The spatial patterns of bacterial communities in suspended particulate matter across the inner Great Barrier Reef
Bibliographic record
Abstract
Abstract Purpose Microbial communities play a significant role in maintaining the health of Great Barrier Reef (GBR) ecosystems, however, the influence of sediment composition and other environmental factors such as temperature and wave regime on microbial communities are largely unknown. Here we show how sediment composition and exposure influences bacterial communities across the inner section of the GBR (Cleveland Bay, Halifax Bay and Dunk Island) between 2016 and 2018. Materials and methods Sediment traps were installed and routinely deployed (~ every 3 months) at eight sites in the inshore GBR and analysed for water chemistry, sediment geochemistry and organic characteristics and associated bacterial communities. Results and discussion Results showed a significant variation in water turbidity, sediment collection rate and geochemistry across the trap sites. Bacterial communities also significantly varied along the inner GBR, with the shift in relative abundance of Actinobacteria, Acidobacteria, Planctomycete, Verrucomicrobia and Chloroflexi being the main cause of the bacterial community dynamics. The variation in spatial patterns of bacterial communities was highly correlated with water turbidity and the geochemical characteristics of associated sediments (e.g., K, Fe, Mn, Co, Al, Cr, Ca) collected across the marine trap sites. Conclusion Our findings indicate that sediment composition and collection rate (and linked water turbidity) can change the spatial patterns of bacterial communities by creating environmental gradients along the inner section of the GBR.
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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 | 0.000 | 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 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".