Climate change at the landscape scale: predicting fine-grained spatial heterogeneity in warming and potential refugia for vegetation

Current predictions of how species will respond to climate change are based on coarse‐grained climate surfaces or idealized scenarios of uniform warming. These predictions may erroneously estimate the risk of extinction because they neglect to consider spatially heterogenous warming at the landscape scale or identify refugia where species can persist despite unfavourable regional climate. To address this issue, we investigated the heterogeneity in warming that has occurred in a 10 km × 10 km area from 1972 to 2007. We developed estimates by combining long‐term daily observations from a limited number of weather stations with a more spatially comprehensive dataset (40 sites) obtained during 2005–2006. We found that the spatial distribution of warming was greater inland, at lower elevations, away from streams, and at sites exposed to the northwest (NW). These differences corresponded with changes in weather patterns, such as an increasing frequency of hot, dry NW winds. As plant species were biased in the topographic and geographic locations they occupied, these differences meant that some species experienced more warming than others, and are at greater risk from climate change. This species bias could not be detected at coarser scales. The uneven seasonal nature of warming (e.g. more warming in winter, minimums increased more than maximums) means that climate change predictions will vary according to which predictors are selected in species distribution models. Models based on a limited set of predictors will produce erroneous predictions when the correct limiting factor is not selected, and this is difficult to avoid when temperature predictors are correlated because they are produced using elevation‐sensitive interpolations. The results reinforce the importance of downscaling coarse‐grained (∼50 km) temperature surfaces, and suggest that the accuracy of this process could be improved by considering regional weather patterns (wind speed, direction, humidity) and topographic exposure to key wind directions.     

Impact of landscape predictors on climate change modelling of species distributions: a case study with Eucalyptus fastigata in southern New South Wales,Australia

Aim We consider three questions. (1) How different are the predicted distribution maps when climate‐only and climate‐plus‐terrain models are developed from high‐resolution data? (2) What are the implications of differences between the models when predicting future distributions under climate change scenarios, particularly for climate‐only models at coarse resolution? (3) Does the use of high‐resolution data and climate‐plus‐terrain models predict an increase in the number of local refugia? Location South‐eastern New South Wales, Australia. Methods We developed two species distribution models for Eucalyptus fastigata under current climate conditions using generalized additive modelling. One used only climate variables as predictors (mean annual temperature, mean annual rainfall, mean summer rainfall); the other used both climate and landscape (June daily radiation, topographic position, lithology, nutrients) variables as predictors. Predictions of the distribution under current climate and climate change were then made for both models at a pixel resolution of 100 m. Results The model using climate and landscape variables as predictors explained a significantly greater proportion of the deviance than the climate‐only model. Inclusion of landscape variables resulted in the prediction of much larger areas of existing optimal habitat. An overlay of predicted future climate on the current climate space indicated that extrapolation of the statistical models was not occurring and models were therefore more robust. Under climate change, landscape‐defined refugia persisted in areas where the climate‐only model predicted major declines. In areas where expansion was predicted, the increase in optimal habitat was always greater with landscape predictors. Recognition of extensive optimal habitat conditions and potential refugia was dependent on the use of high‐resolution landscape data. Main conclusions Using only climate variables as predictors for assessing species responses to climate change ignores the accepted conceptual model of plant species distribution. Explicit statements justifying the selection of predictors based on ecological principles are needed. Models using only climate variables overestimate range reduction under climate change and fail to predict potential refugia. Fine‐scale‐resolution data are required to capture important climate/landscape interactions. Extrapolation of statistical models to regions in climate space outside the region where they were fitted is risky.     

Will northern fish populations be in hot water because of climate change?

