Evidence map›Paper›PMID 39561793›Full record

ArticleProceedings. Biological sciences2024

Character displacement or priority effects: immigration timing can affect community assembly with rapid evolution.

Keiichi Morita, Masato Yamamichi

Abstract read
In one paragraph

Article in Proceedings. Biological sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Keiichi MoritaDepartment of General Systems Studies, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan.ORCID 0000-0001-7096-0099
Masato YamamichiSchool of Biological Sciences, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.ORCID 0000-0003-2136-3399

Funding

Australian Research CouncilCore Research for Evolutional Science and TechnologyInamori FoundationJapan Society for the Promotion of ScienceRIKEN
6 · The paper itself

Abstract

Understanding how biological communities assemble in the presence of rapid evolution is becoming an important topic in ecology. Previous studies demonstrated that community assembly can be affected by two types of eco-evolutionary dynamics: evolution-mediated priority effect (EPE) and ecological character displacement (ECD). In EPE, early-arriving species prevent colonization of late-arriving species via local adaptation (i.e. community monopolization), whereas ECD promotes species coexistence by niche partitioning. Researchers tended to discuss the two processes separately, but it should be possible for those processes to operate in the same system depending on various conditions. Here, we developed a theoretical framework that integrates the two processes by using a simple two-species competition model with eco-evolutionary feedback. We revealed that, when an early-arriving species evolves, the difference in immigration timing between the early-arriving and a late-arriving species can be a key parameter. When the difference is small, ECD occurs because insufficient local adaptation of the early-arriving species allows colonization of the late-arriving species. When the difference is large, however, EPE occurs because niche pre-emption by local adaptation of the early-arriving species prevents colonization of the late-arriving species. Further theoretical and empirical studies will be important to better understand eco-evolutionary community assembly with ECD and EPE.

Indexed as

Biological EvolutionAnimalsBiotaEcosystemModels, BiologicalPopulation Dynamicscommunity assemblycommunity monopolizationecological character displacementevolution-mediated priority effectrapid evolutionresource competition

Identifiers

PMID39561793
PMCPMC11576115

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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.