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Record W2413817559 · doi:10.1093/plankt/fbw008

High intraspecific variation in fatty acids of<i>Eudiaptomus</i>in boreal and subarctic lakes

2016· article· en· W2413817559 on OpenAlexaff
Minna Hiltunen, Sami J. Taipale, Ursula Strandberg, Kimmo K. Kahilainen, Paula Kankaala

Bibliographic record

VenueJournal of Plankton Research · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsToronto Metropolitan University
FundersAcademy of Finland
KeywordsSubarctic climateZooplanktonBorealPhytoplanktonBiologyCopepodAbiotic componentEcologyNutrientCrustacean

Abstract

fetched live from OpenAlex

The fatty acid (FA) composition of zooplankton has taxon-specific characteristics but may also be influenced by various environmental factors. Abiotic properties of lakes (location, morphometry, water chemistry and temperature) shape the phytoplankton community structure. We studied how this may be manifested in the FA composition of the common freshwater calanoid copepod &lt;it&gt;Eudiaptomus&lt;/it&gt; spp. The proportions of saturated and polyunsaturated FA in &lt;it&gt;Eudiaptomus,&lt;/it&gt; sampled from 25 lakes in boreal and subarctic regions, showed large variation (ca. 20–60 and 30–70%, respectively), while the proportion of monounsaturated FA was less variable (5–15%). The FA composition of &lt;it&gt;Eudiaptomus&lt;/it&gt; differed significantly between subarctic and boreal lakes. &lt;it&gt;Eudiaptomus&lt;/it&gt; from subarctic lakes had a higher proportion of 22:6ω3 and lower proportions of 18:2ω6, 18:3ω3 and 20:5ω3 than &lt;it&gt;Eudiaptomus&lt;/it&gt; from boreal lakes. In the boreal lakes, the ω3:ω6 ratio in &lt;it&gt;Eudiaptomus&lt;/it&gt; increased with increasing nutrients, chl &lt;it&gt;a&lt;/it&gt; and dissolved organic carbon, presumably due to parallel changes in phytoplankton community composition, but only in the large and clearwater lakes, and not in the small and humic ones. Copepods are seasonally important prey for planktivorous fish, and the observed among-lake differences in the proportions of essential FA may influence fish growth and reproduction.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.429

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.281
Teacher spread0.258 · 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 teacher head, 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

Citations18
Published2016
Admission routes1
Has abstractyes

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