Pigot, A. L., Sheard, C., Miller, E. T., Bregman, T. P., Freeman, B. G.,Roll, U., Seddon, N., Trisos, C. H., Weeks, B. C., & Tobias, J. A.(2020). Macroevolutionary convergence connects morphological formto ecological function in birds. Nature Ecology and Evolution, 4, 230-239 (2020). https://doi.org/10.1038/s41559-019-1070-4

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1

Macroevolutionaryconvergenceconnectsmorphologicalformto1

ecologicalfunctioninbirds2

3

4

Authors:AlexL.Pigot1,2†*,CatherineSheard3,2†,EliotT.Miller4,5,TomP.Bregman6,2,5

BenjaminG.Freeman7,UriRoll8,2,NathalieSeddon2,BrianC.Weeks9,10,JosephA.6

Tobias11,2*7

8

Affiliations:9 1CentreforBiodiversityandEnvironmentResearch,DepartmentofGenetics,Evolution10

andEnvironment,UniversityCollegeLondon,GowerStreet,London,WC1E6BT,UK.11 2DepartmentofZoology,UniversityofOxford,SouthParksRoad,Oxford,OX13PS,UK.12 3SchoolofBiology,UniversityofStAndrews,Fife,KY169TJ,UK.13 4CornellLabofOrnithology,159SapsuckerWoodsRd.,Ithaca,NY14850,USA.14 5DepartmentofBiologicalSciences,UniversityofIdaho,Moscow,Idaho83844,USA.15 6Future-FitFoundation,1PrimroseStreet,Spitalfields,London,EC2A2EX,UK.16 7BiodiversityResearchCentre,UniversityofBritishColumbia,6270UniversityBlvd.,17

VancouverBC,V6T1Z4,Canada.18 8MitraniDepartmentofDesertEcology,JacobBalausteinInstitutesforDesertResearch,19

Ben-GurionUniversityoftheNegev,MidreshetBen-Gurion8499000,Israel.20 9SchoolforEnvironmentandSustainability,UniversityofMichigan,AnnArbor,MI21

48109,USA.22 10DepartmentofOrnithology,AmericanMuseumofNaturalHistory,79thStreetat23

CentralParkWest,NewYork,NY10024,USA.24 11DepartmentofLifeSciences,ImperialCollegeLondon,SilwoodPark,BuckhurstRoad,25

AscotSL57PY,UK.26

†Equalcontribution27 *Correspondenceto:a.pigot@ucl.ac.uk; j.tobias@imperial.ac.uk 28 29 Wordcount:Abstract(154),Maintext(3,132),Methods(3,654),Captionsfor6figures30 (581)31 References:Maintext(52),Total(75) 32

2

Animalshavediversifiedintoabewilderingvarietyofmorphologicalforms33

exploitingacomplexconfigurationoftrophicniches.Theirmorphological34

diversityiswidelyusedasanindexofecosystemfunction,buttheextenttowhich35

animaltraitspredicttrophicnichesandassociatedecologicalprocessesis36

unclear.Hereweusemeasurementsofninekeymorphologicaltraitsfor>99%37

birdspeciestoshowthataviantrophicdiversityisdescribedbyatraitspacewith38

fourdimensions.Thepositionofspecieswithinthisspacemapswith70-85%39

accuracyontomajornicheaxes,includingtrophiclevel,dietaryresourcetypeand40

finer-scalevariationinforagingbehaviour.Phylogeneticanalysesrevealthat41

theseform-functionassociationsreflectconvergencetowardspredictabletrait42

combinations,indicatingthatmorphologicalvariationisorganisedintoalimited43

setofdimensionsbyevolutionaryadaptation.Ourresultsestablishtheminimum44

dimensionalityrequiredforavianfunctionaltraitstopredictsubtlevariationin45

trophicniches,andprovideaglobalframeworkforexploringtheorigin,function46

andconservationofbirddiversity.47

48

3

Plantsandanimalshavecomplementaryfunctionsinthebiosphere,withplantsmainly49

contributingasautotrophicproducersandanimalsoccupyingmultiplehighertrophic50

levelsasprimary,secondaryandtertiaryconsumers1-4.Restrictionofmostplantspecies51

toasingletrophiclevelatthefoundationoffoodwebstheoreticallylimitsthescopefor52

nichevariation,perhapsexplainingwhytheirvasttraitdiversityispredominantly53

constrainedtoasimpleplanewithtwodimensions5.Incontrast,theecologicaltrait54

spaceofheterotrophicconsumersispotentiallymorecomplexand55

multidimensional6-9,particularlyifdistinctsetsofmorphologicaltraitsare56

consistentlyassociatedwithdifferenttrophiclevelsanddietarytypes¾including57

herbivores,pollinatorsandpredators10.Thisconceptofapredictablelinkbetween58

animalformandfunctionhasexistedsinceAristotle11andnowunderpinsnumerous59

trait-basedresearchprogrammes12,fromresolvingtheevolutionaryoriginsof60

biodiversity13,14toquantifyingecosystemfunction15,16andpredictingresponsesto61

environmentalchange17,18.However,theassumptionthatecologicalnichespaceand62

associatedecosystemfunctionscanbeadequatelyquantifiedusingalimitedsetof63

phenotypictraitsremainscontroversial19,20.64

Atoneextremeofcomplexity,speciesandtheirtraitsmaybeembeddedwithin65

anabstractmultidimensionalnichespace,the‘n-dimensionalhypervolume’ofG.E.66

Hutchinson21.Byassuminganalmostlimitlessnumberofecologicaldimensions,this67

modelprovidesacompellingexplanationforthediversityofspeciesandphenotypes68

foundinnature13,14,21.Attheotherextreme,themappingoftraitsontonichespacemay69

besimplifiedtoasingledimension22-24byfunctionaltrade-offs25orpervasive70

convergentevolution26,27.Whetherform-functionrelationshipsareeitherunfathomably71

complexorunexpectedlysimplehasmajorimplicationsfortheusefulnessoftrait-based72

approachestoquantifyingandconservingbiodiversity16,28,29.73

4

Inahigh-dimensionalHutchinsoniannichespace,pinpointingthefunctionalrole74

ofaspecieswouldrequirenumerousaxesofphenotypicvariation30,potentially75

confoundingeffortstounderstandnichesbasedonstandardisedtraitdatasets12,15,17,18.76

Conversely,ifmostofthediversityinfunctionaltraitscanbecollapsedalongoneor77

twofundamentaldimensions,thenthismaynotprovidesufficienttractionfortraits78

tobeinformativeaboutmultipleecologicalfunctions,particularlyinmultitrophic79

systems19,28.Someecomorphologicalanalyseshavefoundevidencethatthe80

dimensionalityofanimalhypervolumesmayliesomewherebetweentheseextremes30-81

32,raisinghopethattraitcombinationscouldbepartitionedintoarelativelysimplistic82

nicheclassificationsystem¾analogoustotheperiodictableofelements27.Yet,previous83

studieshavefocusedonrestrictedspatialandtaxonomicscales,producing84

contradictoryresultsandnoclearconsensusaboutthestructureorgeneralityofform-85

functionrelationshipsinanimals31-36.86

Herewepresentthefirstcomprehensiveassessmentofphenotypictrait87

diversityforextantbirds(Aves),thelargestclassoftetrapodvertebrates.Forovera88

century,birdshaveplayedacentralroleinthedevelopmentofnicheconceptsand89

ecomorphology31,37-39,andnowprovidetherichesttemplateforexploringthefunction90

andevolutionofmorphologicaltraitsinthecontextofspecies-levelecological40and91

phylogeneticdatasets41.Wemeasuredeightphenotypictraitswithwell-established92

connectionstolocomotion,trophicecology,andtheassociatednichestructureof93

ecologicalcommunities31,32,39,42(ExtendedDataFig.1,seeMethods).Inparticular,the94

beakistheprimaryapparatususedbybirdstocaptureandprocessfood39,43,while95

morphologicaldifferencesinwings,tailsandlegsarerelatedtolocomotion,providing96

insightintothewaybirdsmovethroughtheirenvironmentandforageforresources31.97

Withtheadditionofbodymass,ourdatasetcontainsfullsetsofninetraitsfor9,96398

5

species,representing>99%ofextantbirddiversityandall233avianfamilies(Extended99

DataTable1),therebysummarizingwhole-organismtraitcombinationsin100

unprecedenteddetailforamajorradiationoforganismsdistributedworldwideacross101

marineandterrestrialbiospheres.Weusearangeofanalysestoexplorethestructureof102

thistraitdiversityanditsconnectiontoecologicalfunction.103

104

Themultipledimensionsofaviantraitspace105

Acrossbirds,bodymassvariesbyafactorof50,000(Fig.1a)andthepositionofspecies106

alongthissingleaxishasimportantassociationswithmetabolismandlifehistory44.To107

gobeyondthisbasicvariationamongorganisms,wecanvisualiseaviantraitdiversity108

byprojectingspeciesintoamultivariatespace(hereafter,morphospace)derivedfrom109

principalcomponent(PC)scores(seeMethods).Theseprojectionscanberestrictedto110

thebeak(Fig.1b,ExtendedDataTable2)orexpandedtoencompassalltraits(Fig.1c,111

ExtendedDataTable3),inbothcasesrevealingenormousvariationinsize(PC1)and112

shape(PC2-PC3).113

Unlikethebimodaldistributionofplantforms5,variationinbirdtraitsiscentred114

onasingledensecorearoundwhichspecieswithextrememorphologiesarescattered115

attheperipheryofmorphospace(Fig.1b-c,ExtendedDataFigs.3,4).Thestructureof116

thesethree-dimensionalprojectionshighlightsthediversityofwaysthatbirdshave117

exploreddifferenttraitcombinations.Forinstance,theseconddimensionoftotaltrait118

variation(PC2;6%traitvariance)describesthespectrumfromsmalltolargebeaks,119

whilethethirddimension(PC3;4%oftraitvariance)separatesspecieswithshorttails120

andpointedbeaks(e.g.kiwis)fromthosewithlongtailsandstubbybeaks(e.g.121

frogmouths)(ExtendedDataFig.3).Comparedtotheprimaryaxisofbodysize(PC1),122

alongwhichmost(83%)phenotypicvariationisaligned,theseandtheremaining123

6

dimensionsofavianmorphospaceconstituteonlyafractionoftotalphenotypic124

variation(17%).However,thekeyquestioniswhetherthepositionofspeciesinthis125

high-dimensionalmorphospaceprovidesdeeperinsightintotheirecologicalfunction.126

127

Themappingofformtofunction128

Tounderstandhowmorphologyrelatestoecologicalfunction,weclassifiedspeciesinto129

differenttypesofprimaryconsumers(aquaticandterrestrialherbivores,nectarivores,130

frugivores,granivores),secondaryandtertiaryconsumers(aquaticcarnivores,131

terrestrialinvertivores,terrestrialvertivores),andscavengers(ExtendedDataFig.5a,132

