MELA: Modelling in Ecology with Location Attributes

Abstract

Ecology studies the interactions between individuals, species and the environment. The ability to predict the dynamics of ecological systems would support the design and monitoring of control strategies and would help to address pressing global environmental issues. It is also important to plan for efficient use of natural resources and maintenance of critical ecosystem services. The mathematical modelling of ecological systems often includes nontrivial specifications of processes that influence the birth, death, development and movement of individuals in the environment, that take into account both biotic and abiotic interactions. To assist in the specification of such models, we introduce MELA, a process algebra for Modelling in Ecology with Location Attributes. Process algebras allow the modeller to describe concurrent systems in a high-level language. A key feature of concurrent systems is that they are composed of agents that can progress simultaneously but also interacta good match to ecological systems. MELA aims to provide ecologists with a straightforward yet flexible tool for modelling ecological systems, with particular emphasis on the description of space and the environment. Here we present four example MELA models, illustrating the different spatial arrangements which can be accommodated and demonstrating the use of MELA in epidemiological and predator-prey scenarios.

Quantitative Aspects of Programming Languages and Systems over the past 2^4 years and beyond

“…In the setting of QAPL, we can mention several such examples: probabilistic variant of the process-algebraic µCRL language [90], discrete time variant of distributed πcalculus [48], probabilistic extension of π-calculus [117], interleaving semantics and true concurrent semantics for the probabilistic variant of π-calculus [142], stochastic broadcast π-calculus [131], stochastic version of Mobile Ambient [143], stochastic extension of the hybrid process algebra HYPE [32,33,68], stochastic extension of the Software Component Ensemble Language for modeling ensemble based autonomous systems [101], Linda-like coordination calculus extended with quantitative information [38], and finally a mixture of concurrent and probabilistic Kleene algebras enriched with probabilistic choices [110]. Further examples include process calculi for performance evaluation, like LYSA [28], proposed for the context of cryptographic protocols, CARMA [31], specifically defined for collective adaptive systems, MELA [107], for modeling in ecology with location attributes, and PEPA Queues [13], introduced for the modeling of queueing networks with mobility features. Moreover, PADS [116] is a process algebraic framework, inspired by real-time process algebra, for reasoning compositionally in a component-based fashion about resource demand and supply.…”

Analysis of Spatio-temporal Properties of Stochastic Systems Using TSTL

“…We used the process algebra MELA [30] to formally describe spatial population models and to perform stochastic simulations, in order to produce spatio-temporal trajectories for the SSTL monitoring. This process algebra MELA has been developed to build spatial population models of ecological systems, since consideration of the spatial aspect has been recognized as of key importance in ecology.…”