Low energy reserves and energy allocation decisions affect reproduction by Mountain Pine Beetles,<i>Dendroctonus ponderosae</i>
Bibliographic record
Abstract
Summary Low internal energy reserves at the beginning of the breeding season may impose physiological constraints on an animal's reproductive investment and may alter the optimal trade‐off between investment in reproduction and somatic condition. Here we examine how the energetic condition of female Mountain Pine Beetles (Dendroctonus ponderosae) affects their reproductive investment. We starved beetles to simulate the decrease in energy that accompanies dispersal and tested whether starved beetles had decreased egg number and decreased egg size, or both. We further distinguished whether changes are due to physiological constraints or shifts in allocation between reproduction and somatic condition. We found that starved beetles produced smaller eggs than non‐starved beetles, but females were able to partially offset the energetic deficit by feeding at their breeding habitat. Starvation did not decrease the number of eggs beetles produced. The number and size of eggs produced depended on whether females allocated energy to reproduction or to somatic condition. However, this life‐history allocation decision was independent of the amount of energy beetles had at the beginning of reproduction. Our results demonstrate the importance of assessing reproductive investment in the context of other life‐history trade‐offs. Specifically, since egg size in Mountain Pine Beetles was highly dependent on both the amount of energy remaining after dispersal and whether energy was allocated to reproduction or somatic maintenance, we expect both of these trade‐offs to be under strong selection.
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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".