Protistan plankton time series from the northern Salish Sea and Central Coast, British Columbia, Canada
Notice bibliographique
Résumé
The Hakai Institute Oceanography Program has been monitoring surface (0-1 or 5m depth) protistan plankton community composition, via optical microscopy, at multiple time series stations in the northern Salish Sea (Strait of Georgia) and central coast of British Columbia since 2016 and 2019, respectively. In the northern Salish Sea, data were collected weekly to bi-weekly in surface waters (0-1m prior to April 2019 and 5m afterwards) at a fixed time series location (QU39). On the central coast, data were collected monthly at three locations: within a fjord (River’s Inlet, DFO2), Fitz-Hugh Channel (KC10) and on the shelf (QCS01). Water samples were collected using a Niskin bottle from small research vessels (less than 40 ft). Sample water was transferred into 250 mL amber glass bottles and immediately fixed using Lugol's acid-iodine solution (1% concentration) (Edler & Elbrächter 2010; Del Bel Belluz et al., 2021). Samples were kept cool and stored in a dark fridge until analysis was performed at LCLJ Marine Ecological Services in Victoria, BC, by Dr. Louis Hobson. Protistan plankton were enumerated following the Utermöhl method (Utermöhl, 1931; Edler & Elbrächter 2010) using 50 mL settling chambers and phase contrast microscopy on an inverted light microscope (Hobson & Galbraith, 2018). The analysis targets autotrophic protists, but includes all visible taxa including mixotrophic and heterotrophic microzooplankton species. In addition, harmful algae species are enumerated. The analyst is generally able to resolve species as small as 4 um and taxa are classified to the lowest taxonomic level usually to genus or species. Results are provided as abundance of species in cells/L. These data are published on the Ocean Biodiversity Information System (OBIS) following the required Darwin Core biodiversity data standards (https://manual.obis.org/). In accordance with these standards, taxa name (scientificName) represent the currently accepted name on the World Register of Marine Species (WoRMs). Data are freely available for download from OBIS at https://ipt.iobis.org/obiscanada/resource?r=hakai_protistan_plankton_qu39&v=1.4 and from the Global Biodiversity Information Facility at https://doi.org/10.15468/q748tc. These time series are maintained to characterize and monitor protistan plankton diversity and investigate links to environmental drivers, the food web and carbon dynamics. Additionally, data are used to support group level phytoplankton composition derived via HPLC phytoplankton pigment analysis, particulate organic matter fatty acid analysis, molecular methods (eDNA) and to validate remote sensing products. In the northern Salish Sea, portions of this time series have been published in Del Bel Belluz et al. (2021) and Mclaskey et al. (2022). On the central coast, data have been used to investigate trends and drivers of protistan plankton communities across a fjord to shelf gradient (Del Bel Belluz, submitted). Phytoplankton form the base of the marine food web and drive marine biogeochemical cycling. These species have high turnover rates and quickly respond to environmental perturbation. As a result they are valuable indicators of ecological change. High temporal resolution long term time series are invaluable for investigating dynamic coastal waters with highly variable protistan plankton communities.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,000 | 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 tête enseignante, 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 ».