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Record W2926204011 · doi:10.1111/fwb.13280

The influence of abiotic incubation conditions on the winter mortality of wild salmonid embryos

2019· article· en· W2926204011 on OpenAlexafffundabout
J. Michelle Lavery, Richard A. Cunjak

Bibliographic record

VenueFreshwater Biology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAbiotic componentBiologyEcologyIncubationSTREAMSSalmoPopulationBiotic componentEnvironmental scienceFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract Embryos of many valued salmonid species incubate in the hyporheic zone of boreal streams over winter. Influence of individual winter‐related environmental variables on salmonid embryo success has been previously investigated. However, how multiple variables act together to influence embryo incubation remains poorly understood. Using a naturally spawning population of Atlantic salmon ( Salmo salar ) in the Miramichi River basin (New Brunswick, Canada), we related variation in the abiotic embryo incubation habitat in different streams (spatial) and over the course of two winters (temporal) to embryo mortality between fertilisation and hatch. Over two years (2013–2014 and 2014–2015), we introduced fertilised eggs to six simulated salmon redds in each of three riffles in each of five active spawning reaches ( n redds = 90) with a range of hyporheic conditions. Embryo mortality was quantified at an early sampling event (March; pre‐freshet and during late embryonic development) and a late sampling event (May; post‐freshet and post‐hatch). We extracted 22 abiotic predictor variables for statistical analyses from continuous records of hyporheic environmental conditions, collected for the duration of the incubation period in each study reach. Through partial least squares regression analyses, 37.6% of the total variation in mortality was explained by the predictor variables. Each group of predictor variables explained similar proportions of variation (water temperature: 8.4%, water level: 7.4%, dissolved oxygen: 7.1%, ice conditions: 7.2%, and substrate characteristics: 7.5%), which suggests that mortality is influenced by multiple interacting abiotic conditions, rather than a single variable in isolation, and that the factors contributing to ideal salmonid incubation habitats are complex and interconnected. Our research highlights the value of a multi‐faceted research perspective and provides a baseline from which future changes in threatened salmonid populations can be measured and compared in an effort to identify relevant species‐ or population‐specific differences.

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 categoriesInsufficient payload (model declined to judge)
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 score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.236
Teacher spread0.227 · 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.

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

Citations10
Published2019
Admission routes3
Has abstractyes

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