertebrates to climate change. Among them, the species that inhabit mountains suffer a tremendous amount of climate change-induced pressures. We, therefore, adopted the Azerbaijan Mountain Newt (Neurergus crocatus), which currently inhabits Northwest Iran, North Iraq, and Southeast Turkey, as a case study for assessing the effects of climate change on the distribution patterns of mountain amphibians. By applying the species distribution models (SDMs) in this study, we tried to hindcast the species distribution area in the past and illustrate the impacts of climate change on its distribution in the present and future (the 2050s and 2070s) climate conditions. Also, the patch metrics have been deployed for identifying habitat fragmentation. Our results indicate a more than 50% rise in the species’ current suitable habitats compared to its glacial refugia. The suitable habitat is expected to gradually decrease in RCP 2.6 and RCP 8.5. Among the three countries in which the species occurs, its distribution overlaps with protected areas only in Iraq. The number of habitat patches will grow and reach approximately 20 to 60 patches by 2070 and the average area of the patches will decrease throughout this time. Aside from the numerous threats that endanger the species, climate change puts the long-term existence of Azerbaijan Newt in jeopardy. The results of this study stress the urgent need for taking extreme measures on the species management and conserving its remnant habitat patches.     

Ecological analysis and environmental niche modelling of Dactylorhiza hatagirea (D. Don) Soo: A conservation approach for critically endangered medicinal orchid

The natural populations of Dactylorhiza hatagirea have been greatly affected due to incessant exploitation. As such, studies on its population attributes together with habitat suitability and environmental factors affecting its distribution are needed to be undertaken for its conservation in nature. Present study aimed at accessing an impact of anthropogenic pressure on population structure and locate suitable habitats for the conservation of this critically endangered orchid. Considerable changes in the phytosociological attributes were observed on account of the changing magnitude and extent of anthropogenic threat in their natural abode. The distribution pattern of species indicated that more than 90% of the populations exhibit substantially aggregated spatial distribution. Maximum Entropy (MaxEnt) distribution modelling algorithm was used to predict suitable habitat and potential area for its cultivation and reintroduction. Twenty-seven occurrence records, nineteen bioclimatic variables, altitude, and slope were used. MaxEnt map output gave the habitat suitability for this species and predicted its distribution in the North-Western Himalayas of India for approximately 616 km². Jackknifing indicated that maximum temperature of warmest month, annual mean temperature, mean temperature of the driest quarter, and mean temperature of the wettest quarter were the governing factors for its distribution and hence, presented a higher gain with respect to other variables. According to permutation importance, precipitation seasonality and mean temperature of wettest quarter shows the prominent impact on the habitat distribution. Results of AUC (area under curve) were statistically significant (0.940) and the line of predicted omission falls very close to an omission on training samples, validating a better run of the model. Response curves revealed a probable increase in the occurrence of D. hatagirea with an increase in mean temperature of the wettest quarter and maximum temperature of the warmest month contributed more than 50% to predicted habitat suitability. Direct field observations concurrent with predicted habitat suitability and google-earth images represent greater model thresholds for successful inception of the species. Together, the study proposes that the species can be conserved in or near its present-day natural habitats and is equally effective in determining the possible habitats for its cultivation and reintroduction.     

Coral Reef Habitat Response to Climate Change Scenarios

Coral reef ecosystems are threatened by both climate change and direct anthropogenic stress. Climate change will alter the physico-chemical environment that reefs currently occupy, leaving only limited regions that are conducive to reef habitation. Identifying these regions early may aid conservation efforts and inform decisions to transplant particular coral species or groups. Here a species distribution model (Maxent) is used to describe habitat suitable for coral reef growth. Two climate change scenarios (RCP4.5, RCP8.5) from the National Center for Atmospheric Research’s Community Earth System Model were used with Maxent to determine environmental suitability for corals (order Scleractinia). Environmental input variables best at representing the limits of suitable reef growth regions were isolated using a principal component analysis. Climate-driven changes in suitable habitat depend strongly on the unique region of reefs used to train Maxent. Increased global habitat loss was predicted in both climate projections through the 21^st century. A maximum habitat loss of 43% by 2100 was predicted in RCP4.5 and 82% in RCP8.5. When the model is trained solely with environmental data from the Caribbean/Atlantic, 83% of global habitat was lost by 2100 for RCP4.5 and 88% was lost for RCP8.5. Similarly, global runs trained only with Pacific Ocean reefs estimated that 60% of suitable habitat would be lost by 2100 in RCP4.5 and 90% in RCP8.5. When Maxent was trained solely with Indian Ocean reefs, suitable habitat worldwide increased by 38% in RCP4.5 by 2100 and 28% in RCP8.5 by 2050. Global habitat loss by 2100 was just 10% for RCP8.5. This projection suggests that shallow tropical sites in the Indian Ocean basin experience conditions today that are most similar to future projections of worldwide conditions. Indian Ocean reefs may thus be ideal candidate regions from which to select the best strands of coral for potential re-seeding efforts.     

