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Record W1515391913 · doi:10.1002/ece3.235

Fine‐scale parallel patterns in diversity of small benthic Arctic charr (<i>Salvelinus alpinus</i>) in relation to the ecology of lava/groundwater habitats

2012· article· en· W1515391913 on OpenAlexfundno aff
Bjarni K. Kristjánsson, Skúli Skúlason, Sigurður S. Snorrason, David L. G. Noakes

Bibliographic record

VenueEcology and Evolution · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSalvelinusEcologyHabitatBenthic zoneBiologyArcticBiodiversityDiversity (politics)TroutFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

It is critical to study factors that are important for origin and maintenance of biological diversity. A comparative approach involving a large number of populations is particularly useful. We use this approach to study the relationship between ecological factors and phenotypic diversity in Icelandic Arctic charr (Salvelinus alpinus). Numerous populations of small benthic charr have evolved in lava springs in Iceland. These charr appear morphologically similar, but differ in important morphological features related to feeding. We found a clear relationship between diversity in morphology, diet, and ecological factors among populations. In particular, there were clear differences in morphology and diet between fish coming from habitats where the lava spring flowed on as a stream compared to habitats where the lava spring flowed into a pond. Our study shows that ecological factors are important for the origin and maintenance of biological diversity. The relationship between phenotype and ecological factors are observed on a fine scale, when comparing numerous populations that are phenotypically similar. This strongly suggests that for understanding, managing, and conserving biological diversity important ecological variables have to be taken into the account.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.152
Threshold uncertainty score0.862

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)0.0000.000

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 head0.012
GPT teacher head0.201
Teacher spread0.189 · 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

Citations55
Published2012
Admission routes1
Has abstractyes

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