Integrating patterns of thermal tolerance and phenotypic plasticity with population genetics to improve understanding of vulnerability to warming in a widespread copepod
Bibliographic record
Abstract
Abstract Differences in population vulnerability to warming are defined by spatial patterns in thermal adaptation. These patterns may be driven by natural selection over spatial environmental gradients, but can also be shaped by gene flow, especially in marine taxa with high dispersal potential. Understanding and predicting organismal responses to warming requires disentangling the opposing effects of selection and gene flow. We begin by documenting genetic divergence of thermal tolerance and developmental phenotypic plasticity. Ten populations of the widespread copepod Acartia tonsa were collected from sites across a large thermal gradient, ranging from the Florida Keys to Northern New Brunswick, Canada (spanning over 20 degrees latitude). Thermal performance curves from common garden experiments revealed local adaptation at the sampling range extremes, with thermal tolerance increasing at low latitudes and decreasing at high latitudes. The opposite pattern was observed in phenotypic plasticity, which was strongest at high latitudes. Over a large portion of the sampled range, however, we observed a remarkable lack of differentiation of thermal performance curves. To examine whether this lack of divergence is the result of selection for a generalist performance curve or constraint by gene flow, we analyzed cytochrome oxidase I mtDNA sequences, which revealed abundant genetic diversity and widely-distributed haplotypes. Strong divergence in thermal performance within genetic clades, however, suggests that the pace of thermal adaptation can be relatively rapid. The combined insight from the laboratory physiological experiments and genetic data indicate that gene flow constrains differentiation of thermal performance curves. This balance between gene flow and selection has implications for patterns of vulnerability to warming. Taking both genetic differentiation and phenotypic plasticity into account, our results suggest that local adaptation does not increase vulnerability to warming, and that low latitude populations in general may be more vulnerable to predicted temperature change over the next century.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 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".