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Record W2621085906 · doi:10.37099/mtu.dc.etdr/344

TOWARD A NEW MODELING APPROACH FOR MANAGEMENT OF NUISANCE CLADOPHORA GROWTH IN THE GREAT LAKES

2017· dissertation· en· W2621085906 on OpenAlexaboutno aff
Anika Kuczynski

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
Fundersnot available
KeywordsCladophoraDreissenaBiomass (ecology)PhosphorusEcologyEnvironmental scienceZebra musselNuisanceWater qualityEcosystemBiologyAlgaeBivalviaChemistryMolluscaMussel

Abstract

fetched live from OpenAlex

Cladophora glomerata, a filamentous green alga that grows on hard substrate, first started to attract significant attention in the mid-1970s, when the species spread in Lakes Huron, Erie, and Ontario. High concentrations of soluble reactive phosphorus in discharges led to increased Cladophora growth, which impaired beaches, ecosystem services, and water intakes. The Great Lakes Water Quality Agreement of 1972 (amended in 1978) presumably helped curb the algal proliferation by setting phosphorus limits for any discharges to the Great Lakes. The scientific literature indicates success in this management strategy as measured maximum biomass values decreased. Recent studies, however, show that – while phosphorus limitations are still in effect – Cladophora has returned, and at greater depths. The introduction and establishment of invasive zebra and quagga mussels (Dreissena polymorpha and Dreissena rostriformis bugensis) to the Great Lakes in the late 1980s to early 1990s cause perturbations in the light environment that lead to favorable conditions for Cladophora. This dissertation first investigates the potential drivers of the Cladophora resurgence by comparing historical data and conducting a modeling exercise that – for the first time – quantifies the effect of each driving force on the Cladophora resurgence (Chapter 2). In the spirit of monitoring and analyzing existing data, this section establishes that the Cladophora resurgence is not only perceived but real and that changes in light conditions following the invasion of dreissenids allow for renewed algal proliferation. Chapter 3 of this work describes the development, calibration, and confirmation of a hydrodynamic model, which is applied to describe mass transport in the nearshore of northern Lake Ontario. This work is in response the Great Lakes Water Quality Protocol of 2012, which recognizes that a whole-lake (offshore) approach to controlling nuisance algal growth will not be effective where effluent and tributary discharges are received immediately and locally in the nearshore. Chapter 4 focuses on the development, calibration, and confirmation of the Great Lakes Cladophora Model version 3 (GLCM v3), which includes several improvements of the previous version of the GLCM: redefined light/temperature rate of photosynthesis and respiration response curves, inclusion of a growth-inhibiting self-shading term, a newly defined relationship between the phosphorus uptake rate and stored phosphorus content, replacement of the Droop relationship between the rate of photosynthesis and stored phosphorus content with a similar relationship based on experimental results, and treatment of self-shading and sloughing for an improved understanding and algorithm describing those processes. The

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.053
GPT teacher head0.282
Teacher spread0.229 · 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 designSimulation or modeling
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

Citations2
Published2017
Admission routes1
Has abstractyes

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