Introduction: Special issue on species interactions, ecological networks
ANGOR UNIVERSITY and community dynamics – Untangling the entangled bank using molecular techniques Roslin, Tomas; Traugott, Michael; Jonsson, Mattias; Stone, Graham N.; Creer, Simon; Symondson, William O.C. Molecular Ecology
DOI: 10.1111/mec.14974 PRIFYSGOL BANGOR / B 10.1111/mec.14974 Published: 01/01/2019
Peer reviewed version
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Dyfyniad o'r fersiwn a gyhoeddwyd / Citation for published version (APA): Roslin, T., Traugott, M., Jonsson, M., Stone, G. N., Creer, S., & Symondson, W. O. C. (2019). Introduction: Special issue on species interactions, ecological networks and community dynamics – Untangling the entangled bank using molecular techniques. Molecular Ecology, 28(2), 157-164. https://doi.org/10.1111/mec.14974, https://doi.org/10.1111/mec.14974
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27. Sep. 2021 This article isprotected rights by All copyright. reserved. 10.1111/mec.14974doi: lead todifferences version between this andthe ofPleasec Version Record. been and throughtypesetting, proofreadingwhich may thecopyediting, process, pagination This article undergone has for and buthas accepted been not review publication fullpeer Corresponding* author, email CF10 3AX, UK 5 University, Gwynedd, LL57 2UW, UK 4 EH93FL, UK 3 25, 6020 Innsbruck,Austria 2 Uppsala;Sweden 1 Roslin, T. the Special issue on species interactions,ecological networksand community dynamics: untangling Introduction Articletype : Special Issue GRAHAMPROF. N STONE(Orcid ID : 0000 PROF. TOMASROSLIN (Orcid : ID 0000
AcceptedCardiff School of Biosciences, Cardiff University, Sir Mar Molecular Ecology and FisheriesGenetics Laboratory, School of Natural Sciences, Bangor Institute Evolutionaryof Biology, U Mountain AgricultureResearch Unit, Institute of Ecology, University of Innsbruck,Technikerstr Department of Ecology, Article entangled SPECIAL ISSUE: SPECIES INTERACTIONS, ECOLOGICAL NETWORKS AND COMMUNITYDYNAMICS 1,* , Traugott, , Traugott, M.
bank using molecular techniques
2
, Jonsson, M. P.O. Box7044;P.O. Swedish University of Agricultural Sciences; SE
niversity Edinburgh,of CharlotteAuerbach Road, Edinburgh 1 - , Stone, G.N. 0002 - 0002 - 2957 - 2737
- 4791)
3
, Creer, S , Creer, - 696X)
tin Evans Building, Museum Avenue, Cardiff
4
. & Symondson, W.O.C. ite this articleite this as 5
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This article isprotected rights by All copyright. reserved. – the attendeesat a meeting wider community ecological interactions (i.e. species feeding eachon other), (Symondson previous Special Issue, T reason,is it timeto providesequel a to the seminal Special Issue on the lastThe few years have seenrevolution a inboth sampling and sequencing tech 2016) and howthey changein time and space (‘community dynamics’). uniqueoffer opportunities describingfor both elementsof community structure (Roslin taxonomic units) andlinks the by their interactions (Gravel ecological networks key elements of determinethe distribution and abundance of organisms’ (Krebs may seethe origins of c the complexity linksbetweenof them Inlast the paragraph of us. dependent upon each other inso c earth, and to reflect that theseelaborately constructed forms,so differentfrom each and other, singing on thebushes, with variousinsects flitting about,and with worms crawling through thedamp “ It is interesting to contemplatea tangled bank,clothed with many plants of rophic
regardless of the tools applied. Hence, the current volumeis the result synergisticof
Accepted Article”
collaboration between this audienceand e (Darwin I nteractions ,
& 1859) Harwood 2014). Yet, w this concept of
and ecosystem relevant
’ (
Hagenal. et 2012) edited the current one ommunity ecology on on Molecular Detection Trophicof Interactions, but the Origin Species of five five c years agoSymondson by and Harwood (2014). ommunity structure, we may conveniently describecommunities as omplexa manner, have all been produced bylaws acting around , and theforces creating this “tan herethe previous compilation focused a on specifictype of continues . In such networks,nodes the are formedspecies by (or other
focus. Thus,Special the Issue of 2014 preparedwas by –
todaydefined as , Darwin (1859) cologists a with wider interestin ecological networks the quest of ‘Unpicking theTangled Bank’
herewe have endeavoured to provide et al., et
marvels atdiversity the lifeof forms,
‘the study ofinteractions the that ,
2009). To captureand quantify the
2018). Modern molecula
gled bank” ‘M olecular the currentissuereflects
many kinds,with birds Building the on nologies. For this . In this text,we D etection of back &
r methods Majaneva - to - back
a ,
This article isprotected rights by All copyright. reserved. multiple types of linksamong multiple kingdoms taxaof (Clare canapplied be to describe full communitiesrather than theirparts simultaneously such elements. Asanarguablythought fruitfully applied to many types nodesof and links, and the many types of networksformed from dissection stimulusas a and catalystfor ecologists contemplatinguse the of molecular tools for community theof state theof art inthis rapidlydeveloping field. In particular, wehope that this issuewill serve and terrestrial), hopewe to provide, in a single issue of includingBy blend a papersof studying multiple types interactions, of andtaxa realms (both aquatic approaches. ecology wider range futureof studies. system studied, i.e. particularlyfor by molecular means. identifying the limits and caveats ass technical solutions for dealing large with and diversecommunities, as wellreviews as and summaries networks and theirdynamics.papers The included also comprise studies offering suite studiesof applying molecular tools to resolving questions were added later Many of the papers included inthis volume were presented at oneof these meetings, butothers Networks 3 events organized at the Swedish University of Agricultural Sciences, Uppsala, in September 2017: t rd
Accepted Article Symposium on Molecular Detection of Trophic Interactions and the 3 . In otherwords, , enhanced furthervia networking
(seealso
important and impactful
to increasethe scopeand breadth of the where Bohan When these worksdelive
the methodological improvements et al. et
including
In all ,
2017 other papersother ociated with quantifying community and interaction structure research ) . Individual papersreveal how molecular toolsbeing are - provoking perspective,they also show molecular techniques
studies, where r significantecological findings obtained by molecular .
