Evidence map›Paper›PMID 41279688›Full record

ArticlebioRxiv : the preprint server for biology2025

Macroecological Laws Can Naturally Arise from Chaotic Internal Species Dynamics.

Konstantine Tchourine, Martin Carballo-Pacheco, Dennis Vitkup

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for 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
–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

3 authors.

Konstantine TchourineDepartment of Systems Biology, Columbia University, New York, NY, USA.ORCID 0000-0002-0647-5272
Martin Carballo-PachecoDepartment of Systems Biology, Columbia University, New York, NY, USA.ORCID 0000-0002-9047-1855
Dennis VitkupDepartment of Systems Biology, Columbia University, New York, NY, USA.ORCID 0000-0003-4259-8162

Funding

Ecological dynamics and metabolic interactions in thegut microbiome across space and timeR01DK118044 · NIDDK · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI VITKUP, DENNIS, WANG, HARRIS H · 2018 to 2022
$3.4M
Systems Biology of Protein and Phenotypic EvolutionR35GM131884 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI VITKUP, DENNIS · 2019 to 2023
$2.2M
NIDDK NIH HHS R01 DK118044NIGMS NIH HHS R35 GM131884
6 · The paper itself

Abstract

Macroecological relationships that connect various statistical descriptors of long-term and short-term species dynamics represent some of the most general laws in ecology and biology. These macroecological laws have been observed across diverse ecologies of plants and animals, and more recently, also in microbiota. Yet it remains unclear why strikingly similar macroecological relationships often arise in very different biological communities and various environmental contexts. Here, we investigated whether chaotic internal dynamics in spatially heterogeneous communities could underlie multiple macroecological relationships. Our analyses reveal that very general constraints on species interactions and spatial migration parameters can simultaneously lead to multiple macroecological laws found in microbial ecosystems without requiring external sources of noise. Our study also identifies the mechanistic origins of many empirically observed macroecological relationships, such as Taylor's law, anomalous abundance diffusion, the Laplace distribution of short-term abundance changes, and the distribution of species residence times. Overall, we demonstrate how macroecological laws can arise from interaction-driven chaotic dynamics and common ecological constraints, thereby providing a unifying explanation for their widespread prevalence in nature.

Identifiers

PMID41279688
PMCPMC12632291

What OpenQuestion holds

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LicenceCC BY-NC
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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.