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.     

Multiple axes of ecological vulnerability to climate change

Observed ecological responses to climate change are highly individualistic across species and locations, and understanding the drivers of this variability is essential for management and conservation efforts. While it is clear that differences in exposure, sensitivity, and adaptive capacity all contribute to heterogeneity in climate change vulnerability, predicting these features at macroecological scales remains a critical challenge. We explore multiple drivers of heterogeneous vulnerability across the distributions of 96 vegetation types of the ecologically diverse western US, using data on observed climate trends from 1948 to 2014 to highlight emerging patterns of change. We ask three novel questions about factors potentially shaping vulnerability across the region: (a) How does sensitivity to different climate variables vary geographically and across vegetation classes? (b) How do multivariate climate exposure patterns interact with these sensitivities to shape vulnerability patterns? (c) How different are these vulnerability patterns according to three widely implemented vulnerability paradigms—niche novelty (decline in modeled suitability), temporal novelty (standardized anomaly), and spatial novelty (inbound climate velocity)—each of which uses a distinct frame of reference to quantify climate departure? We propose that considering these three novelty paradigms in combination could help improve our understanding and prediction of heterogeneous climate change responses, and we discuss the distinct climate adaptation strategies connected with different combinations of high and low novelty across the three metrics. Our results reveal a diverse mosaic of climate change vulnerability signatures across the region's plant communities. Each of the above factors contributes strongly to this heterogeneity: climate variable sensitivity exhibits clear patterns across vegetation types, multivariate climate change data reveal highly diverse exposure signatures across locations, and the three novelty paradigms diverge widely in their climate change vulnerability predictions. Together, these results shed light on potential drivers of individualistic climate change responses and may help to inform effective management strategies.     

自然生态系统响应气候变化的脆弱性评价研究进展

以气候变暖为标志的全球气候变化已引起各国政府、国际组织和科学工作者的高度重视.气候变化给人类及自然生态系统带来的风险和危害日趋增大.生态系统脆弱性分析和评价是适应和减缓气候变化的关键和基础,已成为近年来气候变化领域和生态学领域的研究热点.目前国内外学者正在不同领域、不同空间尺度上开展响应气候变化的脆弱性评价,其中以自然生态系统为评价对象的脆弱性研究也有了长足的发展.本文通过对脆弱性的概念、气候变化脆弱性评价研究现状、自然生态系统响应气候变化的脆弱性定量评价方法的综述,探讨了该研究领域存在的问题和未来的发展前景.     

气候变化影响下海岸带脆弱性评估研究进展

近百年来,全球气候系统正经历着以全球变暖为主要特征的显著变化。研究海岸带系统对气候变化的响应机制,评估气候变化对海岸带社会、经济和生态的潜在影响,提出切实可行的应对策略,是保障海岸带系统安全的重要前提。回顾了IPCC的四次评估报告,分析了全球气候变化对海岸带的影响。总结了海岸带脆弱性评估框架以及脆弱性评价指标体系,综述了国内外气候变化影响下海岸带脆弱性评估研究的进展。在综述国内外该领域研究进展的基础上,展望了气候变化影响下海岸带脆弱性评估研究。全球气候变化及其对海岸带的影响还有大量的科学技术问题需要进一步探讨,同时也需要对各种适应气候变化措施的可行性和有效性进行研究和验证。     

中国水稻生产对历史气候变化的敏感性和脆弱性

有效的适应措施需要了解两类基础信息,一是农业生产所面临的各种气候变异风险,二是作物产量对潜在气候变异风险的反应及其机制.评价作物生产对历史气候变化的敏感性和脆弱性,可以在时间上和空间上揭示气候变化的趋势及作物产量对其的反应,从而为适应行动的全面开展提供基础信息.通过分析1981-2007年水稻生育期3个气候因子(平均温度、日较差、辐射)的变化对水稻产量的影响,评估我国水稻生产对这3个气候因子变化的敏感性和脆弱性及其区域分布状况.结果表明,1981-2007年间我国大部分水稻产区生育期内3个气候因子均发生了明显变化,存在着气候变异风险,其中以最高温的变化最普遍和明显,导致水稻生产中高温热害风险增加.部分区域水稻产量变化与单一气象因子的变化存在着显著的线性相关,这些地区气候因子的变化可以一定程度地解释水稻产量变化趋势,其中产量变化对辐射变化最敏感.当水稻生育期内平均温度上升1℃、日较差升高1℃、辐射下降10％时,我国部分地区水稻产量随之发生了相应的变化,其中辐射降低导致我国水稻生产的脆弱面积最大,其次为日较差.受3种气象因子变化趋势的综合影响,约有30％的水稻产区对1981-2007年的气候变化趋势敏感,少部分地区表现为脆弱,但水稻主产区受到的影响不大,且在东北地区还集中表现出产量增加的趋势,为我国水稻发展提供了契机.     