with a method
included inSpecial the Issue, Molecular Ecology the S results pecial o
achieved logical focus, wehave carefully looked et al. focused I clearly ssue ,
XXXX are likely to . on rd The resultingThe issue offers a
, a compr transcend ), thus opening new vistas Symposium on Ecological ecological interaction thefocus broad ranging – ehensiveglimpse be useful for a
the specific i.e. to resolve is on theon he This article isprotected rights by All copyright. reserved. organisms likely causing nobut harm feeding upon bird resources suchasblood or skin fungi, microbesand detritus intheplumage. In fact,the authors find no evidence featherof mites feather mitesshare a commensalistic evidencefrom both lightmicroscopy and metabarcoding, authors these showthat vane can even force usto re As aspecificinsight, the study XXXX). fungus XXXX; ( Doña, Serrano, Mironov, Montesinos interactions (Gariepy interactions ( Sint,Kaufmann, Mayer, & Traugott including predator Tiusanen canapplied be to resolving mutualistic interactions suchpollen as transport(Bell In terms theof types interactionsof addressed, this Special Issue showshow molecular tec cornucopiaA of interaction typesand taxa data sources ( ‘networkson networks’.of AcceptedBhattacharyya, Dawson, Hipperson, Ishtiaq& Article Sepp –
fungivoreinteractions (Koskinen et al., et al., Siegenthaler, Wangensteen, Benvenuto, Campos, & Mariani Pocock, Evans, & Memmott;
XXXX)
XXXX) – prey interactions (Deagle
et et al., and seed dispersal (Gonzalez - evaluate previous concepts of the type specificof interactions. Using plant
Out of XXXX; – by Doña et al. (XXXX) reveals howthe application of molecular tools prey interactions (
Kitson necessity, such i ,
XXXX
- – offering Navarro mutualisticassociation with their bird hosts,by feeding on et al., et etal., ; Walters;
2012, Wirta
et al.,
clear benefitsto their hosts. , & Jovani&
XXXX XXXX XXXX Littlefair, Zander,de SenaCosta, Clare& . Conseq nitiatives sofar havehad to be builtfrom multiple et et al., - XXXX; Varo Varo ), ) and ), host plant , et al., et XXXX
XXXX), etal., multifaceted Eitzinger uently, – - symbiont interactions (Doña etal., fungus interactions (
), 2015)
plant XXXX) predator
the mitesare recast as . et al., et
– , antagonisticinteractions herbivoreinteractions
interactions (Clare
– , XXXX;
prey XXXX),
- and Mata Mata Sch et al., et host - detritus röter et al., et –
parasitoid XXXX; - dwelling commensal
, et al.,
et al., et XXXX hniques
XXXX;
XXXX;
),
This article isprotected rights by All copyright. reserved. techniques emph passing through anarea, butstill be main agents seedof dispersal for particular plants. This concentrated to particular species atparticular points in time. Migratory bird species may only be Arroyo, Jordano& the role individualof seed dispersers in seed dispersal networks. Asa incase point, Montesinos levels of specialization in ecological interaction networks(Doña findingsThe regarding particular interactions rangefrom insightinto emergent features such as work. specificcommunities (Wirta majority of nu reveal new aspects communityof organization. Importantly, thisnot is a question adding of fine andsmall similar to describeby any other means ( XXXX; hosts Zander,deSena Costa, Clare& pinpointassociations between resolving “hidden” and hard Majaneva 2016), the Emphasizing the message from previous reviews (from Symondson Harwood& 2014 to Roslin and
Accepted Articleanceto main color, but repaintingof the whole picture. Since these types interactionsof form the asizesneed the for resolving variation innetworkstructure through time (Gariepy
Kitson
all areideally placed - Navarro etal.,
interactions theon globe, they will profoundlyaffect our et al.,
(XXXX XXXX;
XXXX; & Jovani& featured ) Koskinen areable to show Kitson - et al., et to
( , González case studies , XXXX - organisms
observeecological interactions (Wirta XXXX;
et et al., 2014),but of howcommunities ingeneral are et al., et ; Koskinen Sint, Kaufmann, Mayer, Traugott& -
Varo, Arroyo,Varo, Jordano & XXXX
XXX which liquefy their prey (Eitzinger
al how much an of ecological function (seed dispersal) is so X ), lack), all diagnosticcharacters larvae as (Gariepy ), hunt), nightat (Mata et et al.,
reveal howjust powermuch molecular tools add by Walters
XXXX; et al., et
Sepp
et al., et
, XXXX; et al.,
XXXX et al., et
XXXX; et al., et
). XXXX; Jones and Hallin understanding
,
XXXX XXXX
et al.,et Doña, Serra 2014). By allowing usto Clare ,
