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Food web characteristics of High-Arctic Greiner Lake near Cambridge Bay (Ikaluktutiak), Nunavut, Canada

2020· dataset· en· W6936972470 on OpenAlexaboutno aff

Bibliographic record

VenueNordicana D · 2020
Typedataset
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsFood webBayArcticZooplanktonPelagic zoneBiome

Abstract

fetched live from OpenAlex

The Arctic biome is currently undergoing major modifications with climate change. Arctic freshwater ecosystems, as sentinel ecosystems, can record major climate changes before they affect the entire region. However, to fully evaluate the amplitude of changes in Arctic freshwaters, we need to be able to compare future measurements to baseline data. To date, the food web characteristics of lakes are poorly described in remoter Arctic areas of Canada. Greiner Lake is located in the High-Arctic near Cambridge Bay (Ikalutktutiak) on Victoria Island, Nunavut, Canada, and is an important site for Inuit communities as it has always been known to support high fish biomass. The Lake Greiner watershed also represents a key monitoring site for the recently open Canadian High-Arctic Research Station (CHARS). We provide here a summary of the food web characteristics for Greiner Lake including data on primary producers, littoral and pelagic consumers and apex fish predators. The data were collected during the summers of 2017, 2018 and 2019. Organisms were collected with different types of nets (gill nets, zooplankton nets and kick-nets) and treated on site at CHARS for further analyses. Samples for stable isotopes and fatty acid analyses were preserved at -20°C at CHARS. Samples for stable isotopes were then sent to the stable isotope laboratory of Environment and Climate Change Canada at the University of Saskatchewan. Samples for fatty acid analyses were extracted, analyzed and quantified at University of Quebec In Chicoutimi, Quebec, Canada. Zooplankton community samples were preserved with 4% formaldehyde and then identified using an inverted microscope and binocular. Length measurements of individuals were used to calculate the zooplankton biomass with length-weight relationships and aid in determination of species composition. Algae biomass production (benthic and pelagic) were calculated with 14C assimilation and subsequent measure in a scintillation counter. Bacterial production was measured via assimilation of tritiated leucine. Zooplankton production was estimated via the measurement of enzymes released in water by organisms. Finally, we describe the species composition of the fish community and use their stomach contents to infer diet. The data allowed us to characterize the food web structure and provide estimation of fatty acid origin and transfer within the food web. The baseline data provided will permit future estimates of the amplitude of changes in the region and aid in the prediction of possible trajectories of Arctic freshwaters under human-induced stress.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.147
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.012
GPT teacher head0.213
Teacher spread0.202 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2020
Admission routes1
Has abstractyes

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