Potential Distribution of Dengue Fever Under Scenarios of Climate Change and Economic Development

Dengue fever is the most important viral vector-borne disease with ~50 million cases per year globally. Previous estimates of the potential effect of global climate change on the distribution of vector-borne disease have not incorporated the effect of socioeconomic factors, which may have biased the results. We describe an empirical model of the current geographic distribution of dengue, based on the independent effects of climate and gross domestic product per capita (GDPpc, a proxy for socioeconomic development). We use the model, along with scenario-based projections of future climate, economic development, and population, to estimate populations at risk of dengue in the year 2050. We find that both climate and GDPpc influence the distribution of dengue. If the global climate changes as projected but GDPpc remained constant, the population at risk of dengue is estimated to increase by about 0.28 billion in 2050. However, if both climate and GDPpc change as projected, we estimate a decrease of 0.12 billion in the population at risk of dengue in 2050. Empirically, the geographic distribution of dengue is strongly dependent on both climatic and socioeconomic variables. Under a scenario of constant GDPpc, global climate change results in a modest but important increase in the global population at risk of dengue. Under scenarios of high GDPpc, this adverse effect of climate change is counteracted by the beneficial effect of socioeconomic development.     

Potential Distribution Predicted for Rhynchophorus ferrugineus in China under Different Climate Warming Scenarios

As the primary pest of palm trees, Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) has caused serious harm to palms since it first invaded China. The present study used CLIMEX 1.1 to predict the potential distribution of R. ferrugineus in China according to both current climate data (1981–2010) and future climate warming estimates based on simulated climate data for the 2020s (2011–2040) provided by the Tyndall Center for Climate Change Research (TYN SC 2.0). Additionally, the Ecoclimatic Index (EI) values calculated for different climatic conditions (current and future, as simulated by the B2 scenario) were compared. Areas with a suitable climate for R. ferrugineus distribution were located primarily in central China according to the current climate data, with the northern boundary of the distribution reaching to 40.1°N and including Tibet, north Sichuan, central Shaanxi, south Shanxi, and east Hebei. There was little difference in the potential distribution predicted by the four emission scenarios according to future climate warming estimates. The primary prediction under future climate warming models was that, compared with the current climate model, the number of highly favorable habitats would increase significantly and expand into northern China, whereas the number of both favorable and marginally favorable habitats would decrease. Contrast analysis of EI values suggested that climate change and the density of site distribution were the main effectors of the changes in EI values. These results will help to improve control measures, prevent the spread of this pest, and revise the targeted quarantine areas.     

An Objective Approach to Select Climate Scenarios when Projecting Species Distribution under Climate Change

An impressive number of new climate change scenarios have recently become available to assess the ecological impacts of climate change. Among these impacts, shifts in species range analyzed with species distribution models are the most widely studied. Whereas it is widely recognized that the uncertainty in future climatic conditions must be taken into account in impact studies, many assessments of species range shifts still rely on just a few climate change scenarios, often selected arbitrarily. We describe a method to select objectively a subset of climate change scenarios among a large ensemble of available ones. Our k-means clustering approach reduces the number of climate change scenarios needed to project species distributions, while retaining the coverage of uncertainty in future climate conditions. We first show, for three biologically-relevant climatic variables, that a reduced number of six climate change scenarios generates average climatic conditions very close to those obtained from a set of 27 scenarios available before reduction. A case study on potential gains and losses of habitat by three northeastern American tree species shows that potential future species distributions projected from the selected six climate change scenarios are very similar to those obtained from the full set of 27, although with some spatial discrepancies at the edges of species distributions. In contrast, projections based on just a few climate models vary strongly according to the initial choice of climate models. We give clear guidance on how to reduce the number of climate change scenarios while retaining the central tendencies and coverage of uncertainty in future climatic conditions. This should be particularly useful during future climate change impact studies as more than twice as many climate models were reported in the fifth assessment report of IPCC compared to the previous one.     

