title: Metapopulation theory identifies biogeographical patterns among core and satellite marine bacteria scaling from tens to thousands of kilometers.
abstract: 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.
authors.affiliation: Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
authors.forename: Markus V
authors.initials: MV
authors.lastname: Lindh
authors.affiliation: Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
authors.forename: Johanna
authors.initials: J
authors.lastname: Sjöstedt
authors.affiliation: Department of Biology and Environmental Science, Linnaeus University, Kalmar, SE-39182, Sweden.
authors.forename: Börje
authors.initials: B
authors.lastname: Ekstam
authors.affiliation: Department of Aquatic Resources, Institute of Marine Research, Swedish University of Agricultural Sciences, Lysekil, SE-45330, Sweden.
authors.forename: Michele
authors.initials: M
authors.lastname: Casini
authors.affiliation: Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
authors.forename: Daniel
authors.identifier: 0000-0002-8779-6464
authors.initials: D
authors.lastname: Lundin
authors.affiliation: Science for Life Laboratory School of Biotechnology, KTH Royal Institute of Technology, Stockholm, SE-10691, Sweden.
authors.forename: Luisa W
authors.initials: LW
authors.lastname: Hugerth
authors.affiliation: Science for Life Laboratory School of Biotechnology, KTH Royal Institute of Technology, Stockholm, SE-10691, Sweden.
authors.forename: Yue O O
authors.initials: YO
authors.lastname: Hu
authors.affiliation: Science for Life Laboratory School of Biotechnology, KTH Royal Institute of Technology, Stockholm, SE-10691, Sweden.
authors.forename: Anders F
authors.initials: AF
authors.lastname: Andersson
authors.affiliation: Department of Ecology and Environmental Science, Umeå University, Umeå, SE-90187, Sweden.
authors.forename: Agneta
authors.initials: A
authors.lastname: Andersson
authors.affiliation: Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
authors.forename: Catherine
authors.initials: C
authors.lastname: Legrand
authors.affiliation: Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
authors.forename: Jarone
authors.identifier: 0000-0002-6405-1347
authors.initials: J
authors.lastname: Pinhassi
mesh_terms: D001419:Bacteria / Q000145:classification / Q000235:genetics / Q000302:isolation & purification*; D001454:Baltic States; D044822:Biodiversity; D004463:Ecology; D017753:Ecosystem; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D012623:Seawater / Q000737:chemistry / Q000382:microbiology*
chemical_list: D012336:RNA, Ribosomal, 16S