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arxiv: 1907.05528 · v1 · pith:6UZBUHOUnew · submitted 2019-07-12 · 🧬 q-bio.PE · q-bio.MN

Evolving complexity: how tinkering shapes cells, software and ecological networks

Ricard Sole , Sergi Valverde This is my paper

Pith reviewed 2026-05-24 22:38 UTC · model grok-4.3

classification 🧬 q-bio.PE q-bio.MN
keywords tinkeringduplication-rewiringnetwork evolutionscale-free networksmodular architecturecellular networksecological networkssoftware networks
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The pith

Tinkering through duplication and rewiring generates complex network structures in cells, software, and ecosystems without requiring selection for optimal function.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper argues that many complex networks arise not primarily from selection optimizing for function but from a process of tinkering where existing components are reused through duplication and rewiring. This generative mechanism naturally produces the heterogeneous, sparse, small-world, modular, and scale-free structures observed across biological, technological, and ecological systems. By modeling these dynamics with simple rules, the work shows that such patterns emerge inevitably from reuse and affect functional properties. A sympathetic reader would care because it challenges the standard view that complexity demands deliberate design or strong selection pressures as the main drivers.

Core claim

Against the standard selection-optimisation argument, some networks reveal the inevitable generation of complex patterns resulting from reuse and can be modelled using duplication-rewiring rules. These give rise to the heterogeneous, scale-free and modular architectures observed in the real case studies. Tinkering is a universal mechanism that drives not only biological evolution but also the large-scale dynamics of some technological designs, and the analysis suggests to seriously reconsider the role played by selection forces or design principles as main drivers of network evolution.

What carries the argument

Duplication-rewiring rules that model reuse and generate scale-free and modular topologies from evolutionary dynamics.

If this is right

  • Network architectures in cells, software, and ecology can be explained by generative models based on reuse.
  • Tinkering affects functional properties of these networks in ways that follow from the reuse dynamics.
  • Selection forces or design principles are not required as main drivers to explain the observed topologies.
  • Similar patterns across domains point to a common mechanism of tinkering.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the claim holds, engineering or managing such networks might prioritize enabling reuse mechanisms over top-down optimization.
  • The same rules could be tested against networks in additional domains like social or economic systems to check generality.
  • This view implies that historical contingency from reuse may explain robustness or fragility patterns better than optimality arguments.

Load-bearing premise

Generative models based on duplication-rewiring rules capture the dominant evolutionary dynamics of real networks without requiring additional selection or optimization steps.

What would settle it

A demonstration that duplication-rewiring models fail to reproduce the scale-free or modular features of real cellular, software, or ecological networks unless explicit selection or optimization rules are added.

read the original abstract

A common trait of complex systems is that they can be represented by means of a network of interacting parts. It is, in fact, the network organisation (more than the parts) what largely conditions most higher-level properties, which are not reducible to the properties of the individual parts. Can the topological organisation of these webs provide some insight into their evolutionary origins? Both biological and artificial networks share some common architectural traits. They are often heterogeneous and sparse, and most exhibit the small-world property or the presence of modular or hierarchical patterns. These properties have often been attributed to the selection of functionally meaningful traits. However, the proper formulation of generative network models suggests a rather different picture. Against the standard selection-optimisation argument, some networks reveal the inevitable generation of complex patterns resulting from reuse and can be modelled using duplication-rewiring rules. These give rise to the heterogeneous, scale-free and modular architectures observed in the real case studies. Tinkering is a universal mechanism that drives not only biological evolution but also the large-scale dynamics of some technological designs. Here we examine the evidence for tinkering in cellular, technological and ecological webs and its impact in shaping their architecture and deeply affecting their functional properties. Our analysis suggests to seriously reconsider the role played by selection forces or design principles as main drivers of network evolution.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript argues that the heterogeneous, scale-free, and modular architectures observed in cellular, technological, and ecological networks arise inevitably from tinkering mechanisms (reuse via duplication-rewiring rules) rather than primarily from selection or optimization. It reviews evidence across domains and presents generative models based on these rules as sufficient to reproduce the observed topologies.

