Global patterns in the vulnerability of ecosystems to vegetation shifts due to climate change

Aim Climate change threatens to shift vegetation, disrupting ecosystems and damaging human well‐being. Field observations in boreal, temperate and tropical ecosystems have detected biome changes in the 20th century, yet a lack of spatial data on vulnerability hinders organizations that manage natural resources from identifying priority areas for adaptation measures. We explore potential methods to identify areas vulnerable to vegetation shifts and potential refugia. Location Global vegetation biomes. Methods We examined nine combinations of three sets of potential indicators of the vulnerability of ecosystems to biome change: (1) observed changes of 20th‐century climate, (2) projected 21st‐century vegetation changes using the MC1 dynamic global vegetation model under three Intergovernmental Panel on Climate Change (IPCC) emissions scenarios, and (3) overlap of results from (1) and (2). Estimating probability density functions for climate observations and confidence levels for vegetation projections, we classified areas into vulnerability classes based on IPCC treatment of uncertainty. Results One‐tenth to one‐half of global land may be highly (confidence 0.80–0.95) to very highly (confidence ≥ 0.95) vulnerable. Temperate mixed forest, boreal conifer and tundra and alpine biomes show the highest vulnerability, often due to potential changes in wildfire. Tropical evergreen broadleaf forest and desert biomes show the lowest vulnerability. Main conclusions Spatial analyses of observed climate and projected vegetation indicate widespread vulnerability of ecosystems to biome change. A mismatch between vulnerability patterns and the geographic priorities of natural resource organizations suggests the need to adapt management plans. Approximately a billion people live in the areas classified as vulnerable.     

Simulated distribution of vegetation types in response to climate change on the Tibetan Plateau

Abstract. Questions: What is the relationship between alpine vegetation patterns and climate? And how do alpine vegetation patterns respond to climate changes? Location: Tibetan Plateau, southwestern China. The total area is 2500000 km² with an average altitude over 4000 m. Methods: The geographic distribution of vegetation types on the Tibetan Plateau was simulated based on climatology using a small set of plant functional types (PFTs) embedded in the biogeochemistry‐biography model BIOME4. The paleoclimate for the early Holocene was used to explore the possibility of simulating past vegetation patterns. Changes in vegetation patterns were simulated assuming continuous exponential increase in atmospheric CO concentration, based on a transient ocean‐atmosphere simulation including sulfate aerosol effects during the 21st century. Results: Forest, shrub steppe, alpine steppe and alpine meadow extended while no desert vegetation developed under the warmer and humid climate of the early Holocene. In the future climate scenario, the simulated tree line is farther north in most sectors than at present. There are also major northward shifts of alpine meadows and a reduction in shrub‐dominated montane steppe. The boundary between montane desert and alpine desert will be farther to the south than today. The area of alpine desert would decrease, that of montane desert would increase. Conclusions: The outline of changes in vegetation distribution was captured with the simulation. Increased CO2 concentration would potentially lead to big changes in alpine ecosystems.     

山地物种海拔分布对气候变化响应的研究进展

过去1个世纪以来, 全球气候变化显著并已成为全球生物多样性面临的重要威胁之一。如何利用有限的资源最有效地保护生物多样性已成为亟待解决的最重要科学问题之一。山地因其具有较高的生境异质性、气候多样性和较低的人类活动干扰, 已成为最重要的生物多样性避难所, 也具有较高的生态服务价值, 在生物多样性保护中扮演着重要角色。但山地更容易受到气候变化的影响, 山地地区较为剧烈的气候变化将对山地生态系统的稳定性及其多样性造成严重威胁。理解山地物种海拔分布对气候变化的响应和潜在机理, 以及气候变化带来的物种海拔分布变化的负面效应, 将为全球气候变化背景下的山地生物多样性保护提供参考依据。本文综述了全球山地地区的气候变化情况, 总结了物种海拔迁移的研究进展, 重点讨论了山地物种分布最适海拔、海拔上下限和海拔分布范围变化的研究进展及不足, 比较了不同地区和不同类群物种海拔迁移的差异性, 以及物种对气候变化响应的滞后性。从生物及非生物因素等多个角度概括了物种海拔迁移响应气候变化的潜在机理, 评估并总结了气候变化引起的物种海拔分布所产生的负面效应, 主要对物种向上迁移对高海拔地区物种多样性的影响、物种迁移带来的分布区改变导致的物种灭绝风险以及物种海拔分布变化导致的种间相互作用改变等方面进行全面探讨。最后, 展望了未来在此领域研究中应注意的问题, 提出了在未来气候变化下山地生物多样性保护需要采取的措施, 强调应重点关注对气候变化较为敏感的类群及生物多样性区域, 加强中国山地物种对气候变化响应的监测网络建设和研究力度, 重点加强监测气候变化对动植物互作关系的影响。     

