Characterization of darter (<i>Etheostoma</i> spp.) interspecific energetic responses to acute temperature elevations
Bibliographic record
Abstract
Abstract Understanding metabolic responses to temperature elevations is critical for determining how fish populations will be impacted by the increased occurrence of extreme heat events. Here, we characterized the thermal tolerance limits and metabolic functions of three closely related darter species native to the Grand River of Southern Ontario: Fantail darter (Etheostoma flabellare; FTD), Rainbow darter (Etheostoma caeruleum; RBD) and Johnny darter (Etheostoma nigrum; JD). Brain and heart activity of enzymes associated with cellular respiration were analysed for each species at 15°C baseline and following a Critical Thermal Maximum (CTmax) test. Additionally, aerobic scope (AS) was determined for each species while exposed to four heat ramps designed to mimic previously recorded heatwaves. CTmax significantly differed between species with FTD displaying the highest at 33.3°C, JD second at 31.8°C and RBD the lowest at 30.7°C. In darters not exposed to heat stress, FTD possessed higher brain enzymatic activity rates, specifically in pyruvate kinase (PK), citrate synthase (CS) and malate dehydrogenase (MDH). These patterns shifted slightly after exposure to CTmax, with JD displaying a substantial elevation in PK, lactate dehydrogenase, CS and MDH activity, suggesting they had greater enzymatic capacity at temperature extremes. Within heart tissue, we observed no interspecific differences at baseline temperatures; however, RBD had lower enzyme activity than FTD or JD in all enzymes but cytochrome c oxidase following CTmax. Metabolically, FTD exhibited the highest AS following exposure to 10 and 15°C temperature elevations. Our findings demonstrate that FTD may be the best equipped to respond to temperature-induced increases in metabolic demand due to their elevated baseline enzymatic activity and broader AS. These insights may contribute to future darter conservation efforts by informing predictions on species population shifts, particularly in the context of climate change.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".