Assessment of crop losses from ozone using biomonitor plants and risk estimates by experts
Notice bibliographique
Résumé
Environmental policy makers are required to make decisions under uncertainty regarding the benefits and costs of specific regulatory action. Uncertainty is a phenomenon that cannot be avoided in the assessment of environmental impacts, due to the inherent stochasticity of environmental systems, as well as a lack of adequate empirical data related to specific cause and effect relationships. A primary constraint associated with generation of adequate data from experiments is that environmental research is expensive, and conclusive results may take several years to obtain. In the meantime, significant impacts could be occurring, virtually undetected. A high degree of uncertainty exists in the assessment of the potential effects of ozone (O₃) pollution on agricultural crop yield. Thus, the purpose of this research was to provide information related to the potential impacts of O₃ pollution on crops in the Fraser Valley east of Vancouver, British Columbia, Canada. Two alternate methods were utilized: (i) biomonitoring with Bel W-3 tobacco, a plant variety that is very sensitive to O₃, and (ii) expert judgments of the risks of crop losses from O₃. The biomonitor survey was conducted over three growing seasons (1985 - 1987), in which ambient O₃ pollution conditions were atypically low, limiting the injury response data obtained. However, a correlation was established between biomonitor injury response and ambient O₃ levels, demonstrating that phytotoxic pollution conditions occurred during these years. Calibration of biomonitor injury response with crop yield losses revealed the following: (i) yield losses due to O₃ exposure are likely in the event that biomonitor plants exhibit O₃-induced injury symptoms, and (ii) the absence of biomonitor injury does not preclude the possibility of crop loss, since the O₃ exposure threshold for biomonitor injury may exceed that for loss of certain crops. Although experts are commonly used to provide judgments of potential impacts under uncertainty, there is a paucity of information regarding the desirable attributes of expertise. Selection of experts is largely an ambiguous task, and choices of experts by different persons are likely to be inconsistent. Prior to selection of experts for this project, a comprehensive survey was conducted of over 200 environmental professionals to determine the characteristics of an expert in O₃ effects on crops. It was shown that expertise in this area involves a considerable number of attributes. These were grouped, using factor analysis, into seven independent dimensions: education, type of career experience, length of career experience, cognitive skills, personal qualities related to credibility, scientific recognition and involvement in the scientific community. In general, there was agreement between different groups (e.g., research scientists and members of conservation groups) regarding the relative importance of the various dimensions of expertise. Nine crop loss experts were selected, based on nomination by a large group (166) of their scientific peers. It was demonstrated with regression analysis that nominated experts exhibited the attributes identified in the survey. Logit models were estimated that predict an individual's degree of expertise in O₃ effects on crops, based on specific attributes possessed by that individual. Independent judgments were then obtained from the nine experts regarding probable crop losses under typical O₃ pollution conditions in the Fraser Valley. Probabilistic judgments of crop losses were generally similar among experts and approximated the level of crop losses predicted from the biomonitor survey. Limited empirical exposure-response information for Fraser Valley crops indicated that some cultivars may be more sensitive than assumed by the experts. Additional exposure-response experiments will be required to determine the source of this inconsistency.
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 | 0,005 | 0,005 |
| Méta-épidémiologie (sens strict) | 0,001 | 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 | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».