Variable choice affects estimations of vulnerability to climate change

For practical reasons, assessments of species' vulnerability to rising temperatures are often limited to measuring responses to a single ecological response variable, but this could result in an underestimation of vulnerability. Using the Cape Rockjumper Chaetops frenatus (‘Rockjumper’) we examined the thermal risk to nestling Rockjumpers for sublethal (i.e. reduced nestling mass gain) and lethal (i.e. increased nest predation) consequences of sustained hot weather under both current and predicted future climatic conditions (RCP 8.5). We used a direct approach to examine these risks, first as independent ecological responses and then as combined risk driven by both response variables (mass gain and predation risk). This study revealed that the inclusion of multiple climate-related responses affected the predicted vulnerability to climate change. Further, our analyses showed that increased vulnerability to climate change will vary within the Rockjumper's habitat. Our results demonstrate that the variability in predicted thermal risk depends on which response variable was used, with implications for how and where conservation practitioners direct their already limited resources.     

Assessing the vulnerability of an assemblage of subtropical rainforest vertebrate species to climate change in south‐east Queensland

Global climate change is a threat to ecosystems that are rich in biodiversity and endemism, such as the World Heritage‐listed subtropical rainforests of central eastern Australia. Possible effects of climate change on the biota of tropical rainforests have been studied, but subtropical rainforests have received less attention. We analysed published data for an assemblage of 38 subtropical rainforest vertebrate species in four taxonomic groups to evaluate their relative vulnerability to climate change. Focusing on endemic and/or threatened species, we considered two aspects of vulnerability: (i) resistance, defined by indicators of rarity (geographical range, habitat specificity and local abundance); and (ii) resilience, defined by indicators of a species potential to recover (reproductive output, dispersal potential and climatic niche). Our analysis indicated that frogs are most vulnerable to climate change, followed by reptiles, birds, then mammals. Many species in our assemblage are regionally endemic montane rainforest specialists with high vulnerability. Monitoring of taxa in regenerating rainforest showed that many species with high resilience traits also persisted in disturbed habitat, suggesting that they have capacity to recolonize habitats after disturbance, that is climate change‐induced events. These results will allow us to prioritize adaptation strategies for species most at risk. We conclude that to safeguard the most vulnerable amphibian, reptile and bird species against climate change, climatically stable habitats (cool refugia) that are currently without protection status need to be identified, restored and incorporated in the current reserve system. Our study provides evidence that montane subtropical rainforest deserves highest protection status as habitat for vulnerable taxa.     

Time‐lag effects of global vegetation responses to climate change

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time‐lag effects, which are the most important mechanism of climate–vegetation interactive effects. Extensive studies focused on large‐scale vegetation–climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time‐lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time‐lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time‐lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate‐driving factors for different vegetation types were determined. The results showed that (i) both the time‐lag effects of the vegetation responses and the major climate‐driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time‐lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time‐lag effects; (iii) for the area with a significant change trend (for the period 1982–2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time‐lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change.     

Potential changes in the distributions of latitudinally restricted Australian butterfly species in response to climate change

This study assessed potential changes in the distributions of Australian butterfly species in response to global warming. The bioclimatic program, BIOCLIM, was used to determine the current climatic ranges of 77 butterfly species restricted to Australia. We found that the majority of these species had fairly wide climatic ranges in comparison to other taxa, with only 8% of butterfly species having a mean annual temperature range spanning less than 3 °C. The potential changes in the distributions of 24 butterfly species under four climate change scenarios for 2050 were also modelled using BIOCLIM. Results suggested that even species with currently wide climatic ranges may still be vulnerable to climate change; under a very conservative climate change scenario (with a temperature increase of 0.8–1.4 °C by 2050) 88% of species distributions decreased, and 54% of species distributions decreased by at least 20%. Under an extreme scenario (temperature increase of 2.1–3.9 °C by 2050) 92% of species distributions decreased, and 83% of species distributions decreased by at least 50%. Furthermore, the proportion of the current range that was contained within the predicted range decreased from an average of 63% under a very conservative scenario to less than 22% under the most extreme scenario. By assessing the climatic ranges that species are currently exposed to, the extent of potential changes in distributions in response to climate change and details of their life histories, we identified species whose characteristics may make them particularly vulnerable to climate change in the future.     