seeMethods).Mostavianspeciesarelargelyspecializedonasingletrophiclevel(n=133

8,343species)and,withinthis,asingletrophicniche(n=8,225species).Therest134

constituteomnivoresthatexploitmultipletrophiclevels(n=1,620species)orniches135

(eitherwithinoracrosslevels,n=1,738species)inrelativelyequalproportions(see136

Methods).Totestwhetherthelocationofspeciesinmorphospacepredictstheirtrophic137

niche,weusedaRandomForest(RF)model,atypeofmachinelearningalgorithmthat138

appliesrecursivepartitioning(i.e.decisiontrees)tosubdividemorphospaceintoaset139

ofnon-overlappingrectangularhypervolumeswithinwhichvariationinspeciesniches140

isminimized(seeMethods).Webeganbyassessingwhetherbodymassalonecan141

predictspecies’trophicniche,thenaddedadditionaltraitstobuildupaprogressively142

morecompletedescriptionofavianphenotype.143

Wefoundthatamodelusingonlybodymass(Fig.2a)achievedonlylimited144

accuracyinpredictingeithertrophicniches(29%)orbroadtrophiclevels(38%).Only145

nectarfeedingpollinators—manyofwhich,includinghummingbirds(Trochilidae),have146

evolvedminiaturizedformstofeedonflowers—werepredictedconsistentlybybody147

mass(Fig.2b).Thus,althoughbodysizeaccountsformostofthevarianceinour148

7

phenotypictraits(ExtendedDataTable3),itprovidesarelativelyweakexplanationof149

aviantrophicnichespaceatglobalscales.Thepredictabilityoftrophicnichesmorethan150

doubledwhenincludingbeaksizeandshape(Fig.2a,c)andincreasedfurtherto78%151

whenweusedanine-dimensionalmorphospacewithafullsetofbeakandbodytraits152

(Fig.2a,d).Moreover,whenweexcludedomnivores(seeMethods),therebyrestricting153

theanalysistospecieswiththemostspecializeddiets,thepredictabilityoftrophic154

nichesandtrophiclevelsexceeded80%(Fig.2a).Theseresultswererobusttothe155

methodusedtomatchtraitsandecology,withalternativeapproaches(e.g.discriminant156

analysis)indicatingasimilarriseinpredictiveaccuracyasmorphological157

dimensionalityincreases(ExtendedDataFig.6,seeMethods).158

Tovisualizethestrikingconnectionbetweenphenotypicformandtrophic159

function,wemappedthedensityofeachspecialisttrophicnicheontomorphospace(n=160

8,225).Evenwhenprojectedontoatwo-dimensionalplane,heredefinedbybeaksize161

andshape,itisclearthateachtrophiclevel,andindeedeachtrophicniche,occupiesa162

largelydistinctregionofmorphospace(Fig.3).Specialistinvertivores(n=4,788163

species)andfrugivores(n=1,030species)constitutethebulkofavianspeciesdiversity164

andarediffuselydistributedaroundthecentreofmorphospace(Fig.3f-g).Species165

targetingotherresourcetypespossessmoreextremecombinationsofbeaksizeand166

shape,formingtighterclustersaroundtheperiphery(Fig.3a-e,h-i,ExtendedDataFig.167

4).Theseclustershaveirregularshapesbutgenerallyoccupyasinglecontiguousregion168

ofmorphospace¾a‘phenotypicfingerprint’¾concentratedaroundauniquecentral169

peakofhighspeciesdensity.Thisrelativelysimpleone-to-onemappingofformto170

functionisnotanartefactofprojectingnichesontoasingletwo-dimensionalplane171

becauseeveninthefullnine-dimensionalmorphospaceeachtrophicnichecanbewell172

describedbyjustoneorafewrectangularhypervolumes(seeMethods).173

8

Theecologicalrelevanceoftraitvariationmayextendfarbeyondpredictionsof174

simplistictrophicnichesifmorphologycapturesadditionalaxesofecological175

divergence,includingsubtlegradationsofbehaviourandmicrohabitat.Theintrinsic176

subdivisionofbasictrophicnichesintonumerousvariantsisbestillustratedinbirdsby177

terrestrialinvertivoresthathaveevolvedaremarkablearrayofforagingtechniques,178

fromcatchinginsectsincontinuousflight(e.g.swallows)topluckingfromvegetation179

(e.g.antshrikes)orhoppingontheground(e.g.pittas)(Fig.4,ExtendedDataFig.5b).To180

assesshowmorphologyrelatestothesemorefine-scaleaspectsoftheniche,were-ran181

theRFmodelaftersubdividingtheninespecialisttrophicnichesinto30foragingniches182

(Fig.2e-g,ExtendedDataTable4,seeMethods).183

Asexpected,foragingnichesareevenlesspredictablethantrophicnichesor184

trophiclevelsonthebasisofbodysize(Fig.2a).However,predictabilityincreases185

substantiallywhenusingmultipletrait-dimensions,withthelocationinnine-186

dimensionalmorphospaceaccuratelypredictingnotonlythetypeofresources,butalso187

thespecificforagingmanoeuvreandsubstrateusedbyeachspecies(Fig.2a,e-g).This188

resultshowsthatmostmorphologicalvariationencompassedbyeachtrophicniche189

(Fig.3)isnotsimplyredundant35,36,withnumerousdifferentcombinationsoftraits190

performingsimilarecologicalroles8.Instead,thestrikingcorrespondencebetween191

avianformandfunctionprovidescontinuousmetricsforquantifyingmultitrophic192

nicheswithmuchgreaterdetailandprecisionthanaffordedbycoarseecological193

categories.194

195

Thedimensionalityoftrophicnichespace196

Toinvestigatetheminimumnumberofdimensionsrequiredtopredictavianniches,we197

appliedRFmodelstomorphospacesofvaryingdimensionality,rangingfromonetonine198

9

dimensions,exploringallpossiblecombinationsoftraitaxes(n=511combinations).199

Basedonestimatesofmodelpredictiveaccuracy,wethencalculatedthedimensionality200

(D)oftrophicnichesusingLevene’sindex(seeMethods).Accordingtothisindex,D=201

9ifalltraitdimensionscontributeequallytopredictingtrophicniches,withD202

decreasingtowards1aspredictiveaccuracyisdrivenbyprogressivelyfewertrait203

dimensions.Usingthisapproach,wecalculatedtheoveralldimensionalityoftrophic204

nichespace(DTotal)aswellasthemeandimensionalityacrossindividualtrophic205

niches(𝐷").206

Wefoundthatdimensionalityvariedfromthetwo-dimensionalnicheof207

nectarivorestothefour-dimensionalnicheoffrugivores,andthatnichesareon208

averagedefinedbyatleastthreetraitdimensions(𝐷"=3.5)(ExtendedDataFig.7a).209

Theidentityofthesedimensionsvariesacrossnichesreflectingadaptations210

associatedwithcontrastingmodesoflife(ExtendedDataFig.8).Takingalltrophic211

nichestogether,anintegratednichespaceisminimallydescribedbyafour-212

dimensionalmorphospace(DTotal=4.4).Decreasingdimensionalityfromfourtoone213

dimensionresultsinanalmostlineardeclineintheabilitytopredicttrophicniches,214

whileincreasingdimensionalityfromfourdimensionsupwardsonlyresultsin215

marginalimprovementinnichepredictability(ExtendedDataFig.7a).Similar216

estimatesoftrophicnichedimensionalitywereobtainedregardlessofthemethod217

usedtomatchtraitsandecology(ExtendedDataFig.10)andwhetherornotwe218

accountedforthephylogeneticnon-independenceofspecies(ExtendedDataFig.7b).219

Theseconsistentresultssuggestthattrophicnichespaceisinherently,yetnonetheless220

moderately,multidimensional.Ontheonehand,afour-dimensionalhypervolume221

challengestheview23,24thatanimaltrophicnichescanbecollapsedalonganaxisof222

bodysize,orindeedanysingletraitdimension.Ontheotherhand,thelevelof223

10

dimensionalityseemsremarkablylimitedgiventhescaleofecomorphological224

variationencompassedbytheentireavianradiation.225

Itseemsplausiblethatouruseofsimplelinearmeasurementshasledtoan226

underestimateofnichedimensionalityandthatadditionalormoresophisticatedbody227

shapemeasurements—suchasbeakcurvature43—mayrevealfurtheraxesofecological228

variation.However,theincrementinniche-relatedinformationislikelytobeminorat229

thescaleofouranalyses,particularlyassimulationssuggestthatourestimateof230

dimensionalityisrobusttotheadditionofnumerousalternativetraits(ExtendedData231

Fig.9,seeMethods).Limiteddimensionalitycouldalsoreflectthecoarsenessofour232

nicheclassification,sowere-ranRFmodelsbasedonnichessubdividedintomore233

precisecategoriesrelatingtoforagingbehavioursandsubstrates(ExtendeddataTable234

4).Wefoundthatmoretraitdimensionsareindeedrequiredtopredictthisfiner-235

grainedclassificationsystem(𝐷"=4.1,DTotal=5.6;ExtendedDataFig.7b),withthe236

traitaxesdefiningtrophicnichesforminganestedsubsetofthosedefiningforaging237

niches(ExtendedDataFig.8,seeMethods).However,theincreaseinniche238

dimensionalityisminor,suggestingahierarchicalstructuretonichespacewhereby239

thesamedimensionsarerepeatedlypartitionedacrossmultipleecologicalscales45.240

Whiletheseresultsprovidecompellingevidencethatmultitrophicnichespaceis241

predictablyorganizedalongalimitednumberoffundamentaltraitdimensions,theytell242

uslittleabouthowthiscorrespondencebetweenformandfunctionhasarisen.243

244

Theevolutionofform-functionrelationships245

Oneexplanationfortheapparentmatchingbetweenformandfunctionisthatclosely246

relatedspeciestendtooccupythesamenicheandhavesimilartraitssimplydueto247

sharedancestry46.Alternatively,eachtrophicnichemayhaveevolvedmultipletimes,248

11

withthestrongmatchbetweenformandfunctionarisingfromrepeatedphenotypic249

convergencetowardsthesameadaptiveoptima26,47.Theextenttowhichphylogenetic250

historyoradaptiveevolutionshapecurrentecologicaldiversityisunclear.Toaddress251

this,wecomparedthestrengthoftherelationshipobservedbetweenformand252

trophicfunctiontothatexpectedunderanevolutionarynullmodelinwhich253

similarityinspeciestraitsdependsonthetimeelapsedsincelineagesdivergedas254

wellasvariationintherateofstochastictraitevolution(seeMethods).Wefoundthat255

thismodelcanaccountforasubstantialfractionofthematchbetweenformand256

trophicniches(Expectedaccuracy=65%[95%CI:60-70%])butisinsufficientto257

explainthestrikingpredictabilityofavianecologicalfunctions(Observedaccuracy=258

85%,ExtendedDataFig.11).Althougheachtrophicnicheispopulatedbymultiple259

distantlyrelatedclades(ExtendedDataFig.12a),theselineagesarefarmoretightly260

packedinmorphospace(Fig.3)thanwouldbeexpectedbasedontheirevolutionary261

relatedness(ExtendedDataFig.12b).Thus,whileourresultshighlightthemajor262

imprintofphylogenetichistoryinthestructuringofaviantrophicdiversity,theyalso263

suggestthatthecorrespondencebetweenformandfunctionrequiresanadaptive264

explanation.265

