Assessment of ecological vulnerability and decision-making application for prioritizing roadside ecological restoration: A method combining geographic information system,Delphi survey and Monte Carlo simulation

Study experience of ecologist plays an important role in assessing the contribution of different influencing factors to ecological vulnerability, helping policy makers to target measures for ecological restoration. However, uncertainty is unavoidable due to variation of study experience among experts. In this study, a new method that combines Delphi survey, geographic information system and Monte Carlo simulation was proposed to assess regional ecological vulnerability and to quantify the uncertainty of assessing result. We illustrated the capacity of this method by using a case study in northeastern Inner Mongolia, China. An index system for 13 spatial variables was established to calculate an ecological vulnerability index (EVI) from the three aspects of ecological sensitivity (ES), ecological resilience (ER) and natural-social pressure (NSP). The assessment shows that the southwestern region of the study area, especially in the counties of Sonid Left and Right, was seriously threatened by a high ES and a low ER. Onguiud county in the Greater Hinggan Mountains had a high EVI due to an intensive NSP. Based on the assessing result and regional road distribution, an EVI cost curve was created to facilitate the prioritization of allocating limited funds among the various counties for roadside ecological restoration.     

Impact of landscape patterns on ecological vulnerability and ecosystem service values: An empirical analysis of Yancheng Nature Reserve in China

In this study, an ecological vulnerability assessment indicator system was constructed using the “exposure–climate sensitivity–adaptive capacity” framework according to the theory of ecological vulnerability. An improved ecosystem service value calculation model was proposed based on empirical parameters. Using Yancheng Nature Reserve in China as an example, we employed remote sensing data to conduct an empirical analysis of the changes in the spatiotemporal pattern, ecological vulnerability, and ecosystem services of typical landscape types over the period from 1987 to 2013. The statistical results derived from landscape pattern indices (LPIs) showed that during the investigation period, three natural wetland landscape types (i.e., Spartina alterniflora, Suaeda glauca, and Phragmites australis) showed gradually increased fragmentation in the study area. The ecological vulnerability scores of the major landscape types (in descending order) were P. australis (0.053), farmland (0.047), S. alterniflora (0.042), S. glauca (0.031), and bare mud flat (0.002). The results derived from the ecosystem service value fluctuation index (ESVFI) showed that from 1987 to 1997, the value of the ecosystem services provided by S. glauca and P. australis wetlands decreased, whereas that of S. alterniflora wetlands increased continuously. From 2002 to 2013, the value of the ecosystem services provided by all three types of natural wetland showed a downward trend. In conclusion, the combined effects of human and natural factors, including the expansion of farmland and the invasion of S. alterniflora, and changes in seawater erosion and deposition led to changes in the landscape patterns, ecological vulnerability, and ecosystem services of the Yancheng Nature Reserve during the investigation period. The results indicate that a “dual adaptive” management system based on natural succession and supplemented by appropriate manual intervention should be implemented, and the management efficiency and flexibility should be improved to meet the common needs of biodiversity conservation and economic development.     

闽三角城市群生态环境脆弱性及其驱动力

生态安全是地区社会经济可持续发展的基本前提之一,而生态环境脆弱性会威胁地区的生态安全,进行生态环境脆弱性评价具有重要意义。以闽三角城市群为例,分别选取2000年和2015年的高程、坡度、岩性、土壤类型、NDVI、年均降水量、年均温、人口密度、人均GDP、路网密度、景观多样性、土地利用程度和工业固体废弃物排放量等13个指标,基于空间主成分分析法,并结合全局Moran'I和LISA聚类图,从整体特征、空间差异、空间集聚、地类脆弱性分异以及驱动力5个方面,探讨闽三角城市群的生态环境脆弱性及其驱动力。结果表明:2000—2015年间,闽三角城市群的生态环境脆弱性整体处于中度脆弱,但呈现出由中度脆弱向重度脆弱过渡的趋势;2000—2015年间,生态环境脆弱性呈现出由东南沿海向西北内陆逐渐增强的整体趋势,并存在明显的地带性特征,东南沿海增长不明显,部分地区有所下降,而西北内陆增长明显;生态环境脆弱性存在显著的空间自相关性,且为显著正相关,在西北部山区地带为显著的高高聚集,在东南沿海平原地带为显著的低低聚集,16年间集聚性特征在空间上有所迁移和扩张;2000—2015年间,生态环境脆弱性在各地类存在着一定的异质性,其生态环境脆弱性指数大小顺序始终为:林地未利用地草地耕地水域建设用地,整体由中度脆弱向重度脆弱过渡;2000—2015年间,生态环境脆弱性的驱动力有所变化,但人口密度、景观多样性、岩性和土壤类型一直是闽三角城市群生态环境脆弱性主要的驱动力。     

