UNGULATES SEARCH FOR THE IDEAL HOME: HOW PREDATION AND FORAGE DIFFERENTIALLY AFFECT MALES AND FEMALES IN A PARTIALLY MIGRATORY POPULATION
Bibliographic record
Abstract
Migration is a strategy used across taxa to access resources in temporally heterogenous landscapes. Migratory species can attain higher abundances because access to higher quality resources, and/or reduction in predation risk. However, most migratory species occur in partially migratory populations, a mix of migratory and non-migratory, resident individuals. I first investigate the potential mechanisms maintaining partial migration in a partially migratory elk (Cervus canadensis) population. I test whether the theory of Ideal Free Distribution (IFD) can explain the coexistence of different migratory tactics in a partially migratory population. IFD predicts that individuals exhibit density-dependent vital rates and should select different migratory tactics to maximize individual fitness, resulting in equal fitness () between tactics. We found density dependent pregnancy and adult female survival for residents, providing a fitness incentive to switch tactics. Despite differences in vital rates between tactics, mean λ (fitness) was equal, as predicted by IFD, because individual females switched tactics toward those of higher fitness. Next, I tested the Reproductive Strategy Hypothesis (RSH) for sexual segregation in the context of partial migration. I compared males and females for differences in their use and selection for forage and predation risk across spatiotemporal scales. I found support for the RSH as males adopted the migratory tactic with the highest forage quality and used higher quality forage than females. In summer, females avoided the primary predator of neonate calves further supporting the RSH, but potentially at the expense of increased exposure to wolf predation risk. Antler growth and development was driven by age and forage quality, and because migration increased forage quality, migration likely benefits male reproductive success, also supporting the RSH. Finally, I investigated the effect of age, forage, predation and harvest on male elk survival. Male elk survival was largely a function of age, as human harvest was the primary cause of mortality and antler-point-restrictions resulted in low survival for male elk over 4 years of age (S=0.42). My work demonstrates ecological drivers of population dynamics of partially migratory ungulates that has global relevance given recent declines in migratory large ungulate populations and migratory routes.
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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 | 0.001 | 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) | 0.000 | 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".