Toexploretheseevolutionarypatternsinmoredetail,weidentified91pairsof266

avianfamilieswiththemostsimilartraitswithineachtrophicniche(seeMethods).We267

foundthatsome(10%)morphologicallymatchedfamiliesaresistercladeswherein268

phenotypicsimilaritycanbeexplainedbysharedancestraltraits(Fig.4a).However,269

mostpairingsrepresentmuchmoreancientdivergenceevents(mediandivergencetime270

=55[Interquartilerange:39-75]millionyears[Ma]versus28[Interquartilerange:21-271

51]Maforsisterclades),suggestingthattraitsimilarityhasresultedfromconvergent272

evolution(Fig.4a).273

12

Classifyingphenotypicconvergenceeventsbyspatialcontextrevealedthatsuch274

casestendtooccurinpairsofcladeswithnon-overlappinggeographicaldistributions275

(Fig.4b;seeMethods).Wealsoassessedwhethersimilarityinforagingnichespredicted276

evolutionaryconvergenceeventsinthetwomostheterogeneoustrophicgroups277

(aquaticpredatorsandterrestrialinvertivores).Inthesediverseniches,wefoundthat278

convergenceamongpairsoffamiliesusingthesameforagingtechniquesandsubstrates279

occurredfarmoreoftenthanpredictedbychance(Fig.4c).Akeyroleforboth280

geographicalisolationandecologicalsimilarityisconsistentwiththeviewthat281

macroevolutionaryconvergenceisdrivenbyadaptationtovacantecologicalniches47.282

Thus,theNeotropicalregionishometoarborealfrugivoroustoucans(Ramphastidae)283

andground-dwellinginvertivorousantpittas(Grallariidae),whicharereplacedinthe284

Palaeotropicsbyhornbills(Bucerotidae;Fig.5a)andpittas(Pittidae;Fig,5b),285

respectively.Aminorityoffamilies,suchasSwallows(Hirundinidae)andSwifts286

(Apodidae),appeartohaveconvergeddespitebroadspatialoverlap(Fig.5c),although287

itremainsplausiblethattheearlystagesofconvergenceoccurredingeographical288

isolation.289

Bytracingevolutionarytrajectoriesthroughmorphospace,wecanvisualisethe290

likelyhistoryofconvergenceeventsaccordingtoaglobalphylogenetictree41.These291

reconstructionsshowthat,withinmatchedfamilypairs,eachcladehasonaverage292

evolvedadistanceequivalenttoone-thirdthespanoftotalavianmorphospacebefore293

arrivingatitscurrentposition(Fig.5a-c,ExtendedDataFig.13).Insomecases294

(illustratedinFig.5a),familypairshavefollowedlargelyparalleltrajectories,whilein295

others(Fig.5b-c)convergencehasoccurredfromdifferentpointsinmorphospace,such296

thatthecurrentgapbetweenfamiliesissubstantiallynarrowerthanitwasinthepast.297

13

Acorollaryofwidespreadconvergentecologicaladaptationtogeographically298

segregatedvacantnichespaceisthatspeciesoccupyingagivennichewillcluster299

togetherinmorphospaceregardlessoftheirgeographicorigins.Torevealthisglobal300

mappingofformtofunction,wepartitionedtheavianhypervolumeintobiogeographic301

realms(seeMethods).Wefoundthateachtrophicnichehasthesamemorphological302

signatureworldwide,highlightingtherepeatabilityofconvergenceeventsacross303

multipleevolutionaryarenas(Fig.6).304

305

Conclusions306

Theconnectionbetweenavianmorphospaceandtrophicnichesprovidescompelling307

evidenceofwidespreaddeterministicconvergenceinadiversemultitrophic308

assemblage27.Ouranalysesrevealthatthepredictablepatternsofnichefillingobserved309

amongindividuallineages26,48,orinmorelocalizedsettings47,49,arepartofagrander310

evolutionarydynamicoperatingacrossentireclassesoforganismsataglobalscale.This311

pervasiveconvergentevolutionofmorphologicaltraitsoverridestheimprintof312

phylogenetichistoryinstructuringaviannichespace,reducingthepowerof313

phylogeneticbiodiversitymetricstopredictecologicalfunction50unlesscombinedwith314

otherinformationabouttraits.Wehavedemonstratedthataminimumoffour315

independentmorphologicaltraitaxesarerequiredtopredictvariationinaviantrophic316

niches,callingintoquestionthevalidityoftrait-basedmacroecologicalanalyses317

assessingfunctionaldiversityonthebasisoffewermorphologicaltraitdimensions(e.g.318

bodymass).Wealsoshowthatcontinuousmorphologicalvariablescanpredictmuch319

moresubtlefine-scalevariationindietaryandbehaviouralnichesthancanbeachieved320

usingstandardnichecategories(e.g.diet).321

14

Moregenerally,thesefindingshaverelevancetomultipleenvironmental322

researchprogrammesandpolicyframeworks,manyofwhichhavetakenonincreased323

urgencyinlightofrapiddeclinesinanimaldiversityandabundance3,4.Theaviantrait324

spacepresentedhere¾basedonthemostcompletesampleofmorphologicalvariation325

foranymajortaxon¾providesahighlyresolvedtemplatelinkingspeciestraitsto326

ecologicalfunction.Traitvariationwithinanyaviantrophicguild,orclade,orindeed327

anyhistorical,contemporaryorpredictedfuturebirdcommunity,canbemappedonto328

thistemplateandinterpretedinthecontextofregionalorglobalpatterns.Inpractical329

terms,thisresourcepavesthewaytoanewgenerationoffunctionalandbehavioural330

diversityindicatorsforuseinsettingandmeasuringprogresstowardsinternational331

conservationtargets,understandingfunctionaleffectsofextinction51,andevaluating332

howanimalcommunitiesassembleandrespondtochange16,29,52.333

334

15

335

336

337

Figure1.Theavianmorphospace.a,Distributionofavianbodymassesfromthe338

lightest(Mellisugahelenae,2g)totheheaviestspecies(Struthiocamelus,111kg).b,339

Variationinbeakshape,akeytraitrelatedtoresourceuse.Thefirstthreedimensionsof340

beakspacecapturevariationinbeaksize(PC1),relativebeaklength(PC2)andratioof341

beakdepthtowidth(PC3).c,Athree-dimensionalmorphospacecombiningdataon342

bodymass,beak,wing,tailandtarsus.Axislabelsindicatetheproportionofvariance343

explained.Thedensityofspeciesisprojectedontoeachtwo-dimensionalplane.Data344

areshownfor9,963species,representing>99%ofallbirds.345

346

16

347

348

Figure2.Trophicstructuringofmultidimensionalmorphospace.a,Meanaccuracy349

(%)ofaRandomForestmodelpredictingtrophiclevel,trophicnicheandforagingniche350

forallbirds(n=9,963species)onthebasisofbodysize(mass),sizeandbeaktraits,or351

thefullnine-dimensionalmorphospace.Stipplingindicatesimprovementinpredictive352

accuracyafteromittingomnivores(seeMethods).b-g,Confusionmatricesshow353

predictionsforeachtrophic(b-d)andforagingniche(e-g).Diagonalelementsofeach354

matrixindicatecorrectmatchesbetweenpredictedandobservedniches;off-diagonal355

elementsindicatemisclassification.Red=highlevelsofaccuracy(diagonal)or356

misclassification(off-diagonal).357

17

358

359

Figure3.Partitioningofavianmorphospaceacrosstrophiclevelsandniches.360

Heterotrophicconsumersshapethebiospherethroughnumerousfeedbacksonnutrient361

cyclingandproductivity2.Hereweillustratethecomplexityofavianecologicalfunction362

asamultitrophicpyramidbuiltonafoundationofautotrophicproducers(plants),363

whichareexploiteddirectlybyaquaticherbivores(a),terrestrialherbivores(b),364

nectarivores(c),frugivores(d),granivores(e),andindirectlybyaquaticcarnivores(f),365

terrestrialinvertivores(g),terrestrialvertivores(h),andscavengers(i).Withineach366

trophicniche,thefirsttwodimensionsofbeakmorphospace,capturingvariationin367

beaksize(PC1)andshape(PC2),areplottedagainsttotalbeakvariationof9,963368

species,representing>99%ofallbirds(lightgrey).Contoursindicatedensityofspecies;369

warmercoloursindicatinghigherdensity.Omnivoresarenotshown.370

371

372

18

373

374

Figure4.Scaleandcontextofmacroevolutionaryconvergenceinbirds.a,Lines375

connectphenotypicallymatchedfamilies(n=91pairs)spanningtheavianevolutionary376

tree.Exemplarshighlightedwithboldlines;sistercladeswithdashedlines.Treetipsare377

colouredaccordingtothepredominanttrophicniche(seeFig.3).Matchedfamilypairs378

arenotrandomlydistributedinrelationto(b)geographic(n=91pairs)and(c)379

foragingnicheoverlap(n=64pairs),withmostcaseshavingdisjunctgeographical380

distributionsandsimilarforagingniches.Redpointsandwhiskersshowtheexpectation381

(medianand95%confidenceinterval)underanullmodeloftraitevolution(see382

Methods).383

384

385

19

386

Figure5.Convergentevolutionarytrajectoriesthroughavianmorphospace.To387

illustratetheprobablehistoryofconvergenceevents,datafromancestraltrait388

reconstructionsareshownforthreeexemplarpairsofconvergentavianfamilies(a,top:389

Bucerotidae;bottomRamphastidae;b,top:Pittidae;bottom:Grallaridae;c,top:390

Apodidae;bottom:Hirundinidae).Uppermostpanelsshowthecumulativephenotypic391

distancetravelledbyeachfamilypairthroughmorphospace,andthecorresponding392

phenotypicgapbetweenfamilies.Phylomorphospaceplots(lowerpanels)showthe393

positionofancestralnodeswithineachclade(transitionfromyellowtoredindicates394

increasingtimebeforepresent,Ma)andpriortodivergenceofthefamilypair(grey).395

Sizeofdiscsaroundnodesindicatesuncertaintyintraitreconstruction.Nodesleading396

tootherlineagesarenotshown.Mapsshowglobaldistributionofeachfamilyinrelation397

tobiogeographicrealms(seeFig.6).398

399

400

20

401

402

403

404

Figure6.Theglobalmappingofformtofunctionacrossbirds.Clusteredpoints405

alongeachprincipalcoordinateaxis(PCoA)showtherelativemorphologicalsimilarity406

betweentrophicnichesfromdifferentecologicaltheatres(biogeographicrealms)based407

ontheaveragepairwisedistancebetweenspecies(n=9,963species)innine-408

dimensionalmorphospace(seeMethods).Individualtrophicnichesareomittedfrom409

realmsinwhichtheyareabsentorrare(<6species).410

411

412

413

21

Methods414

Morphologicaltraitdata415

Weassembledadatabaseofmorphometricmeasurementsfrom52,870livecaught416

individualsandpreservedmuseumskins,ofwhich2,288specimenswerefromexisting417

publisheddatabases53,54.Intotal,ourdatabaserepresents9,963ofthe9,993extant418

species(99.7%)recognizedintheglobalaviantaxonomyutilizedbyJetzetal.41.For419

eachindividual,wemeasuredeighttraits(generallytothenearest0.1mm):beaklength420

(fromtiptoskullalongtheculmen,andtothenares),beakwidthanddepthatthenares,421

tarsuslength,winglength,firstsecondarylength,andtaillength(seeExtendedDataFig.422

