Vulnerability assessments have often invoked sustainable livelihoods theory to support the quantification of adaptive capacity based on the availability of capital—social, human, physical, natural, and financial. However, the assumption that increased availability of these capitals confers greater adaptive capacity remains largely untested. We quantified the relationship between commonly used capital indicators and an empirical index of adaptive capacity (ACI) in the context of vulnerability of Australian wheat production to climate variability and change. We calculated ACI by comparing actual yields from farm survey data to climate-driven expected yields estimated by a crop model for 12 regions in Australia’s wheat-sheep zone from 1991–2010. We then compiled data for 24 typical indicators used in vulnerability analyses, spanning the five capitals. We analyzed the ACI and used regression techniques to identify related capital indicators. Between regions, mean ACI was not significantly different but variance over time was. ACI was higher in dry years and lower in wet years suggesting that farm adaptive strategies are geared towards mitigating losses rather than capitalizing on opportunity. Only six of the 24 capital indicators were significantly related to adaptive capacity in a way predicted by theory. Another four indicators were significantly related to adaptive capacity but of the opposite sign, countering our theory-driven expectation. We conclude that the deductive, theory-based use of capitals to define adaptive capacity and vulnerability should be more circumspect. Assessments need to be more evidence-based, first testing the relevance and influence of capital metrics on adaptive capacity for the specific system of interest. This will more effectively direct policy and targeting of investment to mitigate agro-climatic vulnerability.

In many agricultural countries, development of rural livelihood through increasing capital is a major regional policy to adapt to climate change. However, the role of livelihood capital in reducing climatic vulnerability is uncertain. This study assesses vulnerability and identifies the effects of common capital indicators on it, using Australian wheat as an example. We calculate exposure (a climate index) and sensitivity (a wheat failure index) to measure vulnerability and classify the resilient and sensitive cases, and express adaptive capacity through financial, human, natural, physical, and social capital indicators for 12 regions in the Australian wheat–sheep production zone from 1991–2010. We identify relationships between 12 indicators of five types of capital and vulnerability with t-tests and six logistic models considering the capital indicator itself, its first-order lag and its square as dependent variables to test the hypothesis that a high level of each capital metric results in low vulnerability. Through differing adaptive capacities between resilient and sensitive groups, we found that only four of the 12 (e.g., the access to finance, cash income level, total crop gross revenues, and family share of farm income) relate to vulnerability, which challenges the hypothesis that increasing capital reduces vulnerability. We conclude that further empirical reexaminations are required to test the relationships between capital measures and vulnerability under the sustainable livelihood framework (SLF).

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Although enhancing resilience is a well-recognized adaptation to climate change, little research has been undertaken on the dynamics of resilience. This occurs because complex relationships exist between adaptive capacity and resilience, and some issues also create challenges related to the construction, operation, and application of resilience. This study identified the dynamics of temporal, spatial changes of resilience found in a sample of wheat–drought resilience in Australia’s wheat–sheep production zone during 1991–2010. I estimated resilience using principal component analysis, mapped resilience and its components, distinguished resilient and sensitive regions, and provided recommendations related to improving resilience. I frame that resilience is composed of social resilience including on- and off-site adaptive capacity as well as biophysical resilience including resistance and absorption. I found that resilience and its components have different temporal trends, spatial shifts and growth ratios in each region during different years, which results from complicated interactions, such as complementation and substitution among its components. In wheat-sheep zones, I recommend that identifying regional bottlenecks, science-policy engagement, and managing resilience components are the priorities for improving resilience.