Climate‐niche factor analysis: a spatial approach to quantifying species vulnerability to climate change

Climate change vulnerability assessments are an important tool for understanding the threat that climate change poses to species and populations, but do not generally yield insight into the spatial variation in vulnerability throughout a species’ habitat. We demonstrate how to adapt the method of ecological‐niche factor analysis (ENFA) to objectively quantify aspects of species sensitivity to climate change. We then expand ENFA to quantify aspects of exposure and vulnerability to climate change as well, using future projections of global climate models. This approach provides spatially‐explicit insight into geographic patterns of vulnerability, relies only on readily‐available spatial data, is suitable for a wide range of species and habitats, and invites comparison between different species. We apply our methods to a case study of two species of montane mammals, the American pika Ochotona princeps and the yellow‐bellied marmot Marmota flaviventris.     

A global assessment of the vulnerability of shellfish aquaculture to climate change and ocean acidification

Human‐induced climate change and ocean acidification (CC‐OA) is changing the physical and biological processes occurring within the marine environment, with poorly understood implications for marine life. Within the aquaculture sector, molluskan culture is a relatively benign method of producing a high‐quality, healthy, and sustainable protein source for the expanding human population. We modeled the vulnerability of global bivalve mariculture to impacts of CC‐OA over the period 2020–2100, under RCP8.5. Vulnerability, assessed at the national level, was dependent on CC‐OA‐related exposure, taxon‐specific sensitivity and adaptive capacity in the sector. Exposure risk increased over time from 2020 to 2100, with ten nations predicted to experience very high exposure to CC‐OA in at least one decade during the period 2020–2100. Predicted high sensitivity in developing countries resulted, primarily, from the cultivation of species that have a narrow habitat tolerance, while in some European nations (France, Ireland, Italy, Portugal, and Spain) high sensitivity was attributable to the relatively high economic value of the shellfish production sector. Predicted adaptive capacity was low in developing countries primarily due to governance issues, while in some developed countries (Denmark, Germany, Iceland, Netherlands, Sweden, and the United Kingdom) it was linked to limited species diversity in the sector. Developing and least developed nations (n = 15) were predicted to have the highest overall vulnerability. Across all nations, 2060 was identified as a tipping point where predicted CC‐OA will be associated with the greatest challenge to shellfish production. However, rapid declines in mollusk production are predicted to occur in the next decade for some nations, notably North Korea. Shellfish culture offers human society a low‐impact source of sustainable protein. This research highlights, on a global scale, the likely extent and nature of the CC‐OA‐related threat to shellfish culture and this sector enabling early‐stage adaption and mitigation.     

Past vegetation dynamics in the Yellowstone region highlight the vulnerability of mountain systems to climate change

Aim

Reconstruct the long‐term ecosystem dynamics of the region across an elevational gradient as they relate to climate and local controls. In particular, we (1) describe the dominant conifers' history; (2) assess changes in vegetation composition and distribution; and (3) note periods of abrupt change versus stability as means of better understanding vegetation responses to environmental variability.

Location

Greater Yellowstone Ecosystem (GYE; USA).

Time period

16.5 ka bp ‐present.

Major taxa studied

Juniperus, Picea, Abies, Pinus, Pseudotsuga.

Methods

The vegetation reconstruction was developed from 15 pollen records. Results were interpreted based on modern pollen–vegetation relationships estimated from a suite of regression‐based approaches.

Results

Calibrated pollen data suggest that late‐glacial vegetation, dominated by shrubs and Juniperus, lacks a modern counterpart in the area. Picea, Abies and Pinus expanded at 16 ka bp in association with postglacial warming and co‐occurred in mixed‐conifer parkland/forest after 12 ka bp . This association along with Pinus contorta forest, which was present after 9 ka bp , has persisted with little change at middle and high elevations to the present day. This stability contrasts with the dynamic history of plant communities at low elevations, where shifts between parkland, steppe and forest over the last 8,000 years were likely driven by variations in effective moisture and fire.

