Cryptofauna associated with rhodoliths: Diversity is species‐specific and influenced by habitat
Bibliographic record
Abstract
Abstract Rhodoliths are recognised as providing critical ecosystem services in nearshore systems through habitat provision. We tested the influence of rhodolith hosts and habitat on the diversity and composition of sessile and motile invertebrates found associated with two species of rhodolith. Investigations of cryptofauna were undertaken at three beds within the Bay of Islands, northern New Zealand. Lithothamnion crispatum , which was smaller in overall size, and had less free space and a smaller internal volume than Sporolithon sp., provided habitat for more species of distinct life forms, both motile and sessile species, than Sporolithon sp. Although there were few differences in the dimensions of L . crispatum found in the beds, there was significantly more free space available in Sporolithon sp. rhodoliths found in one of two beds where it occurred, and the associated cryptofaunal richness of both sessile and motile species was significantly higher in this population. This study revealed species‐specific differences in the rhodolith‐associated cryptofauna and a significant impact of rhodolith habitat on growth form and cryptofaunal assemblages at the sites investigated in one of the host species ( Sporolithon sp.). Understanding interactions between species and habitats provided by rhodoliths is critical to understanding the nature of ecosystem services provided in these biogenic habitats.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".