The ghosts of predators past: population cycles and the role of maternal programming under fluctuating predation risk
Bibliographic record
Abstract
Maternal effects may be a major factor influencing the demography of populations. In mammals, the transmission of stress hormones between mother and offspring may play an important role in these effects. Laboratory studies have shown that stressors during pregnancy and lactation result in lifelong programming of the offspring phenotype. However, the relevance of these studies to free-living mammals is unclear. The 10-year snowshoe hare (Lepus americanus) cycle is intimately linked to fluctuating predation pressure and predation risk. The enigma of these cycles is the lack of population growth following the decline phase, when the predators have virtually all disappeared and the food supply is ample. We have shown that a predator-induced increase in maternal stress hormone levels resulted in a decline in reproduction. Here we examine population and hormone changes over a four-year period from the increase (2005) to the decline (2008). We report (1) that an index of maternal stress (fecal corticosteroid metabolite [FCM] concentrations) fluctuates in synchrony with predator density during the breeding season; (2) that maternal FCM levels are echoed in their offspring, and this occurs at a population-wide level; and (3) that higher maternal FCM levels at birth are correlated with an increased responsiveness of the hypothalamic-pituitary-adrenal (HPA) axis in their progeny. Our results show an intergenerational inheritance of stress hormones in a free-ranging population of mammals. We propose that the lack of recovery of reproductive rates during the early low phase of the hare cycle may be the result of the impacts of intergenerational, maternally inherited stress hormones caused by high predation risk during the decline phase.
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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 | 0.002 |
| 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".