Huge Challenges

In this series of post specially dedicated to the role playing environmental modelling facing the global environmental change, we analysed different models approaches and the huge challenges facing modellers. Probably the most significant analysis that should carry out regarding to the weaknesses of models, it is the opportunity that those areas give us to improve models.

The huge environmental threat has placed to models in a really significant role. As the title of this blog say, there are enormous challenges for a huge concern. This huge concern has led to an intense global debate and models are giving us day to day more understanding and more accuracy in the prediction about our future and the potential negatives impacts; the threat is real.

As a result of this massive concern, another challenge arises from the necessity to communicate how the different models work and how the outcomes obtained by complex methods should be suitably communicated to stakeholders. This group involves not only decision makers (authorities) but also the global community. All of us are potential affected. A suitable way in this direction it is to include the technical aspect behind environmental modelling in an accessible and clear system for the community and political authorities. For instance, through simplified and interactive web tools or through open public presentations. In this task, as Hall et al. (2014) have argued, a major difficulty has been that students has been educated in technical aspects of models but the normal tools of education in this field have omitted the role of communication.

When specialists are presenting relevant results to communities, the interpretation of results can be influenced by personal biased concerns which give different point of view from a non-technical perspective. The experience of knowing the concerns (even from personal and partial point of view) of potentially affected communities could be highly beneficial for certain elements in the research. 

Finally, it is fundamental to look the future with a clear understanding of models as an abstraction of reality, with strengths and weaknesses. Although the final result is taken from the model, this is finally given by the capacity of the modeller to interpret those outcomes in a particular modelling context.