Modeling the Impact of White-Plague Coral Disease in Climate Change Scenarios

Coral reefs are in global decline, with coral diseases increasing both in prevalence and in space, a situation that is expected only to worsen as future thermal stressors increase. Through intense surveillance, we have collected a unique and highly resolved dataset from the coral reef of Eilat (Israel, Red Sea), that documents the spatiotemporal dynamics of a White Plague Disease (WPD) outbreak over the course of a full season. Based on modern statistical methodologies, we develop a novel spatial epidemiological model that uses a maximum-likelihood procedure to fit the data and assess the transmission pattern of WPD. We link the model to sea surface temperature (SST) and test the possible effect of increasing temperatures on disease dynamics. Our results reveal that the likelihood of a susceptible coral to become infected is governed both by SST and by its spatial location relative to nearby infected corals. The model shows that the magnitude of WPD epidemics strongly depends on demographic circumstances; under one extreme, when recruitment is free-space regulated and coral density remains relatively constant, even an increase of only 0.5°C in SST can cause epidemics to double in magnitude. In reality, however, the spatial nature of transmission can effectively protect the community, restricting the magnitude of annual epidemics. This is because the probability of susceptible corals to become infected is negatively associated with coral density. Based on our findings, we expect that infectious diseases having a significant spatial component, such as Red-Sea WPD, will never lead to a complete destruction of the coral community under increased thermal stress. However, this also implies that signs of recovery of local coral communities may be misleading; indicative more of spatial dynamics than true rehabilitation of these communities. In contrast to earlier generic models, our approach captures dynamics of WPD both in space and time, accounting for the highly seasonal nature of annual WPD outbreaks.     

气候变化下青藏高原全缘叶绿绒蒿的潜在分布变迁

青藏高原物种丰富且属于气候变化敏感区,研究气候变化对青藏高原物种的潜在分布影响,对于该区域物种多样性保护具有重要意义。该研究以一级濒危藏药植物全缘叶绿绒蒿为研究对象,利用加权平均算法(weighted average algorithm, WAA)构建随机森林(RF)、灵活判别分析(FDA)及人工神经网络(ANN)的集成模型,同时对比分析了WAA模型和不同生态位模型的预测精度。最后利用WAA模型预测了全缘叶绿绒蒿在当前(1970~2000年平均)和未来(2041~2060年平均)气候情景下的潜在分布,其中未来气候考虑了2种“共享社会经济路径”(SSP2-45和SSP5-85)。结果显示:(1) WAA模型的预测表明,基于RF、FDA和ANN的集成模型的AUC值为0.926,在AUC值最高RF模型的基础上提高了3%,在FDA和ANN模型的AUC值的基础上均提高了5%。(2) WAA模型确定,全缘叶绿绒蒿的潜在分布对年降水量和最暖季降水量最为敏感,其次是最热月份最高气温,同时对最湿月份降水量以及等温性表现出较低的敏感性。(3)当前全缘叶绿绒蒿潜在分布区主要分布在甘肃西南部、青海东部至南部、四川西部和西北部、云南西北部和东北部、西藏东部。(4)未来气候变化下青藏高原全缘叶绿绒蒿潜在分布预测表明,在2050年SSP2-45情景下,全缘叶绿绒蒿的潜在分布区大小与当前潜在分布区大小基本相同,但整体向西北方向高海拔高纬度地区迁移;在SSP5-85情景下,全缘叶绿绒蒿的潜在分布区明显收缩,且向西北高纬度高海拔地区延伸的趋势更加明显。     

气候变化下青藏高原两种云杉植物的潜在适生区预测

为了预测未来气候变化下云杉属植物的适宜生境,选择青藏高原暗针叶林的两种重要建群植物丽江云杉（Picea likiangensis）和紫果云杉（Picea purpurea）作为研究对象,采用MaxEnt模型预测21世纪50年代（2050s）和70年代（2070s）两物种在未来气候情景下的潜在分布,并结合ArcGIS计算物种分布面积和空间格局变化。结果表明：（1）丽江云杉的潜在适宜分布区主要集中在四川西南部和西藏东部。紫果云杉潜在适宜分布区主要集中在四川西北部、甘肃南部、青海东南部,以及西藏东部地区。（2）在未来两个时期丽江云杉的分布面积总体呈增加趋势,紫果云杉呈先增加后减少的趋势,但与其现代分布面积相比,两种云杉的总适生区面积都有不同程度的增加。（3）丽江云杉适宜生境未来可能会向北迁移,而紫果云杉可能会向西迁移。（4）影响丽江云杉和紫果云杉潜在地理分布的主要气候因子为最暖季降水量和最暖季均温。研究结果可为丽江云杉和紫果云杉在未来气候变化情景下的可持续管理提供一定的理论依据和参考价值。     

