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Record W2891209113 · doi:10.3354/meps12751

Host diet influences parasite diversity: a case study looking at tapeworm diversity among sharks

2018· article· en· W2891209113 on OpenAlexaboutno aff
TK Rasmussen, H. S. Randhawa

Bibliographic record

VenueMarine Ecology Progress Series · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
FundersUniversity of Otago
KeywordsEcologySpecies richnessTrophic levelHost (biology)BiologyBiodiversityDiversity (politics)HabitatAbundance (ecology)Geography

Abstract

fetched live from OpenAlex

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 605:1-16 (2018) - DOI: https://doi.org/10.3354/meps12751 FEATURE ARTICLE Host diet influences parasite diversity: a case study looking at tapeworm diversity among sharks Trent K. Rasmussen1,*, Haseeb S. Randhawa1,2,3,4 1Ecology Degree Programme, University of Otago, PO Box 56, Dunedin 9054, New Zealand 2Present address: Falkland Islands Fisheries Department, Directorate of Natural Resources, Falkland Islands Government, Bypass Road, Stanley FIQQ 1ZZ, Falkland Islands 3Present address: South Atlantic Environmental Research Institute, PO Box 609, Stanley Cottage, Stanley FIQQ 1ZZ, Falkland Islands 4Present address: New Brunswick Museum, 277 Douglas Avenue, Saint John, New Brunswick E2K 1E5, Canada *Corresponding author: t.k.rasmussen@outlook.com ABSTRACT: In theory, animal diets may act as important filters for different parasite species. However, there is currently a lack of empirical research looking at host diet as a potential predictor of parasite diversity among different host species. The aim of this study was to assess the influence of several host diet features (including diet breadth, diet composition, and trophic level) on tapeworm diversity in sharks, relative to other key factors, including host size, habitat, phylogeny, latitude, and depth. Data on these host features were compiled from a comprehensive analysis of literature records including 91 different shark species, and 3 measures of tapeworm diversity were examined: tapeworm species richness, tapeworm taxonomic distinctness (TD), and variance in tapeworm TD. The diet breadth of a shark species was revealed to be a better predictor of tapeworm species richness than other host features examined to date. Host size, trophic level, diet TD, latitudinal range, and the mid-point of a shark's depth range also significantly influenced tapeworm richness when analyses were adjusted to prevent confounding by phylogenetic relationships between hosts. The TD of tapeworm assemblages was influenced by diet breadth, diet TD, host size, and depth range when analysed independently of host phylogeny. Overall, our findings demonstrate that aspects of host diet have important consequences for parasite diversity in sharks. We emphasise that studies of parasite diversity in other systems should more seriously consider including aspects of host diet (particularly diet breadth) as potential key predictors of parasite diversity. KEY WORDS: Sharks · Cestodes · Tapeworms · Species richness · Diet · Species diversity · Taxonomic distinctness · Phylogenetically independent contrasts Full text in pdf format Information about this Feature Article Supplementary material NextCite this article as: Rasmussen TK, Randhawa HS (2018) Host diet influences parasite diversity: a case study looking at tapeworm diversity among sharks. Mar Ecol Prog Ser 605:1-16. https://doi.org/10.3354/meps12751 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 605. Online publication date: October 26, 2018 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2018 Inter-Research.

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 categoriesScience and technology studies, Open science, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.998

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 studies0.0040.002
Scholarly communication0.0000.001
Open science0.0000.011
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.297
Teacher spread0.282 · 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 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

Citations18
Published2018
Admission routes1
Has abstractyes

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