Integrated organismal responses induced by projected levels of CO<sub>2</sub> and temperature exposures in the early life stages of lake sturgeon
Bibliographic record
Abstract
Abstract Atmospheric CO2 and temperature are rising concurrently, and may have profound impacts on the transcriptional, physiological and behavioural responses of aquatic organisms. Further, spring snowmelt may cause transient increases of pCO2 in many freshwater systems. We examined the behavioural, physiological and transcriptomic responses of an ancient fish, the lake sturgeon (Acipenser fulvescens) to projected levels of warming and pCO2 during its most vulnerable period of life, the first year. Specifically, larval fish were raised in either low (16°C) or high (22°C) temperature, and/or low (1000 μatm) or high (2500 μatm) pCO2 in a crossed experimental design over approximately 8 months. Following overwintering, lake sturgeon were exposed to a transient increase in pCO2 of 10,000 μatm, simulating a spring melt based on data in freshwater systems. Transcriptional analyses revealed potential connections to otolith formation and reduced growth in fish exposed to high pCO2 and temperature in combination. Network analyses of differential gene expression revealed different biological processes among the different treatments on the edges of transcriptional networks. Na+/K+‐ATPase activity increased in fish not exposed to elevated pCO2 during development, and mRNA abundance of the β subunit was most strongly predictive of enzyme activity. Behavioural assays revealed a decrease in total activity following an acute CO2 exposure. These results demonstrate compensatory and compounding mechanisms of pCO2 and warming dependent on developmental conditions in lake sturgeon. Conserved elements of the cellular stress response across all organisms provide key information for how other freshwater organisms may respond to future climate change.
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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".