Factors determining the abundance, distribution and population size–structure of the penshell<i>Pinna carnea</i>
Bibliographic record
Abstract
Surveys conducted in the south-western Dominican Republic showed that the penshellPinna carneais a consistent component of seagrass beds and is absent in adjacent sandflats. Population densities were low (0.012–0.076·m−2) and the size–structure skewed towards large individuals. Trials with different types of substrata in caged spat collectors, involving a combination of sand, seagrass blades and roots, and an artificial treatment by itself, indicated no settlement preference for any of the substrata tested. Comparison of additional spat collectors (caged and uncaged) indicated high predation losses (84%) for recently settled penshells. Experiments with penshells measuring 10–30, 50–70 and 90–110 mm (anterior to posterior dorsal tip) transplanted to plots in a seagrass bed and sandflat showed that predation losses decreased with increasing size and were much less in seagrass than in the sandflat. In 10-day trials, survival in the three size-groups was 27-fold greater in the seagrass bed than on the sandflat. During 3-day trials in the sandflat, survival increased from 6% for 50–100 mm penshells to 93% for 150–170 mm penshells. At the end of 100-day trials, during which the study area was subjected to Hurricane Dennis, the only surviving penshells were large individuals (90–110 mm) that had been transplanted to the seagrass bed. All individuals transplanted to the sandflat went missing. Growth measurements showed that small penshells grow rapidly (up to 2.2 mm·d−1), but the growth rate drops markedly at ~150 mm. Rapid juvenile growth may be a strategy for reducing the period of high vulnerability to predators. The high proportion of large individuals in the population likely represents the accumulation of successive recruitments as growth slows in older penshells.Pinna carneais mainly restricted to seagrass beds because they provide more protection from predators than adjacent habitats. Moreover, the consolidation of sediments in seagrass beds by roots and algal rhizoids provides a degree of protection from physical disturbances such as hurricanes. The advantages provided by the seagrass habitat come at a cost because we detected a mortality factor in the seagrass bed (possibly related to the ~3-fold higher silt load) that was absent on the sandflat.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".