Connectivity of sponge grounds in the deep sea: genetic diversity, gene flow and oceanographic pathways in the fan-shaped sponge Phakellia ventilabrum in the northeast Atlantic
Bibliographic record
Abstract
Little is known about dispersal in deep-sea sponges, yet understanding patterns of gene flow and connectivity is essential for their effective management. Given rising pressure from harmful anthropogenic activities, schemes that manage resource extraction whilst conserving species diversity are increasingly necessary. Here, we used ddRADseq derived SNPs to investigate the genetic diversity and connectivity for the deep-sea sponge Phakellia ventilabrum across the northeast Atlantic Ocean (from the Cantabrian Sea to Norway). The analysis of 166 individuals collected from 57 sampling stations were grouped into 17 different areas, including two MPAs, one SAC and other areas with different levels of protection. The 4,017 neutral SNPs we uncovered indicated high connectivity and panmixis amongst the majority of areas, spanning a ca. 2,500-kilometre range and depths of 99–900 m. This was likely due to the presence of strong ocean currents aiding larval transport, as supported by our migration analysis and also by 3D particle tracking modelling using information on the reproductive cycle of P. ventilabrum . We also observed significant genetic similarity between samples from the Cantabrian Sea and Roscoff (France) as compared to the remainder of the collection areas, likely arising from physical drivers such as prevailing current circulation patterns and topographic features, acting as barriers for gene flow. Despite this, our results suggest that all protected areas studied are well connected with each other. The relatively low genetic diversity observed in all areas, though, highlights the potential fragility of this species to changing climates, which might compromise resilience to future threats.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".