Evidence map›Paper›PMID 42863072›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2026

Evolution shapes ecosystem resilience through spatial self-organization.

Xiaoli Dong, Alexander J Richardson, Rachata Muneepeerakul

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 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
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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

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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.

Xiaoli DongDepartment of Environmental Science and Policy, University of California, Davis, CA 95616.ORCID 0000-0003-3303-0735
Alexander J RichardsonDepartment of Mathematics, University of California, Davis, CA 95616.
Rachata MuneepeerakulDepartment of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611.ORCID 0000-0001-9533-2611

Funding

NSF (NSF) DEB 2320296NSF (NSF) OPP 2333917
6 · The paper itself

Abstract

Drylands are globally widespread and ecologically important but vulnerable to climate change. Many exhibit spatially self-organized vegetation patterns that enhance resilience by enabling vegetation to reorganize their patterns under drying, thereby optimizing water use and maintaining productivity. Plants can also undergo evolution in response to environmental change. Although both spatial self-organization and rapid evolution are fundamental mechanisms of resilience, their interaction remains largely unknown. Using a theoretical model, we examine how these mechanisms interact to shape vegetation transitions-abrupt or gradual-and ecosystem resilience under climatic drying. We find that pattern formation can suppress adaptation by maintaining soil moisture beneath vegetation patches despite rainfall decline, thereby limiting selection for increased drought tolerance. However, this suppression is largely alleviated under the variable rainfall typical of drylands. In turn, evolution feeds back on self-organization by increasing the spatial plasticity of vegetation patterns and their ability to reorganize under changing climate, although this positive effect weakens as evolutionary rate increases. Considering direct (adaptation) and indirect (pattern-mediated) effects, evolution enhances resilience, with indirect effects via pattern plasticity dominating. Within model scenarios spanning plausible rainfall variability and relative evolutionary-to-ecological rates, more than half of vegetation transitions are abrupt involving biomass losses exceeding 50%, highlighting a potential mechanism underlying recent global observations of widespread abrupt vegetation losses in drylands. These results demonstrate that evolution and spatial self-organization jointly determine dryland resilience under environmental change and highlight the unexpected role of evolution in patterned landscapes, calling for integrative approaches to predict ecosystem responses in a changing world.

Indexed as

drylandsmultistabilitypattern formationrainfall variabilitystochasticity

Identifiers

PMID42863072
PMCPMC13684302

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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.