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dc.contributor.authorHartop, Emily
dc.contributor.authorLee, Leshon
dc.contributor.authorSrivathsan, Amrita
dc.contributor.authorJones, Mirkka
dc.contributor.authorPeña-Aguilera, Pablo
dc.contributor.authorOvaskainen, Otso
dc.contributor.authorRoslin, Tomas
dc.contributor.authorMeier, Rudolf
dc.date.accessioned2024-10-23T10:27:48Z
dc.date.available2024-10-23T10:27:48Z
dc.date.issued2024
dc.identifier.citationHartop, E., Lee, L., Srivathsan, A., Jones, M., Peña-Aguilera, P., Ovaskainen, O., Roslin, T., & Meier, R. (2024). Resolving biology’s dark matter : species richness, spatiotemporal distribution, and community composition of a dark taxon. <i>BMC Biology</i>, <i>22</i>, Article 215. <a href="https://doi.org/10.1186/s12915-024-02010-z" target="_blank">https://doi.org/10.1186/s12915-024-02010-z</a>
dc.identifier.otherCONVID_243249773
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/97642
dc.description.abstractBackground Zoology’s dark matter comprises hyperdiverse, poorly known taxa that are numerically dominant but largely unstudied, even in temperate regions where charismatic taxa are well understood. Dark taxa are everywhere, but high diversity, abundance, and small size have historically stymied their study. We demonstrate how entomological dark matter can be elucidated using high-throughput DNA barcoding (“megabarcoding”). We reveal the high abundance and diversity of scuttle flies (Diptera: Phoridae) in Sweden using 31,800 specimens from 37 sites across four seasonal periods. We investigate the number of scuttle fly species in Sweden and the environmental factors driving community changes across time and space. Results Swedish scuttle fly diversity is much higher than previously known, with 549 putative specie) detected, compared to 374 previously recorded species. Hierarchical Modelling of Species Communities reveals that scuttle fly communities are highly structured by latitude and strongly driven by climatic factors. Large dissimilarities between sites and seasons are driven by turnover rather than nestedness. Climate change is predicted to significantly affect the 47% of species that show significant responses to mean annual temperature. Results were robust regardless of whether haplotype diversity or species-proxies were used as response variables. Additionally, species-level models of common taxa adequately predict overall species richness. Conclusions Understanding the bulk of the diversity around us is imperative during an era of biodiversity change. We show that dark insect taxa can be efficiently characterised and surveyed with megabarcoding. Undersampling of rare taxa and choice of operational taxonomic units do not alter the main ecological inferences, making it an opportune time to tackle zoology’s dark matter.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherBioMed Central
dc.relation.ispartofseriesBMC Biology
dc.rightsCC BY 4.0
dc.subject.otherdark taxa
dc.subject.othermegabarcoding
dc.subject.otherDNA barcoding
dc.subject.otherbiodiversity discovery
dc.subject.otherhierarchical modelling of species communities
dc.subject.otherdiptera
dc.subject.otherphoridae
dc.titleResolving biology’s dark matter : species richness, spatiotemporal distribution, and community composition of a dark taxon
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202410236499
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.relation.issn1741-7007
dc.relation.volume22
dc.type.versionpublishedVersion
dc.rights.copyright© The Author(s) 2024
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber345110
dc.relation.grantnumber336212
dc.subject.ysoDNA-viivakoodit
dc.subject.ysobiodiversiteetti
dc.subject.ysolajistokartoitus
dc.subject.ysohyönteistiede
dc.subject.ysoeliöyhteisöt
dc.subject.ysosekvensointi
dc.subject.ysokaksisiipiset
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p28412
jyx.subject.urihttp://www.yso.fi/onto/yso/p5496
jyx.subject.urihttp://www.yso.fi/onto/yso/p29383
jyx.subject.urihttp://www.yso.fi/onto/yso/p16960
jyx.subject.urihttp://www.yso.fi/onto/yso/p4636
jyx.subject.urihttp://www.yso.fi/onto/yso/p25917
jyx.subject.urihttp://www.yso.fi/onto/yso/p9122
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.datasethttps://github.com/leshonlee/DocumentingPhorids
dc.relation.doi10.1186/s12915-024-02010-z
dc.relation.funderResearch Council of Finlanden
dc.relation.funderResearch Council of Finlanden
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
jyx.fundingprogramResearch costs of Academy Professor, AoFen
jyx.fundingprogramResearch post as Academy Professor, AoFen
jyx.fundingprogramAkatemiaprofessorin tutkimuskulut, SAfi
jyx.fundingprogramAkatemiaprofessorin tehtävä, SAfi
jyx.fundinginformationOpen access funding provided by NTNU Norwegian University of Science and Technology (incl St. Olavs Hospital - Trondheim University Hospital) EH was funded by Swedish Taxonomy Initiative grant 2016–203 4.3. TR and OO were funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC-synergy grant 856506—LIFEPLAN). OO was funded by Academy of Finland (grant no. 336212 and 345110). MJ was supported by the Academy of Finland’s “Thriving Nature” research profiling action.
dc.type.okmA1


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