Density estimates for Canada lynx vary among estimation methods
Bibliographic record
Abstract
Abstract Unbiased population density estimates are critical for ecological research and wildlife management but are often difficult to obtain. Researchers use a variety of sampling and statistical methods to generate estimates of density, but few studies have compared estimates across methods. During 2016–2017, we surveyed Canada lynx ( Lynx canadensis ) in southwestern Yukon Territory, Canada, using track transect counts, hair snares, camera traps, live traps, and Global Positioning System (GPS) collars. From these data, we estimated lynx density with two linearly scaled count methods, one spatial mark–recapture method, three spatial mark–resight methods, and one cumulative‐time method. We found up to fivefold variation in point density estimates despite adhering to method requirements and assumptions in a manner consistent with other studies. Our results highlight the dependency of density estimates on sampling process and model assumptions and demonstrate the value of careful and unbiased sampling design. Further research is needed to fully assess the accuracy and limitations of the many wildlife density estimation methods that are currently in use so that techniques can be appropriately applied to typical study systems and species.
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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) | 0.004 | 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".