), hidewithin their for which molecular ) areor simply too assembled
XXXX; et al., González
of notof only
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Littlefair XXXX
and - ), they Varo, ) to) et al., ,
This article isprotected rights by All copyright. reserved. Acceptedspecificinteractions occur. papers interactions vary ( However, recent research forces usto re If two speciesinteract at onepointin space, thenthey are expected to do so whereverthey meet. Much of community Environmental imprints on ecological interactions based identification approaches. Resolving such taxonomic diversity across largescales be would next to impossible with morphology richness, avens). Targeting multiple sit identifying which arthropods visit the flowers severalof arctic identifyto what the shrimp feeds on, Tiusanen etal. Where Article fish communitiesfor biomonitoring purposes ‘environmental DNA’ Mariani extremeflexibility and fish. Substantial variation indiet both at regional and scales local add to the impression of generalist,feeding hundredson of taxa, with its overall diet dominated by crustaceans, polychaetes shrimp, Campos, & Mariani within larger communities and interaction networks. Insimilar a vein, molecular dietanalysis shedsnew light theon trophic position of i in thisissue Siegenthaler, Wangensteen, Benvenuto, Campos, & Mariani , Crangon crangon
XXXX in this case of ) , but also reveal the potential for bottom Poisot,Stouffer, Gravel& in this common species (
showhow molecular tools can reveal where,and under what circumstances, (XXXX ecology to datehas assumed that eachparticular interactiona fixed is feature: ( Bohmann literallythousands of art , inEuropean six estuaries. Th )
use metabarcodinguse of gutcontents to establish the dietof brown the
es aroundes the A
et al.,
2014 visit Siegenthaler,Wangensteen, Benvenuto, Campos, & , ;
2015; rctic, they too find anastonishing taxonomic rangeand Deiner . this assumption, and add empha
hropod species sharing thiscommon
Pellissier
etal., (XXXX) Siegenthaler, Wangensteen, Benvenuto, e speciese turns out to be an extreme - dwelling 2017 apply them to theopposite task of etal.,
Dryas ; Creer marine
2017
(XXXX)
species (all known as mountain
etal., ;
Gravel generaliststo harvest the use molecular techniques
2016 sis just on why et al., ) ndividual species signal broaderof
floral 2018). Two resource.
- This article isprotected rights by All copyright. reserved. Accepted inoccur space.Here, Jones and Hallin oxidizenitrite to nitrate, littleis known about howthese functionally archaealor communitiesfirst oxidize ammonia to nitrite,and bacterial communitiesthen further ecological funct ecological interaction networks, Jones and Hallin In furtherevidence ofpower the of molecular data inresolving spatiotemporal patterning in ecological interaction networks. between theseis challenging may reflectdifferences inavailable prey rather than in realized interactions, butdistinguishi studies haveshown elevation elevationof theon prey community carnivorousof Among predators different a of type, Articleavailable, rather than directly modifying whatpreferred is (Eitzinger and regardless theirof environment. However, the environment gradient,these authors demonstratethat spiderstend prey to theon same taxa Arctic. By describing thecommunitie Eitzingeret al. preferencesduring foraging ( the pika varies with elevation and with habitatstructure, lik Royle's pika ( Bhattacharyya, Dawson, Hipperson, Ishtiaq&
so theso effect of current Arctic changewill likely act indirectly, by changing what a re alsore characterized by moredifferent contents theof plants’ pitchers. Since other Ochotona roylei (XXXX) ion . Where nitrification pathways tend to consist separateof steps inwhich bacterial differences infree focus a on very different predator, thewolf spider
), a lagomorph), endemicto the Himalayas. They showhow the diet of Bhattacharyya, Dawson, Hipperson, & Ishtiaq –
attesting to the need to resolvenodes and links
s bothof availableand consumed prey along anelevational Littlefair, Zander,Sena de (XXXX) - living arthropod communities with elevation, thispattern
are able discernto distinct modules co of (XXXX) (XXXX) Sarracenia analyze the plantcontents of pellets fecal of target ely reflecting constraintsand
hasstrong a impact availableon prey,
pitcherplants. Sites moredifferent in communities of microbes linked by Costa, Clare& et al., et - coupled organism groups co Pardosa glacialis
, XXXX
XXXX
(XXXX)
separately in ). – ).
