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Record W4391174806 · doi:10.1111/oik.10374

Parasite‐mediated changes in host traits alter food web dynamics

2024· article· en· W4391174806 on OpenAlexfundno aff
Ines Klemme, Tommi Perälä, Sami O. Lehtinen, Anna Kuparinen

Bibliographic record

VenueOikos · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsHost (biology)BiologyParasite hostingFood webEcologyDynamics (music)ZoologyTrophic levelWorld Wide WebComputer sciencePsychology

Abstract

fetched live from OpenAlex

Parasites commonly alter the phenotype of their hosts, thereby influencing competitive and consumer–resource interactions. This could trigger a cascade effect on the dynamics of biological communities, but the role of parasites in ecosystem processes is poorly understood. In this study, we investigate how parasite‐induced trait modifications shape the dynamics of a complex lake food web using an allometric trophic network model (ATN). We simulated infections of stage‐structured fish host populations via increased maintenance costs and predation risk. Our results show that host trait modifications can significantly impact host demography, with stage‐specific biomass declines up to 60%. However, less severely affected host stages buffered these effects and sustained the population. Importantly, host biomass decline altered the dynamics of species interactions and these effects cascaded through the entire community, with biomass changes observed at all trophic levels. Our findings emphasize the importance of incorporating both indirect parasite effects and host life history in ecological network studies for more realistic simulations of community dynamics.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.003

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 head0.013
GPT teacher head0.296
Teacher spread0.283 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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