Modeling the effective spawning and nursery habitats of northern pike within a large spatiotemporally variable river landscape (St. Lawrence River, Canada)
Bibliographic record
Abstract
Abstract Spawning and nursery habitats are often spatially disjunct as a consequence of specific life history stage habitat requirements and spatiotemporal habitat changes. Nevertheless, free‐swimming larvae originating from spawning habitats must reach productive nurseries to maximize survival. We examined spawning and nursery habitats of northern pike (Esox lucius) over the past 50 yr to investigate how habitat connectivity and hydrological variability interact to alter the distribution of effective spawning habitat. Habitat models coupled to a least‐cost approach were developed to quantify connectivity between habitats in two contrasting regions of the St. Lawrence River (Canada): a riverine corridor lake (~ 46 km) and a large fluvial lake (~ 48 km). Our simulations demonstrate that depending on hydrological conditions, between 3% to 51% of spawning habitat used by adults in the riverine corridor, and 22% to 90% in the lake, allowed larval survival up to the fifth week of development. Although rapid dewatering of spawning habitat is responsible for most spawning losses in the fluvial lake, increasing water currents were responsible for dispersing larvae away from suitable habitats in the riverine corridor. However, stable hydrological conditions led to spatial overlapping of spawning and nursery habitats favoring larval survival and growth. In addition, downstream larval dispersal by low water currents allowed larvae to reach spatially disjunct nursery habitat, especially in the lake. Our results indicate that despite the vast areas of potentially suitable habitats provided by large vegetated floodplains of fluvial lakes, the effective spawning habitats favoring early‐life recruitment are much more heterogeneous and variable both spatially and temporally.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".