when available
prey speciesare f i - nd animprint occurring
inHigh the ng - –
This article isprotected rights by All copyright. reserved. perspective, communities still end up very similar interms theirof trophic composition, with highly largerscales, env spatial scales. Atlocal scales, forest management and tree selection haveclearer a impact, butat temperate forest sites, and findthe that relative impactof differentstructuring forces differs across Schröter et al. blown in from other, more advanced communities. young food chains of glacier forelandsbased are on on similar age,they areable to reconstruct howfood web is exposed in front retreatingof glaciers. By revealing feeds who on what inreplicate valleys of Sint,Kaufmann, Mayer, & Traugott precipitation and temperature(Tiusanen history on current p expansion routesacross theArctic from shared refugia. This revealsstrong a imprint geologicalof faunistic similarity across Arcticsites, they showthat plants and arthropods have u likely diversity with thosepreviously observed in plants, andmatching by pairwisepatterns floristicof and al. currentThe issue showshow molecular data can reveal processes shaping communities. Tiusanen et Molecular insights into community assembly a con networks: speciesgroups canlinked be by group one preparing the metabolic substrate for another, microbial ecology dominated by different lineagesand groups of microbes associated with the two steps
Accepted Article(XXXX) study cept perhaps familiar less to those us of working with macroscopic taxa. (XXXX) flower ironmental cuesand hostresource traitsare the most prevalentforces. Fromnet a example reveals newdimensions in the structuring of ecological interaction atterns community of structure, compare the composition rootof - visiting communit
(XXXX) are associated with different edaphic factors. Thus, this iesacross the Arctic.By comparing patterns phylogenetic of et al., et describehow arthropod communities assemble once soil
XXXX :
modules
beyond imprints of current climate such as )
- s are formed.s are Their findings suggest thatthe - site processessite rather than resourceson associated
which inoccur disparate areas
fungi across more thanhundred a
sed similar
are This article isprotected rights by All copyright. reserved. Accepted traits, painting a dynamic picture of patterns identify showing signs of seemed hosts to be there as more than beto moreassociated between them than overall, theass than previously assumed. Yet, mites showed predictable fidelity interms of hostbody size,and consisting of Building extensive on examiningevidence the for host shiftsamong symbiontspresumed beto Doña, Serrano, Mironov, Montesinos Articlelocally more abun facultative partnerselection fungiAM with which they partner. Grasseshost more plant host species structured with Seppal. et range of climaticand edaphic conditions fungi. Community assembly processesthus seem to secure functional resilience underthe current similar proportions of symbiotrophic, ectomycorrhizal, saprotrophic, en
(XXXX) mycorrhizal feather ociation network proved modular (i.e., inhomogeneous a dry plot of calcareous grassland both reproduction and somelevel of population di
host than do dantplant species. , abundance examine how
mitespecies and hostbird species, finding much more variation inlinkstructure - DNA metabarcoding switchinga frequent as phenomenon shaped by ecological filters associations appear less forbs. More and functional group on root the -
- colonizing fungi Navarro Jovani& (XXXX) takean over, just accidental coevolution .
, these a
with the other plantspecies characterized by obligaterather than specializ uthors between forming a fung some groupssome birdof and mite species tended tourists, with the ed in terms of their fungal partners,as do
study group al partnersand richness and community composition
symbionts and their hosts rbuscular mycorrhiza associations between nodes s) . Mitesdetected unexpected on . They find fferentiation mite popula evolutionaryperspective by dotrophic,and pathotrophic highlyhost appear a significant . Overall, these tions hosts rare on more generalistmore in
- (AM) (AM) specific
. such as
imprint a re . host of of of of This article isprotected rights by All copyright. reserved. Accepted authorsThese demonstratethat metabarcodinglargely is robustfor determining pollen quantitative evidence p Bell et al. accurateless with a higher diversity food of intaxa the samples. moreaccurate view popuof approach is often advancedmore as conservative thanlatter, the the latter may actuallyprovide a the use relativeof number sequenceof reads per sample. They stressthat while theformer approach focusingof on thefrequency of occurrence di of Drawing bothon critical literature analysis and simulations, Deagleet al. Deagle et al. this from multiple perspectives. sequencedata as a still Contributions to the currentSpecial Issueidentify Article (e.g. diet.predator Thepapers pointed several out biases,and approaches also that can adjustfor them abundance communityof members pondering whethersequence read numbers may or maynot beused SpecialThe Issue compiled Whatcommunity features can and cannotbe quantifiedsequence by data placement, and in without the current molecular Overall, theseinsights regarding communities how form inspaceand timewould beunachievable Greenstone, Payton, Weber, Simmon& (XXXX) (XXXX) turn to mixes pollenof grains, taking an empirical approach to examining the ternal relatedness return to the issue at the heart of the previous Special Issue dietaryon samples. - rovidedcontrolled by blends of pollen vibrantand partly contentious field of research. Individual papersapproach five five lation workflows years ago (Symondson and Harwood 2014) featured several papers
- level dietunder many circumstances. Both approaches ; .
in thatcase focusing communities on preyof insamples of , offering clueson both trophic position, taxonomic s ,
2014). the issue of
fferent food taxa across samples
from disparatetaxonomic sources what wecan and cannotquantify from
to quantify the relative (XXXX)
comparethe become versus .
