Concordance spatiale entre les empreintes élémentaires des otolithes de poissons et les eaux du bassin versant du Saint-Laurent, Canada
Bibliographic record
Abstract
L’hétérogénéité physique et chimique des grands écosystèmes fluviaux génère des mosaïques d'habitats répondant aux besoins variés des poissons, qui abrite diverses communautés de poissons. Pour effectuer une gestion durable des pêcheries, il faut comprendre la structure des populations de poissons exploités et la connectivité entre les habitats. L’objectif de ce mémoire était de développer une carte de référence des empreintes élémentaires des otolithes dans le système du Saint-Laurent (Canada), en comparant les concentrations en éléments traces dans l'eau et les otolithes de poissons. Pour ce faire, 136 échantillons d'eau et 930 poissons de 21 espèces ont été prélevés dans 16 affluents et différents habitats du Saint-Laurent. Les résultats révèlent des compositions en éléments traces très variables spatialement, dans l'eau et dans les otolithes. Les variations des concentrations en Sr et Ba étaient suffisamment marquées pour assigner avec précision les poissons à leur région de capture et montrer des variations entre les familles de poissons. Ce travail ouvre la possibilité de se référer directement à la chimie de l'eau pour effectuer une assignation géographique, sans passer par les otolithes. L'élaboration de cette carte de référence des empreintes élémentaires est fondamentale pour comprendre la structure des populations de poissons, valider la connectivité de certains habitats, ou encore retracer l’historique des habitats empruntés par des espèces envahissantes. \n \nThe physical and chemical heterogeneity of large river ecosystems generate mosaics of habitats, that meet the various needs of fish and support diverse fish communities. Understanding the structure of exploited fish population and the connectivity between habitats is necessary for sustainable management of fisheries. The objective of this thesis was to develop a reference map of otolith elemental fingerprints in the St. Lawrence River (SLR; Canada), by comparing trace element concentrations in water and fish otoliths. To do so, 136 water samples and 930 fish of 21 species were collected in 16 tributaries and various habitats of the SLR. The results revealed highly variable trace element compositions spatially, in water and in otoliths. However, Sr and Ba concentrations were sufficiently high to accurately assign fish to their capture region, and show variations between fish families. This work opens the possibility of referring directly to water chemistry to make a geographic assignation, without going through otolith. The development of this elemental fingerprint reference map is fundamental to understanding the structure of exploited fish populations, validating the connectivity of certain habitats, or tracing the history of habitats used by invasive fish species.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".