A data‐driven demographic model to explore the decline of the Bathurst caribou herd
Bibliographic record
Abstract
Abstract The Bathurst herd of barren‐ground caribou ( Rangifer tarandus groenlandicus ) in the Canadian central arctic declined from an estimated 203,800 to 16,400 breeding females from 1986 to 2009, with the most rapid decline from 2006 to 2009. A key research and management question was whether the decline was mainly due to decreases in productivity alone or also due to reduced adult female survival. Investigating causes of the decline was hampered by a lack of direct estimates of caribou demographic parameters. We developed a demographic model that could be objectively fitted to field data to explore the mechanisms for the Bathurst decline, with a focus on the recent accelerated decline from 2006 to 2009. Our modeling indicated that the decline was driven by increasing negative trends in adult female and calf survival rates and possibly reduced fecundity The effect of a constant hunter harvest on the declining herd was one potential cause for the recent accelerated decline in adult survival. The demographic model detected negative trends in adult female survival that were not detected using standalone analyses of collar‐based survival data. The model allowed rigorous interpretation of trends in productivity by controlling for the simultaneous influence of trends in adult, calf, and yearling survival and adult fecundity on field‐based calf–cow ratios. Stochastic simulations suggested that large increases in adult survival and productivity would be needed for the herd to recover. Our methods enable objective modeling of caribou demography that can assist in caribou management based upon all sources of available data. © 2011 The Wildlife Society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| 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".