Optimization hardness constrains ecological transients.

Living systems operate far from equilibrium, yet few general frameworks provide global bounds on biological transients. In high-dimensional biological networks like ecosystems, long transients arise from the separate timescales of interactions within versus among subcommunities. Here, we use tools f...

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Main Author: William Gilpin
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-05-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1013051
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author William Gilpin
author_facet William Gilpin
author_sort William Gilpin
collection DOAJ
description Living systems operate far from equilibrium, yet few general frameworks provide global bounds on biological transients. In high-dimensional biological networks like ecosystems, long transients arise from the separate timescales of interactions within versus among subcommunities. Here, we use tools from computational complexity theory to frame equilibration in complex ecosystems as the process of solving an analogue optimization problem. We show that functional redundancies among species in an ecosystem produce difficult, ill-conditioned problems, which physically manifest as transient chaos. We find that the recent success of dimensionality reduction methods in describing ecological dynamics arises due to preconditioning, in which fast relaxation decouples from slow solving timescales. In evolutionary simulations, we show that selection for steady-state species diversity produces ill-conditioning, an effect quantifiable using scaling relations originally derived for numerical analysis of complex optimization problems. Our results demonstrate the physical toll of computational constraints on biological dynamics.
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spelling doaj-art-a9f36021d8d145d08a8c92480df2a1b92025-08-20T03:47:41ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-05-01215e101305110.1371/journal.pcbi.1013051Optimization hardness constrains ecological transients.William GilpinLiving systems operate far from equilibrium, yet few general frameworks provide global bounds on biological transients. In high-dimensional biological networks like ecosystems, long transients arise from the separate timescales of interactions within versus among subcommunities. Here, we use tools from computational complexity theory to frame equilibration in complex ecosystems as the process of solving an analogue optimization problem. We show that functional redundancies among species in an ecosystem produce difficult, ill-conditioned problems, which physically manifest as transient chaos. We find that the recent success of dimensionality reduction methods in describing ecological dynamics arises due to preconditioning, in which fast relaxation decouples from slow solving timescales. In evolutionary simulations, we show that selection for steady-state species diversity produces ill-conditioning, an effect quantifiable using scaling relations originally derived for numerical analysis of complex optimization problems. Our results demonstrate the physical toll of computational constraints on biological dynamics.https://doi.org/10.1371/journal.pcbi.1013051
spellingShingle William Gilpin
Optimization hardness constrains ecological transients.
PLoS Computational Biology
title Optimization hardness constrains ecological transients.
title_full Optimization hardness constrains ecological transients.
title_fullStr Optimization hardness constrains ecological transients.
title_full_unstemmed Optimization hardness constrains ecological transients.
title_short Optimization hardness constrains ecological transients.
title_sort optimization hardness constrains ecological transients
url https://doi.org/10.1371/journal.pcbi.1013051
work_keys_str_mv AT williamgilpin optimizationhardnessconstrainsecologicaltransients