sustainability-logo

Journal Browser

Journal Browser

Climate Risk Management for Resilient Agricultural Systems

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 7202

Special Issue Editors


E-Mail Website1 Website2
Guest Editor
Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba QLD 4350, Australia
Interests: climate services; climate risk management; sustainable food production systems; water security; agri-ecosystem function; integrated modelling; ecosystem services

E-Mail Website1 Website2
Co-Guest Editor
Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba QLD 4350, Australia
Interests: climate variability; climate services; user engagement; climate risk management; adaptation; resilience; agricultural systems modelling

E-Mail Website
Co-Guest Editor
Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba QLD 4350, Australia and UK Met Office, Exeter UK
Interests: climate variability; climate change; climate services; user engagement; climate risk management; adaptation; resilience

E-Mail Website1 Website2
Co-Guest Editor
Centre for Applied Climate Sciences, University of Southern Queensland, Toowoomba QLD 4350, Australia
Interests: climate risk management; adaptation; resilience; economic valuation; food security; water management; climate finance and insurance

Special Issue Information

All guest editors acknowledge funding received through the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety through the International Climate Initiative (IKI) and the MDC-funded Northern Australian Climate Program.

Dear colleagues,

Climate variability and change pose significant challenges to the resilience of a wide range of social, economic, and ecological systems. Managing associated risks in these systems, while also capitalising on potential benefits, requires adaptive decision-making—including within policy arenas—that is actively informed by scientific knowledge and especially climate sciences. Within agricultural systems, climate information—from observations and monitoring, forecasts on monthly to multi-annual timescales, and multi-decadal projections of climate change—delivered in the form of climate services, can aid preparedness and contribute to positive socio-economic and environmental outcomes. However, the value of climate services based on such information is unlikely to be fully realised unless it is (i) relevant to and actionable by users; and (ii) users also understand when and how to use such information.

This Special Issue (SI) focuses on cross-disciplinary research that applies climate knowledge in order to enhance its value to agricultural climate risk decision-making and support the resilience of agricultural production systems and associated socio-ecological systems (rural landscapes and communities). As such, we invite manuscripts that meet the following criteria:

  1. Focus: Integrated climate services (early warning and management of extreme events, including flash droughts; past and future climate on timescales including months, seasons, years and decades; value of climate services; adaptation decision support; climate insurance; policy; extension models; novel approaches to overcoming adoption barriers) for agricultural climate risk decision-making
  2. Scope: Land-based agricultural (food and fibre) production systems—global

The SI will provide a collection of state-of-the-art research on the application of climate science for climate risk mitigation in agricultural contexts; and, within the context of climate services and agricultural innovation, provide examples of approaches that integrate climate risk into the analysis of agricultural production systems and an evidence base for integrated and adaptive climate risk management policy and practice.

Dr. Kathryn Reardon-Smith
Prof. Dr. Shahbaz Mushtaq
Prof. Dr. Chris Hewitt
Dr. David Cobon
Guest Editors

References:

