Dataset Information

Ecological drivers of global gradients in avian dispersal inferred from wing morphology.

ABSTRACT: An organism's ability to disperse influences many fundamental processes, from speciation and geographical range expansion to community assembly. However, the patterns and underlying drivers of variation in dispersal across species remain unclear, partly because standardised estimates of dispersal ability are rarely available. Here we present a global dataset of avian hand-wing index (HWI), an estimate of wing shape widely adopted as a proxy for dispersal ability in birds. We show that HWI is correlated with geography and ecology across 10,338 (>99%) species, increasing at higher latitudes and with migration, and decreasing with territoriality. After controlling for these effects, the strongest predictor of HWI is temperature variability (seasonality), with secondary effects of diet and habitat type. Finally, we also show that HWI is a strong predictor of geographical range size. Our analyses reveal a prominent latitudinal gradient in HWI shaped by a combination of environmental and behavioural factors, and also provide a global index of avian dispersal ability for use in community ecology, macroecology, and macroevolution.

SUBMITTER: Sheard C

PROVIDER: S-EPMC7235233 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Ecological drivers of global gradients in avian dispersal inferred from wing morphology.

Sheard Catherine C Neate-Clegg Montague H C MHC Alioravainen Nico N Jones Samuel E I SEI Vincent Claire C MacGregor Hannah E A HEA Bregman Tom P TP Claramunt Santiago S Tobias Joseph A JA

Nature communications 20200518 1

An organism's ability to disperse influences many fundamental processes, from speciation and geographical range expansion to community assembly. However, the patterns and underlying drivers of variation in dispersal across species remain unclear, partly because standardised estimates of dispersal ability are rarely available. Here we present a global dataset of avian hand-wing index (HWI), an estimate of wing shape widely adopted as a proxy for dispersal ability in birds. We show that HWI is cor ...[more]

PMID: 32424113

Similar Datasets

Project description:The diversity of influenza A viruses (IAV) is primarily hosted by two highly divergent avian orders: Anseriformes (ducks, swans and geese) and Charadriiformes (gulls, terns and shorebirds). Studies of IAV have historically focused on Anseriformes, specifically dabbling ducks, overlooking the diversity of hosts in nature, including gull and goose species that have successfully adapted to human habitats. This study sought to address this imbalance by characterizing spillover dynamics and global transmission patterns of IAV over 10 years at greater taxonomic resolution than previously considered. Furthermore, the circulation of viral subtypes in birds that are either host-adapted (low pathogenic H13, H16) or host-generalist (highly pathogenic avian influenza-HPAI H5) provided a unique opportunity to test and extend models of viral evolution. Using Bayesian phylodynamic modelling we uncovered a complex transmission network that relied on ecologically divergent bird hosts. The generalist subtype, HPAI H5 was driven largely by wild geese and swans that acted as a source for wild ducks, gulls, land birds, and domestic geese. Gulls were responsible for moving HPAI H5 more rapidly than any other host, a finding that may reflect their long-distance, pelagic movements and their immuno-naïve status against this subtype. Wild ducks, long viewed as primary hosts for spillover, occupied an optimal space for viral transmission, contributing to geographic expansion and rapid dispersal of HPAI H5. Evidence of inter-hemispheric dispersal via both the Pacific and Atlantic Rims was detected, supporting surveillance at high latitudes along continental margins to achieve early detection. Both neutral (geographic expansion) and non-neutral (antigenic selection) evolutionary processes were found to shape subtype evolution which manifested as unique geographic hotspots for each subtype at the global scale. This study reveals how a diversity of avian hosts contribute to viral spread and spillover with the potential to improve surveillance in an era of rapid global change.

Project description:Geographical background and dispersal ability may strongly influence assemblage dissimilarity; however, these aspects have generally been overlooked in previous large-scale beta diversity studies. Here, we examined whether the patterns and drivers of taxonomic beta diversity (TBD) and phylogenetic beta diversity (PBD) of breeding birds in China vary across (1) regions on both sides of the Hu Line, which demarcates China's topographical, climatic, economic, and social patterns, and (2) species with different dispersal ability. TBD and PBD were calculated and partitioned into turnover and nestedness components using a moving window approach. Variables representing climate, habitat heterogeneity, and habitat quality were employed to evaluate the effects of environmental filtering. Spatial distance was considered to assess the impact of dispersal limitation. Variance partitioning analysis was applied to assess the relative roles of these variables. In general, the values of TBD and PBD were high in mountainous areas and were largely determined by environmental filtering. However, different dominant environmental filters on either side of the Hu Line led to divergent beta diversity patterns. Specifically, climate-driven species turnover and habitat heterogeneity-related species nestedness dominated the regions east and west of the line, respectively. Additionally, bird species with stronger dispersal ability were more susceptible to environmental filtering, resulting in more homogeneous assemblages. Our results indicated that regions with distinctive geographical backgrounds may present different ecological factors that lead to divergent assemblage dissimilarity patterns, and dispersal ability determines the response of assemblages to these ecological factors. Identifying a single universal explanation for the observed pattern without considering these aspects may lead to simplistic or incomplete conclusions. Consequently, a comprehensive understanding of large-scale beta diversity patterns and effective planning of conservation strategies necessitate the consideration of both geographical background and species dispersal ability.

Dataset Information

Ecological drivers of global gradients in avian dispersal inferred from wing morphology.

Publications

Ecological drivers of global gradients in avian dispersal inferred from wing morphology.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets