Abstract
Small lakes and ponds occupy an enormous surface area of inland freshwater and represent an important terrestrial–water interface. Disturbances caused by extreme weather events can have substantial effects on these ecosystems. Here, we analysed the dynamics of nutrients and the entire plankton community in two flood events and afterwards, when quasi-stable conditions were established, to investigate the effect of such disturbances on a small forest pond. We show that floodings result in repeated washout of resident organisms and hundredfold increases in nutrient load. Despite this, the microbial community recovers to a predisturbance state within two weeks of flooding through four well-defined succession phases. Reassembly of phytoplankton and especially zooplankton takes up to two times longer and features repetitive and adaptive patterns. Release of dissolved nutrients from the pond is associated with inflow rates and community recovery, and returns to predisturbance levels before microbial compositions recover. Our findings shed light on the mechanisms underlying functional resilience of small waterbodies and are relevant to global change-induced increases in weather extremes.
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Data availability
The 16S rRNA and rDNA amplicon data from this study were deposited to NCBI under BioProject PRJNA547706, BioSamples SAMN11974970-11975031. Sequences of 23S rRNA genes obtained from clone libraries were submitted to NCBI under accession numbers MN565597–MN565664. The Silva SSU and LSU databases release 132 (https://www.arb-silva.de/download/archive/) were used for the sequence analysis and probe design. Source data are provided with this paper. Additional information can be obtained from the corresponding author upon request.
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Acknowledgements
We would like to thank all scientific and technical staff supporting the team during the exhausting but exciting sampling campaign, especially R. Malá, V. Kasalický and H. Kratochvílová. The study was supported by projects from the Czech Science Foundation project 20-23718Y awarded to T.S., project 13-00243S awarded to K.Š., project 19-00113S awarded to P.P. and projects 19-23469S and 20-12496X awarded to M.M.S. H.P.G. was supported by the German Federal Ministry of Education and Science (BMBF) in the frame of the BIBS project (TP2: 01LC1501G).
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Contributions
T.S., M.M.S. and K.Š. designed the study, and collected and enumerated bacterial and protist samples. T.S. contributed to CARD-FISH analysis, performed bioinformatics analysis of amplicon sequences and statistical analyses of data, interpreted the data, designed the graphs and wrote the manuscript. M.M.S. designed the CARD-FISH probes, contributed to CARD-FISH analysis, prepared the phylogenetic trees and participated in data interpretation and manuscript writing. P.P. collected and analysed chemistry samples, and contributed to interpretation of data and manuscript revision. P.Z. and J.N. collected and analysed samples for phytoplankton and contributed to interpretation of data and manuscript revision. H.P.G. was responsible for the isolation of the nucleic acids and preparation of the amplicon libraries, and participated in data interpretation and manuscript writing. J.S. collected and analysed zooplankton data, and contributed to interpretation of data and manuscript revision. J.H. collected and analysed meteorological and hydrological data, calculated the transfer models and nutrient balances, and contributed to interpretation of data and manuscript revision. K.Š. analysed protist community-related parameters and contributed to interpretation of data and manuscript writing.
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Extended data
Extended Data Fig. 1 Agglomerative hierarchical clustering (AHC) based on Bray–Curtis dissimilarity matrix of 16S rDNA amplicon data.
Dashed lines show the level of truncation. Sample names are composed of the date and the first letter of the sampling site (P – pond, S – stream). Samples from the pond are depicted in blue, samples from the stream in orange, samples collected during EREs are shown in red. a, AHC of pond samples. Coloured background areas highlight clusters, which defined four phases of the succession cycle: violet – ‘K’ conservation phase, orange – ‘Ω’ release phase, light green – ‘α’ reorganization phase, and aquamarine – ‘r’ exploitation phase. b, AHC of stream samples. c AHC of all stream and pond samples.
Extended Data Fig. 2 Mass balances of different chemical compounds in Jiřická Pond.