1andExtendedDataTable1forfurtherdescriptions).Weobtainedmeasurementsfrom423

atleastfouradultindividualsfromeachspecieswherepossible(twofromeachsex;424

meantotal=5.3individuals).Samplingwasconductedby93researchersacross65425

museumcollectionsworldwideusingastandardprotocol(seeSupplementary426

Information).Toassessrepeatability,wecompiledmeasurementsbydifferent427

researchersonthesamespecimens(n=2752individualsof2523species).Repeated428

measureswerehighlyconcordantasmeasureridentityaccountedforonly0.74%of429

totaltraitvarianceinthisdataset(ExtendedDataFig.2;seeSupplementarymaterialfor430

details).Weextractedestimatesofmeanspeciesbodymass(g)fromWilmanetal.40,431

largelybasedonthecompilationbyDunning55.Tomatchthespecieslevelresolutionof432

ourecologicalnichedata(see‘Ecologicalnichedata’fordetails),wecalculatedmean433

traitvaluesforeachspecies.Thisisjustifiablebecausemostofthevarianceintrait434

valuesoccursbetween(98.25%)ratherthanwithin(1.75%)species(ExtendedData435

Table1;seeSupplementarymaterialfordetails).Weperformedaprincipalcomponents436

(PC)analysisonthelog-transformedmeanspeciestraitvalues.Wecentredandrescaled437

eachphenotypictraittounitvariancebeforeperformingtwoseparatePCanalysesusing438

(1)thefourbeakmeasurements(beaklengthatnaresandculmen,beakwidthand439

depthatnares)and(2)allninephenotypictraits(ExtendedDataFig.3).Wevisualised440

thedistributionofspeciesthroughoutnine-dimensionalmorphospacebycalculatingthe441

densityofspecieswithinconcentricshellswithawidthofonemorphologicalunit442

(ExtendedDataFig.4).443

444

Ecologicalnichedata445

22

Foreachspecies,wescoredtheproportionofitsdietobtainedfromthreetrophiclevels446

(primaryconsumer;secondary/tertiaryconsumer;scavenger)andninetrophicniches447

(aquaticherbivore;terrestrialherbivore;nectarivore;granivore;frugivore;aquatic448

predator;invertivore;vertivore;scavenger)encompassingthemajorresourcetypes449

utilizedbybirds(ExtendedDataFig.5a).Ourscoringofspeciesdietsisprimarilybased450

ondatafromWilmanetal.40,extensivelyupdatedandre-organizedbasedonrecent451

literature.Forinstance,weclassifiedspecieseatinganykindofaquaticpreyasaquatic452

predators,whereasinWilmanetal.40speciesfeedingonaquaticandterrestrial453

invertebratesweregroupedtogether(e.g.flamingoswithwarblers).Basedonthese454

dietaryscoresweassignedspeciestothetrophiclevelfromwhichtheyobtainedatleast455

70%oftheirresources,withspeciesutilizingmultipletrophiclevelsinrelativelyequal456

proportionsclassifiedas‘omnivores’56.Similarly,weassignedspeciestothetrophic457

nichefromwhichtheyobtainedatleast60%oftheirresources(thislowerthreshold458

waschosenduetothelargernumberoftrophicnichecategories56).Speciesutilizing459

multipleniches,withinoracrosstrophiclevels,inrelativelyequalproportionswere460

classifiedas‘trophicgeneralists’.Althoughnotallomnivoresaretrophicgeneralists,461

andviceversa,thereisnonethelessbroadoverlap,andforsimplicityweusetheterm462

‘omnivore’whenreferringtobothcategoriestogether.463

FollowingthestandardizedprotocoloutlinedinWilmanetal.40,weusedthe464

extensiveliteratureonavianfeedingecologyandbehaviour(e.g.57)toquantifyforeach465

speciestherelativeuseof31differentforagingniches(scoredin10%intervals),466

describingdifferentcombinationsofdiet,foragingmanoeuvreandsubstrate(Extended467

DataFig.5b-c).Theseforagingnichesexpandonpreviousguildclassifications31,32,34,58-61468

toreflectthewidertaxonomicandecologicalscopeofouranalysis.Basedonthese469

scores,weassignedeachspeciesoccupyingaspecialisttrophicniche(i.e.excluding470

omnivores)totheforagingstrategybywhichitaccessedatleast60%ofitsdominant471

resourcetype.Twoforagingniches(groundandarborealgleaningvertivores)were472

eachrepresentedbyonlysixspeciesandsowereexcluded.Speciesutilisingmultiple473

foragingstrategiesinrelativelyequalproportionswereclassifiedas‘foraging474

generalists’,thusprovidingatotalof30foragingnichesusedinouranalysis.Further475

descriptionsofeachforagingniche,andtheassignmentofspeciestoeachcategory,are476

providedinExtendedDataTable4.477

478

23

Phylogeneticdata479

Toexploretheevolutionarybasisofform-functionrelationships,weusedthetime-480

calibratedmolecularphylogenyofJetzetal.41usingtheHackettetal.62backbone.To481

ensurereliableestimatesofevolutionaryparameters,werestrictedourphylogenetic482

analysestothen=6,666specieswithmorphologicaldataandforwhichbranchlengths483

wereestimatedonthebasisofgeneticdata.Becausetheevolutionarymodelsweuse484

arecomputationallyexpensivetofittotheentireavianphylogeny,webasedour485

analysisonthemaximumcladecredibility(MCC)treegeneratedfromacross1,000486

treessampledatrandomfromtheposteriordistributionusingTREEANNOTATOR487

(includedinBEASTv.1.6.1)63.488

489

Geographicdata490

RangemapsofspeciesbreedingdistributionswereobtainedfromBirdlifeInternational491

(http://www.birdlife.org/datazone/home).Owingtothetaxonomiclumpingor492

splittingofvariouslineages,therearedifferencesinthespeciesclassificationusedby493

IUCNandJetzetal.41.WealignedtheIUCNdatasetwiththatofJetzetal.41byediting494

speciesrangemapsinArcMapv10.364basedonpublishedinformationongeographical495

rangesofrelevanttaxa57.Speciesrangeswerethenextractedontoanequalareagrid496

(Behrmannprojection)witharesolutionof110km(≈1°attheequator).497

498

Quantifyingthematchbetweentraitsandniches499

Wetestedwhetherspeciesecologicalnichescanbepredictedonthebasisofspecies500

traitsusingRandomForest(RF)models65implementedusingtheR66package501

‘randomForest’67.Thismethodissuitableformatchingtraitstoecologybecauseit502

makesminimalassumptionsabouttheshapesofspeciesnichesandcanaccommodate503

interactionsacrossmultipletraitaxes.RFmodelsuseanensembleofdecisiontreesto504

partitionfeaturespace(i.e.morphospace)intoasetofnon-overlappingrectangular505

hypervolumeswithinwhichimpurityinecologicalnichesisminimised(Supplementary506

Fig.1).Eachinternalnodeinatreethuscorrespondstoasplitalongonerandomly507

selecteddimensionofmorphospace,witheachterminalnodecorrespondingtoaunique508

rectangularhypervolume.EachdecisiontreeintheRFprovidesa‘vote’ontheidentity509

ofaspecies’ecologicalnichebasedonitspositioninmorphospace.Weusedthe510

majorityvoteacrosstreestopredicttheecologicalnicheofspeciesandthencalculated511

24

theproportionofspeciescorrectlyassignedtoeachniche.Throughoutwereport512

overallmodelpredictiveperformanceasthemeanclassificationaccuracyacross513

ecologicalniches.Modelparameters,includingthenumberoftrees(n=500)andthe514

numberofrandomtraitstosampleateachnode(n=2),wereselectedbasedoninitial515

sensitivitytests.516

Becausespeciesarehighlyunevenlydistributedacrossecologicalniches,we517

randomlyup-sampledordown-sampledeachnichetoanequivalentnumberofspecies518

beforefittingthemodels(n=5000,2000and1000speciesfortrophiclevels,trophic519

nichesandforagingnichesrespectively).Toprovideunbiasedestimatesofpredictive520

performance,weused5-foldcrossvalidation.Werandomlysplitourdataintofiveequal521

sizedsets,maintainingthesamerelativefrequencyofeachecologicalnichewithineach522

set.Wetrainedamodelon80%ofthedata(‘trainingset’)andusedthistopredict523

speciesnichesintheremaining20%ofthedata(‘testset’),repeatingthisfivetimes,524

onceforeachpartition.Toaccountforstochasticityinmodelfitarisingtherandom525

partitioningofthedatasetduringcross-validation,wefittedelevenreplicatemodels526

andusedthemodalpredictionforeachspecies.Wecomparedthepredictive527

performanceofRFmodelsincluding:(1)onlybodymass,(2)bodymassandPCscores528

basedonallbeakmeasurements(length,widthanddepth),and(3)PCscoresbasedon529

allninephenotypictraits.530

531

Sensitivitytestsoftrait-nichematching532

WhiletheRFmodeldetectsastrongstatisticalmatchbetweentraitsandecological533

niches(Fig.2),itispossiblethatthisaccuracyisonlyachievedthroughahighlycomplex534

mappingofformtofunction.Forexample,eachnichecouldbecomprisedofmultiple,535

widelyscatteredclustersinmorphospacerepresentingaseriesofuniqueevolutionary536

radiations.Ifonememberofeachclusterisincludedinthetrainingdataset,wemay537

inferahighstatisticalpredictabilityoftrophicniches,despitethelinkbetween538

morphologyandecologybeingunpredictable(i.e.notrepeatable)inanevolutionary539

sense26.Weexaminedthisby(1)re-fittingaRFmodelconstrainingthenumberof540

terminalnodespermittedineachtree,and(2)repeatingouranalysisusingLinear541

(LDA)andMixtureDiscriminantAnalysis(MDA).DiscriminantAnalysisiswidelyused542

formatchingvariationinecologyandmorphologybasedonrestrictiveassumptions543

abouttheshapeofecologicalniches.UnlikeourRFmodel,LDAassumesthateachniche544

25

correspondstoasinglemultivariatenormallydistributedmorphologicalcluster,with545

equalvarianceacrossniches.MDArelaxestheseassumptionsbyallowingeachnicheto546

bemodelledbyaGaussiandistributionofsubclasses,withanequalcovariance547

structureacrosssubclasses.548

First,wefoundthatevenwhenRFtreesizeisstronglyconstrained(e.g.n=20549

terminalnodes),predictiveaccuracyremainshigh,indicatingthateachtrophicniche550

canbewelldescribedbyoneorafewrectangularhypervolumes(SupplementaryFig.551

2).Second,despitetheirrestrictiveassumptions,theLDAandMDApredictedspecialist552

trophicnicheswitha71%and80%accuracy,respectively(ExtendedDataFig.6).Thus,553

additionalanalysessupporthighpredictabilityofecologicalniches,indicatingthatthe554

