Identifying the habitat suitability and built-in corridors for Asiatic black bear (Ursus thibetanus) movement in the northern highlands of Pakistan

Identifying habitat suitability and potential corridors are important tools for biodiversity conservation in the face of climate change. We modeled habitat suitability and simulated possible corridors for movement and gene flow among the Asiatic black bear (Ursus thibetanus) population in the Northern Highlands of Pakistan (NHP). Results indicated that the areas of 13,923 km² and 21,931 km² suitable for the Asiatic black bear under current and future scenarios respectively. Under the future scenario, we found an area of 12,657 km² (57.21%) as increase in suitable habitat (ISH_f) and 4649 km² (33.39%) area as a decrease in current suitable habitat (DSH_c). Our model predicted that about >65% (9274 km²) of the current suitable habitat as a climate refugia which is projected from the center to southeast east and northwest of the NHP primarily in the Khyber Pakhtunkhwa (KPK) and Pakistan Administered Kashmir (PAK). The attitudinal range of refugia was projected from 688 m to 4483 m with >56% at the elevations between 2001 m to 3000 m. A very small portion of suitable habitats (current suitable habitat = 2.75%, future suitable habitat = 5.11%) were projected under the protected areas. Maps connecting suitable habitats identified different regions delineated as important for the dispersal of Asiatic black bears, which mainly distributed in the PAK and KPK. Our results help informs conservation strategies and management plans for mitigating the impacts of climate change on Asiatic black bears in the NHP.     

Identifying refugia and corridors under climate change conditions for the Sichuan snub‐nosed monkey (Rhinopithecus roxellana) in Hubei Province,China

Using a case study of an isolated management unit of Sichuan snub‐nosed monkey (Rhinopithecus roxellana), we assess the extent that climate change will impact the species’ habitat distribution in the current period and projected into the 2050s. We identify refugia that could maintain the population under climate change and determine dispersal paths for movement of the population to future suitable habitats. Hubei Province, China. We identified climate refugia and potential movements by integrating bioclimatic models with circuit theory and least‐cost model for the current period (1960–1990) and the 2050s (2041–2060). We coupled a maximum entropy algorithm to predict suitable habitat for the current and projected future periods. Suitable habitat areas that were identified during both time periods and that also satisfied home range and dispersal distance conditions were delineated as refugia. We mapped potential movements measured as current flow and linked current and future habitats using least‐cost corridors. Our results indicate up to 1,119 km² of currently suitable habitat within the study range. Based on our projections, a habitat loss of 67.2% due to climate change may occur by the 2050s, resulting in a reduced suitable habitat area of 406 km² and very little new habitat. The refugia areas amounted to 286 km² and were located in Shennongjia National Park and Badong Natural Reserve. Several connecting corridors between the current and future habitats, which are important for potential movements, were identified. Our assessment of the species predicted a trajectory of habitat loss following anticipated future climate change. We believe conservation efforts should focus on refugia and corridors when planning for future species management. This study will assist conservationists in determining high‐priority regions for effective maintenance of the endangered population under climate change and will encourage increased habitat connectivity.     

Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya

Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator–prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy‐deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate‐only model shows that only 11.64% (17,190 km²) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km² (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate‐only model. It is predicted that future climate may alter the predator–prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards – a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future.     

Spatial conservation planning under climate change: Using species distribution modeling to assess priority for adaptive management of Fagus crenata in Japan

Protected areas are the basis of modern conservation systems, but current climate change causes gaps between protected areas and the species distribution ranges. To mitigate the impact of climate change on species distribution ranges, revision of protected areas are necessary. Alternatively, active management such as excluding competitive species or transplanting target species would be effective. In this study, we assessed optimal actions (revision of protected areas or active management) in each geographical region to establish an effective spatial conservation plan in Japan. Gaps between the protected areas and future potential habitats were assessed using species distribution models and 20 future climate simulations. Fagus crenata, an endemic and dominant species in Japan, was used as a target species. Potential habitats within the protected areas were predicted to decrease from 22,122 km² at present to 12,309 km² under future climate conditions. Sustainable potential habitats (consistent potential habitats both at present and in future) without the protected areas extended to 13,208 km², and were mainly found in northeast Japan. These results suggest that, in northeast Japan, revisions to protected areas would be effective in preserving sustainable potential habitats under future climate change. However, the potential habitats of southwestern Japan, in which populations were genetically different from northeastern populations, were predicted to virtually disappear both within and outside of protected areas. Active management is thus necessary in southwestern Japan to ensure intraspecific genetic diversity under future climate change.     

