Forest harvesting impacts on mortality of an endangered lichen at the landscape and stand scales
Bibliographic record
Abstract
Industrial forestry can negatively affect biodiversity, and rare or endangered species are particularly vulnerable. Boreal felt lichen (Erioderma pedicellatum (Hue) P.M.Jørg.) is a globally critically endangered species, and its population in Nova Scotia has been reduced through harvesting of its host tree balsam fir (Abies balsamea (L.) Mill.). We hypothesized that forest harvesting adjacent to and within the landscape of boreal felt lichen could increase the risk of mortality by negatively affecting microclimate of its habitat. Autologistic regression models were used to measure probability of mortality (death or disappearance) with harvesting history at the stand and landscape scales. Erioderma pedicellatum mortality and 17-year tree harvesting history derived from satellite data were used in the model. Modeling at the stand scale suggested that the probability of E. pedicellatum mortality increased as the area of tree harvesting increased. At the landscape scale, the model suggested that probability of E. pedicellatum mortality increased as the area of harvest within 500 m increased. Adjacent tree harvesting may increase solar radiation, wind, and temperature, which could have a negative effect on E. pedicellatum survival. We recommend maintaining uncut buffer zones around E. pedicellatum and limiting the size of harvest blocks and amount of harvesting in the landscape over a given time period to help conserve this endangered species.
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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 | 0.001 |
| 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 | 0.000 | 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".