A study of green crab (Carcinus maenas) interactions, cannibalism, and a first approach to model the effects of harvesting on its populations
Notice bibliographique
Résumé
Green crabs (Carcinus maenas) have been extensively studied because of the negative impacts that they have on the ecosystems that they invade. However, there are still substantial gaps of knowledge about their interactions and population dynamics. As green crabs continue to invade new locations, it is important to gain a deeper understanding of these subject areas in order to prevent or mitigate further introductions or spread. This thesis aims to address these knowledge gaps by focusing on two main topics: (1) green crab predator-prey interactions with smaller conspecifics and a native counterpart, the mud crab (Dyspanopeus sayi), and (2) a first attempt using a model to predict green crab population dynamics and the potential effects of a removal program.\nFirst, I analysed long-term observational beach-seine data collected from the southern Gulf of St. Lawrence, and found that there was a negative association between native mud crabs and green crabs in this area. Then I used laboratory experiments to examine their predator-prey interactions and assessed the influence of habitat complexity on the outcome of these interactions. I found that green crab predators consumed almost twice as many mud crabs compared to juvenile green crabs in the two less structured habitats (no substrate or sandy substrate), but predation rates were statistically similar in oyster bed habitat. This study found that mud crab mortality was significantly affected by habitat type, whereas green crab mortality was not. I then focused on green crab cannibalism by adults on juveniles with similar laboratory experiments. In this study, I included habitat types that represented a wider range of structural complexity, and found that cannibalism rates declined with increasing habitat complexity. I also conducted field inclusion experiments that gathered similar results, though the differences were not significant.\nI identified knowledge gaps and areas of future research by gathering all the available information about green crab life stages. This population information was used to build a relatively simple stage-based population matrix model for green crabs. The outcome of the model estimated that a theoretical green crab population could increase by approximately 43%. The outcome of this model also suggested that even if adult survival is set to zero (representing intensive trapping and effective removal of adults), the population was still able to grow because numbers in the other life stages were abundant enough to feed and maintain the population growth rate. These results suggests that current removal programs that catch mostly adults have little-to-no effect on the population growth rate, indicating that harvesting alone is unlikely to result in a reduction of annual green crab abundance.
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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) | 0,001 | 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 | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».