Biofouling sponges as natural eDNA samplers for marine vertebrate biodiversity monitoring
Bibliographic record
Abstract
Environmental DNA (eDNA) analysis has now become a core approach in marine biodiversity research, which typically involves the collection of water or sediment samples. Yet, recently, filter-feeding organisms have received much attention for their potential role as natural eDNA samplers. While the indiscriminate use of living organisms as 'sampling tools' might in some cases raise conservation concerns, there are instances in which highly abundant sessile organisms may become a nuisance as biofouling on artificial marine structures. Here we demonstrate how a sea sponge species that colonizes the moorings of the world's largest curtain of hydroacoustic receivers can become a powerful natural collector of fish biodiversity information. By sequencing eDNA extracted from Vazella pourtalesii retrieved from moorings during routine biofouling maintenance, we detected 23 species of marine fish and mammals, compared to 19 and 15 species revealed by surface and bottom water eDNA respectively, and 28 species captured by groundfish survey in the surrounding area, which are more ecologically impactful and involve higher additional costs. Sponge-based species inventories proved at least as informative as those obtained by traditional survey methods, and are also able to detect seasonal differences in fish assemblages. We conclude that opportunistic sampling of marine sponge biofouling may become an efficient way to document and monitor biodiversity in our rapidly changing oceans.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".