Identifying climate refugia and its potential impact on Tibetan brown bear (Ursus arctos pruinosus) in Sanjiangyuan National Park,China

Climate change has direct impacts on wildlife and future biodiversity protection efforts. Vulnerability assessment and habitat connectivity analyses are necessary for drafting effective conservation strategies for threatened species such as the Tibetan brown bear (Ursus arctos pruinosus). We used the maximum entropy (MaxEnt) model to assess the current (1950–2000) and future (2041–2060) habitat suitability by combining bioclimatic and environmental variables, and identified potential climate refugia for Tibetan brown bears in Sanjiangyuan National Park, China. Next, we selected Circuit model to simulate potential migration paths based on current and future climatically suitable habitat. Results indicate a total area of potential suitable habitat under the current climate scenario of approximately 31,649.46 km², of which 28,778.29 km² would be unsuitable by the 2050s. Potentially suitable habitat under the future climate scenario was projected to cover an area of 23,738.6 km². Climate refugia occupied 2,871.17 km², primarily in the midwestern and northeastern regions of Yangtze River Zone, as well as the northern region of Yellow River Zone. The altitude of climate refugia ranged from 4,307 to 5,524 m, with 52.93% lying at altitudes between 4,300 and 4,600 m. Refugia were mainly distributed on bare rock, alpine steppe, and alpine meadow. Corridors linking areas of potentially suitable brown bear habitat and a substantial portion of paths with low‐resistance value were distributed in climate refugia. We recommend various actions to ameliorate the impact of climate change on brown bears, such as protecting climatically suitable habitat, establishing habitat corridors, restructuring conservation areas, and strengthening monitoring efforts.     

气候变化情景下裸冠菊在中国的潜在适生区分布预测

外来入侵植物裸冠菊(Gymnocoronis spilanthoides)具有较强的入侵适应性能快速繁殖扩散,会对本土物种的生长繁殖及本地生态安全、景观格局等产生不良影响。基于265个有效分布点和7个环境变量,调整优化预测模型的调控倍频和特征组合参数,应用MaxEnt、ArcGIS、R软件预测当前和未来(2050s, 2070s)不同气候情景(SSP126, SSP245,SSP370, SSP585)下裸冠菊在中国的潜在地理分布,定量分析其适生区的空间变化及质心移动轨迹,最后采用受试者工作特征(ROC)曲线下面积(AUC)和测试遗漏率评估模型的精确性。未来气候模式选择中国国家气候中心开发的CMIP6中BCC-CSM2-MR。结果表明：(1)模型预测结果极准确,各组模型的AUC值均高于0.97;(2)最干季降水量(bio17)、最冷季度平均温(bio11)、温度季节性变化(bio4)和最暖季度平均降雨量(bio18)是影响裸冠菊地理分布的主导气候因子;(3)当前气候条件下,裸冠菊的总适生区面积达到191.18×10⁴km²,约占国土总面积的1...     

Expansion risk of the toxic dinoflagellate Gymnodinium catenatum blooms in Chinese waters under climate change

