Mate Preference and Larval Growth of Great Lakes Sea Lamprey (Petromyzon Marinus) in a Warming Climate
Notice bibliographique
Résumé
Sea lamprey (Petromyzon marinus) are parasitic pests in the Great Lakes. Once sea lamprey started to have a negative impact on important game fish populations, management efforts began. More information on how sea lamprey choose mates and how larval sea lamprey grow could give more insight on how to better manage their populations. Increased temperatures due to global climate change may result in increased growth of individuals, higher count of eggs, higher quality of eggs, and higher sperm production. I presented an average-sized ovulating female with the choice of a small or large spermiating male in a two-way mate preference experiment. Trials were conducted and investigated whether stream side bias, male or female activity, or the presence of male odor upstream affected the female’s preference. Results showed the female sea lamprey had a mesocosm side bias and females preferred to be in front of the small male when male odor was released. Improving the accuracy of larval sea lamprey growth models would benefit management strategies by providing better predictions as to when metamorphosis could occur. The primary technique used to establish growth of sea lamprey within the control program is the use of an incomplete growing degree day (GDD) metric, where average daily growth across a latitudinal gradient during the warmer months is used to predict time of metamorphosis. I tested a complete GDD metric in which the number of year-round growing degree days for each age-class of sea lamprey population tested was calculated. Water temperatures were obtained as much as possible during the larval growth time frame for each stream examined. For streams in which I did not have water temperature, I placed data loggers in streams to record the temperature every hour for one year. Air temperatures were then obtained from weather station locations closest to the mouth of the river for the same year. A relationship between the air and water temperature for each stream was established from this year’s data. Air temperature were then obtained from weather stations closest to each stream during the periods of larval growth, and air temperature was used to predict water temperature larval sea lamprey experienced. A generalized linear model was used to determine the relationship between the response variable, lamprey length-at-age, and one or more predictors, which included log-transformed GDD, log-transformed calendar days, stream, and lake. The best fit model, which used basin wide data, was log-transformed calendar days and lake. The results show that GDD was the best predictor for Lake Ontario and calendar days were the best predictor for Lakes Huron and Michigan to determine growth of sea lamprey. Calendar days and GDD both predicted length-at-age for Lake Superior populations equally well.
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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) | 0,000 | 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) | 0,000 | 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 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 ».