Theory underlying the Virtual Ecosystem#

Ecosystems are complex systems that arise from the interplay between animals, plants, and soil microbes with their abiotic environment. Many of these interactions are non-linear and happen across a wide range of spatial and temporal scales which makes ecosystem dynamics and emergent phenomena such as resilience to environmental stressors challenging to understand and predict.

Despite rapid advancements in the development of detailed ecological models for terrestrial ecosystems (Best et al., 2011, Clark et al., 2011, Fatichi et al., 2019, Geary et al., 2020, Harfoot et al., 2014) , most models are limited in the breadth of processes being incorporated, and in the diversity of users that might benefit from such models.

The general approach of the Virtual Ecosystem is to build on these model frameworks, and to connect this prior work into a single modelling framework that provides a fully mechanistic, fully integrated representation of key abiotic and biotic processes that govern three key emergent properties of terrestrial ecosystems: their stability, resilience, and sustainability.

We think we can replicate complex ecosystem dynamics by focussing on the physiology of individual organisms and how that’s influenced by the abiotic environment simulated based on first-principles physics Fig. 1. The development serves the perspectives of a wide variety of users and disciplines (see Box; Virtual Ecosystem Project Team 2024).

A diagram of the four domains in the Virtual Ecosystem — Fig. 1 The key processes in the Virtual Ecosystem (from Ewers *et al.*, 2024). The model aims to replicate ecosystem dynamics across four ecological domains: plants, animals, soil, and the abiotic environment. These domains are dynamically connected through the transfer of matter and energy.#

The ecological (or physical) theory underlying each of our core set of models are described in the following pages:

The animal model.
The plants model.
The abiotic models (i.e. hydrology, abiotic and abiotic_simple)
The soil models (i.e. soil and litter)

User stories serve as a project management tool that outlines the criteria for project success. Below, we present example user stories as outlined in (Ewers et al., 2024), each equally vital in defining the success of a holistic ecosystem model. Fulfilling the requirements of all user stories is necessary for the model to achieve complete success.

Core user stories

As a systems ecologist, I will be able to identify any core components and sub-networks that exert strong control over the full system dynamics, so that I can understand the mechanisms underlying ecosystem stability.
As a disturbance ecologist, I will be able to track the attenuation of external perturbations through the system, so that I can understand the mechanisms underlying ecosystem resilience.
As a sustainability scientist, I will be able to calculate the rate at which ecosystem services are provided, so that I can make predictions about the long-term sustainability of the ecosystem.
As a biogeochemist, I will be able to track the flow of carbon, nitrogen and phosphorus through the ecosystem, so that I can quantify elemental balances and residence times.
As a computational ecologist, I will have a modular tool that will allow me to contrast different approaches to modelling ecosystems, so that I can better understand the processes that drive ecosystem dynamics.
As a community ecologist, I will be able to predict the spatial and temporal distribution of biomass within and among functional groups, so that I can understand how functional diversity is maintained.

Applied User stories

As a hydrologist, I will be able to predict the frequency and magnitude of flood events, so that I can design downstream flood defences.
As a field ecologist, I will be able to identify knowledge gaps that significantly impair our ability to predict ecosystem dynamics, so that I can prioritise future data collection activities.
As an applied ecologist, I will be able to examine the impact of climate change and extreme climatic events on ecosystem dynamics, so that I can predict the likely future state of the ecosystem.
As a conservation biologist, I will be able to examine the impacts of invasion, introduction and extinction on ecosystem dynamics, so that I can quantify the importance of species-level conservation actions.
As a climate scientist or carbon offsetting company, I will be able to examine the net carbon sequestration potential of an ecosystem over decadal to centennial timescales.
As a resource manager, I will be able to predict the outcomes of competing sets of management strategies, so that I can make informed decisions about implementing cost-effective management actions.