Evolutionary fields can explain patterns of high-dimensional complexity in ecology

Abstract

One of the properties that make ecological systems so unique is the range of complex behavioural patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors which have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviours are possible. We propose a model inspired by particle mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, that suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

Modelling coevolution in ecological networks with adaptive dynamics

“…For reducing evolutionary pressures, species can modify their functional and morphological traits under the constraints of functional trade‐offs . Adaptive dynamics has been proven to be a powerful tool for exploring the rich possibility of ecological dynamics and evolutionary trajectories in multispecies ecological networks. Adaptive diversification from coevolution can be considered a possible pathway leading to contemporary multispecies ecological networks.…”

Order Parameter in Bacterial Biofilm Adaptive Response

“…Both theorists and biologists are proposing that physical or chemical laws cannot be directly brought into biology, but a novel theory for organisms is needed (Soto et al, 2016 ). Although I do agree that theories for biology require rethinking, I cannot but help to quote several important discoveries in physics that are also present in biology (Jeong et al, 2000 ; Wilsenach et al, 2017 ). In particular, scale invariance leading to fractal structure and power laws are nowadays ubiquitously observed from biological data (Piras and Selvarajoo, 2015 ; Simeoni et al, 2015 ).…”