Protistan plankton time series from the northern Salish Sea and Central Coast, British Columbia, Canada
Bibliographic record
Abstract
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".