气候变化情景下中国荒漠锦鸡儿潜在适生区的时空变化分析

荒漠锦鸡儿是一种强旱生矮灌木,主要分布在荒漠草原和草原化荒漠中。该研究以植物志和数字标本库中获取的130条记录生成的荒漠锦鸡儿分布记录样点图为基础,运用组合模型(ESDM)模拟荒漠锦鸡儿在末次冰盛期、全新世中期、当前和未来(2030s)气候情景下的潜在地理分布,通过ArcGIS计算适生区面积及质心迁移轨迹,探讨末次冰盛期以来气候变迁对荒漠锦鸡儿分布的影响,为气候变化背景下荒漠锦鸡儿的保护提供理论基础。结果表明:(1)降水因子对荒漠锦鸡儿分布的影响高于温度因子和地形因子。(2)当前荒漠锦鸡儿的中、高适生区面积为10.172×10^(5) km^(2),质心位于阿拉善左旗。(3)末次冰盛期质心向东南迁移至全新世中期质心,继而向东北迁移至当前质心,荒漠锦鸡儿能较好地适应末次冰盛期寒冷干燥的环境。(4)在未来RCP2.6、RCP4.5和RCP6.0情景下,荒漠锦鸡儿中、高适生区面积均成增加趋势,但RCP8.5情景下的适生区面积却比当前减少了1.981×105 km^(2)。研究推测,轻度的气候变暖有利于荒漠锦鸡儿的生存与分布。     

Climate Change Influences on the Global Potential Distribution of Bluetongue Virus

The geographic distribution of arboviruses has received considerable attention after several dramatic emergence events around the world. Bluetongue virus (BTV) is classified among category “A” diseases notifiable to the World Organization of Animal Health (OIE), and is transmitted among ruminants by biting midges of the genus Culicoides. Here, we developed a comprehensive occurrence data set to map the current distribution, estimate the ecological niche, and explore the future potential distribution of BTV globally using ecological niche modeling and based on diverse future climate scenarios from general circulation models (GCMs) for four representative concentration pathways (RCPs). The broad ecological niche and potential geographic distribution of BTV under present-day conditions reflected the disease’s current distribution across the world in tropical, subtropical, and temperate regions. All model predictions were significantly better than random expectations. As a further evaluation of model robustness, we compared our model predictions to 331 independent records from most recent outbreaks from the Food and Agriculture Organization Emergency Prevention System for Transboundary Animal and Plant Pests and Diseases Information System (EMPRES-i); all were successfully anticipated by the BTV model. Finally, we tested ecological niche similarity among possible vectors and BTV, and could not reject hypotheses of niche similarity. Under future-climate conditions, the potential distribution of BTV was predicted to broaden, especially in central Africa, United States, and western Russia.     

气候变化下耐旱藓类连轴藓属在新疆的分布模拟

该研究基于耐旱藓类连轴藓属5种53条在新疆的地理分布信息和7个气候变量,利用最大熵模型和ArcGIS 10.2软件,分别模拟现代气候和未来气候情景下连轴藓属在新疆的适生分布区,为探讨气候变化对干旱、半干旱区苔藓植物物种分布的影响提供参考。结果表明:(1)Maxent模型预测连轴藓属在新疆适生区的准确性非常高(AUC=0.957)。(2)年降雨量、最干季度降雨量和最暖季度平均气温是影响连轴藓属分布的主要气候因子。(3)连轴藓属在新疆的适生区主要集中在阿尔泰山和天山沿线,在未来(2061~2080年)气候情景下,连轴藓属分布面积将比现代气候下减少10.39%,其绝大部分现有南部适生区将丧失。     

The Fate of Threatened Coastal Dune Habitats in Italy under Climate Change Scenarios

Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an “indirect” plant-species-based one and a simple “direct” one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the “direct” approach was unsatisfactory, “indirect” models had a good predictive performance, highlighting the importance of using species’ responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats’ distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.     

