Climate change induced elevational range shifts of Himalayan tree species

Global warming may force montane species to shift upward to keep pace with their shifting climate niche. How species differences in such distribution shifts depend on their elevational positions, elevation-dependent warming rates, and other environmental constraints, or plant functional traits is poorly understood. Here, we analyzed for 137 Himalayan tree species how distribution shifts vary with elevational niche positions, environmental constraints, and their functional traits. We developed ecological niche models using MaxEnt by combining species survey and botanical collections data with 19 environmental predictors. Species distributions were projected to 1985 and 2050 conditions, and elevational range parameters and distribution areas were derived. Under the worst-case RCP 8.5 scenario, species are predicted to shift, on average, 3 m/year in optimum elevation, and have 33% increase in distribution area. Highland species showed faster predicted elevational shifts than lowland species. Lowland and highland species are predicted to expand in distribution area in contrast to mid-elevation species. Tree species for which species distribution models are driven by responses to temperature, aridity, or soil clay content showed the strongest predicted upslope shifts. Tree species with conservative trait values that enable them to survive resource poor conditions (i.e., narrow conduits) showed larger predicted upslope shifts than species with wide conduits. The predicted average upslope shift in maximum elevation (8 m/year) is >2 times faster than the current observations indicating that many species will not be able to track climate change and potentially go extinct, unless they are supported by active conservation measures, such as assisted migration.     

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。     

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。     

Current and Future Niche of North and Central American Sand Flies (Diptera: Psychodidae) in Climate Change Scenarios

Ecological niche models are useful tools to infer potential spatial and temporal distributions in vector species and to measure epidemiological risk for infectious diseases such as the Leishmaniases. The ecological niche of 28 North and Central American sand fly species, including those with epidemiological relevance, can be used to analyze the vector''s ecology and its association with transmission risk, and plan integrated regional vector surveillance and control programs. In this study, we model the environmental requirements of the principal North and Central American phlebotomine species and analyze three niche characteristics over future climate change scenarios: i) potential change in niche breadth, ii) direction and magnitude of niche centroid shifts, iii) shifts in elevation range. Niche identity between confirmed or incriminated Leishmania vector sand flies in Mexico, and human cases were analyzed. Niche models were constructed using sand fly occurrence datapoints from Canada, USA, Mexico, Guatemala and Belize. Nine non-correlated bioclimatic and four topographic data layers were used as niche components using GARP in OpenModeller. Both B2 and A2 climate change scenarios were used with two general circulation models for each scenario (CSIRO and HadCM3), for 2020, 2050 and 2080. There was an increase in niche breadth to 2080 in both scenarios for all species with the exception of Lutzomyia vexator. The principal direction of niche centroid displacement was to the northwest (64%), while the elevation range decreased greatest for tropical, and least for broad-range species. Lutzomyia cruciata is the only epidemiologically important species with high niche identity with that of Leishmania spp. in Mexico. Continued landscape modification in future climate change will provide an increased opportunity for the geographic expansion of NCA sand flys'' ENM and human exposure to vectors of Leishmaniases.     

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.     

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.     

Predicting current and future distributions of Mentha pulegium L. in Tunisia under climate change conditions,using the MaxEnt model

Climate change and human activities have caused the degeneration of the natural habitats of medicinal plants. Mentha pulegium L. is one of the most common medicinal plants in Tunisia that features high economic and ecological values. Predicting species' suitable habitats, through modeling, has evolved as a useful tool for the assessment of resource conservation to protect medicinal plants. Herein, we used MaxEnt model to predict current and future distributions of M. pulegium under two representative concentration pathways (RCP2.6 and RCP8.5) for the years 2050 and 2070. MaxEnt modeling was in the “Excellent” category since all the AUCs were above 0.9. Results showed that high and moderate suitable habitats for the current distribution of M. pulegium encompassed ca. 9929 km² and 16,423 km², respectively. These areas are mainly located in North Tunisia. Precipitation of the coldest quarter (Bio19) was identified as the most critical factor shaping M. pulegium distribution. Compared to the current distribution, the highly and moderately suitable areas for M. pulegium under the two RCPs (RCP2.6 and RCP8.5) would decrease in the 2050s and 2070s. The model projected a shift of the suitable area from Northeastward to Center-eastward. These results may provide a useful tool for developing adaptive management strategies to enhance M. pulegium protection and sustainable utilization in the context of global climate change.     

