A model is a simplification of reality. Simulation models describe events as they develop over time; for example, changes in populations as organisms develop, mature, collapse and die. Such models provide us with tools to consolidate knowledge, to test hypotheses, to use as decision support tools (DSTs) in biotechnological applications, and the only way to ‘see into the future’ under climate change.
System dynamics is a computer-based simulation modelling approach that uses feed-back and feed-forward controls. These controls, termed cybernetics, characterises how the model processes information and adapts its behaviour in a fashion designed to mimic reality. Such interactions are fundamental to how real organisms function.
System dynamics modelling provides a robust and tractable approach to exploring complex interactive processes. It is especially suitable in situations where a reasonable general understanding is available of how individual sub-components operate, even in the absence of large numeric data series that are required to support traditional simulation modelling. These simulators, coupled with an interactive interface for the user, provide insights into real world problems that are not readily available through other means.
We have built and used system dynamics simulation models of microalgae and plankton for 30 years in pure and applied applications. Our simulators build on unique and broad level of expertise supported by empirical data from our EU and UK funded projects.
What is special about our Simulators?
The growth and survival of any organism depends on its characteristics and traits. Expression and regulation of these features under different conditions governs the behaviour of organisms and contribute to their success. A simulation model that can capture such reality provides a ‘digital twin’.
Most traditional microalgae and plankton models use approaches akin to Discrete Event Simulations (DES). DES models have a series of processes operating in a chain, with no feedbacks modulating the behaviour and physiology of the organisms. At the other extreme, Metabolic Flux Analysis (MFA) models are used in systems biology applications coupling ’omics and biochemistry. However, MFA models provide steady-state solutions and are thus ill-suited for dynamic simulations.
Our simulation models are different. We use System Dynamics (SD) approaches. These enable us to incorporate feedback mechanisms modulating physiological processes that are core to real biology and ecology. These feedback controls, termed cybernetics, facilitate the digital twin organisms to self-modulate their behaviour according to their environment.
The core of the organism models used in our products function efficiently, capable of being operated even in 3D scenarios involving finite volume computations. Our models can be configured to be consistent with available biodiversity information, describing a multitude of interacting traits. Each trait expression itself can be readily adjustable by the user to configure the description to best align with organisms of interest. Our models are thus ideal for ecological and biotechnological simulations.
Contact us to discuss how we can work together to support your interests.
ARK Dynamics Simulators – simulation models of plankton by people who have researched real plankton and microalgae.