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Record W2613388136 · doi:10.1093/icesjms/fsx077

High fishing intensity reduces females’ sperm reserve and brood fecundity in a eubrachyuran crab subject to sex- and size-biased harvest

2017· article· en· W2613388136 on OpenAlexaff
Luis Miguel Pardo, Marcela Paz Riveros, Juan Pablo Fuentes, Ramona Pinochet, Carla Cárdenas, Bernard Sainte‐Marie

Bibliographic record

VenueICES Journal of Marine Science · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicCrustacean biology and ecology
Canadian institutionsFisheries and Oceans Canada
FundersFondo de Financiamiento de Centros de Investigación en Áreas PrioritariasFondo Nacional de Desarrollo Científico y Tecnológico
KeywordsFecunditySpermBroodBiologyFishingPopulationEcologyZoologyFisheryDemographyBotany

Abstract

fetched live from OpenAlex

Abstract Size-selective male fisheries may result in sperm limitation whereby the number of sperm is insufficient to fertilize all oöcytes produced by females. In eubrachyuran crabs, females have seminal receptacles for sperm storage which may reduce the risk of sperm limitation over their lifetime. In this study on the commercially exploited eubrachyuran Metacarcinus edwardsii, we evaluate the sperm limitation hypothesis by measuring female reproductive success in five Chilean populations subjected to low or high fishing intensity. The quantity and viability of sperm stored by females was measured in each season and population, and related to resulting brood fecundity. Females’ sperm reserve was larger when fishing intensity was low than when it was high—paralleling previously demonstrated differences in males’ sperm reserve—and especially in the season before oviposition. Sperm viability was in general high (92%) and independent of fishing intensity. Mean brood fecundity adjusted to constant female size was about 60% greater under low compared with high fishing intensity. Thus, in M. edwardsii, population reproductive output could be depressed by male-biased fishing in spite of female sperm storage capability.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.017
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.002
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 head0.026
GPT teacher head0.277
Teacher spread0.251 · 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

Citations32
Published2017
Admission routes1
Has abstractyes

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