Central Taxa Are Keystone Microbes During Early Succession
Bibliographic record
Abstract
Microorganisms underpin numerous ecosystem processes and support biodiversity globally. Yet, we understand surprisingly little about what structures environmental microbiomes, including how to efficiently identify key players. Microbiome network theory predicts that highly connected hubs act as keystones, but this has never been empirically tested in nature. Combining culturing, sequencing, networks and field experiments, we isolated 'central' (highly connected, hub taxa), 'intermediate' (moderately connected), and 'peripheral' (weakly/unconnected) microbes and experimentally evaluated their effects on soil microbiome assembly during early succession in nature. Central early colonisers significantly (1) enhanced biodiversity (35%-40% richer communities), (2) reshaped trajectories of microbiome assembly and (3) increased recruitment of additional influential microbes by > 60%. In contrast, peripheral microbes did not increase diversity and were transient taxa, minimally affected by the presence of other microbes. This work elucidates fundamental principles of network theory in microbial ecology and demonstrates for the first time in nature that central microbes act as keystone taxa.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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 teacher head, 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".