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Record W2763868024 · doi:10.5194/bgd-12-12121-2015

Phototrophic pigment diversity and picophytoplankton abundance in permafrost thaw lakes

2015· preprint· en· W2763868024 on OpenAlexfundaboutno aff
Anna Przytulska, Jérôme Comte, Sophie Crévecoeur, Connie Lovejoy, Isabelle Laurion, Warwick F. Vincent

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsnot available
FundersFonds de recherche du Québec – Nature et technologies
KeywordsPhototrophPicoplanktonPermafrostPhytoplanktonThermokarstChlorophyll aEnvironmental scienceDominance (genetics)EcologyDiatomOceanographyEnvironmental chemistryPhotosynthesisBiologyBotanyGeologyNutrientChemistry

Abstract

fetched live from OpenAlex

Abstract. Permafrost thaw lakes (thermokarst lakes) are widely distributed across the northern landscape, and are known to be biogeochemically active sites that emit large amounts of carbon to the atmosphere as CH4 and CO2. However, the abundance and composition of the photosynthetic communities that consume CO2 have been little explored in this ecosystem type. In order to identify the major groups of phototrophic organisms and their controlling variables, we sampled 12 permafrost thaw lakes along a permafrost degradation gradient in northern Québec, Canada. Additional samples were taken from 5 rock-basin reference lakes in the region to determine if the thaw waters differed in limnological properties and phototrophs. Phytoplankton community structure was determined by high performance liquid chromatography analysis of their photoprotective and photosynthetic pigments, and autotrophic picoplankton concentrations were assessed by flow cytometry. One of the black colored lakes located in a andscape of rapidly degrading palsas (permafrost mounds) was selected for high-throughput 18S rRNA sequencing to help interpret the pigment and cytometry data. The results showed that the limnological properties of the thaw lakes differed significantly from the reference lakes, and were more highly stratified. However, both waterbody types contained similarly diverse phytoplankton groups, with dominance of the pigment assemblages by fucoxanthin-containing taxa, as well as chlorophytes, cryptophytes and cyanobacteria. Chlorophyll a concentrations (Chl a) were correlated with total phosphorus (TP), and both were significantly higher in the thaw lakes (overall means of 3.3 μg Chl a L−1 and 34 μg TP L−1) relative to the reference lakes (2.0 μg Chl a L−1 and 8.2 μg TP L−1). Stepwise multiple regression of Chl a against the other algal pigments showed that it was largely a function of lutein, fucoxanthin and peridinin (R2 = 0.78). The bottom waters of two of the thaw lakes also contained high concentrations of bacteriochlorophyll d, showing the presence of green photosynthetic sulphur bacteria. The molecular analyses indicated a relatively minor contribution of diatoms, while chrysophytes, dinoflagellates and chlorophytes were well represented; the heterotrophic eukaryote fraction was dominated by numerous ciliate taxa, and also included Heliozoa, Rhizaria, chytrids and flagellates. Autotrophic picoplankton occurred in cell concentrations up to 8.8 × 105 mL−1 (picocyanobacteria) and 4.6 × 105 mL−1 (picoeukaryotes). Both groups of picophytoplankton were positively correlated with total phytoplankton abundance, as measured by Chl a; picocyanobacteria were inversely correlated with dissolved organic carbon, while picoeukaryotes were correlated with conductivity. Despite their net heterotrophic character, subarctic thaw lakes are rich habitats for diverse phototrophic communities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.331

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.203
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2015
Admission routes2
Has abstractyes

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