DOI: 10.1111/gcb.13869
Scopus记录号: 2-s2.0-85030324244
论文题名: Using fuzzy logic to determine the vulnerability of marine species to climate change
作者: Jones M.C. ; Cheung W.W.L.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2018
卷: 24, 期: 2 起始页码: e719
结束页码: e731
语种: 英语
英文关键词: climate change
; fishes
; fuzzy logic
; invertebrates
; marine
; ocean acidification
; risk of impacts
; vulnerability
Scopus关键词: climate change
; climate effect
; ecological impact
; environmental disturbance
; fish
; fuzzy mathematics
; invertebrate
; marine ecosystem
; marine environment
; ocean acidification
; vulnerability
; Invertebrata
; Pisces
英文摘要: 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. © 2017 John Wiley & Sons Ltd Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/110522
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Changing Ocean Research Unit, Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, Canada
Recommended Citation:
Jones M.C.,Cheung W.W.L.. Using fuzzy logic to determine the vulnerability of marine species to climate change[J]. Global Change Biology,2018-01-01,24(2)