The paralytic shellfish poison toxin (PST)-producing dinoflagellate, Gymnodinium catenatum, frequently blooms in China, posing a threat to food safety and human health. To understand the drivers of G. catenatum blooms and predict potential habitats for G. catenatum under climate change, samples from occurrence localities and environmental datasets from multiple agencies were aggregated and used to model the habitat suitability of G. catenatum in the China Sea using a maximum entropy model (Maxent). The accumulated variable contributions for the Maxent model were defined to measure the importance of key predictors in the model. The most important environmental variables were distance to the coastline, depth of seawater, and long-term average of the minimum annual temperature. This highlights the main reasons why G. catenatum blooms always occur in coastal waters. Occurrence probabilities higher than 0.66 were defined as habitats with high suitability for shellfish management and aquaculture. Projected habitats with high suitability in Haizhou Bay, coastal waters along the western Taiwan Strait, and Bohai Bay remained stable with increasing temperature by 2100, regardless of the IPCC Representative Concentration Pathways (RCPs). However, those in the China Sea would be reduced overall, leading to a northward movement of the center of integrated habitats. Habitats with a spatial area of >6000 km² in the Bohai Sea, Yellow Sea, and South China Sea and >23,000 km² in the East China Sea would be exposed to high risk under low greenhouse gas emission scenarios (RCP2.6).     

The impact of climate change on the distribution of rare and endangered tree Firmiana kwangsiensis using the Maxent modeling

The upsurge in anthropogenic climate change has accelerated the habitat loss and fragmentation of wild animals and plants. The rare and endangered plants are important biodiversity elements. However, the lack of comprehensive and reliable information on the spatial distribution of these organisms has hampered holistic and efficient conservation management measures. We explored the consequences of climate change on the geographical distribution of Firmiana kwangsiensis (Malvaceae), an endangered species, to provide a reference for conservation, introduction, and cultivation of this species in new ecological zones. Modeling of the potential distribution of F. kwangsiensis under the current and two future climate scenarios in maximum entropy was performed based on 30 occurrence records and 27 environmental variables of the plant. We found that precipitation‐associated and temperature‐associated variables limited the potentially suitable habitats for F. kwangsiensis. Our model predicted 259,504 km² of F. kwangsiensis habitat based on 25 percentile thresholds. However, the high suitable habitat for F. kwangsiensis is only about 41,027 km². F. kwangsiensis is most distributed in Guangxi''s protected areas. However, the existing reserves are only 2.7% of the total suitable habitat and 4.2% of the high suitable habitat for the plant, lower than the average protection area in Guangxi (7.2%). This means the current protected areas network is insufficient, underlining the need for alternative conservation mechanisms to protect the plant habitat. Our findings will help identify additional F. kwangsiensis localities and potential habitats and inform the development and implementation of conservation, management, and cultivation practices of such rare tree species.     

美味猕猴桃地理分布模拟与气候变化影响分析

为了解气候变化对美味猕猴桃(Actinidia deliciosa)地理分布的影响,结合气候情景,采用Maxent预测美味猕猴桃的适生区的变化趋势。结果表明,基准气候和未来情景下构建的美味猕猴桃分布模型的AUC值均达到极好的标准。基准气候条件下,美味猕猴桃在中国的适生区为22°~38°N,96°~122°E,总面积为3.367 9×106 km2,高适生区位于秦岭-巴山、四川盆地东部、云贵高原东部、武陵山-巫山、武夷山脉。RCP4.5和RCP8.5情景下,美味猕猴桃在中国的高适生区面积将显著减少,中适生区面积则呈增加趋势,两种情景下高、中质心均向偏南或低纬度方向移动,RCP8.5情景下质心的迁移轨迹最长,变动范围最大。Maxent模型的准确预测对于优化猕猴桃产业结构具有重要指导意义。     

The influence of coarse‐scale environmental features on current and predicted future distributions of narrow‐range endemic crayfish populations

1. A major limitation to effective management of narrow‐range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2. Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate‐change scenarios. 3. The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 65–87% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4. Current models created using two spatial resolutions (1 and 4.5 km²) showed that fine‐resolution data more accurately represented current distributions. For three of the four species, the 1‐km² resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1‐km² resolution models were more accurate than 4.5‐km² resolution models. 5. Future projected (4.5‐km² resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low‐emission scenario, whereas two of four species would be severely restricted in range under moderate–high emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species‐distribution models. 6. These model predictions illustrate possible impacts of climate change on narrow‐range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.     

