MétaCan
Menu
← Retour à la cohorte
Enregistrement W4241351756 · doi:10.22215/etd/2016-11416

Behavioural and physiological ecology of coastal marine fish: basic and applied perspectives

2016· dissertation· en· W4241351756 sur OpenAlexafffund
Jacob W. Brownscombe

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueCoral and Marine Ecosystems Studies
Établissements canadiensCarleton University
Organismes subventionnairesNatural Sciences and Engineering Research Council of CanadaOntario Federation of Anglers and HuntersFisheries Society of the British IslesBonefish and Tarpon TrustPuerto Rico Sea Grant, University of Puerto Rico
Mots-clésEcologyEnergeticsHabitatGeographyCoral reefFisheryEnvironmental scienceBiology

Résumé

récupéré en direct d'OpenAlex

Energy is the currency of life, by which we can measure how ecological and anthropogenic factors influence individual fitness, scaling up to population and ecosystem dynamics.Energy is expended and gained by organisms through diverse behavioural tactics aimed at maximizing fitness.My overarching hypothesis for this dissertation is that ecological and anthropogenic factors influence animal behaviour and energetics.I tested this hypothesis in two coastal marine fish species, bonefish (Albula vulpes) and great barracuda (Sphyraena barracuda) using a combination of field studies and controlled experiments.In the wild, landscape features had the greatest impact on bonefish activity and energy expenditure at both fine (i.e., between habitats on a single coral reef crest) and broad (i.e., between coastal habitats and regions) spatial scales.Diel period, water temperature, and tide state also influenced bonefish behaviour and energetics, with some consistent patterns across environments, including greater activity and energy expenditure during the day, as well as ebbing and low tides.Bonefish activity levels and habitat selection also corresponded with temperature-related physiological performance.Comparing two disparate coastal ecogeographic regions, activity-and temperature-based estimates of bonefish energy expenditure were higher in the fringing coral reefs of tropical Culebra, Puerto Rico than the expansive sand flats of sub-tropical Eleuthera, The Bahamas; however, home ranges were significantly larger in Eleuthera than Culebra, which likely has significant energetic costs that may contribute to differences in growth rates between the regions.From a more applied perspective, a common anthropogenic stressor, recreational angling, caused significant locomotory (i.e., iii swimming capabilities) and behavioural (i.e., refuge use) impairment in bonefish and great barracuda, which resulted in increased post-release predation risk.Retaining bonefish for a short period prior to release reduced this impairment and may be a useful strategy for improving post-release survival in environments with high predator burden.Collectively, by examining how ecological and anthropogenic factors influence fish behaviour and energetics, my dissertation has advanced our understanding of fundamental ecology and management of coastal marine fish and their ecosystems.provided me is truly remarkable.They have taught me not only the fundamentals of science, but also the value and skills of social networking, extracurricular activities, science outreach, striking a healthy work-life balance, and how to acquire research funding and scholarships.Since the beginning they treated me not simply as a student, but as a colleague, and their faith in my abilities has strengthened my confidence as a scientist, enabling me to accomplish far more than I could have ever imagined in these past 4 years.I also extend my gratitude to my thesis committee members, Sue Bertram and Pat Walsh, as well as my comprehensive exam external Gabriel Blouin-Demers and dissertation defence examiners Nann Fangue and Murray Richardson, who contributed positive feedback and constructive criticism that helped shape this thesis and contributed to my development as a scientist.They are all busy people, but still took the time to provide critical input to my work while asking for nothing in return, for which I am very thankful.Thank you my partner Caitlin Higginson and my entire family for their unconditional support.I would not do the work that I do had I not grown up fishing and v exploring the wilderness with my father and grandfather.My mother imparted in me a level of determination that is certainly required to spend 10 years in post secondary education.Without the support of Caitlin, there is no way I would have been as productive as have been in these past years.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,021

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0020,003
Études des sciences et des technologies0,0010,003
Communication savante0,0020,002
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,220
Écart entre enseignants0,207 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2016
Routes d'admission2
Résumé présentoui

Explorer davantage

Même sujetCoral and Marine Ecosystems Studies→Travaux en français237 207→