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Impacts of climate change and extreme weather on food supply chains cascade across sectors and regions in Australia

Abstract

Disasters resulting from climate change and extreme weather events adversely impact crop and livestock production. While the direct impacts of these events on productivity are generally well known, the indirect supply-chain repercussions (spillovers) are still unclear. Here, applying an integrated modelling framework that considers economic and physical factors, we estimate spillovers in terms of social impacts (for example, loss of job and income) and health impacts (for example, nutrient availability and diet quality) resulting from disruptions in food supply chains, which cascade across regions and sectors. Our results demonstrate that post-disaster impacts are wide-ranging and diverse owing to the interconnected nature of supply chains. We find that fruit, vegetable and livestock sectors are the most affected, with effects flowing on to other non-food production sectors such as transport services. The ability to cope with disasters is determined by socio-demographic characteristics, with communities in rural areas being most affected.

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Fig. 1: Consumption losses in terms of regional and sectoral spillovers across 15 broad food and non-food categories for climate change and extreme weather events.
Fig. 2: Socio-demographic dimensions as well as impacts of climate change and extreme weather events across NSW: socio-demographic dimensions (top row), the effect on jobs and economy (middle row) and nutrient availability (bottom row).
Fig. 3: Reduction in macronutrient and energy availability, jobs and value-added across 15 broad categories, resulting from extreme heatwaves (scenario ‘Extreme_weather_heatwaves’).
Fig. 4: Reduction in macronutrient and energy availability, jobs and value-added across 15 broad categories, resulting from climate change (‘HighAdapt2030’ in Supplementary Information 5).
Fig. 5: Consumption losses in terms of diet quality across broad ADG groups for all scenarios.
Fig. 6: Vulnerability to climate change and extreme weather events, for four selected SA2 regions in NSW, Australia.

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Data availability

Data used in this study are stored in the Australian IELab (ielab.info), and are accessible from the authors upon request. Source data are provided with this paper.

Code availability

Codes used in this study are stored in the Australian IELab (ielab.info), and are accessible from the authors upon request.

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Acknowledgements

This work was financially supported by the NSW Department of Planning, Industry and Environment via the Human Health and Social Impact Node, Australian Research Council (projects DP0985522, DP130101293, DP190102277, LE160100066, DP200102585, DP200103005, LP200100311 and IH190100009), the National eResearch Collaboration Tools and Resources project, through the Industrial Ecology Virtual Laboratory infrastructure VL 201 and the University of Sydney SOAR prize. We thank N. Herold for providing expert advice on design of scenarios for assessing the impact of climate change and extreme weather events, J. Pardoe for her ongoing advice in workshops and on draft versions of this report, L. Merrington for his input in classification of food sectors into ADG groups, S. Juraszek for expertly managing the computational requirements, and C. Jarabak and C. Mora for help with collecting information.

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M. Lenzen, A.M., K.B. and S.B. conceptualized and planned the paper; A.M., M. Lenzen, K.B., N.L., J.F., A.L., S.B., A.G. and M. Li, coordinated the construction of the gamma matrix and data collection; M. Li, M. Lenzen and A.M. processed data and produced figures; A.M., M. Lenzen, N.L., J.F., A.L., D.R., S.B., M.P., M. Li and K.B. wrote the paper.

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Correspondence to Arunima Malik.

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Nature Food thanks Cheikh Mbow, Ray Taylor and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Malik, A., Li, M., Lenzen, M. et al. Impacts of climate change and extreme weather on food supply chains cascade across sectors and regions in Australia. Nat Food 3, 631–643 (2022). https://doi.org/10.1038/s43016-022-00570-3

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