承灾脆弱性视角下的生态系统服务需求评估及供需空间匹配

生态系统服务供需空间分布格局及匹配关系是生态系统服务领域的热点问题。将生态系统服务聚焦于增强城市系统承受自然灾害的能力和恢复力功能上,引入承灾脆弱性表征生态系统服务需求。选择首批经济特区之一的珠海市为案例研究区,土壤保持服务为供需分析的对象,利用承灾脆弱性评价城市系统及居民的服务需求并刻画需求的空间异质性,采用基于"3S技术"的In VEST模型定量评估服务供给潜力,从流域与镇、街道两种尺度分析生态系统服务供需匹配状况,以期为市级土地利用管理、景观格局优化及城市经济建设提供建议。研究结果表明:根据供需空间匹配状况,珠海市包含高供给高需求、低供给高需求、低供给低需求与高供给低需求四种供需匹配类型。珠海市土壤保持服务供需空间错位状况较为严重,人口密集的城镇区域需求极高但供给严重缺乏,部分生态源地的高供给无法惠及周边区域人口;兼顾经济建设与生态保护的高供给高需求地区仅占全域面积的8.7%;以农业导向且经济发展缓慢的低供给低需求地区分布较广。是对生态系统服务供给与需求的空间异质性刻画及供需空间匹配的重要尝试,为城市建设和生态管理提供参考。     

省域乡村旅游扶贫重点村生态脆弱性评价——以福建省为例

贫困与生态环境问题呈现强烈的相关性,为避免旅游扶贫重点村发展落入"贫困陷阱",有效地评价其生态脆弱性成为开展旅游扶贫和精准脱贫的重要前提。然而,当前鲜有将旅游扶贫与生态环境问题置于同一分析框架内,开展乡村旅游扶贫重点村生态脆弱性及其驱动因子研究的成果。以福建省472个全国乡村旅游扶贫重点村为样本,基于"成因-结果"模型构建生态脆弱性评价指标体系,采用空间主成分分析法测算样本生态脆弱性指数,并深入分析其空间分异与驱动因子。结果显示:重点村生态脆弱性指数平均值为4.84,总体处于轻度脆弱;30 m×30 m栅格单元生态脆弱性呈零散分布格局,空间分异不显著;极度和重度生态脆弱村主要分布在三明市、宁德市、南平市和龙岩市,并在宁德市和三明市形成3处高度脆弱核心区;餐饮和床位数、旅游基础设施状况、土壤侵蚀强度、人口密度、多年平均降水量、坡度、休闲农业园面积等为生态脆弱性主要驱动因子。     

Assess the human and environmental vulnerability for coastal hazard by using a multi-criteria decision analysis

This study provides an integrated approach using geographical information system (GIS) based on a multi-criteria approach (MCDA) to assess coastal vulnerability, resulting from human activity, population density, erosion, and climate change-induced sea level rise. A coastal vulnerability index (CVI) for erosion and floods was calculated and mapped (～24 km in length; ～400 m in width, and 11.47 km² in surface) for the lagoon barrier of Nador located on the Mediterranean coast of Morocco. Results suggest that 54% (～13 km) of the shoreline is moderately vulnerable, while 42% (～10 km) is highly vulnerable and only 4% (1 km) present a low vulnerability. The vulnerability map of the socio-economic activities indicates that most wetlands and forest areas 83% (～31 ha) and 50% (～440 ha) respectively, present low vulnerability. 52% percent of artificial areas (～23 ha), 73% of agricultural land (～128 ha), and 41% of natural areas (～363 ha) present moderate vulnerability. However, the level of vulnerability of the remaining artificial and agricultural areas classifies from high to very high. The north-western sector was classified as the most vulnerable area, characterized by an erosion (?0.6 m/yr to ?1.20 m/yr) for 70% of this area, while the south-eastern part shows a low to moderate vulnerability marked by an erosion (?0.1 m/yr to ?1m/yr) for 40% of this area. Coastal vulnerability maps have potential as decision tools to prepare and respond to sea level rise, and identify exposed coastal zones, as such contributing to national climate action and disaster risk reduction sustainable development goals (goals 13 and 11, respectively).     

