Idiosyncrasy and overdominance in the structure of natural communities of arbuscular mycorrhizal fungi: is there a role for stochastic processes?
Bibliographic record
Abstract
Summary 1. Most studies of species abundance patterns focus on conspicuous macroorganisms while microbial communities remain relatively understudied. This bias is a concern given the functional importance and high diversity of microbes. 2. We determine whether a common species abundance distribution (SAD) is observed in communities of a widespread group of soil microbes, the Glomeromycota or arbuscular mycorrhizal (AM) fungi. Using molecular techniques, we intensively sampled the AM fungal community of a woodland–grassland ecotone in Yorkshire, UK. Observed species abundances were compared to theoretical models describing SADs. We also reanalysed 32 previously published data sets in a similar manner. 3. Species abundance distributions in all the AM fungal communities fitted both lognormal and broken‐stick models. However, these models consistently and significantly underpredicted the abundance of the most abundant AM fungal taxon. We found that AM fungal communities are typically dominated by a single taxon; representing on average 40% of total abundance within the community. Phylogenetic analysis of the most abundant taxa across data sets showed that the dominant AM fungal type in each community was different and not a widespread generalist. 4. We conclude that a common community structure is present in AM fungal communities from different habitats. The fit to log‐normal and broken‐stick models suggests the influence of niche differentiation structuring these communities. However, the consistently observed overdominance indicates that local adaptation and stochastic processes may also play important roles in structuring these communities, and we propose a mechanism to explain overdominance in AM fungal communities. 5. Synthesis. This paper applies ecological models derived from studies on larger organisms to microbial communities. Results from this study suggest that a common log‐normal SAD is likely to be observed across both microbial and macro taxa. However, due to the distinctive features of microbial biology, some noticeable differences, such as heavy overdominance, may lead to unique structures in microbial communities. This research not only highlights that, to a first approximation, microbial communities follow similar processes and have similar patterns to those of macroorganisms, but also the need for large‐scale microbial data sets, if we are to understand the patterns and processes regulating global biodiversity.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".