中国特有属秤锤树属植物的潜在分布区预测

秤锤树属（Sinojackia）是中国特有属,包括7个物种,各物种的种群及个体数量均较少,预测其潜在适宜分布区及其主要影响因素对制定保护措施至关重要。该研究在全面收集秤锤树属植物分布位点数据的基础上,结合气候、土壤和植被数据,运用物种分布模型（MaxEnt）和ArcGIS,预测该属植物当前的分布范围以及未来（2050s和2070s）潜在分布区的变化,分析影响该属植物分布的主要环境变量。预测结果显示：（1）当前秤锤树属高适宜地区主要在我国的亚热带地区,分布在长江中下游平原,包括湖南、浙江的大部分地区,河南、安徽和江苏南部地区以及湖北和江西两省交界处,四川、贵州零星分布着高适宜度位点;纬度范围为25.42°~31.84°N。（2）当前秤锤树属的高适宜性（0.665）生境面积仅为4.07×10⁴ km²,占国土面积的4.23％,分布区极为狭窄。未来（2050s和2070s）的高适宜分布地区将大幅度缩减,其中在2070s的RCP8.5排放情景下减少最多。（3）随着温度的上升,秤锤树属植物有向高纬度迁移的趋势。研究结果可为濒危植物的就地保护提供科学依据,同时也可为其迁地保护位点的选择提供参考。     

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.     

Inferring distributional shifts of epidemiologically important North and Central American sandflies from Pleistocene to future scenarios

Nine sandfly species (Diptera: Psychodidae) are suspected or proven vectors of Leishmania spp. in the North and Central America region. The ecological niches for these nine species were modelled in three time periods and the overlaps for all time periods of the geographic predictions (G space), and of ecological dimensions using pairwise comparisons of equivalent niches (E space), were calculated. Two Nearctic, six Neotropical and one species in both bioregions occupied a reduced number of distribution areas. The ecological niche projections for most sandfly species other than Lutzomyia shannoni and Lutzomyia ovallesi have not expanded significantly since the Pleistocene. Only three species increase significantly to 2050, whereas all others remain stable. Lutzomyia longipalpis shared a similar ecological niche with more species than any other, although both L. longipalpis and Lutzomyia olmeca olmeca had conserved distributions over time. Climate change, at both regional and local levels, will play a significant role in the temporal and spatial distributions of sandfly species.     

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.     

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.     

未来气候变化下黑沙蒿在中国的潜在地理分布及变迁

黑沙蒿是我国荒漠草原防风固沙的先驱植物,在生态系统恢复和重建中有非常重要的作用,然而其在发挥重要生态功能之余,也给我国北方地区人类的健康带来了一定影响。本研究基于黑沙蒿当前在中国分布的89条有效数据和典型19个气候环境因子,通过MaxEnt模型,模拟了当前和未来(2050s、2070s)2种情景下(RCP 4.5、RCP 8.5)黑沙蒿在中国的潜在分布区,利用ArcGIS软件中SDM工具箱分析黑沙蒿的潜在分布范围及其变化,综合贡献率、刀切法及环境变量响应曲线评估了关键气候因子的重要性,并使用检验受试者工作特征(ROC)曲线下面积(AUC)对模型精度检验和评估。结果表明: MaxEnt模型模拟效果极好(AUC=0.980),预测显示黑沙蒿主要集中分布在毛乌素沙地及周边地区,该结果与当前实际分布范围相吻合;黑沙蒿在未来2种情景下的潜在高适生区分布面积与当前相比减少了5.2%～26.8%,气候变化对黑沙蒿的分布有一定的负面影响,其中,温度季节变化、最冷季度降水量及年平均温度的影响最大;黑沙蒿未来在中国潜在分布核心区位于毛乌素沙地,且有向东北部(吉林、黑龙江、辽宁及河北部分地区)扩散趋势。     

Shifts in the ecological niche of Lutzomyia peruensis under climate change scenarios in Peru

