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Linking the occurrence of brook trout with isolation and extinction in small Boreal Shield lakes

2007· article· en· W2075071187 on OpenAlexafffundabout
Andrea Bertolo, Pierre Magnan, Michel Plante

Bibliographic record

VenueFreshwater Biology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBeaverEcologyFontinalisSalvelinusBiologyExtinction (optical mineralogy)TroutPredationEnvironmental scienceFishery

Abstract

fetched live from OpenAlex

Summary 1. We surveyed 62 Canadian Shield lakes (<50 ha) to determine the relationship between factors related to isolation and extinction and the occurrence of brook trout (BT) ( Salvelinus fontinalis ), for which local extinctions have been documented over the last century in half of the lakes. 2. Logistic regression and information–theoretic model selection were used to determine the importance for the occupancy of BT of (i) isolation factors (degree of lake connectivity and the proximity of source populations of BT in neighbouring bodies of water) and (ii) extinction factors (lake morphometry and trophic status, as proxies of the risk of lake anoxia; predation and competition; and flooding caused by beaver ( Castor canadensis ) dams, which could potentially increase the risk of anoxia). 3. Isolation factors were the best predictors of the absence of BT in these lakes. Among extinction factors, only the impact of beaver dams (as measured by an index of increased water level and mortality of shrubs and trees in the littoral zone) improved model fits. Beaver dams were present at the outlets of all study lakes, but extensive mortality of riparian trees and shrubs was more common in lakes where BT populations were extinct. 4. Taken together, these results suggest that recolonization is a major factor determining the occurrence of BT while flooding caused by beaver dams might contribute to BT extinction by increasing the likelihood of winterkill in these small lakes.

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)0.000
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 score0.105
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.014
GPT teacher head0.211
Teacher spread0.197 · 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

Citations11
Published2007
Admission routes3
Has abstractyes

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