Tuesday 6
Social-ecological resilience indicators: a participatory tool to measure landscape resilience
Nadia Bergamini, Dunja Mijatovic, Pablo Eyzaguirre
› 11:35 - 12:30 (55min)
› JOFFRE B
Incorporating Indicators of the Resilience of Water Bodies in an Urban Development Decision Support System
Jonathan Moores  1, *@  , Christopher Batstone  2@  , Malcolm Green  1@  , Annette Semadeni-Davies  1@  , Sharleen Harper  1@  
1 : National Institute of Water and Atmospheric Research Ltd  (NIWA)  -  Website
Private Bag 99940 Auckland 1149 -  Nouvelle-Zélande
2 : Cawthron Institute  -  Website
Private Bag 2, Nelson 7042 -  Nouvelle-Zélande
* : Corresponding author

Throughout the world cities have been founded next to streams, rivers and harbours, but urban development has resulted in the degradation of these water bodies. Contaminants discharged in urban stormwater runoff affect water quality and ecosystem health, with consequential impacts on the ways in which water bodies are used and valued by urban communities. This paper describes research in New Zealand to develop indicators of the resilience of urban water bodies to the effects of development. The context is a multi-disciplinary project to develop a decision support system (DSS) for assessing the impacts of alternative urban development scenarios on ecosystem services available from freshwater and estuarine waterbodies.

The research conceptualizes urban development and stormwater management as occurring within the setting of an ‘urban aquatic social-ecological system.' This (sub-)system is defined as comprising “those elements of an urban social-ecological system which influence the generation and consequences of stormwater-related changes to the provision of aquatic ecosystem services.” The system includes both natural elements, being the receiving water bodies that provide ecosystem services, and societal elements, which can be further divided into built and non-built elements. Built elements include the urban surfaces and infrastructure that generate, convey, control and deliver stormwater. Non-built elements include the governance frameworks and social capital that influence the form of urban development and stormwater management.

A pilot version of the DSS allows users to compare alternative future urban development scenarios by varying inputs representing land use change and stormwater management approaches. These inputs drive a set of models which predict changes to biophysical attributes such as water and sediment quality and indicators of ecosystem health in rivers and estuaries. These attributes are in turn used to assess changes in a range of supporting, provisioning, regulating and cultural ecosystem services, reported as indicators of environmental, economic, social and cultural well-being.

The further development of the DSS involves extending the existing reporting framework to incorporate indicators of resilience. Reflecting the restrictions of the system definition, the research is focusing on indicators of specified, rather than general, resilience. Resilience is defined as “the capacity of the natural and societal elements of an urban aquatic social-ecological system to provide the same, similar or a better level of aquatic ecosystem services in the face of the stormwater-related effects of urban development.” Accordingly, two sets of indicators are required: (1) those which reflect the capacity of natural elements, i.e. receiving water bodies, to provide ecosystem services; and (2), those which reflect the capacity of society to manage, adapt and potentially transform stormwater management to support or substitute for the provision of ecosystem services. Indicators of natural capacity are assessed through the trajectories of key biophysical variables, such as water and sediment quality, and their proximity to critical thresholds. Indicators of societal capacity are assessed through criteria such as diversity, redundancy and adaptability in stormwater management infrastructure and institutions. The current focus of the research is to develop the methods by which this resilience indicator framework can be operationalized within the DSS.


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