# Metabolic scaling from Fibonacci dynamics

## TL;DR

This paper introduces a discrete Fibonacci-based model for metabolic scaling, linking organism development stages to scaling exponents and improving empirical data fit over traditional continuous fractal models.

## Contribution

It presents a novel discrete approach to metabolic scaling using Fibonacci growth patterns, contrasting with classical continuous fractal models like WBE.

## Key findings

- Fibonacci-based scaling exponents vary with developmental stages.
- Model aligns well with empirical metabolic data across mammals.
- Captures deviations from classical scaling laws.

## Abstract

We propose a discrete model to determine the metabolic scaling exponent based on Fibonacci growth patterns and discrete biological development phases. In contrast to continuous fractal models such as the West-Brown-Enquist (WBE) theory, the present approach describes metabolic scaling as the cumulative result of successive discrete stages, each incrementally contributing to metabolic activity. The scaling exponent b(n) emerges naturally from the logarithmic relationship between consecutive Fibonacci numbers, varying systematically with the organism's developmental stage. A refined logarithmic formulation significantly enhances quantitative agreement with empirical metabolic data across various mammalian species. This discrete framework effectively captures deviations from classical scaling laws, directly connecting recursive hierarchical structures with metabolic processes. Our model provides an alternative to traditional fractal transport approaches and can be naturally extended to hierarchical physical systems, opening new avenues to explore stage-dependent scaling phenomena in complex adaptive systems.