Predicted increases in water temperature in response to climate change will have large implications for aquatic ecosystems, such as altering thermal habitat and potential range expansion of fish species. Warmwater fish species, such as smallmouth bass, Micropterus dolomieu , may have access to additional favourable thermal habitat under increased surface-water temperatures, thereby shifting the northern limit of the distribution of the species further north in Canada and potentially negatively impacting native fish communities. We assembled a database of summer surface-water temperatures for over 13 000 lakes across Canada. The database consists of lakes with a variety of physical, chemical and biological properties. We used general linear models to develop a nation-wide maximum lake surface-water temperature model. The model was extended to predict surface-water temperatures suitable to smallmouth bass and under climate-change scenarios. Air temperature, latitude, longitude and sampling time were good predictors of present-day maximum surface-water temperature. We predicted lake surface-water temperatures for July 2100 using three climate-change scenarios. Water temperatures were predicted to increase by as much as 18 °C by 2100, with the greatest increase in northern Canada. Lakes with maximum surface-water temperatures suitable for smallmouth bass populations were spatially identified. Under several climate-change scenarios, we were able to identify lakes that will contain suitable thermal habitat and, therefore, are vulnerable to invasion by smallmouth bass in 2100. This included lakes in the Arctic that were predicted to have suitable thermal habitat by 2100.     

Comparing stream-specific to generalized temperature models to guide salmonid management in a changing climate

Global climate change is predicted to increase air and stream temperatures and alter thermal habitat suitability for growth and survival of coldwater fishes, including brook charr (Salvelinus fontinalis), brown trout (Salmo trutta), and rainbow trout (Oncorhynchus mykiss). In a changing climate, accurate stream temperature modeling is increasingly important for sustainable salmonid management throughout the world. However, finite resource availability (e.g. funding, personnel) drives a tradeoff between thermal model accuracy and efficiency (i.e. cost-effective applicability at management-relevant spatial extents). Using different projected climate change scenarios, we compared the accuracy and efficiency of stream-specific and generalized (i.e. region-specific) temperature models for coldwater salmonids within and outside the State of Michigan, USA, a region with long-term stream temperature data and productive coldwater fisheries. Projected stream temperature warming between 2016 and 2056 ranged from 0.1 to 3.8 °C in groundwater-dominated streams and 0.2–6.8 °C in surface-runoff dominated systems in the State of Michigan. Despite their generally lower accuracy in predicting exact stream temperatures, generalized models accurately projected salmonid thermal habitat suitability in 82% of groundwater-dominated streams, including those with brook charr (80% accuracy), brown trout (89% accuracy), and rainbow trout (75% accuracy). In contrast, generalized models predicted thermal habitat suitability in runoff-dominated streams with much lower accuracy (54%). These results suggest that, amidst climate change and constraints in resource availability, generalized models are appropriate to forecast thermal conditions in groundwater-dominated streams within and outside Michigan and inform regional-level salmonid management strategies that are practical for coldwater fisheries managers, policy makers, and the public. We recommend fisheries professionals reserve resource-intensive stream-specific models for runoff-dominated systems containing high-priority fisheries resources (e.g. trophy individuals, endangered species) that will be directly impacted by projected stream warming.     

Use of an individual-based model to forecast the effect of climate change on the dynamics, abundance and geographical range of the pest slug Deroceras reticulatum in the UK

Slugs are serious agricultural pests and their activity is strongly driven by ambient temperature and soil moisture. The strength of this relationship has been shown through the development of a deterministic model, based upon temperature and soil moisture conditions alone, which accurately describes the population dynamics and abundance of Deroceras reticulatum . Because of this strong climatic dependence, slug abundance and dynamics are likely to be affected by climate change. We used a validated individual-based model (IbM) of D. reticulatum , to assess the effects of climate change on the abundance of this species in the UK. Climatic scenarios were based on the UKCIP02 predictions and constructed using the LARS-WG stochastic weather generator. The IbM of slugs predicted population dynamics at three time slices (2020s, 2050s and 2080s), and two scenarios of greenhouse gas emissions. The maximum generation number, the number of population peaks, the number of slug-days in each season, the percentage of years when the population passes over a threshold for damage and the percentage of years in which populations go extinct were investigated. Currently, the south-west of the UK has the best conditions for D. reticulatum to thrive, with the north-east of Scotland having the most adverse. By 2080 under both low- and high-emissions scenarios, the north and west of Scotland will have the most favourable conditions for the survival of this species and the east of the UK and Scotland will have the harshest. By 2080 the climate in the north-west of Scotland will become more like the current climate in south-east England, which explains the shift in the pattern of abundance. The north-west of Scotland will have increased slug damage and south-west England and west-Wales will have decreased slug damage with some changes becoming evident by 2020.     