Modeling impacts of climate change on the potential distribution of three endemic Aloe species critically endangered in East Africa

Climate change has had a significant impact on natural ecosystems and endemic species around the world and substantial impacts are expected in the future. As a result, knowing how climate change affects endemic species can help in putting forward the necessary conservation efforts. The use of niche modeling to predict changes in species distributions under different climate change scenarios is becoming a hot topic in biological conservation. This study aimed to use the global circulation model (CMIP5) to model the current distribution of suitable habitat for three critically endangered Aloe species endemic to Kenya and Tanzania in order to determine the impact of climate change on their suitable habitat in the years 2050 and 2070. We used two representative concentration pathways scenarios (RCP4.5 and RCP8.5) to project the contraction of suitable habitats for Aloe ballyi Reynolds, A. classenii Reynolds, and A. penduliflora Baker. Precipitation, temperature and environmental variables (Potential evapotranspiration, land cover, soil sedimentary and solar radiation) have had a significant impact on the current distribution of all the three species. Although suitable habitat expansion and contraction are predicted for all the species, loss of original suitable habitat is expected to be extensive. Climate change is expected to devastate >44% and 34% of the original habitats of A. ballyi and A. classenii respectively. Based on our findings, we propose that areas predicted to contract due to climate change should be designated as key protection zones for Aloe species conservation.     

Predictive Modeling and Mapping of Malayan Sun Bear (Helarctos malayanus) Distribution Using Maximum Entropy

One of the available tools for mapping the geographical distribution and potential suitable habitats is species distribution models. These techniques are very helpful for finding poorly known distributions of species in poorly sampled areas, such as the tropics. Maximum Entropy (MaxEnt) is a recently developed modeling method that can be successfully calibrated using a relatively small number of records. In this research, the MaxEnt model was applied to describe the distribution and identify the key factors shaping the potential distribution of the vulnerable Malayan Sun Bear (Helarctos malayanus) in one of the main remaining habitats in Peninsular Malaysia. MaxEnt results showed that even though Malaysian sun bear habitat is tied with tropical evergreen forests, it lives in a marginal threshold of bio-climatic variables. On the other hand, current protected area networks within Peninsular Malaysia do not cover most of the sun bears potential suitable habitats. Assuming that the predicted suitability map covers sun bears actual distribution, future climate change, forest degradation and illegal hunting could potentially severely affect the sun bear’s population.     

气候变化情景下外来入侵植物刺苍耳在新疆的潜在分布格局模拟

明确区域尺度上外来入侵种的潜在分布格局及其对气候变化的响应对入侵种的预防和控制具有重要意义。以外来入侵植物刺苍耳(Xanthium spinosum L.)为研究对象,以其扩散蔓延的新疆地区为研究区域,结合中国国家气候中心开发的BCC—CSM1—1模式下的将来气候条件,应用MaxEnt模型和ArcGIS空间分析技术构建了未来不同气候变化情景(RCP4.5,8.5)下2050s和2070s的刺苍耳适宜生境预测模型,定量的展示了气候变化情景下刺苍耳在新疆的扩散趋势及其适宜生境的面积空间变化和分布区中心移动轨迹。结果表明:年降雨量、下层土壤有机碳含量、上层土壤pH值、年温度变化范围、降雨量的季节性变化和年平均温度是影响刺苍耳地理分布的主导环境因子;博州、塔城、阿勒泰西北部、哈密中部、巴州北部、克州中部、阿克苏北部、奎屯市、克拉玛依市、五家渠市、喀什市等地为高危入侵风险区;两种气候模式下刺苍耳的各级适生区面积和总适生面积均呈持续增加的变化趋势,且在RCP8.5情景(最高温室气体排放情景)下响应更为敏感;总体上看,刺苍耳在新疆的分布未达到饱和,呈现以塔城中部为中心,向天山北麓和塔克拉玛干北缘方向辐射状扩散,且两种气候变化情景下至2070s分布区中心均向伊犁州奎屯方向移动。     

