INFERRING SHRIMP (PANDALUS BOREALIS) GROWTH CHARACTERISTICS FROM LIFE HISTORY STAGE STRUCTURE ANALYSIS
Bibliographic record
Abstract
An aged-based population model was used to simulate shrimp (Pandalus borealis Krøyer) age and stage structures at different growth rates and the results compared with stage structures of populations with known growth rates. Both simulations and field data indicate that different growth rates result in characteristic stage structures, which can be used to infer spatial and temporal differences in growth rates. It is concluded that the mean carapace lengths of all life history stages ordered chronologically (stage structure), contains more information on growth characteristics than the carapace length of individual stages (e.g., length at sex change, L50) alone. In the absence of growth information, based on direct ageing methods, it is recommended that the complete stage structure be used when inferring growth characteristics from carapace length data. In addition to allowing specific spatial and temporal comparisons of growth rates, stage structure analysis allowed inference of the following growth characteristics, including: growth rates are highly site specific and sensitive to environmental conditions such as food availability and temperatures; environmental influences on growth rates tend to affect all size categories (i.e., stages and ages) simultaneously and without time lags; the “invariant” relationship between L50 and maximum size (Lmax) is not unique to these stages and simply a consequence of environmental influences on the growth rate of all stages simultaneously; length at sex change is directly related to growth/metabolic rates; length and age at sex change are highly flexible, occurring at the age and size a shrimp happens to be when growth/metabolic rates determine sex change. The usefulness of stage structure analysis as an indicator of ecosystem change is discussed in light of the results.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.034 | 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 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".