sustainable agricultural systems

1. sustainable agricultural systems Actionable climate knowledge – from analysis to synthesis Experiences from 20 years of applied climate risk research in Australia Holger Meinke, Rohan Nelson, Roger Stone, Selvaraju, Aline de Holanda, Walter Baethgen

2. Why focus on case studies from Australia? • has long been at the forefront of applied climate research • often regarded (rightly or wrongly) as a role model for the creation and maintenance of ‘actionable climate knowledge’ • has one of the most variable climates in the world

3. Why focus on case studies from Australia? • has strong ENSO impact and vulnerable sectors with considerable scope to improve risk management • climate change already a reality and not just a scenario • public policy focus on self-reliance, resilience and societal benefits • involves many agencies and many stakeholders (farmers, agribusiness, policy makers)

4. Climate knowledge vs climate forecasting • Climate knowledge is more that ENSO and more than just forecasting. • Climate knowledge is the intelligent use of climate information. This includes knowledge about climate variability, climate change AND climate forecasting used such that it enhances resilience by increasing profits and reducing economic/environmental risks.

5. sustainable agricultural systems Risk management • The systematic process of identifying, analysing and responding to risk. It includes maximising the probability and consequences of positive and adverse events. (Guide to the Project Management Body of Knowledge) • ‘It is our competitive advantage that we show courage after carefully deliberating our actions. Others, in contrast, are courageous from ignorance but hesitant upon reflection’. (Pericles’ Funeral Oration, 431 AD; Thucydides 2, 40, 3)

6. sustainable agricultural systems Risks arise from variability Australian farmers are excellent risk managers. They run successful businesses within the world’s most variable climate and without subsidies. …it seems that the 21st century has a good chance of becoming ‘the climate century’, a century in which climate-related concerns will occupy significant attention of the next generations of policy makers… Mickey Glantz, 2003

7. sustainable agricultural systems Sources of variability • Temporal and spatial weather (hail, frost); climate (at a range of temporal scales); soils (at a range of spatial scales); economic conditions (inputs, commodity prices); management • External and internal either beyond manager’s control or consequence of management

8. sustainable agricultural systems

9. Three important steps to create climate knowledge • understanding rainfall (climate) variability (physical measure) • understanding production variability (bio-physical measure) • understanding farm income variability (economic measure)

10. The first step: understanding rainfall JJA rainfall for Dalby, Queensland

11. The first step: understanding rainfall JJA rainfall for Dalby, Queensland

12. How good is the forecast?Skill vs Discriminatory Ability S quantifies agreement between observed and predicted values DA represents the additional knowledge about future states arising from the forecast system over and above the total variability of the prognostic variable

14. The first step: understanding rainfall Discriminatory Ability of the 5-phase SOI forecast system as quantified by KW p-values (KW is a measure of shift in distributions)

15. sustainable agricultural systems The second step: understanding production impacts Simulation models for better risk management • how do they work? • are based on our component knowledge of science • integrate many sources of variability • account for management options • what can they do? • benchmark, assess and quantify potential, attainable, economically optimal and achieved yield or income • overcome issues related to moral hazards and ground truthing

16. sustainable agricultural systems WhopperCropper for on-farm decision making WhopperCropper training and distribution is now through Nutrient Management Systems. www.apsru.gov.au/apsru/products/whopper

17. Wheat, Dalby, 150mm, 2/3 full, 15 June sowing, April/May SOI phase 5 4 3 2 1 0 Negative SOI Phase Positive SOI Phase Gross Margin (100$ per ha) 0N 25N 50N 100N0N 25N 50N 100N Applied Nitrogen and SOI Phase sustainable agricultural systems SOI effect on gross margins

18. Wheat, Dalby, 150mm, 2/3 full, 15 June sowing, April/May SOI phase 5 4 3 2 1 0 Negative SOI Phase Positive SOI Phase Gross Margin (100$ per ha) 0N 25N 50N 100N0N 25N 50N 100N Applied Nitrogen and SOI Phase sustainable agricultural systems SOI effect on gross margins

19. sustainable agricultural systems Using field/farm scale models • Tactical risk management (which crop to grow when and how) • Optimising resource use (how much water / nitrogen to use when and where) • Estimating crop value (benchmarking, forward selling, insurance) • Determine enterprise mix (rotation planning)

20. sustainable agricultural systems Regional Commodity Models (RCM)

21. Predicted sorghum shire yield for the 2004/2005 season, ranked relative to all years (1901-2003)

22. July 2001 July 2002 (a) (b) Probabilities of exceeding long-term median wheat yields for every wheat producing shire (= district) in Australia issued in July 2001 and July 2002, respectively.