Ecological niche modeling of coastal dune plants and future potential distribution in response to climate change and sea level rise

Climate change (CC) and sea level rise (SLR) are phenomena that could have severe impacts on the distribution of coastal dune vegetation. To explore this we modeled the climatic niches of six coastal dunes plant species that grow along the shoreline of the Gulf of Mexico and the Yucatan Peninsula, and projected climatic niches to future potential distributions based on two CC scenarios and SLR projections. Our analyses suggest that distribution of coastal plants will be severely limited, and more so in the case of local endemics (Chamaecrista chamaecristoides, Palafoxia lindenii, Cakile edentula). The possibilities of inland migration to the potential ‘new shoreline’ will be limited by human infrastructure and ecosystem alteration that will lead to a ‘coastal squeeze’ of the coastal habitats. Finally, we identified areas as future potential refuges for the six species in central Gulf of Mexico, and northern Yucatán Peninsula especially under CC and SLR scenarios.     

Phenotypic distribution models corroborate species distribution models: A shift in the role and prevalence of a dominant prairie grass in response to climate change

Phenotypic distribution within species can vary widely across environmental gradients but forecasts of species’ responses to environmental change often assume species respond homogenously across their ranges. We compared predictions from species and phenotype distribution models under future climate scenarios for Andropogon gerardii, a widely distributed, dominant grass found throughout the central United States. Phenotype data on aboveground biomass, height, leaf width, and chlorophyll content were obtained from 33 populations spanning a ~1000 km gradient that encompassed the majority of the species’ environmental range. Species and phenotype distribution models were trained using current climate conditions and projected to future climate scenarios. We used permutation procedures to infer the most important variable for each model. The species‐level response to climate was most sensitive to maximum temperature of the hottest month, but phenotypic variables were most sensitive to mean annual precipitation. The phenotype distribution models predict that A. gerardii could be largely functionally eliminated from where this species currently dominates, with biomass and height declining by up to ~60% and leaf width by ~20%. By the 2070s, the core area of highest suitability for A. gerardii is projected to shift up to ~700 km northeastward. Further, short‐statured phenotypes found in the present‐day short grass prairies on the western periphery of the species’ range will become favored in the current core ~800 km eastward of their current location. Combined, species and phenotype models predict this currently dominant prairie grass will decline in prevalence and stature. Thus, sourcing plant material for grassland restoration and forage should consider changes in the phenotype that will be favored under future climate conditions. Phenotype distribution models account for the role of intraspecific variation in determining responses to anticipated climate change and thereby complement predictions from species distributions models in guiding climate adaptation strategies.     

Evaluating the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO₂, and few studies have considered how and to what extent climate change and CO₂ influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP‐DGVM coupled with CLM3 and CLM4‐CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO₂ concentration. In the temperature sensitivity tests, warming reduced the global area‐averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (ΔF_tree; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether ΔF_tree was positive or negative, while the tree fractional coverage (F_tree; %) played a decisive role in the amplitude of ΔF_tree around the globe, and the dependence was more remarkable in IAP‐DGVM. In cases with precipitation change, F_tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% < F_tree < 60%) for IAP‐DGVM and in semiarid and arid regions for CLM4‐CNDV. Moreover, ΔF_tree had a stronger dependence on F_tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO₂ concentration.     

气候变化对东北主要地带性植被类型分布的影响

准确地划分地带性主要植被类型分布的适宜区域,可为区域植被恢复与重建、生物多样性保护等工作提供有益的理论参考。在检验1961—2013年东北地区气候变化突变点的基础上,基于东北地区主要植被类型热量指标,研究气候变化对该区域主要植被类型适宜分布区域的影响,并利用2000年和2013年土地类型覆盖数据(MCD12Q1),对推算的适宜分布区域进行验证,结果表明:大兴安岭气温突变点为1982年,其它地区为1988年,东北地区各生态地理区年降水量没有明显的突变点。气温突变点后适宜在东北地区生长的主要植被种类没有变化,但各植被类型的分布区域均有所改变,其中高山冻原、亚高山矮曲林、寒温带针叶林和温带针阔叶混交林适宜分布区域面积减小,暖温带落叶阔叶林和温带草原面积增大。气温突变点前后各植被类型适宜分布区的地理中心均发生了不同程度的移动,其中移动距离最大的是南部地区的亚高山矮曲林,向东北方向移动了135.44km。与主要植被类型实际分布相对比,证明气候变化对研究区植被类型分布可能已经产生了影响。     

