Data files for Fontenelle et al. 2024. Multi-year genotype characterization of eastern spruce budworm outbreaking populations from Quebec and adjacent regions. Accepted at Ecology.
Notice bibliographique
Résumé
Population outbreaks are characterized by irruptive changes in population density and connectivity resulting in rapid demographic and spatial expansion, often at the landscape scale. Outbreaks are common across multiple taxa, many of which inhabit northern ecosystems. Outbreaks of Lepidopteran defoliators in forest ecosystems are a particularly compelling example of this phenomenon, given the massive spatial scales over which these outbreaks can occur, their frequency, and socioeconomic impacts. Theeastern spruce budworm(SBW) is a native outbreaking Lepidopteran defoliator of North American boreal forests. Cyclic outbreaks of the SBW influence ecosystem functioning and resilience, as well as forest productivity, timber supply, and other socioeconomic values related to management and mitigation. Despite these significant impacts, the ecological and biological drivers and outcomes of these outbreaks remain poorly understood. Here, we present an extensive genotypic dataset for 1998 geo-referenced SBW individuals collected between the years of 2012 and 2017, during the rising and peak phases of an outbreak that began approximately in 2006. Our sampling covers an unprecedented scope in extent and number of individuals collected between 2012 and 2017 from Quebec, and in 2015 from New Brunswick (Canada) and from Maine (USA), from multiple SBW life stages, including early and late instar larvae (L2 - L6), pupae, and adult moths. Genomic DNA extraction was followed by library preparation and high-throughput sequencing using Genotyping-by-Sequencing (GBS). Samples were genotyped for single nucleotide polymorphisms (SNPs) and aligned to the bw6 version of the SBW genome. This dataset represents one of the most extensive genotypic datasets to date for a boreal insect, and is unique as it includes multiple years during a developing (ongoing, at time of sampling) outbreak. Sampling effort covered areas close to the epicenter of the outbreak (Quebec/Canada) and adjacent areas affected by the outbreak progress. This dataset also provides genome-wide characterization of SBW populations from Quebec, serving as a standard for identification of future samples regarding their locality of origin, structure and connectivity. These data represent a valuable novel resource for further study of the spatial and temporal dynamics of SBW, and how spatial genetic diversity and gene flow is affected by population outbreaks. These data provide a temporal snapshot of SBW genetic diversity, which can serve as baseline for future studies regarding outbreaks, and the impact of human-induced environmental changes on complex population dynamics. This genotype dataset comprises a unique representation of genomic-level composition and variation observed in subsequent generations of an irruptive, cyclic outbreaking species, and is of utmost importance for exploring and describing how accelerated demographic variation impacts the development of spatial genetic structure across heterogeneous landscapes. We believe this dataset is essential to management and conservation biology initiatives not only for SBW and boreal forests, but also providing a starting point for broader evolutionary and ecological studies of complex population dynamics. Furthermore, the knowledge, data collection, curation framework we present here can be used to inform similar spatial temporal baseline studies of other outbreaking (e.g., mountain pine beetle, red-backed voles) and invasive species (e.g., spongy moth, emerald ash borer).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,338 | 0,062 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».