Pathways to a Low Carbon Economy

Last week (Friday 21 October), a talk was given by Nick Winder from Newcastle University; a key member of a team of ‘science monkeys’, as he put it himself, that  were enlisted by the European Union to develop a series of non-resilient cycling models. These would then be used to help set strategies and put plans in place that could lead to a low carbon economy.

The Complex Project (above) was an ambitious venture which set out to design scientific models which would allow the prediction of carbon cycle systems, which cannot easily be observed, and from these models- methods to reduce carbon could be created.

Traditionally, many models use the basiscycle-of-adaptive-change of adaptive cycles (left), which are typically resilient due to the ability to show stability in the form of a sort period cycle which returns to the same place again and again.

Due to the evolving relationship between humans and the environment, this form of model was inadequate as there is a lack of resilience in real life systems.

Therefore a model is required that returns to a different place. This however provides a remarkable problem to scientists who set out to make models, by creating non-resilient models which by nature change their starting place repeatedly, it is impossible to predict the outcome of the simulation. How does one go about creating a model to represent something that know one knows is going to happen?

This need to create models which are capable of breaking down and being reinvented calls into question several forms of doubt-

  • Uncertainness, as in the question of “What will happen in the model?”
  • Meaninglessness, as in the question of “Will the outcome be useful?”

All these requirements have lead to the choice of one specific form of model, a Participatory Model.

This requires a stakeholder community (often including other scientists as well as donors) and the focal environment or landscape to be modelled. The model will then be created to represent the system as best as possible, and then tested rigorously to highlight any weaknesses. One must also consider within this model the multiple levels of causality built around various spatial and temporal factors.


Personally, as a Zoologist with a keen interest in Animal Behaviour, I find this to be a subject that I have little understanding of and no particular desire to invest in. The talk gave an interesting insight into the use of scientific models, however the speaker gave most details at a complexity level above novice (which is where I stand in this topic) so I struggled to follow. I was disappointed by the startling lack of information regarding the results of the project and little to no mention of carbon at all.

Due to this, I would say it has confirmed my choice of subject areas in which I wish to look for a career. This talk has had little effect on my overall goals.

Complex have since published ~70 papers with more to come.


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