Project Framework

The Climate Vulnerability Assessment was designed to help primary industries in NSW understand the risks and opportunities associated with climate change on economically significant commodities over the near-to-medium term future (2050). The Climate Vulnerability Assessment was undertaken to understand how climate suitability will change for a range of specific commodities and biosecurity risks under climate change.

To do this we need to understand the exposure of the assessed item to the climate and then understand the sensitivity of it to different climate variables. For example, cherry is sensitive to winter chill and hot weather close to harvest. This relationship between exposure (being exposed to less chill in winter) and sensitivity (less chill reduces the quantity of fruit the following summer) allows us to understand the potential impact of climate change on cherries. There are some adaptations available to cherry growers such as installing covers and using varieties of cherry that do not require as much winter chill to produce fruit. If you apply adaptations but they don't resolve all the impacts of climate change, then that remaining impact is the vulnerability to climate change as illustrated below.

The guiding principles for the Climate Vulnerability Assessment are to employ a consistent approach across industries to allow comparability, ensure a state-wide focus, and enable strategic industry planning and inform government policy-making. It combines historical climate data and future climate projections with expert knowledge drawn from research literature, Department of Primary Industries and Regional Development staff, and industry experts in a unique approach to this problem.

To ensure consistency and comparability across the assessments, a comprehensive and flexible framework (Multi-Criteria Analysis (MCA) Model) was developed to assess the climate suitability of different commodities and biosecurity risks in NSW, providing valuable insights on their response to climate change. This framework provides quantitative, qualitative, and geospatial information about the climate suitability of plants, animals, and biosecurity risks assessed. The MCA model was then combined with historical climate data to produce a climate suitability map as illustrated below.

Climate projections used in this assessment

The Climate Vulnerability Assessment used the CSIRO Climate Change in Australia: Application Ready Data. The dataset was:

• comprised of 8 CMIP5 global climate models (5 global climate models were used for marine fisheries)
• run with 2 future emissions scenarios - an intermediate scenario (RCP4.5) and a high emissions scenario (RCP8.5)
• downscaled to approximately a 5km² (0.05 degrees) which is appropriate for regional assessment processes

Importantly the assessments all used the same timeframes:

• Historical baseline period: 1981-2010 with a mid-point of 1995
• Future projection period: 2036-2065 with a mid-point of 2050

The framework developed for the Climate Vulnerability Assessments provides a rigorous, flexible and repeatable process for undertaking the assessments. The diagram below contains a summary of the steps required for the assessment.

Expert knowledge was an essential component of the Climate Vulnerability Assessment as indicated by the green steps in the figure above. The literature review step identified that there were large gaps in the published knowledge on all commodities and biosecurity risks that we wished to assess. Filling those knowledge gaps required for the formation of expert focus groups supported by DPIRD experts. These groups would meet at critical phases of the project specifically and agree on the specific information that needed to be included in the multi-criteria analysis models used to understand the growing requirements of the commodities and biosecurity threats we were assessing.

For more information on the methodology and data used in the Climate Vulnerability Assessment, please refer to the Climate Vulnerability Assessment Methodology Report.