  1. An-Vo, D.-A., Mushtaq, S., Reardon-Smith, K., Kouadio, L., Attard, S., Cobon, D. and Stone, R. (2019). Value of seasonal forecasting for sugarcane farm irrigation planning. European Journal of Agronomy 104, 37–48. https://doi.org/10.1016/j.eja.2019.01.005
  2. An-Vo, D.-A., Reardon-Smith, K., Mushtaq, S., Cobon, D., Kodur, S. and Stone, R. (2019). Value of seasonal climate forecasts in reducing economic losses for grazing enterprises: Charters Towers case study. The Rangeland Journal 41(3), 165–175. https://doi.org/10.1071/RJ18004
  3. Brasseur, G.P. and Gallardo, L. (2016). Climate services: lessons learned and future prospects. Earth’s Future 4, 79–89. https://doi.org/10.1002/2015EF000338
  4. Capela Lourenço, T., Swart, R., Goosen, H. and Street, R. (2016). The rise of demand-driven climate services. Nature Clim Change 6, 13–14. https://doi.org/10.1038/nclimate2836
  5. Clar, C. and Steurer, R. (2018). Why popular support tools on climate change adaptation have difficulties in reaching local policy-makers: qualitative insights from the UK and Germany. Environ Policy Gov 28, 1–11. https://doi.org/10.1002/eet.1802
  6. Clifford, K.R., Travis, W.R. and Nordgren, L.T (2020). A climate knowledges approach to climate services. Climate Services. https://doi.org/10.1016/j.cliser.2020.100155
  7. Cobon, D.H., Darbyshire, R., Crean, J., Kodur, S., Simpson, M. and Jarvis, C. (2020). Valuing seasonal climate forecasts in the northern Australia beef industry. Weather and Climate Extremes 12, 3–14. https://doi/pdf/10.1175/WCAS-D-19-0018.1
  8. Cobon, D.H., Kouadio, L., Mushtaq, S., Jarvis, C., Carter, J., Stone, G. and Davis, P. (2019). Evaluating the shifts in rainfall and pasture-growth variabilities across the pastoral zone of Australia during 1910–2010. Crop and Pasture Science 70, 634–647. https://doi.org/10.1071/CP18482
  9. Cowan, T., Wheeler, M.C., Alves, O., Narsey, S., de Burgh-Day, C., Griffiths, M., Jarvis, C. and Cobon, D. (2019). Forecasting the extreme rainfall, low temperatures, and strong winds associated with the northern Queensland floods of February 2019. Weather and Climate Extremes 26, 100232. https://doi.org/10.1016/j.wace.2019.100232
  10. Dinku, T., Block, P., Sharoff, J. et al. (2014). Bridging critical gaps in climate services and applications in Africa. Earth Perspectives 1, 15. https://doi.org/10.1186/2194-6434-1-15
  11. Giuliani, G., Nativi, S., Obregon, A., Beniston, M. and Lehmann, A. (2017). Spatially enabling the Global Framework for Climate Services: Reviewing geospatial solutions to efficiently share and integrate climate data & information. Climate Services 8, 44–58. https://doi.org/10.1016/j.cliser.2017.08.003
  12. Golding, N., Hewitt, C., Zhang, P., Bett, P., Fang, X., Hu, H. and Nobert, S. (2017). Improving user engagement and uptake of climate services in China. Clim Serv 5, 39–45. https://doi.org/10.1016/j.cliser.2017.03.004
  13. Haworth, B.T., Biggs, E., Duncan, J., Wales, N., Boruff, B. and Bruce, E. (2018). Geographic information and communication technologies for supporting smallholder agriculture and climate resilience. Climate 6, 97. https://doi.org/10.3390/cli6040097
  14. Hewitt, C., Mason, S. and Walland, D. (2012). The Global Framework for Climate Services. Nature Clim Change 2, 831–832. https://doi.org/10.1038/nclimate1745
  15. Hewitt, C., Stone, R. and Tait, A. (2017). Improving the use of climate information in decision-making. Nature Clim Change 7, 614–616. https://doi.org/10.1038/nclimate3378
  16. Hewitt, C.D., Allis, E., Mason, S.J., Muth, M., Pulwarty, R., Shumake-Guillemot, J., Bucher, A., Brunet, M., Fischer, A.M., Hama, A.M., Kolli, R.K., Lucio, F., Ndiaye, O. and Tapia, B. (2020). Making society climate-resilient: international progress under the Global Framework for Climate Services. Bull. Amer. Meteor. Soc. E237-E252. https://doi.org/10.1175/bams-d-18-0211.1
  17. Hoffmann, E., Rupp, J. and Sander, K. (2020). What do users expect from climate adaptation services? Developing an information platform based on user surveys. Handbook of Climate Services (pp. 105–113). https://doi.org/10.1007/978-3-030-36875-3_7
  18. Jagannathan, K., Jones, A.D. and Kerr, A.C. (in press). Implications of climate model selection for projections of decision-relevant metrics: A case study of chill hours in California. Climate Services Article 100154
  19. Kath, J., Mushtaq, S., Henry, R., Kouadio, L., Adeyinka, A., Stone. R.C. and Marcussen, T. (2019). Efficiency of rainfall index insurance for Australia’s wheat regions. Climate Risk Management 24, 13–29. https://doi.org/10.1016/j.crm.2019.04.002
  20. Lemos, M., Kirchhoff, C. and Ramprasad, V. (2012). Narrowing the climate information usability gap. Nature Climate Change 2, 789–794. https://doi.org/10.1038/nclimate1614
