Bobcat Population Status and Management in North America: Evidence of Large-Scale Population Increase
Bibliographic record
Abstract
Abstract Bobcat Lynx rufus populations are thought to be increasing in North America; however, little information exists on their current population status. In the United States, management and monitoring of bobcat populations is the responsibility of state wildlife management agencies. We surveyed state wildlife management agencies in each of the 48 contiguous states regarding the current population status, distribution, and monitoring protocols of bobcats within each respective jurisdiction. We also surveyed the governments of Mexico and Canada regarding bobcat population status within their jurisdictions. We received responses from 47 U.S. states, Mexico, and 7 Canadian provinces. Responses indicate that bobcats occur in each of the contiguous states except for Delaware. Populations were reported to be stable or increasing in 40 states, with 6 states unable to report population trends and only 1 state (Florida) reporting decreases in bobcat populations. Of the 47 states in which bobcats occur, 41 employ some form of population monitoring. Population density estimates were available for 2,011,518 km2 (33.6%) of the estimated bobcat range in the United States, with population estimates between 1,419,333 and 2,638,738 individuals for this portion of their range and an estimated 2,352,276 to 3,571,681 individuals for the entire United States. These results indicate that bobcat populations have increased throughout the majority of their range in North America since the late 1990s and that populations within the United States are much higher than previously suggested.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".