CROSS‐GENERATIONAL EFFECTS OF HABITAT AND DENSITY ON LIFE HISTORY IN RED DEER
Bibliographic record
Abstract
We used long-term data on movements, survival, and reproduction of female red deer (Cervus elaphus Linnaeus) of the Isle of Rum, Scotland (1970-2001), to explain variation in life history (age at maturity) from a hind's access to habitat resources and exposure to local density, and cross-generational (maternal) effects on observed relationships. We described each hind's use of resources relative to availability in the study area from an individual-based resource selection function (RSF); we defined local density as the total number of hinds aged > or = 1 year within the subpopulation cluster to which an individual belonged. The likelihood of a hind producing her first calf in the period from birth to the end of the summer in which she turned age 3 was positively related to relative use of Agrostis/Festuca grasslands and other low-elevation communities, and inversely related to a hind's mean annual local density. However, when we considered both a daughter's RSF and exposure to local density and her mother's RSF and exposure to local density, maternal data alone most parsimoniously explained variation in age at maturity of daughters. Mothers were able to lower age at maturity in their daughters in two, non-mutually exclusive ways. First, birth mass of daughters was inversely related to age at maturity, and mothers that used relatively less uplands (Calluna-dominated heath and heather moorland) and occupied areas of lower density produced larger offspring. Second, mothers could establish a home range that enabled daughters to mature in areas with access to high quality Agrostis/Festuca grasslands at low density. Lifetime reproductive success was inversely associated with a hind's age at maturity via extension of the reproductive life span. Longevity did not change in association with age at maturity. Patterns in how animals use available habitat resources may depend on that of previous generations, especially at larger scales of resource selection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".