How Much Greater Than the Sum of Its Parts? Evaluating Interactions Between Complex Policies

This presentation focuses on methods for the evaluation of complex policies. In particular, it focuses on evaluating interactions between policies and the extent to which two or more interacting policies mutually reinforce or hinder one another, in the area of environmental sustainability. Environmental sustainability is increasingly gaining recognition as a complex policy area, requiring a more systemic perspective and approach (e.g. European Commission, 2011). Current trends in human levels of resource consumption are unsustainable, and single solutions which target isolated issues independently of the broader context have so far fallen short. Instead there is a growing call among both academics and policy practitioners for systemic change which acknowledges and engages with the complex interactions, barriers and opportunities across the different actors, sectors, and drivers of production and consumption. Policy mixes, and the combination and ordering of policies within, therefore become an important focus for those aspiring to design and manage transitions to sustainability. To this end, we need a better understanding of the interactions, synergies and conflicts between policies (Cunningham et al., 2013; Geels, 2014). As a contribution to this emerging field of research and to inform its next steps, I present a review on what methods are available to try to quantify the impacts of complex policy interactions, since there is no established method among practitioners, and I explore the merits or value of such attempts. The presentation builds on key works in the field of complexity science (e.g. Anderson, 1972), revisiting and combining these with more recent contributions in the emerging field of policy and complex systems, and evaluation (e.g. Johnstone et al., 2010). With a coalition of UK Government departments, agencies and Research Councils soon to announce the launch of a new internationally-leading centre to pioneer, test and promote innovative and inclusive methods for policy evaluation across the energy-environment-food nexus, the contribution is particularly timely.

Storytelling and story testing in domestication

The domestication of plants and animals marks one of the most significant transitions in human, and indeed global, history. Traditionally, study of the domestication process was the exclusive domain of archaeologists and agricultural scientists; today it is an increasingly multidisciplinary enterprise that has come to involve the skills of evolutionary biologists and geneticists. Although the application of new information sources and methodologies has dramatically transformed our ability to study and understand domestication, it has also generated increasingly large and complex datasets, the interpretation of which is not straightforward. In particular, challenges of equifinality, evolutionary variance, and emergence of unexpected or counter-intuitive patterns all face researchers attempting to infer past processes directly from patterns in data. We argue that explicit modeling approaches, drawing upon emerging methodologies in statistics and population genetics, provide a powerful means of addressing these limitations. Modeling also offers an approach to analyzing datasets that avoids conclusions steered by implicit biases, and makes possible the formal integration of different data types. Here we outline some of the modeling approaches most relevant to current problems in domestication research, and demonstrate the ways in which simulation modeling is beginning to reshape our understanding of the domestication process.