Tracing the evolution of key traits in dorid nudibranchs
Bibliographic record
Abstract
Reconstructing trait evolution is critically important for elucidating the processes generating biodiversity. However, this work is in its infancy in non-model clades for which we lack a basic understanding of their ecology and biology. Here, we compile information about prey preference, chemical acquisition and colour pattern in dorid nudibranchs (Nudibranchia: Doridoidei) and reconstruct their ancestral states using a multi-gene phylogeny to investigate the evolution of these key traits. Our analyses show that the most recent common ancestor (MRCA) of Doridoidei preferred sponge prey from which they sequestered metabolites, and subsequent shifts to different prey types and de novo synthesis of defensive compounds occurred multiple times independently across the phylogeny. Additionally, the MRCA likely exhibited complex colour patterns, including spots or stripes, with uniform morphotypes evolving in most families. Despite the fact that many dorid nudibranchs derive both metabolites and pigments from their prey, we found no evidence of correlated evolution amongst these traits. As part of this work, we present a multi-gene phylogeny for Doridoidei with representatives from 88 genera and 18 families, but there remain issues with poor support across the tree. Nonetheless, for the first time, we explore the evolution of key traits that contributed to the diversification of dorid nudibranchs, highlighting the need for more refined trait data and greater phylogenetic resolution for future work.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".