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Record W4407748577 · doi:10.1111/gcb.70066

Host Species–Microbiome Interactions Contribute to <i>Sphagnum</i> Moss Growth Acclimation to Warming

2025· article· en· W4407748577 on OpenAlexaff
Tatjana Živković, Alyssa A. Carrell, Gustaf Granath, A. Jonathan Shaw, Dale A. Pelletier, Christopher W. Schadt, Dawn M. Klingeman, Mats B. Nilsson, Manuel Helbig, Denis Warshan, Ingeborg J. Klarenberg, Daniel Gilbert, Joel E. Kostka, David J. Weston

Bibliographic record

VenueGlobal Change Biology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPeatlands and Wetlands Ecology
Canadian institutionsDalhousie University
FundersOffice of ScienceOak Ridge National LaboratoryVetenskapsrådetBattelleU.S. Department of Energy
KeywordsSphagnumMicrobiomeMossBiologyAcclimatizationHost (biology)EcologyPeatBotany

Abstract

fetched live from OpenAlex

Sphagnum moss is the dominant plant genus in northern peatlands responsible for long-term carbon accumulation. Sphagnum hosts diverse microbial communities (microbiomes), and its phytobiome (plant host + constituent microbiome + environment) plays a key role in nutrient acquisition along with carbon cycling. Climate change can modify the Sphagnum-associated microbiome, resulting in enhanced host growth and thermal acclimation as previously shown in warming experiments. However, the extent of microbiome benefits to the host and the influence of host-microbe specificity on Sphagnum thermal acclimation remain unclear. Here, we extracted Sphagnum microbiomes from five donor species of four peatland warming experiments across a latitudinal gradient and applied those microbiomes to three germ-free Sphagnum species grown across a range of temperatures in the laboratory. Using this experimental system, we test if Sphagnum's growth response to warming depends on the donor and/or recipient host species, and we determine how the microbiome's growth conditions in the field affect Sphagnum host growth across a range of temperatures in the laboratory. After 4 weeks, we found that the highest growth rate of recipient Sphagnum was observed in treatments of matched host-microbiome pairs, with rates approximately 50% and 250% higher in comparison to maximum growth rates of non-matched host-microbiome pairs and germ-free Sphagnum, respectively. We also found that the maximum growth rate of host-microbiome pairs was reached when treatment temperatures were close to the microbiome's native temperatures. Our study shows that Sphagnum's growth acclimation to temperature is partially controlled by its constituent microbiome. Strong Sphagnum host-microbiome species specificity indicates the existence of underlying, unknown physiological mechanisms that may drive Sphagnum's ability to acclimatize to elevated temperatures. Together with rapid acclimation of the microbiome to warming, these specific microbiome-plant associations have the potential to enhance peatland resilience in the face of climate change.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 science0.0000.001
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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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
Published2025
Admission routes1
Has abstractyes

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