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Enregistrement W3098661658 · doi:10.22215/etd/2020-14288

Sociality in caterpillars: Investigations into the mechanisms associated with grouping behaviour, from vibroacoustics to sociogenomics

2020· dissertation· en· W3098661658 sur OpenAlexaff
Chanchal Yadav

Notice bibliographique

Revuenon disponible
Typedissertation
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueInsect and Arachnid Ecology and Behavior
Établissements canadiensCarleton University
Organismes subventionnairesnon disponible
Mots-clésInstarBiologySocialityLarvaLepidoptera genitaliaCaterpillarZoologyEcology

Résumé

récupéré en direct d'OpenAlex

Social grouping is widespread among larval insects, particularly in a number of phytophagous larval Lepidoptera (caterpillars).Although the benefits of social grouping are widely recognized, the proximate mechanisms mediating grouping behaviour, such as group formation and maintenance, are poorly understood.My Ph.D. thesis takes a pioneering approach to understanding these mechanisms, specifically, by studying the roles of vibroacoustics and sociogenomics, using the masked birch caterpillar, Drepana arcuata (Lepidoptera: Drepanoidea), as a model.There are two main objectives of my thesis -(i) to test the hypothesis that caterpillars employ plant-borne vibratory signals to recruit conspecifics to social groups; and (ii) to test the hypothesis that differential gene expression is associated with developmental transitions from social to solitary behavioural states.For the first objective, I documented morphological and behavioural changes in the larvae, showing that there are five larval instars, and developmental changes in social and signalling behaviour.Specifically, early instars (I, II) live in small social groups, and late instars (IV, V) live solitarily, with third instars (III) being transitional.Instars I-III generate four signal types (AS, BS, MS, MD), instars IV, V generate three signals (AS, MS, MD).I then used an experimental approach to test if early instars employ vibrations during social recruitment, and found that vibratory signals are used to advertise feeding and silk shelters, leading to recruitment, with higher signalling rates resulting in faster joining times by conspecifics.For the second objective, comparative transcriptomic analysis indicates that there are 3300 transcripts differentially expressed between early (social) and late (solitary) instars, and these include transcripts potentially coding for candidate 'social' genes.One of these genes-an octopamine receptor gene-was further functionally tested using RNAi, iii and preliminary results suggest that its reduced expression is associated with hastened social to solitary transition.As this research contributes the first genomic data on an entire lepidopteran superfamily (Drepanoidea), I also assembled a draft genome of D. arcuata.The research is the first to test hypotheses on the roles of vibrational signalling and genomics in the social behaviour of larval insects, many of which are of great economic and ecological importance.the day I walked into her office with an international undergrad degree (and all the complications that go into applying to grad school with that), she has been wonderful mentor, providing tremendous support in everything that I pursued, both as a researcher and as an individual.Not only did she put phenomenal work in to helping me with my research, but also, she always encouraged me and provided me with numerous opportunities and support to present my work at different platforms.Thank you for always providing the opportunity to work with you, for believing in me, making me realize my true potential, for always pushing me to succeed, to strive for excellence, for all the cheers, for picking me up every time I was down, the list is endless!Having her as a supervisor made grad school such a wonderful experience for me that I will cherish forever.She has played the biggest role in my 'metamorphosis', both as a researcher as well as a person.I will always remember her words "hard work + perseverance= success".With all the personal and professional advices that I have received from you over the years, I can safely assume you're like my second mother who always has my best interests at heart.A big thanks goes to Dr. Myron Smith (committee), for his invaluable support, constant guidance and encouragement throughout my doctorate.Thank you for helping me with all the molecular work in lab, in finding things in your lab, for the honey that you 'stole' from bees, and for always coming up with new experimental ideas to try with drepanids, which reminds me we should really finish those pesticide trials.Thanks to Dr.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
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 enseignants0,002
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,012
Tête enseignante GPT0,248
Écart entre enseignants0,236 · 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

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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