Main conclusions

The postglacial vegetation history of the GYE highlights the dynamic nature of mountain ecosystems and informs on their vulnerability to future climate change: (1) most of the conifers have been present in the area for >12,000 years and survived climate change by adjusting their elevational ranges; (2) some plant associations have exhibited stability over millennia as a result of nonclimatic controls; and (3) present‐day forest cover is elevationally more compressed than at any time in history, probably due to the legacy of the Medieval Climate Anomaly and the Little Ice Age.     

浙江省植被NDVI动态及其对气候的响应

利用GIMMS和MODIS两种归一化植被指数(NDVI)资料反演了1982—2010年浙江植被覆盖状况,结合同期研究区63个气象站点的气温、降水和湿润指数等气候指标,分析了该地区植被年际变化、月际变化及其对气候要素的响应特征。结果表明:(1)研究期间,浙江气候总体呈暖干化趋势,植被覆盖缓慢下降,主要是由于森林植被遭破坏,农业生产活动受抑制影响所致,其中NDVI显著减少的地区约占全省陆域面积的29.1%,主要发生在6—11月;(2)降水量及干湿程度对浙江植被NDVI年变化起着决定性作用。植被与气候要素年变化相关分析发现,NDVI与湿润指数关系较降水、气温更为密切,两者相关及偏相关系数均通过0.05水平的置信度检验,这表明在年际尺度上,湿度的增加增大了植被的生长势,有利于植被生长;(3)植被与气候要素月变化分析表明冬季的热量供给是影响浙江植被生长的重要因子,而植被变化对夏季降水和干湿程度的最大响应为滞后两个月;(4)农业生产水平的提高使得农作物种植区NDVI有所增加,人类活动对浙江植被覆盖的影响不可忽视。     

Stepping inside the niche: microclimate data are critical for accurate assessment of species' vulnerability to climate change

To assess a species'' vulnerability to climate change, we commonly use mapped environmental data that are coarsely resolved in time and space. Coarsely resolved temperature data are typically inaccurate at predicting temperatures in microhabitats used by an organism and may also exhibit spatial bias in topographically complex areas. One consequence of these inaccuracies is that coarsely resolved layers may predict thermal regimes at a site that exceed species'' known thermal limits. In this study, we use statistical downscaling to account for environmental factors and develop high-resolution estimates of daily maximum temperatures for a 36 000 km² study area over a 38-year period. We then demonstrate that this statistical downscaling provides temperature estimates that consistently place focal species within their fundamental thermal niche, whereas coarsely resolved layers do not. Our results highlight the need for incorporation of fine-scale weather data into species'' vulnerability analyses and demonstrate that a statistical downscaling approach can yield biologically relevant estimates of thermal regimes.     

气候变化背景下野生动物脆弱性评估方法研究进展

脆弱性评估是研究气候变化影响野生动物的重要内容,识别野生动物脆弱性,是适应和减缓气候变化影响的关键和基础。开展气候变化背景下野生动物的脆弱性评估工作,目的是为了确定易受气候变化影响的物种和明确导致物种脆弱性的因素,其评估结果有助于人类认识气候变化对野生动物的影响,为野生动物适应气候变化保护对策的制定提供科学依据。对野生动物而言(物种),脆弱性是物种受气候变化影响的程度,包括暴露度、敏感性和适应能力三大要素。其中,暴露度是由气候变化引起的外在因素,如温度、降雨量、极值天气等;敏感性是受物种自身因素影响,如种间关系、耐受性等;适应能力是物种通过自身调整来减小气候变化带来的影响,如迁移或扩散到适宜生境的能力、塑性反应和进化反应等。对近期有关气候变化背景下野生动物脆弱性评估方法予以综述,比较每种评估方法所选取指标的差异,总结在脆弱性评估中遇到的不确定性指标的处理方法,以及脆弱性评估结果在野生动物适应气候变化对策中的应用。通过总结野生动物脆弱性评估方法,以期为气候变化背景下评估我国野生动物资源的脆弱性提供参考方法。     

Assessing household livelihood vulnerability to climate change: The case of Northwest Vietnam

