Middle of the road: enhanced habitat for salamanders on unused logging roads
Bibliographic record
Abstract
Context Amphibians are particularly susceptible to the effects of habitat loss and fragmentation. The construction and use of roads is among the most common sources of habitat fragmentation and can lead to serious population declines. Unused resource access roads, such as those formerly used for logging, can still negatively impact salamanders and reduce habitat quality through edge effects. Unfortunately, habitat rehabilitation and enhancement is rarely attempted on unused forest roads. Aims Our aim was to elaborate on a previous study that tested several types of woody debris to mitigate the negative impacts of forest roads by creating a novel habitat on an unused forest road in Algonquin Provincial Park. Here we focus solely on the use of large, squared timbers and their use by salamanders. Methods We tested the application of coarse woody debris (CWD) to the surface of an unused forest road. CWD were sampled for salamanders seven times during the 2011 field season. Local climatic variables were tested against salamander captures, and CWD size preferences and patterns of salamander aggregation under CWD were assessed. Key results We observed five salamander species and 415 individuals under timbers in the 2011 field season. Larger timbers (>1 m3) were preferred by all species observed and a significant proportion of animals were found in groups of two or more under larger timbers. High ambient temperature and low relative humidity negatively affected the number and species composition observed under timbers, suggesting that the efficiency of CWD as a survey method and enhanced habitat is season dependent. Implications Large timbers placed on unused forest roads may provide suitable refuges for migrating or dispersing forest salamanders while they attempt to cross the road. The tendency of salamanders to aggregate under CWD allows individual red efts to reduce water loss; however, red-backed salamanders are territorial and may drive off conspecifics. The use of large CWD may be an effective and low-cost method to rehabilitate unused forest roads and can be used to promote habitat connectivity for salamanders in targeted habitats, such as near wetlands, or for other species of concern.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".