Projecting marine species range shifts from only temperature can mask climate vulnerability

Climate change is causing range shifts in many marine species, with implications for biodiversity and fisheries. Previous research has mainly focused on how species' ranges will respond to changing ocean temperatures, without accounting for other environmental covariates that could affect future distribution patterns. Here, we integrate habitat suitability modeling approaches, a high‐resolution global climate model projection, and detailed fishery‐independent and ‐dependent faunal datasets from one of the most extensively monitored marine ecosystems—the U.S. Northeast Shelf. We project the responses of 125 species in this region to climate‐driven changes in multiple oceanographic factors (e.g., ocean temperature, salinity, sea surface height) and seabed characteristics (i.e., rugosity and depth). Comparing model outputs based on ocean temperature and seabed characteristics to those that also incorporated salinity and sea surface height (proxies for primary productivity and ocean circulation features), we explored how an emphasis on ocean temperature in projecting species' range shifts can impact assessments of species' climate vulnerability. We found that multifactor habitat suitability models performed better in explaining and predicting species historical distribution patterns than temperature‐based models. We also found that multifactor models provided more concerning assessments of species' future distribution patterns than temperature‐based models, projecting that species' ranges will largely shift northward and become more contracted and fragmented over time. Our results suggest that using ocean temperature as a primary determinant of range shifts can significantly alter projections, masking species' climate vulnerability, and potentially forestalling proactive management.     

Sensitivity of Siberian larch forests to climate change

The Northern Hemisphere's boreal forests, particularly the Siberian boreal forest, may have a strong effect on Earth's climate through changes in dominant vegetation and associated regional surface albedo. We show that warmer climate will likely convert Siberia's deciduous larch (Larix spp.) to evergreen conifer forests, and thus decrease regional surface albedo. The dynamic vegetation model, FAREAST, simulates Russian boreal forest composition and was used to explore the feedback between climate change and forest composition at continental, regional, and local scales. FAREAST was used to simulate the impact of changes in temperature and precipitation on total and genus‐level biomass at sites across Siberia and the Russian Far East (RFE), and for six high‐ and low‐diversity regions. Model runs with and without European Larch (Larix decidua) included in the available species pool were compared to assess the potential for this species, which is adapted to warmer climate conditions, to mitigate the effects of climate change, especially the shift to evergreen dominance. At the continental scale, when temperature is increased, larch‐dominated sites become vulnerable to early replacement by evergreen conifers. At the regional and local scales, the diverse Amur region of the RFE does not show a strong response to climate change, but the low‐diversity regions in central and southern Siberia have an abrupt vegetation shift from larch‐dominated forest to evergreen‐conifer forest in response to increased temperatures. The introduction of L. decidua prevents the collapse of larch in these low‐diversity areas and thus mitigates the response to warming. Using contemporary MODIS albedo measurements, we determined that a conversion from larch to evergreen stands in low‐diversity regions of southern Siberia would generate a local positive radiative forcing of 5.1±2.6 W m^?2. This radiative heating would reinforce the warming projected to occur in the area under climate change.     

气候变化下西南地区植物功能型地理分布响应

以中国西南地区(云南、贵州、四川和重庆)为研究区,基于中国植被图划分植物功能型,筛选影响各植物功能型分布的主导环境因子,进而通过最大熵模型结合未来气候情景(2050年)预测西南地区植物功能型地理分布。结果表明:(1)根据植物冠层特征(针叶/阔叶、常绿/落叶)及对水分和温度的需求,结合研究区实际植被数据,筛选得到15类植物功能型,包含6类乔木、6类灌木和3类草本功能型;(2)影响西南地区热带乔木分布的主导因子为最冷月最低温度和年降水量(贡献率达90.3%),亚热带植物功能型分布主要受到温度变化影响(贡献率达41.7%),温带植物功能型则受降水因子的影响最大(贡献率约40.1%),高寒草甸草和高寒常绿阔叶灌木主要受温度和海拔因子影响,高寒落叶阔叶灌木受降水因子影响大;(3)随CO₂排放量增加,未来西南各植物功能型分布呈现不同变化,其中,热带常绿阔叶乔木适宜区逐渐扩大;亚热带落叶木本类植物功能型的高适宜区面积2050年(RCP8.5)增至10.3%,呈东移趋势;亚热带常绿木本和草本类植物功能型适宜区广(占研究区总面积86.5%),未来气候下分布呈不规则波动;温带植物功能...     

