Decoupling the effects of food and density on life history plasticity of wild animals using field experiments: Insights from the steward who sits in the shadow of its tail, the North American red squirrel
Bibliographic record
Abstract
Long-term studies of wild animals provide the opportunity to investigate how phenotypic plasticity is used to cope with environmental fluctuations, and how the relationships between phenotypes and fitness can be dependent upon the ecological context. Most previous studies have only investigated life history plasticity in response to changes in temperature, yet wild animals often experience multiple environmental fluctuations simultaneously. This requires field experiments to decouple which ecological factor induces plasticity in fitness-relevant traits to better understand their population-level responses to those environmental fluctuations. For the past 32 years, we have conducted a long-term integrative study of individually marked North American red squirrels (Tamiasciurus hudsonicus Erxleben) in the Yukon, Canada. We have used multi-year field experiments to examine the physiological and life history responses of individual red squirrels to fluctuations in food abundance and conspecific density. Our long-term observational study and field experiments show that squirrels can anticipate increases in food availability and density, thereby decoupling the usual pattern where animals respond to, rather than anticipate, an ecological change. As in many other study systems, ecological factors that can induce plasticity (such as food and density) co-vary. However, our field experiments that manipulate food availability and social cues of density (frequency of territorial vocalizations) indicate that increases in social (acoustic) cues of density in the absence of additional food can induce similar life history plasticity, as does experimental food supplementation. Changes in the levels of metabolic hormones (glucocorticoids) in response to variation in food and density are one mechanism that seems to induce this adaptive life history plasticity. Although we have not yet investigated the energetic response of squirrels to elevated density or its association with life history plasticity, energetics research in red squirrels has overturned several standard pillars of knowledge in physiological ecology. We show how a tractable model species combined with integrative studies can reveal how animals cope with resource fluctuations through life history plasticity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".