Over the next 9 posts I’ll discuss the validation, evaluation and interpretation of environmental simulation modelling. Much of this discussion is taken from chapter seven of my PhD thesis, arising out of my efforts to model the impacts of agricultural land use change on wildfire regimes in Spain. Specifically, the discussion and argument are focused on simulation models that represent socio-ecological systems. Socio-Ecological Simulation Models (SESMs), as I will refer to them, are those that represent explicitly the feedbacks between the activities and decisions of individual actors and their social, economic and ecological environments.
To represent such real-world behaviour, models of this type are usually spatially explicit and agent-based (e.g. Evans et al., Moss et al., Evans and Kelley, An et al., Matthews and Selman) – the model I developed is an example of a SESM. One motivating question for the discussion that follows is, considering the nature of the systems and issues they are used to examine, how we should go about approaching model evaluation or ‘validation’. That is, how do we identify the level of confidence that can be placed in the knowledge produced by the use of a SESM? A second question is, given the nature of SESMs, what approaches and tools are available and should be used to ensure models of this type provide the most useful knowledge to address contemporary environmental problems?
The discussion that follows adopts a (pragmatic) realist perspective (in the tradition of Richards and Sayer) and recognises and the importance of the open, historically and geographically contingent nature of socio-ecological systems. The difficulties of attempting to use general rules and theories (i.e. a model) to investigate and understand a unique place in time are addressed. As increasingly acknowledged in environmental simulation modelling (e.g. Sarewitz et al.), socio-ecological simulation modelling is a process in itself in which human decisions come to the fore – both because human decision-making is being modelled but also, importantly, because modellers’ decisions during model construction are a vital component of the process.
If these models intended to inform policy-makers and stakeholders about potential impacts of human activity, the uncertainty inherent in them needs to be managed to ensure their effective use. Fostering trust and understanding via a model that is practically adequate for purpose may aid traditional scientific forms of model validation and evaluation. The list below gives the titles of the posts that will follow over the next couple of weeks (and will become links when the post is online).
The Nature of Open Systems
Realist Philosophy in the Environmental Sciences
Interactive vs. Indifferent Kinds
Affirming the Consequent
Relativism in Modelling
Alternative Model Assessment Criteria
Stakeholder Participation and Expertise