strongmatchbetweentraitsandecologydoesnotarisefromover-fittingoftheRF555

modelandinsteadreflectsarelativelysimpleone-to-onemappingofmorphologyto556

ecologicalniches.557

Simulationsshowthat,dependingontheshapeandarrangementofecological558

nichesinmorphospace,MDAandLDAmayunderestimatethetruematchbetween559

traitsandecologicalniches(SupplementaryFig.3).Specifically,whennichesoccuras560

disjunctclustersinmorphospace,asobservedinsomesmallerspeciesradiations(e.g.561

Anolislizards47),thenLDAandMDAaccuratelypredictnicheidentity(Supplementary562

Fig.3a-b).However,whennicheshaveirregularshapesthatcloselyabutin563

morphospace,asinourempiricaldataset(Fig.3),speciesalongtheboundariesofeach564

nichearelikelytobemisclassifiedleadingtoalowerpredictiveaccuracy(LDA=84%;565

MDA=95%)(SupplementaryFig.3c-d).Incontrast,aRFmodelcanreadilyincorporate566

closenon-linearrelationships,providingamorerobustestimateofthematchbetween567

morphologyandecology.WethereforefocusouranalysisontheresultsfromtheRF568

model.569

570

Phylogeneticnullmodeloftrait-nicherelationships571

Thepredictablerelationshipbetweentraitsandecologicalnichesmaysimplyreflect572

sharedphylogeneticancestry.Weassessedthispossibilitybycomparingtheempirical573

estimatesofnichepredictabilitytothoseexpectedunderanevolutionarynullmodel.574

Keepingthetrophicnicheofeachspeciesfixed,wesimulatedmorphologicaltraitvalues575

accordingtoaBrownianmotionmodeloftraitevolutionappliedtotheavian576

phylogenetictree(seesection‘PhylogeneticmodelsofBrowniantraitevolution’for577

26

details)68.Thisnullmodelallowedustoquantifythesimilarityinspeciestraitsexpected578

duetophylogeneticrelatednessintheabsenceofecologicaladaptation.WefittedaRF579

modeltoeachof100replicatesimulatedtraitdistributionsinordertocalculatethe580

expectedpredictabilityofoverallnichespaceandeachindividualtrophicniche581

(ExtendedDataFig.11a).WerepeatedthisanalysisusingMDAandLDAasalternative582

methodsformatchingtraitstonichesandobtainedsimilarresults(ExtendedDataFig.583

11b-c).Asafurthertest,weassessedwhetherspeciessharingthesametrophicniche584

aremoredenselypackedintraitspacethanexpectedundertheevolutionarynullmodel585

bycomparingthemeanpairwiseEuclidiantraitdistancebetweenspecieswithineach586

trophicnichetothatexpectedacross1000simulationsofthenullmodel(ExtendedData587

Fig.12).588

589

PhylogeneticmodelsofBrowniantraitevolution590

WeparameterizedthenullmodelofBrowniantraitevolutionaccordingtotheempirical591

ratesoftraitevolutionestimatedacrosstheavianphylogenetictreeusingBAMM69,70.592

ThismodellingframeworkusesreversiblejumpMarkovchainMonteCarlo(MCMC)to593

fitasetofdistinctmacro-evolutionaryregimesacrossthephylogenetictree,the594

number,locationandparametersofwhichareestimatedfromthedata.Eachregime595

maybecharacterizedbyadifferentrateanddynamicoftraitevolution,includingeither596

increasingordecreasingratesthroughtime.Unlikemanystudies,wearenot597

specificallyinterestedintheseestimatedparametersperse,andinsteadsimplyuse598

themtoparameterizeournullmodelsimulationstoaccountforthepotentiallycomplex599

dynamicsofavianphenotypicevolution.600

WefittedthismodelseparatelytoeachofourninePCtraitaxestoestimate601

marginaldensitiesofphenotypicratesoneachbranchoftheavianphylogeny.Sensible602

priorsonrateparameterswereassignedusingthesettBAMMpriorsfunctions.Weran603

theMCMCsimulationfor600milliongenerations,samplingtheparametersevery604

80,000generations.Wediscardedthefirst10%ofsamplesasburn-inandassessed605

convergencebycalculatingtheeffectivesamplesize(ESS)ofthemodellog-likelihood606

andtheestimatednumberofmacro-evolutionaryregimeshifts.ESSforeachtraitwas607

consistentlyabovetherecommendedvalueof200.Weusedthemeanmarginalrate608

configurationacrossthephylogenytoparameterisethesimulations.609

610

27

Quantifyingthedimensionalityoftrophicnichespace611

Toquantifythedimensionalityoftrophicnichespace,wefittedRFmodelsto612

morphospacesconsistingofonetoninetraitdimensions,exploringallpossible613

combinationsofPCtraitaxes(n=511traitcombinationsforninetraits)(ExtendedData614

Fig.7a).Werepeatedthisanalysisusingphylogeneticallycorrectedprincipal615

componentscores,obtainingverysimilarresults(ExtendedDataFig.7b).Foreachlevel616

ofdimensionality,weidentifiedthecombinationoftraitaxesthatprovidedthehighest617

meannichepredictability(ExtendedDataFig.7).Inonedimension,PC1istheoptimal618

traitaxis.However,inhigherdimensionstheidentityoftheoptimaltraitaxesdoesnot619

simplycorrespondtotheirrelativecontributiontototalphenotypicvariance(Extended620

DataFig.7).Forinstance,inthreedimensions,trophicnichespaceisbestdescribedby621

PC1,PC3andPC4ratherthanPC2(ExtendedDataFig.8a).Ingeneral,traitaxes622

accountingforonlyaminorfractiontothetotalphenotypicvariancecontribute623

disproportionatelytodefiningecologicalnichespace.624

Usingthemaximumpredictiveaccuracyateachlevelofmorphospace625

dimensionality,wecalculatedthedimensionalityoftrophicnichespace(DTotal)626

accordingtoLevene’sindex71,627

628

𝐷#$%&' =1

∑𝑝,-629

630

wherepiistheproportionofthemaximumpredictiveaccuracy(acrossalltrait631

combinations)accountedforbydimensioni.Weappliedthesameapproachtocalculate632

thedimensionalityofeachindividualtrophicnicheandalsoforagingnichespace.633

Thecoretraitdimensionsidentifiedusingtheseestimatesofdimensionality634

(ExtendedDataFig.8c-d)variedacrossnichesinecologicallyinformativeways.For635

instance,itmakessensethatPC7formsoneofthreecoreaxesofthegranivore(seed-636

eating)nichebecauseitdescribestheratioofbeakdepthtowidth,withhighervalues637

correspondingtoastrongerbiteforceandabilitytocrushseeds39.Similarly,oneof638

threecoreaxesoftheaquaticpredatornicheisPC8,acorrelateofwingpointedness,639

withhighervaluescorrespondingtogreatersoaringabilityandflightefficiency72.640

641

Sensitivitytestsofnichedimensionality642

28

ToassesstherobustnessofourestimatesofnichedimensionalityD,weperformed643

multiplesensitivitytests.First,werepeatedouranalysisusingsyntheticmorphological644

axesgeneratedfromaphylogeneticPCAthataccountsforthenon-independenceof645

species73.Estimatesofnichedimensionality(DTotal=4.4)andpredictiveaccuracy(81%)646

obtainedusingthismethodwereverysimilartothosebasedonphylogenetically-647

uncorrectedPCaxes(ExtendedDataFig.7a-b).Second,ratherthanaRFmodelweused648

LDAandMDAtopredicttrophicniches.Estimatesoftrophicnichedimensionality649

(DTotal)varyfromDTotal=3.3forMDAtoDTotal=6forLDA,withaRFmodelprovidingan650

intermediateestimateofDTotal=4.4(ExtendedDataFig.10).Atthescaleofforaging651

niches,estimatesofdimensionalityweremoreconstrainedvaryingfromDTotal=5.6(RF652

andMDA)toDTotal=6(LDA)(ExtendedDataFig.10).Thus,allmodelsagreethat(1)653

trophicnichespaceisminimallydescribedbyatleastfourcompletetraitdimensions654

andthat(2)whennichesareresolvedatamuchfinerscale(i.e.foragingbehavioursand655

substrates),dimensionalityincreasesonlymarginally,withnichespacedescribedwith656

sixorfewertraitdimensions.GiventhehigherpredictiveaccuracyoftheRFmodeland657

theknownsensitivityofMDAandLDAtonicheshapeweconsidertheRFestimatesto658

bethemostrobust(see‘Sensitivitytestsoftrait-nichematching’,SupplementaryFig.3).659

Ourtraitsamplinggeneratesimperfectpredictionsoftrophicniches,suggesting660

thatadditionaltraitaxesmayberequiredtofullydescribenichespace,leadingto661

potentiallyhigherestimatesofdimensionality.Toexplorethispossibility,wesimulated662

howtotalnichedimensionality(DTotal)changeswhentheremainingvariationinniches663

leftunexplainedbyournine-dimensionalmorphospaceisequitablydividedamongan664

additionalnumberofhypotheticaltraitdimensions.Simulationsshowthatevenwith665

theadditionofmanyhypotheticaltraitaxes(e.g.n=100traitdimensions),ourestimate666

oftrophicnichedimensionalityincreasesonlymarginally(DTotal=6.1versus4.4,667

ExtendedDataFig.9a).DTotalisrobusttothisproliferationoftraitdimensionsbecause668

somuchvariationintrophicnichesisexplainedbyourexistingnine-dimensional669

morphospace(ExtendedDataFig.7a).Estimatesofforagingnichedimensionalityare670

potentiallymoresensitivetotheinclusionofadditionaltraitaxes,withoursimulations671

suggestinganupperboundofDTotal<11(ExtendedDataFig.9b).Wenote,however,672

thatthesesimulationsarelikelytooverestimatethepotentialincreasein673

dimensionalityfrommeasuringadditionaltraits.Forinstance,ifsomevariationin674

ecologyoccursindependentlyoftraitsoriftherearedifferencesintheamountof675

29

ecologicalvariationexplainedbyhypotheticaltraitdimensions,thisleadsto676

substantiallysmallerincreasesinDTotal(ExtendedDataFig.9b).Thus,oursimulations677

shouldbeviewedasprovidinganupperboundonnichedimensionality.678

679

Identifyingphenotypicallymatchedfamilies680

Toidentifycladeswithsimilarecologiesthataremostsimilarintheirfunctionaltraits,681

