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Historical Rainforest Contractions, Localized Extinctions and Patterns of Vertebrate Endemism in the Rainforests of Australia's Wet Tropics

Stephen E. Williams and Richard G. Pearson
Proceedings: Biological Sciences
Vol. 264, No. 1382 (May 22, 1997), pp. 709-716
Published by: Royal Society
Stable URL: http://www.jstor.org/stable/51092
Page Count: 8
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Historical Rainforest Contractions, Localized Extinctions and Patterns of Vertebrate Endemism in the Rainforests of Australia's Wet Tropics
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Abstract

The spatial patterns in the distributions of vertebrates in the rainforests of the wet tropics biogeographic region of north-eastern Australia were examined to form hypotheses on the processes that have shaped vertebrate assemblages and patterns of species richness and regional endemism. These rainforests occur in a relatively narrow and discontinuous strip along the coast of north-eastern Australia. We found that the number of regionally endemic species and the proportion of regional endemics present in each subregion are both strongly related to the geographic shape of subregional patches of rainforest, independent of rainforest area, within Australian tropical rainforests. Shape has a more significant influence on regional endemism than area, and area has a stronger influence on species richness. These patterns were congruent for all terrestrial vertebrate classes (mammals, birds, reptiles and frogs), and for the four groups combined. Our results suggest that the combination of current rainforest area and shape are an index of the relative susceptibility of each area of rainforest to historical contractions, with the implication that historical habitat fluctuations, coupled with subsequent localized extinctions (species sifting), have been extremely important processes in determining current patterns of endemism in Australia's wet tropical rainforests. This hypothesis is supported by the highly nested structure of the subregional distribution patterns.

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