Modeling the habitat suitability for deep-water gorgonian corals based on terrain variables

The coral species Paragorgia arborea and Primnoa resedaeformis are abundant and widely distributed gorgonians in North Atlantic waters. Both species add significant habitat complexity to the benthic environment, and support a host of invertebrate species. Mapping their distribution is an essential step in conservation and resource management, but challenging as a result of their remoteness. In this study, three predictive models — Ecological Niche Factor Analysis, Genetic Algorithm for Rule-set Production and Maximum Entropy modeling (MaxEnt) were applied to predict the distribution of species' suitable habitat across a region of Røst Reef (Norwegian margin) based on multiscale terrain variables.All three models were successful in predicting the habitat suitability for both gorgonian species across the study area, and the MaxEnt predictions were shown to outperform other predictions. All three models predicted the most suitable habitats for both species to mainly occur along the ridges and on the upper section of the large slide, suggesting both species preferentially colonize topographic highs. Jackknife tests for MaxEnt predictions highlighted the seabed aspect in relation to P. arborea distribution, and the seabed relative position (curvature) in relation to the distribution of both species. Given the vulnerability of deep-water corals to anthropogenic impacts, further comparative study over a wider study area would be particularly beneficial for the management of the species.     

Risk map for the range expansion of Thrips palmi in Korea under climate change: Combining species distribution models with land-use change

Climate change and land-use change are the most powerful drivers for the invasion of alien species. To understand the integrated effects of these two drivers on pest invasion risk in the future, this study assessed how they impact the invasion risk of Thrips palmi Karny, which is the most serious invasive species in the Korean peninsula. The potential distribution of T. palmi was projected with a MaxEnt model for current and future climate change scenarios (RCP 4.5 and 8.5) based on occurrence records. The potential distribution extends to the north over time, except the eastern high mountainous area, for both RCPs in 2075. The MaxEnt outputs were filtered with agricultural area using data from three land-use change scenarios derived from the Shared Socio-economic Pathways (SSPs), because T. palmi populations can only be sustained in agricultural areas. The potential risk of T. palmi, based on the potential distribution probability in the future agricultural area, increased over time under all RCPs-SSPs combinations. The total area of T. palmi occurrence increased under RCPs-SSP1 and -SSP2 but decreased under RCPs-SSP3, due to agricultural areas being converted to urban areas. In conclusion, based on future climate change scenarios, T. palmi could be distributed throughout the Korean peninsula in the future. The invasion risk in agricultural areas will increase substantially; thus, intensive control measures for T. palmi are required in the future. Our research suggests that using both climate change and land-use change in pest risk mapping study can provide informative data for management strategy.     

Fishing cat Prionailurus viverrinus distribution and habitat suitability in Nepal

The fishing cat Prionailurus viverrinus is a wetland specialist species endemic to South and Southeast Asia. Nepal represents the northern limit of its biogeographic range, but comprehensive information on fishing cat distribution in Nepal is lacking. To assess their distribution, we compiled fishing cat occurrence records (n = 154) from Nepal, available in published literature and unpublished data (2009–2020). Bioclimatic and environmental variables associated with their occurrence were used to predict the fishing cat habitat suitability using MaxEnt modeling. Fishing cat habitat suitability was associated with elevation (152–302 m), precipitation of the warmest quarter, i.e., April–June (668–1014 mm), precipitation of the driest month (4–7 mm), and land cover (forest/grassland and wetland). The model predicted an area of 4.4% (6679 km²) of Nepal as potential habitat for the fishing cat. About two‐thirds of the predicted potentially suitable habitat lies outside protected areas; however, a large part of the highly suitable habitat (67%) falls within protected areas. The predicted habitat suitability map serves as a reference for future investigation into fishing cat distribution as well as formulating and implementing effective conservation programs in Nepal. Fishing cat conservation initiatives should include habitats inside and outside the protected areas to ensure long‐term survival. We recommend conservation of wetland sites, surveys of fishing cats in the identified potential habitats, and studying their genetic connectivity and population status.     