This study applied livelihood vulnerability index (LVI) and livelihood effect index (LEI) to assess vulnerability from climate variability and change of three agricultural and natural resources dependent commune in northwest Vietnam, a country that is expected to bear some of the most severe impacts of climate change. Based on a survey of 335 farm household data, complemented with secondary data on climate factors, a composite index was calculated and differential vulnerabilities were compared. The results of the analysis suggest that one of the communities, “Pa Vay Su,” was more vulnerable than the others, particularly in relation to housing, knowledge and skills, socio-demographics, health and water security, social networks, and livelihood strategy. “Hien Luong” commune, on the other hand, was more vulnerable in relation to other LVI indicators with the exception of food security, climate variability, and natural disasters. “Moc Chau” community was more vulnerable in relation to water security, social demographic than Hien Luong commune. Overall, the article shows that three different vulnerability assessment indices can be broadly applied in comparable setting in other areas of country and they could usefully establish the basis for a nationally applicable index to identify and prioritize adaptation and mitigation needs.     

Profiling urban vulnerabilities to climate change: An indicator-based vulnerability assessment for European cities

Governing climate change in cities entails a good understanding of urban vulnerabilities. This research presents an Indicator-based Vulnerability Assessment for 571 European cities. Basing on panel data from Urban Audit database and a set of newly developed indicators, we assessed urban vulnerabilities for the following impact chains: (i) heatwaves on human health; (ii) drought on water planning, and; (iii) flooding (sub-divided into pluvial, fluvial and coastal) on the socio-economic tissue and the urban fabric. Results shed light on the key challenges that specific groups of European cities face in order to better deal with the expected impacts of climate change. This knowledge is a necessary step to advance in the understanding of urban risks to climate change and the development of effective EU policies for urban adaptation.     

Livestock and food security: vulnerability to population growth and climate change

Livestock production is an important contributor to sustainable food security for many nations, particularly in low‐income areas and marginal habitats that are unsuitable for crop production. Animal products account for approximately one‐third of global human protein consumption. Here, a range of indicators, derived from FAOSTAT and World Bank statistics, are used to model the relative vulnerability of nations at the global scale to predicted climate and population changes, which are likely to impact on their use of grazing livestock for food. Vulnerability analysis has been widely used in global change science to predict impacts on food security and famine. It is a tool that is useful to inform policy decision making and direct the targeting of interventions. The model developed shows that nations within sub‐Saharan Africa, particularly in the Sahel region, and some Asian nations are likely to be the most vulnerable. Livestock‐based food security is already compromised in many areas on these continents and suffers constraints from current climate in addition to the lack of economic and technical support allowing mitigation of predicted climate change impacts. Governance is shown to be a highly influential factor and, paradoxically, it is suggested that current self‐sufficiency may increase future potential vulnerability because trade networks are poorly developed. This may be relieved through freer trade of food products, which is also associated with improved governance. Policy decisions, support and interventions will need to be targeted at the most vulnerable nations, but given the strong influence of governance, to be effective, any implementation will require considerable care in the management of underlying structural reform.     

喀斯特流域径流对植被和气候变化的多尺度响应

植被覆盖和气候变化对径流的影响可能具有尺度依赖性,而在生态环境脆弱和地质结构复杂的西南喀斯特区开展研究较少。为此,以喀斯特地貌广泛发育的西江流域为研究区,选取郁江、红水河、浔江和梧州4个流域,利用Mann-Kendall趋势检验对4个流域年径流深、NDVI、降水量、潜在蒸散发和气温(1982—2015)的变化趋势进行了分析,运用多元经验模态分解(MEMD)量化了流域径流深与植被和气候因子在不同尺度上的相关性,并预测了年径流深,旨在研究喀斯特流域径流对植被和气候变化的多尺度响应。结果表明,径流深仅有红水河流域呈显著下降趋势(P<0.05)。其中郁江流域径流深主要表征尺度为3年和5年,红水河流域径流深主要表征尺度为10年和22年,浔江和梧州流域径流深主要表征尺度为3年和22年。径流深与植被和气候因子的关系具有尺度依赖性,在不同尺度下,4个流域径流深与降水量和潜在蒸散发始终呈显著相关性(P<0.05),而径流深与NDVI和气温的多尺度关系在某些表征尺度上并不显著。利用MEMD法对径流深的预测效果(R²=0.81—0.86)要优于基于原始数据的多元逐步回归方法...