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Record W1872947996 · doi:10.1111/bij.12122

Ontogenetic shifts in phenotype-environment associations in Nile perch,<i>Lates niloticus</i>(Perciformes: Latidae) from Lake Nabugabo, Uganda

2013· article· en· W1872947996 on OpenAlexafffund
Elizabeth A. Nyboer, Lauren J. Chapman

Bibliographic record

VenueBiological Journal of the Linnean Society · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBiologyPerchLatesEcomorphologyMorphometricsEcologyHabitatPerciformesPredationPhenotypic plasticityOntogenyAbiotic componentZoologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Habitat-associated trait divergence may vary across ontogeny if there are strong size-related shifts in selection pressures. We quantified patterns of phenotypic divergence in Nile perch (Lates niloticus) from ecologically distinct wetland edge and forest edge habitats in Lake Nabugabo, Uganda, and we compared patterns of divergence across three size classes to determine whether trends are consistent through Nile perch ontogeny. We predicted that inter-habitat variation in biotic (e.g. vegetation structure) and abiotic (e.g. dissolved oxygen concentration) variables may create divergent selective regimes. We compared body morphology using geometric morphometrics and found substantial differences between habitats, although not all trends were consistent across size classes. The most striking aspects of divergence in small Nile perch were in mouth orientation, head size, and development of the caudal region. Medium-sized Nile perch also showed differences in mouth orientation. Differences in large individuals were related to eye size and orientation, as well as caudal length. The observed patterns of divergence are consistent with functional morphological predictions for fish across divergent trophic regimes, high and low predation environments, and complex and simple habitats. Although this suggests adaptive divergence, the source of phenotypic variation is unknown and may reflect phenotypic plasticity and/or genetic differences. © 2013 The Linnean Society of London, Biological Journal of the Linnean Society, 2013, 110, 449–465.

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)0.001
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 score0.003
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.194
Teacher spread0.175 · 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

Citations13
Published2013
Admission routes2
Has abstractyes

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