Automatic classification of climate change effects on marine species distributions in 2050 using the AquaMaps model

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• 作者：Gianpaolo Coro ; Chiara Magliozzi…
• 关键词：AquaMaps ; Big Data ; Climate change ; Clustering analysis ; Ecological niche modelling ; GIS ; Maps comparison ; OGC standards ; Species distribution maps
• 刊名：Environmental and Ecological Statistics
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：23
• 期：1
• 页码：155-180
• 全文大小：2,136 KB
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• 作者单位：Gianpaolo Coro (1)
  Chiara Magliozzi (1)
  Anton Ellenbroek (2)
  Kristin Kaschner (3)
  Pasquale Pagano (1)
  
  1. Istituto di Scienza e Tecnologie dell’Informazione “Alessandro Faedo” – CNR, via Moruzzi 1, 56124, Pisa, Italy
  2. Food and Agriculture Organization of the United Nations (FAO), Viale delle Terme di Caracalla, 00153, Rome, Italy
  3. Department of Biometry and Environmental Systems Analysis, Albert-Ludwigs University, Hauptstrasse 1, 79104, Freiburg, Germany
  
• 刊物类别：Biomedical and Life Sciences
• 刊物主题：Life Sciences
  Ecology
  Statistics
  Mathematical Biology
  Evolutionary Biology
  
• 出版者：Springer Netherlands
• ISSN：1573-3009

文摘

Habitat modifications driven by human impact and climate change may influence species distribution, particularly in aquatic environments. Niche-based models are commonly used to evaluate the availability and suitability of habitat and assess the consequences of future climate scenarios on a species range and shifting edges of its distribution. Together with knowledge on biology and ecology, niche models also allow evaluating the potential of species to react to expected changes. The availability of projections of future climate scenarios allows comparing current and future niche distributions, assessing a species’ habitat suitability modification and shift, and consequently estimating potential species’ reaction. In this study, differences between the distribution maps of 406 marine species, which were produced by the AquaMaps niche models on current and future (year 2050) scenarios, were estimated and evaluated. Discrepancy measurements were used to identify a discrete number of categories, which represent different responses to climate change. Clustering analysis was then used to automatically detect these categories, demonstrating their reliability compared to human supervised classification. Finally, the distribution of characteristics like extinction risk (based on IUCN categories), taxonomic groups, population trends and habitat suitability change over the clustering categories was evaluated. In this assessment, direct human impact was neglected, in order to focus only on the consequences of environmental changes. Furthermore, in the comparison between two climate snapshots, the intermediate phases were assumed to be implicitly included into the model of the 2050 climate scenario. Keywords AquaMaps Big Data Climate change Clustering analysis Ecological niche modelling GIS Maps comparison OGC standards Species distribution maps