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Record W4360603204 · doi:10.1016/j.foreco.2023.120847

The increasing threat to European forests from the invasive foliar pine pathogen, Lecanosticta acicola

2023· article· en· W4360603204 on OpenAlexfundno aff
Katherine Tubby, Katarína Adamčíková, Kalev Adamson, Mitsuteru Akiba, Irene Barnes, P Boroń, Helena Bragança, Timur S. Bulgakov, N. Burgdorf, Paolo Capretti, T. L. Cech, Michelle Cleary, Kateryna Davydenko, Rein Drenkhan, Margarita Elvira‐Recuenco, Rasmus Enderle, J. F. Gardner, Маргарита Георгиева, Luisa Ghelardini, Claude Husson, Eugenia Iturritxa, Svetlana Markovskaja, Nebai Mesanza, ̧Nikica Ogris, Funda Oskay, Barbara Piškur, Valentin Queloz, Kristina Raitelaitytė, Rosa Raposo, M. Soukainen, L. Strasser, Petr Vahalík, Marili Vester, Martin Mullett

Bibliographic record

VenueForest Ecology and Management · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersNatureRegione ToscanaMinistry of Rural AffairsBundesamt für UmweltVetenskapsrådetJavna Agencija za Raziskovalno Dejavnost RSSvenska Forskningsrådet FormasRussian Academy of SciencesUniversità degli Studi di FirenzeEesti TeadusfondiEuropean Commission
KeywordsRange (aeronautics)GeographyEcologyThreatened speciesInvasive speciesClimate changeBiologyAgroforestryHabitat

Abstract

fetched live from OpenAlex

European forests are threatened by increasing numbers of invasive pests and pathogens. Over the past century, Lecanosticta acicola, a foliar pathogen predominantly of Pinus spp., has expanded its range globally, and is increasing in impact. Lecanosticta acicola causes brown spot needle blight, resulting in premature defoliation, reduced growth, and mortality in some hosts. Originating from southern regions of North American, it devastated forests in the USA’s southern states in the early twentieth century, and in 1942 was discovered in Spain. Derived from Euphresco project ‘Brownspotrisk,’ this study aimed to establish the current distribution of Lecanosticta species, and assess the risks of L. acicola to European forests. Pathogen reports from the literature, and new/ unpublished survey data were combined into an open-access geo-database (http://www.portalofforestpathology.com), and used to visualise the pathogen’s range, infer its climatic tolerance, and update its host range. Lecanosticta species have now been recorded in 44 countries, mostly in the northern hemisphere. The type species, L. acicola, has increased its range in recent years, and is present in 24 out of the 26 European countries where data were available. Other species of Lecanosticta are largely restricted to Mexico and Central America, and recently Colombia. The geo-database records demonstrate that L. acicola tolerates a wide range of climates across the northern hemisphere, and indicate its potential to colonise Pinus spp. forests across large swathes of the Europe. Preliminary analyses suggest L. acicola could affect 62% of global Pinus species area by the end of this century, under climate change predictions. Although its host range appears slightly narrower than the similar Dothistroma species, Lecanosticta species were recorded on 70 host taxa, mostly Pinus spp., but including, Cedrus and Picea spp. Twenty-three, including species of critical ecological, environmental and economic significance in Europe, are highly susceptible to L. acicola, suffering heavy defoliation and sometimes mortality. Variation in apparent susceptibility between reports could reflect variation between regions in the hosts’ genetic make-up, but could also reflect the significant variation in L. acicola populations and lineages found across Europe. This study served to highlight significant gaps in our understanding of the pathogen’s behaviour. Lecanosticta acicola has recently been downgraded from an A1 quarantine pest to a regulated non quarantine pathogen, and is now widely distributed across Europe. With a need to consider disease management, this study also explored global BSNB strategies, and used Case Studies to summarise the tactics employed to date in Europe.

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.009
GPT teacher head0.209
Teacher spread0.200 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations29
Published2023
Admission routes1
Has abstractyes

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