气候变化对阔叶红松林潜在地理分布区的影响

物种地理分布主要取决于它对气候、地形等环境因子的适应性。基于22个环境因子和阔叶红松林的4类主要建群树种——红松、紫椴、水曲柳和蒙古栎的地理分布数据,采用最大熵模型模拟了阔叶红松林的潜在分布区域,并分析决定阔叶红松林地理分布的主要气候和地形因子,最后利用政府间气候变化专门委员会(IPCC)发布的3种排放场景(SRES-A2、SRES-A1B、SRES-B1)下2020、2050、2080年的气候数据预测阔叶红松林的未来潜在分布区。结果表明:各树种的受试者工作特征曲线下面积(AUC值)都大于0.8,说明模型有很好的预测能力;影响阔叶红松林分布的主导环境因子是年降雨量、季节性降雨量、海拔、年平均温度、最湿季度的平均温度。在基准气候条件下,阔叶红松林的高度适宜分布区主要分布在长白山和小兴安岭地区,占研究区总面积的11.69%,低度适宜区面积、不适宜区面积分别占研究区总面积的23%和65.31%。模型预测结果显示,未来在A2、A1B和B1气候情景下,阔叶红松林高度适宜区的南界与北界都向北移动,其面积有缩减的趋势,而低度适宜区的面积有增加的趋势。     

Modelling both dominance and species distribution provides a more complete picture of changes to mangrove ecosystems under climate change

Dominant species influence the composition and abundance of other species present in ecosystems. However, forecasts of distributional change under future climates have predominantly focused on changes in species distribution and ignored possible changes in spatial and temporal patterns of dominance. We develop forecasts of spatial changes for the distribution of species dominance, defined in terms of basal area, and for species occurrence, in response to sea level rise for three tree taxa within an extensive mangrove ecosystem in northern Australia. Three new metrics are provided, indicating the area expected to be suitable under future conditions (E_occupied), the instability of suitable area (E_instability) and the overlap between the current and future spatial distribution (E_overlap). The current dominance and occurrence were modelled in relation to a set of environmental variables using boosted regression tree (BRT) models, under two scenarios of seedling establishment: unrestricted and highly restricted. While forecasts of spatial change were qualitatively similar for species occurrence and dominance, the models of species dominance exhibited higher metrics of model fit and predictive performance, and the spatial pattern of future dominance was less similar to the current pattern than was the case for the distributions of species occurrence. This highlights the possibility of greater changes in the spatial patterning of mangrove tree species dominance under future sea level rise. Under the restricted seedling establishment scenario, the area occupied by or dominated by a species declined between 42.1% and 93.8%, while for unrestricted seedling establishment, the area suitable for dominance or occurrence of each species varied from a decline of 68.4% to an expansion of 99.5%. As changes in the spatial patterning of dominance are likely to cause a cascade of effects throughout the ecosystem, forecasting spatial changes in dominance provides new and complementary information in addition to that provided by forecasts of species occurrence.     

高山林线生态交错区木本植物幼苗分布特征、更新机制及其对气候变化的响应

木本植物幼苗是高山林线生态交错区的重要组成部分,其更新对气候变化背景下树线的移动至关重要.本研究通过对近几十年来全球范围内林线生态交错区的木本植物幼苗分布特征、更新机制及其对气候变化响应的研究总结得出:林线生态交错区木本植物幼苗的空间分布类型主要为渐变型和聚集型,且不同分布类型对树线动态的指示意义各异.在全球尺度上,其分布的海拔高限通常与生长季长度、均温和物种特性等有关,而在区域尺度上则多受降水影响.在幼苗更新初期,种源在很大程度上决定了种子的萌发及分布位置,之后微环境的促进作用为幼苗的定植提供庇护,提高其存活率,而在更新后期多种生物和非生物因素及其相互作用则非常关键.气候变暖促使林线生态交错区气温升高、降水充沛,有利于幼苗生长,使其向高海拔区域扩张而成为树线上移的先兆,但部分物种受遗传特性或适应策略影响,仅表现为密度增加,使树线保持相对稳定.未来应借助树轮、14C等精确定年技术,通过长期的野外定位观测和室内模拟,加强多时空尺度下林线幼苗的空间分布特征和更新机制研究,分析不同类型林线内木本植物幼苗的适应策略,预测气候变化背景下的树线动态,为山地生态系统恢复及保护提供科学依据.     

