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<eml:eml scope="system" system="https://dataportal.senckenberg.de" packageId="bea0f12d-d073-4580-95f2-5410aa223965" xsi:schemaLocation="https://eml.ecoinformatics.org/eml-2.2.0" xmlns:eml="https://eml.ecoinformatics.org/eml-2.2.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><dataset><title>Rates of ecomorphological trait evolution in passerine birds are independent of clade age</title><creator><individualName><givenName>Anna</givenName><surName>Phillips</surName></individualName><organizationName>Senckenberg Biodiversity and Climate Research Centre (SBiK-F)</organizationName><address /></creator><associatedParty><individualName><givenName>Anna</givenName><surName>Phillips</surName></individualName><role>associatedParty</role></associatedParty><associatedParty><individualName><givenName>Katrin</givenName><surName>B&#246;hning-Gaese</surName></individualName><role>Co-owner</role></associatedParty><associatedParty><individualName><givenName>Susanne</givenName><surName>Fritz</surName></individualName><role>Co-owner</role></associatedParty><pubDate>2018-03-28</pubDate><abstract><para>While the links between species richness and diversification rates with clade age have been studied extensively, very few studies have investigated the relationship between the rates of trait evolution and clade age. It is therefore not well understood whether the rate of morphological trait evolution within a clade is similar or dissimilar in clades of different ages. We compare the relationship between the rates of trait evolution and clade age across eight monophyletic clades of passerine birds by investigating ecomorphological traits, i.e. morphological traits that are of high ecological importance. We study the ecomorphological divergence pattern using disparity through time analyses and then determine the best-fitting model of evolution for each trait in each clade. We find no support for a dependence of evolutionary rates on clade age, and further show that Early Burst models of trait evolution are rarely the best fitting models within these clades. Our results reveal the unpredictability of ecomorphological trait evolution despite commonly suggested evolutionary patterns of key innovations or adaptive radiations.</para></abstract><keywordSet><keyword>evolutionary models</keyword><keyword>passeriformes</keyword><keyword>rate-age relationship</keyword><keyword>trait evolution</keyword></keywordSet><intellectualRights><para>Obtain permission from data set owner(s)</para></intellectualRights><coverage><geographicCoverage><geographicDescription>Global</geographicDescription><boundingCoordinates><westBoundingCoordinate>180.0</westBoundingCoordinate><eastBoundingCoordinate>-180.0</eastBoundingCoordinate><northBoundingCoordinate>90.0</northBoundingCoordinate><southBoundingCoordinate>-90.0</southBoundingCoordinate></boundingCoordinates></geographicCoverage><temporalCoverage><singleDateTime><calendarDate>2014-11-01</calendarDate></singleDateTime></temporalCoverage><taxonomicCoverage><generalTaxonomicCoverage>The following clades were chosen across the order of passerine birds (Aves: Passeriformes) based on morphological diversity, high phylogenetic resolution, and a similar species richness in each clade: Cardinalidae, Parulidae (Setophaga-Myiothlypis clade), Tyrannidae (Xolmiini clade), Muscicapidae (Oenanthe-Monticola clade), Turdidae (genus Turdus), Hirundinidae, Vireonidae, Corvidae (genus Corvus). Species names follow IOC taxonomy v 5.01.</generalTaxonomicCoverage><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Cardinalidae</taxonRankValue></taxonomicClassification><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Parulidae (Setophaga-Myiothlypis clade)</taxonRankValue></taxonomicClassification><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Tyrannidae (Xolmiini clade)</taxonRankValue></taxonomicClassification><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Muscicapidae (Oenanthe-Monticola clade)</taxonRankValue></taxonomicClassification><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Turdidae (genus Turdus)</taxonRankValue></taxonomicClassification><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Hirundinidae</taxonRankValue></taxonomicClassification><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Vireonidae</taxonRankValue></taxonomicClassification><taxonomicClassification><taxonRankName>Family</taxonRankName><taxonRankValue>Corvidae (genus Corvus)</taxonRankValue></taxonomicClassification></taxonomicCoverage></coverage><contact><individualName><givenName>Susanne</givenName><surName>Fritz</surName></individualName><organizationName>Senckenberg Biodiversity and Climate Research Centre (SBiK-F)</organizationName><address><deliveryPoint>Senckenberganlage 25</deliveryPoint><city>Frankfurt am Main</city><postalCode>60325</postalCode><country>Germany</country></address><electronicMailAddress>susanne.fritz@senckenberg.de</electronicMailAddress></contact><methods><methodStep><description><section>
<title>Construction of phylogenies</title>
<para>We constructed phylogenies for each clade. Sequences for each species in each clade were obtained from GenBank (www.ncbi.nlm.nik.gov/genbank) for between two and tree genes per clade, and aligned using MUSCLE alignment for DNA in MEGA7. An appropriate nucleotide-substitution model was chosen based on the Akaike information criterion calculated using JModeltest version 2.0. We used BEAST version 2.4.4 (Bayesian Evolutionary Analysis Sampling Trees) to estimate the phylogeny for each clade. Probabilities for all gene sequences were calculated under the HKY nucleotide-substitution model, assuming rate variation across sites according to a gamma distribution with four rate categories and an estimated proportion of invariable sites. We repeated the analysis in four separate runs with 50 million generations, with the Yule model selected as the species tree prior and a relaxed log-normal molecular clock. Convergence of individual runs was assessed in TRACER version 1.4, and we combined the results following burn-in (5-16%) from all runs using LogCombiner enabled in BEAST2. We calculated a maximum clade credibility tree using TreeAnnotator for analyses (also enabled in BEAST2) and additionally sampled 100 trees from the posterior distribution for further model fitting. Each clade was processed separately.</para>
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<temporalDataType>timeseries</temporalDataType>
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<temporalDataInfo>Start of PhD project</temporalDataInfo>
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<temporalResolution>other</temporalResolution>
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<climaticNiche />
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