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Record W2045357748 · doi:10.1080/02755947.2013.785995

Differentiating between Sampling‐ and Environment‐Related Mortality in Shortnose Sturgeon Larvae Collected Using Anchored D‐Frame Nets

2013· article· en· W2045357748 on OpenAlexafffund
Sima Usvyatsov, James Watmough, Matthew K. Litvak

Bibliographic record

VenueNorth American Journal of Fisheries Management · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of New BrunswickMount Allison University
FundersFonds en Fiducie pour la Faune du Nouveau-BrunswickMitacs
KeywordsLarvaIchthyoplanktonBiologySturgeonAcipenserZoologyLake sturgeonFisheryEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract This study provided the first attempt to differentiate between environmental‐ and sampling‐related mortality in larval Shortnose Sturgeon Acipenser brevirostrum. Anchored D‐frame nets are widely used for sampling sturgeon larvae, but the associated larval mortality rates are not known. We assessed larval mortality (1) by examining the effect of net deployment period on mortality rate; (2) directly, by deploying live larvae in nets and observing survival over time; and (3) indirectly, by establishing the time of larval death based on body decomposition. Larval mortality in nets deployed for 12 and 24 h was similar: 50% of the nets contained no live larvae. After a 6‐h deployment, half of the nets contained 60% or more live larvae. After placement of live larvae in nets for 12 h, the nets retained 60.0 ± 20.4% (mean ± SE) of the deployed larvae. Of the retained larvae, only 6.5 ± 2.3% (mean ± SE) survived 12 h inside the net. Decomposition rates of dead larvae were examined both in a controlled environment and in the nets. Dead larvae that were deployed in nets decomposed faster than those in a controlled environment, with high decay after only 12 h of deployment. A discriminant function analysis differentiated well between larvae that had been dead for 9 h and larvae that had been dead for 21 or 32 h. The assessment of time of death based on decomposition was used to identify the cause of mortality for Shortnose Sturgeon larvae collected in the Saint John River, New Brunswick, during 2008–2010. We propose that in short to medium deployment periods (up to overnight), pristine and partly decayed larvae can be assigned to sampling mortality, while highly decayed larvae can be assigned to environment‐related mortality. Using this distinction, sampling and environmental sources of mortality accounted for at least 20–56% and 4–25%, respectively, of the sampled Shortnose Sturgeon larvae. Received June 13, 2012; accepted March 7, 2013

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.017
GPT teacher head0.226
Teacher spread0.209 · 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 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

Citations2
Published2013
Admission routes2
Has abstractyes

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