The future of terrestrial mammals in the Mediterranean basin under climate change

The Mediterranean basin is considered a hotspot of biological diversity with a long history of modification of natural ecosystems by human activities, and is one of the regions that will face extensive changes in climate. For 181 terrestrial mammals (68% of all Mediterranean mammals), we used an ensemble forecasting approach to model the future (approx. 2100) potential distribution under climate change considering five climate change model outputs for two climate scenarios. Overall, a substantial number of Mediterranean mammals will be severely threatened by future climate change, particularly endemic species. Moreover, we found important changes in potential species richness owing to climate change, with some areas (e.g. montane region in central Italy) gaining species, while most of the region will be losing species (mainly Spain and North Africa). Existing protected areas (PAs) will probably be strongly influenced by climate change, with most PAs in Africa, the Middle East and Spain losing a substantial number of species, and those PAs gaining species (e.g. central Italy and southern France) will experience a substantial shift in species composition.     

气候变化对马尾松潜在分布影响预估的多模型比较

物种分布模型被广泛应用于评估气候变化对物种分布的影响。随着计算机和统计学的发展, 模拟物种分布的模型层出不穷, 但对这些模型的相对表现知之甚少, 因此需要对其进行对比分析, 以便更可靠地评估气候变化的影响。该文采用3个比较新颖的组合集成学习(ensemble learning)模型(随机森林(random forest, RF)、广义助推法和NeuralEnsembles)、3个常规模型(广义线性模型、广义加法模型和分类回归树)、3个大气环流模型(global circulation model, GCM) (MIROC32_medres, JP; CCCMA_CGCM3, CA; BCCR-BCM2.0, NW)和一个气体排放情景(SRES_A2), 模拟分析了马尾松(Pinus massoniana)历史基准气候(1961-1990)和未来3个不同时期(2010-2039, 2020s; 2040-2069, 2050s; 2070-2099, 2080s)的潜在分布。基于环境阈值方法选择物种不发生区, 依据ClimateChina软件进行当前和未来气候数据的降尺度处理, 采用接收机工作特征曲线(receiver operator characteristic, ROC)下的面积(area under the curve, AUC)、Kappa值和真实技巧统计法(true skill statistic, TSS)以及马尾松种子区划范围来评价模型的预测精度。结果表明: 6个物种分布模型都具有较高的预测精度, 但组合集成学习模型的预测精度稍高于其他常规模型, 其中RF的预测精度最高。3个GCM和6个模型模拟条件下, 马尾松对气候变化的响应格局既有一致性也有异同性。一致性表现在: 随着时间的推移, 马尾松分布区将逐渐向北迁移, 未来潜在分布区的面积将逐渐增加; 异同性表现在: 在不同模型和不同气候情景下, 马尾松潜在分布区的迁移距离和面积变化幅度不同, 其中NW模式下预测的变化幅度小于CA和JP模式; RF模型预测的分布区迁移距离和面积变化幅度最大。随着时间的推移, 未来马尾松的18个潜在分布空间预测图(6个模型 × 3 GCM)之间的差异也逐渐增大, 其中空间不一致性地区主要集中发生在马尾松潜在分布区的北部和西部边缘地带。模型本身不同的构建原理以及GCM之间的差异是导致预测结果存在差异的主要原因。     

An approach to consider behavioral plasticity as a source of uncertainty when forecasting species' response to climate change

The rapid ecological shifts that are occurring due to climate change present major challenges for managers and policymakers and, therefore, are one of the main concerns for environmental modelers and evolutionary biologists. Species distribution models (SDM) are appropriate tools for assessing the relationship between species distribution and environmental conditions, so being customarily used to forecast the biogeographical response of species to climate change. A serious limitation of species distribution models when forecasting the effects of climate change is that they normally assume that species behavior and climatic tolerances will remain constant through time. In this study, we propose a new methodology, based on fuzzy logic, useful for incorporating the potential capacity of species to adapt to new conditions into species distribution models. Our results demonstrate that it is possible to include different behavioral responses of species when predicting the effects of climate change on species distribution. Favorability models offered in this study show two extremes: one considering that the species will not modify its present behavior, and another assuming that the species will take full advantage of the possibilities offered by an increase in environmental favorability. This methodology may mean a more realistic approach to the assessment of the consequences of global change on species' distribution and conservation. Overlooking the potential of species' phenotypical plasticity may under‐ or overestimate the predicted response of species to changes in environmental drivers and its effects on species distribution. Using this approach, we could reinforce the science behind conservation planning in the current situation of rapid climate change.     

