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Record W2061839758 · doi:10.1007/s11160-009-9127-0

A synthesis of the ecological processes influencing variation in life history and movement patterns of American eel: towards a global assessment

2009· article· en· W2061839758 on OpenAlexaff
Luis A. Vélez‐Espino, Marten A. Koops

Bibliographic record

VenueReviews in Fish Biology and Fisheries · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReproductive biology and impacts on aquatic species
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsPanmixiaBiologyEcologyHabitatPopulationProductivityFisheryLife history theoryRange (aeronautics)Fisheries managementLife historyGenetic structureFishing

Abstract

fetched live from OpenAlex

American eel, Anguilla rostrata , is a catadromous fish that spawns in the Sargasso Sea and migrates to coastal waters and freshwater systems ranging from Greenland down the Atlantic coast to South America and has been regarded as comprising a panmictic population. American eel is in decline across much of its range. Research and management is primarily conducted at local to regional scales, yielding inconsistent research results and management recommendations that may be inhibited by large-scale processes. We review the research on American eel ecology demonstrating that its variable life history and movement patterns can be explained based on: (1) latitudinal productivity gradients; (2) ideal free habitat selection; (3) conditional evolutionarily stable life history strategies; (4) size at arrival to the coast (correlated with distance from the spawning grounds); and, (5) temperature variance and annual degree-day effects on somatic growth. Using these ecological processes, we outline how local and large-scale effects on American eel dynamics can be integrated in a panmictic (or quasi-panmictic) modelling framework to enable defensible predictions of population responses to anthropogenic and oceanic phenomena. Due to its widespread distribution and existing knowledge gaps, the conservation and management of American eel will require international cooperation.

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)0.002
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 score0.028
Threshold uncertainty score0.282

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0000.000

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 head0.022
GPT teacher head0.286
Teacher spread0.264 · 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

Citations43
Published2009
Admission routes1
Has abstractyes

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