Emergent “core communities” of microbes, meiofauna and macrofauna at hydrothermal vents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Assessment of ecosystem health entails consideration of species interactions within and between size classes to determine their contributions to ecosystem function. Elucidating microbial involvement in these interactions requires tools to distil diverse microbial information down to relevant, manageable elements. We used covariance ratios (proportionality) between pairs of species and patterns of enrichment to identify "core communities" of likely interacting microbial (<64 µm), meiofaunal (64 µm to 1 mm) and macrofaunal (>1 mm) taxa within assemblages hosted by a foundation species, the hydrothermal vent tubeworm Ridgeia piscesae. Compared with samples from co-located hydrothermal fluids, microbial communities within R. piscesae assemblages are hotspots of taxonomic richness and are high in novelty (unclassified OTUs) and in relative abundance of Bacteroidetes. We also observed a robust temperature-driven distinction in assemblage composition above and below ~25 °C that spanned micro to macro size classes. The core high-temperature community included eight macro- and meiofaunal taxa and members of the Bacteroidetes and Epsilonbacteraeota, particularly the genera Carboxylicivirga, Nitratifractor and Arcobacter. The core low-temperature community included more meiofaunal species in addition to Alpha- and Gammaproteobacteria, and Actinobacteria. Inferred associations among high-temperature core community taxa suggest increased reliance on species interactions under more severe hydrothermal conditions. We propose refinement of species diversity to "core communities" as a tool to simplify investigations of relationships between taxonomic and functional diversity across domains and scales by narrowing the taxonomic scope.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it