Habitat associations and distribution model for<i>Fuscopannaria leucosticta</i>in Nova Scotia, Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Fuscopannaria leucosticta is a rare and understudied cyanolichen with an interesting and unusual distribution in tertiary relict hotspots worldwide. There is a relatively large population in eastern North America, where it occurs mostly throughout the Appalachian Mountains and reaches its northernmost extent in New Brunswick and Nova Scotia, Canada. The ability to detect this species, and thus determine its habitat requirements, is critical for understanding how it might be affected by human-induced environmental degradation. Maximum entropy modelling with MaxEnt was used to predict the distribution of suitable habitat for this species in Nova Scotia using 62 presence locations, 1405 pseudo-absence locations and four environmental covariates: depth to water table (a proxy for relative soil moisture), distance to the coast and mean annual temperature and precipitation. Our predictive maps identify important habitat features and areas of high suitability in Nova Scotia with an area under the curve value of 0·85. The predicted distribution of this lichen was most affected by temperature. This study elucidates locations as well as species-habitat relationships for F. leucosticta, providing land managers with baseline data that can aid in the discovery of additional populations and provide a better understanding of its ecological requirements which will support the development of sound conservation strategies for this rare lichen.
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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) | 0.001 | 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 it