Climatic limitation of emerald ash borer impacts on black ash in canada
Bibliographic record
Abstract
Emerald Ash Borer (Agrilus planipennis) is an introduced Asian wood boring beetle (family Buprestidae) that is rapidly spreading in North America and poses a significant threat to all North American ash (Fraxinus) species (Herms and McCullough 2014; COSEWIC in prep.). In 2016, the Aboriginal Traditional Knowledge (ATK) Subcommittee of the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) solicited the Atlantic Canada Conservation Data Centre (AC CDC) and Donna Hurlburt to co-write a federal status report on Black Ash (Fraxinus nigra) (COSEWIC in prep.). Emerald Ash Borer (EAB) is clearly the largest threat to Black Ash in Canada, already having caused 95% to 99+% ash mortality in heavily susceptible areas (Klooster et al. 2013; 2014). There is, however, good evidence from experimental and modeling studies that cold winter temperatures will limit or prevent the establishment of Emerald Ash Borer in the northern part of Black Ash range (Venette and Abrahamson 2010; Crosthwaite et al. 2011; Sobek-Swant et al. 2012; DeSantis et al. 2013). The extent to which Canadian Black Ash may be protected by cold temperatures is thus a crucial question relative to assessing the species’ federal status. Relatively fine-scale data on climate and Black Ash abundance exist for most of its Canadian range, but a detailed GIS analysis of climate-related limitation of EAB impacts was beyond the scope of the initial COSEWIC status report contract. The COSEWIC ATK Subcommittee thus solicited AC CDC to conduct the analysis described in this report.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".