Forecasting the Effects of Land Use Scenarios on Farmland Birds Reveal a Potential Mitigation of Climate Change Impacts

Climate and land use changes are key drivers of current biodiversity trends, but interactions between these drivers are poorly modeled, even though they could amplify or mitigate negative impacts of climate change. Here, we attempt to predict the impacts of different agricultural change scenarios on common breeding birds within farmland included in the potential future climatic suitable areas for these species. We used the Special Report on Emissions Scenarios (SRES) to integrate likely changes in species climatic suitability, based on species distribution models, and changes in area of farmland, based on the IMAGE model, inside future climatic suitable areas. We also developed six farmland cover scenarios, based on expert opinion, which cover a wide spectrum of potential changes in livestock farming and cropping patterns by 2050. We ran generalized linear mixed models to calibrate the effects of farmland cover and climate change on bird specific abundance within 386 small agricultural regions. We used model outputs to predict potential changes in bird populations on the basis of predicted changes in regional farmland cover, in area of farmland and in species climatic suitability. We then examined the species sensitivity according to their habitat requirements. A scenario based on extensification of agricultural systems (i.e., low-intensity agriculture) showed the greatest potential to reduce reverse current declines in breeding birds. To meet ecological requirements of a larger number of species, agricultural policies accounting for regional disparities and landscape structure appear more efficient than global policies uniformly implemented at national scale. Interestingly, we also found evidence that farmland cover changes can mitigate the negative effect of climate change. Here, we confirm that there is a potential for countering negative effects of climate change by adaptive management of landscape. We argue that such studies will help inform sustainable agricultural policies for the future.     

Projected Future Distributions of Vectors of Trypanosoma cruzi in North America under Climate Change Scenarios

Background

Chagas disease kills approximately 45 thousand people annually and affects 10 million people in Latin America and the southern United States. The parasite that causes the disease, Trypanosoma cruzi, can be transmitted by insects of the family Reduviidae, subfamily Triatominae. Any study that attempts to evaluate risk for Chagas disease must focus on the ecology and biogeography of these vectors. Expected distributional shifts of vector species due to climate change are likely to alter spatial patterns of risk of Chagas disease, presumably through northward expansion of high risk areas in North America.

Methodology/Principal Findings

We forecast the future (2050) distributions in North America of Triatoma gerstaeckeri and T. sanguisuga, two of the most common triatomine species and important vectors of Trypanosoma cruzi in the southern United States. Our aim was to analyze how climate change might affect the future shift of Chagas disease in North America using a maximum entropy algorithm to predict changes in suitable habitat based on vector occurrence points and predictive environmental variables. Projections based on three different general circulation models (CCCMA, CSIRO, and HADCM3) and two IPCC scenarios (A2 and B2) were analyzed. Twenty models were developed for each case and evaluated via cross-validation. The final model averages result from all twenty of these models. All models had AUC >0.90, which indicates that the models are robust. Our results predict a potential northern shift in the distribution of T. gerstaeckeri and a northern and southern distributional shift of T. sanguisuga from its current range due to climate change.

Conclusions/Significance

The results of this study provide baseline information for monitoring the northward shift of potential risk from Chagas disease in the face of climate change.     

气候变化背景下基于MaxEnt模型的刺梨潜在适生区分布预测

为阐明气候变化背景下刺梨(Rosa roxburghii)在中国的潜在适生区分布,该研究基于刺梨的自然分布数据及当代(1960～1990)、未来(21世纪50年代及70年代)气候因子数据,采用最大熵(MaxEnt)模型模拟了当前和未来气候情景下刺梨在中国的潜在适生区,并确定影响其地理分布的主要气候因子.结果表明:(1)...     

