Adaptive governance for a changing coastline: science, policy and publics in search of a sustainable future

Annotation for Adaptive governance for a changing coastline: science, policy and publics in search of a sustainable future

Nicholson-Cole S., O'Riordan T.. 2009. Adaptive governance for a changing coastline: science, policy and publics in search of a sustainable future. Adapting to climate change: thresholds, values, governance.

Aim/objectives: 

Discusses the opportunities for adaptive governance of England’s coastline in response to climate change.

Geographic Focus: 

Methods: 

Key Findings: 

This chapter examines the challenges of creating effective governance for a sustainable coastline and describes conditions necessary for an adaptive response to climate change threats. The authors describe a poor match between national and coastal management policies and strategies. It is also argued that the present scientific evidence is insufficient to enable political and electoral consensus over decisions being made for coastal planning amongst the diverse stakeholders involved. Robust scientific information, shared visions, coordination of responsibility, adequate financing, and responsive public engagement are identified as building blocks for good coastal governance.

Lessons: 

For coastal organisations attempting to adapt to the emerging conditions imposed by climate change scenarios, robust scientific evidence may be beneficial and desirable to guide decision-making. However, consensus over scientific evidence is not a pre-condition of adaptive learning. In fact, it could be argued that issues of consensus are related more to social/cultural values rather than a lack of ‘robust science’. Nonetheless, adaptive learning processes should be capable of acting on incomplete information and understandings. This is the design and function of adaptive learning. In this way, adaptive learning itself becomes the process by which new information and understandings emerge, in a sense, building the ‘science of change.’ Adaptive learning also does not guarantee consensus. On the contrary, it is unlikely. However, it has been shown empirically that collective decision-making and action is possible, in spite of contrary values and opinions, where respect and trust have been generated. This again highlights the point that adaptive governance for a sustainable future is more likely related to issues of a social nature than the robustness of available science.