This article isprotected rights by All copyright. reserved. Accepted Senar,Piñol, Symondson& sources of bias n the Special Issue four years (cf. ago Bell more optimistic picture of theinformation valueincluded inread the countsthan contributions to a data as still Together, these paperspoint toissue the of what can variance platform type, the number specieof a for substantial fraction of studies, no quantitativerelationship detected, is and neither the extent to which Lamb al.et ( hope Articlevary with the primerpair usedand on the character template mismatches as a metric key interest.of They showquantitativity that canexpected be to with quantitative. They stress that “universal primers” will always comewith moreor fewer mismatches berephrased as numbersfail to do so some experimental studies tend to report quantitativemetabarcoding results whereassimilar Senar,Piñol, Symondson& grains. presence/absence,but discourage the use of sequencereads to inferrelative abundance pollenof community heterogeneous sources o , that
between studies quantification can oftentimesbe reasonably good. XXXX - vibrant andcontentious partly field research.of
to be quantified, they find proportions of when, and under what circumstances eed to be considered and the methods usedshould be justified (Deagle ) present an empirical meta . H encethe question of .
,
(XXXX) (XXXX)
XXXX; f
sequence target Lamb approach related questions s used in a trial, orsource the of DNA templateDNA, and thus focus on the numberof primer et al., et et al., et reads a weak quantitativerelationship (slope=0.52 ±0.34) whether -
analysis studiesof published to date
XXXX XXXX correspond ) ). Strongerbiases at particular steps sampleof istics of the mixture analyzed, . Yet, each
, ,technique the can beexpected to be meta
versus cannot
barcoding is quantitative should actually to the original proportion
When combined in silico stress that for abalanced view, all ,
be inferred from sequence , pointing tofact the that can accountfor the large , they drawperhaps a
. but
Focusing theon s speciesof in , inspiring et al., sequencing –
. Yet, XXXX;
This article isprotected rights by All copyright. reserved. and better skin health, this research may lead usto novel insights intodeterminants the of inskin the microbiome theof killer whale. By describing microbial communities associated with poor species. At the community level, Hooper However, applications clearly do not stop identifying at enemies the economicallyof important individual level. the oakprocessionary moth T. established in the theof oakprocessionary moth ( Kitson et al. rangeis now an activefield research. of species still try to exploi native confamilial species. Someparasitoid species unable to develop on the eggs of the invasive high parasitism rates, butthe invasive species was significantly less likely beto parasitized than between nativebugs, their parasitoids and the newcomer. Molecular Targeting the invasive pentatomid bug realized enemies invasiveof species. control agents againstinvasive species. Two Using molecular tools to spotinteractions between species allowsus to identify potential biological Applied perspectives relativesequence contents (Bell preparation, PCR and DNA sequencing still will blur correlations between
Acceptedprocessionea Article (XXXX)
as UK Carcelia iliaca use nested . Overall, they are able to identify the main parasitoid theof larvallate stages of
t themt under field conditions. How this translates into parasitism inthe new and - tagging DNA metabarcoding for exploringparasitoid the community Thaumet
et al., et the tagset needed to process massiveecological samplesat the –
at theat same timecreating the fortools describing alllifest
XXXX; Halyomorpha halys
opoea processionea et al.et
papers usemolecular tools to scout potential out and Lamb (XXXX) et et al., aim toaim identifyquantitatively dominant species
XXXX , Gariepy et al. ), an), invasivespecies recently
) .
