Disentangling seasonal bacterioplankton population dynamics by high-frequency sampling.
Multiyear comparisons of bacterioplankton succession reveal that environmental conditions drive community shifts with repeatable patterns between years. However, corresponding insight into bacterioplankton dynamics at a temporal resolution relevant for detailed examination of variation and characteristics of specific populations within years is essentially lacking. During 1 year, we collected 46 samples in the Baltic Sea for assessing bacterial community composition by 16S rRNA gene pyrosequencing (nearly twice weekly during productive season). Beta-diversity analysis showed distinct clustering of samples, attributable to seemingly synchronous temporal transitions among populations (populations defined by 97% 16S rRNA gene sequence identity). A wide spectrum of bacterioplankton dynamics was evident, where divergent temporal patterns resulted both from pronounced differences in relative abundance and presence/absence of populations. Rates of change in relative abundance calculated for individual populations ranged from 0.23 to 1.79 day(-1) . Populations that were persistently dominant, transiently abundant or generally rare were found in several major bacterial groups, implying evolution has favoured a similar variety of life strategies within these groups. These findings suggest that high temporal resolution sampling allows constraining the timescales and frequencies at which distinct populations transition between being abundant or rare, thus potentially providing clues about physical, chemical or biological forcing on bacterioplankton community structure.
Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
Markus V
MV
Lindh
Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
Johanna
J
Sjöstedt
Science for Life Laboratory, KTH Royal Institute of Technology, School of Biotechnology, Stockholm, SE-10691, Sweden.
Anders F
AF
Andersson
Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.|Department of Marine Sciences, University of Otago, PO Box 56, Dunedin, NZ-9054, New Zealand.
Federico
F
Baltar
Science for Life Laboratory, KTH Royal Institute of Technology, School of Biotechnology, Stockholm, SE-10691, Sweden.
Luisa W
LW
Hugerth
Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
Daniel
D
Lundin
Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
Saraladevi
S
Muthusamy
Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
Catherine
C
Legrand
Centre for Ecology and Evolution in Microbial model Systems - EEMiS, Linnaeus University, Kalmar, SE-39182, Sweden.
Jarone
J
Pinhassi
D059001:Aquatic Organisms / Q000235:genetics / Q000382:microbiology*; D001419:Bacteria / Q000235:genetics*; D001454:Baltic States; D044822:Biodiversity; D014644:Genetic Variation / Q000235:genetics*; D010933:Plankton / Q000235:genetics*; D011157:Population Dynamics; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D012621:Seasons
D012336:RNA, Ribosomal, 16S