Complexity, Collective Effects and Modelling of Ecosystems: formation, function and stability

TL;DR

This paper explores how applying statistical mechanics to ecology enhances understanding of ecosystem formation, function, and stability by modeling complex interactions and emergent properties.

Contribution

It advocates for integrating statistical mechanics into ecological modeling to better capture the non-stationary, complex nature of ecosystems.

Findings

Statistical mechanics provides a quantitative framework for ecology.

Combining these fields improves ecological models.

The approach broadens the scope of statistical mechanics.

Abstract

We discuss the relevance of studying ecology within the framework of Complexity Science from a statistical mechanics approach. Ecology is concerned with understanding how systems level properties emerge out of the multitude of interactions amongst large numbers of components, leading to ecosystems that possess the prototypical characteristics of complex systems. We argue that statistical mechanics is at present the best methodology available to obtain a quantitative description of complex systems, and that ecology is in urgent need of ``integrative'' approaches that are quantitative and non-stationary. We describe examples where combining statistical mechanics and ecology has led to improved ecological modelling and, at the same time, broadened the scope of statistical mechanics.