analysis of egg massesreveal original sample and (XXXX) lookfor links
skin ages of This article isprotected rights by All copyright. reserved. spatial scales overof 1,000 in km more than 100 temperate fores associated mycobiomes encompassingtotal a of 5,955 different Operational Taxonomic Units across ind Tiusanen et al. from bird species, whereas metabarcoding to determinegut contents from 1,833 individual mites of 18 spe In evidence theseof claims, Doña etal. allowing thesimultaneous characterization of massive numbers of to the potential for handling and individual tagging (Kitson precision in terms of information value generatedsingle from a sequencing run, resulting inever development insight powercurrently is increasing a at massivespeed, and the involved. Here, arewe not (only) referringhigh to the numbers sequenceof reads. Sequencing and links. Perhaps the moststriking feature ofpapers the in thisSpecial Issue are the largenumbers Community ecologists tend deal to with Vistas level. more originally taken for population genomic studies. This analyzing health among both larger and smaller species. All this achievethey by
Acceptedividuals, detecting 1,360 barcoding BINs in the process. Schröter al.et Article
25,540 individual mites(representing 64 species)from 1,130 birds (representing 71 species). biodiversity
shotgun sequencedata from (XXXX) information from extant samples of rareor elusivespecies, even the at community
tabulatingnodes the present in thesample. Yet, equally importantly, referwe ;
Doña, Serrano, sampled 31,345 arthropods, of which they individually sequenced 13,681 quitethe contrary (e.g. Loman Mironov, Montesinos hard (XXXX) –
or or leastat cravefor - to - usehigh come by samples shows the extremepotential for extracting et al., et - throughputsequencing (HTS)and DNA re isre as yet attenuation no of that
et al., et - 2012). Thisdevelopment increasesthe Navarro
–
massivedata
XXXX of t plots.t Clare et al. ecologi
skin biopsies of killer whales,
& Jovani& ) of largenumbers samples,of intensively and carefully (XXXX) cal - improved resolution and
samples featuring (XXXX cies inhabiting 18 deal with root ) (XXXX)
reportfindings
and taxa
both node both tabulate . - re
- s This article isprotected rights by All copyright. reserved. Acceptedlinksby molecular data, may wenot base our full description communitiesof and interaction challengesahead. What Clareet al. time. molecular analyses of both communities how are currently structured and how they change over stages of work(Kitson involved to morphologically (Kitson offers uniqueopportunities for constructing large, highlyresolved speciesinteraction networks means (Roslin and Majaneva 2016). In particular, DNA metabarcoding based on nested tagging species content a of community, directdata linkon occurre links,molecular data offer unrivalled benefits. Where arethere multiple modes of describing the components communitiesof community ecologists: the scope for generating more relevantdata in higherquantities theon ke ArticleTogether, thepapers contributed to this Special Issue thusto point a fascinating development for all heraldnew a era incommunity ecology, all taxonomic impediment by automatic species delimitation and recognition. among samples when taken sequentially rather than simultaneously. They also circumvent the bypassing phenological changeand othertypes shiftof in time co available now for community description, wecan sample very many sitesin a shorttime, thus What thesefigures attest toa is quantum leap in community description. By building the on tools mutualistic, and predatory interactions interactions3304 between 762 nodes of trophic8
et al.,
(XXXX)
XXXX point to particularlyfascinating perspectives ). Generatio et al., this paper -
identifiable stages bypassesboth important biases and highlylaborious , i.e. XXXX; n dataof on species associations without rearing theorganisms
the
Koskinen propose
nodesand the . And thegoes list on. owing usto finally s
et et al., is this:
functions XXXX
G linksof i ven thatven we can now delimit nodes both and ). These methods open new horizons nce arence often unachievable by other , thus encompassing which they are built
view
–
and to particularly strong mplicating commensurability
the bigger Overall ecological . In terms theof parasitic, , these numbers picture.
for
y This article isprotected rights by All copyright. reserved. networks. Buta contribute littleinsight into the “true” composition of the network howor species present inthe community. Undersuch a scenario, molecular description communitiesof will nodes varying with thesimilarity threshold that usewe to define them unknown life molecularly To compareto role the and to, this namestays constant across community networks. Only the lattercriterion will allowus Hebert bynamed Latin binomials or some otherdesignations (cf. taxonomy need to maintainlink a between papers (most in this Specialis Issue) perhaps theeasiest way to go. For each of these network/community structure(Tiusanen DNA) o blowflies indifferentecosystems”). Mapping nodes(be they defined by any criteria, morphology or within webs, and for comparingroles the suchof similar blocks among regions (e.g. role “the of how they live their lives. Itis alsobasis the Thus, naming a node connects itto everything thatwe know about what they are,what they do and connect lists of their memberswith what these membersare: their life cycles, size,and other traits. but also one fraughtwith difficulties. Akey step inmaking sense of communities is n missing, approaches networks suchon data, thus curtailing the reliance on traditional approaches
Acceptedstress Article , nto someconcept of phylogeny will significantly increase understandingour of 2013 such
this point, we may considercontrasting scenarios. Asa perhaps worst
( Hebert, Cywinska,& Ball - proveimmed based food web reconstruction, we may end up dealing unnamed with MOTUs of - ) is ) secondaryof importance, as long as weknow which particular nodethe name refers c as many tropical ycleand unknown affinity to each other, with the numbersand connections between s a best casescena of the same node across networks (Cirtwill et al.,2018). iate, deep insightsinto systems and/ molecular rio, molecular characterization of communities us allow to rapidly or or marine ,
2003; et al., et
for groupinginto nodes andmore less similar blocks Hebert barcoding, MOTUsand someaspects traditionalof environments
XXXX
& Gregory ), and mapping them onto known taxonomy
where traditional data are limited or Hebert et al., 2016; ? ? This isa most stimulating perspective,
2005 ) .
