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Record W4221079961 · doi:10.1002/rra.3964

Spatial patterns of stable isotopes and trophic ecology in a hydropeaking river

2022· article· en· W4221079961 on OpenAlexaff
Nicholas E. Jones, Tim Haxton

Bibliographic record

VenueRiver Research and Applications · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsTrent UniversityMinistry of Energy, Northern Development and MinesMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsTroutEnvironmental scienceTrophic levelBenthic zoneEcologyAbiotic componentBiotaFontinalisSalvelinusSculpinInvertebrateδ15NIsotope analysisδ13CStable isotope ratioHydrology (agriculture)BiologyFisheryFish <Actinopterygii>Geology

Abstract

fetched live from OpenAlex

Abstract While the impacts of dams are known, there are gaps in our understanding, particularly with respect to longitudinal patterns of environmental and biological gradients downstream of dams. We investigated longitudinal patterns of stable isotope ratios of carbon and nitrogen in brook trout ( Salvelinus fontinalis ) in the regulated Magpie River. We also examined the diet of brook trout via mixing models using the dominant forage items in the river. For brook trout, δ 13 C values increased and δ 15 N values decreased in reaches progressing downstream. River distance downstream of the dam explained the variation in levels of stable isotopes in brook trout. Most changes occurred within the first eight kilometres of the river. The fish length had a significant but weak positive effect on stable isotope levels. Based on the MixSiar mixing model, the diet of brook trout consisted of 72% longnose dace, 27% benthic invertebrates, and 1% sculpin. The Magpie River had isotope values that were lower for δ 13 C and higher for δ 15 N when compared to nine neighbouring natural unregulated rivers. Previous research on the Magpie River demonstrated that the upstream reservoir exports large quantities of plankton that likely provides a quality food source for river biota and shows a clear downstream gradient in energy sources similar to the changes found for δ 13 C. For the Magpie River, and other regulated rivers, statistical comparisons of many abiotic and biotic variables, including stable isotopes, could lead to erroneous conclusions if samples are not collected with explicit consideration of spatial gradients.

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)0.000
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 score0.031
Threshold uncertainty score0.778

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.285
Teacher spread0.261 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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