Heterogeneity in body condition, survival, and seasonal origins among lesser snow and Ross's geese
Bibliographic record
Abstract
Individual heterogeneity in fitness within a population is well established and provides the required variability for natural selection to take place. Yet, in the case of overabundant midcontinent lesser snow (Anser caerulescens caerulescens) and Ross's geese (A. rossii), individual variation in regards to harvest effects on population growth has largely not been considered when evaluating management actions to reduce population size. In this dissertation, I first examined heterogeneity in body condition among hunter harvested individuals and the general population of midcontinent lesser snow and Ross's geese during the spring Light Goose Conservation Order in 2015 and 2016 across Arkansas, Missouri, Nebraska, and South Dakota. I found a body condition bias in decoy harvested geese, such that individuals removed by hunters were in lower body condition (less lipid content) relative to the general population. This finding suggests that disproportionate removal of lower conditioned individuals is a feature of the currently observed compensatory nature of harvest among midcontinent light geese. I also explored methods to estimate the magnitude of individual variation in survival rates of adult lesser snow geese using mark-recovery data via a Bayesian state-space model. I identified limitations to estimating heterogeneous survival rates using mark-recovery data alone and suggest future simulations to explore alternative methodological approaches. Finally, I evaluated differences in spring body condition among individuals using different wintering habitats through stable isotope analysis. I found that individuals overwintering in coastal marsh habitats had lower lipid reserves relative to those individuals overwintering in rice-based agricultural landscapes, suggesting a carry-over effect from winter habitat use that may influence harvest susceptibility or other fitness parameters. In conclusion, continued research to identify the amount of individual variation in survival parameters of cohort specific geese can further elucidate the role of heterogeneity on the Light Goose Conservation Order attempts to reduce population size.
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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 | 0.000 | 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".