MétaCan
Menu
← Back to cohort
Record W2895034418

Progression of marine phytoplankton blooms and environmental dynamics from sea-ice coverage to open waters in the coastal Arctic: comparing experimental data with continuous cabled observations

2018· dissertation· en· W2895034418 on OpenAlexaboutno aff
Lucianne M. Marshall

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2018
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsOceanographyPhytoplanktonArcticEnvironmental scienceSea iceAlgal bloomOpen waterThe arcticOpen seaFisheryGeologyEcologyBiologyNutrient
DOInot available

Abstract

fetched live from OpenAlex

In this thesis, I present a unique temporal study of phytoplankton, nutrient and environmental dynamics that focussed on the transitional period between sea-ice cover conditions and open waters in a coastal inlet of the Canadian Arctic during 2016. I also compared the 2016 experimental data with continuous observations made by the Ocean Networks Canada (ONC) underwater observatory. Surface seawater sampling was conducted in Cambridge Bay with high temporal resolution from June 16 to August 3, to measure phytoplankton carbon and nitrate utilisation, silica production, phytoplankton biomass, phytoplankton taxonomy and dissolved nutrients. Throughout the study period, nitrate concentrations averaged 0.67  0.08 µmol L-1, and chlorophyll a and primary production were low at 0.11  0.005 µg L-1 and 0.25  0.02 µmol C L-1 d-1, respectively. The presence of sea-ice reduced physical mixing, which resulted in low surface nitrate concentrations. Phytoplankton assemblages, production rates and biomass were dominated by small flagellated cells (<5 µm) until late July, yet increases in temperature and nitrate later in the season enabled larger Chaetoceros spp. diatoms to bloom. The Chaetoceros bloom coincided with a peak in silica production (0.429 µmol Si L-1 d-1), which was otherwise low, but variable. The time series was divided into three phases based on changes in environmental conditions, these phases were used to evaluate changes in biological dynamics. Phase I was characterised by sea-ice, low nitrate and increasing phytoplankton biomass and primary production. Phase II was a transitional period, with calm water conditions a drop in phytoplankton biomass, however, an increase in the mean nitrate concentration enabled more consistent carbon fixation. PIII had greater environmental variability driven by mixing events. The mixing of the water column in PIII enabled larger Chaetoceors spp. to become prevalent in the surface waters contributing increasingly to the biomass and carbon utilisation. Overall, the nutrient concentrations, levels of biomass and production rates in Cambridge Bay were more reflective of those from oligotrophic regions. When comparing experimental data with observations made by the ONC observatory, a strong relationship between carbon utilisation and apparent oxygen utilisation became evident. This finding suggests that long-term in situ observations can potentially be used to monitor biological rates in the Arctic. The temporal resolution of this field study adds a seasonal perspective to our understanding of Arctic ecosystems, complements studies with greater spatial and interannual coverage, and can contribute to future numerical modelling of Arctic change. Furthermore, this study provides a first-time comparison between experimentally-measured phytoplankton production and cabled observations in the Arctic.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.184
Threshold uncertainty score0.365

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.260
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueUVic’s Research and Learning Repository (University of Victoria)→Same topicArctic and Antarctic ice dynamics→French-language works237,207→