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Record W2011982079 · doi:10.1111/oik.01988

Top–down control by great blue herons <i>Ardea herodias</i> regulates seagrass‐associated epifauna

2015· article· en· W2011982079 on OpenAlexafffund
Andrew C. Huang, Martha Essak, Mary I. O’Connor

Bibliographic record

VenueOikos · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSeagrassZostera marinaArdeaEcologyTrophic cascadeBiologyPredationAbundance (ecology)ZosteraFisheryFood webEcosystemHeron

Abstract

fetched live from OpenAlex

Top predators can influence the structure and function of plant and animal communities. In coastal marine systems, fish, shark and mammal population declines are major drivers of recent ecosystem‐level change. Cascading effects of predatory wading birds, however, are less understood, even though wading bird populations have declined in many regions. We quantified the effects of predation by the piscivorous great blue heron Ardea herodias fannini on fish, invertebrates and epiphytes living in eelgrass Zostera marina . We found that herons forage on benthic fish in seagrass meadows, and foraging intensity increased from late spring until midsummer. When we experimentally excluded herons, benthic fish abundance increased, and the invertebrate assemblage shifted to more shrimp‐dominated assemblages while grazing gammarid amphipod abundance declined. These shifts were associated with reduced epiphyte abundance when herons were excluded, reflecting a four‐level trophic cascade and mediated by shifts in the grazer assemblage. In summary, we found that a piscivorous wading bird species exerts top down control in a subtidal seagrass ecosystem. Losses and recovery of wading birds could have ecosystem‐level ecological consequences that may need to be considered in the context of concern for overfishing and predator recovery in marine coastal 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.999

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)0.0020.001

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 head0.010
GPT teacher head0.190
Teacher spread0.179 · 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.

Study designNot applicable
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

Citations28
Published2015
Admission routes2
Has abstractyes

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