全球气候变化下贵州省青冈林的潜在生境动态

为了解贵州省青冈林在全球气候变化下的潜在分布特征,基于现状分布数据,结合当前气候数据和未来气候变化情景(RCP8.5情景,2070-2099年)构建Maxent潜在分布模型,预测贵州省青冈林的潜在分布变化。结果表明,最冷季均温(bio11)、最冷月最低温度(bio6)和年均降水量(bio12)为控制贵州省青冈林潜在生境的主导气候因子;RCP8.5情景下贵州省青冈林的潜在分布面积相较当前气候条件增加,中度适宜生境增加19 419 km2,高度适宜生境增加9 944 km2;中度适宜生境平均海拔较当前气候条件上升126 m,高度适宜生境平均上升85 m。总的来说,贵州省青冈林对全球气候变化的响应不十分敏感。     

气候变化下矩镰荚苜蓿的地理分布格局及潜在适生区预测

该研究基于标本和文献信息,选取19个环境因子和1个海拔因子,利用ArcGIS软件和MaxEnt模型对矩镰荚苜蓿(Medicago archiducis nicolai)在5个气候情景(末次间冰期、末次盛冰期、全新世纪中期、当前和未来气候)下的地理分布进行空间重建,模拟预测了气候变化背景下的分布格局和潜在适生区变迁。预测结果显示：(1)当前气候下,矩镰荚苜蓿集中分布在青藏高原东缘与黄土高原的交汇地带,具体包括青海东部 南部、甘肃中部 西南部、四川西北部、宁夏南部、西藏东部和陕西西部边缘。(2)高海拔、寒冷和干燥是矩镰荚苜蓿适生区的主要环境特征。(3)不同气候下潜在适生区的总面积变化相对稳定,但高度适生区对气候变化较敏感,从末次间冰期到末次盛冰期,高度适生区从青海东部的河湟谷地向甘肃中部的洮河谷地东移,全新世纪中期又西移至河湟谷地,但始终没有迁离出陇中盆地。(4)未来气候(2070s)背景下,矩镰荚苜蓿的高度和中度适生区面积较当前气候有小幅增加,但潜在适生区面积和分布格局仍保持稳定。研究表明,在青藏高原东缘地带,由昆仑山、祁连山和秦岭三大山脉造就的高原盆谷,为矩镰荚苜蓿提供了安全的就地避难所,形成了其独特而稳定的狭域分布格局,未来气候变化(2070s)对该植物不会造成很大威胁。     

气候变化对6种荒漠植物分布的潜在影响

分析气候变化对植物分布的影响,对保护生物多样性具有重要意义。利用CART(分类和回归树)模型及A2和B2情景,分析了气候变化对短叶假木贼(Anabasis brevifolia)、裸果木(Gymnocarpos przewalskii)、梭梭(Haloxylon ammoden-dron)、膜果麻黄(Ephedra przewalskii)、驼绒藜(Ceratoides latens)和喀什膜果麻黄(Ephedra przewalskii var.kaschgarica)分布范围及空间格局的影响。结果表明:气候变化下,这些植物目前适宜分布范围减小;从新适宜及总适宜分布范围而言,短叶假木贼和梭梭从1991-2020年到2051-2080年时段增加,之后减小,其它植物从1991-2020年到2081-2100年时段减小;喀什膜果麻黄和驼绒藜适宜分布范围减小并破碎化,其它植物向目前适宜分布的西部、西北部(或青海西南部)、昆仑山、阿尔金山和祁连山区扩展;除驼绒藜和喀什膜果麻黄与年均气温变化具显著相关性外,其它植物分布范围与年均气温和降水量变化的相关性较弱(P0.05),除驼绒藜、喀什膜果麻黄和裸果木目前分布范围与年均气温和降水量变化的回归关系较强外,其它植物分布范围与年均气温和年降水量变化多元线性回归关系较弱。上述研究结果表明,气候变化下,这些植物空间分布格局改变,目前分布范围减少,新适宜及总适宜分布范围近期增加,随着气候变化程度的增强,又逐渐减小。     

Potential Changes in the Distributions of Western North America Tree and Shrub Taxa under Future Climate Scenarios

