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dc.contributor.authorBurner, Ryan C.
dc.contributor.authorStephan, Jörg G.
dc.contributor.authorDrag, Lukas
dc.contributor.authorPotterf, Mária
dc.contributor.authorBirkemoe, Tone
dc.contributor.authorSiitonen, Juha
dc.contributor.authorMüller, Jörg
dc.contributor.authorOvaskainen, Otso
dc.contributor.authorSverdrup‐Thygeson, Anne
dc.contributor.authorSnäll, Tord
dc.date.accessioned2023-11-01T13:50:32Z
dc.date.available2023-11-01T13:50:32Z
dc.date.issued2023
dc.identifier.citationBurner, R. C., Stephan, J. G., Drag, L., Potterf, M., Birkemoe, T., Siitonen, J., Müller, J., Ovaskainen, O., Sverdrup‐Thygeson, A., & Snäll, T. (2023). Alternative measures of trait–niche relationships : A test on dispersal traits in saproxylic beetles. <i>Ecology and Evolution</i>, <i>13</i>(10), Article e10588. <a href="https://doi.org/10.1002/ece3.10588" target="_blank">https://doi.org/10.1002/ece3.10588</a>
dc.identifier.otherCONVID_194221671
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/91235
dc.description.abstractFunctional trait approaches are common in ecology, but a lack of clear hypotheses on how traits relate to environmental gradients (i.e., trait–niche relationships) often makes uncovering mechanisms difficult. Furthermore, measures of community functional structure differ in their implications, yet inferences are seldom compared among metrics. Community-weighted mean trait values (CWMs), a common measure, are largely driven by the most common species and thus do not reflect community-wide trait–niche relationships per se. Alternatively, trait–niche relationships can be estimated across a larger group of species using hierarchical joint species distribution models (JSDMs), quantified by a parameter Γ. We investigated how inferences about trait–niche relationships are affected by the choice of metric. Using deadwood-dependent (saproxylic) beetles in fragmented Finnish forests, we followed a protocol for investigating trait–niche relationships by (1) identifying environmental filters (climate, forest age, and deadwood volume), (2) relating these to an ecological function (dispersal ability), and (3) identifying traits related to this function (wing morphology). We tested 18 hypothesized dispersal relationships using both CWM and Γ estimates across these environmental gradients. CWMs were more likely than Γ to show support for trait–niche relationships. Up to 13% of species' realized niches were explained by dispersal traits, but the directions of effects were consistent with fewer than 11%–39% of our 18 trait–niche hypotheses (depending on the metric used). This highlights the difficulty in connecting morphological traits and ecological functions in insects, despite the clear conceptual link between landscape connectivity and flight-related traits. Caution is thus warranted in hypothesis development, particularly where apparent trait–function links are less clear. Inferences differ when CWMs versus Γ estimates are used, necessitating the choice of a metric that reflects study questions. CWMs help explain the effects of environmental gradients on community trait composition, whereas the effects of traits on species' niches are better estimated using hierarchical JSDMs.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherWiley
dc.relation.ispartofseriesEcology and Evolution
dc.rightsCC BY 4.0
dc.subject.otherBayesian joint species distribution model
dc.subject.othercommunity-weighted mean trait values
dc.subject.otherdeadwood
dc.subject.otherdispersal capacity
dc.subject.othermorphological traits
dc.subject.otherphylogeny
dc.subject.otherresponse trait
dc.subject.otherwing length
dc.titleAlternative measures of trait–niche relationships : A test on dispersal traits in saproxylic beetles
dc.typeresearch article
dc.identifier.urnURN:NBN:fi:jyu-202311017257
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.issn2045-7758
dc.relation.numberinseries10
dc.relation.volume13
dc.type.versionpublishedVersion
dc.rights.copyright© 2023 the Authors
dc.rights.accesslevelopenAccessfi
dc.type.publicationarticle
dc.subject.ysokovakuoriaiset
dc.subject.ysofylogenia
dc.subject.ysoekosysteemit (ekologia)
dc.subject.ysoekologinen lokero
dc.subject.ysomorfologia
dc.subject.ysoeliöyhteisöt
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p6734
jyx.subject.urihttp://www.yso.fi/onto/yso/p25760
jyx.subject.urihttp://www.yso.fi/onto/yso/p4997
jyx.subject.urihttp://www.yso.fi/onto/yso/p27164
jyx.subject.urihttp://www.yso.fi/onto/yso/p1524
jyx.subject.urihttp://www.yso.fi/onto/yso/p4636
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1002/ece3.10588
jyx.fundinginformationThe study was funded by Formas (2018-02435) and the part of the BiodivERsA project “BioESSHealth—Scenarios for biodiversity and ecosystem services acknowledging health” coordinated by TS. Clayton Traylor provided helpful comments on the manuscript. The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at UPPMAX partially funded by the Swedish Research Council through grant agreement no. 2018-05973. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
dc.type.okmA1


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