Validation of species–climate impact models under climate change

Increasing concern over the implications of climate change for biodiversity has led to the use of species–climate envelope models to project species extinction risk under climate‐change scenarios. However, recent studies have demonstrated significant variability in model predictions and there remains a pressing need to validate models and to reduce uncertainties. Model validation is problematic as predictions are made for events that have not yet occurred. Resubstituition and data partitioning of present‐day data sets are, therefore, commonly used to test the predictive performance of models. However, these approaches suffer from the problems of spatial and temporal autocorrelation in the calibration and validation sets. Using observed distribution shifts among 116 British breeding‐bird species over the past ～20 years, we are able to provide a first independent validation of four envelope modelling techniques under climate change. Results showed good to fair predictive performance on independent validation, although rules used to assess model performance are difficult to interpret in a decision‐planning context. We also showed that measures of performance on nonindependent data provided optimistic estimates of models' predictive ability on independent data. Artificial neural networks and generalized additive models provided generally more accurate predictions of species range shifts than generalized linear models or classification tree analysis. Data for independent model validation and replication of this study are rare and we argue that perfect validation may not in fact be conceptually possible. We also note that usefulness of models is contingent on both the questions being asked and the techniques used. Implementations of species–climate envelope models for testing hypotheses and predicting future events may prove wrong, while being potentially useful if put into appropriate context.     

Climate‐change winners and losers: stream macroinvertebrates of a submontane region in Central Europe

1. Freshwater ecosystems will be profoundly affected by global climate change, especially those in mountainous areas, which are known to be particularly vulnerable to warming temperatures. We modelled impacts of climate change on the distribution ranges of 38 species of benthic stream macroinvertebrates from nine macroinvertebrate orders covering all river zones from the headwaters to large river reaches. 2. Species altitudinal shifts as well as range changes up to the year 2080 were simulated using the A2a and B2a Intergovernmental Panel on Climate Change climate‐warming scenarios. Presence‐only species distribution models were constructed for a stream network in Germany’s lower mountain ranges by means of consensus projections of four algorithms, as implemented in the BIOMOD package in R (GLM, GAM, GBM and ANN). 3. Species were predicted to shift an average of 122 and 83 m up in altitude along the river continuum by the year 2080 under the A2a and B2a climate‐warming scenarios, respectively. No correlation between altitudinal shifts and mean annual air temperature of species’ occurrence could be detected. 4. Depending on the climate‐warming scenario, most or all (97% for A2a and 100% for B2a) of the macroinvertebrate species investigated were predicted to survive under climate change in the study area. Ranges were predicted to contract for species that currently occur in streams with low annual mean air temperatures but expand for species that inhabit rivers where air temperatures are higher. 5. Our models predict that novel climate conditions will reorganise species composition and community structure along the river continuum. Possible effects are discussed, including significant reductions in population size of headwater species, eventually leading to a loss of genetic diversity. A shift in river species composition is likely to enhance the establishment of non‐native macroinvertebrates in the lower reaches of the river continuum.     

Climate change resilience of a globally important sea turtle nesting population

Few studies have looked into climate change resilience of populations of wild animals. We use a model higher vertebrate, the green sea turtle, as its life history is fundamentally affected by climatic conditions, including temperature‐dependent sex determination and obligate use of beaches subject to sea level rise (SLR). We use empirical data from a globally important population in West Africa to assess resistance to climate change within a quantitative framework. We project 200 years of primary sex ratios (1900–2100) and create a digital elevation model of the nesting beach to estimate impacts of projected SLR. Primary sex ratio is currently almost balanced, with 52% of hatchlings produced being female. Under IPCC models, we predict: (a) an increase in the proportion of females by 2100 to 76%–93%, but cooler temperatures, both at the end of the nesting season and in shaded areas, will guarantee male hatchling production; (b) IPCC SLR scenarios will lead to 33.4%–43.0% loss of the current nesting area; (c) climate change will contribute to population growth through population feminization, with 32%–64% more nesting females expected by 2120; (d) as incubation temperatures approach lethal levels, however, the population will cease growing and start to decline. Taken together with other factors (degree of foraging plasticity, rookery size and trajectory, and prevailing threats), this nesting population should resist climate change until 2100, and the availability of spatial and temporal microrefugia indicates potential for resilience to predicted impacts, through the evolution of nest site selection or changes in nesting phenology. This represents the most comprehensive assessment to date of climate change resilience of a marine reptile using the most up‐to‐date IPCC models, appraising the impacts of temperature and SLR, integrated with additional ecological and demographic parameters. We suggest this as a framework for other populations, species and taxa.     

