Canada lynx occurrence and forest management in the Acadian Forest
Bibliographic record
Abstract
Abstract We evaluated patterns of occurrence and non‐occurrence for Canada lynx ( Lynx canadensis ) across a 16,530‐km 2 study area in Maine to provide a better understanding of lynx habitat selection and habitat ecology on commercially managed forestlands in the Acadian Forest. Because of the influence of forest structure on lynx habitat selection and abundance of their primary prey, the snowshoe hare ( Lepus americanus ), and to improve our ability to build robust models, we used habitat information derived from a time series of Landsat satellite imagery spanning the period 1973–2004. We defined and mapped 10 forest types based on forest harvest history, time since harvest, and current forest condition. We compared a suite of models to evaluate relative influences of forest composition, habitat patch configuration, and hare density on habitat selection by lynx at the landscape scale. Occupied areas had greater average hare densities and percentage of mature conifer. Average hare density in occupied areas (0.74 hares/ha) was greater than in unoccupied areas (0.62 hares/ha), but was less than previous research has suggested may be necessary to support lynx populations in the southern portion of the species' range. No occupied areas occurred where average hare density was <0.5 hares/ha. Average hare density at the landscape‐scale was strongly influenced by amount of high‐quality hare habitat (i.e., conifer or mixedwood regenerating forest, 15–35 yr post‐harvest). Edge density between mature conifer and high‐quality hare habitat was substantially greater in occupied areas compared to unoccupied areas. Juxtaposition of those 2 forest types may provide edge habitat where lynx experience easier travel and improved access to prey in landscapes with extensive areas of high‐quality hare habitat where travel and access may be somewhat limited by high understory stem density. Probability of occurrence declined nonlinearly with changes in hare density and percent mature conifer forest in the landscape; thus, suitability of currently occupied landscapes could change markedly with future changes in landscape‐level hare densities and changing habitat associated with forest management. Where lynx conservation is a priority, we recommend that managers focus on creating and maintaining a minimum of 27% high‐quality hare habitat within 100‐km 2 areas to promote landscape‐scale hare densities >0.5 hares/ha. © The Wildlife Society, 2013
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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 | 0.001 | 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 | 0.000 | 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".