The accumulation of vast numbers of molecular phylogenetic studies has contributed to huge knowledge gains in the evolutionary history of birds. This permits subsequent analyses of avian diversity, such as how and why diversification varies across the globe and among taxonomic groups. However, available genetic data for these meta-analyses are unevenly distributed across different geographic regions and taxonomic groups. To comprehend the impact of this variation on the interpretation of global diversity patterns, I examined the availability of genetic data for possible biases in geographic and taxonomic sampling of birds. I identified three main disparities of sampling that are geographically associated with latitude (temperate, tropical), hemispheres (East, West), and range size. Tropical regions, which host the vast majority of species, are substantially less studied. Moreover, Eastern regions, such as the Old World Tropics and Australasia, stand out as being disproportionately undersampled, with up to half of communities not being represented in recent studies. In terms of taxonomic discrepancies, a majority of genetically undersampled clades are exclusively found in tropical regions. My analysis identifies several disparities in the key regions of interest of global diversity analyses. Differential sampling can have considerable impacts on these global comparisons and call into question recent interpretations of latitudinal or hemispheric differences of diversification rates. Moreover, this review pinpoints understudied regions whose biota are in critical need of modern systematic analyses.
|Original language||English (US)|
|Number of pages||7|
|Journal||Molecular Phylogenetics and Evolution|
|State||Published - Aug 2014|
Bibliographical noteFunding Information:
This work was conducted with financial support from the US National Science Foundation ( DEB-0962078 ) and facilitated by the National Centre for Biological Sciences (India). Access to species distribution data was generously provided by BirdLife International and NatureServe. I am grateful to D. Treering and V. Varma for advice regarding GIS analyses and J. Bates, L. Davalos, P. Makovicky, R. Nandini, H. Skeen, U. Ramakrishnan, D. Rabosky, V.V. Robin, and two anonymous reviewers for constructive comments to improve this manuscript.
- DNA sequences
- Diversity patterns
- Sampling bias