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Record W2065559541 · doi:10.1139/f09-151

Long-term food web change in Lake Superior

2009· article· en· W2065559541 on OpenAlexvenueno aff
Stephanie N. Schmidt, M. Jake Vander Zanden, James F. Kitchell

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsFood webTrophic levelCoregonus clupeaformisContext (archaeology)EcologyIsotope analysisBiologyGeographyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Restoration and rehabilitation of native species in the Laurentian Great Lakes is a priority for fisheries management agencies. Restoration efforts are increasingly incorporating a perspective that considers species within a broader food web context. We used stable isotope analysis and museum-preserved specimens to describe and quantify 100 years of food web changes in the Lake Superior fish community. We validated stable isotope analysis of museum specimens by showing a positive correlation between isotope- and diet-based estimates of trophic position. While introductions have created a more trophically diverse food web than historically found in Lake Superior, two separate metrics revealed little community-wide change in the food web. Our species-specific analysis revealed trophic niche differences between shortjaw ( Coregonus zenithicus ) and shortnose ( Coregonus reighardi ) ciscoes, two species previously argued to be indistinguishable based on morphological characteristics. By providing a historical context, our findings show the ability of the Lake Superior food web to accommodate non-native species introductions over the last century while still supporting native species populations. This long-term information about food web structure can help guide management and restoration goals in Lake Superior. Furthermore, Lake Superior can serve as a basis for comparing food web changes in other, more highly altered Great 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 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 score0.726
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.229
Teacher spread0.207 · 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

Citations68
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicIsotope Analysis in EcologyFrench-language works237,207