Adaptive thermoregulation in endotherms may alter responses to climate change

Climate change is one of the major issues facing natural populations and thus a focus of recent research has been to predict the responses of organisms to these changes. Models are becoming more complex and now commonly include physiological traits of the organisms of interest. However, endothermic species have received less attention than have ectotherms in these mechanistic models. Further, it is not clear whether responses of endotherms to climate change are modified by variation in thermoregulatory characteristics associated with phenotypic plasticity and/or adaptation to past selective pressures. Here, we review the empirical data on thermal adaptation and acclimatization in endotherms and discuss how those factors may be important in models of responses to climate change. We begin with a discussion of why thermoregulation and thermal sensitivity at high body temperatures should be co-adapted. Importantly, we show that there is, in fact, considerable variation in the ability of endotherms to tolerate high body temperatures and/or high environmental temperatures, but a better understanding of this variation will likely be critical for predicting responses to future climatic scenarios. Next, we discuss why variation in thermoregulatory characteristics should be considered when modeling the effects of climate change on heterothermic endotherms. Finally, we review some biophysical and biochemical factors that will limit adaptation and acclimation in endotherms. We consider both long-term, directional climate change and short-term (but increasingly common) anomalies in climate such as extreme heat waves and we suggest areas of important future research relating to both our basic understanding of endothermic thermoregulation and the responses of endotherms to climate change.     

Expected future plague levels in a wildlife host under different scenarios of climate change

We predicted future plague and black-tailed prairie dog dynamics in the North American prairies under different scenarios of climate change. A climate-driven model for the joint dynamic of the host–parasite system was used. Projections for the regional climate were obtained through empirical–statistical downscaling of global climate scenarios generated by an ensemble of global climate models for the recent Fourth Assessment Report by the IPCC. The study shows the uncertainties involved in predicting future regional climate and climate-driven population dynamics, but reveals that unchanged or lower levels of plague, leading to increased black-tailed prairie dog colonies, can be expected. Less plague is particularly expected for scenarios that assume the highest emission of greenhouse gases associated with the greatest projected future warming. Moreover, under high-emission scenarios, decreased probabilities of extremely high numbers of infected colonies are expected, along with decreased probabilities of extremely low total numbers of colonies. The assumed main underlying mechanism is an inhibiting effect of high temperatures on fleas (dispersal vector) and on flea-mediated transmission of the disease-causing bacterium. Our study highlights the importance of using dynamic ecological (here host–parasite) models together with ensembles of climate projections to investigate the responses of populations and parasites to a changed climate.     

Evaluating within‐population variability in behavior and demography for the adaptive potential of a dispersal‐limited species to climate change

Multiple pathways exist for species to respond to changing climates. However, responses of dispersal‐limited species will be more strongly tied to ability to adapt within existing populations as rates of environmental change will likely exceed movement rates. Here, we assess adaptive capacity in Plethodon cinereus, a dispersal‐limited woodland salamander. We quantify plasticity in behavior and variation in demography to observed variation in environmental variables over a 5‐year period. We found strong evidence that temperature and rainfall influence P. cinereus surface presence, indicating changes in climate are likely to affect seasonal activity patterns. We also found that warmer summer temperatures reduced individual growth rates into the autumn, which is likely to have negative demographic consequences. Reduced growth rates may delay reproductive maturity and lead to reductions in size‐specific fecundity, potentially reducing population‐level persistence. To better understand within‐population variability in responses, we examined differences between two common color morphs. Previous evidence suggests that the color polymorphism may be linked to physiological differences in heat and moisture tolerance. We found only moderate support for morph‐specific differences for the relationship between individual growth and temperature. Measuring environmental sensitivity to climatic variability is the first step in predicting species' responses to climate change. Our results suggest phenological shifts and changes in growth rates are likely responses under scenarios where further warming occurs, and we discuss possible adaptive strategies for resulting selective pressures.     