Predicting the effects of future climate change on the distribution of an endemic damselfly (Odonata,Coenagrionidae) in subtropical South American grasslands

Climate change is predicted to affect the distribution of freshwater taxa, and stronger impacts are expected on endemic species. However, the effects of future climates on freshwater insects from the Neotropical region have been generally overlooked. In this study, the distribution of a damselfly (Cyanallagma bonariense, Odonata, Coenagrionidae) endemic to the subtropical South American grasslands (Pampa) was modelled in relation to future scenarios of high greenhouse gas emissions (RCP 8.5) for 2050 and 2070. For this purpose, ecological niche models were developed based on assumptions of limited dispersal and niche conservatism, and the projected distribution of C. bonariense was contrasted with the location of current protected areas (PAs) in the Pampa. A broad potential distribution of C. bonariense was indicated throughout the Pampa, and projections predicted a predominance of range contractions rather than range shifts in climatically suitable areas for C. bonariense in 2050 and 2070. Projections of suitable areas overlapped in central Argentina and southernmost Uruguay in these periods. Our results indicated a potential resilience of C. bonariense to future climate change, which is likely related to the low restrictions in habitat use of C. bonariense. In every projection, however, most PAs were expected to lose effectiveness, as by 2070 most PAs fall outside the range of the predicted distribution of C. bonariense. Thus, the creation or enlargement of PAs in these areas is recommended and these results represent an important information for the conservation of endemic freshwater insects under global warming scenarios in an overlooked Neotropical landscape.     

不同气候条件下沙冬青属植物在我国的潜在分布——基于生态位模型预测

沙冬青属（Ammopiptanthus）植物是古地中海第三纪孑遗濒危物种,包括沙冬青（Ammopiptanthus mgolicus）和矮沙冬青（Ammopiptanthus nanus）,主要分布在我国西北干旱、半干旱地区,其不仅具有较高的研究价值,同时对我国西北干旱地区生态环境具有十分重要的作用。近年来由于全球气候变化及人为干扰等因素,沙冬青属植物天然分布面积骤缩,濒临灭绝。本研究利用MaxEnt模型、Bioclim模型和Domain模型对沙冬青属植物在我国末次间冰期（Last Interglacial）、末次冰盛期（Last Glacial Maximum）、当代和2050年（RCP4.5和RCP8.5）4个时期气候情景下的潜在适生区进行预测。结果表明：MaxEnt模型对沙冬青属植物潜在分布区的预测具有极高的准确度,所有模型的平均受试者工作特征曲线下面积（AUC测试值）均高于0.80。当代沙冬青最佳及高适生区占全国总面积的2.78%,主要集中在内蒙古中部、宁夏北部和甘肃北部等地;未来沙冬青最佳及高适生区在现有分布范围呈现向外扩张的趋势,主要分布在内蒙古鄂托克旗、鄂尔多斯、阿拉善左旗、宁夏吴忠和甘肃民勒县等地。当代矮沙冬青最佳及高适生区占全国总面积的2.23%,主要集中在新疆南部;未来矮沙冬青最佳及高适生区向新疆乌恰县南部、乌鲁木齐北部移动和扩大,主要分布在新疆乌恰县、乌苏市、吐鲁番市和乌鲁木齐市。未来2050年（RCP4.5和RCP8.5）两种气候情景下沙冬青和矮沙冬青的潜在分布总面积均有所增加,与当代相比变化不明显,但不同适生等级的潜在分布面积变化较大,在更高的CO₂排放量（RCP8.5）情景下沙冬青和矮冬青的最佳及高适生区范围的预测结果都将减少。从气候因素角度考虑,研究表明未来气候情景下沙冬青属植物的适生区变化过程中,年均温（Bio1）、最湿月降水量（Bio13）和温度季节性变化（Bio4）是影响沙冬青属植物分布的关键因子,并为我国西北干旱半干旱地区具有重要的经济价值并将持续其生态服务功能。