Implication of global climate change on the distribution and activity of Phytophthora ramorum
Notice bibliographique
Résumé
Global climate change is predicted to alter the distribution and activity of several forest pathogens. Boland et al. (2004) suggested that climate change might affect pathogen establishment, rate of disease progress, and the duration of epidemics, each in a potentially different way. In some cases, climate changes may favor the onset of disease and potentially accelerate the displacement of a tree species from portions of its current geographic range. In other instances, climate changes may be detrimental to the development of disease. Boland et al. (2004) qualitatively predicted that climate change would have a strong positive net effect on four of 18 tree pathogens in Ontario, Canada and would have a negative net effect on another four pathogens. Phytophthora ramorum is an alien invasive pathogen, likely present in the United States since the mid-1990s. The pathogen is the cause of Sudden Oak Death (SOD) and several other diseases. Infected tanoaks (Lithocarpus spp.) and oaks (Quercus spp.) are found in 14 western counties of California and one county in Oregon. Previous work has suggested that the distribution of the pathogen is affected by regional climate patterns. The purpose of the study was to quantify the potential change in occurrence of climatically suitable habitat for P. ramorum under future climate scenarios. All analyses were conducted with the ecological niche model, CLIMEX. Biological parameters describing the response of the pathogen to temperature and moisture were taken from Venette and Cohen (2006). Baseline and future climate projections, downscaled to a 10minute resolution, were obtained from worldclim.org. Baseline data represented the period from 1961-1990. Climate projections were based on the Canadian General Circulation Model-1 (CGCM1) from the Canadian Centre for Climate Modeling and Analysis under emissions scenario b2 (assumes slowed population growth and reduced greenhouse gas emissions). Climate projections were available for the years 2020, 2050, and 2080. For each year, CLIMEX provided several indices of climatic suitability for the presence of the species. The Ecoclimatic index provides a measure of overall habitat suitability. The Ecoclimatic Index for the baseline climate data gave a qualitatively satisfactory fit to observed occurrences of the pathogen in California. The pathogen was observed more often in areas that were predicted to be favorable or very favorable than in areas predicted to be marginal or unsuitable. Because the model parameters were not estimated directly or indirectly from field observations, the field observations provide a completely independent validation of the model. The baseline model predicts that climatically favorable or very favorable habitat in the contiguous US should currently extend along the west coast from approximately Monterey, CA to Puget Sound, WA. Large areas of climatically suitable habitat also occur in the eastern half of the United States. Based on the predictions from CGCM1, we predict that the area that is favorable or very favorable will decrease substantially in the eastern US, but will increase in WA, OR, and CA. By 2050, favorable habitat will extend from Los Angeles, CA to Puget Sound, WA. Inland progression of climatically favorable habitat, even by 2080, is predicted to be modest. In the eastern US, only fragmented pockets of favorable or very favorable habitat are predicted to occur in far western North Carolina, in the northeast quarter of West Virginia, and a small region from northern New Jersey to the southern half of Massachusetts.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».