Will Lynx Lose Their Edge? Canada Lynx Occupancy in Washington
Bibliographic record
Abstract
ABSTRACT Populations of species located at southern range edges may be particularly vulnerable to the effects of climate change as warming temperatures and subsequent changes to ecosystems exceed species‐specific tolerances. One such species is Canada lynx ( Lynx canadensis ), a cold‐adapted mesocarnivore that maintains a large core population in Alaska, USA, and Canada but exists within several peripheral populations in the contiguous United States. Increases in temperature, declines in snow pack, and climate‐influenced increases in fire frequency and intensity, could negatively affect lynx populations, threatening their long‐term persistence in the continental United States. Despite these threats, our understanding of broad‐scale effects on lynx occupancy and the extent of current lynx distribution in many of these peripheral populations is minimal. We conducted an occupancy survey of lynx in Washington, USA, using a spatially extensive camera‐trapping array covering 7,000 km 2 of potential lynx habitat. We used the resulting database of detection data to develop single‐season occupancy models to examine the abiotic and biotic effects on current lynx occupancy and predict future lynx distribution based on climate change forecasts. Our results show lynx occupancy across the Washington landscape is restricted and dictated largely by abiotic factors, disturbance regimes, and distance from source populations in Canada. Predictions of future distribution suggest lynx will be increasingly challenged by climatic changes, particularly at the southern and lower elevation portions of their range in Washington. Our results paint an alarming picture for lynx persistence in Washington that is relevant to current deliberations regarding lynx delisting from the Endangered Species Act. Our simple camera design was a highly effective method for surveying lynx across broad spatial scales, and could be a key monitoring tool for lynx that is easy to implement by researchers and government agencies. © 2020 The Wildlife Society.
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 | 0.001 |
| 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".