Comprehensive sampling of an isolated dune system demonstrates clear patterns in soil fungal communities across a successional gradient
Bibliographic record
Abstract
Coastal sand dunes are extremely dynamic ecosystems, characterized by stark ecological succession gradients. Dune stabilization is mainly attributed to plant growth, but the establishment and survival of dune-inhabiting vegetation is closely linked to soil microorganisms and to the ecological functions they fulfill. Fungi are particularly important in this context, as some interact intimately with plant roots, while others are critical to soil structure and nutrient availability. Our study aimed to describe wholly fungal diversity and community composition in a secluded coastal dune ecosystem at eight different stages of succession. We comprehensively sampled a relic foredune plain, which is part of an archipelago in the Gulf of Saint Lawrence (Québec, Canada), by collecting soils from 80 sites and measuring soil characteristics. Soil fungal communities were characterized by pyrosequencing, followed by taxonomic classification and assignment of putative roles. Even though we did not observe clear patterns in diversity, we were able to detect distinct taxonomic and community composition signatures across succession stages, which seemed to translate into variations in fungal life strategies. Our results show that a taxonomically and functionally diverse fungal community exists at each dune succession stage, even in the barren foredunes.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".