Novel Insights to Be Gained From Applying Metacommunity Theory to Long-Term, Spatially Replicated Biodiversity Data

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dc.contributor.authorRecord, Sydne
dc.contributor.authorVoelker, Nicole
dc.contributor.authorZarnetske, Phoebe L.
dc.contributor.authorWisnoski, Nathan I.
dc.contributor.authorTonkin, Jonathan D.
dc.contributor.authorSwan, Christopher
dc.contributor.authorMarazzi, Luca
dc.contributor.authorLany, Nina
dc.contributor.authorLamy, Thomas
dc.contributor.authorCompagnoni, Aldo
dc.contributor.authorCastorani, Max C. N.
dc.contributor.authorAndrade, Riley
dc.contributor.authorSokol, Eric R.
dc.date.accessioned2022-06-14T20:41:49Z
dc.date.available2022-06-14T20:41:49Z
dc.date.issued2021-01-14
dc.description.abstractGlobal loss of biodiversity and its associated ecosystem services is occurring at an alarming rate and is predicted to accelerate in the future. Metacommunity theory provides a framework to investigate multi-scale processes that drive change in biodiversity across space and time. Short-term ecological studies across space have progressed our understanding of biodiversity through a metacommunity lens, however, such snapshots in time have been limited in their ability to explain which processes, at which scales, generate observed spatial patterns. Temporal dynamics of metacommunities have been understudied, and large gaps in theory and empirical data have hindered progress in our understanding of underlying metacommunity processes that give rise to biodiversity patterns. Fortunately, we are at an important point in the history of ecology, where long-term studies with cross-scale spatial replication provide a means to gain a deeper understanding of the multiscale processes driving biodiversity patterns in time and space to inform metacommunity theory. The maturation of coordinated research and observation networks, such as the United States Long Term Ecological Research (LTER) program, provides an opportunity to advance explanation and prediction of biodiversity change with observational and experimental data at spatial and temporal scales greater than any single research group could accomplish. Synthesis of LTER network community datasets illustrates that long-term studies with spatial replication present an under-utilized resource for advancing spatio-temporal metacommunity research. We identify challenges towards synthesizing these data and present recommendations for addressing these challenges. We conclude with insights about how future monitoring efforts by coordinated research and observation networks could further the development of metacommunity theory and its applications aimed at improving conservation efforts.en_US
dc.description.sponsorshipThis work was conducted as a part of the LTER Metacommunity Dynamics and Community Responses to Disturbance Synthesis Group funded by the National Science Foundation under grant DEB#1545288, administered through the Long Term Ecological Research Network Communications Office (LNCO), National Center for Ecological Analysis and Synthesis, University of California, Santa Barbara. ecocommDP work by SR, NL, ES, and MC was funded by the National Science Foundation under grants DBI#1931143 to M. Servilla and DBI#1931174 to C. Gries. SR was additionally supported by National Science Foundation grant DEB#1926568.en_US
dc.description.urihttps://www.frontiersin.org/articles/10.3389/fevo.2020.612794/fullen_US
dc.format.extent10 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2zuov-4kzd
dc.identifier.citationRecord S, Voelker NM,, Zarnetske PL, Wisnoski NI, Tonkin JD, Swan C, Marazzi L, Lany N, Lamy T, Compagnoni A, Castorani MCN, Andrade R and Sokol ER (2021) Novel Insights to Be Gained From Applying Metacommunity Theory, to Long-Term, Spatially Replicated Biodiversity Data., Front. Ecol. Evol. 8:612794., doi: 10.3389/fevo.2020.612794.en_US
dc.identifier.urihttps://doi.org/10.3389/fevo.2020.612794
dc.identifier.urihttp://hdl.handle.net/11603/24938
dc.language.isoen_USen_US
dc.publisherFrontiersen_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Geography and Environmental Systems Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.titleNovel Insights to Be Gained From Applying Metacommunity Theory to Long-Term, Spatially Replicated Biodiversity Dataen_US
dc.typeTexten_US
dcterms.creatorhttps://orcid.org/0000-0002-9763-9630en_US
dcterms.creatorhttps://orcid.org/0000-0002-4366-6449en_US

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