Recent progress in marine mycological research in different countries, and prospects for future developments worldwide
Bibliographic record
Abstract
Abstract Early research on marine fungi was mostly descriptive, with an emphasis on their diversity and taxonomy, especially of those collected at rocky shores on seaweeds and driftwood. Subsequently, further substrata (e.g. salt marsh grasses, marine animals, seagrasses, sea foam, seawater, sediment) and habitats (coral reefs, deep-sea, hydrothermal vents, mangroves, sandy beaches, salt marshes) were explored for marine fungi. In parallel, research areas have broadened from micro-morphology to ultrastructure, ecophysiology, molecular phylogenetics, biogeography, biodeterioration, biodegradation, bioprospecting, genomics, proteomics, transcriptomics and metabolomics. Although marine fungi only constitute a small fraction of the global mycota, new species of marine fungi continue to be described from new hosts/substrata of unexplored locations/habitats, and novel bioactive metabolites have been discovered in the last two decades, warranting a greater collaborative research effort. Marine fungi of Africa, the Americas and Australasia are under-explored, while marine Chytridiomycota and allied taxa, fungi associated with marine animals, the functional roles of fungi in the sea, and the impacts of climate change on marine fungi are some of the topics needing more attention. In this article, currently active marine mycologists from different countries have written on the history and current state of marine fungal research in individual countries highlighting their strength in the subject, and this represents a first step towards a collaborative inter- and transdisciplinary research strategy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".