The Peruvian Andes presents a climate suitable for many species of sandfly that are known vectors of leishmaniasis or bartonellosis, including Lutzomyia peruensis (Diptera: Psychodidae), among others. In the present study, occurrences data for Lu. peruensis were compiled from several items in the scientific literature from Peru published between 1927 and 2015. Based on these data, ecological niche models were constructed to predict spatial distributions using three algorithms [Support vector machine (SVM), the Genetic Algorithm for Rule‐set Prediction (GARP) and Maximum Entropy (MaxEnt)]. In addition, the environmental requirements of Lu. peruensis and three niche characteristics were modelled in the context of future climate change scenarios: (a) potential changes in niche breadth; (b) shifts in the direction and magnitude of niche centroids, and (c) shifts in elevation range. The model identified areas that included environments suitable for Lu. peruensis in most regions of Peru (45.77%) and an average altitude of 3289 m a.s.l. Under climate change scenarios, a decrease in the distribution areas of Lu. peruensis was observed for all representative concentration pathways. However, the centroid of the species' ecological niche showed a northwest direction in all climate change scenarios. The information generated in this study may help health authorities responsible for the supervision of strategies to control leishmaniasis to coordinate, plan and implement appropriate strategies for each area of risk, taking into account the geographic distribution and potential dispersal of Lu. peruensis.     

未来气候变化对重庆榨菜种植适宜区的影响

榨菜为十字花科植物,是我国特有的经济作物,气候因子是影响榨菜种植分布的重要因素.通过收集榨菜分布的279个坐标点和22个高分辨率环境因子图层,利用MaxEnt模型进行重庆榨菜种植区预测,并基于该模型预测政府间气候变化专门委员会(IPCC)发布的RCP 2.6、RCP 4.5、RCP 6.0和RCP 8.5气候情景下21世纪50和70年代榨菜种植区分布范围.结果表明: MaxEnt模型的预测效果为优秀,其中,最湿月份降水量(贡献率为30.2%).年均温变化范围(17.2%)、最冷月份最低温(9.6%)、等温性(9.1%)、昼夜温差月均值(8.1%)和平均最高温度(7.5%)6个因子为主导因子,累积贡献率高达81.7％,且其各主导因子阈值分别为173～183 mm、27.2～28.3 ℃、1.8～3.8 ℃、22.5～24 ℃、6.2～6.8 ℃和14.8～18.0 ℃.在当前气候条件下,榨菜的适宜种植区比例为4.2%,主要集中在重庆涪陵的东北、西部和东部、长寿的东部和南部、垫江的南部和东南部、丰都的西北部和北部、忠县的东南部区域,以及武隆和南川的少部分区域等,中度适宜种植区面积比例为6.3%.在RCP 2.6、RCP 4.5、RCP 6.0和RCP 8.5气候情景下,预测21世纪50年代榨菜适宜生境的比例下降,分别为2.7%、3.8％、3.1％和3.2％;21世纪70年代比例也下降,分别为3.1%、3.7％、3.5％和2.9％,而中度适宜种植区的比例有所上升.     

Alpha richness and niche breadth of a widespread group of aquatic insects in Nearctic and Neotropical streams

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Predicted changes in the potential distribution of seerfish (Scomberomorus sierra) under multiple climate change scenarios in the Colombian Pacific Ocean

Some projections predict that fishery resources in tropical areas will be negatively affected by climate change, resulting in the displacement of species and reducing their availability for fishing. In this study, the potential geographic distribution of Scomberomorus sierra under current conditions in the Colombian Pacific Ocean was simulated using maximum entropy (MaxEnt) modeling software, based on species presence data and satellite-derived environmental variables (Sea Surface Temperature (SST), Chlorophyll-a and bathymetry). The future distributions of S. sierra in 2020s (short term) and 2080s (long term) were projected under the RCP 2.6 and 8.5 scenarios for four ensembled global circulation models (GCM) obtained from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The current and future geographical distributions were modeled for the species' fishing months (November to April), and pixel-wise change distribution and core shift were determined. The results indicated good performance for the distribution models in the present and future scenarios (AUC > 0.9). The RCP 8.5 scenario, in both, the short and long term, indicated the highest adverse changes in the species distribution. The distribution core shift indicates that under RCP 2.6 in the 2020s for November and December, the shift is towards the central zone of the Colombian Pacific. In the 2080s (long term), the distribution centroid tends to move towards the central zone, further from the coastline. Results also showed the same change tendency for RCP 8.5 in both the 2020s and 2080s. This is one of the first studies that elucidate the effects of climate change on a commercial species in the Colombian Pacific. The results give an insight into future management strategies for seerfish fisheries, which can also be used as a reference for studying other species.     

