Size-based dynamics of a demersal fish community: modeling fish-fisheries interactions
Why this work is in the frame
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Bibliographic record
Abstract
This thesis defends a holistic approach to fish dynamics, supports size as a factor \ndetermining functional groups in a community, and presents a model that can serve as a \nframework for the integration of biological knowledge of fish communities with decision-making \nabout resource exploitation. \nWe discuss the aspects that should be considered to approach the study of fish \nspecies dynamics. In their natural environment fish species dynamics are influenced by \nthe presence of other species. Interacting species form a community that lies at the core of \nthis thesis. Fishery and survey data show drastic changes in the Newfoundland demersal \nfish community during the period from the late 70s to the early 90s. \nWe use these changes to analyse size as an indicator of species response to \nfisheries. We find that size at the community level can substitute for species to determine \nfunctional groups that direct community dynamics. \nThis size-based approach shows properties of the community that cannot be \nexplained by looking at each single species one at a time. Thus, a size-based simulation \nmodel is built to analyse long-term community dynamics and its response to fisheries. \nThe model has only three simple assumptions: (1) fish pass through a series of age-determined \nsize classes through their life history, (2) big fish eat little fish, and (3) \npredation cannot drive species to extinction. The model is stable over runs of centuries, \nand from a stabilized state can be used to explore several scenarios involving \nenvironmental and fishery disturbances.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it