水菜花种群潜在生境选择与空间格局预测

国家二级保护野生植物水菜花(Ottelia cordata)，喜生于清洁的水环境中，对环境变化极为敏感，是检验湿地环境及气候变化的关键指示物种之一，在我国仅零星分布于海南北部的火山熔岩湿地区，生存状况不容乐观。研究水菜花种群潜在生境选择及其空间格局演变，有利于加强濒危物种保护保育及湿地生态系统修复、管理。该研究基于GIS平台和MaxEnt模型，结合气候、地形和土壤因子，探究水菜花种群环境限制因子及其在气候变化背景下潜在适宜生境的演变格局。结果表明，水菜花种群对温差与降水量变化敏感，等温性、最冷季度降水量、土壤类型和年均降水量对水菜花种群分布影响显著；全新世中期-当前-2070年气候变化背景下，水菜花适宜生境面积先减小后增大，分布重心呈西南-东北-西南转移格局；未来气候情景下，水菜花种群高度和中度适宜生境缩减，低适宜生境增加，南部地区将出现新增适宜生境，东北、西北及西南部适宜生境将发生消减。该研究从气候环境角度论证了水菜花种群的潜在生境选择及空间变化特征，可为濒危物种保护保育、湿地管理及其生物多样性维护工作提供参考和指导。     

中南半岛前期异常气候条件对中国南方稻区褐飞虱灾变性迁入的影响及其预测模型

近30多年来,气候变化对中国褐飞虱的灾变性迁入带来了明显的影响,为了进一步了解虫源地的异常气候变化对我国褐飞虱迁入量的影响,利用1980—2016年中国各植保站提供的褐飞虱虫情资料及同期美国国家环境预测中心(NCEP)提供的全球气象再分析资料,分析了中国褐飞虱境外主要虫源地中南半岛前期异常气候条件对中国南方稻区褐飞虱发生程度的影响,并对褐飞虱发生等级与影响其迁飞的气象因子进行了相关性分析,筛选出关键预报因子,分别应用支持向量机(SVM)、BP神经网络和多元回归分析3种方法对代表站点褐飞虱年发生等级进行了预测,并比较了3种预测模型的优劣。结果表明:(1)中南半岛气候异常区主要分布在北部,异常气候的发生次数在中南半岛呈现出北高南低的特征,并从北向南呈环状递减。(2)中南半岛前期温度偏高(暖冬、暖春)、相对湿度偏大(湿冬、湿春),易引起褐飞虱在中国南方稻区的偏重以上发生;若中南半岛前期气候偏冷(冷冬、冷春)、偏干(干冬、干春),则常导致褐飞虱在中国南方稻区的偏轻以下发生。(3)通过比较3种模型的历史回代率和预测准确率,发现3种模型对褐飞虱的发生程度均有一定的预测能力,其中SVM模型的预测效果最好,BP神经网络次之,多元线性回归模型最差,表明SVM更加适用于生产实际中的褐飞虱发生程度预测。     

气候变化情景下大沙鼠潜在地理分布

大沙鼠（Rhombomys opimus）是中亚地区典型的荒漠啮齿动物，其采食和掘洞行为造成了荒漠林和荒漠草原退化加剧，生态环境恶化。基于大沙鼠分布数据、气候、土壤和地形因子数据，采用MaxEnt模型预测大沙鼠在当前气候和温室气体低、中、高3种浓度排放情景下2050年和2070年的潜在适生区，分析亚洲大陆未来气候条件下大沙鼠适生面积和分布格局的变化趋势，探讨影响大沙鼠分布的主要环境因子。结果表明：模型AUC（Area Under Curve）值达到0.9以上，预测的准确性达到"极好"。经刀切法分析（Jackknife）表明，影响大沙鼠在适生区分布最主要的环境变量为温度季节性变化的标准差、土壤基本饱和度、最干季度降水量、最暖季度降水量和土壤可交换钠盐。Rcp2.6、Rcp4.5和Rcp8.5三种气候场景下2050年高适生区面积较当前分别增长15.78%、15.10%和13.44%；Rcp2.6、Rcp4.5和Rcp8.5三种气候场景下2070年高适生区面积较当前增长8.32%、13.18%和18.18%。中国大沙鼠适生区范围内，新疆所分布的大沙鼠适生区分布范围变化较大，3种情景模式下大沙鼠的适生区位置向新疆北部扩张；甘肃适生区位置向西北部扩张；内蒙西北部和阿拉善地区大沙鼠的适生区位置向四周扩张。研究揭示了未来气候下大沙鼠高适生区范围和空间变化，并得到影响其分布的主要环境变量，对其防控具有重要意义。     

