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Record W2145446082 · doi:10.1139/f07-136

Ecological change in Great Lakes communities — a matter of perspective

2008· article· en· W2145446082 on OpenAlexvenueaboutno aff
W. Gary Sprules

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEcologyZooplanktonLake ecosystemEcosystemBiomass (ecology)Climate changeFaunaFood webEnvironmental changeGeographyEnvironmental scienceBiology

Abstract

fetched live from OpenAlex

Enormous change in food webs of the Laurentian Great Lakes has been documented from the early 1970s to the 1990s. Variation in abundances of species at all levels in these food webs has been attributed to a variety of causes, including nutrient abatement, invasive species, fishing practices, and climate change. However, this impression of great change is not obvious if food webs are examined from the different perspective of the biomass size spectrum. Despite large shifts in the species structure of zooplankton communities in Lakes Erie and Ontario from 1991 to 1997, zooplankton size spectra have not changed. Furthermore, size spectra for complete food webs of Lake Ontario (Laurentian Great Lake) and Lake Malawi (African Rift Valley Lake) are statistically indistinguishable despite enormous contrast in the geological age and fauna of the two lakes. I conclude that constraints on bioenergetic rate processes and physiological and ecological similarities of like-sized organisms at various hierarchical levels of organization lead to regular and repeatedly observed emergent properties of aquatic ecosystems that are independent of specific species.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0020.003
Open science0.0000.001
Research integrity0.0010.001
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 head0.035
GPT teacher head0.225
Teacher spread0.191 · 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

Citations36
Published2008
Admission routes2
Has abstractyes

Explore more

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