ECOLOGICAL CONSEQUENCES OF INTRASPECIFIC VARIATION IN ENERGY ALLOCATION PATTERNS IN COLUMBIAN GROUND SQUIRRELS (UROCITELLUS COLUMBIANUS)
Bibliographic record
Abstract
Energy is a temporally and spatially limited resource, often regarded as the currency or the “fire of life”. In highly seasonal environments with fluctuating food availability and climatic conditions, individuals must carefully match energy acquisition, allocation, and the timing of energy demanding activities to maximize fitness. However, considerable intraspecific variation exists in how energy is acquired and used, as well as in the timing of costly activities such as reproduction and growth. Hibernating mammals are a unique system to study how intraspecific variation in energetics and phenological traits influences life history, as their brief active season requires them to obtain enough energy for reproduction, growth, and overwinter survival within a limited period. Columbian ground squirrels (Urocitellus columbianus) have a short active season of 3-4 months, during which adults must meet the energy demands of breeding, moulting, survival, and fattening prior to hibernation. Females finance reproduction primarily through daily income (by increasing their foraging rate), but also rely on capital resources (through endogenous fat stores), likely beginning the season with varying amounts of fat stores, which could influence how they allocate their energy throughout reproduction. In contrast, juveniles have an active season of only 1.5 to 2 months, likely facing energetic trade-offs between investing in structural growth and accumulating sufficient fat reserves to survive hibernation. In this thesis, I investigated how intraspecific variation in energetic (e.g., metabolic rates, body composition) and phenological traits (e.g., timing of parturition) in Columbian ground squirrels influences key life history traits, such as female reproductive output, juvenile growth, and survival. To do so, I used a multi-disciplinary approach that combined long-term ecological data, as well as physiological measurements, and targeted food supplementation. I found that different life history traits within the same system may support different models of energy allocation. The positive and significant associations between resting metabolic rate (RMR), daily energy expenditure (DEE), and reproductive output during lactation aligned with the predictions of the performance model, whereas the lack of a significant association between RMR and post-weaning growth aligned more closely with the predictions of the independent model of energy allocation. Additionally, I found that even slight differences in parturition timing significantly influenced juvenile body mass and growth trajectories. While females did not compensate for late breeding by increasing juvenile body mass at birth, they did show compensatory adjustments during lactation, resulting in higher body masses at weaning for late-born offspring. However, late born juveniles did not exhibit compensatory growth after weaning, nor did they extend their growth period which may underlie the decline in annual fitness among late emerging females reported in previous studies. The supplemental food treatment significantly influenced energy allocation on both reproductive females and juveniles. For females, it increased capital resources before reproduction, leading them to rely more on fat stores during gestation. In juveniles, the treatment enhanced post-weaning growth rates, extended growth duration, increased asymptotic body mass, and enhanced fat accumulation. Overall, this research advances our understanding of energy use and allocation in wild mammals, providing valuable insights into how environmental factors (such as resource availability), maternal investment, and metabolic rates contribute to intraspecific variation in life history traits.
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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 | 0.001 |
| 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".