Morphological variation in salamanders and their potential response to climate change

Despite the recognition that some species might quickly adapt to new conditions under climate change, demonstrating and predicting such a fundamental response is challenging. Morphological variations in response to climate may be caused by evolutionary changes or phenotypic plasticity, or both, but teasing apart these processes is difficult. Here, we built on the number of thoracic vertebrae (NTV) in ectothermic vertebrates, a known genetically based feature, to establish a link with body size and evaluate how climate change might affect the future morphological response of this group of species. First, we show that in old‐world salamanders, NTV variation is strongly related to changes in body size. Secondly, using 22 salamander species as a case study, we found support for relationships between the spatial variation in selected bioclimatic variables and NTV for most of species. For 44% of species, precipitation and aridity were the predominant drivers of geographical variation of the NTV. Temperature features were dominant for 31% of species, while for 19% temperature and precipitation played a comparable role. This two‐step analysis demonstrates that ectothermic vertebrates may evolve in response to climate change by modifying the number of thoracic vertebrae. These findings allow to develop scenarios for potential morphological evolution under future climate change and to identify areas and species in which the most marked evolutionary responses are expected. Resistance to climate change estimated from species distribution models was positively related to present‐day species morphological response, suggesting that the ability of morphological evolution may play a role for species’ persistence under climate change. The possibility that present‐day capacity for local adaptation might help the resistance response to climate change can be integrated into analyses of the impact of global changes and should also be considered when planning management actions favouring species persistence.     

伊春地区红松和红皮云杉径向生长对气候变化的响应

树木生长-气候关系对准确评估气候变化对森林生态系统影响、预测森林生产力与植被动态及揭示树木对气候变化的响适应策略至关重要。在全球变暖背景下,升温可能会对树木的生长产生影响,从而改变区域森林生态系统的生产力或碳储量。本研究利用生长-气候响应函数、滑动相关分析等树木年轮学方法,探讨伊春地区阔叶红松林内红松和红皮云杉径向生长的主要限制因子及两者径向生长对快速升温(1980年后)响应的异同。结果表明:1980年前红松径向生长有明显加速的趋势,红皮云杉上升趋势较弱;而1980年后红松径向生长趋势显著下降,红皮云杉则下降不明显。红皮云杉径向生长与上一年9月及当年6月平均气温显著负相关,而红松径向生长与上一年12月及当年1月、4月和6月最低气温显著正相关。1980年快速升温后,高温对两树种生长的抑制作用增强,尤其是红松。生长季末(9月)降水对红松和红皮云杉的限制作用由升温前的负相关转变为升温后的显著正相关。温度是限制红松和红皮云杉径向生长的主要气候因子,降水影响相对较弱;其中红松径向生长对气候变化的响应比红皮云杉更敏感。快速升温后,红松和红皮云杉生长-气候关系的变化可能与升温导致的暖干旱化有关。若气候变暖持续或加剧,二者径向生长的气候限制因子也将由温度转变为水分;红松和红皮云杉会出现生长衰退,尤其是红松。     

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...     