Whetherthese taxa arethen and
itrelates to other
with thecontext of other
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ightnot such endeavors, we This article isprotected rights by All copyright. reserved. AcceptedBhattacharyya, S., Dawson, A., Hipperson, D. H., Ishtiaq& F.( Bell, K. Burgess,L, K. S.,Botsch, J. C.,Dobbs, E. K., Read, D., T. Brosi, & B.J. ( References compiling thisSpecial Issue for M like to warmly thankKaren Chambers and Armando Moreno Geraldesfor their extensivehelp with 06872)and theSwedish University Agriculturalof Sciences, Centrefor Biological Control. Wewould Interactions were ArticleThe Acknowledgements to the ecological co contemporary molecular approachesfor determi beaiming is well evident. hopeWe that this Special Issue arewe at present onscale the between theseext structure to e.g. variation in theirfunctioning, then that isindeedfantastic a development. Where describeus to the structureof, say,hundred a replicate communitiesand to relate variation intheir taxonomic position and whatis known about the sameor related species. Ifsuch approaches al generate 3 rd
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- This article isprotected rights by All copyright. reserved. AcceptedDoña, J., Proctor, H., Serrano, D., Deiner, Bik, K., H. M., M Deagle, B.E., Thomas, A.C, McInnes, J. C., Clarke, J.,L. Vesterinen, E.J., Clare, E. L., Darwin, C. ( S.,Creer, Deiner,K., Frey, S., Porazinska, TaD., ArticleClare,E. Fazekas,L., A., Ivanova, N., Floyd,Hebert, R., Adams,P., A., Cirtwill, A. R., Dalla Riva, G. V.,Gaiarsa, M. Bimler,P., D.,M. Cagua, E.F., Coux, C., & Dehling, M. D. Bohmann, Evans, K., A., Gilbert, T. M. Carvalho,P., G Bohan, A.,D. Vacher, C., Tamaddoni 1859). On the Origin Species of by Means Natural of Selection, or thePreservation of (XXXX). (XXXX). and plantcommunities. E.(2017).M. Environmental DNA metabarcoding: transforming howwe survey animal https://doi.org/10.1111/mec.14734 sequencereads to dietary data? P. Favoured Racesin theStruggle for JohnLife. Murray, London. Ecology and Evolution ecologist's field guideto sequence‐based identification biodiversity. of issue: xxx approaches to integrating geneticdata into ecological networks. (2018). Evolution Environmental DNA for wildlifebiology and biodiversity monitoring. ecological networks. (2017). Next ( XXX X). Counting with DNA in metabarcoding studies: Howshould we convert A r Feather mitesplay a role incleaning hostfeathers: Newinsights from DNA , – 29 eview speciesof role conceptsin food webs. Food Webs, 16, e00093. xxx ächler, E.,Seymour, M., Lacoursière‐Roussel, A.,Altermatt, F.,.. - (6), 358 generation global biomonit .
– Johnson Trendsin Ecology & Evolution 367. , 7 - Nezhad, A., Raybould, A., Dumbrell, A.J., & Woodward, G. Molecular Ecology , 1008
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This article isprotected rights by All copyright. reserved. AcceptedHagen, M., Kissling, W. D., Rasmussen, C., De Aguiar, A.,M. Brown, E., L. Carstensen, D. ... W., ,& Greenstone, H., M. Payton, M.E., Weber, D. C., & Simmons, A. (2014)M. detectabilityThe half Gravel González ArticleGariepy, T. D., Bruin, A.,Konopka,J., Eitzinger,B., Abrego, N., Gravel, Huotari,D., T., Vesterinen, E.J., & Roslin, T. Doña, J., Serrano, Mironov,D., S.,Montesinos ,
D - . Varo, J. P., Arroyo, J. &M., Jordano, ( P. , Baiser Guimaraes Jr, R.(2012).P. use how to it. arthropod predator 10.1111/ecog.04006 biogeography of ecological interaction networks. Bringing and Elton Grinnell together: a quantitative https://doi.org/10.1111/mec.14850 dispersal effectiveness. https://doi.org/10.1111/mec.14868 exoticpentatomids and their parasitoids. modified DNAbarcode approach to definetrophic interactions between nativeand https://doi.org/10.1111/ analysis changesin arthropod predator mites eco host https://doi.org/10.1111/mec.14581 metabarcoding and microscopy. - ,
symbiontassociations with DNA metabarcoding revealsdynamic a bird B . , Dunne — - variable environment, stable diet. evolutionary scenario. Molecular Ecology ,
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prey research Kopelke Molecular Ecology Scott mec.14872 Biodiversity, speciesinteractions and ecological networks in a - , J. Dupree,C., Fraser,H., Bon, M – prey interactions through DNA‐based gutcontent - , Molecular Ecology P., - Molecular Ecology 23 Navarro,Jovani, A.,& (XXXX) R. : what: it is, why we need it, howto measureit, and
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– ( XXX xxx . - . lifein X). A X). This article isprotected rights by All copyright. reserved. AcceptedKoskinen Kitson, J. J. N., Hahn, C.,S Jones ArticleHooper,Brealey, R., J. C., van derValk, T., Hebert, P. Ratnasingham,D., S.,Zakharov, E. V.,Telfer, A. C.,Levesque Hebert, P. Cywinska,D., A., Ball, & (2003). S.L. Hebert, P. &D., Gregory, T.(2005). R. promiseThe of DNA barcoding for taxonomy. ,