气候变化对丹顶鹤秋季迁徙路线潜在生境适宜性的影响

目前全球变暖趋势的加剧对丹顶鹤等大型濒危水禽的栖息地造成了严重的威胁。由于监测方法和技术手段的限制,丹顶鹤在迁徙路线上潜在生境的分布范围尚不清楚,气候变化对丹顶鹤迁徙路线生境适宜性的影响机理有待进一步研究。基于138个丹顶鹤样本分布信息和19种环境变量数据,利用 BIOMOD2 软件包构建了丹顶鹤潜在生境评价的组合模型,对丹顶鹤在亚洲东部秋季迁徙路线上的生境适宜性进行数值模拟,并预测SSP1.2-6气候背景下2021-2040年、2041-2060年、2061-2080年、2081-2100年四个不同阶段的丹顶鹤潜在生境范围的变化趋势。研究结果表明:与单模型的模拟结果相比,集成9种单模型的BIOMOD2组合模型预测精度更高。集成模型的重要性分析表明,气温日较差是丹顶鹤生境适宜性变化的最重要的影响因子。受气候变化的影响2021-2040年、2041-2060年、2061-2080年、2081-2100年丹顶鹤潜在生境的面积将分别减少到2.60×10⁵km²、2.58×10⁵km²、2.75×10⁵km²、2.56×10⁵km²,迁徙路线上胶东半岛和环渤海地区适栖生境面积减少的最为显著。本研究对于迁徙路线上珍稀水禽潜在适宜生境的模拟及全球变化背景下珍稀水禽栖息地的保育和修复具有重要意义。     

Marine species in ambient low‐oxygen regions subject to double jeopardy impacts of climate change

We have learned much about the impacts of warming on the productivity and distribution of marine organisms, but less about the impact of warming combined with other environmental stressors, including oxygen depletion. Also, the combined impact of multiple environmental stressors requires evaluation at the scales most relevant to resource managers. We use the Gulf of St. Lawrence, Canada, characterized by a large permanently hypoxic zone, as a case study. Species distribution models were used to predict the impact of multiple scenarios of warming and oxygen depletion on the local density of three commercially and ecologically important species. Substantial changes are projected within 20–40 years. A eurythermal depleted species already limited to shallow, oxygen‐rich refuge habitat (Atlantic cod) may be relatively uninfluenced by oxygen depletion but increase in density within refuge areas with warming. A more stenothermal, deep‐dwelling species (Greenland halibut) is projected to lose ~55% of its high‐density areas under the combined impacts of warming and oxygen depletion. Another deep‐dwelling, more eurythermal species (Northern shrimp) would lose ~4% of its high‐density areas due to oxygen depletion alone, but these impacts may be buffered by warming, which may increase density by 8% in less hypoxic areas, but decrease density by ~20% in the warmest parts of the region. Due to local climate variability and extreme events, and that our models cannot project changes in species sensitivity to hypoxia with warming, our results should be considered conservative. We present an approach to effectively evaluate the individual and cumulative impacts of multiple environmental stressors on a species‐by‐species basis at the scales most relevant to managers. Our study may provide a basis for work in other low‐oxygen regions and should contribute to a growing literature base in climate science, which will continue to be of support for resource managers as climate change accelerates.     

Mutualism influences species distribution predictions for a bromeliad‐breeding anuran under climate change

Ecological niche models, or species distribution models, have been widely used to identify potentially suitable areas for species in future climate change scenarios. However, there are inherent errors to these models due to their inability to evaluate species occurrence influenced by non‐climatic factors. With the intuit to improve the modelling predictions for a bromeliad‐breeding treefrog (Phyllodytes melanomystax, Hylidae), we investigate how the climatic suitability of bromeliads influences the distribution model for the treefrog in the context of baseline and 2050 climate change scenarios. We used point occurrence data on the frog and the bromeliad (Vriesea procera, Bromeliaceae) to generate their predicted distributions based on baseline and 2050 climates. Using a consensus of five algorithms, we compared the accuracy of the models and the geographic predictions for the frog generated from two modelling procedures: (i) a climate‐only model for P. melanomystax and V. procera; and (ii) a climate‐biotic model for P. melanomystax, in which the climatic suitability of the bromeliad was jointly considered with the climatic variables. Both modelling approaches generated strong and similar predictive power for P. melanomystax, yet climate‐biotic modelling generated more concise predictions, particularly for the year 2050. Specifically, because the predicted area of the bromeliad overlaps with the predictions for the treefrog in the baseline climate, both modelling approaches produce reasonable similar predicted areas for the anuran. Alternatively, due to the predicted loss of northern climatically suitable areas for the bromeliad by 2050, only the climate‐biotic models provide evidence that northern populations of P. melanomystax will likely be negatively affected by 2050.     

