Population projections of an endangered cactus suggest little impact of climate change

Oecologia - Population projections coupled with downscaled climate projections are a powerful tool that allows predicting future population dynamics of vulnerable plants in the face of a changing...     

Predicted insect diversity declines under climate change in an already impoverished region

Being ectotherms, insects are predicted to suffer more severely from climate change than warm-blooded animals. We forecast possible changes in diversity and composition of butterflies, grasshoppers and dragonflies in Belgium under increasingly severe climate change scenarios for the year 2100. Two species distribution modelling techniques (Generalised Linear Models and Generalised Additive Models), were combined via a conservative version of the ensemble forecasting strategy to predict present-day and future species distributions, considering the species as potentially present only if both modelling techniques made such a prediction. All models applied were fair to good, according to the AUC (area under the curve of the receiver operating characteristic plot), sensitivity and specificity model performance measures based on model evaluation data. Butterfly and grasshopper diversity were predicted to decrease significantly in all scenarios and species-rich locations were predicted to move towards higher altitudes. Dragonfly diversity was predicted to decrease significantly in all scenarios, but dragonfly-rich locations were predicted to move upwards only in the less severe scenarios. The largest turnover rates were predicted to occur at higher altitudes for butterflies and grasshoppers, but at intermediate altitudes for dragonflies. Our results highlight the challenge of building conservation strategies under climate change, because the changes in the sites important for different groups will not overlap, increasing the area needed for protection. We advocate that possible conservation and policy measures to mitigate the potentially strong impacts of climate change on insect diversity in Belgium should be much more pro-active and flexible than is the case presently.     

Identifying conservation priority areas and predicting the climate change impact on the future habitats of endangered Nepenthes khasiana Hook.f. utilizing ecological niche modelling

Developing strategies for effective species conservation is necessary to counter the ever-fluctuating environmental conditions with increasing anthropogenic activities. Studies have proven Ecological Niche Modelling (ENM) as an effective tool for sustainable conservation. Nepenthes khasiana Hook.f. is an endangered pitcher plant facing a constant decline in population due to anthropogenic activities. This study aimed to locate the most suitable areas for re-establishing the species in natural habitats using Maximum Entropy (MaxEnt) modelling, and to forecast the effects of current and future climate conditions on its distribution throughout Northeast India. The potential suitable areas in future climate under three Representative Concentration Pathway (RCP) scenarios and in the current climate were predicted utilizing the 30 occurrence data, bioclimatic predictors, and variables from BCC-CSM1.1 model and WorldClim respectively. The results of the current study showed significant relationships among annual precipitation, precipitation in the driest month, seasonality of precipitation, annual range iso-thermality of temperature, mean diurnal range [Mean of monthly (max temp - min temp)], and the distribution of the analysed species. The optimum model performance was represented by the AUC value of 0.972 ± 0.007. The model predicted 10.70% of the NE Indian region as climatically suitable, which will expand under RCP4.5 and RCP6.0, reaching 15.35%, and 12.64%, respectively. However, this may degrade significantly under RCP8.5, reducing to 8.14%. Based on the analysis of modelling results it was found that the Nokrek belt and the Khasi hills as highly suitable regions for the reintroduction of the species. The study revalidated ENM as an effective means to identify new populations and predict the influence of climate change on the future habitat which can benefit the concurrent species management strategies.     

