Adaptation of plasticity to predicted climates in Australian rainbowfishes ( <i>Melanotaenia</i> ) across climatically defined bioregions
Bibliographic record
Abstract
Abstract Resilience to environmental stressors due to climate warming is influenced by local adaptations, including the capacity for plastic responses. The recent literature has focussed on genomic signatures of climatic adaptation, however little work has been done to address how plastic capacity may be influenced by biogeographic history and evolutionary processes. Here, we investigate phenotypic plasticity as a target of climatic selection, hypothesising that lineages that evolved under warmer climate will exhibit greater plastic adaptive resilience to thermal stress. This was tested using common garden experiments to compare gene expression regulation within and among a temperate, a subtropical and a desert ecotype of Australian rainbowfish. Individuals from each ecotype were subjected to contemporary and projected summer thermal conditions for 2070, and their global patterns of gene expression were characterized using liver transcriptomes. Critical thermal maximums were also determined for each ecotype to assess thermal tolerance. A comparative phylogenetic expression variance and evolution model framework was used to assess plastic and evolved changes in gene expression. Similar changes in both the direction and the magnitude of expressed genes were found within ecotypes. Although most expressed genes were identified in all ecotypes, 532 genes were identified as candidates subject to ecotype-specific directional selection. Twenty-three of those genes showed signal of adaptive (i.e. genetic-based) plastic response to future increases in temperature. Network analyses demonstrated centrality of these genes in thermal response pathways, along with several highly conserved hub genes thought to be integral for heat stress responses. The greatest adaptive resilience to warming was shown by the subtropical ecotype, followed by the desert and temperate ecotypes. Our findings indicate that vulnerability to climate change will be highly influenced by biogeographic factors, and we stress the need for integrative assessments of climatic adaptive traits for accurate estimations of population and ecosystem responses.
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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 | 0.000 |
| 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 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".