Future vulnerability mapping based on response to extreme climate events: Dieback thresholds in an endemic California oak

Aim

This study presents a bioclimate modelling approach, using responses to extreme climate events, rather than historical distributional associations, to project future species vulnerability and refugia. We aim to illustrate the compounding effects of groundwater loss and climate on species vulnerability.

Location

California, USA.

Methods

As a case study, we used the 2012–2015 California drought and resulting extensive dieback of blue oak (Quercus douglasii). We used aerial dieback surveys, downscaled climate data and subsurface water change data to develop boosted regression tree models identifying key thresholds associated with dieback throughout the blue oak distribution. We (1) combined observed dieback–climatic threshold relationships with climate futures to anticipate future areas of vulnerability and (2) used satellite‐derived measurements of subsurface water loss in drought/dieback modelling to capture the mediating effect of groundwater on species response to climatic drought.

Results

A model including climate, climate anomalies and subsurface water change explained 46% of the variability in dieback. Precipitation in 2015 and subsurface water change accounted for 62.6% of the modelled probability of dieback. We found an interaction between precipitation and subsurface water in which dieback probability increased with low precipitation and subsurface water loss. The relationship between precipitation and dieback was nonlinear, with 99% of dieback occurring in areas that received <363 mm precipitation. Based on a MIROC_rcp85 future climate scenario, relative to historical conditions, 13% of the blue oak distribution is predicted to experience more frequent years below this precipitation threshold by mid‐century and 81% by end of century.

Main conclusions

As ongoing climate change and extreme events impact ecological processes, the identification of thresholds associated with observed dieback may be combined with climate futures to help identify vulnerable populations and refugia and prioritize climate change‐related conservation efforts.     

Ecological genomics predicts climate vulnerability in an endangered southwestern songbird

Few regions have been more severely impacted by climate change in the USA than the Desert Southwest. Here, we use ecological genomics to assess the potential for adaptation to rising global temperatures in a widespread songbird, the willow flycatcher (Empidonax traillii), and find the endangered desert southwestern subspecies (E. t. extimus) most vulnerable to future climate change. Highly significant correlations between present abundance and estimates of genomic vulnerability – the mismatch between current and predicted future genotype–environment relationships – indicate small, fragmented populations of the southwestern willow flycatcher will have to adapt most to keep pace with climate change. Links between climate‐associated genotypes and genes important to thermal tolerance in birds provide a potential mechanism for adaptation to temperature extremes. Our results demonstrate that the incorporation of genotype–environment relationships into landscape‐scale models of climate vulnerability can facilitate more precise predictions of climate impacts and help guide conservation in threatened and endangered groups.     

Using fuzzy logic to determine the vulnerability of marine species to climate change

Marine species are being impacted by climate change and ocean acidification, although their level of vulnerability varies due to differences in species' sensitivity, adaptive capacity and exposure to climate hazards. Due to limited data on the biological and ecological attributes of many marine species, as well as inherent uncertainties in the assessment process, climate change vulnerability assessments in the marine environment frequently focus on a limited number of taxa or geographic ranges. As climate change is already impacting marine biodiversity and fisheries, there is an urgent need to expand vulnerability assessment to cover a large number of species and areas. Here, we develop a modelling approach to synthesize data on species‐specific estimates of exposure, and ecological and biological traits to undertake an assessment of vulnerability (sensitivity and adaptive capacity) and risk of impacts (combining exposure to hazards and vulnerability) of climate change (including ocean acidification) for global marine fishes and invertebrates. We use a fuzzy logic approach to accommodate the variability in data availability and uncertainties associated with inferring vulnerability levels from climate projections and species' traits. Applying the approach to estimate the relative vulnerability and risk of impacts of climate change in 1074 exploited marine species globally, we estimated their index of vulnerability and risk of impacts to be on average 52 ± 19 SD and 66 ± 11 SD, scaling from 1 to 100, with 100 being the most vulnerable and highest risk, respectively, under the ‘business‐as‐usual' greenhouse gas emission scenario (Representative Concentration Pathway 8.5). We identified 157 species to be highly vulnerable while 294 species are identified as being at high risk of impacts. Species that are most vulnerable tend to be large‐bodied endemic species. This study suggests that the fuzzy logic framework can help estimate climate vulnerabilities and risks of exploited marine species using publicly and readily available information.