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Frontiers of Biogeography

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Birds and barriers: present and past seas are dominant correlates of avian turnover in the Indo-Australian Archipelago

Abstract

The Indo-Australian Archipelago (IAA) is a geologically dynamic area of high biotic endemism that spans the continental shelves of Sunda and Sahul and intervening oceanic islands. We provide a comprehensive quantitative assessment of how bird communities are structured across the IAA using beta diversity indices. We focus on three key questions. Are the islands of Wallacea a biogeographically cohesive unit or a more heterogeneous transition zone? Is the rich biota of New Guinea and the East Melanesian islands most closely linked to that of Sunda, Sahul or Wallacea? What are the geographic and environmental correlates of biotic structuring across the region and how does this compare with determinants of plant diversity? We measure the dissimilarity of bird species composition between eleven major areas within the IAA using a new compilation of distribution data and calculate taxonomic beta diversity at species, genera, and family levels. To compare with recent analyses of plants, we analysed potential correlates of turnover, focusing on geographic proximity, sea barriers, land area, and climatic variation. We also used connectivity analyses to estimate the minimum number of connection events needed to explain the current distribution of shared taxa. We found that islands recently connected by land have lower beta diversity than oceanic islands. Additionally, avifaunas on the islands of Wallacea have little biotic cohesion, reflecting their complex geological history. The avifaunas of New Guinea and the Eastern Melanesian islands are very distinctive. Where New Guinea birds are most similar to Australia, East Melanesian birds are more similar to either Sahul or Wallacea, depending on taxonomic level. Isolation through space and time had the strongest influence on avifaunal turnover at all taxonomic scales, in contrast to plants for which climatic variation was the strongest predictor. Further analyses incorporating phylogeny, biome, trait, and biotic interaction data are needed to investigate the processes that have caused biotic turnover across this fascinating biogeographic region.

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