Functional response shift and opportunistic predation of northern shrimp (Pandalus borealis) by redfish (Sebastes sp.) under prey rarefaction and environmental change
Bibliographic record
Abstract
The Gulf of St. Lawrence (GSL) is a semi-enclosed sea located in Atlantic Canada, which is warming rapidly. Redfish, a complex of two morphologically similar, demersal fish species ( Sebastes mentella and S. fasciatus ), have drastically increased in biomass after two decades of low biomass. Meanwhile, several cold-water species, such as the northern shrimp ( Pandalus borealis ), are collapsing. The latter is an important prey for redfish and, in addition to a temperature-driven shrinking habitat, they are likely suffering from an increase in predation pressure. To better understand the trophic dynamics between these key species of the GSL, we studied their functional response. Functional responses describe how the rate of consumption of a resource by a consumer changes with the resource’s density, providing precious insights on the energy flow between the two species and the stability of their dynamics. Using Generalized Additive Models, we show that redfish currently exhibit a type III functional response towards northern shrimp, associated with a predation pressure that decreases at low shrimp densities. This type of response is known to have a stabilising effect on population dynamics and might mitigate redfish impact on shrimp populations. Furthermore, this response evolved between the 1990s and the 2010s, suggesting a possible adaptation of redfish to their changing environment. Our models also showed significant negative effects of warming environmental conditions as well as trophic competition on shrimp consumption by redfish and confirmed the importance of predator size on their feeding habits, as observed in previous studies.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".