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Record W2123764943 · doi:10.1139/f07-197

Long-term trends in zooplankton of Dorset, Ontario, lakes: the probable interactive effects of changes in pH, total phosphorus, dissolved organic carbon, and predators

2008· article· en· W2123764943 on OpenAlexvenueaboutno aff
Norman D. Yan, Keith M. Somers, R. Girard, Andrew M. Paterson, W. Keller, Charles W. Ramcharan, James A. Rusak, Ron Ingram, George Emir Morgan, John M. Gunn

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsZooplanktonSpecies richnessEcologyAbundance (ecology)Context (archaeology)PredationEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Time trends in abundance, body size, species richness, and species composition indicate that crustacean zooplankton communities of southern Canadian Shield lakes changed between 1980 and 2003. Total abundance did not decline despite reductions in total phosphorus, but all other metrics changed. Species richness declined in Harp Lake (Ontario, Canada) following its Bythotrephes invasion, but richness increased in three other lakes. Average cladoceran body length increased from 0.6 to 1.0 mm in seven of the lakes, as larger-bodied taxa replaced smaller ones. Correlations with water quality and fish metrics suggest that cladoceran size increases were attributable to many factors: a decline in food availability following declining phosphorus levels increasing the competitive advantage of larger herbivores, a decline in acidity favouring the larger, acid-sensitive daphniids, and reduced risk of planktivory linked to a rise in dissolved organic carbon levels and changes in predation regimes. Zooplankton communities on the Canadian Shield are changing, and these changes are best viewed in a multiple-stressor context. Key anthropogenic stressors have also changed and may do so again if Ca concentrations continue to decline.

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 score0.831
Threshold uncertainty score0.884

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)0.0000.000

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 head0.008
GPT teacher head0.191
Teacher spread0.183 · 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

Citations119
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicAquatic Ecosystems and Phytoplankton DynamicsFrench-language works237,207