Anticipation and Stimulation of Transitions

Goal of Research Group

The research group Anticipation and Stimulation of Transitions seeks to bring together insights on transitions in human and natural systems from researchers across all faculties at Utrecht University. The focus ranges from fundamental to applied research questions. We aim to develop a fundamental understanding of transitions that allows us to anticipate under what conditions a transition may occur. Building on that fundamental understanding we aim to identify how we can intervene in systems to stimulate transitions to desired system states or prevent systems from transitioning to undesired states.

The focus on transition arises from an urgent need to understand, manage and adapt to the rapid and non-linear changes facing human societies and the environment.

The research group is open to all UU researchers. The detailed research focus will be determined by the participants themselves and their interests and expertise.

Format of Meetings

We will organize idea-generator meetings and idea-development meetings. In generator meetings, 2 or 3 people will present their differing perspective on the topic under discussion. Following the presentations in each case, we will break into groups to discuss what was presented.  Each group reports in plenary on what they discussed, and the most promising ideas are written on the board. Follow-up is a crucial part of these meetings. At the end of each meeting those people who would like to follow-up with that idea or outcome sign their name on the board and organize a follow-up idea-development meeting. In those meetings, researchers can develop the initial ideas further.

What are the specific goals of this research group?

  1. To produce interdisciplinary papers, proposals, educational resources, popular media articles etc.
  2. To build a consortium towards a larger future grant such as the NWO Gravitation
  3. To develop interdisciplinary Master Thesis projects and create a stimulating interdisciplinary research environment for masters and PhD students
  4. To share knowledge of methods and approaches to understanding transitions
  5. To develop new integrative theories of transition across disciplines

Anticipation of Transitions

Anthropogenic change is perturbing many biophysical systems such as drylands, lakes and the dynamical systems in oceans (Kéfi et al., 2007; Scheffer et al., 2001; te Raa and Dijkstra, 2002), with the risk of critical transitions in these systems is increasing (Steffen et al., 2018). To protect natural biophysical systems from transitions we need to be able to anticipate which systems are at risk of transition and where the tipping points in these systems may lie (Feng Qing Yi et al., 2014; Yin et al., 2016). Where we anticipate transitions are likely, we need to intervene to prevent a transition to an undesirable system state (Scheffer et al., 2001). To do this, requires an understanding of the resilience of these systems and how that may be increased.

Figure 1. Anticipation of Transitions (taken from Scheffer et al. 2009).

Figure 1 shows many systems, such as the dryland system shown here, undergo subtle but predictable changes as they approach a critical transition. These changes may provide early warnings that allow us to anticipate the transition. Anticipation allows us, in certain instances, to take measures to intervene and prevent a transition. In others it gives us time to prepare so we can adapt to sudden future changes.

Stimulation of Transitions

To slow down anthropogenic change and move towards a sustainable development pathway, we require an urgent transition in human systems. Rather than anticipating transitions and building resilience, the goal is often to stimulate transition and undermine resilience of incumbent regimes such as the current fossil energy and industrialized food regimes. Knowledge on the social tipping points in these systems is crucial to increase understanding how such transitions come about (Farmer et al., 2019). A range of theories exist within the social sciences to explain how transitions occur in society and how we may stimulate them (Folke, 2006; Geels, 2011; Hekkert et al., 2007; Markard et al., 2012; Westley et al., 2011). However, we lack fundamental theories which unifies the disparate approaches in the social sciences and explains how social transition dynamics relate with transitions in nature.

Figure 2. Stimulation of Transitions in socio-technical systems (taken from Loorbach et al., 2017).

Figure 2 shows socio-technical regimes are resilient to innovation. For new innovations to break into an incumbent regime requires a number of niche innovations to coordinate and undermine the resilience of the incumbent regime. Equally landscape changes, for example in the wider global economy or a disruptive technology, such as the internet can also undermine the resilience of the regime.