Predicting range shifts of Davidia involucrata Ball. under future climate change

Understanding and predicting how species will respond to climate change is crucial for biodiversity conservation. Here, we assessed future climate change impacts on the distribution of a rare and endangered plant species, Davidia involucrate in China, using the most recent global circulation models developed in the sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC6). We assessed the potential range shifts in this species by using an ensemble of species distribution models (SDMs). The ensemble SDMs exhibited high predictive ability and suggested that the temperature annual range, annual mean temperature, and precipitation of the driest month are the most influential predictors in shaping distribution patterns of this species. The projections of the ensemble SDMs also suggested that D. involucrate is very vulnerable to future climate change, with at least one‐third of its suitable range expected to be lost in all future climate change scenarios and will shift to the northward of high‐latitude regions. Similarly, at least one‐fifth of the overlap area of the current nature reserve networks and projected suitable habitat is also expected to be lost. These findings suggest that it is of great importance to ensure that adaptive conservation management strategies are in place to mitigate the impacts of climate change on D. involucrate.     

The pace of past climate change vs. potential bird distributions and land use in the United States

Climate change may drastically alter patterns of species distributions and richness, but predicting future species patterns in occurrence is challenging. Significant shifts in distributions have already been observed, and understanding these recent changes can improve our understanding of potential future changes. We assessed how past climate change affected potential breeding distributions for landbird species in the conterminous United States. We quantified the bioclimatic velocity of potential breeding distributions, that is, the pace and direction of change for each species’ suitable climate space over the past 60 years. We found that potential breeding distributions for landbirds have shifted substantially with an average velocity of 1.27 km yr^?1, about double the pace of prior distribution shift estimates across terrestrial systems globally (0.61 km yr^?1). The direction of shifts was not uniform. The majority of species’ distributions shifted west, northwest, and north. Multidirectional shifts suggest that changes in climate conditions beyond mean temperature were influencing distributional changes. Indeed, precipitation variables that were proxies for extreme conditions were important variables across all models. There were winners and losers in terms of the area of distributions; many species experienced contractions along west and east distribution edges, and expansions along northern distribution edges. Changes were also reflected in the potential species richness, with some regions potentially gaining species (Midwest, East) and other areas potentially losing species (Southwest). However, the degree to which changes in potential breeding distributions are manifested in actual species richness depends on landcover. Areas that have become increasingly suitable for breeding birds due to changing climate are often those attractive to humans for agriculture and development. This suggests that many areas might have supported more breeding bird species had the landscape not been altered. Our study illustrates that climate change is not only a future threat, but something birds are already experiencing.     

Modeling nonbreeding distributions of shorebirds and waterfowl in response to climate change

To identify areas on the landscape that may contribute to a robust network of conservation areas, we modeled the probabilities of occurrence of several en route migratory shorebirds and wintering waterfowl in the southern Great Plains of North America, including responses to changing climate. We predominantly used data from the eB ird citizen‐science project to model probabilities of occurrence relative to land‐use patterns, spatial distribution of wetlands, and climate. We projected models to potential future climate conditions using five representative general circulation models of the Coupled Model Intercomparison Project 5 (CMIP 5). We used Random Forests to model probabilities of occurrence and compared the time periods 1981–2010 (hindcast) and 2041–2070 (forecast) in “model space.” Projected changes in shorebird probabilities of occurrence varied with species‐specific general distribution pattern, migration distance, and spatial extent. Species using the western and northern portion of the study area exhibited the greatest likelihoods of decline, whereas species with more easterly occurrences, mostly long‐distance migrants, had the greatest projected increases in probability of occurrence. At an ecoregional extent, differences in probabilities of shorebird occurrence ranged from ?0.015 to 0.045 when averaged across climate models, with the largest increases occurring early in migration. Spatial shifts are predicted for several shorebird species. Probabilities of occurrence of wintering Mallards and Northern Pintail are predicted to increase by 0.046 and 0.061, respectively, with northward shifts projected for both species. When incorporated into partner land management decision tools, results at ecoregional extents can be used to identify wetland complexes with the greatest potential to support birds in the nonbreeding season under a wide range of future climate scenarios.