globalchange  > 气候减缓与适应
DOI: 10.1007/s10584-017-2082-1
Scopus记录号: 2-s2.0-85030325182
论文题名:
Predictor weighting and geographical background delimitation: two synergetic sources of uncertainty when assessing species sensitivity to climate change
作者: Acevedo P.; Jiménez-Valverde A.; Lobo J.M.; Real R.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2017
卷: 145, 期:2018-01-02
起始页码: 131
结束页码: 143
语种: 英语
英文关键词: European wild mammals ; Extent ; Historical factors ; Spatial factors ; Spatial structure ; Species distribution models
Scopus关键词: Climate models ; Mammals ; Population distribution ; Uncertainty analysis ; Extent ; Historical factors ; Spatial factors ; Spatial structure ; Species distribution models ; Climate change ; assessment method ; climate change ; climate effect ; endemic species ; factor analysis ; geographical distribution ; geographical variation ; mammal ; numerical model ; prediction ; sensitivity analysis ; uncertainty analysis ; wild population ; Western Europe ; Mammalia
英文摘要: An accurate estimation of the expected consequences of climate change requires the proper quantification of the effect of climate on current species distributions. Several interrelated sources of uncertainty may affect the likelihood of species distribution models (SDMs) to determine the relative importance of climate. Our aim was to assess the relationship between the influence of geographical background (GB) delimitation and that of subtracting the non-climate effects from the weight of climatic predictors to estimate the combined influence of these two factors on predictions in climate change scenarios. The distribution of 40 endemic mammals in Western Europe have been modeled by (i) using the whole territory of Western Europe as the GB and also specifically delimiting the GB with a geographical criterion and (ii) considering climatic predictors in addition to other non-climatic variables in order to extract the pure effect of climate. The models were used to quantify species’ sensitivity to new climate scenarios. Results showed discrepancies among the analytical approaches. Changes in distribution obtained by considering the pure effect of climate were lower than those obtained by considering the apparent effect, and GB-delimited models yielded higher changes than those trained in Western Europe. We evidence that climate weighting and GB delimitation have dramatic influences on the projections of models when transferred to new scenarios. We emphasize that scientific studies and derived adaptation policies based on SDMs without an explicit consideration of the GB and the weighting of the climate-related variables may be misleading and in need of revision. © 2017, Springer Science+Business Media B.V.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/83885
Appears in Collections:气候减缓与适应
气候变化事实与影响

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作者单位: Instituto de Investigación en Recursos Cinegéticos (IREC), UCLM-CSIC-JCCM, Ciudad Real, Spain; Grupo de Investigación de Biología del Suelo y de los Ecosistemas Subterráneos, Departamento de Ciencias de la Vida, Universidad de Alcalá. A.P. 20 Campus Universitario, Alcalá de Henares, Madrid, Spain; Departamento de Biogeografía y Cambio Global, Museo Nacional de Ciencias Naturales (CSIC), Madrid, Spain; Departamento de Biología Animal, Facultad de Ciencias, Universidad de Málaga, Málaga, Spain

Recommended Citation:
Acevedo P.,Jiménez-Valverde A.,Lobo J.M.,et al. Predictor weighting and geographical background delimitation: two synergetic sources of uncertainty when assessing species sensitivity to climate change[J]. Climatic Change,2017-01-01,145(2018-01-02)
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