  21. Marshall, N.A., Crimp, S., Curnock, M., Greenhill, M., Kuehne, G., Leviston, Z. and Ouzman, J. (2016). Some primary producers are more likely to transform their agricultural practices in response to climate change than others. Agriculture, Ecosystems & Environment 222, 38–47. https://doi.org/10.1016/j.agee.2016.02.004
  22. Mushtaq, S., Kath, J., Stone, R., Henry, R., Laderach, P., Reardon-Smith, K., Cobon, D., Marcussen, T., Cliffe, N., Kristiansen, P. and Pischke, F. (2020). Creating positive synergies between risk management and transfer to accelerate food systems climate resilience. Climatic Change https://doi.org/10.1007/s10584-020-02679-5
  23. Mushtaq, S. (2016). Economic and policy implications of relocation of agricultural production systems under changing climate: example of Australian rice industry. Land Use Policy 52, 277–286. https://doi.org/10.1016/j.landusepol.2015.12.029
  24. Nguyen, H., Wheeler, M.C., Otkin, J.A., Cowan, T., Frost, A. and Stone, R. (2019). Using the evaporative stress index to monitor flash drought in Australia. Environmental Research Letters 14, 6. https://doi.org/10.1088/1748-9326/ab2103
  25. Nguyen, T., Kath, J., Mushtaq, S., Cobon, D., Stone, G. and Stone, R. (2020). Integrating climate information and spatial diversification increases grazing profitability and decreases risk. Agronomy for Sustainable Development 40, 4. https://doi.org/10.1007/s13593-020-0605-z
  26. Pendergrass, A.G., Meehl, G.A., Pulwarty, R. et al. (2020). Flash droughts present a new challenge for subseasonal-to-seasonal prediction. Nature Climate Change 10, 191–199. https://doi.org/10.1038/s41558-020-0709-0
  27. Prasada, D.V.P. (2020). Climate-Indexed Insurance as a Climate Service to Drought-Prone Farmers: Evidence from a Discrete Choice Experiment in Sri Lanka. Handbook of Climate Services (pp.423–445). https://doi.org/10.1007/978-3-030-36875-3_21
  28. Sharmila, S. and Hendon, H. (2020). Mechanisms for multiyear variations of northern Australia wet-season rainfall. Nature Scientific Report 10, 5086. https://doi.org/10.1038/s41598-020-61482-5
  29. Shinbrot, X.A., Jones, K.W., Rivera-Castañeda, A. et al. (2019). Smallholder farmer adoption of climate-related adaptation strategies: the importance of vulnerability context, livelihood assets, and climate perceptions. Environmental Management 63, 583–595. https://doi.org/10.1007/s00267-019-01152-z
  30. Singh, C., Daron, J., Bazaz, A., Ziervogel, G., Spear, D., Krishnaswamy, J., Zaroug, M. & Kituyi, E. (2018). The utility of weather and climate information for adaptation decision-making: current uses and future prospects in Africa and India. Climate and Development 10(5), 389–405. https://doi.org/10.1080/17565529.2017.1318744
  31. Smith, D.M., Eade, R., Scaife, A.A. et al. (2019). Robust skill of decadal climate predictions. npj Clim Atmos Sci 2, 13. https://doi.org/10.1038/s41612-019-0071-y
  32. Stone, R. and Meinke, H. (2006). Weather, climate, and farmers: an overview. Meteorological Applications 13(S1), 7–20. https://doi.org/10.1017/S1350482706002519
  33. Tall, A., Hansen, J., Jay, A., Campbell, B., Kinyangi, J., Aggarwal, P.K. and Zougmoré, R. (2014). Scaling up climate services for farmers: Mission Possible. Learning from good practice in Africa and South Asia. CCAFS Report No. 13. Copenhagen, Denmark: CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS). https://hdl.handle.net/10568/42445
  34. Tesfaye, A., Hansen, J., Kassie, G.T., Radeny, M. and Solomon, D. (2019). Estimating the economic value of climate services for strengthening resilience of smallholder farmers to climate risks in Ethiopia: A choice experiment approach. Ecological Economics 162, 157–168. https://doi.org/10.1016/j.ecolecon.2019.04.019
  35. Tomlinson, J. and Rhiney, K. (2018). Assessing the role of farmer field schools in promoting pro-adaptive behaviour towards climate change among Jamaican farmers. J Environ Stud Sci 8, 86–98. https://doi.org/10.1007/s13412-017-0461-6
  36. Trinh, T.Q., Rañola, R.F., Camacho, L.D. and Simelton, E. (2018). Determinants of farmers’ adaptation to climate change in agricultural production in the central region of Vietnam. Land Use Policy 70, 224–231. https://doi.org/10.1016/j.landusepol.2017.10.023
  37. Vaughan, C. and Dessai, S. (2014). Climate services for society: origins, institutional arrangements, and design elements for an evaluation framework. WIRES Climate Change https://onlinelibrary.wiley.com/doi/full/10.1002/wcc.290
  38. Vaughan, C., Dessai, S. and Hewitt, C. (2018). Surveying climate services: what can we learn from a bird’s-eye view? Weather Climate Soc., 10, 373–395. https://doi.org/10.1175/WCAS-D-17-0030.1
  39. Vedeld, T., Mathur, M. and Bharti, N. (2019). How can co-creation improve the engagement of farmers in weather and climate services (WCS) in India. Climate Services 15, 100103. https://doi.org/10.1016/j.cliser.2019.100103