Precipitation of the warmest quarter and temperature of the warmest month are key to understanding the effect of climate change on plant species diversity in Southern African savannah

In this study, we test for the key bioclimatic variables that significantly explain the current distribution of plant species richness in a southern African ecosystem as a preamble to predicting plant species richness under a changed climate. We used 54,000 records of georeferenced plant species data to calculate species richness and spatially interpolated climate data to derive nineteen bioclimatic variables. Next, we determined the key bioclimatic variables explaining variation in species richness across Zimbabwe using regression analysis. Our results show that two bioclimatic variables, that is, precipitation of the warmest quarter (R² = 0.92, P < 0.001) and temperature of the warmest month (R² = 0.67, P < 0.001) significantly explain variation in plant species richness. In addition, results of bioclimatic modelling using future climate change projections show a reduction in the current bio‐climatically suitable area that supports high plant species richness. However, in high‐altitude areas, plant richness is less sensitive to climate change while low‐altitude areas show high sensitivity. Our results have important implications to biodiversity conservation in areas sensitive to climate change; for example, high‐altitude areas are likely to continue being biodiversity hotspots, as such future conservation efforts should be concentrated in these areas.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

Predicting the distributions of Pouteria adolfi-friederici and Prunus africana tree species under current and future climate change scenarios in Ethiopia

Distributions of potential ranges of plant species are not yet fully known in Ethiopia where high climatic variability and vegetation types are found. This study was undertaken to predict distributions of suitable habitats of Pouteria adolfi-friederici and Prunus africana under current and two future climate scenarios (RCP 4.5 and RCP 8.5 in 2050 and 2070) in Ethiopia. Eleven environmental variables with less correlation coefficients (r < 0.7) were used to make the prediction. Shifting in extents of habitat suitability and effects of elevation, solar radiation and topographic position in relation to the current and future climatic scenarios were statistically analysed using independent t-test and linear model. We found decreasing area of highly suitable habitat from 0.51% to 0.46%, 0.36% and 0.33%, 0.24% for Prunus africana and 1.13% to 1.02%, 0.77% and 0.76%, 0.60% for Pouteria adolfi-friederici, under RCP 4.5 and RCP 8.5 by 2050 and 2070 respectively. Moist and dry afromontane forests are identified as the most suitable habitat for both species. Overall, our results suggest that climate change can promote dynamic suitable habitat niches under different future climate scenarios. Therefore, biodiversity conservation strategies should take into account habitat suitability dynamics issues and identify where to conserve species before implementing conservation practices.     

Potential distribution of Notopterygium incisum Ting ex H. T. Chang and its predicted responses to climate change based on a comprehensive habitat suitability model

Notopterygium incisum Ting ex H. T. Chang is a rare and endangered traditional Chinese medicinal plant. In this research, we built a comprehensive habitat suitability (CHS) model to analyze the potential suitable habitat distribution of this species in the present and future in China. First, using nine different algorithms, we built an ensemble model to explore the possible impacts of climate change on the habitat distribution of this species. Then, based on this model, we built a CHS model to further identify the distribution characteristics of N. incisum‐suitable habitats in three time periods (current, 2050s, and 2070s) while considering the effects of soil and vegetation conditions. The results indicated that the current suitable habitat for N. incisum covers approximately 83.76 × 10³ km², and these locations were concentrated in the Tibet Autonomous Region, Gansu Province, Qinghai Province, and Sichuan Province. In the future, the areas of suitable habitat for N. incisum would significantly decrease and would be 69.53 × 10³ km² and 60.21 × 10³ km² in the 2050s and 2070s, respectively. However, the area of marginally suitable habitat would remain relatively stable. This study provides a more reliable and comprehensive method for modelling the current and future distributions of N. incisum, and it provides valuable insights for highlighting priority areas for medicinal plant conservation and resource utilization.     

