Hybrid theory offers new way to model disturbed complex systems
Multiscale complex systems are ubiquitous in fields ranging from immunology and ecology to economics and thermodynamics. They are also notoriously difficult to model. The traditional approach uses a bottom-up approach or Top-down approach. But in disturbed systems, such as forest ecosystems after fire or societies during a pandemic, these one-way models fail to capture the interaction between small-scale behavior and system-level properties. SFI External Professor John Harte (UC Berkeley) and his collaborators worked to address this challenge by building a hybrid approach that combines bottom-up behavior and top-down behavior in a single theory. Cause and effect relationships.
The paper by Harte et al. Proceedings of the National Academy of SciencesPublished on December 6, they outline their approach and provide four simplified examples where it can be applied.
“Over the past 14 years, we have written a series of papers showing that in ecology this top-down approach is very powerful and reveals patterns in ecosystems,” Hart said. “It accurately predicts ecological patterns such as species-area relationships (how diversity increases with plot size) and the distribution of species abundance and body size. But six years ago, we found that when ecosystems are severely When disturbances occur – and as a result, system-level properties change – then top-down approaches fail miserably. So Hart and his colleagues set out to develop a theory that could describe system-level dynamics and representations. Probability distributions of system components in changing complex systems.
Disturbance and the bidirectional feedback it can cause occur in many types of systems. In the event of a pandemic, the traditional bottom-up Susceptible-Infected-Recovery (SIR) equation helps measure an individual’s chance of becoming ill due to proximity to an infected person. However, this approach does not capture the interaction between micro and macro scales. As cases of a disease increase at a macro level, individuals may notice and change their behavior, causing the number of cases to decrease.
Likewise, within an economy, individuals’ decisions about whether to take a job or shop are affected by system-level attributes such as gross national product growth and inflation rates. At the same time, consumer spending is a driver of the economy and can influence economic growth or decline.
In 2021, Harte and colleagues presented their new method for the first time in the journal Ecological Express Their paper “DynaMETE: A hybrid MaxEnt plus mechanism theory for dynamic macroecology”. The team tested their theory on data from heavily disturbed forests in Panama, showing that their hybrid model could explain changes in species distributions. The authors now generalize their model to possible applications in other scenarios.
“This model allows us to calculate things we couldn’t calculate before,” Hart said. “In these two-tier systems, when there are both top-down and bottom-up influences, how do you calculate how the system behaves when it is disturbed? and Do individuals respond over time? There weren’t enough theories before. This theory allows us to predict the trajectories of system-level variables and probability distributions across parts of that system.
Hart proposed testing the theory in a combustion tank, a simple thermodynamic system, and said other tests were needed. “The biggest insight here is recognizing the importance of this problem. We think the theory is good, but it may not be correct. It still needs to be tested on multiple types of systems.”
In nonequilibrium thermodynamics, such as the proposed combustion box experiment, predicting the probability distribution of molecular kinetic energy has been a frontier problem. “It doesn’t count,” Hart said.
Mixture theory offers a new way to study dynamics, both in controlled laboratory settings and in some of the most tantalizing and critical problems facing humanity, from climate change and pandemics to economic fluctuations.
2024-12-06 21:19:04