Relative efficiency of hunting methods during an incomplete Sitka black‐tailed deer eradication on Haida Gwaii, Canada
Bibliographic record
Abstract
Abstract Invasive species are reducing global biodiversity. The Llgaay gwii sdiihlda—Restoring Balance project was initiated to halt and reverse biodiversity loss on six islands on Haida Gwaii, Canada through the eradication of invasive Sitka Black‐tailed deer ( Odocoileus hemionus sitkensis ). Invasive deer were killed using various hunting methods including bait station, boat, aerial and indicator dog hunting as well as a combination of bailing dogs with boat and aerial hunting. Cost was quantified in terms of helicopter hunting hours ($1965 CAD/hr at the time of the study) to facilitate comparisons. Efficiency was quantified as the expected number of deer per helicopter hour. Hierarchical Bayesian integrated removal models were used to estimate the change in efficiency of the various hunting methods with deer density based on a power function. The models used the number of scent trail detections by dogs at the end of the study to help parameterise the population density. At densities between 2 and 30 deer/km 2 , boat hunting was estimated as the most efficient method while at lower densities indicator dog hunting was most efficient. The eradication was incomplete. The estimated cost to completion using indicator dog hunting for each island was 43 helicopter hours (~$84,000) on Ramsay Island (95% CI = 19–128), 3.9 helicopter hours on Murchison Island (95% CI = 0.56–18) and no additional hours on House (95% CI = 0–1.6) though the selected method would likely have been indicator dogs with combined hunting due to the variable terrain. Lessons learned: DNA connectivity analysis can be used to determine project durability, pilot studies to confirm method efficiency in local context will increase the chances of success, local knowledge improves efficiency of hunting methods, population and efficiency estimates should be updated throughout operations to allow adaptive management, eradications on ungulates can include pauses to facilitate adaptive management, the level of certainty for determining eradication completion should be determined in advance of operations with explicit trade‐offs identified for managers.
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 | 0.001 |
| 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 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".