OOS 7-6
Resilience, livelihoods and safeguarding food production under uncertainty
Resilient systems have been characterised as those that have a higher capacity to absorb shocks and stresses; possess the ability to self-organize into flexible and responsive networks for learning, distribution and change, and; have greater capacity for adaptability. While these concepts have been well developed in the literature as theoretical and conceptual frameworks, there are few examples of operationalizing and empirically applying these concepts, particularly for agroecosystems which are among the most complex of social-ecological systems. Tworecent studies from New Zealand are presented:the first, sought to operationalise resilience thinking through the development of a suite of proxies or ‘surrogates’ for resilience, to obtain insight into the relationship between intensification and vulnerability to climate change. Through semi-structured interviews, and surveys with farmers resilience proxies for social, agroecological and economic elements of dairy farm systems were identified, and used to facilitate a comparative analysis across intensive, high-input; low-input, grass-based operations; and organic farms. The second study used an existing model – the landscape stability model – as the basis for identifying quantitative indicators for resilience in dryland, sheep and beef farm systems. Three elements of resilience – resistance, precariousness and latitude – were characterised and provided the foundation for identifying quantitative indicators used to inform decision-making for more sustainable land management.
Results/Conclusions Results of both studies presented reveal insights into the vale – as well as the challenges – of operationalising resilience, or using it as a heuristic or conceptual device. In the dairying case study, the application of the resilience surrogates revealed differences in the resilience and capacity for adaptation for different farm types. The ‘lock in trap' of highly intensive systems, while profitable in the near term, may be less resilient to climate shocks as these are likely to occur in conjunction with changing market and financial risks. Low-input farming systems are less dependent, in particular, on fossil fuels and were associated with higher levels of farmer satisfaction and well-being. In our second study, using a qualitative and quantitative data to characterise thresholds and tipping points in land-management systems, provided a robust – and conceptually sound – basis for applying quantitative metrics. Together, both approaches provide a useful template for cross-sector comparison, and demonstrate that in-depth, robust qualitative assessments of resilience can provide a complement to quantitative metrics. The characterisation of resilient farm-systems also has the potential to contribute to broader sustainability frameworks for agriculture, food systems and land-management.