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Metapopulation theory identifies biogeographical patterns among core and satellite marine bacteria scaling from tens to thousands of kilometers
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2017 (English)In: Environmental Microbiology, ISSN 1462-2912, E-ISSN 1462-2920, Vol. 19, no 3, 1222-1236 p.Article in journal (Refereed) Published
Abstract [en]

Metapopulation theory developed in terrestrial ecology provides applicable frameworks for interpreting the role of local and regional processes in shaping species distribution patterns. Yet, empirical testing of metapopulation models on microbial communities is essentially lacking. We determined regional bacterioplankton dynamics from monthly transect sampling in the Baltic Sea Proper using 16S rRNA gene sequencing. A strong positive trend was found between local relative abundance and occupancy of populations. Notably, the occupancy-frequency distributions were significantly bimodal with a satellite mode of rare endemic populations and a core mode of abundant cosmopolitan populations (e.g. Synechococcus, SAR11 and SAR86 clade members). Temporal changes in population distributions supported several theoretical frameworks. Still, bimodality was found among bacterioplankton communities across the entire Baltic Sea, and was also frequent in globally distributed datasets. Datasets spanning waters with widely different physicochemical characteristics or environmental gradients typically lacked significant bimodal patterns. When such datasets were divided into subsets with coherent environmental conditions, bimodal patterns emerged, highlighting the importance of positive feedbacks between local abundance and occupancy within specific biomes. Thus, metapopulation theory applied to microbial biogeography can provide novel insights into the mechanisms governing shifts in biodiversity resulting from natural or anthropogenically induced changes in the environment.

Place, publisher, year, edition, pages
2017. Vol. 19, no 3, 1222-1236 p.
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Ecology
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URN: urn:nbn:se:umu:diva-133803DOI: 10.1111/1462-2920.13650ISI: 000397525100031PubMedID: 28028880OAI: oai:DiVA.org:umu-133803DiVA: diva2:1089642
Available from: 2017-04-20 Created: 2017-04-20 Last updated: 2017-04-20Bibliographically approved

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Andersson, Agneta
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  • apa
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