weassignedavianfamiliestooneofthreefunctionalgroups:(1)primaryconsumers,682

(2)terrestrialsecondary/tertiaryconsumers,and(3)aquaticsecondary/tertiary683

consumers.Werestrictedtheanalysistofamiliescontainingmorethan5specieswith684

bothgeneticandmorphologicaldata(n=132).Becauserelativelyfewlargefamilies685

wereaquaticprimaryconsumersorscavengers,thesegroupswerelumpedwith686

terrestrialprimaryconsumersandterrestrialsecondary/tertiaryconsumers,687

respectively.Withineachofthesefunctionalgroups,weidentifiedphenotypically688

matchedpairsoffamiliesbyfittingaRFmodelpredictingfamilyidentityonthebasisof689

morphologicaltraitsandthencalculatingthemeanspeciesproximityscoresforeach690

pairwisecombinationofclades.Thesescoresindicatetheproportionoftimesaspecies691

inacladeisassignedtothesamerectangularhypervolumeasaspeciesfromanother692

clade.Thismetricofproximityhasanadvantageoverstandarddistance-based693

measures(e.g.Euclidiandistances)becauseitdoesnotrequireanyassumptions694

regardingtherelativeimportanceofdifferenttraitaxesindiscriminatingbetween695

families.Instead,thisinformationislearntfromthedata.Intotal,weidentifiedn=91696

uniquefamilypairs(41reciprocallymatchedpairswereonlycountedonceinthe697

analysis)(Supplementarytable1).698

699

Reconstructionsofancestraltraits700

Tovisualisehowmatchedfamilypairshaveevolvedsimilartraitvalues,weusedthe701

branchandtraitspecificrateestimatesobtainedfromourBAMManalysisto702

reconstructtraitvaluesateachnodeinthephylogenetictreeaswellat1millionyear703

(myr)timeintervalsalongeachbranch74.Foreachtimestep,wequantifiedthemean704

positionofeachfamilyalongeachtraitaxis,andsummedtheEuclidiandistance705

betweenthesesuccessivetimepointstoestimatethetotaldistanceevolvedacross706

morphospacebyeachfamilysincetheydiverged75.Tovisualisetheevolutionary707

trajectoriesofselectedfamiliesthroughmorphospace(Fig.4b-d),wealsocalculatedthe708

30

traitgap(i.e.5%quantileofminimumpairwisedistances)betweeneachfamilyateach709

1myrtimeinterval75.710

Differentfamilypairsoccupydifferenttrophicandforagingnichesandthese711

nichesaredefinedbydifferentsetsoftraits(ExtendedDataFig.8).Whencalculating712

phenotypicdistancemetrics,wethereforeselectedthetwotraitaxesthatbestdescribe713

thenicheofeachfamilypair(Supplementarytable1).Thesetraitaxeswereidentified714

usingthemeanrankingofvariableimportancescoresacrossthetwofamiliesfromthe715

RFmodel.Tocomparedistancemetricsbasedondifferentcombinationsoftraitaxes,716

werescaledcurrentandancestralspeciestraitvaluestounitvariancepriorto717

calculatingphenotypicdistances.Weexpressthesedistancesasaproportionofthetotal718

spanofavianmorphospace,calculatedasthediameterofacirclecentredonthe719

centroidofmorphospaceandcontaining95%ofspecies(ExtendedDataFig.13).720

721

Theecologyandgeographicdistributionofphenotypicallymatchedclades722

Toexplorethegeographicandecologicalcontextofconvergence,wequantifiedspatial723

overlapandsimilarityinforagingbehaviouroffamilieswithinmatchedpairs724

(Supplementarytable1).Spatialoverlapbetweenfamilies(n=91pairs)wasquantified725

usingthesummedproportionofeachspeciesgeographicrangeoccurringineachof726

ninebiogeographicrealms76.Foragingnicheoverlapbetweenfamiliesofaquatic727

predatorsandinvertivores(n=64pairs)wasquantifiedusingthesummed728

proportionaluseofeachforagingniche.Spatialandforagingoverlapwerescoredusing729

Schoener’sDstatistic(heredenotedbythesymbolStodistinguishfromour730

Dimensionalitymetric),731

732

𝑆(𝑝0, 𝑝2) = 1 −127|𝑝0,, − 𝑝2,,|

,

733

734

wherepX,i(orpY,i)istheproportionaluseofregion/nicheibyspeciesX(orY).ValuesofS735

varyfrom0(nooverlap)to1(completeoverlap)andweremultipliedby100toreport736

overlapscoresforeachfamilypairfrom0to100%(in10%intervals).737

Iffamiliesarerestrictedtosinglebiogeographicrealmsorforagingniches,then738

manyfamilypairswouldbeexpectedtoshowlittlespatialorecologicaloverlapsimply739

bychance.Wethereforecomparedtheobservedfrequencyofspatialandforaging740

31

overlaptothatexpectedunder100replicatesimulationsofourphylogeneticnull741

model,inwhichmatchedfamilypairsaregeneratedthroughaprocessofcomplex742

Browniantraitevolution(seesection‘Phylogeneticnullmodelsoftrait-niche743

relationships’fordetails).744

Tovisualizetheeffectsofthesenon-randomevolutionarydynamics,we745

generatedamatrixofpairwisetraitdistancesbetweenthespeciesinthefullnine-746

dimensionalmorphospace.Wecalculatedthemeandistancebetweenspeciesineach747

combinationoftrophicnicheandbiogeographicrealmandusedNonmetric748

MultidimensionalScalingtotranslatethisdistancematrixontotwoorthogonalprincipal749

coordinateaxes.750

751

Dataavailability752

Allgeographicandphylogeneticdataarepubliclyavailable.Morphologicaldataand753

ecologicalnicheassignmentswillbemadeavailablewiththefinalacceptedversionof754

thearticle.755

Codeavailability756

Allcustomscriptswillbemadeavailablewiththefinalacceptedversionofthearticle.757

758

32

ExtendedDataTable1.Descriptionofspeciestraitsand%ofvarianceattributedto759 intraspecificdifferences(fromavariancecomponentsanalysis).760 761 Trait(mm) Description

%variancewithinspecies

Beaklength(tip-to-nares) Distancefromtheanterioredgeofthenostrilstothetip 1.39

Beaklength(culmen) Distancealongtheculmenfromthebaseofthebeaktothetip 1.71

Beakwidth Widthofbeakattheanterioredgeofthenostrils 2.49

Beakdepth Verticalheightofbeakattheanterioredgeofnostrils 1.62

Tarsuslength Distancefromthemiddleoftherearanklejoint,i.e.thenotchbetweenthetibiaandtarsus,totheendofthelastscaleoftheacrotarsium

1.71

Winglength(mm) Distancebetweenthecarpaljointtowingtip 0.72

Secondarylength(mm) Distancebetweenthecarpaljointtothetipofthefirstsecondaryfeather 1.33

Taillength(mm) Distancefromthetipofthelongestrectrixtothepointatwhichthetwocentralrectricesprotrudefromtheskin

2.99

Bodymass(g) Mass NA

Estimatesofintraspecificvariationarenotavailableforbodymass.762 763 764

33

ExtendedDataTable2.Traitloadingsforbeakspaceand%ofvarianceaccountedfor765 byeachprincipalcomponentaxis(n=9963species).766 767

Trait PC1 PC2 PC3 PC4Beaklength(culmen) 0.46 0.47 -0.01 -0.75

Beaklength(tip-to-nares) 0.52 0.55 0.02 0.66Beakwidth 0.47 -0.46 0.76 -0.01Beakdepth 0.55 -0.52 -0.65 0.02Variance% 84.2 13.0 1.7 1.1

Cumulativevariance 84.2 97.2 98.9 100 768

34

769 ExtendedDataTable3.Traitloadingsforphenotypespaceand%ofvariance770 accountedforbyeachprincipalcomponentaxis(n=9963species).771 772

PC1 PC2 PC3 PC4 PC5 PC6 PC7 PC8 PC9

Beaklength(culmen) 0.22 -0.42 0.30 -0.26 0.08 -0.10 0.07 0.01 0.77Beaklength(tip-to-nares) 0.23 -0.67 0.23 -0.26 0.05 0.08 -0.04 0.06 -0.60

Beakwidth 0.23 -0.26 -0.37 0.41 0.01 0.06 0.75 -0.11 0.01Beakdepth 0.28 -0.29 -0.39 0.47 0.13 -0.05 -0.65 -0.06 0.11Tarsuslength 0.23 0.26 0.13 -0.06 0.86 0.00 0.06 -0.34 -0.09

Winglength 0.26 0.10 -0.15 -0.28 -0.30 0.66 -0.10 -0.53 0.07Taillength 0.21 0.07 -0.58 -0.56 -0.06 -0.54 0.02 -0.07 -0.06

Secondarylength 0.25 0.14 -0.26 -0.18 0.22 0.44 0.02 0.76 0.07Bodymass 0.74 0.34 0.36 0.19 -0.31 -0.23 0.00 0.10 -0.10

Variance% 83 6.1 3.8 3.2 2.1 0.8 0.5 0.3 0.2

Cumulativevariance 83 89.2 93 96.2 98.3 99.1 99.6 99.9 100 773

35

ExtendedDataTable4.Descriptionofforagingnicheswithinspecialisttrophicniches.774 Scavenger(n=22)

Ground(SCG,n=22)–specieseatingcarrion(deadanimalorfishremains)ontheground(e.g.vultures).