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J . . , , Roslin & https://doi.org/10.1111/mec.14810 novel molecular method. the mushroom soup: Host specificity of fungus‐associated communitiesrevisited a with https://doi.org/10.1111/mec.14518 metabarcoding. parasitoid interactions inan invasiveLepidopteran using tagging nested DNA https://doi.org/10.1111/mec.14893 microbial guilds. https://doi.org/10.1111/mec.14860 diatom composition theof killerwhale skin. K. ( 20150333. Philosophical Jannetta, (2016).P. Counting s animal Proceedings ofthe Royal Society ofLondon B: Biological Sciences Biology https://doi.org/10.1016/B978 fragmented world. In Hallin XXX ,
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This article isprotected rights by All copyright. reserved. AcceptedPoisot, Stouffer, T., D. B.,& Gravel, D. Pocock, M. M. J., Senar,Piñol, A.,M. Pellissier. L V.Mata, A.,Rebelo, H., Amorim, F., McCracken, G. F., Jarman, S., Be & ArticleLoman, N. J., Misra, R. V., Dallman Littlefair, J. Zander, E., A., deSena Costa, C., Clare,& E. ( L. Lamb, Hunt P., Krebs, C. (2009). Ecology: theexperimental analysis of distribution and abundance. 6th ed. Pearson, ., Albouy, C.,Bascompte, J., through space and time. network of ecological networks. quantitative. characteristics of the species mixture determinewhen DNA metabarcoding can be Reviews Comparing species interaction networksalong environmental gradients. analysis. enough? Effects of technical and biological replication on metabarcoding dietary Nature Biotechnology (2012). Ecology changesin the contents of carnivorous plants along an elevation gradient. xxx meta San Francisco. er, E.,er, Pinnegar, J., Creer, S., Davies,R., Taylor,& M. ( J. O.,Evans, M. D. D., & Memmott, J. (2012). .
- analysis: Howquantitative is metabarcoding? Performancecomparison benchtopof high , ,
this issue: xxx Molecular Ecology DOI: 10.1111/brv.12366 & Symondson, W. O Molecular Ecology
, T. J., Constantinidou, C.,Gharbia, S. E., Wain, J., & Pallen, JM. , – 30 xxx Oikos (5),434. (2015). Beyond species: why ecological interactions va Farwig, N. . ,
https://doi.org/10.1111/mec.14832 this issue: xxx . , C. (XXXX). 124 ,
Science this issue: xxx
, 243 , Graham, C., Loreau, ...M., , – The choiceThe universalof primers and the 335 251. – xxx (6071), 973 XXX
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X). X). DNA m - . throughputsequencing platforms. Molecular Ecology https://doi.org/10.1111/mec.1477 XXX – ja, (XXXX).P. 977. X). Structured review and etabarcoding reveals
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This article isprotected rights by All copyright. reserved. AcceptedWalter Tiusanen, M., Huotari, Hebert, T., Symondson, O. W. C.,& Harwood, J. (2014).D. Introduction. Special issue on molecular detection of Sint Siegenthaler, A., Wangensteen, S., O. Benvenuto C., ArticleSepp, S. Schröter, K., Wemheuer, B., Pena,Schoning, R., I., Roslin, T., & Ratnasingham, S., Hebert, & P. N.D. (2013). A DNA ,
D . s, T. Lamboley,L., L. LópezM., , Kaufmann - K., Davison, J., Jairus, Vasar, T.,
Majaneva, S.(2016). useThe of DNA barcodesin food web construction Frischer, E.( M. phylogeneticdiversity and ecological functioning. Flower doi: 10.1111/mec.12831 trophic interactions: Unpickingtangled the bank. this issue: xxx Arthropod predator food webs in pioneersites glacierof forelands. opportunist. metabarcoding unveils multi specificity. association patterns inaplant Molecular Ecology Assembly processes trophicof guilds intheroot mycobiome temperateof forests. aquatic ecologistsunite! http://doi.org/10.1371/journal.pone.0066213 Index
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M., Moora, M., Zobel, M. - PLoS ONE scale trophic variation in a widespread coastal , - this issue: xxx mycorrhizal fungal network reveal host , ,
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Molecular Ecology Molecular Ecology . - – & M Santiago, Á.E., Gibson, M.,D. & Schall, https://doi.org/10.1111/mec.14886 , &
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This article isprotected rights by All copyright. reserved. Accepted Article Wirta, H. K., Vesterinen, E. J., Hambäck, A., P. Weingartner, E., Ras Wirta, H. K., Hebert, D.,P. Kaartinen, R., Prosser,S. W., Várkonyi, G., Roslin,& T. (2014). 5 Roslin, T. (2015). Exposing thestructure anArcticof food web. Proceedings ofthe National Academyof Scienc Complementary molecular information changes perceptionour food of web structure. Ecology gelatinous marine zooplankter, (17), 3842 ,
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