Increases in atmospheric greenhouse gases are driving significant changes in global climate. To project potential vegetation response to future climate change, this study uses response surfaces to describe the relationship between bioclimatic variables and the distribution of tree and shrub taxa in western North America. The response surfaces illustrate the probability of the occurrence of a taxon at particular points in climate space. Climate space was defined using three bioclimatic variables: mean temperature of the coldest month, growing degree days, and a moisture index. Species distributions were simulated under present climate using observed data (1951–80, 30-year mean) and under future climate (2090–99, 10-year mean) using scenarios generated by three general circulation models—HADCM2, CGCM1, and CSIRO. The scenarios assume a 1% per year compound increase in greenhouse gases and changes in sulfate (SO₄) aerosols based on the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. The results indicate that under future climate conditions, potential range changes could be large for many tree and shrub taxa. Shifts in the potential ranges of species are simulated to occur not only northward but in all directions, including southward of the existing ranges of certain species. The simulated potential distributions of some species become increasingly fragmented under the future climate scenarios, while the simulated potential distributions of other species expand. The magnitudes of the simulated range changes imply significant impacts to ecosystems and shifts in patterns of species diversity in western North America. Received 12 May 2000; accepted 20 December 2000.     

气候变化对6种荒漠植物分布的潜在影响

分析气候变化对植物分布的影响,对保护生物多样性具有重要意义。利用CART（分类和回归树）模型及A2和B2情景,分析了气候变化对短叶假木贼（Anabasis brevifolia）、裸果木（Gymnocarpos przewalskii）、梭梭（Haloxylon ammoden-dron）、膜果麻黄（Ephedra przewalskii）、驼绒藜（Ceratoides latens）和喀什膜果麻黄（Ephedra przewalskii var.kaschgarica）分布范围及空间格局的影响。结果表明：气候变化下,这些植物目前适宜分布范围减小;从新适宜及总适宜分布范围而言,短叶假木贼和梭梭从1991-2020年到2051-2080年时段增加,之后减小,其它植物从1991-2020年到2081-2100年时段减小;喀什膜果麻黄和驼绒藜适宜分布范围减小并破碎化,其它植物向目前适宜分布的西部、西北部（或青海西南部）、昆仑山、阿尔金山和祁连山区扩展;除驼绒藜和喀什膜果麻黄与年均气温变化具显著相关性外,其它植物分布范围与年均气温和降水量变化的相关性较弱（P〉0.05）,除驼绒藜、喀什膜果麻黄和裸果木目前分布范围与年均气温和降水量变化的回归关系较强外,其它植物分布范围与年均气温和年降水量变化多元线性回归关系较弱。上述研究结果表明,气候变化下,这些植物空间分布格局改变,目前分布范围减少,新适宜及总适宜分布范围近期增加,随着气候变化程度的增强,又逐渐减小。     

气候变化对7种保护植物分布的潜在影响

利用CART（classification and regression tree,分类和回归树）模型,采用A2和B2气候变化情景,模拟分析了气候变化对桫椤（Alsophila spinulosa（wall.ex hook.）Tryon）、水青树（Tetracentron sinenseOliv）、十齿花（Dipentondon sinicus Dunn）、青檀（Pteroceltis tatarinowii Maxim）、桃儿七（Sinopodophyllum emodi（Wall.）Ying）、太白红杉（Larix chinensis Beissn）和山白树（Sinowilsonia henryi Hemsl）的分布范围及空间格局的可能影响。结果显示：在气候变化下,这些植物目前适宜分布范围将缩小,其中太白红杉、山白树和水青树减少幅度较大,十齿花和青檀次之,桫椤和桃儿七较小。就植物新适宜及总适宜分布范围,太白红杉和山白树从1991～2020年到2081～2100年时段呈现减少趋势,其它植物却呈现增加趋势。气候变化下,这些植物空间分布格局将发生较大改变,太白红杉将失去适宜分布范围,其它植物目前适宜分布区的西部、南部、西南、东部和东南部一些区域将不再适宜,新适宜分布区将主要向北部、东北部、西部、西南或西北部一些区域扩展。气候变化下,这些植物适宜分布范围与年均气温和降水量变化的相关性并不一致,一些植物适宜分布范围与年均气温和降水量变化相关系数并不显著（p〉0.05）;除了桫椤新适宜及总适宜、十齿花和桃儿七目前适宜分布范围与年均气温和年降水量变化回归关系较密切外,其它植物适宜分布范围与年均气温和年降水量变化的多元线性回归关系都较弱。这说明,在气候变化情况下,这些植物空间分布格局将发生改变,目前适宜分布范围缩小,除太白红杉和山白树外,其他几种植物新适宜范围扩大。