Activities

First idea generator meeting on 29th November 13:00 – 14:30

Key speakers:

  • Dr. Anna von der Heydt: Anticipating environmental transitions
  • Prof. Koen Frenken: Stimulating innovation transitions

References

  • Feng Qing Yi, Viebahn Jan P., Dijkstra Henk A., 2014. Deep ocean early warning signals of an Atlantic MOC collapse. Geophysical Research Letters 41, 6009–6015. https://doi.org/10.1002/2014GL061019
  • Folke, C., 2006. Resilience: The emergence of a perspective for social–ecological systems analyses. Global environmental change 16, 253–267.
  • Geels, F.W., 2011. The multi-level perspective on sustainability transitions: Responses to seven criticisms. Environmental Innovation and Societal Transitions 1, 24–40. https://doi.org/10.1016/j.eist.2011.02.002
  • Hekkert, M.P., Suurs, R.A.A., Negro, S.O., Kuhlmann, S., Smits, R.E.H.M., 2007. Functions of innovation systems: A new approach for analysing technological change. Technological Forecasting and Social Change 74, 413–432. https://doi.org/10.1016/j.techfore.2006.03.002
  • Kéfi, S., Rietkerk, M., Alados, C.L., Pueyo, Y., Papanastasis, V.P., ElAich, A., Ruiter, P.C. de, 2007. Spatial vegetation patterns and imminent desertification in Mediterranean arid ecosystems. Nature 449, 213–217. https://doi.org/10.1038/nature06111
  • Loorbach, D., Frantzeskaki, N., Avelino, F., 2017. Sustainability Transitions Research: Transforming Science and Practice for Societal Change. Annual Review of Environment and Resources 42, 599–626. https://doi.org/10.1146/annurev-environ-102014-021340
  • Markard, J., Raven, R., Truffer, B., 2012. Sustainability transitions: An emerging field of research and its prospects. Research Policy, Special Section on Sustainability Transitions 41, 955–967. https://doi.org/10.1016/j.respol.2012.02.013
  • Scheffer, M., Carpenter, S., Foley, J.A., Folke, C., Walker, B., 2001. Catastrophic shifts in ecosystems. Nature 413, 591–596. https://doi.org/10.1038/35098000
  • Scheffer, M., Bascompte, J., Brock, W.A., Brovkin, V., Carpenter, S.R., Dakos, V., Held, H., van Nes, E. H., Rietkerk, M & Sugihara, G., 2009. Early-warning signals for critical transitions. Nature 461, 53-59
  • Steffen, W., Rockström, J., Richardson, K., Lenton, T.M., Folke, C., Liverman, D., Summerhayes, C.P., Barnosky, A.D., Cornell, S.E., Crucifix, M., Donges, J.F., Fetzer, I., Lade, S.J., Scheffer, M., Winkelmann, R., Schellnhuber, H.J., 2018. Trajectories of the Earth System in the Anthropocene. PNAS 115, 8252–8259. https://doi.org/10.1073/pnas.1810141115
  • te Raa, L.A., Dijkstra, H.A., 2002. Instability of the Thermohaline Ocean Circulation on Interdecadal Timescales. J. Phys. Oceanogr. 32, 138–160. https://doi.org/10.1175/1520-0485(2002)032<0138:IOTTOC>2.0.CO;2
  • Westley, F., Olsson, P., Folke, C., Homer-Dixon, T., Vredenburg, H., Loorbach, D., Thompson, J., Nilsson, M., Lambin, E., Sendzimir, J., Banerjee, B., Galaz, V., Van Der Leeuw, S., 2011. Tipping toward sustainability: Emerging pathways of transformation. Ambio 40, 762–780. https://doi.org/10.1007/s13280-011-0186-9
  • Yin, Z., Dekker, S.C., Rietkerk, M., van den Hurk, B.J.J.M., Dijkstra, H.A., 2016. Network based early warning indicators of vegetation changes in a land–atmosphere model. Ecological Complexity 26, 68–78. https://doi.org/10.1016/j.ecocom.2016.02.004