Assembly and co-occurrence networks of nitrogen-fixing bacteria associated with epiphyllous liverworts in fragmented tropical forests
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Understanding the spatial dynamics of plant-associated microbial communities is increasingly urgent in the context of habitat loss and the biodiversity crisis. However, the influence of reduced habitat size and connectivity on the assembly mechanisms underlying microbial associations is fundamental to advancing microbial ecology and conservation. In the Brazilian Amazon, we investigated nitrogen-fixing (diazotrophic) bacterial communities associated with two epiphyllous liverworts, Cololejeunea surinamensis and Radula flaccida, across 11 forest sites within the Biological Dynamics of Forest Fragments Project landscape. Using amplicon sequencing targeting the nitrogenase gene (nifH), we characterized diazotroph community diversity, inferred assembly mechanisms through null models, and analyzed co-occurrence network structure. Host-specific associations were evident: C. surinamensis predominantly hosted Hassallia, while R. flaccida was primarily associated with Fischerella. Despite habitat fragmentation, diazotrophic richness and composition remained similar across habitats of different sizes, consistent with strong homogenizing dispersal. Network analyses revealed that smaller fragments harbored more modular communities with fewer module hubs, pronounced shifts in key species relative abundance, and reduced network robustness. Our findings underscore the influence of habitat size on the stability of liverwort-associated diazotrophs, with smaller fragments exhibiting lower key species specificity and disruption of microbe-microbe interactions. Our results emphasize the importance of conserving large, connected forest habitats to maintain the functional integrity of phyllosphere N-fixing microbiota.
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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 | 0.000 | 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 it