Habitat choice promotes and constrains phenotypic plasticity
Bibliographic record
Abstract
Habitat choice can either speed up or slow rates of phenotypic evolution, depending on which trait is measured. We suggest that habitat choice plays an analogous, and generally overlooked, role in shaping patterns of phenotypic plasticity. Using our work with an amphibious fish, we discuss two case studies that demonstrate how habitat choice can both promote and constrain expression of plasticity. First, habitat choice during the dry season accentuates adaptive metabolic plasticity and minimizes maladaptive changes to muscle, ultimately increasing survival time out of water. Second, a trade-off between water- and air-breathing drives matching habitat choice, resulting in positive feedback that reinforces respiratory specialization and environmental preference. Overall, these case studies demonstrate that we must consider the interactions between plasticity and habitat choice to fully understand how animals survive in the face of environmental change. Without considering both processes simultaneously, the performance of animals in challenging conditions can be either under- or over-estimated. Finally, because habitat choice shapes the frequency and predictability of environmental changes that animals experience, feedback between habitat choice and expressions of phenotypic plasticity may be an important factor that influences how plasticity evolves.
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.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".