Evidence map›Paper›PMID 40817347›Full record

ArticleCommunications biology2025

Information dynamics and the emergence of high-order individuality in ecosystems.

Hardik Rajpal, Clem von Stengel, Pedro A M Mediano, Fernando E Rosas, Eduardo Viegas, Pablo A Marquet, Henrik J Jensen

Abstract read
In one paragraph

Article in Communications biology, 2025. 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
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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

7 authors.

Hardik RajpalCentre for Complexity Science, Imperial College London, London, UK. h.rajpal15@imperial.ac.uk.ORCID http://orcid.org/0000-0002-1291-4817
Clem von StengelAlignment of Complex Systems, Centre for Theoretical Study, Charles University, Prague, Czechia.
Pedro A M MedianoCentre for Complexity Science, Imperial College London, London, UK.ORCID http://orcid.org/0000-0003-1789-5894
Fernando E RosasCentre for Complexity Science, Imperial College London, London, UK.ORCID http://orcid.org/0000-0001-7790-6183
Eduardo ViegasCentre for Complexity Science, Imperial College London, London, UK.ORCID http://orcid.org/0000-0003-2422-0254
Pablo A MarquetFacultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile.ORCID http://orcid.org/0000-0001-6369-9339
Henrik J JensenCentre for Complexity Science, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-5398-3288

Funding

RCUK | Economic and Social Research Council (ESRC) ES/T005319/2RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/W007142/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/W024020/1RCUK | Engineering and Physical Sciences Research Council (EPSRC) EP/X03870X/1
6 · The paper itself

Abstract

At what level does natural selection occur? When considering the reproductive dynamics of interacting and mutating agents, it has long been debated whether selection is better understood by focusing on the individual or if hierarchical selection emerges as a consequence of joint adaptation. Despite longstanding efforts in theoretical ecology, there is still no consensus on this fundamental issue, most likely due to the difficulty in obtaining adequate data spanning a sufficient number of generations and the lack of adequate tools to quantify the effect of hierarchical selection. Here, we capitalise on recent advances in information-theoretic data analysis to advance this state of affairs by investigating the emergence of high-order structures- such as groups of species- in the collective dynamics of the Tangled Nature model of evolutionary ecology. Our results show that evolutionary dynamics can lead to clusters of species that act as a self-perpetuating group that exhibits greater information-theoretic agency than a single species for a broad range of stable mutation rates. However, this higher-order organization breaks down for mutation rates close to the error threshold, where increased information processing is observed at the level of a single species. For mutation rates higher than the error threshold, no stable population of species are observed in time, and all individuality is lost in the ecosystem. Overall, our findings provide quantitative evidence supporting the emergence of higher-order structures in evolutionary ecology from relatively simple processes of adaptation and reproduction.

Indexed as

Biological EvolutionEcosystemInformation TheorySelection, GeneticMutationPopulation Dynamics

Identifiers

PMID40817347
PMCPMC12356948

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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.