Invertivore(n=4765)

Aerialscreen(IASC,n=278)–speciescapturingflyinginvertebratesonthewing(e.g.swallows,swifts).Oftendescribedas‘hawking’.IncontrasttoISA,IASCischaracterizedbycontinuousandextendedflightwithmultipleitemscapturedbeforelanding.Aerialsally(ISA,n=317)–speciescapturingflyinginvertebratesinmid-air,withtheattackstartingfromaperch(i.e.branch,rock,fencepost,telegraphwire,etc.)andthenreturningtoaperch(e.g.jacamars,kingbirds,etc).‘Hawking’willsometimesrefertothiscategory,butthekeydistinguishingfeatureisthatonlyasinglepreyitemiscapturedbeforereturningtoaperch.Sallytosubstrate(ISS,n=343)–speciescapturinginvertebrates(includingarachnids,worms,molluscs,etc.)attachedtothesubstrate(e.g.leaves,twigs,branches,rockfaces,etc)followinganaerialattackmanoeuvre(e.g.flight,pounce,jump,hover).Sallytoground(ISG,n=245)–speciescapturinginvertebratesonthegroundfollowinganaerialattackmanoeuvre(e.g.flying,gliding,droppingorpouncing)(e.g.chats,shrikes,kiskadeeetc).Theaerialmanoeuvremaybefollowedbybriefhoppingtowardprey(e.g.terns).Gleanarboreal(IGA,n=1792)–speciescapturinginvertebratesattachedtothesubstrate(e.g.leaves,twigs,branches,grass,bamboo,stems,hangingdead-leaves[notdeadleavesontheground]etc).Noaerialattackmanoeuvreisinvolved.Gleanbark(IGB,n=339)–speciescapturinginvertebratesattachedtoorconcealedwithinlargebranchesandtrunksoftrees(e.g.woodpeckers,treecreepers,woodcreepers,wallcreepers,nuthatches,sittelas,nuthatches,vangas,etc.,includinghoneyguides).ThisisdistinguishedfromIGAbyatleastonecriterion.First,thespeciesemploysspecializedmethodsformovingoversurfaceswhichareoften,butnotalwaysvertical,verticalandtoolargetobegrippedbytheclosedfoot(includingcreeping,climbingorscaling).Second,thespeciesextractspreyfromin/underthebarkusingspecializedmethods(includinghammering,probingorchiselling).Alsoincludesspeciescapturinginsectsfromrockandcliff-faces(thoughnotjustonboulders[seeIGG]),habituallyperchingonorclingingtolargemammalsandspeciesthatfeedonhoneyandbeeswax.Gleanground(IGG,n=1026)–speciescapturinginvertebratesontheground.IncontrasttoISG,thesearchandattackmanoeuvrestakeplaceontheground(e.g.thrushes).Thisincludesspeciesstandingonthegroundandgleaninginsectsfromvegetation(e.g.tinamousorlarks)butexcludesspeciesthatjumporsallyupwardstocapturepreyfromvegetation(ISS)ortheair(ISA).Thegroundisdryandthusexcludesaquatichabitats(includingbeaches,estuaries,wetlandsandmarshes[seeAQGR]).

Aquaticpredator(n=757)

Ground(AQGR,n=314)–speciescapturinginvertebratesorvertebrateswhilestandinginaquatichabitats(includingbeaches,estuaries,wetlandsandmarshes)(e.g.storks,herons,shorebirds).Preymaybecapturedonthegroundoron/underwater.Thiscategoryincludesspeciescapturingaquaticprey(e.g.fish)orterrestrialpreyinaquatichabitats(e.g.grasshopper).Perch(AQPE,n=44)–speciescapturinginvertebratesorvertebrateson/underwaterfollowingadirectattackflightfromaperch(e.g.kingfisher).Aerial(AQAE,n=87)–speciescapturinginvertebratesorvertebrateson/underwaterduringcontinuousflight(includingdipping,hovering,pattering,snatching).IncontrasttoAQPE,preyitemisidentifiedwhileflying(notfromperch).Thepredatorsbodymaypartiallysubmergebutdoesnotplungebeneaththesurface(AQPL).Includeskleptoparasiticspeciescapturingfishbychasingotherpiscivoresandforcingthemtoregurgitate(e.g.skuas,frigatebirds).Plunge(AQPL,n=59)–speciescapturinginvertebratesorvertebratesbyplungingunderwaterfollowingcontinuousflight.Thepredatorsbodysubmerges

36

entirelybeneaththesurface,withthepreycapturedeitherbythemomentumoftheplungeorfollowingpropelledswimming.Surface(AQSU,n=73)–speciescapturinginvertebratesorvertebrateson/underwaterwhilstswimmingonthewatersurface.IncontrasttoAQPEorAQAIthereisnodirectattackflight.Thespeciesmaydipunderthewaterbut,incontrasttoAQDI,contactwiththesurfaceismaintained.Dive(AQDI,n=134)–speciescapturinginvertebratesorvertebratesunderwaterbydivingfromthesurface(nottheair,seeAQPEandAQPL).

Vertivore(n=311)

Aerialscreening(VASC,n=20)–speciescapturesvertebratepreyduringflight.Bothpredatorandpreyareinflight(e.g.peregrine,hobby,falcon)Aerialtosubstrate(VAS,n=54)–speciescapturespreyonbranchesorthegroundbydivingfromtheair,usuallyaftercirclingorhoveringinflight.Includesquarteringflight(e.g.kestrels,kites,someowls).Sallytosubstrate(VSS,n=190)–speciescapturespreyonbranchesorthegroundbydivingfromaperch(e.g.manyowls,eagles).Gleanground(VGG,n=6)–speciescapturingpreyontheground,includingeggsingroundnests,whiletheythemselvesarealsowalkingorrunningontheground(e.g.secretarybird,seriemas,groundhornbills).Gleanarboreal(VGA,n=6)–speciescapturingpreyfromfoliage,branches,epiphytes,cavities,barkorotherarborealsubstratewhileperchedonthesubstrate.Thereisnoflightattackinvolved.Thisincludeseatingbirdchicksfromarborealnestsanddrinkingbloodwhileperchedonmammals(e.g.oxpeckers).

Nectarivore(n=507)

Aerial(NAE,n=318)–speciesfeedingonnectarorotherplantexudates(e.g.sap)whileinflight(e.g.hummingbirds).Glean(NGL,n=184)–speciesfeedingonnectarorotherplantexudates(e.g.sap)whileperched,includingnectarpredatorsthatpiercecorollas(e.g.sunbirds,flowerpiercers).Speciesfeedingonhoney(e.g.honeyguides)includedunderIGB.

Granivore(n=662)

Granivoreabove-ground(GRA,n=185)–speciesforagingonseeds,grainsandnutstakenfromvegetation(e.g.trees,grassstems)whileperched(e.g.seedeaters,finches).Granivoreground(GRG,n=408)–speciesforagingonfallenseeds,grainsandnutscollectedfromtheground.Includingbirdsthateatgrainsby,on,andunderwater(e.g.partridges,pheasants,finches).

Herbivoreterrestrial(n=93)

Above-ground(PA,n=13)–speciesforagingonleaves,buds,blossom,orothervegetation(exceptfruit,seedsandnectar).Thefoodistakenfromaboveground,generallywhilethespeciesisperchingonbranchesorotherstems.Generally,asmallpartofdiet,exceptforthehoatzin,plantcutters.Ground(PG,n=73)–speciesforagingongrass,leaves,buds,blossom,orothervegetation(notfruitorseeds)takenwhilethespeciesisontheground(e.g.geese).Thevegetationmayitselfbeofftheground.

Herbivoreaquatic(n=82)

Aquaticground(PAQGR,n=9)–speciesforagingonaquaticvegetation(includingseeds)eitherbeloworabovethewatersurface(algae,pondweed,watersidevegetation).Thespeciescollectsvegetationwhileunderwater,sittingonthewatersurfaceorwading.Aquaticsurface(PAQSU,n=47)–speciesforagingonaquaticvegetation(includingseeds)on/underwaterwhilstswimmingonthewatersurface.Thespeciesmaydipunderthewaterbut,incontrasttoPAQDI,contactwiththesurfaceismaintained.Aquaticdive(PAQDI,n=13)--speciesforagingonaquaticvegetation(includingseeds)underwaterbydivingfromthesurface.

Frugivore(n=1030)

Aerial(FAE,n=88)–speciesforagingonfruitsinflight,includingthosethathovertopluckfruitfrombushesandtrees(e.g.oilbird,somemanakins).Glean(FGL,n=894)–speciesforagingonfruitswhileperched(notinflight)abovegroundandpluckingfruitsfromvegetation(e.g.toucans,hornbills).Ground(FGR,n=20)–speciesforagingonfruitslyingontheground(e.g.trumpeters).

n=numberofspecieswithineachspecialisttrophicandforagingniche.Thenumberofspecieswithinatrophicnicheisgenerally775 greaterthanthesumoftheconstituentforagingnichesbecausesomespecies(n=642)usemultipleforagingmanoeuvresand776 substratesinrelativelyequalproportionsandareclassedasforaginggeneralists.777

37

778 779

780 ExtendedDataFigure1.Diagramoflinearmeasurementsofavianmorphology.a,781 Residentfrugivoroustropicalpasserine(fiery-cappedmanakin,Machaeropterus782 pyrocephalus)showingfourbeakmeasurements:(1)beaklengthmeasuredfromtipto783 skullalongtheculmen;(2)beaklengthmeasuredfromthetiptotheanterioredgeof784 thenares;(3)beakdepth;(4)beakwidth.b,Insectivorousmigratorytemperate-zone785 passerine(redwing,Turdusiliacus)showingfivebodymeasurements:(5)tarsuslength;786 (6)winglengthfromcarpaljointtowingtip;(7)secondarylengthfromcarpaljointto787 tipoftheoutermostsecondary;(8)Kipp'sdistance,calculatedaswinglengthminus788 first-secondarylength;(9)taillength.AnalysesexcludeKipp'sdistance,and789 thusinclude8traitsshownhere(plusbodymass,making9traitsintotal).Illustration790 byRichardJohnson.791 792 793

38

794 795 796 ExtendedDataFigure2.Repeatabilityofavianmorphologicaltrait797 measurements.Datapointsshowreplicatemeasurementstakenbydifferent798 researchersonthesamemuseumspecimensforasubsetofourglobaldataset(n=2752799 specimensofn=2523species).Pointsfallingalongthe1:1lineindicateaperfect800 correspondencebetweenmeasurers.The%oftotaltraitvariance(Var)occurring801 betweenmeasurerswithinspecimensisshown.Thenumberofspecimensvariesacross802 traitsandisindicatedinthetopleftofeachplot.803 804 805 806

39

807 808 809 ExtendedDataFigure3.Traitloadingsalongprincipalcomponent(PC)810 dimensionsbasedonall9phenotypictraits.ResultsareshownforPCaxes811 representingvariationinshape,andtherebyexcludingPC1whichrepresentsvariation812 inbodysize.Coloursindicatetheincreasingdensityofspecies(fromyellowtored)on813 each2-dimensionalplane(n=9,963species).SeeExtendedDataTable3fortrait814 loadings.815 816

40

817

818 ExtendedDataFigure4.Densityprofilesthroughmultidimensionalmorphospace.819 Therelativedensityofspecieswithdistancefromthecentroidofnine-dimensional820 morphospaceiscalculatedforconcentricshellsof1-unitdiameter.Densityisshownfor821 allspecies(n=9,963)andeachtrophicnicheseparately.822 823

824

41

825

826 827 828 ExtendedDataFigure5.Aviantrophicnichesandforagingniches.Silhouettes829 depictarchetypalspeciesbelongingto(a)ninespecialisttrophicniches,(b)seven830 majorforagingnichesusedbyterrestrialinvertivores,and(c)sixmajorforagingniches831 usedbyaquaticpredators.Foragingnichesfortheremainingsevenspecialisttrophic832 nichesarelessdiverseandarenotshown.SeeExtendedDataTable4forafulllistand833 descriptionoftrophicandforagingniches.834 835 836

