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タイトル
和文:Ecological niche modelling for archaeological prediction: Case studies from the Pleistocene Levant and Holocene East Japan 
英文:Ecological niche modelling for archaeological prediction: Case studies from the Pleistocene Levant and Holocene East Japan 
著者
和文: 近藤 康久, 小口高.  
英文: Yasuhisa Kondo, Takashi Oguchi.  
言語 English 
掲載誌/書名
和文: 
英文: 
巻, 号, ページ        
出版年月 2012年3月28日 
出版者
和文: 
英文: 
会議名称
和文:Computer Applications and Quantitative Methods in Archaeology 
英文:Computer Applications and Quantitative Methods in Archaeology 
開催地
和文:サウザンプトン 
英文:Southampton 
アブストラクト Ecological niche modelling is a method to predict presence of a given biological species by environmental parameters. It is also applicable to humans as eco-cultural niche modelling (ECNM) under the condition that the human behaviour significantly depends on the natural environment [1]. There are two methods of ECNM––Genetic Algorithm for Rule-set Production (GARP) [2] and Maximum Entropy Model (Maxent) [3]. Both models require geocoordinates of archaeological sites and environmental variables such as terrain elevation, slope, mean temperature, and annual precipitation. GARP outputs prediction in binary [0,1], while Maxent outputs in continuous probability [0...1]. This paper applies these predictive models to two case studies: 1) the replacement of Neanderthals by anatomically modern humans in the Levant, and 2) the subsistence economy of Jomon hunter-gatherer-fishers in East Japan. Then validity of the models is discussed and a hybrid model based on the two models is proposed for better predicting and visualising site presence.[1] Banks, W. E. et al. 2008. Human ecological niches and ranges during the LGM in Europe derived from an application of eco-cultural niche modeling. Journal of Archaeological Science 35:481-491. [2] Stockwell, D. R. B. 1999. Genetic Algorithms II: spatial distribution modelling. In: Machine Learning Methods for Ecological Applications, edited by A. H. Fielding, Kluwer, pp. 123-144.[3] Phillips, S. J. et al. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190:231-59.

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