Projecting the future of an alpine ungulate under climate change scenarios

Climate change represents a primary threat to species persistence and biodiversity at a global scale. Cold adapted alpine species are especially sensitive to climate change and can offer key “early warning signs” about deleterious effects of predicted change. Among mountain ungulates, survival, a key determinant of demographic performance, may be influenced by future climate in complex, and possibly opposing ways. Demographic data collected from 447 mountain goats in 10 coastal Alaska, USA, populations over a 37‐year time span indicated that survival is highest during low snowfall winters and cool summers. However, general circulation models (GCMs) predict future increase in summer temperature and decline in winter snowfall. To disentangle how these opposing climate‐driven effects influence mountain goat populations, we developed an age‐structured population model to project mountain goat population trajectories for 10 different GCM/emissions scenarios relevant for coastal Alaska. Projected increases in summer temperature had stronger negative effects on population trajectories than the positive demographic effects of reduced winter snowfall. In 5 of the 10 GCM/representative concentration pathway (RCP) scenarios, the net effect of projected climate change was extinction over a 70‐year time window (2015–2085); smaller initial populations were more likely to go extinct faster than larger populations. Using a resource selection modeling approach, we determined that distributional shifts to higher elevation (i.e., “thermoneutral”) summer range was unlikely to be a viable behavioral adaptation strategy; due to the conical shape of mountains, summer range was expected to decline by 17%–86% for 7 of the 10 GCM/RCP scenarios. Projected declines of mountain goat populations are driven by climate‐linked bottom‐up mechanisms and may have wide ranging implications for alpine ecosystems. These analyses elucidate how projected climate change can negatively alter population dynamics of a sentinel alpine species and provide insight into how demographic modeling can be used to assess risk to species persistence.     

Predicted impact of climate change on European bats in relation to their biogeographic patterns

There has been considerable recent interest concerning the impact of climate change on a wide range of taxa. However, little is known about how the biogeographic affinities of taxa may affect their responses to these impacts. Our main aim was to study how predicted climate change will affect the distribution of 28 European bat species grouped by their biogeographic patterns as determined by a spatial Principal Component Analysis. Using presence‐only modelling techniques and climatic data (minimum temperature, average temperature, precipitation, humidity and daily temperature range) for four different climate change scenarios (IPCC scenarios ranging from the most extreme A1FI, A2, B2 to the least severe, B1), we predict the potential geographic distribution of bat species in Europe grouped according to their biogeographic patterns for the years 2020–2030, 2050–2060 and 2090–2100. Biogeographic patterns exert a great influence on a species' response to climate change. Bat species more associated with colder climates, hence northern latitudes, could be more severely affected with some extinctions predicted by the end of the century. The Mediterranean and Temperate groups seem to be more tolerant of temperature increases, however, their projections varied considerably under different climate change scenarios. Scenario A1FI was clearly the most detrimental for European bat diversity, with several extinctions and declines in occupied area predicted for several species. The B scenarios were less damaging and even predicted that some species could increase their geographical ranges. However, all models only took into account climatic envelopes whereas available habitat and species interactions will also probably play an important role in delimiting future distribution patterns. The models may therefore generate ‘best case’ predictions about future changes in the distribution of European bats.     

The future of Iranian wetlands under climate change

Temporal changes in the area of 10 significant wetlands in Iran were determined using the remote sensing image of TM and ETM+ band 5 for a period of 15 years (1998–2012). The relationship between the annual time series of the area and the difference of precipitation and potential evaporation (P-E) was obtained for the wetlands using three evaporation methods. The area of the wetlands was predicted for 2050 using the best-fitting model and seven global climate models under four representative concentration pathways (a total of 28 climate scenarios). The area of five wetlands had a significant positive correlation with the P-E (R² > 0.72). The area of one wetland (Ghoorigol) is predicted to increase and the area of four wetlands (Bakhtegan, Chaghakhor, Parishan and Gavkhooni) is predicted to decrease in 2050 in comparison to the maximum area of the wetlands from 1998 to 2012 under all the climate scenarios. In comparison to the mean area of the wetlands (1998–2012), one wetland (Ghoorigol) is predicted to be larger and two wetlands (Gavkhooni and Parishan) are predicted to be smaller under all the climate scenarios. Two wetlands (Bakhtegan and Chaghakhor) are predicted to be larger under most of the climate scenarios in 2050. The Uromia wetland, the largest wetland in Iran, is predicted to become completely dry by 2032 if anthropogenic impacts continue similar to what occurred from 1998 to 2012.     

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.     

