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Record W2308762221 · doi:10.1139/cjfas-2015-0460

The <i>Cladophora</i> resurgence in Lake Ontario: characterization and implications for management

2016· article· en· W2308762221 on OpenAlexvenueaboutno aff
Anika Kuczynski, Martin Auer, Colin Brooks, Amanda G. Grimm

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
FundersMichigan Technological University
KeywordsCladophoraNuisanceEcologyBiologyBiomass (ecology)DreissenaAlgaePhosphorusBivalvia

Abstract

fetched live from OpenAlex

Nuisance growth of the alga Cladophora, reported from Lake Ontario since the 1930s, abated in the decades following implementation of phosphorus control measures in the 1970s. Our examination of beach fouling records and historical observations of algal biomass has confirmed literature reports that a resurgence in nuisance growth of Cladophora has occurred since invasion of Great Lakes waters by dreissenids. Our findings indicate that the growth rate of Cladophora (specific rate of net photosynthesis) has decreased by 44% since 1972 in response to phosphorus controls. However, improved transparency, a response to mussel activity, has increased the maximum depth colonizable by Cladophora by a factor of 5 over that same interval. The net result is a sixfold increase in production potential since the late 1980s (the Post-P Management II Period) and a threefold increase since the 1970s (the Pre-P Management Period). Although the Cladophora resurgence has been driven by dreissenid modification of the light environment, phosphorus management remains the only alternative for reversing and ameliorating nuisance conditions. Elucidation of the nature of the Cladophora resurgence will aid decision-makers in maintaining a focus on phosphorus management as the appropriate means of remediating nuisance growth of the alga.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.069
Threshold uncertainty score0.140

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.017
GPT teacher head0.214
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 source (direct Gemma or distilled Codex), 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

Citations31
Published2016
Admission routes2
Has abstractyes

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