Maternal age effects on Atlantic cod recruitment and implications for future population trajectories
Bibliographic record
Abstract
Abstract Exploited fish populations frequently exhibit truncated age-structure. To address a basic question in fisheries science and conservation biology—how does age truncation affect population dynamics and productivity?—we explored the effect of age-structure on recruitment dynamics of ten stocks of Atlantic cod (Gadus morhua). Based on six alternative stock–recruitment relationships, we compared models that included and excluded maternal age-structure effects on recruitment. In all ten stocks, a recruitment model that included a maternal age-dependent effect was preferred over the standard Ricker model and in seven of the ten stocks, the preferred statistical model included a positive effect of either maternal age or mass on recruitment. Simulations comparing standard and maternal age dependent recruitment two decades into the future suggest that the inclusion of maternal age in recruitment models has little effect on projected biomasses. However, this similarity in biomass trajectory masked an increased sensitivity of populations with maternal age-dependent recruitment to stock age-structure. In particular, simulations with maternal age-dependent recruitment responded strongly to changes in fishing mortality on the oldest age classes, while simulations using standard recruitment models did not. Populations with maternal age-dependent recruitment can exhibit increased biomass catch even if fishing mortality on older individuals was reduced. Overall, simulations suggested that the influence of maternal age on population dynamics are more nuanced than suggested by previous research and indicate that careful consideration of the effects of age-structure on populations may lead to substantially different fisheries management reference points—particularly with respect to age-specific fishing mortality—than classical models. While these results suggest a link between maternal age and population productivity, future research requires the incorporation of biologically reasonable and empirically defensible mechanisms to clarify the effect of age on population dynamics.
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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 | 0.001 | 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) | 0.000 | 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 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".