Morphological variation over ontogeny and environments in resource polymorphic arctic charr (<i>Salvelinus alpinus</i>)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natural selection requires genetically based phenotypic variation to facilitate its action and cause adaptive evolution. It has become increasingly recognized that morphological development can become canalized likely as a result of selection. However, it is largely unknown how selection may influence canalization over ontogeny and differing environments. Changes in environments or colonization of a novel one is expected to result in adaptive divergence from the ancestral population when selection favors a new phenotypic optimum. In turn, a novel environment may also expose variation previously hidden from natural selection. We tested for changes in phenotypic variation over ontogeny and environments among ecomorphs of Arctic charr (Salvelinus alpinus) from two Icelandic lakes. Populations represented varying degrees of ecological specialization, with one lake population possessing highly specialized ecomorphs exhibiting a large degree of phenotypic divergence, whereas the other displayed more subtle divergence with more ecological overlap. Here we show that ecomorphs hypothesized to be the most specialized in each lake possess significant reductions in shape variation over ontogeny regardless of environmental treatment suggesting canalized development. However, environments did change the amount of shape variation expressed in these ecomorphs, with novel environments slowing the rate at which variation was reduced over ontogeny. Thus, environmental conditions may play an important role in determining the type and amount of genetically based phenotypic variation exposed to natural selection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 it