Evidence map›Paper›PMID 34646480›Full record

ArticleEcology and evolution2021

The effect of dilution on eco-evolutionary dynamics of experimental microbial communities.

Thomas Scheuerl, Veijo Kaitala

Abstract read
In one paragraph

Article in Ecology and evolution, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Eco-evolutionary dynamics of experimentalMicrobiology (Reading, England) · 2023
    Article
  2. Article
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.

Thomas ScheuerlDepartment of Plant Sciences University of Cambridge Cambridge UK.ORCID https://orcid.org/0000-0001-5216-5630
Veijo KaitalaOrganismal and Evolutionary Biology Research Programme University of Helsinki Helsinki Finland.ORCID https://orcid.org/0000-0001-5626-9752

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Changing environmental conditions can infer structural modifications of predator-prey communities. New conditions often increase mortality which reduces population sizes. Following this, predation pressure may decrease until populations are dense again. Dilution may thus have substantial impact not only on ecological but also on evolutionary dynamics because it amends population densities. Experimental studies, in which microbial populations are maintained by a repeated dilution into fresh conditions after a certain period, are extensively used approaches allowing us to obtain mechanistic insights into fundamental processes. By design, dilution, which depends on transfer volume (modifying mortality) and transfer interval (determining the time of interaction), is an inherent feature of these experiments, but often receives little attention. We further explore previously published data from a live predator-prey (bacteria and ciliates) system which investigated eco-evolutionary principles and apply a mathematical model to predict how various transfer volumes and transfer intervals would affect such an experiment. We find not only the ecological dynamics to be modified by both factors but also the evolutionary rates to be affected. Our work predicts that the evolution of the anti-predator defense in the bacteria, and the evolution of the predation efficiency in the ciliates, both slow down with lower transfer volume, but speed up with longer transfer intervals. Our results provide testable hypotheses for future studies of predator-prey systems, and we hope this work will help improve our understanding of how ecological and evolutionary processes together shape composition of microbial communities.

Indexed as

ecological dynamicsevolutionary interactionpredator‐prey coexistence

Identifiers

PMID34646480
PMCPMC8495831

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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.