Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5742232 | Ecological Modelling | 2017 | 12 Pages |
â¢Spatial Simulation is fuelled and challenged by big spatial data and strong computers.â¢Potential: explain process-pattern relationships and simulate realistic scenarios.â¢Challenges: Validity? Communicating complexity? Contribution to theory?â¢Further research: scrutinising the role of space to address these challenges.
Spatial Simulation is a spatially explicit, bottom-up modelling approach that includes individual-based models and cellular automata. While spatial heterogeneity and individual variation have been considered as noise in the past, this is exactly what has become the centre of interest of the individual-based paradigm in ecology. According to Individual-based Ecology, the interaction and behaviour of individual organisms leads to the emergence of macro-level patterns on the system scale. Although individual-based models have almost always been spatially explicit, the focus was commonly given to temporal processes and behavioural rules over spatial aspects. Today, the wide availability of spatial data and ever increasing computational power together with a strive for realistic models has renewed the attention to spatial aspects in simulation modelling. This review provides an overview of the state of the art of Spatial Simulation modelling in Ecology, reviews its limitations and open issues and it discusses future research avenues by taking an explicit geospatial perspective. The main avenues that are discussed revolve around the role of spatial context to determine the structure of living systems, potentials of hybrid top-down/bottom-up model designs to integrate hierarchical, spatial and temporal scales of ecological systems, and current trends in the representation and analysis of simulated spatio-temporal (big) data.
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