Scaling laws for function diversity and specialization across socioeconomic and biological complex systems
Function diversity, the range of tasks individuals perform, and specialization, the distribution of function abundances, are fundamental to complex adaptive systems. In the absence of overarching principles, these properties have appeared domain-specific. Here, we introduce an empirical framework and a mathematical model for the diversification and specialization of functions across disparate systems, including bacteria, federal agencies, universities, corporations, and cities. We find that the number of functions grows sublinearly with system size, with exponents from 0.35 to 0.57, consistent with Heaps' law. In contrast, cities exhibit logarithmic scaling. To explain these empirical findings, we generalize the Yule-Simon model by introducing two key parameters: a diversification parameter that characterizes how existing functions inhibit the creation of new ones and a specialization parameter that describes how a function's attractiveness depends on its abundance. Our model enables cross-system comparisons, from microorganisms to metropolitan areas. The analysis suggests that what drives the creation of new functions depends on the system's goals and structure: federal agencies tend to ensure comprehensive coverage of necessary functions; cities tend to slow the creation of new occupations as existing ones expand; and cells occupy an intermediate position. Once functions are introduced, their growth follows a remarkably universal pattern across all systems.
Authors
- S. Redner
- Vicky Chuqiao Yang (ORCID: https://orcid.org/0000-0001-6111-3699)
- Geoffrey B. West
- H. C. Youn
- Christopher P. Kempes
- José Ignacio Arroyo
- James Holehouse
Institutions
- Santa Fe Institute (US)
- Seoul National University (KR)
- Research Organization of Information and Systems (JP)
- Massachusetts Institute of Technology (US)
- Graduate School USA (US)
- London School of Economics and Political Science (GB)
Publication Details
- Journal
- Proceedings of the National Academy of Sciences
- Published
- 2026-02-12
- DOI
- https://doi.org/10.1073/pnas.2509729123
- Primary Topic
- Evolutionary Game Theory and Cooperation
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- Santa Fe Institute
- Institute of Management Research, College of Business Administration Seoul National University
- National Research Foundation
- Seoul National University
- National Research Foundation of Korea