Fungal diversity and community structure from coastal and barrier island beaches in the United States Gulf of Mexico
Bibliographic record
Abstract
Fungi are an important and understudied component of coastal biomes including sand beaches. Basic biogeographic diversity data are lacking for marine fungi in most parts of the world, despite their important role in decomposition. We examined intertidal fungal communities at several United States (US) Gulf of Mexico sand beach sites using morphology and ITS rDNA terminal restriction fragment length polymorphism (T-RFLP) analyses. Fungal biogeographical patterns from sand beach detritus (wood, emergent plant [mangrove/ saltmarsh], or marine [algae, seagrass]) from Florida, Mississippi, and Texas were investigated using diversity indices and multivariate analyses. Fungal diversity increased with decreasing latitude at our study sites. Substrate type strongly influenced fungal community structure in this region, with different fungal communities on detrital marine versus emergent substrates, as well as detrital marine versus wood substrates. Thirty-five fungi were identified morphologically, including new regional and host records. Of these, 86% were unique to an individual collection (i.e., sampled once from one site). Rarefaction curves from pooled morphological data from all sites estimate the number of samples required to characterize the mycota of each substrate. As sampling occurred before the Deepwater Horizon oil spill (April-2010), our findings contribute pre-oil spill sand beach biodiversity data and marine fungal distribution trends within this economically important oceanographic region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".