Climate change decreases the cooling effect from postfire albedo in boreal North America

Fire is a primary disturbance in boreal forests and generates both positive and negative climate forcings. The influence of fire on surface albedo is a predominantly negative forcing in boreal forests, and one of the strongest overall, due to increased snow exposure in the winter and spring months. Albedo forcings are spatially and temporally heterogeneous and depend on a variety of factors related to soils, topography, climate, land cover/vegetation type, successional dynamics, time since fire, season, and fire severity. However, how these variables interact to influence albedo is not well understood, and quantifying these relationships and predicting postfire albedo becomes increasingly important as the climate changes and management frameworks evolve to consider climate impacts. Here we developed a MODIS‐derived ‘blue sky’ albedo product and a novel machine learning modeling framework to predict fire‐driven changes in albedo under historical and future climate scenarios across boreal North America. Converted to radiative forcing (RF), we estimated that fires generate an annual mean cooling of ?1.77 ± 1.35 W/m² from albedo under historical climate conditions (1971–2000) integrated over 70 years postfire. Increasing postfire albedo along a south–north climatic gradient was offset by a nearly opposite gradient in solar insolation, such that large‐scale spatial patterns in RF were minimal. Our models suggest that climate change will lead to decreases in mean annual postfire albedo, and hence a decreasing strength of the negative RF, a trend dominated by decreased snow cover in spring months. Considering the range of future climate scenarios and model uncertainties, we estimate that for fires burning in the current era (2016) the cooling effect from long‐term postfire albedo will be reduced by 15%–28% due to climate change.     

气候变化对雪豹全球潜在适生区分布的影响与评估

气候变化不仅是人类正在面临的挑战,也是野生动物需要应对的危机。雪豹(Panthera uncia)作为亚洲中部高原和山脉的旗舰种,它的生存和繁衍可以反映青藏高原等地区生态系统的健康状况。青藏高原等地区的气候变暖速度远快于全球平均水平,研究气候变化对雪豹的生境的影响对于高原物种的保护有重要意义。以雪豹为研究对象,采用第六次国际耦合模式比较计划(CMIP6)气候模式下四种共享社会经济路径(SSPs)对应的未来21世纪中期和21世纪末期的环境数据,并基于最大熵模型(MaxEnt),结合ENMTool、SDMTool、ArcGIS和R等工具对当前和未来全球不同发展模式引起的气候变化对雪豹适宜生境的影响进行了模拟预测和分析评估。研究发现：(1)影响雪豹分布的主要环境因素包括：两种气候变量(年平均气温和最冷月最低温度),两种地形变量(海拔和坡度)和一种水文变量(距离最近河流的距离)。(2)当前气候模式下雪豹的全球潜在适宜分布区的总面积约为1122.05万km²,其中低适生区面积为534.5万km²,中适生区面积为386.15万km²...     

Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change

Climate change influences species geographical distribution and diversity pattern. The Chinese fire‐bellied newt (Cynops orientalis) is an endemic species distributed in East‐central China, which has been classified as near‐threatened species recently due to habitat destruction and degradation and illegal trade in the domestic and international pet markets. So far, little is known about the spatial distribution of the species. Based on bioclimatic data of the current and future climate projections, we modeled the change in suitable habitat for C. orientalis by ten algorithms, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. In this study, 46 records of C. orientalis from East China and 8 bioclimatic variables were used. Among the ten modeling algorithms, four (GAM, GBM, Maxent, and RF) were selected according to their predictive abilities. The current habitat suitability showed that C. orientalis had a relatively wide but fragmented distribution, and it encompassed 41,862 km². The models suggested that precipitation of warmest quarter (bio18) and mean temperature of wettest quarter (bio6) had the highest contribution to the model. This study revealed that C. orientalis is sensitive to climate change, which will lead to a large range shift. The projected spatial and temporal pattern of range shifts for C. orientalis should provide a useful reference for implementing long‐term conservation and management strategies for amphibians in East China.     

