Ontogenetic Patterns in Juvenile Blue Crab density: Effects of Habitat and Turbidity in a Chesapeake Bay Tributary
Bibliographic record
Abstract
Nursery habitats are characterized by favorable conditions for juveniles, such as higher food availability and lower predation risk, and dispropor-tionately contribute more individuals per unit area to adult segments of the population compared to other habitats. However, nursery habitat inference is complicated by changes in habitat preferences with ontogeny; individuals in early-life stages frequently inhabit different habitats than older juveniles or adults. In this mensurative field experiment, we modeled the density of two juvenile blue crab, Callinectes sapidus , size classes based on carapace width (CW) across multiple habitats at various locations within an estuarine seascape during the blue crab recruitment season. We examined four habi-tat types—unstructured sand, seagrass meadows, salt marsh edge (SME), and shallow detrital habitat (SDH). Results indicated that densities of small ju-venile blue crabs ( ≤ 15 mm CW) were highest in seagrass, whereas densities of larger juveniles (16–30 mm CW) were highest in SME. Densities of large juveniles in SME were also greater than those of small juveniles, suggest-ing possible secondary dispersal to SME by small juveniles after settlement and recruitment in seagrass. Turbidity was positively correlated with densi-ties of both size classes, although our model did not address whether this was due to top-down (refuge) or bottom-up (food availability) mechanisms. Ob-served patterns in size-specific habitat utilization may result from changing requirements of juvenile blue crabs with size, as animals minimize mortality-to-growth ratios. Taken together with previous work and patterns observed in SME, these findings emphasize the role of salt marsh habitat within juve-nile blue crab ontogeny and underscore the need to quantify and preserve the complete chain of habitats used by juveniles.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".