Chemical ecology and genetics of rough-skinned newts, Taricha granulosa
Bibliographic record
Abstract
Interactions between predator and prey have played a crucial role in adaptive evolutionary processes; however, phenotypic and genetic variation may also be driven by many other spatially variable biotic and abiotic factors. Rough-skinned newts, Taricha granulosa, possess a neurotoxin known as tetrodotoxin (TTX), which acts as an antipredator defense and was originally presumed to be a result of reciprocal coevolutionary interactions with resistant garter snakes across a geographic mosaic. In this thesis, I investigate several aspects of the chemical ecology and genetics of rough-skinned newts and consider how these factors play out on Vancouver Island, an interesting study region due to its isolation from mainland populations and recent non-native species introductions. By characterizing toxicity both within and among 23 populations of newts on Vancouver Island, I found significant variation in TTX and evidence for a previously unidentified hotspot, indicating selection pressures besides reciprocal coevolution may contribute to the observed patterns. Next, I present the first investigation into molecular mechanisms of tetrodotoxin expression in newts using an RNA-sequencing approach. By creating a de novo transcriptome assembly and annotation, I was able to identify novel differentially expressed genes putatively related to endogenous sources of TTX. Amphibians are also facing worldwide population declines due to factors such as negative impacts by non-native species, and Vancouver Island has experienced a recent introduction of signal crayfish and American bullfrogs. I reviewed the potential impacts of these species on rough-skinned newts and found a negative correlation between their presence and newt relative abundance, but no effect on body condition or toxicity. Using the aforementioned transcriptome assembly, I identified thousands of single nucleotide polymorphisms in 32 newts from BC and Oregon and characterized the population genetic structure at two spatial scales. Vancouver Island newts were found to belong to a cluster genetically distinct from Oregon with lower heterozygosity while displaying a lack of population structure across the island. Collectively, these results improve our understanding of the spatial variation and genetics of chemical defense in rough-skinned newts while integrating these findings with conservation implications for Vancouver Island populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".