Habitat assessment of Marco Polo sheep (Ovis ammon polii) in Eastern Tajikistan: Modeling the effects of climate change

Identifying the factors predicting the high‐elevation suitable habitats of Central Asian argali wild sheep and how these suitable habitats are affected by the changing climate regimes could help address conservation and management efforts and identify future critical habitat for the species in eastern Tajikistan. This study used environmental niche models (ENMs) to map and compare potential present and future distributions of suitable environmental conditions for Marco Polo argali. Argali occurrence points were collected during field surveys conducted from 2009 to 2016. Our models showed that terrain ruggedness and annual mean temperature had strong correlations on argali distribution. We then used two greenhouse gas concentration trajectories (RCP 4.5 and RCP 8.5) for two future time periods (2050 and 2070) to model the impacts of climate change on Marco Polo argali habitat. Results indicated a decline of suitable habitat with majority of losses observed at lower elevations (3,300–4,300 m). Models that considered all variables (climatic and nonclimatic) predicted losses of present suitable areas of 60.6% (6,928 km²) and 63.2% (7,219 km²) by 2050 and 2070, respectively. Results also showed averaged habitat gains of 46.2% (6,106 km²) at much higher elevations (4,500–6,900 m) and that elevational shifts of habitat use could occur in the future. Our results could provide information for conservation planning for this near threatened species in the region.     

Evaluation of habitat sustainability and vulnerability for beech (Fagus crenata) forests under 110 hypothetical climatic change scenarios in Japan

Questions: Are there any sustainable or vulnerable habitats in which beech (Fagus crenata) forests could survive in Japan under 110 hypothetical climate change scenarios? Location: Six islands of Japan on which beech grows naturally. Methods: An ecological habitat model was used to simulate the potential habitat shifts of beech forests under 110 climate change scenarios. The amount of suitable habitat loss and gain was calculated with three migration options and risk surfaces. Vulnerable and sustainable habitats were identified to evaluate the potential risks and survival of beech forests. Results: The total areas of potential suitable habitats differed considerably depending on the future temperature and precipitation changes. Some areas on the Sea of Japan (SOJ) side showed higher probability of maintaining suitable habitats, whereas there were wider areas in which suitable habitats could not persist under any of the 110 climate change scenarios. Conclusions: The risk surfaces of the suitable habitats showed that decreases in precipitation along with increases in temperature reduced the total areas of suitable habitats. Increases in precipitation with increases in temperature of more than or equal to 2°C always reduce the areas of suitable habitats. Under increased precipitation with a temperature increase of <2°C, the areas of suitable habitats showed an increase, maintenance of the status quo or a decrease, depending on the size of the increase in precipitation. Beech forests in western Japan are predicted to be vulnerable to climate change, whereas some mountains on the SOJ side are predicted to be possible future refugia.     

Predicted declines in suitable habitat for greater one‐horned rhinoceros (Rhinoceros unicornis) under future climate and land use change scenarios

Rapidly changing climate is likely to modify the spatial distribution of both flora and fauna. Land use change continues to alter the availability and quality of habitat and further intensifies the effects of climate change on wildlife species. We used an ensemble modeling approach to predict changes in habitat suitability for an iconic wildlife species, greater one‐horned rhinoceros due to the combined effects of climate and land use changes. We compiled an extensive database on current rhinoceros distribution and selected nine ecologically meaningful environmental variables for developing ensemble models of habitat suitability using ten different species distribution modeling algorithms in the BIOMOD2 R package; and we did this under current climatic conditions and then projected them onto two possible climate change scenarios (SSP1‐2.6 and SSP5‐8.5) and two different time frames (2050 and 2070). Out of ten algorithms, random forest performed the best, and five environmental variables—distance from grasslands, mean temperature of driest quarter, distance from wetlands, annual precipitation, and slope, contributed the most in the model. The ensemble model estimated the current suitable habitat of rhinoceros to be 2610 km², about 1.77% of the total area of Nepal. The future habitat suitability under the lowest and highest emission scenarios was estimated to be: (1) 2325 and 1904 km² in 2050; and (2) 2287 and 1686 km² in 2070, respectively. Our results suggest that over one‐third of the current rhinoceros habitat would become unsuitable within a period of 50 years, with the predicted declines being influenced to a greater degree by climatic changes than land use changes. We have recommended several measures to moderate these impacts, including relocation of the proposed Nijgad International Airport given that a considerable portion of potential rhinoceros habitat will be lost if the airport is constructed on the currently proposed site.