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Record W3087501169 · doi:10.7717/peerj.9821

Assessing the responses of <i>Sphagnum</i> micro-eukaryotes to climate changes using high throughput sequencing

2020· article· en· W3087501169 on OpenAlexfundno aff
Monika Reczuga, Christophe V. W. Seppey, Matthieu Mulot, Vincent E. J. Jassey, Alexandre Buttler, Sandra Słowińska, Michał Słowiński, Enrique Lara, Mariusz Lamentowicz, Edward A. D. Mitchell

Bibliographic record

VenuePeerJ · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsnot available
FundersUniwersytet im. Adama Mickiewicza w PoznaniuNorges ForskningsrådNarodowym Centrum NaukiEuropean CommissionComunidad de MadridSCIEX
KeywordsEcosystemSphagnumClimate changePeatEnvironmental scienceEcologyGlobal warmingCarbon cycleBiology

Abstract

fetched live from OpenAlex

Current projections suggest that climate warming will be accompanied by more frequent and severe drought events. Peatlands store ca. one third of the world’s soil organic carbon. Warming and drought may cause peatlands to become carbon sources through stimulation of microbial activity increasing ecosystem respiration, with positive feedback effect on global warming. Micro-eukaryotes play a key role in the carbon cycle through food web interactions and therefore, alterations in their community structure and diversity may affect ecosystem functioning and could reflect these changes. We assessed the diversity and community composition of Sphagnum -associated eukaryotic microorganisms inhabiting peatlands and their response to experimental drought and warming using high throughput sequencing of environmental DNA. Under drier conditions, micro-eukaryotic diversity decreased, the relative abundance of autotrophs increased and that of osmotrophs (including Fungi and Peronosporomycetes) decreased. Furthermore, we identified climate change indicators that could be used as early indicators of change in peatland microbial communities and ecosystem functioning. The changes we observed indicate a shift towards a more “terrestrial” community in response to drought, in line with observed changes in the functioning of the ecosystem.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.344

Codex and Gemma teacher scores by category

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

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 head0.053
GPT teacher head0.301
Teacher spread0.247 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations19
Published2020
Admission routes1
Has abstractyes

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Same venuePeerJSame topicPeatlands and Wetlands EcologyFrench-language works237,207