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Record W2159960526 · doi:10.1093/biosci/bit001

Changing Ecosystem Dynamics in the Laurentian Great Lakes: Bottom-Up and Top-Down Regulation

2013· article· en· W2159960526 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBioScience · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsnot available
FundersUniversity of Illinois at Urbana-ChampaignCollege of Engineering, Michigan State UniversityMichigan Department of Natural ResourcesU.S. Geological SurveyMinistry of Natural ResourcesUniversity of Illinois at ChicagoNational Oceanic and Atmospheric AdministrationMichigan State UniversityU.S. Fish and Wildlife ServiceUniversity of MichiganU.S. Environmental Protection AgencyGreat Lakes Fishery CommissionChina Scholarship CouncilOhio State UniversityNew York State Department of Environmental Conservation
KeywordsTrophic levelFood webEcosystemTrophic cascadeBiomass (ecology)EcologyLake ecosystemEnvironmental scienceApex predatorEcosystem-based managementPredationInvertebratePhytoplanktonFisheryBiologyNutrient

Abstract

fetched live from OpenAlex

Understanding the relative importance of top-down and bottom-up regulation of ecosystem structure is a fundamental ecological question, with implications for fisheries and water-quality management. For the Laurentian Great Lakes, where, since the early 1970s, nutrient inputs have been reduced, whereas top-predator biomass has increased, we describe trends across multiple trophic levels and explore their underlying drivers. Our analyses revealed increasing water clarity and declines in phytoplankton, native invertebrates, and prey fish since 1998 in at least three of the five lakes. Evidence for bottom-up regulation was strongest in Lake Huron, although each lake provided support in at least one pair of trophic levels. Evidence for top-down regulation was rare. Although nonindigenous dreissenid mussels probably have large impacts on nutrient cycling and phytoplankton, their effects on higher trophic levels remain uncertain. We highlight gaps for which monitoring and knowledge should improve the understanding of food-web dynamics and facilitate the implementation of ecosystem-based management.

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.

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 score0.017
Threshold uncertainty score0.725

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 studies0.0000.000
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 head0.006
GPT teacher head0.192
Teacher spread0.186 · 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