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Record W4414327982 · doi:10.3897/neobiota.101.157996

An annotated registry of established forest pathogens in the continental USA, Canada, and Hawaiian Islands

2025· article· en· W4414327982 on OpenAlex

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNeoBiota · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsBiosecurityTaxonRange (aeronautics)ShrubInvasive speciesPEST analysisIntroduced speciesBiodiversity

Abstract

fetched live from OpenAlex

General understanding of disease epiphytotics caused by introduced agents (pathogens) in forest systems, as well as the ability to assess risk of future introductions within a process-barrier framework of biological invasion, are impeded by a lack of systematically compiled information on origins and functional traits of pathogens that have become established outside their range. To address these gaps, substantially update previous registries, and provide critical biosecurity information, we assembled a list of established forest phytopathogens that are present, but not thought to be native in the continental United States (CONUS), Canada, and the Hawaiian islands under working hypotheses of their origins. We restricted the present list to phytopathogens that cause disease on native tree or woody shrub species, excluding the larger number of species of non-native phytopathogens of trees that are exclusive to agricultural and horticultural species and landscapes which are already well-represented in pest databases (e.g., CABI, EPPO, APHIS, etc.). We used previous databases as a scaffold and supplemented those lists with additional taxa by cross-referencing with lists of forest pathogens and hypothetical origins for other regions (Australia and Europe) as well as by reviewing taxonomic, host, and distribution history of pathogen species that have been recorded in both the study area (CONUS-Canada-Hawaii) and at least one other continent. For each of the 93 species in our database, we provide a relational database of a) taxonomic information, b) invasion status in each region, c) first year on record in each region, d) working hypotheses of original range (where possible), e) traits including disease type and name, dispersal mode, and organs and host life stages infected, f) major hosts, g) and > 7,000 chronological records of potential location-year and host-location-year combinations for each pathogen. We also provide a reference-annotated classification system for types of evidence for first years (c), original ranges (d), and major hosts (f). This represents a significant expansion of our knowledge of non-native infectious microorganisms of forest trees compared to previous registries, particularly in terms of its comprehensiveness, precision, and accuracy of information that includes a way to assess and compare the level of uncertainty associated with key information.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.200
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it