Spatiotemporal data of algal blooms phenology
Notice bibliographique
Résumé
The spatio-temporal data contain annual phytoplankton bloom phenology from 2000 to 2016 on 580 lakes located in the province of Quebec, Canada, between 44 and 50°N and 67 and 80°W. The data include height phenological variables related to phytoplankton blooms, and 17 physiographical, morphological, and climatic descriptors of the lake and the watershed. For each studied year, phenological variables were established as follows: (1) the frequency (the number of days when Chl-a concentrations remained above the threshold), (2) the intensity (the maximum concentration of Chl-a detected during a bloom), (3) the relative area (the maximum area occupied by a bloom normalized by the lake area), (4) the onset date and (5) the end date (respectively, the first and last day of the year when a bloom was detected), and (6) the duration (the number of days between the onset date and the end date). Remote sensing determination of the end date and duration of blooms is challenging because the studied region is frequently covered by clouds during the fall, significantly reducing the number of MODIS images available for this period. This is especially true during the month of October, for which there was on average half as many MODIS images without full cloud cover than between May and September. The variables describe what can be considered as an annual-based phenology, compiling days with less than 25% cloud cover and for which remotely sensed Chl-a was above the established threshold, for any given pixel. A geo-referenced database of 17 morphological, physiographic, and climatic characteristics of the watershed of each studied lake was established. The boundaries and morphological descriptors of the watersheds (area, slope) were calculated from the Canadian Digital Elevation Model with a spatial resolution of approximately 30 m. Climate data were calculated from North American Regional Reanalyses with a spatial resolution of approximately 32 km. The cumulative degree-days (°C day) was calculated by summing the recorded degrees (°C) each day above 20°C, considered as a threshold for cyanobacterial growth. Even though the remote sensing approach used here is not specific to cyanobacterial biomass, this climate proxy is considered valid since algal growth in general is stimulated by warm waters. Land use data (at 40 m spatial resolution) as well as agricultural and ecumene data (at 25 m spatial resolution) were provided by Natural Resources Canada. The environmental indicators were considered stationary over the period 2000–2016.
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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) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».