Sociality in caterpillars: Investigations into the mechanisms associated with grouping behaviour, from vibroacoustics to sociogenomics
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".