A socio‐ecological model for predicting impacts of land‐use and climate change on regional plant diversity in the Austrian Alps

Climate and land‐use change jointly affect the future of biodiversity. Yet, biodiversity scenarios have so far concentrated on climatic effects because forecasts of land use are rarely available at appropriate spatial and thematic scales. Agent‐based models (ABMs) represent a potentially powerful but little explored tool for establishing thematically and spatially fine‐grained land‐use scenarios. Here, we use an ABM parameterized for 1,329 agents, mostly farmers, in a Central European model region, and simulate the changes to land‐use patterns resulting from their response to three scenarios of changing socio‐economic conditions and three scenarios of climate change until the mid of the century. Subsequently, we use species distribution models to, first, analyse relationships between the realized niches of 832 plant species and climatic gradients or land‐use types, respectively, and, second, to project consequent changes in potential regional ranges of these species as triggered by changes in both the altered land‐use patterns and the changing climate. We find that both drivers determine the realized niches of the studied plants, with land use having a stronger effect than any single climatic variable in the model. Nevertheless, the plants' future distributions appear much more responsive to climate than to land‐use changes because alternative future socio‐economic backgrounds have only modest impact on land‐use decisions in the model region. However, relative effects of climate and land‐use changes on biodiversity may differ drastically in other regions, especially where landscapes are still dominated by natural or semi‐natural habitat. We conclude that agent‐based modelling of land use is able to provide scenarios at scales relevant to individual species distribution and suggest that coupling ABMs with models of species' range change should be intensified to provide more realistic biodiversity forecasts.     

Evaluating drivers of vulnerability to climate change: a guide for insect conservation strategies

Ongoing global climate change presents serious challenges in conservation biology, forcing us to revisit previous tools and principles based on how species may respond to novel climatic conditions. There is currently a major gap between predictions of species vulnerability and management strategies, despite the fact that linking these areas is fundamental for future biodiversity conservation. Herein, we evaluate what drives vulnerability to climate change in three Iberian endemic water beetles, representing three independent colonizations of the same habitat, employing comparative thermal physiology, species distribution models and estimations of species dispersal capacity. We derive conservation strategies for each species based on their differential capacity to persist and/or potential to shift their ranges in response to global warming. We demonstrate that species may be affected by climatic warming in very different ways, despite having broadly similar ecological and biogeographical traits. The proposed framework provides an effective complement to traditional species vulnerability assessments, and could aid the development of more effective conservation strategies in the face of global warming.     

From projected species distribution to food‐web structure under climate change

Climate change is inducing deep modifications in species geographic ranges worldwide. However, the consequences of such changes on community structure are still poorly understood, particularly the impacts on food‐web properties. Here, we propose a new framework, coupling species distribution and trophic models, to predict climate change impacts on food‐web structure across the Mediterranean Sea. Sea surface temperature was used to determine the fish climate niches and their future distributions. Body size was used to infer trophic interactions between fish species. Our projections reveal that 54 fish species of 256 endemic and native species included in our analysis would disappear by 2080–2099 from the Mediterranean continental shelf. The number of feeding links between fish species would decrease on 73.4% of the continental shelf. However, the connectance of the overall fish web would increase on average, from 0.26 to 0.29, mainly due to a differential loss rate of feeding links and species richness. This result masks a systematic decrease in predator generality, estimated here as the number of prey species, from 30.0 to 25.4. Therefore, our study highlights large‐scale impacts of climate change on marine food‐web structure with potential deep consequences on ecosystem functioning. However, these impacts will likely be highly heterogeneous in space, challenging our current understanding of climate change impact on local marine ecosystems.     

Combining population genetics,species distribution modelling and field assessments to understand a species vulnerability to climate change

Climate change is recognized as a major threat to biodiversity. Multidisciplinary approaches that combine population genetics and species distribution modelling to assess these threats and recommend conservation actions are critical but rare. Combined, these methods provide independent verification and a more compelling case for developing conservation actions. This study integrates these data streams together with field assessments and spatial analyses to develop future genetic resource management recommendations. The study species was Callistemon teretifolius (Needle Bottlebrush), a shrub species endemic to the Mount Lofty and Flinders Ranges, South Australia, and potentially vulnerable to climate change. Chloroplast microsatellite and Amplified Fragment Length Polymorphism data were combined with species distribution modelling (MaxEnt), spatial analysis and field assessment to evaluate climate change vulnerability. Two major genetic groups were identified (Mount Lofty and Flinders Ranges). Populations in the Flinders Ranges, especially the Southern Flinders Ranges exhibited the highest genetic diversity, indicating a possible genetic refugium. Lower genetic diversity to the south in the Mount Lofty Ranges and north in the Gammon Ranges may be due to post‐glacial expansion into these areas from the Flinders Ranges or loss of alleles. Low levels of contemporary gene flow were identified, which suggests Callistemon teretifolius may have a limited capacity to respond to climate change through migration. Range restrictions were predicted for all future climates, especially in the north. It is likely that C. teretifolius will be adversely affected by climate change, due to limited gene flow, predicted range restriction and loss of suitable habitat. The Southern Flinders Ranges should be a priority for conservation because it contains the highest number of individuals and genetic diversity. We recommend monitoring and adaptive management involving restoration in the Southern Flinders Ranges, potentially incorporating genetic translocations from other areas to capture diversity, to assist C. teretifolius to adapt to climate change.     

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.