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Food quality, nutrient limitation of secondary production, and the strength of trophic cascades

2007· article· en· W1966215460 on OpenAlexfundno aff
Spencer R. Hall, Jonathan B. Shurin, Sebastian Diehl, Roger M. Nisbet

Bibliographic record

VenueOikos · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaDeutsche ForschungsgemeinschaftNational Science Foundation
KeywordsHerbivoreTrophic levelEcological stoichiometryBiomass (ecology)EcosystemTrophic cascadeNutrientFood chainEcologyFood webBiologyTerrestrial ecosystemEnvironmental science

Abstract

fetched live from OpenAlex

Recent meta‐analyses confirm that the strength of trophic cascades (indirect positive effects of predators on plant biomass through control of herbivores) varies among ecosystem types. In particular, most terrestrial systems show smaller cascades than most aquatic ones. Ecologists still remain challenged to explain this variation. Here, we examine a food quality hypothesis which states that higher quality plants should promote stronger trophic cascades. Food quality involves two components: digestion resistance of plants and magnitude of stoichiometric imbalance between plants and herbivores (where stoichiometry involves ratios of nutrient:carbon ratio of tissues). Both factors vary among ecosystems and could mediate conversion efficiency of plants into new herbivores (and hence control of plants by herbivores). We explored the food quality hypothesis using two models, one assuming that plant stoichiometry is a fixed trait, the other one allowing this trait to vary dynamically (but with a minimal nutrient:carbon ratio of structural mass). Both models produce the same suite of results. First, as expected, systems with more easily digested plants promote stronger cascades. Second, contrary to expectations, higher (fixed or minimal) nutrient:carbon ratio of plants do not promote stronger cascades, largely because of the net result of ecosystem feedbacks. Still, the model with dynamic stoichiometry permits positive correlations of realized plant nutrient:carbon ratio and cascade strength (as predicted), mediated through digestion resistance. Third, lower nutrient:carbon ratio of herbivores promotes stronger cascades. However, this result likely cannot explain variation in cascade strength because nutrient:carbon stoichiometry of herbivores does not vary greatly between terrestrial and aquatic ecosystems. Finally, we found that predation promotes nutrient limitation of herbivores. This finding highlights that food web processes, such as predation, can influence stoichiometry‐mediated interactions of plants and herbivores.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.172
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.252
Teacher spread0.238 · 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

Citations77
Published2007
Admission routes1
Has abstractyes

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