Evidence map›Paper›PMID 28931738›Full record

ArticleProceedings. Biological sciences2017

Biological and statistical processes jointly drive population aggregation: using host-parasite interactions to understand Taylor's power law.

Pieter T J Johnson, Mark Q Wilber

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.

  1. Article
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  8. Article
  9. Measuring aggregation in parasite populations.Journal of the Royal Society, Interface · 2020
    Article
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  12. Article
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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

2 authors.

Pieter T J JohnsonEcology and Evolutionary Biology, University of Colorado, Boulder, CO 80309, USA pieter.johnson@colorado.edu.ORCID http://orcid.org/0000-0002-7997-5390
Mark Q WilberEcology, Evolution and Marine Biology, University of California, Santa Barbara, CA, 93106, USA.

Funding

EID disease in complex communities: multi-host multi-pathogen interactionsR01GM109499 · NIGMS · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI BRIGGS, CHERYL J · 2013 to 2016
$1.7M
NIGMS NIH HHS R01 GM109499
6 · The paper itself

Abstract

The macroecological pattern known as Taylor's power law (TPL) represents the pervasive tendency of the variance in population density to increase as a power function of the mean. Despite empirical illustrations in systems ranging from viruses to vertebrates, the biological significance of this relationship continues to be debated. Here we combined collection of a unique dataset involving 11 987 amphibian hosts and 332 684 trematode parasites with experimental measurements of core epidemiological outcomes to explicitly test the contributions of hypothesized biological processes in driving aggregation. After using feasible set theory to account for mechanisms acting indirectly on aggregation and statistical constraints inherent to the data, we detected strongly consistent influences of host and parasite species identity over 7 years of sampling. Incorporation of field-based measurements of host body size, its variance and spatial heterogeneity in host density accounted for host identity effects, while experimental quantification of infection competence (and especially virulence from the 20 most common host-parasite combinations) revealed the role of species-by-environment interactions. By uniting constraint-based theory, controlled experiments and community-based field surveys, we illustrate the joint influences of biological and statistical processes on parasite aggregation and emphasize their importance for understanding population regulation and ecological stability across a range of systems, both infectious and free-living.

Indexed as

Host-Parasite InteractionsModels, BiologicalTrematodaAmphibiansAnimalsParasitesPopulation Densitycommunity ecologydisease ecologyfeasible setsmacroecologypopulation regulationsuperspreaders

Identifiers

PMID28931738
PMCPMC5627205

What OpenQuestion holds

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Registered trials

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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.