Megabenthic biotope composition of the Rockall Escarpment, Northeast Atlantic
Bibliographic record
Abstract
The depths of the ocean have been largely shrouded in the unknown. However, technological advances made in the past 60 years have provided researchers with the opportunity to start unravelling the complexities of the deep sea. There is now an understanding that the deep sea is host to a complex and diverse mosaic of communities that we also realize are in peril due to the effects of climate change. This thesis examined the biodiversity patterns and biotope composition present within the Rockall Escarpment, situated in the Northeast Atlantic Ocean. We used data that was annotated from images across nine transects, totalling to 16,150 m, obtained by a Remotely Operated Vehicle. Benthic community composition was assessed across the whole study area using Non-Metric Multidimensional Scaling (nMDS), followed by SIMPER, and indicator species analysis to classify the benthic taxa observed into biotopes. In total, 59,418 individual organisms representing 199 megafaunal morphospecies were analyzed. Twelve biotopes were identified, biotopes five, six, nine, and twelve composed of vulnerable sessile taxa including the cold-water corals Solenosmilia variabilis, Madrepora oculata, and Desmophyllum pertusum. Substrate, food availability and currents are among the most significant factors influencing the complex geomorphology and consequently, the distribution of megafaunal species. Determining the megafaunal species richness and abundance present, and the factors that affect their distribution, provide insights into vulnerable biotopes. Understanding the vulnerable biotopes present will ultimately contribute to our baseline knowledge of the distribution of taxa in the Northeast Atlantic and hopefully, management measures that are climate adaptive.
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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 | 0.000 | 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) | 0.001 | 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".