Comparison of species distribution models for assessing the impacts of climate change

Yuko Onishi; Pam Berry

doi:10.14866/ajg.2012s.0_100283

Annual Meeting of the Association of Japanese Geographers, Spring 2012

Session ID : P1204

DOI https://doi.org/10.14866/ajg.2012s.0_100283

Conference information

Host: The Association of Japanese Geographers

Abstract

Comparison of species distribution models for assessing the impacts of climate change

*Yuko Onishi, Pam Berry

Author information

Keywords: Climate change, Impact assessment, Species Distribution, Statistical Modelling

CONFERENCE PROCEEDINGS FREE ACCESS

Details

Abstract

We compared the accuracy of five different methods of species distribution models in predicting the potential distribution of plant species in Japan. The result showed that, on average, Artificial Neural Network (ANN) had the highest accuracy, followed by Generalised Additive Models (GAM), Generalised Boosted Models (GBM), Random Forest (RF), and Classification Tree Analysis (CTA).

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