BERGEN SUMMER RESEARCH SCHOOL – 2016: Water, Climate and Society

The annual Bergen Summer Research School (BSRS) is an interdisciplinary venue for exploring some of the greatest challenges of our time. Focus this year is Water, Climate and Society. Seven parallel courses will span disciplines from the natural, health, and social sciences to the humanities.

This year’s scientific leader, Professor Terje Tvedt, is series editor of the nine-volume series A History of Water with contributions from over two hundred researchers from most disciplines — and from about one hundred countries. He has published extensively on the River Nile and on theoretical issues involved in studying water-society issues, see Water and Society, 2016. Professor Tvedt is known for three award-winning TV-documentaries on water that has been shown all over the world.

BSRS seeks to create a unique environment for participants to present, engage, discuss, progress their thinking, and improve on their work. As part of the taught courses, there will be an excursion into the waterscape of western Norway to explore the impact of rivers, fjords and glaciers on societies.

Keynote speakers include Professor Terje Tvedt, Professor Owen McIntyre, University College Cork , Professor Robin Marsh, University of Berkeley, and Docent Terje Oestigaard at Uppsala University, Sweden

Modelling the complexities of water, climate and society

This course will address the complexities of the water, climate and society nexus by way of computer based modelling and simulation. The intent is for participants to familiarize themselves with system dynamics, – a method aimed at explaining and managing change (i.e. dynamics) at large based on an understanding of the underlying structure governing such change.

Course leader: Professor Pål Davidsen, Department of Geography, UiB

A language for interdisciplinary teaching and research
Erling Moxnes
Professor, Department of Geography, UiB

Interdisciplinary teaching and research is challenging as long as the individual disciplines operate with different discipline specific languages. Stock and flow diagrams with only four unique symbols represent a “language” that is common to all dynamic systems. The lecture shows how nearly identical diagrams can be used to portray problem oriented models from different fields. Thus, deep un­der­standing of one problem can be easily transferred to other and similar pro­blems. One example is transfer of knowledge from the fishery sector to the climate problem. Having a common language also makes it possible to combine knowledge from many fields when studying a specific problem. One example is the introduction of economic variables into a biological model of a fishery.

Reading list:
Moxnes, E. (1998). “Not only the tragedy of the commons, misperceptions of bioeconomics.” Management Science 44(9): 1234-1248.

Moxnes, E. (2004). “Misperceptions of basic dynamics, the case of renewable resource management.” System Dynamics Review 20(2): 139-162.

Moxnes, E. and A. K. Saysel (2009). “Misperceptions of global climate change: information policies.” Climatic Change 93(1-2): 15-37.

Sterman, J. D. (2011). “Communicating climate change risks in a skeptical world.” Climatic Change 108: 811-826.

An introduction to system dynamics based modeling and analy­sis of complex, dynamic systems
Pål I. Davidsen
Professor, Department of Geography, UiB

Complex, dynamic systems are characterized by causal structures that en­com­pass accumulation processes, feedback processes and non-linearity. Such struc­tures give rise to dynamic developments over time. Using system dynamics, we study the intimate relationship between structure and dynamics by way of com­puter based model­ing and simulation. We investigate how the underlying struc­ture gives rise to dynamic behavior and how that behavior feeds back to modify the relative significance of the underlying structure components.

Reading list:
Ford, A. (1998). “Modeling the environment”, Island Press, pp. 1 – 100.

Davidsen, P. I. (2016). “Introduction to System Dynamics”, PPT-presentation.

Davidsen, P. I. (1989): “The structure-behavior graph”, IFI-publication.

Modeling the dynamics of rivers and wetlands
Pål I. Davidsen
Professor, Department of Geography, UiB

Fresh water is a main resource that, in very many ways, constitutes a boundary condition in our lives. It defines the geographical space that is available to us, and the conditions under which we live in that space. The dynamics of water, including floods and draughts, are, consequently, essential to us. Modeling the water in rivers and wetlands and its co-flows of nutrients and pollutants, is thus essential in our studies of water and its social consequences.

Reading list:
(in preparation)

Modeling population dynamics
David Wheat
Associate Professor, Department of Geography, UiB

Circular and cumulative causation is a common feature of interactive social sys­tems, and it is also frequently true of interaction between social and natural sys­tems.  The role of population dynamics is often central to both types of interact­tion, and that is the focus of this lecture.   Students will learn to build simple popu­lation models involving births, deaths, immigration, and emigration, and they will experiment and analyze more complex models that interact with a soci­al system (e.g., a national or regional economy) and with a natural system (e.g., a rural or urban water system).   The students will observe that many of the mo­del­ing principles and techniques can be transferred from social system analysis to natural system analysis.  The goal of this lecture is to develop students’ intu­ition for thinking systemically about the central role of population dynamics in the context of pressing environmental issues such as water supply and quality in an era of climate change.

Reading list:
(in preparation)

Modeling Epidemics
Pål I. Davidsen
Professor, Department of Geography, UiB

Epidemic diseases are often associated with water, whether carried by the water, or by vectors that are dependent on still water.  Such diseases spread effectively in a population in ways that are characterized by the non-linear interaction be­tween posi­tive and negative feedback. Consequently, we may effectively model and analyze such epidemics by way of a system dynamics approach.

Reading list:
Bruce Hannon & Matthias Ruth: Dynamic Modeling of Diseases and Pests, Springer Verlag, 2009, pp. 1 – 58.

System dynamics at the water – food nexus

Birgit Kopainsky
Researcher, Department of Geography, UiB

Food and farming systems are both complex and dynamic in nature and require stakeholders to constantly learn and adapt to change. This lecture explores the contributions that system dynamics modeling tools and techniques can make in this regard. Selected case studies illustrate the diversity of the practical implementation of the method, e.g. for national-level policy making, elicitation and re-representation of stakeholder knowledge and for building local knowledge and decision making capacity. Case studies focus on small-scale farming systems and their interactions with water both in sub Saharan Africa (Zambia) and in Asia (Cambodia).

In the afternoon, we will discuss a systems mapping workshop held in the Blue Nile catchment area in Ethiopia where participants used system dynamics tools to reflect on the requirements for sustainable development of this coupled human-nature system. Participants will then use the same approach to reflect on their own research projects.

Reading list:
Kopainsky, B., K. Tröger, S. Derwisch, and S. Ulli-Beer 2012. Designing sustain­able food security policies in sub-Saharan African countries: How social dynam­ics over-ride utility evaluations for good and bad. Systems Research and Beha­vioral Science 29(6):575-589.

Kopainsky, B., R. Huber, and M. Pedercini 2015. Food provision and environ­men­tal goals in the Swiss agri-food system: System dynamics and the social-ecologi­cal systems framework. Systems Research and Behavioral Science 32(4):414-432.

Saysel, A. K., and Y. Barlas 2001. A dynamic model of salinization on irrigated lands. Ecological Modelling 139(2–3):177-199.