Predicting the impact of climate change on Australia's most endangered snake, Hoplocephalus bungaroides

Aim  To predict how the bioclimatic envelope of the broad-headed snake (BHS) ( Hoplocephalus bungaroides ) may be redistributed under future climate warming scenarios.
Location  South-eastern New South Wales, Australia.
Methods  We used 159 independent locations for the species and 35 climatic variables to model the bioclimatic envelope for the BHS using two modelling approaches – B ioclim and M axent . Predictions were made under current climatic conditions and we also predicted the species distribution under low and high climate change scenarios for 2030 and 2070.
Results  Broad-headed snakes currently encompass their entire bioclimatic envelope. Both modelling approaches predict that suitable climate space for BHS will be lost to varying degrees under both climate warming scenarios, and under the worst case, only 14% of known snake populations may persist.
Main conclusions  Areas of higher elevation within the current range will be most important for persistence of this species because they will remain relatively moist and cool even under climate change and will match the current climate envelope. Conservation efforts should focus on areas where suitable climate space may persist under climate warming scenarios. Long-term monitoring programs should be established both in these areas and where populations are predicted to become extirpated, so that we can accurately determine changes in the distribution of this species throughout its range.     

Eastern Suburbs Banksia Scrub: Rescuing an endangered ecological community

On‐ground works prove an important mechanism for gaining knowledge about this near‐extinct ecological community, providing new insights into ways to manage and restore it.     

未来气候变化下栎树猝死病菌在中国的适生性分析

基于中国国家有害生物检疫信息平台的有关记录和文献以及WoldClim网站,获取栎树猝死病菌的地理分布数据及气候数据,并用SPSS软件和刀切法筛选主导环境变量。利用MaxEnt生态位模型和ArcGIS软件,对栎树猝死病菌现代和未来情景下在我国的潜在适生区进行预测,并计算和绘制栎树猝死病菌高风险区质心转移轨迹。通过不同年份和不同气候情况下的受试者工作特征曲线(ROC)的训练集和测试集受试者工作特征曲线下面积(AUC)值均大于0.91,说明MaxEnt模型准确并适用于预测栎树猝死病菌在我国的潜在分布,同时结合其主要寄主植物的地理分布进一步增强预测模型的可信度。预测结果表明,最冷季度降水量、最冷季度平均温度、最干季度平均温度和年均降水量是影响栎树猝死病菌分布的主要环境变量。而2030s(2021—2040年)、2050s(2041—2060年)和2070s(2061—2080年)在3种气候情景下(SSP1-2.6、SSP2-4.5、SSP5-8.5),栎树猝死病菌的潜在适生区相较于现代情景下都有所增加。此外,高风险区面积在3个年代3种情景下的面积增长率均高于45%。高风险区质心变化的预测结果表...     

Predicted responses of arctic and alpine ecosystems to altered seasonality under climate change

Global climate change is already having significant impacts on arctic and alpine ecosystems, and ongoing increases in temperature and altered precipitation patterns will affect the strong seasonal patterns that characterize these temperature‐limited systems. The length of the potential growing season in these tundra environments is increasing due to warmer temperatures and earlier spring snow melt. Here, we compare current and projected climate and ecological data from 20 Northern Hemisphere sites to identify how seasonal changes in the physical environment due to climate change will alter the seasonality of arctic and alpine ecosystems. We find that although arctic and alpine ecosystems appear similar under historical climate conditions, climate change will lead to divergent responses, particularly in the spring and fall shoulder seasons. As seasonality changes in the Arctic, plants will advance the timing of spring phenological events, which could increase plant nutrient uptake, production, and ecosystem carbon (C) gain. In alpine regions, photoperiod will constrain spring plant phenology, limiting the extent to which the growing season can lengthen, especially if decreased water availability from earlier snow melt and warmer summer temperatures lead to earlier senescence. The result could be a shorter growing season with decreased production and increased nutrient loss. These contrasting alpine and arctic ecosystem responses will have cascading effects on ecosystems, affecting community structure, biotic interactions, and biogeochemistry.     

Designing ecological climate change impact assessments to reflect key climatic drivers

Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.     

