Modeling the Geographic Distribution of Cantharellus formosus Under Climate Change
Bibliographic record
Abstract
Maximum entropy, presence-only, species distribution modeling of the current and future habitat of Cantharellus formosus across North America is modeled under a range of climate change scenarios. C. formosus is a culturally and economically important ectomycorrhizal Basidiomycetes mushroom species which is highly prized by foragers for its gourmet flavor. It is symbiotic with Pseudotsuga menziesii (Douglas Fir) and widespread along the US west coast, particularly in heavily forested areas of Washington and Oregon, west of the Cascades. C. formosus has been observed as far south as Berkeley, California, and as far north as southern Alaska, as well as in limited areas of the northern Rockies, near the Canada - Idaho border. Using 663 research-grade, crowed-sourced presence observations obtained from the Global Biodiversity Information Facility and 23 ecological variables, the ecological-niche and species distribution of C. formosus was modeled using a maximum entropy, machine learning algorithm. Further, the future distribution of C. formosus was forecast using a range of climate projections, out to the year 2100. Projections indicate that highly suitable habitat is likely to decline, by 8% to 94%, particularly in California where multiple projections show a complete loss of highly suitable habitat. Conversely, suitable and somewhat suitable habitat may increase by upwards of 100%, as the projected habitat migrates to the north. Importantly, due to the ecology and symbiotic nature of C. formosus, while loss of habitat may occur relatively quickly under changing climatic conditions, establishment and/or expansion into new habitat is likely to be slower by comparison.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".