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Species and sex biases in ectoparasitism of dragonflies by mites

2004· article· en· W2001965207 on OpenAlexfundno aff
Marc J. Lajeunesse, Mark R. Forbes, Bruce P. Smith

Bibliographic record

VenueOikos · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsParasitismBiologyDragonflyEcologyHost (biology)OdonataMiteRange (aeronautics)Zoology

Abstract

fetched live from OpenAlex

An important problem in understanding the evolution of parasite host range is determining the extent to which parasite fitness varies among host species and the factors affecting that fitness variation. We present a detailed investigation on the patterns of host use and successful parasitism of two dragonfly species by the ectoparasitic water mite, Limnochares americana Lundblad. In our field surveys, we found both species biases and sex biases in parasitism by mites, which appear explained by differences in exposure. Differential habitat use by dragonflies helped explain male biases in parasitism in both host species, but was not useful in explaining species biases in parasitism. Species biases in parasitism may be explained by more subtle variation in habitat use not explored in this study, or perhaps by differences in timing of emergence, as we found for the two dragonfly species. Despite species differences in parasitism in nature, we found that mites attached equally successfully to both dragonfly species during experimental infestations. However, mites failed to engorge more often on the dragonfly species less often used as a host in nature. This host species also was more likely to have dead mites in natural infestations as compared to the other host species, which was more often and more heavily parasitized. Our results are consistent with previous research suggesting parasites are less successful on less often used hosts. Such research has implications for understanding determinants of host range for animal parasites.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.061
Threshold uncertainty score0.824

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)0.0010.000

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 head0.016
GPT teacher head0.295
Teacher spread0.279 · 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

Citations37
Published2004
Admission routes1
Has abstractyes

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