The role of dispersal and retention in the early life stages of shrimp in a lowland river
Bibliographic record
Abstract
This study investigated the importance of dispersal and retention processes during early ontogeny for three caridean shrimp species that complete their entire life history in freshwater. Directional traps were used to examine the small-scale movement patterns of shrimp into and out of nursery habitat patches (slackwaters) in a small lowland river in southeastern Australia. Movement patterns provided evidence for two contrasting life history based dispersal and retention strategies. For the two smaller atyid species, Paratya australiensis and Caridina mccullochi , the majority of larvae remained within the slackwater in which they were hatched until the final stage of development, at which point dispersal, either among slackwaters or out of slackwaters to faster-flowing pool and run habitats, occurred. For the larger palaemonid species, Macrobrachium australiense , larvae were hatched into slackwaters and dispersal occurred predominately during the first stage of larval development and then decreased as development progressed. Despite the differences in dispersal strategies among species, movement was mostly associated with a particular larval stage and thus emphasizes the importance of retention during critical developmental periods and of the potential impact that flow alteration could have on these and other species with similar life histories.
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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 | 0.000 | 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) | 0.001 | 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".