AbstractChange in access to natural resources is occurring globally due to a changing environment, government policy, market conditions and other factors. This presents a risk of downturn to natural resource-dependent industries and of negative livelihood impacts for the people who depend on them. Policy response to mitigate livelihood impacts should target those most vulnerable to harm so it is important to identify who is most vulnerable and why.
It is widely recognised that household incomes are a key pathway by which people are vulnerable to the impacts of natural resource change, yet little work has examined vulnerability with exposure defined in this way. Further, vulnerability levels vary within communities, yet most vulnerability assessments still examine average characteristics across communities, hiding the most vulnerable people.
The objective of this study was: to develop an economic perspective on social vulnerability to regional industry downturn in natural resource-dependent industries and to operationalise the concept as an input for designing evidence based livelihood impact mitigation policy. This overall objective was explored through three specific research questions:
RQ1. How can the nature of social vulnerability to industry downturn in natural resource-dependent industries be described from an economic perspective?
RQ2. How is this concept of vulnerability most appropriately operationalised for use in vulnerability assessment?
RQ3. What are the implications of operationalising this concept for designing livelihood impact mitigation policy for regional industry downturn?
Two journal papers were developed and submitted, addressing the research questions. The first developed a concept of social vulnerability to regional industry downturn in natural resource-dependent industries from an economic perspective, operationalised it with an index and applied the index to a case study survey of households in a forest-dependent industry in Australia. The second contextualised the results from the first to better describe the severity of the vulnerability being assessed by comparing it to the vulnerability of other households in the region to downturn in other industries. As the requisite data for comparison did not exist, a fitness-based synthesis approach to spatial microsimulation was applied to generate a synthetic population for this purpose. The findings were:
RQ1 – it is useful to conceptualise exposure to industry downturn as the proportion of household income earned in that industry using an exposure, sensitivity and adaptive capacity concept of vulnerability, but this should be described at the household scale while incorporating information from individual and community scales.
RQ2 – it is appropriate to operationalise the concept with a household index where multiple scales of indicators map onto its components, the relationships between components are represented in the index calculation and results are contextualised by comparing to other vulnerabilities.
RQ3 – understanding who is most vulnerable and the differing levels of exposure, sensitivity and adaptive capacity associated with their vulnerability allows targeting of support at those who need it most as well as prioritising of the most appropriate types of support, making policy more effective and efficient.
|Date of Award||2022|
|Supervisor||Jacki Schirmer (Supervisor) & Robert Tanton (Supervisor)|