The effect of turbulence on survival, dispersal, and swimming behavior of grass carp eggs and larvae
Notice bibliographique
Résumé
There is an urgent need to monitor and control the spread of invasive grass carp (Ctenopharyngodon idella) in North America. Grass carp are reproducing in tributaries to Lake Erie and control efforts targeting reproduction are greatly needed. Current strategies for their control and removal are costly and report mixed degrees of efficacy. However, an alternative way to monitor and control their spread consists of increasing capture and mortality rates during early life stages (i.e. eggs and larvae stages) when they are more susceptible to damage via enhanced flow turbulence levels and altered flow conditions. In order for these alternative strategies to be effective, is necessary to study the physics underlying the movement of eggs and larvae in streamflow, and to quantify the turbulence thresholds that trigger those behavioral and physiological effects.\nThis study examines how early-life-stage grass carp interact with turbulent flows, how turbulence affects their survival, and whether turbulence-based control methods could work. An extensive series of laboratory experiments were conducted with live grass carp eggs and larvae in a grid-stirred turbulence tank and in a race-track flume to: a) explore the effect of turbulence intensity on egg mortality, and b) to document the behavioral response of grass carp larvae to spatially-variable, turbulent flows. \nA turbulence intensity threshold was identified, above which egg mortality substantially increased due to short- (10 seconds) and long-term (5 minutes) exposure at different turbulence levels. Larvae actively responded to changes in turbulence intensity and shear stresses produced by obstructions in the flow (e.g. rocks, piers, and submerged vegetation), avoiding areas of high shear and seeking low-turbulence, low-vorticity regions. These swimming capabilities were quantified by estimating burst swimming speeds and were correlated with the spatial distributions of turbulent kinetic energy, vorticity, and Reynolds stresses for future predictions of larvae dispersion on natural streams.\nThis study produced a unique and extensive data set that may allow for the development of turbulence-based control methods for grass carp. Such control methods could include increasing egg mortality by increasing turbulence intensity through temporary and permanent in-stream structures or using natural or modified hydrodynamics to attract, guide, and aggregate larvae at predefined control points for collection or extermination.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| 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) | 0,001 | 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 tête enseignante, 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 ».