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Record W6892075140 · doi:10.5061/dryad.55c84q7

Data from: Life at the top: lake ecotype influences the foraging patterns, metabolic costs and life history of an apex fish predator

2018· dataset· en· W6892075140 on OpenAlexaff

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2018
Typedataset
Languageen
Field
Topic
Canadian institutionsLakehead UniversityFisheries and Oceans CanadaUniversity of Toronto
Fundersnot available
KeywordsPredationDiel vertical migrationPredatorForagingApex predatorPelagic zoneLittoral zoneInvertebrateAllometry

Abstract

fetched live from OpenAlex

1.We used acoustic telemetry and acceleration sensors to compare population-specific measures of the metabolic costs of an apex fish predator living in four separate lakes. We chose our study species and populations to provide a strong test of recent theoretical predictions that optimal foraging by an apex fish predator in a typical aquatic environment would be consistent with feeding to satiation rather than continuous feeding. We chose four populations where the primary prey type differed along a body size gradient (from small invertebrates to large planktivorous fish) and along a thermal accessibility gradient (from easily accessible coldwater pelagic prey to less accessible warmwater epilimnetic and littoral prey). We expected that these gradients in prey type would evoke distinctly different activity gradients depending on whether predators fed to satiation (e.g. less frequent ‘rest’ detections where primary prey are smaller/less accessible) or fed continuously (e.g. fixed level of ‘rest’ detections under all prey conditions). 2. Our study organism was a fall spawning, coldwater visual apex predator (lake trout). Therefore, we focused our study on diel (early night, dawn, day, dusk, late night) changes in metabolic costs associated with summer feeding behaviour. The duration (~20 days) and fine temporal scale (~30 minutes) of our behavioural data provided a uniquely detailed picture of intra- and inter-population differences in activity patterns over a critical period in the annual growing season. 3. In all populations, diel shifts in activity were qualitatively consistent with that expected of a visual predator (e.g. resting state detections were most frequent at night). 4. Between-lake differences in daytime thermal experience were qualitatively consistent with between-lake differences in the location of primary prey (e.g. excursions to warm habitats were common in lakes with epilimnetic/littoral fish as primary prey and relatively rare in lakes with pelagic coldwater invertebrates/fish as primary prey). 5. Daytime activity patterns were consistent with feeding to satiation rather than continuous feeding: (a) individuals in all four populations exhibited clearly delineated bouts of resting behaviour and active behaviour; (b) the frequency of resting bouts and the resultant overall cost of daily activity were strongly associated with the size and accessibility of prey – in lakes with smaller and/or less accessible prey, predators rested less frequently, exhibited marginally higher costs when active and had higher overall daytime activity costs. Within each lake, similar changes in activity occurred concurrently with diel changes in prey accessibility/relative density.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.049
Threshold uncertainty score0.165

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0490.012

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 head0.038
GPT teacher head0.272
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 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
Published2018
Admission routes1
Has abstractyes

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