Quantifying spatiotemporal variability in mesozooplankton distribution and nutritional quality around seamounts within the Canadian Offshore Pacific Bioregion
Bibliographic record
Abstract
Zooplankton are a diverse group of organisms that are the key link between primary producers and higher trophic levels in marine ecosystems. They are an important food source for many fish, marine mammal, and sea bird species, and are a major allochthonous energy source for seamounts. Therefore, zooplankton are an important indicator of ecosystem processes in the open ocean. The southern portion of the Canadian Offshore Pacific Bioregion (OPB), in the Northeast Pacific, is a seamount-rich environment that has recently been a target of conservation efforts by the Canadian Government via the proposal of the Tang.G̲wan - ḥačxwiqak - Tsig̲is (TḥT) Marine Protected Area (MPA). Oceanographic research expeditions (Northeast Pacific Deep-sea Exploration Project; NEPDEP) from 2015 to 2022 surveyed near seamounts to inform the monitoring and management of TḥT and other MPAs in the Canadian OPB. Part of this sampling program included oceanographic and zooplankton sampling. Marine monitoring typically only accounts for variability in zooplankton biomass and/or species abundance, overlooking potential variability in zooplankton nutritional quality. This thesis uses size fractionated zooplankton biomass samples to quantify the spatiotemporal variability in zooplankton biomass and nutritional quality (i.e., energy density, total lipids, and total proteins) in the Canadian OPB. The data presented in this thesis indicate that zooplankton distribution is driven primarily by mesoscale oceanographic processes and not by the presence of seamounts, per se. Interannual variability was the most significant driver of change in the zooplankton community, representing up to a 7-fold difference in biomass and up to a 2-fold difference in zooplankton nutritional quality, where generally warm (cool) water years had less (more) nutritious zooplankton communities. Spatially, there were distinct differences between zooplankton collected within offshore and continental slope regions, which influences the allochthonous energy provided to seamount ecosystems. This data was also used to identify key zooplankton taxa which appear to have a disproportionate effect on total zooplankton nutritional quality. Notably, Neocalanus spp. were associated with lipid-rich zooplankton samples, while gelatinous species (e.g., doliolids and salps) were associated with lower energy density. These data and analyses have important implications for the future monitoring and conservation of the Canadian OPB and provide important baseline characterization of the spatiotemporal variability of the zooplankton community around seamounts in this region.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".