Protecting rare and endangered species under climate change on the Qinghai Plateau,China

Climate change‐induced species range shift may pose severe challenges to species conservation. The Qinghai‐Tibet Plateau is the highest and biggest plateau, and also one of the most sensitive areas to global warming in the world, which provides important shelters for a unique assemblage of species. Here, ecological niche‐based model was employed to project the potential distributions of 59 key rare and endangered species under three climate change scenarios (RCP2.6, RCP4.5 and RCP8.5) in Qinghai Province. I assessed the potential impacts of climate change on these key species (habitats, species richness and turnover) and effectiveness of nature reserves (NRs) in protecting these species. The results revealed that that climate change would shrink the geographic ranges of about a third studied species and expand the habitats for two thirds of these species, which would thus alter the conservation value of some local areas and conservation effectiveness of some NRs in Qinghai Province. Some regions require special attention as they are expected to experience significant changes in species turnover, species richness or newly colonized species in the future, including Haidong, Haibei and Haixi junctions, the southwestern Yushu, Qinghai Nuomuhong Provincial NR, Qinghai Qaidam and Haloxylon Forest NR. The Haidong and the eastern part of Haibei, are projected to have high species richness and conservation value in both current and future, but they are currently not protected, and thus require extra protection in the future. The results could provide the first basis on the high latitude region to formulate biodiversity conservation strategies on climate change adaptation.     

The impacts of climate change on the wintering distribution of an endangered migratory bird

There is now ample evidence of the effects of anthropogenic climate change on the distribution and abundance of species. The black-faced spoonbill (Platalea minor) is an endangered migratory species and endemic to East Asia. Using a maximum entropy approach, we predicted the potential wintering distribution for spoonbills and modeled the effects of future climate change. Elevation, human influence index and precipitation during the coldest quarter contributed most to model development. Five regions, including western Taiwan, scattered locations from eastern coastal to central mainland China, coastal areas surrounding the South China Sea, northeastern coastal areas of Vietnam and sites along the coast of Japan, were found to have a high probability of presence and showed good agreement with historical records. Assuming no limits to the spread of this species, the wintering range is predicted to increase somewhat under a changing climate. However, three currently highly suitable regions (northeastern Vietnam, Taiwan and coastal areas surrounding the South China Sea) may face strong reductions in range by 2080. We also found that the center of the predicted range of spoonbills will undergo a latitudinal shift northwards by as much as 240, 450, and 600 km by 2020, 2050 and 2080, respectively. Our findings suggest that species distribution modeling can inform the current and future management of the black-faced spoonbill throughout Asia. It is clear that a strong international strategy is needed to conserve spoonbill populations under a changing climate.     

Individualistic vs community modelling of species distributions under climate change

Studies investigating the consequences of future climate changes on species distributions usually start with the assumption that species respond to climate changes in an individualistic fashion. This assumption has led researchers to use bioclimate envelope models that use present climate-range relationships to characterize species' limits of tolerance to climate, and then apply climate-change scenarios to enable projections of altered species distributions. However, there are techniques that combine climate variables together with information on the composition of assemblages to enable projections that are expected to mimic community dynamics. Here, we compare, for the first time, the performance of GLM (generalized linear model) and CQO (canonical quadratic ordination; a type of community-based GLM) for projecting distributions of species under climate change scenarios. We found that projections from these two methods varied both in terms of accuracy (GLM providing generally more accurate projections than CQO) and in the broad diversity patterns yielded (higher species richness values projected with CQO). Model outputs were also affected by species-specific traits, such as species range size and species geographical positions, supporting the view that methods are sensitive to different degrees of equilibrium of species distributions with climate. This study reveals differences in projections between individual- and community-based approaches that require further scrutiny, but it does not find support for unsupervised use community-based models for investigating climate change impacts on species distributions. Reasons for this lack of support are discussed.     

