Post-fire movements of Pacific marten (Martes caurina) depend on the severity of landscape change
Bibliographic record
Abstract
BACKGROUND: Wildfires and forestry activities such as post-fire salvage logging are altering North American forests on a massive scale. Habitat change and fragmentation on forested landscapes may threaten forest specialists, such as Pacific marten (Martes caurina), that require closed, connected, and highly structured habitats. Although marten use burned landscapes, it is unclear how these animals respond to differing burn severities, or how well they tolerate additional landscape change from salvage logging. METHODS: We used snow tracking and GPS collars to examine marten movements in three large burns in north-central Washington, USA (burned in 2006) and central British Columbia, Canada (burned in 2010 and 2017). We also assessed marten habitat use in relation to areas salvage-logged in the 2010 burn. We evaluated marten path characteristics in relation to post-fire habitat quality, including shifts in behaviour when crossing severely-disturbed habitats. Using GPS locations, we investigated marten home range characteristics and habitat selection in relation to forest cover, burn severity, and salvage logging. RESULTS: Marten in the 2006 burn shifted from random to directed movement in areas burned at high severity; in BC, they chose highly straight paths when crossing salvage-blocks and meadows. Collared marten structured their home ranges around forest cover and burn severity, avoiding sparsely-covered habitats and selecting areas burned at low severity. Marten selected areas farther from roads in both Washington and BC, selected areas closer to water in the 2006 burn, and strongly avoided salvage-logged areas of the 2010 burn. Marten home ranges overlapped extensively, including two males tracked concurrently in the 2010 burn. CONCLUSIONS: Areas burned at low severity provide critical habitat for marten post-fire. Encouragingly, our results indicate that both male and female marten can maintain home ranges in large burns and use a wide range of post-fire conditions. However, salvage-logged areas are not suitable for marten and may represent significant barriers to foraging and dispersal.
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) | 0.005 | 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".