Climate change‐induced migration patterns and extinction risks of Theaceae species in China

Theaceae, an economically important angiosperm family, is widely distributed in tropical and subtropical forests in Asia. In China, Theaceae has particularly high abundances and endemism, comprising ~75% of the total genera and ~46% of the total species worldwide. Therefore, predicting the response of Theaceae species to climate change is vital. In this study, we collected distribution data for 200 wild Theaceae species in China, and predicted their distribution patterns under current and future climactic conditions by species distribution modeling (SDM). We revealed that Theaceae species richness is highest in southeastern China and on Hainan Island, reaching its highest value (137 species) in Fujian Province. According to the IUCN Red List criteria for assessing species threat levels under two dispersal assumptions (no dispersal and full dispersal), we evaluated the conservation status of all Theaceae species by calculating loss of suitable habitat under future climate scenarios. We predicted that nine additional species will become threatened due to climate change in the future; one species will be classified as critically endangered (CR), two as endangered (EN), and six as vulnerable (VU). Given their extinction risks associated with climate change, we recommended that these species be added to the Red List. Our investigation of migration patterns revealed regional differences in the number of emigrant, immigrant, and persistent species, indicating the need for targeted conservation strategies. Regions containing numerous emigrants are concentrated in Northern Taiwan and coastal regions of Zhejiang and Fujian provinces, while regions containing numerous immigrants include central Sichuan Province, the southeastern Tibet Autonomous Region, southwest Yunnan Province, northwest Sichuan Province, and the junction of Guangxi and Hunan provinces. Lastly, regions containing persistent species are widely distributed in southern China. Importantly, regions with high species turnover are located on the northern border of the entire Theaceae species distribution ranges owing to upwards migration; these regions are considered most sensitive to climate change and conservation planning should therefore be prioritized here. This study will contribute valuable information for reducing the negative impacts of climate change on Theaceae species, which will ultimately improve biodiversity conservation efficiency.     

Increased evapotranspiration demand in a Mediterranean climate might cause a decline in fungal yields under global warming

Wild fungi play a critical role in forest ecosystems, and its recollection is a relevant economic activity. Understanding fungal response to climate is necessary in order to predict future fungal production in Mediterranean forests under climate change scenarios. We used a 15‐year data set to model the relationship between climate and epigeous fungal abundance and productivity, for mycorrhizal and saprotrophic guilds in a Mediterranean pine forest. The obtained models were used to predict fungal productivity for the 2021–2080 period by means of regional climate change models. Simple models based on early spring temperature and summer–autumn rainfall could provide accurate estimates for fungal abundance and productivity. Models including rainfall and climatic water balance showed similar results and explanatory power for the analyzed 15‐year period. However, their predictions for the 2021–2080 period diverged. Rainfall‐based models predicted a maintenance of fungal yield, whereas water balance‐based models predicted a steady decrease of fungal productivity under a global warming scenario. Under Mediterranean conditions fungi responded to weather conditions in two distinct periods: early spring and late summer–autumn, suggesting a bimodal pattern of growth. Saprotrophic and mycorrhizal fungi showed differences in the climatic control. Increased atmospheric evaporative demand due to global warming might lead to a drop in fungal yields during the 21st century.     

Amazon's vulnerability to climate change heightened by deforestation and man‐made dispersal barriers

Species migrations in response to climate change have already been observed in many taxonomic groups worldwide. However, it remains uncertain if species will be able to keep pace with future climate change. Keeping pace will be especially challenging for tropical lowland rainforests due to their high velocities of climate change combined with high rates of deforestation, which may eliminate potential climate analogs and/or increase the effective distances between analogs by blocking species movements. Here, we calculate the distances between current and future climate analogs under various climate change and deforestation scenarios. Under even the most sanguine of climate change models (IPSL_CM4, A1b emissions scenario), we find that the median distance between areas in the Amazon rainforest and their closest future (2050) climate analog as predicted based on just temperature changes alone is nearly 300 km. If we include precipitation, the median distance increases by over 50% to >475 km. Since deforestation is generally concentrated in the hottest and driest portions of the Amazon, we predict that the habitat loss will have little direct impact on distances between climate analogs. If, however, deforested areas also act as a barrier to species movements, nearly 30% or 55% of the Amazon will effectively have no climate analogs anywhere in tropical South America under projections of reduced or Business‐As‐Usual deforestation, respectively. These ‘disappearing climates’ will be concentrated primarily in the southeastern Amazon. Consequently, we predict that several Amazonian ecoregions will have no areas with future climate analogs, greatly increasing the vulnerability of any populations or species specialized on these conditions. These results highlight the importance of including multiple climatic factors and human land‐use in predicting the effects of climate change, as well as the daunting challenges that Amazonian diversity faces in the near future.