Benthic habitat mapping of the glass sponge (<i>Vazella pourtalesii</i>), and associated community composition on Sambro Bank, Scotian Shelf, Canada
Bibliographic record
Abstract
Sponges have been identified as ecosystem engineers, providing habitat structure for many other benthic organisms, but are vulnerable to the impacts of bottom contact fishing. The Sambro Bank Sponge Conservation Area (SBSCA) protects a globally unique aggregation of the glass sponge ( Vazella pourtalesii) off the east coast of Canada. Here, we present the first comprehensive, high-resolution mapping study of this site. Multispectral multibeam echosounder (MBES) mapping at three operating frequencies and 12 benthic drop camera stations were conducted at the SBSCA in 2022. Video data were analysed to record the presence and location of V. pourtalesii, and extracted still images were used to quantify all benthic fauna and sediment characteristics for each station. Using the MBES backscatter data sets as predictor variables, the study created a generalized linear mixed model of V. pourtalesii presence in the SBSCA, with 90.1% accuracy. Four seafloor benthoscape classes were identified (hard substrata, mixed substrata, sand/mud substrata, and sand/mud veneer) from the video imagery, with statistically distinct benthic macrofaunal communities associated with each class. The study creates a baseline assessment of the current community composition and habitat characteristics of the site, which can be used for future ecological monitoring and management.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".