The environmental domain poses a number of important challenges for the modeling task. First, we have to deal with multiple dynamics that often involve spatial variations. The time-scales of the relevant phenomena range from long-term changes in climatic conditions to chemical reactions occurring within parts of a second. Second, we face largely incomplete knowledge in various respects. The obs...

In recent years, ecologists have stepped up to address the challenges imposed by rapidly changing climates. Some researchers have developed niche-based methods to predict how species will shift their ranges. Such methods have evolved rapidly, resulting in models that incorporate physiological and behavioral mechanisms. Despite their sophistication, these models fail to account for environmental...

Many biological phenomena are inherently multiscale, i.e. they are characterized by interactions involving different spatial and temporal scales simultaneously. Though several approaches have been proposed to provide “multilayer” models, only Complex Automata, derived from Cellular Automata, naturally embed spatial information and realize multiscaling with well-established inter-scale integrati...

Predicting the quality of water and air is a particular challenge for forecasting systems that support them. In order to represent the small-scale phenomena, a high-resolution model needs accurate capture of air and sea circulations, significant for forecasting environmental pollution. Data assimilation is one of the state of the art methods to be used for this purpose. Due to the importance of...

Predicting the quality of water and air is a particular challenge for forecasting systems that support them. In order to represent the small-scale phenomena, a high-resolution model needs accurate capture of air and sea circulations, significant for forecasting environmental pollution. Data assimilation is one of the state of the art methods to be used for this purpose. Due to the importance of...