Depth, sediment type, biogeography and high species richness in shallow-water benthos
Bibliographic record
Abstract
Until recently, quantitative data on the benthic fauna along the coast of Victoria, south-east Australia, were restricted to those few areas (potentially) receiving commercial and industrial effluent. Collectively, studies in these areas covered ~50 to 60 km of a coastline that extends for 1000 km. Recently, samples were taken from depths of 10, 20 and 40 m along the entire coast, and analysis of these made it possible to examine benthic community structure throughout the region. Species richness is high along the entire length of the coast, supporting the argument that species richness in temperate areas is not always higher in the deep sea than in shallow water. The major factor influencing species richness was depth. Although slightly more individuals were collected from stations at 10-m depth than from stations at 40-m depth, almost three times as many species were found at the deeper stations. Sediment type also influenced species richness. For the stations at 40-m depth, species richness was ~25% higher in medium and coarse sands than in fine sand. Pattern analysis suggested some bioregionalisation of the fauna, but the effect of geographical location on affinities among sample stations was much less than the effects of depth and sediment type.
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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 | 0.003 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".