Significance. If the generative models are shown to operate under minimal non-tuned assumptions, the work would offer a parsimonious alternative to selection-optimization accounts of network evolution, with implications for systems biology and complex systems. The cross-domain comparison of tinkering as a universal driver is a strength.

major comments (2)
  1. [Generative network models] Generative network models section: the central claim that duplication-rewiring rules generate the observed architectures 'without requiring additional selection or optimization steps' is load-bearing. The manuscript must demonstrate that the models match empirical networks under minimal, non-tuned assumptions rather than parameter regimes chosen to recover target statistics (which could embed selection-like effects).
  2. [Case studies] Case studies (cellular, software, ecological webs): the inference that tinkering is the dominant driver requires explicit comparison showing that the generative models outperform or are more parsimonious than selection-based alternatives on the same networks; conceptual similarity alone does not establish dominance.
minor comments (1)
  1. [Abstract] Abstract: the phrasing 'can be modelled using' is appropriately cautious, but the final sentence calling to 'seriously reconsider the role played by selection forces' would benefit from qualification that the argument is one of sufficiency rather than necessity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

Thank you for the opportunity to respond to the referee's report. We address the major comments below and propose revisions where appropriate to strengthen the manuscript.

read point-by-point responses

  1. Referee: [Generative network models] Generative network models section: the central claim that duplication-rewiring rules generate the observed architectures 'without requiring additional selection or optimization steps' is load-bearing. The manuscript must demonstrate that the models match empirical networks under minimal, non-tuned assumptions rather than parameter regimes chosen to recover target statistics (which could embed selection-like effects).

    Authors: We acknowledge the importance of this point. The models in the manuscript use duplication-rewiring rules with parameters drawn from plausible ranges based on empirical observations in each domain, rather than optimized to fit network metrics. To address this, we will revise the Generative network models section to include additional analyses demonstrating that the key topological features (heterogeneity, scale-freeness, modularity) emerge across a wide range of untuned parameter values, without fine-tuning to target statistics. revision: yes

  2. Referee: [Case studies] Case studies (cellular, software, ecological webs): the inference that tinkering is the dominant driver requires explicit comparison showing that the generative models outperform or are more parsimonious than selection-based alternatives on the same networks; conceptual similarity alone does not establish dominance.

    Authors: The manuscript emphasizes the sufficiency of tinkering mechanisms in generating observed architectures, thereby questioning the necessity of selection as the primary driver. We do not claim empirical dominance in every instance but argue for a reevaluation of the role of selection. However, we agree that explicit model comparisons would strengthen the case. We will add a discussion in the case studies section outlining how future work could perform such comparisons and note the current limitations in establishing strict dominance. revision: partial

Circularity Check

0 steps flagged

No significant circularity detected

full rationale

The paper's central argument contrasts selection-optimization with generative duplication-rewiring models that produce heterogeneous, scale-free and modular topologies. The provided abstract and description frame this as a conceptual comparison of model outcomes to observed patterns ('can be modelled using duplication-rewiring rules. These give rise to... architectures observed'), without any quoted equations, parameter-fitting procedures, or self-citation chains that reduce predictions to inputs by construction. No self-definitional steps, fitted-input predictions, or load-bearing uniqueness claims appear. The derivation remains self-contained via external generative rules whose properties are independently verifiable.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Review performed on abstract only; no explicit free parameters, invented entities, or detailed axioms are extractable. The central argument rests on the domain assumption that duplication-rewiring suffices to generate observed topologies.

axioms (1)
  • domain assumption Duplication-rewiring rules generate the heterogeneous, scale-free and modular architectures observed in real networks
    Stated in the abstract as the alternative to selection-optimization.

pith-pipeline@v0.9.0 · 5768 in / 1325 out tokens · 32804 ms · 2026-05-24T22:38:33.374364+00:00 · methodology

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Reference graph

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