Evidence map›Paper›PMID 29263286›Full record

ArticleProceedings. Biological sciences2017

Scale dependencies and generalism in host use shape virus prevalence.

Michael McLeish, Soledad Sacristán, Aurora Fraile, Fernando García-Arenal

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Michael McLeishCentro de Biotecnología y Genómica de Plantas UPM-INIA and Escuela Técnica Superior de Ingeniería Agronómica, Agroambiental y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, Madrid 28223, Spain.ORCID http://orcid.org/0000-0002-4525-5221
Soledad SacristánCentro de Biotecnología y Genómica de Plantas UPM-INIA and Escuela Técnica Superior de Ingeniería Agronómica, Agroambiental y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, Madrid 28223, Spain.
Aurora FraileCentro de Biotecnología y Genómica de Plantas UPM-INIA and Escuela Técnica Superior de Ingeniería Agronómica, Agroambiental y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, Madrid 28223, Spain.
Fernando García-ArenalCentro de Biotecnología y Genómica de Plantas UPM-INIA and Escuela Técnica Superior de Ingeniería Agronómica, Agroambiental y de Biosistemas (ETSIAAB), Universidad Politécnica de Madrid, Campus de Montegancedo, Pozuelo de Alarcón, Madrid 28223, Spain fernando.garciaarenal@upm.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Processes that generate the distribution of pathogens and their interactions with hosts are not insensitive to changes in spatial scale. Spatial scales and species traits are often selected intentionally, based on practical considerations, ignoring biases that the scale and type of observation may introduce. Specifically, these biases might change the interpretation of disease-diversity relationships that are reported as either 'dilution' or 'amplification' effects. Here, we combine field data of a host-pathogen community with empirical models to test the effects that (i) spatial scale and (ii) host range have on the relationship between plant-virus infection prevalence and diversity. We show that prevalence-diversity relationships are scale-dependent and can produce opposite effects associated with different habitats at sub-ecosystem scales. The total number of host species of each virus reflected generalism at the ecosystem scale. However, plasticity in host range resembled habitat-specific specialization and also changed model predictions. We show that habitat heterogeneity, ignored at larger (ecosystem) spatial scales, influences pathogen distributions. Hence, understanding disease distributions and the evolution of pathogens requires reconciling specific hypotheses of the study with an appropriate spatial scale, or scales, and consideration of traits, such as host range, that might strongly contribute to biotic interactions.

Indexed as

EcosystemHost-Pathogen InteractionsPlant DiseasesHost SpecificityModels, BiologicalPlantsPlant Virusesamplificationcommunitydilutionhost–pathogenhost rangeinfection network

Identifiers

PMID29263286
PMCPMC5745412

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.