Some Pacific island societies, such as those of Easter Island and Mangareva, inadvertently contributed to their own collapse by causing massive deforestation1,2,3,4,5,6,7. Others retained forest cover and survived3,8,9. How can those fateful differences be explained? Although the answers undoubtedly involve both different cultural responses of peoples and different susceptibilities of environments, how can one determine which environmental factors predispose towards deforestation and which towards replacement of native trees with useful introduced tree species? Here we code European-contact conditions and nine environmental variables for 81 sites on 69 Pacific islands from Yap in the west to Easter in the east, and from Hawaii in the north to New Zealand in the south. We thereby detect statistical decreases in deforestation and/or forest replacement with island rainfall, elevation, area, volcanic ash fallout, Asian dust transport and makatea terrain (uplifted reef), and increases with latitude, age and isolation. Comparative analyses of deforestation therefore lend themselves to much more detailed interpretations than previously possible. These results might be relevant to similar deforestation-associated collapses (for example, Fertile Crescent, Maya and Anasazi) or the lack thereof (Japan and highland New Guinea) elsewhere in the world.
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We thank D. Clague, C. Field, B. Huebert, B. Keating, P. Kirch, L. Kronke, A. Kurtz, E. Landaw, G. Merchant, J. Prospero and P. Vitousek for discussions, and J. Gornbein for the statistical design and analyses.
The authors declare that they have no competing financial interests.
This file describes our statistical analyses in more detail. (DOC 22 kb)
This table gives values of our two outcome variables, nine independent variables, and alternative values for area and isolation, for our 81 data entries. Our 69-entry set omitted islands 1–10, 29 and 30. (XLS 34 kb)
This table gives Spearman correlation coefficients for our 81-entry data set. (XLS 21 kb)
This table gives Spearman correlation coefficients for our 69-entry data set. (XLS 19 kb)
These tables give Spearman correlation coefficients for our 81-entry and 69-entry data sets. (DOC 27 kb)
This table compares results of conventional multiple linear regression (minimizing squared differences between observed and model-predicted values) with results from robust linear regression (minimizing absolute unsigned differences between observed and model-predicted values). (DOC 24 kb)
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