气候变化下生物交互作用对树线生态过程的影响

树线交错带是具有强烈生物交互作用的高寒生态过渡带,生物互作与树线生态过程密切相关。本研究系统综述了气候变化下植物间、动植物间和微生物与植物间互作因子对树线生态过程的影响。植物间互利或竞争作用的强度调控变暖背景下树线生态过程的变化,目前尚缺少树轮生态学证据,且亟待检验高阶互作的适用性;动物采食活动、微生物与植物间互作可通过影响土壤状况、改变树木生长和更新等生态过程动态,增强或削弱树线与气候间耦合关系。迄今为止,地下与地上过程联系如何影响气候变暖下的树线动态尚不明晰,而营养级间互作可能调制树线生态过程对气候响应。青藏高原等高寒区具有开展此类研究的优势与潜力。     

An ecological 'footprint' of climate change

Recently, there has been increasing evidence of species' range shifts due to changes in climate. Whereas most of these shifts relate ground truth biogeographic data to a general warming trend in regional or global climate data, we here present a reanalysis of both biogeographic and bioclimatic data of equal spatio-temporal resolution, covering a time span of more than 50 years. Our results reveal a coherent and synchronous shift in both species' distribution and climate. They show not only a shift in the northern margin of a species, which is in concert with gradually increasing winter temperatures in the area, they also confirm the simulated species' distribution changes expected from a bioclimatic model under the recent, relatively moderate climate change.     

未来气候变化下两种红景天植物的脆弱性

气候变化对全球的物种多样性有深远影响, 尤其是对高山物种多样性。研究未来气候变化下物种的灭绝风险对生物多样性保护具有重要的意义。本文针对青藏高原的2种重要药用植物大花红景天(Rhodiola crenulata)和菊叶红景天(R. chrysanthemifolia), 利用气候生态位因子分析法研究了它们对气候变化的敏感性、暴露性和脆弱性, 讨论了2种“共享社会经济途径” (SSP2-45和SSP5-85)情景下的未来气候对这2个物种脆弱性的影响。同时计算了2种红景天的气候生态位的边缘性和特化性, 通过主成分分析法对其气候生态位进行了二维可视化, 并分析了它们的气候变化脆弱性与气候生态位之间的关系。结果表明, 未来气候变化情景下2种红景天在其分布区都显示出西部脆弱性高而东部脆弱性低的特征, 而脆弱性都表现为较低的横断山脉地区将成为其未来气候避难所。2种红景天在SSP5-85气候情景下的脆弱性高于SSP2-45, 资源和能源密集型社会经济途径(即SSP5-85)将会增大物种的灭绝风险。此外, 被《中国物种红色名录》评估为无危的菊叶红景天的气候变化脆弱性反而大于被评估为濒危的大花红景天。生态位因子分析结果表明大花红景天的生态位边缘性和特化性都低于菊叶红景天, 研究推断同地区不同物种的气候变化脆弱性主要由物种的气候生态位决定。     

Global diversity patterns of larger benthic foraminifera under future climate change

Global warming threatens the viability of tropical coral reefs and associated marine calcifiers, including symbiont-bearing larger benthic foraminifera (LBF). The impacts of current climate change on LBF are debated because they were particularly diverse and abundant during past warm periods. Studies on the responses of selected LBF species to changing environmental conditions reveal varying results. Based on a comprehensive review of the scientific literature on LBF species occurrences, we applied species distribution modeling using Maxent to estimate present-day and future species richness patterns on a global scale for the time periods 2040–2050 and 2090–2100. For our future projections, we focus on Representative Concentration Pathway 6.0 from the Intergovernmental Panel on Climate Change, which projects mean surface temperature changes of +2.2°C by the year 2100. Our results suggest that species richness in the Central Indo-Pacific is two to three times higher than in the Bahamian ecoregion, which we have identified as the present-day center of LBF diversity in the Atlantic. Our future predictions project a dramatic temperature-driven decline in low-latitude species richness and an increasing widening bimodal latitudinal pattern of species diversity. While the central Indo-Pacific, now the stronghold of LBF diversity, is expected to be most pushed outside of the currently realized niches of most species, refugia may be largely preserved in the Atlantic. LBF species will face large-scale non-analogous climatic conditions compared to currently realized climate space in the near future, as reflected in the extensive areas of extrapolation, particularly in the Indo-Pacific. Our study supports hypotheses that species richness and biogeographic patterns of LBF will fundamentally change under future climate conditions, possibly initiating a faunal turnover by the late 21st century.