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climate risk management
  • climate services
  • sustainable food production systems
  • rural livelihoods
  • climate variability
  • climate change
  • climate finance
  • economic valuation
  • climate insurance
  • policy
  • adaptation
  • resilience

Published Papers (2 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

22 pages, 2024 KiB  
Article
Assessing Livelihood Vulnerability of Minority Ethnic Groups to Climate Change: A Case Study from the Northwest Mountainous Regions of Vietnam
by Van Thanh Tran, Duc-Anh An-Vo, Geoff Cockfield and Shahbaz Mushtaq
Sustainability 2021, 13(13), 7106; https://doi.org/10.3390/su13137106 - 24 Jun 2021
Cited by 23 | Viewed by 4135
Abstract
Climate variability, climate change, and extreme events can compound the vulnerability of people heavily reliant on agriculture. Those with intersecting disadvantages, such as women, the poor, and ethnic minority groups, may be particularly affected. Understanding and assessing diverse vulnerabilities, especially those related to [...] Read more.
Climate variability, climate change, and extreme events can compound the vulnerability of people heavily reliant on agriculture. Those with intersecting disadvantages, such as women, the poor, and ethnic minority groups, may be particularly affected. Understanding and assessing diverse vulnerabilities, especially those related to ethnicity, are therefore potentially important to the development of policies and programs aimed at enabling adaptation in such groups. This study uses a livelihood vulnerability index (LVI) method, along with qualitative data analysis, to compare the vulnerability of different smallholder farmers in Son La province, one of the poorest provinces in Vietnam. Data were collected from 240 households, representing four minority ethnic groups. The results indicated that household vulnerability is influenced by factors such as income diversity, debt, organizational membership, support from and awareness by local authorities, access to health services, water resources, and location. Results revealed that two of the ethnic groups’ households were, on average, more vulnerable, particularly regarding livelihood strategies, health, water, housing and productive land, and social network items when compared to the other two ethnic groups. The study shows the need for targeted interventions to reduce the vulnerability of these and similarly placed small ethnic communities. Full article
(This article belongs to the Special Issue Climate Risk Management for Resilient Agricultural Systems)
Show Figures

Figure 1

23 pages, 4402 KiB  
Article
Contrasting Influences of Seasonal and Intra-Seasonal Hydroclimatic Variabilities on the Irrigated Rice Paddies of Northern Peninsular Malaysia for Weather Index Insurance Design
by Zed Zulkafli, Farrah Melissa Muharam, Nurfarhana Raffar, Amirparsa Jajarmizadeh, Mukhtar Jibril Abdi, Balqis Mohamed Rehan and Khairudin Nurulhuda
Sustainability 2021, 13(9), 5207; https://doi.org/10.3390/su13095207 - 7 May 2021
Cited by 3 | Viewed by 2361
Abstract
Good index selection is key to minimising basis risk in weather index insurance design. However, interannual, seasonal, and intra-seasonal hydroclimatic variabilities pose challenges in identifying robust proxies for crop losses. In this study, we systematically investigated 574 hydroclimatic indices for their relationships with [...] Read more.
Good index selection is key to minimising basis risk in weather index insurance design. However, interannual, seasonal, and intra-seasonal hydroclimatic variabilities pose challenges in identifying robust proxies for crop losses. In this study, we systematically investigated 574 hydroclimatic indices for their relationships with yield in Malaysia’s irrigated double planting system, using the Muda rice granary as a case study. The responses of seasonal rice yields to seasonal and monthly averages and to extreme rainfall, temperature, and streamflow statistics from 16 years’ observations were examined by using correlation analysis and linear regression. We found that the minimum temperature during the crop flowering to the maturity phase governed yield in the drier off-season (season 1, March to July, Pearson correlation, r = +0.87; coefficient of determination, R2 = 74%). In contrast, the average streamflow during the crop maturity phase regulated yield in the main planting season (season 2, September to January, r = +0.82, R2 = 67%). During the respective periods, these indices were at their lowest in the seasons. Based on these findings, we recommend temperature- and water-supply-based indices as the foundations for developing insurance contracts for the rice system in northern Peninsular Malaysia. Full article
(This article belongs to the Special Issue Climate Risk Management for Resilient Agricultural Systems)
Show Figures

Figure 1

Back to TopTop