Ten dimensions of integration: Guidelines for modellers

Community member post by Serena Hamilton and Tony Jakeman

serena-hamilton
Serena Hamilton (biography)
tony-jakeman
Tony Jakeman (biography)

Why Integrated Assessment and Integrated Modelling? In our highly connected world environmental problems have social or economic causes and consequences, and decisions to assist one segment of a population can have negative repercussions on other parts of the population. It is broadly accepted that we require integrated, rather than piecemeal approaches to resolve environmental or other complex problems.

Integrated Assessment and its inherent platform, Integrated Modelling, bring together diverse knowledge, data, methods and perspectives into one coherent and comprehensive framework. This process of organizing and synthesizing multiple forms of information across disciplinary and conceptual boundaries allows us to explore linkages and feedbacks between different parts of the system, as well as the trade-offs involved with alternative management interventions on different socioeconomic and environmental criteria.

While Integrated Assessment, Integrated Modelling and other forms of Integration are not new concepts, there has been little agreement on what constitutes “integration”. What are we actually integrating? We shed light on this by viewing integration in terms of ten salient dimensions.

integration-modelling_capture

The first three dimensions represent the key drivers of integration, specifically the need to address multiple: i) issues of concern, ii) management interventions and governance arrangements, and iii) stakeholders. This requires the integration of different elements from iv) natural systems and v) human/social systems, in addition to their vi) spatial scales and vii) temporal scales. The final dimensions relate to the methodological aspects of the integration of multiple viii) disciplines, ix) methods, models, tools and data and x) sources and types of uncertainty.

These ten dimensions are intricately linked – such that the nature of one dimension is highly dependent on all others, and inadequate attention to any one dimension can render the analysis irrelevant. For example, the parts of the system to be integrated and the methodological considerations are contingent on the issues of concern. However the issues can also depend on what spatial and temporal boundaries are being assessed and the stakeholders’ worldviews and positions in the system.

A key challenge in Integrated Assessment and Modelling is accommodating the multiple spatial and temporal scales of system processes and interests, and the need to upscale or downscale processes. Further, disciplines, data, methods and tools use different languages or formats which are not always readily compatible. One term can mean different things across disciplines or tools; conversely, different terms can be used to describe the same thing.

Uncertainty, which is rarely given holistic treatment, pervades all other dimensions. The combination of elements within, as well as across, dimensions can easily lead to a surge in uncertainty. Uncertainty also varies as a function of time, with projections further into the future involving higher uncertainties. How to best manage uncertainty depends on the problem and task at hand. Reducing uncertainty may not always be practical or even possible.

With colleagues we discuss all dimensions in detail in a recent paper and outline possible approaches to combining elements within each dimension (Hamilton et al, 2015). We are keen to hear your experiences of integration in modelling. Do our ten dimensions ring true? Can you offer good examples? Are there other dimensions that you would add? If you are not a modeller, do these dimensions seem useful in other ways?

Reference:
Hamilton, S. H., ElSawah, S., Guillaume, J. H. A., Jakeman, A. J. and Pierce, S. A. (2015). Integrated assessment and modelling: overview and synthesis of salient dimensions. Environmental Modelling and Software, 64: 215-229. Online: http://www.sciencedirect.com/science/article/pii/S1364815214003600

Biography: Dr Serena Hamilton is a Postdoctoral Research Fellow at the Centre for Ecosystem Management at Edith Cowan University, Western Australia. Her research interests include integrated assessment and modelling, Bayesian networks and decision support tools for water resources management. Her recent research focuses on modelling for improving understanding of system linkages and management of complex socioecological systems.

Biography: Prof Tony Jakeman is Director of the Integrated Catchment Assessment and Management (iCAM) Centre, at Fenner School of Environment and Society, The Australian National University. His research interests include system identification, integrated assessment methods and decision support systems for water and associated land resource problems. He is leader of the National Centre for Groundwater Research and Training Program on Integrating Socioeconomics, Policy and Decision Support and Principal Investigator on a project to synthesise core modeling practices funded by the National Socio-Environmental Synthesis Center (SESYNC).

5 thoughts on “Ten dimensions of integration: Guidelines for modellers

  1. Thank you Kai, Tim and Phil for your comments. It is encouraging to hear that the dimensions align well with your experiences dealing with other complex problems. Interdisciplinary problems must be addressed in an interdisciplinary manner, and their complexity does not just stem from one dimension – as Phil mentioned. It is all the dimensions, and perhaps more importantly, their interactions with one another. Tim, your multi-lens framework sounds like an interesting approach to understanding and managing sustainability problems.

  2. One of the issues I had when the first models for ‘complex’ project management were put forward was the idea that it was the management of projects which was complex. I disagreed then, and still do. As this article amply demonstrates, it is the environment and context within which a project is managed which brings into play complex systems and structures. The need to identify and manage projects being run at ‘the edge of chaos’ are, in my opinion, the essentials of ‘complex’ project management. All the rest – management of time, costs, resources, risk etc., – vary in only minor aspects from project management in stable and controlled environments.

  3. [copied from LinkedIn discussion] We all have our mental models of the world and I have applied and shared several of my own in the years. Recently I began to appreciate the transdisciplinary nature of most things social and the limitations of the scientific method to understand them. When I view this from a sustainability science perspective, the result was a Sustainability Scientific Method v1.0 – – an analysis framework one can “drop” into on-going issues such as agriculture sustainability, in situ, if you will. I have a strong bias toward governance of such systems and so the first lens focuses on governance actors and styles. The second lens is identifying the desired outcomes/outputs of the system (using landscape management indices). I can then read the system as it unfolds.

  4. Thank you for your article and diagram – it is aligned with my experiences. My decades-long focus has been on agriculture landscape sustainability and recently honed in on how shared governance can support a transdisciplinary approach. I recently completed a Taylor & Francis manuscript, Shared Governance for Sustainable Working Landscapes. A bit more at http://bit.ly/20ZWl1Z

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