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Record W2618333779 · doi:10.1111/een.12421

Effect of dung beetle species richness and chemical perturbation on multiple ecosystem functions

2017· article· en· W2618333779 on OpenAlexaff
Paul Manning, Eleanor M. Slade, Sarah A. Beynon, Owen T. Lewis

Bibliographic record

VenueEcological Entomology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsDalhousie University
FundersRhodes Scholarships
KeywordsSpecies richnessBiologyDung beetleEcosystemEcologyPerturbation (astronomy)BiodiversitySpecies diversityScarabaeidaePhysics

Abstract

fetched live from OpenAlex

1. The relationship between biodiversity and ecosystem functioning is typically positive but saturating, suggesting widespread functional redundancy within ecological communities. However, theory predicts that apparent redundancy can be reduced or removed when systems are perturbed, or when multifunctionality (the simultaneous delivery of multiple functions) is considered. 2. Manipulative experiments were used to test whether higher levels of dung beetle species richness enhanced individual functions and multifunctionality, and whether these relationships were influenced by perturbation (in this case, non‐target exposure to the veterinary anthelmintic ivermectin). The four ecosystem functions tested were dung removal, primary productivity, soil faunal feeding activity and reduction in soil bulk density. 3. For individual functions, perturbation had limited effects on functioning, with only dung removal significantly (negatively) affected. Species richness did not, on its own, explain significant variation in the delivery of individual functions. In the case of primary productivity, an interaction between richness and perturbation was found: species‐rich dung beetle assemblages enhanced forage growth in the unperturbed treatment, relative to the perturbed treatment. 4. Using a composite ‘multifunctionality index’ it was found that species‐rich dung beetle assemblages delivered marginally higher levels of multifunctionality in unperturbed conditions; however, this benefit was lost under perturbation. Using a relatively new and robust method of assessing diversity–multifunctionality relationships across a range of thresholds, no significant effect of species richness on multifunctionality was found.

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)0.001
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 score0.011
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.241
Teacher spread0.231 · 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

Citations36
Published2017
Admission routes1
Has abstractyes

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