Diatom abundance and community structure in Barkley Sound, Vancouver Island, BC: significant impacts on primary productivity
Bibliographic record
Abstract
Climate change and the ocean's affects on CO 2 in the atmosphere have been recent topics of interest.As more information is obtained about the role of phytoplankton in carbon export, a process commonly known as the biological pump, the importance of these organisms gains better recognition.Little is known about diatom abundance and community structure on the coastal fjords and embayments of Vancouver Island.Large diatoms increase zooplankton abundance, leading to increased carbon export through fecal pellets.Large diatoms also affect carbon flux directly by sinking faster than smaller diatoms, which may remain suspended in the water column.This validates the significant influence of large diatoms in carbon export.The study took place in the Barkley Sound, Vancouver Island, Canada.Chlorophyll a concentrations, oxygen concentrations and biogenic silica concentrations were sampled using Niskin bottles attached to a CTD.Phytoplankton community structure was determined by using microscopy for genera identification.The results suggest sampling took place during the early stages of a spring bloom in Trevor Channel and a more stable bloom in Effingham Inlet.There was high phytoplankton biomass and high diatom biomass Effingham Inlet as well as higher primary productivity in Effingham Inlet.The spring bloom was dominated by Skeletonema, accounting for over 80% of absolute abundances.High abundances of Skeletonema correlated with high primary productivity in Trevor Channel.her guidance in helping me process and analyze my data.I would like to thank the Armbrust lab for letting me use their facilities for my biogenic silica analysis and Kathy Newell for letting me use her lab for the phytoplankton/diatom counts and for her help in this process.I would like to thank Carly Moreno, who collaborated with me in measuring primary productivity and diatom cell counts and also collected my Effingham Inlet samples.I would like to thank Rachel Emswiler for making the CTD data accessible and Dane Logan for sharing his map of Barkley Sound and Ashley Leung for sharing her data.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".