Multiscale investigations into the thermal habitat use and conservation of Arctic grayling (Thymallus arcticus) in the Parsnip River watershed, Canada
Notice bibliographique
Résumé
,The drivers of the abundance and distribution of riverine species are often multiscale; they depend on both the local heterogeneity of habitats within the river and the context of the larger landscapes through which they flow. Methodological constraints can limit the ability of river ecologists to conduct studies over large scales, often producing results over fine scales that must then be extrapolated over unsampled units. Multiscale sampling approaches have been increasing in riverine studies, but the applications of their findings to conservation management – which operates over its own scales – are not always clear. In this dissertation, I investigate the use of physical and thermal habitats by Arctic grayling (Thymallus arcticus) at the reach, river, and watershed scales. Through experiments and observational studies, I investigated how this species used habitats in a degraded watershed. As a component of my research, I developed new statistical models that were parameterized with data from acoustic telemetry and applied new approaches using drone technology. Results from those models will allow fisheries ecologists to better understand the distribution of fish in river networks. I found strong associations between the distribution of Arctic grayling and pool habitats at the reach and river scales, and nonlinear relationships with temperature at the reach (11.0–16.0 °C) and watershed scales (11.1–17.1 °C). Unexpectedly, I found that the combination of upstream distance and pool habitats were a stronger predictor of Arctic grayling abundance than temperature at the river scale. This was explained by the fact that upstream distance accounted in part for the effects of temperature but also likely explained variation in other important predictors of Arctic grayling abundance (e.g. forage density, site fidelity, and territoriality). I quantified a thermal preference range (10.1–13.0 °C) for Arctic grayling in the laboratory and related this metric to the in-situ thermal habitat use of tagged but free-ranging individuals to determine the effectiveness of behavioural thermoregulation as a strategy for maintaining body temperature. I found that Arctic grayling used behavioural thermoregulation to effectively maintain their body temperatures during their summer feeding window, that heat transfer in Arctic grayling was slightly more efficient when cooling than warming, and that heat transfer was more rapid in smaller fish. I found novel evidence that Arctic grayling may be single-direction thermoregulators that will invest energy into cooling but not into warming. Contrary to my expectations, I found that the effectiveness of behavioural thermoregulation was more strongly related to thermal heterogeneity in time (along diel and seasonal axes) than in space. My findings related to the thermal ecology of Arctic grayling emphasized the continued conservation of coldwater-producing habitats (i.e. headwaters). I also found through my reach and river-scale studies that additional conservation of highly structured instream habitats that support thermal refugia and feeding opportunities across local scales would support better outcomes for the conservation of this population. I identified potential future risks, namely territoriality and dominance hierarchies that may keep Arctic grayling from leaving unfavorable thermal habitats during heatwaves.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».