BROAD-SCALE PREDICTORS OF CANADA LYNX OCCURRENCE IN EASTERN NORTH AMERICA
Bibliographic record
Abstract
The Canada lynx (Lynx canadensis) is listed as a threatened species throughout the southern extent of its geographic range in the United States. Most research on lynx has been conducted in the western United States and Canada; little is known about the ecology of lynx in eastern North America. To fill critical knowledge gaps about this species, we modeled and mapped lynx occurrence using habitat and weather data from 7 eastern states and 3 Canadian provinces. Annual snowfall, road density, bobcat (L. rufus) harvest, deciduous forest, and coniferous forest were compared at 1,150 lynx locations and 1,288 random locations. Nineteen a priori models were developed using the information–theoretic approach, and logistic regression models were ranked using Akaike's Information Criterion (AIC) and by our ability to correctly classify reserved data (Kappa). Annual snowfall and deciduous forest predicted lynx presence and absence for a reserved dataset (n = 278) with 94% accuracy. A map of the probability of lynx occurrence throughout the region revealed that 92% of the potential habitat (i.e., >50% probability of occurrence) was concentrated in a relatively contiguous complex encompassing northern Maine, New Brunswick, and the Gaspé peninsula of Quebec. Most of the remaining potential habitat (5%) was on northern Cape Breton Island in Nova Scotia. Potential habitat in New Hampshire, Vermont, and New York was small (1,252 km2), fragmented, and isolated (>200 km) from known lynx populations. When federally listed as threatened in the contiguous United States in 2000, inadequate regulations on federal lands were cited as the primary threat to Canada lynx. However, the majority of potential lynx habitat in the eastern United States is on private lands and continuous with potential habitat in Canada. Therefore, lynx conservation in eastern North America will need to develop partnerships across national, state, and provincial boundaries as well as with private landowners.
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 | 0.000 | 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) | 0.000 | 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".