Ecological networks simulation with CytoSense data

14.08.2019  by  Tina Silovic


Fig 1: Conceptual model of the environmental impact assesment in aquatic ecosystem

Fig 2: Ecological networks with their functional groups according to their trophic levels and total node throughflows.

Flow cytometric data from a CytoSense was used in a new paper by Pereira et al. (2019): "Ecological networks simulation by fuzzy ecotoxicological rules".

The main objective of this paper was to present the development of an early warning tool for environmental risk assessment (Fig 1).

Pollutants present an emergent treat in many coastal areas. Therefore, defining their impact and effect of pollutants on the whole ecosystem  is of utter importance. Due to the limited tolerance to pollutants, plankton presents an important bioindicators for early warning signals of any disturbances happening in the ecosystem. Yet, direct observations are often time-consuming and infeasible, this is why the usage of computational models within the regulatory decision process has been continually growing and might be highly helpful when direct sampling is not possible. In order to build a good mathematical model, one needs to rely on the quality of the input data. In this case, the main input data was information about plankton cells obtained by CytoSense in mesocosm experiments. Moreover, flow cytometric data was used to build planktonic ecological network*, while ecotoxicological data were compiled to make a fuzzy knowledge base** (Fig 2). Applying fuzzy ecotoxicological rules to prune the ecological network proved to be able to demonstrate significant effects on the structure and functioning of marine ecosystem apart from its regime shift.

The methodology used in this article  is still in its infancy but its further development and consequential application  will surely present an important advance in environmental management.

*Details of how to build the ecological network topology of this paper can be found in Andrade et al., 2016 and Pereira et al., 2016.
**Fuzzy systems models form a special class of systems models that use the apparatus of fuzzy logic to represent the essential features of a system.