Scaling Laws for Function Diversity and Specialization Across Socioeconomic and Biological Complex Systems

TL;DR

This paper introduces an empirical and mathematical framework to understand how function diversity and specialization scale across various complex systems, revealing universal growth patterns and system-specific differences.

Contribution

It develops a generalized Yule-Simon model with key parameters to explain diverse scaling laws of function diversity across biological, social, and economic systems.

Findings

Function diversity grows sublinearly with system size, with exponents from 0.35 to 0.57.

Cities exhibit logarithmic scaling of function diversity.

The model explains system-specific differences in diversification and specialization patterns.

Abstract

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.