Evidence map›Paper›PMID 41786703›Full record

ArticleNature communications2026

The eco-evolutionary assembly of complex communities with multiple interaction types.

Gui Araujo, Miguel Lurgi

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Gui AraujoDepartment of Biosciences, Swansea University, Singleton Park, Swansea, SA2 8PP, UK.
Miguel LurgiDepartment of Biosciences, Swansea University, Singleton Park, Swansea, SA2 8PP, UK. miguel.lurgi@swansea.ac.uk.ORCID http://orcid.org/0000-0001-9891-895X

Funding

Leverhulme Trust RPG-2022-114
6 · The paper itself

Abstract

Identifying the mechanisms that generate structure in complex ecological communities is fundamental for understanding their assembly. Yet a comprehensive picture of how ecology and evolution combine to generate these patterns remains limited. We use an eco-evolutionary model of community assembly that incorporates interaction-driven population dynamics and evolutionary processes, including speciation and inheritance of interactions, to unveil the mechanisms generating and maintaining biodiversity in complex species interaction networks. Importantly, our model unpicks the effects of selection of interaction types from those of inheritance by comparing evolutionary assembly with invasion-based assembly under different combinations of interaction types. We find that a cost-benefit balance in accumulating interactions separates communities into two distinct types. Weakly beneficial interactions produce sparse, competition-dominated networks, whereas strongly beneficial interactions generate highly mutualistic, more connected communities. Mutualism, driven by both selection and inheritance, facilitates the emergence of large communities with increased complexity. Comparing model results with empirical patterns from microbial communities, we identify potential drivers of ecosystem assembly and characteristic interaction structures. Our results provide a classification system of complex ecosystems based on their composition of ecological interactions, thus generating testable hypotheses on the conditions under which different community types (mutualistic vs. competitive) might emerge.

Indexed as

Biological EvolutionEcosystemBiodiversityModels, BiologicalPopulation DynamicsSymbiosis

Identifiers

PMID41786703
PMCPMC13083869

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.