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Record W3006048893 · doi:10.3354/meps13261

Neonatal nutritional strategy of a viviparous elasmobranch with extremely low reproductive output

2020· article· en· W3006048893 on OpenAlexaff
Bianca de Sousa Rangel, NE Hussey, Yuri Niella, Luiz Antônio Martinelli, Aline D. Gomes, RG Moreira

Bibliographic record

VenueMarine Ecology Progress Series · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBiologyOffspringTrophic levelPolyunsaturated fatty acidPregnancyForagingParental investmentδ13CReproductive successCholesterolBiomarkerZoologyInternal medicineEndocrinologyEcologyFatty acidBiochemistryStable isotope ratioGeneticsPopulation

Abstract

fetched live from OpenAlex

Throughout evolutionary history, elasmobranchs have developed diverse reproductive strategies. Little focused work, however, has addressed how neonatal nutritional state is affected by differing degrees of maternal investment associated with these markedly different reproductive strategies. To investigate the effect of maternal investment on the nutritional quality of pups during the early life history of an extremely viviparous elasmobranch, quantitative biomarker analysis including lipids, fatty acids and stable isotopes was conducted. Using the cownose ray Rhinoptera bonasus (histotrophic viviparous) as a model, we found that pups were initially born in a positive nutritional state, enriched in physiologically important essential fatty acids and nitrogen and carbon stable isotope values (δ 15 N and δ 13 C), a result of maternal intrauterine transfer. A systematic decrease in some fatty acids and δ 15 N values, as well as a decrease in cholesterol with growth, confirmed that these substrates were derived from maternal resources and used in initial metabolic processes following birth. An observed increase in condition factor, plasma essential fatty acids and triglyceride:cholesterol ratio with increasing body size identified a progression towards successful independent foraging with pups not displaying marked nutritional deficiency or fasting phases. Our multi-tracer approach allowed the identification of 2 size classes of young rays (<50 and <70 cm disc width) that displayed distinct physiological states. Since prenatal maternal investment is critical for offspring condition and to promote successful foraging post birth, understanding the trophic ecology and physiological state of pups during their first year is critical to guide management and conservation within nursery grounds.

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 score0.014
Threshold uncertainty score0.999

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.201
Teacher spread0.190 · 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

Citations26
Published2020
Admission routes1
Has abstractyes

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