(a–g) Black circles represent values of compounds measured in the pond. Grey surfaces represent theoretical hydrological transport of compounds from the inlet (calculated with CE-QUAL-W2 Hydrodynamic and Water Quality Model using settings for conservative tracer). Dashed lines indicate two flood events observed during the sampling campaign. Precipitation events >3 mm d−1 are depicted in aquamarine above panel a. (a–c) Phosphorus fractions. TP, total phosphorus; DP, dissolved phosphorus; DRP, dissolved reactive phosphorus. (d–f) Nitrogen fractions. DN, dissolved nitrogen. g, Dissolved organic carbon (DOC). (h–n) Daily import and export rates of different compounds. Dotted lines separate three equal periods of 23 days each. Import to the pond is shown in orange, export from the pond in blue. (h–j) Phosphorus fractions. TP, total phosphorus; DP, dissolved phosphorus; DRP, dissolved reactive phosphorus. (k–m) Nitrogen fractions. DN, dissolved nitrogen. n, Dissolved organic carbon (DOC).
Extended Data Fig. 3 Highly abundant ASVs detectable only during conservation phase.
Type K, typical K-strategists. Circles connected with lines represent percentages of 16S rDNA amplicon reads, triangles represent percentages of 16S rRNA amplicons reads. Samples from the pond are depicted in blue, samples from the stream in orange. Background colours indicate different phases of the succession: violet – ‘K’ conservation phase, orange – ‘Ω’ collapse and release phase, light green – ‘α’ reorganization phase, and aquamarine – ‘r’ exploitation phase. Displayed taxonomy is based on naive Bayesian classifier method and trained Silva SSU database release 132 incorporated in the DADA2 pipeline; additionally, if available, 100% identity matches obtained with BLAST are shown in brackets, and CARD-FISH probes matching the ASVs (R-BT065 and opitu-346) are indicated in italics.
Extended Data Fig. 4 Highly abundant ASVs displaying highest read proportions in conservation phases and already detectable in exploitation phases.
Type K (r), fast recovering K-strategists. Circles connected with lines represent percentages of 16S rDNA amplicon reads, triangles represent percentages of 16S rRNA amplicons reads. Samples from the pond are depicted in blue, samples from the stream in orange. Background colours indicate different phases of the succession: violet – ‘K’ conservation phase, orange – ‘Ω’ collapse and release phase, light green – ‘α’ reorganization phase, and aquamarine – ‘r’ exploitation phase. Displayed taxonomy is based on naive Bayesian classifier method and trained Silva SSU database release 132 incorporated in the DADA2 pipeline; additionally, if available, 100% identity matches obtained with BLAST are shown in brackets, and CARD-FISH probes matching the ASVs (R-BT065 and opitu-346) are indicated in italics.
Extended Data Fig. 5 Highly abundant ASVs displaying highest read proportions in EREs or reorganization phases.
Circles connected with lines represent percentages of 16S rDNA amplicon reads, triangles represent percentages of 16S rRNA amplicons reads. Samples from the pond are depicted in blue, samples from the stream in orange. Background colours indicate different phases of the succession: violet – ‘K’ conservation phase, orange – ‘Ω’ collapse and release phase, light green – ‘α’ reorganization phase, and aquamarine – ‘r’ exploitation phase. Displayed taxonomy is based on naive Bayesian classifier method and trained Silva SSU database release 132 incorporated in the DADA2 pipeline; additionally, if available, 100% identity matches obtained with BLAST are shown in brackets, and CARD-FISH probes matching the ASVs (RBT-065 and opitu-346) are indicated in italics. a, Type Ω, ASVs displaying highest read proportions during the EREs (emigrants) that do not belong to the most common pond ASVs. b, Type α, ASVs displaying highest reads proportions during reorganization phase (inlet associated r-strategists).
Extended Data Fig. 6 Highly abundant omnipresent ASVs and ASVs displaying highest read proportions in exploitation phases.