Tracing the future of epidemics: Coincident niche distribution of host animals and disease incidence revealed climate-correlated risk shifts of main zoonotic diseases in China

Climate has critical roles in the origin, pathogenesis and transmission of infectious zoonotic diseases. However, large-scale epidemiologic trend and specific response pattern of zoonotic diseases under future climate scenarios are poorly understood. Here, we projected the distribution shifts of transmission risks of main zoonotic diseases under climate change in China. First, we shaped the global habitat distribution of main host animals for three representative zoonotic diseases (2, 6, and 12 hosts for dengue, hemorrhagic fever, and plague, respectively) with 253,049 occurrence records using maximum entropy (Maxent) modeling. Meanwhile, we predicted the risk distribution of the above three diseases with 197,098 disease incidence records from 2004 to 2017 in China using an integrated Maxent modeling approach. The comparative analysis showed that there exist highly coincident niche distributions between habitat distribution of hosts and risk distribution of diseases, indicating that the integrated Maxent modeling is accurate and effective for predicting the potential risk of zoonotic diseases. On this basis, we further projected the current and future transmission risks of 11 main zoonotic diseases under four representative concentration pathways (RCPs) (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) in 2050 and 2070 in China using the above integrated Maxent modeling with 1,001,416 disease incidence records. We found that Central China, Southeast China, and South China are concentrated regions with high transmission risks for main zoonotic diseases. More specifically, zoonotic diseases had diverse shift patterns of transmission risks including increase, decrease, and unstable. Further correlation analysis indicated that these patterns of shifts were highly correlated with global warming and precipitation increase. Our results revealed how specific zoonotic diseases respond in a changing climate, thereby calling for effective administration and prevention strategies. Furthermore, these results will shed light on guiding future epidemiologic prediction of emerging infectious diseases under global climate change.     

Projected climate changes threaten ancient refugia of kelp forests in the North Atlantic

Intraspecific genetic variability is critical for species adaptation and evolution and yet it is generally overlooked in projections of the biological consequences of climate change. We ask whether ongoing climate changes can cause the loss of important gene pools from North Atlantic relict kelp forests that persisted over glacial–interglacial cycles. We use ecological niche modelling to predict genetic diversity hotspots for eight species of large brown algae with different thermal tolerances (Arctic to warm temperate), estimated as regions of persistence throughout the Last Glacial Maximum (20,000 YBP), the warmer Mid‐Holocene (6,000 YBP), and the present. Changes in the genetic diversity within ancient refugia were projected for the future (year 2100) under two contrasting climate change scenarios (RCP2.6 and RCP8.5). Models predicted distributions that matched empirical distributions in cross‐validation, and identified distinct refugia at the low latitude ranges, which largely coincide among species with similar ecological niches. Transferred models into the future projected polewards expansions and substantial range losses in lower latitudes, where richer gene pools are expected (in Nova Scotia and Iberia for cold affinity species and Gibraltar, Alboran, and Morocco for warm‐temperate species). These effects were projected for both scenarios but were intensified under the extreme RCP8.5 scenario, with the complete borealization (circum‐Arctic colonization) of kelp forests, the redistribution of the biogeographical transitional zones of the North Atlantic, and the erosion of global gene pools across all species. As the geographic distribution of genetic variability is unknown for most marine species, our results represent a baseline for identification of locations potentially rich in unique phylogeographic lineages that are also climatic relics in threat of disappearing.     

北重楼潜在适生区对气候变化的响应及其主导气候因子

基于现有物种数据结合气候变量来预测物种的潜在地理分布,对于了解物种进化以及合理保护具有重要意义。本研究基于中国境内220个北重楼分布点和12个相关系数较低的气候因子,利用MaxEnt模型和ArcGIS软件预测了北重楼在当前时期和未来时期(2050s、2070s)的潜在适生区,并分析了影响其地理分布的主导气候因子。结果表明: MaxEnt模型AUC值为0.940,预测结果准确性较高;当前时期,北重楼的总适生区面积占整个研究区域面积的18.1%,其中,高适生区和低适生区分别占7.0%和11.1%,主要位于大兴安岭、小兴安岭、长白山山脉、秦岭-大巴山区、河北、山西以及山东北部等地区;未来时期在RCP 2.6、RCP 4.5、RCP 6.0、RCP 8.5气候情景下,2050s和2070s中国境内北重楼的总适生区面积均呈现缩减趋势,其中,高适生区面积均减少,而低适生区面积则全部有所增加,且北重楼适生区的范围和几何中心逐渐向东北方向的高海拔地区扩散;影响北重楼地理分布的主导气候因子分别为最湿月降水量、年平均温度、等温性和1月降水量,累积贡献率高达89.2%,其适宜范围分别为100～275 mm、-0.1～16 ℃、21～35和3～14 mm。