837

838

42

839 840 841 ExtendedDataFigure6.Classificationaccuracy(%)usingalternative842 classificationalgorithms.Predictionsofspeciestrophiclevels,trophicnichesand843 foragingnichesusing(a)RandomForest,(b)MixtureDiscriminantAnalysis,and(c)844 LinearDiscriminantAnalysisforallbirds(n=9,963species)onthebasisofbodysize845 (mass),sizeandbeaktraits,orthefullnine-dimensionalmorphospace.Stippling846 indicatesimprovementinpredictiveaccuracyafteromittingomnivoresandforaging847 generalists(seeMethods).848 849

43

850

ExtendedDataFigure7.Intermediatedimensionalityofaviannichespace.Accuracy851 curves indicatethemaximumpredictabilityof(a-b)trophicand(c) foragingniches in852 morphospacesconsistingofdifferentnumbersoftraitdimensions.Resultsareshownfor853 a morphospace based on (a,c) standard and (b) phylogenetic principal components854 analysis.Accuracyisshownforindividualniches(coloursmatchingthosedepictedinFig.855 3)andtotalnichespace(black,DTotal).Pointsindicatethelevelofnichedimensionality856 (D) according to Levene’s index. Horizontal bar shows the mean (𝐷") and range in857 dimensionalityestimatesforeachniche.858 859

44

860

ExtendedDataFigure8.Thedimensionalityofaviantrophicandforagingniches.861 a-b,Theidentityofthetraitdimensionsbestdescribing(a)trophicand(b)foraging862 nichesfordifferentlevelsofdimensionality.c-d,estimatesofdimensionality(D)863 accordingtoLevene’sindexfor(c)trophicnichesand(d)foragingniches.Eachnicheis864 givenseparately,andwithallnichescombined(‘All’),alongwiththeidentityofthe865 principalcomponent(PC)dimensions(colouredsquares)thatbestpredicttheniche.866

867 868 869 870 871 872

45

873 874

875 876 ExtendedDataFigure9.Estimatedtotaldimensionality(DTotal)ofmorphospaceis877 robusttotheinclusionofadditionalhypotheticaltraitaxes.Resultsareshownfor878 (a)specialisttrophicnichesand(b)foragingniches.Inadditiontotheninemeasured879 traits,wesimulatedtheeffectsofincludingadditionalhypotheticaltraitaxes,uptoa880 totalof100axes.Weassumethateachadditionaltraitaxishasanequalcontributionin881 accountingforthevariationinnichescurrentlyunexplainedbyourempiricalnine-882 dimensionalmorphospace.Thisassumptionisconservative,becauseanyvariationin883 therelativecontributionoftheseadditionaltraitaxeswouldleadtosmallerincreasesin884 DTotalthanestimatedhere.Thus,oursimulationsarebestinterpretedasprovidingan885 upperboundonDTotalfrommeasuringadditionaltraitaxes.DTotalalsodependsonthe886 assumptionofwhethertheseadditionaltraitaxeswouldenableecologicalnichestobe887 predictedwithcompleteaccuracy(i.e.100%)orwhethersomevariationinnichesis888 inherentlyunpredictable.Assuminglowerlevelsofmaximumpredictiveaccuracy(e.g.889 85%)leadstolesssensitivityinestimatesofDTotaltovariationinthenumberoftrait890 axes.891 892

893

46

894 895 896 ExtendedDataFigure10.Estimatingdimensionalityofaviannichespaceusing897 alternativeclassificationalgorithmsRandomForest(a,d),MixtureDiscriminant898 Analysis(b,e)andLinearDiscriminantAnalysis(c,f).Accuracycurvesindicatethe899 cumulativemaximumpredictabilityof(a-c)trophicand(d-f)foragingnichesin900 morphospacesconsistingofdifferentnumbersoftraitdimensions.Pointsindicatethe901 dimensionalityofnichespace(DTotal)accordingtoLevene’sindex.902 903

47

904 905

906 907 ExtendedDataFigure11.Theexpectedmatchbetweenaviantraitsandtrophic908 nichesarisingfromsharedphylogenetichistory.Boxplotsshowthepredictive909 accuracyofthreealternativeclassificationalgorithms¾RandomForest(RF),Mixture910 DiscriminantAnalysis(MDA),andLinearDiscriminantAnalysis(LDA)¾usedto911 estimatetrophicnicheswiththefullnine-dimensionalmorphospace(points)forn=912 6,666specieswithbothmorphologicalandgeneticdata.Ineachcase,overall913 classificationaccuracyexceedsthatexpectedundertheevolutionarynullmodel(box914 andwhiskersshow50%interquartilerangeand95%confidenceinterval).Thenull915 modelincorporatesamulti-rateprocessofBrowniantraitevolutionwherebyratesof916 evolutioncanvarybothacrosslineagesandovertime. 917

48

918

919

920 921 922 ExtendedDataFigure12.Non-randomtraitpackingwithinaviantrophicniches.923 a,Phylogeneticdistributionofaviantrophicnichesacrossthecompleteaviantree(n=924 9,963species)withspecieslackinggeneticdatainsertedaccordingtotaxonomic925 constraints41.Tipsandinternalbranchesconnectedbyspeciessharingthesametrophic926 nichearehighlightedacrosstheavianevolutionarytree.b,Meanpairwisetraitdistance927 betweenspeciesineachtrophicniche(points)islessthanexpectedduetophylogenetic928 relatedness,basedonspecieswithbothmorphologicalandgeneticdata(n=6,666).Box929 andwhiskersshow50%interquartilerangeand95%confidenceintervalofmean930 pairwisetraitdistancesexpectedunderanevolutionarynullmodel.Thisnullmodel931 incorporatesamulti-rateprocessofBrowniantraitevolutionwherebyratesof932 evolutioncanvarybothacrosslineagesandovertime.933 934 935

49

936 937 ExtendedDataFigure13.Thedistanceacrossmorphospaceindependently938 evolvedbyphenotypicallymatchedpairsofavianfamilies.Wecalculatedthe939 averagephenotypicdistanceevolvedbyeachcladesincetheylastsharedacommon940 ancestorwiththeirphenotypicallymatchedfamily(n=91pairs).Distancesare941 expressedin(a)rawmorphologicalunits(traitaxesscaledtounitvariance)and(b)asa942 proportionofthetotalspanofmorphospace.Onaverage,eachcladewithinamatched943 familypairhasindependentlyevolvedadistanceequivalenttoone-thirdofthetotal944 spanofmorphospace.Forcomparison,the9matchedfamilypairsthatarealsosister945 clades(i.e.eachother’sclosestrelative)haveeachonaverageevolvedadistance946 equivalenttoonly~10%ofthetotalspanofmorphospace.Positionoflettersindicate947 theaveragedistanceevolvedbyfamilieswithinsisterclades:(A) Cettiidae-948 Phylloscopidae,(B) Cardinalidae-Thraupidae,(C)Emberizidae-Passerellidae,(D)949 Phalacrocoracidae-Sulidae,(E) Odontophoridae-Phasianidae,(F)Strigidae-Tytonidae,950 (G)Ardeidae-Threskiornithidae,(H) Cacatuidae-Psittacidae,(I)Accipitridae-951 Cathartidae.952 953

50

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Acknowledgements:1115

Wearegratefultonumerousfieldbiologistsandexplorerswhocollectedandprepared1116 thespecimensusedinthisstudy.WethanktheNaturalHistoryMuseum,Tring,UK,the1117 AmericanMuseumofNaturalHistory,USA,and63otherresearchcollectionsfor1118 providingaccesstospecimens.IllustrationsarereproducedwithpermissionofLynx1119 Edicions.FinancialsupportwasreceivedfromaRoyalSocietyUniversityResearch1120 Fellowship(ALP);aPhDstudentshipfundedbytheOxfordClarendonFundandtheUS-1121 UKFulbrightCommission(CS);andNaturalEnvironmentResearchCouncilgrants1122 NE/I028068/1andNE/P004512/1(JAT).Secondarysourcesoffundingarelistedin1123 SupplementaryInformation,alongwithacompletelistofindividualsandinstitutions1124 thatcontributeddirectlytodatacollection,logisticsandspecimenaccess.1125 1126 AuthorInformation1127 1128 Affiliations1129

CentreforBiodiversityandEnvironmentResearch,DepartmentofGenetics,Evolution1130 andEnvironment,UniversityCollegeLondon,GowerStreet,London,WC1E6BT,UK.1131 AlexPigot1132 DepartmentofZoology,UniversityofOxford,SouthParksRoad,Oxford,OX13PS,UK.1133 TomP.Bregman,AlexPigot,CatherineSheard,UriRoll,NathalieSeddon,JosephA.1134 Tobias,ChristopherH.Trisos1135 SchoolofBiology,UniversityofSt.Andrews,Fife,KY169TJ,UK.1136 CatherineSheard1137 CornellLabofOrnithology,159SapsuckerWoodsRd.,Ithaca,NY14850,USA.1138 EliotT.Miller1139 DepartmentofBiologicalSciences,UniversityofIdaho,Moscow,Idaho83844,USA.1140 EliotT.Miller1141 GlobalCanopyProgramme,3FrewinChambers,FrewinCourt,Oxford,OX13HZ,UK.1142 TomP.Bregman1143 BiodiversityResearchCentre,UniversityofBritishColumbia,6270UniversityBlvd.,1144 VancouverBC,V6T1Z4,Canada.1145 BenjaminG.Freeman1146 MitraniDepartmentofDesertEcology,JacobBalausteinInstitutesforDesertResearch,1147 Ben-GurionUniversityoftheNegev,MidreshetBen-Gurion8499000,Israel.1148 UriRoll1149 AfricanClimateandDevelopmentInitiative,UniversityofCapeTown,SouthAfrica.1150 ChristopherH.Trisos1151 DepartmentofLifeSciences,ImperialCollegeLondon,SilwoodPark,BuckhurstRoad,1152 AscotSL57PY,UK.1153 DanielSwindlehurst,JosephA.Tobias1154 DepartmentofEcology,EvolutionandEnvironmentalBiology,Columbia1155 University,1200AmsterdamAvenueMC5557,NewYork,NY10027,USA.1156 BrianC.Weeks1157

55

DepartmentofOrnithology,AmericanMuseumofNaturalHistory,79thStreetatCentral1158 ParkWest,NewYork,NY10024,USA.1159 BrianC.Weeks1160 1161 Contributions1162 ThisstudywasconceivedandcoordinatedbyJATandALP,anddesignedbyJAT,ALP,1163 CS,ETMandUR.Morphological,ecologicalandgeographicdatawerecompiledbyCS,1164 ALP,TB,BF,UR,CT,DS,BW,NSandJAT.AnalyseswereledbyALP,andallauthors1165 contributedtowritingthemanuscript.1166 1167 Competinginterests1168 Theauthorsdeclarenocompetingfinancialinterests.1169

Correspondence1170 CorrespondenceandrequestsforinformationshouldbeaddressedtoAlexPigot1171 (a.pigot@ucl.ac.uk)andJosephTobias(j.tobias@imperial.ac.uk).1172 1173 Reprintsandpermissions1174 Reprintsandpermissionsinformationisavailableatwww.nature.com/reprints.1175 1176