The freeze-avoiding mountain pine beetle (Dendroctonus ponderosae) survives prolonged exposure to stressful cold by mitigating ionoregulatory collapse
Bibliographic record
Abstract
Insect performance is intrinsically linked to environmental temperature, and surviving through winter represents a key challenge for temperate, alpine, and polar species. To overwinter, insects have adapted a wide range of strategies to become truly cold hardy. However, while the physiological mechanisms underlying the ability to avoid or tolerate freezing have been well-studied, little attention has been given to the challenge of maintaining ion homeostasis at frigid temperatures in these species, despite this being a central issue for insects susceptible to mild chilling. Here we investigate how prolonged exposure to temperatures just above the supercooling point affects ion balance in freeze-avoiding larvae of the mountain pine beetle (Dendroctonus ponderosae) in autumn, mid-winter, and spring, and relate it to organismal recovery times and survival outcomes. We found that hemolymph ion balance was gradually disrupted during the first day of exposure, characterized by hyperkalemia and hyponatremia, after which a plateau was reached and maintained for the rest of the seven day experiment. The degree of ionoregulatory collapse experienced by larvae correlated strongly with recovery times, which followed a similar asymptotical progression. Mortality increased slightly during the most severe cold exposures, where hemolymph K+ concentration was highest, and a logistic relationship was found between survival and hyperkalemia. Thus, the cold tolerance of the freeze-avoiding larvae of D. ponderosae appears limited by the ability to prevent ionoregulatory collapse in a manner similar to less tolerant chill-susceptible insects, albeit at much lower temperatures. Furthermore, we posit that a prerequisite for the evolution of insect freeze avoidance is a convergent or ancestral ability to maintain ion homeostasis during exposure to extreme cold stress.
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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) | 0.000 | 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".