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Record W3126206325 · doi:10.1002/ecy.3308

Environment–host–microbial interactions shape the <i>Sarracenia</i><i>purpurea</i> microbiome at the continental scale

2021· article· en· W3126206325 on OpenAlexafffundabout
Zachary B. Freedman, Alicia McGrew, Benjamin Baiser, Mathilde Besson, Dominique Gravel, Timothée Poisot, Sydne Record, Lauren B. Trotta, Nicholas J. Gotelli

Bibliographic record

VenueEcology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and Biological Electrophysiology Studies
Canadian institutionsUniversité de SherbrookeUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaHoward Hughes Medical Institute
KeywordsBiologyEcologyAbundance (ecology)BiodiversityTrophic levelSpecies richness

Abstract

fetched live from OpenAlex

The importance of climate, habitat structure, and higher trophic levels on microbial diversity is only beginning to be understood. Here, we examined the influence of climate variables, plant morphology, and the abundance of aquatic invertebrates on the microbial biodiversity of the northern pitcher plant Sarracenia purpurea. The plant's cup-shaped leaves fill with rainwater and support a miniature, yet full-fledged, ecosystem with a diverse microbiome that decomposes captured prey and a small network of shredding and filter-feeding aquatic invertebrates that feed on microbes. We characterized pitcher microbiomes of 108 plants sampled at 36 sites from Florida to Quebec. Structural equation models revealed that annual precipitation and temperature, plant size, and midge abundance had direct effects on microbiome taxonomic and phylogenetic diversity. Climate variables also exerted indirect effects through plant size and midge abundance. Further, spatial structure and climate influenced taxonomic composition, but not phylogenetic composition. Our results suggest that direct effects of midge abundance and climate and indirect effects of climate through its effect on plant-associated factors lead to greater richness of microbial phylotypes in warmer, wetter sites.

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 categoriesInsufficient payload (model declined to judge)
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 score0.884
Threshold uncertainty score0.997

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.009
GPT teacher head0.184
Teacher spread0.176 · 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.

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

Citations27
Published2021
Admission routes3
Has abstractyes

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