Circles connected with lines represent percentages of 16S rDNA amplicon reads, triangles represent percentages of 16S rRNA amplicons reads. Samples from the pond are depicted in blue, samples from the stream in orange. Background colours indicate different phases of the succession: violet – ‘K’ conservation phase, orange – ‘Ω’ collapse and release phase, light green – ‘α’ reorganization phase, and aquamarine – ‘r’ exploitation phase. Displayed taxonomy is based on naive Bayesian classifier method and trained Silva SSU database release 132 incorporated in the DADA2 pipeline; additionally, if available, 100% identity matches obtained with BLAST are shown in brackets, and CARD-FISH probes matching the ASVs (R-BT065 and opitu-346) are indicated in italics. a: Type r, ASVs displaying highest reads proportions during exploitation phase (pond associated r-strategists). b: Type all-rounders, ASVs displaying comparable read proportions during all phases except EREs.
Extended Data Fig. 7 Changes in different size fractions of algae in the context of ciliate dynamics and contributions to the total bacterial loss.
a, b, Abundances and biovolumes of algal cells <600 µm3 and >600 µm3, respectively (that is, suitable or not suitable for ciliate grazing). c, Abundances of ciliates and the most dynamic fraction of algae <150 µm3 (represented mostly by small Chlamydomonas spp.). d, Total bacterial loss rate and HNF and ciliates grazing rates (GR). The dashed lines indicate the two EREs.
Extended Data Fig. 8 Hydrological, physical, chemical and microbial parameters measured in the stream and pond.
Extended version of Fig. 1. a, b, Precipitation (grey shade) in the watershed of Jiřícká Pond, stream flow rate (a) and water retention time at 0.5 m depth in the pond (b). c, d, Water temperature and pH. e, f, Concentrations of phosphorus fractions, TP – total phosphorus, DP – dissolved phosphorus, DRP – dissolved reactive phosphorus. g, h, Concentrations of nitrogen fractions, DN – dissolved nitrogen. i, j, Concentrations of dissolved organic carbon (DOC) and DOC size fractions. k, l, Concentrations of carboxylic acids (CA). m, n, Abundances of prokaryotic cells and virus-like particles. Prokaryotic abundances counted from two independent biological samples are presented as circles. Dashed lines indicate two flood events during the sampling campaign.
Extended Data Fig. 9 Bootstrapped maximum likelihood tree of 16S rRNA gene sequences of the closest relatives of the 50 most abundant ASVs detected in stream and pond samples and most abundant EREs genotypes.
The colours of the branches and ASVs correspond to the source: orange – stream, blue – pond, red – EREs, orange with red line – stream and EREs. ASVs are depicted as circles with different diameters representing the maximal percentages of corresponding reads, ASVs shared between pond and stream are shown as divided circles. Asterisks indicate ASVs with low identity values to the closest relatives (90–97%). Specific CARD-FISH probes are shown in italics. Bootstraps (100 repetitions) are indicated by different sized circles at the nodes, the scale bar applies to 20% sequence divergence.
Extended Data Fig. 10 Dynamics in stream microbial community.
a, Multidimensional scaling based on Bray–Curtis distances of bacterial community compositions in the stream samples (16S rRNA gene amplicons), Kruskal’s stress: 0.2; (start) and (end) indicate the first and last samples, respectively. The line connecting samples follows a chronological order. The diameters of the circles are proportional to the Pielou’s evenness of the samples (varying between 0.71 and 0.94). Orange circles indicate samples taken during the EREs. b, Pie charts depict the contribution of large taxonomical groups and follow the chronological order from left to right. The samples associated with EREs are highlighted with orange frames. *Gammaproteobacteria are shown without Betaproteobacteriales, which are presented as a separate group.
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Shabarova, T., Salcher, M.M., Porcal, P. et al. Recovery of freshwater microbial communities after extreme rain events is mediated by cyclic succession. Nat Microbiol 6, 479–488 (2021). https://doi.org/10.1038/s41564-020-00852-1
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DOI: https://doi.org/10.1038/s41564-020-00852-1
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