Intraspecific differences in alkaline tolerance in brook stickleback ( <i>Culaea inconstans</i> ) inhabiting neutral and alkaline lakes
Bibliographic record
Abstract
Abstract Exposure to alkaline water (pH > 9.0) is physiologically challenging for fish, yet our understanding of the physiology of alkaline tolerance in fishes is limited to a small number of ihighly specialized species. This study aimed to characterize mechanisms of alkaline tolerance in brook stickleback ( Culaea inconstans ), a fish species with a broad pH habitat range, including highly alkaline waters such as Buffalo Lake (pH = 9.2) in Alberta, Canada. Stickleback from Buffalo Lake and a neutral reference lake (Buck Lake; pH = 8.2) were collected from the wild and acclimated to common conditions (pH = 8.0) for at least 2 months. Both populations were then exposed to alkaline conditions (pH = 9.5), resulting in a significant decrease in survival (14% by 7 d of exposure) in Buck Lake fish, but no mortality in Buffalo Lake stickleback. In a 4-d exposure to alkaline water, fish from both populations experienced characteristic inhibitions of ammonia excretion followed by subsequent recovery, in conjunction with an accumulation of ammonia within the body. However, no differences were observed between populations. Analysis of tissue Na + and Cl - content showed a more pronounced decrease in Cl - in Buck Lake fish, suggesting that tighter regulation of Cl - homeostasis and/or acid-base balance may be an important feature of alkaline tolerance. RNA-sequencing analysis highlighted large differences in gene expression between the alkaline and neutral lake populations, and in response to alkaline exposure. Few of these changes in the expression involved genes known to be associated with nitrogen, ion, or acid-base balance. These data indicate that alkaline tolerance is higher in brook stickleback resident to an alkaline lake than those sourced from a neutral lake, a trait that may be related to differences in physiological and transcriptomic responses to alkaline exposure.
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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 | 0.001 | 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".