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Record W2136978676 · doi:10.1111/ele.12434

From mice to elephants: overturning the ‘one size fits all’ paradigm in marine plankton food chains

2015· review· en· W2136978676 on OpenAlexaff
Daniel G. Boyce, Kenneth T. Frank, William C. Leggett

Bibliographic record

VenueEcology Letters · 2015
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal ecosystems
Canadian institutionsBedford Institute of OceanographyQueen's University
Fundersnot available
KeywordsTrophic levelPhytoplanktonPlanktonZooplanktonEcologyBiologyFood chainTrophic cascadePredationMarine biologyEnvironmental scienceOceanographyFood web

Abstract

fetched live from OpenAlex

It is widely believed that consumer control is a weak regulator of marine phytoplankton communities. It remains unclear, however, why this should be the case when marine consumers routinely regulate their prey at higher trophic levels. One possibility is that the weak consumer control of phytoplankton communities results from the inability of field researchers to effectively account for consumer-prey trophic relationships operating at the scale of the plankton. We explored this issue by reviewing studies of trophic control in marine plankton. Experimental studies indicate that size is a critical determinant of feeding relationships among plankton. In sharp contrast, of the 51 field studies reviewed, 78% did not distinguish among the sizes or species of phytoplankton and their consumers, but instead assumed a general bulk phytoplankton-zooplankton trophic connection. Such an approach neglects the possibility that several trophic connections may separate the smallest phytoplankton (0.2 μm) from the larger zooplankton (~ 1000 μm), a remarkable size differential exceeding that between a mouse (~10 cm) and an elephant (~2500 cm). The size-based approach we propose integrates theory, experiments and field observations and has the potential to greatly enhance our understanding of the causes and consequences of recently documented restructuring of plankton communities.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.944
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.034
GPT teacher head0.246
Teacher spread0.213 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations87
Published2015
Admission routes1
Has abstractyes

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