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Nutrient co‐limitation of primary producer communities

2011· review· en· W2118123652 on OpenAlexaff
W. Stanley Harpole, Jacqueline T. Ngai, Elsa E. Cleland, Eric W. Seabloom, Elizabeth T. Borer, Matthew E. S. Bracken, James J. Elser, Daniel S. Gruner, Helmut Hillebrand, Jonathan B. Shurin, Jennifer E. Smith

Bibliographic record

VenueEcology Letters · 2011
Typereview
Languageen
FieldEnvironmental Science
TopicSoil and Water Nutrient Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsBiomass (ecology)Resource (disambiguation)EcologyNutrientLimitingPhosphorusPrimary producersConstraint (computer-aided design)Production (economics)Primary productionPrimary successionEnvironmental scienceBiologyEcosystemComputer scienceMathematicsChemistryPhytoplanktonEconomics

Abstract

fetched live from OpenAlex

Synergistic interactions between multiple limiting resources are common, highlighting the importance of co-limitation as a constraint on primary production. Our concept of resource limitation has shifted over the past two decades from an earlier paradigm of single-resource limitation towards concepts of co-limitation by multiple resources, which are predicted by various theories. Herein, we summarise multiple-resource limitation responses in plant communities using a dataset of 641 studies that applied factorial addition of nitrogen (N) and phosphorus (P) in freshwater, marine and terrestrial systems. We found that more than half of the studies displayed some type of synergistic response to N and P addition. We found support for strict definitions of co-limitation in 28% of the studies: i.e. community biomass responded to only combined N and P addition, or to both N and P when added separately. Our results highlight the importance of interactions between N and P in regulating primary producer community biomass and point to the need for future studies that address the multiple mechanisms that could lead to different types of co-limitation.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
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 head0.045
GPT teacher head0.256
Teacher spread0.211 · 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 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

Citations1,086
Published2011
Admission routes1
Has abstractyes

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