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Record W2150985248 · doi:10.1139/f04-183

Modelling habitat requirement of European fishes: do species have similar responses to local and regional environmental constraints?

2005· article· en· W2150985248 on OpenAlexvenueno aff
Didier Pont, Bernard Hugueny, Thierry Oberdorff

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLeuciscusRutilusPhoxinusElectrofishingEcologyMinnowBarbusSalmoHabitatBiologyPerchBrown troutBarbelDrainage basinCyprinidaeFisheryGeographyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

To test the hypothesis that different species have similar responses to local and regional environmental constraints, we modelled the occurrences of 13 species using a data set of 413 undisturbed river reaches. Three environmental descriptors were considered at the local scale (river slope, river width, and upstream drainage area) and three at the regional scale (mean annual and mean range air temperature and basin unit). Using multiple logistic regression modelling techniques, we correctly predicted the occurrence of 11 of the 13 retained species. The hierarchical partitioning analysis that we used allowed us to jointly consider all possible models in a multiple regression setting and to evaluate the independent explanatory power of each of our five environmental variables. We reject the hypothesis of a common species response to the environmental constraints. Species inhabiting upstream river reaches (bullhead (Cottus gobio), brown trout (Salmo trutta), minnow (Phoxinus phoxinus), and stone loach (Barbatula barbatula)) are more sensitive to basin unit. All species representative of downstream areas (barbel (Barbus barbus), dace (Leuciscus leuciscus), chub (Leuciscus cephalus), gudgeon (Gobio gobio), roach (Rutilus rutilus), bleak (Alburnus alburnus), and perch (Perca fluviatilis)) exhibit a positive continuous response to the drainage area, in agreement with the view of a continuous increase of local richness downstream. River slope is an important variable for all species. Main species habitat requirements are discussed for each species.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.999

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 studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.033
GPT teacher head0.211
Teacher spread0.179 · 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

Citations130
Published2005
Admission routes1
Has abstractyes

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