23. Chance of exceeding median pasture growth for NSW, April to June 2005

24. sustainable agricultural systems Using regional models • Marketing decisions (hedging, contract negotiations, logistics) • Value chain issues (quality fluctuations, export vs domestic use, milling operations) • Anticipating resource use (water allocations, nitrogen or seed demand, storage capacity)

25. ? ? Simulated Wheat Yield 1890+ 1.5 5-year running mean - Wentworth, 1884 to 1998 1.0 0.5 0.0 Standard Deviations from the mean -0.5 -1.0 -1.5 1901 1908 1915 1922 1950 1957 1992 1985 1894 1929 1936 1943 1964 1971 1978 sustainable agricultural systems Simulated Wheat Yield 1950+ When is a drought a drought?

26. sustainable agricultural systems Using models for public and private policy decisions • When is a drought a drought (Exceptional circumstances, drought relief, structural adjustments etc). • Investment / disinvestment (portfolio balance; cotton, grain or pastures) • Structural adjustment (diversification, industry mix eg. sugar industry)

27. The policy relevance gap • no policy mechanisms for influencing rainfall (step 1), • few policy options to affect crop or pasture yields(step 2), • but strong community demand for policies to anticipate and moderate the effects of climate variability on farm incomes (step 3).

28. The third step ( ‘the big stumble’): making science relevant Drought “The defining feature of drought is its impact on human activity – it is essentially socially constructed. It is about the mismatch between the availability of water and the uses to which human communities wish to put it.” Linda Courtenay Botterill 2003 Exposure to risk does not equal vulnerability

29. Climate is often ‘important but not urgent’ • Many problems are the result of applying narrow, specialised knowledge to complex systems • Modern science has been described as ‘islands of understanding in oceans of ignorance’ • Scientists and practitioners need to work together to produce trustworthy knowledge that combines scientific excellence with social relevance Hayman (2001); Lowe (2001)

30. The multiple dimensions of vulnerability Human Carney, 1998; Ellis, 2000 Financial Social Exposure to risk does not equal vulnerability Physical Natural

31. 10% (most extreme) 10 to 25% (extreme) below 25% (least extreme) Vulnerability of Australian agriculture: Exposure vs Coping Capacity (Nelson et al. 2005)

32. Vulnerability includes • exposure to climate risk • exposure to other sources of risk • capacity of rural households to cope with risk

33. Why is coping capacity so important? • Farming systems have evolved to effectively manage the risks of farming in a highly variable climates – without science intervention. • While climate synthesis tools might have contributed to the development of more effective on-farm risk management, there is little or no connection to policy.

34. Why is coping capacity so important? • Greater diversity of income sources facilitates substitution between activities and assets in response to shocks such as drought. • Policies that enhance diversity of farm income include investment in production, transport and marketing infrastructure, education and training, regional development, and policies that impact on the cost and availability of rural credit.

35. Why is coping capacity so important? • We need to distinguish the effects of climate from other sources of income risk. • Without a capacity to distinguish between sources of income variability, policies directed toward reducing the impact of climate risk may inadvertently reduce incentives to better manage other sources of risk.

36. A tool for bridging the policy relevance gap • The Agricultural Farm Income Risk Model (AgFIRM) combines regional, biophysical models of Australian crop and pasture yield with an econometric model of farm incomes. • AgFIRM simulates regional impacts of climate variability on farm incomes.

37. Forecasting farm incomesProbability of exceeding median farm income 2002/3 2001/2 2002-03 2001-02 1982/3 1982-83 (Nelson et al. 2005)

38. 2002-03 2001-02 1982-83 1982-83 Better drought assistanceProbability of 1-in-20 worst farm income (Nelson et al. 2005)

39. Tools for bridging the policy relevance gap • Policies aimed at increasing the capacity of rural communities to cope with climate risk need to be informed by measures of the multiple socio-economic dimensions of resilience. • Current emphasis on rainfall and production variability only informs policy makers of the exposure to drought, for which there is no policy solution.

40. Public versus private policy development • Risk managers must decide which risks should be retained and managed adaptively and which risks should be shared through risk sharing contracts. • It requires financial markets to device and price risk sharing contracts in a manner that create benefits for all stakeholders involved, a process that has only just begun in Australia.

41. Farm Reinsurer Weather/ climate derivatives Community Insurer Financial Derivatives Business sustainable agricultural systems Real options, insurance and other financial products shared risks retained risks courtesy of Greg Hertzler, Uni of WA

42. Climate knowledge or seasonal rainfall forecasting? • Applied climate knowledge is generated by synthesising scientific insights across disciplinary boundaries, often through the use of models and always jointly with stakeholders. • Climate risk management in rural industries is not solely the responsibility of farmers. Likewise, it is not the role of Governments to absorb these risks. • Risk managers, policy makers and private sector companies all play important roles in this process.

43. The case for institutional realignment • Rainfall and production are not what policy makers are interested in. They are interested in the social and economic wellbeing of rural communities. • Analytical support for drought policy that focuses on exposure to climate risk is largely irrelevant  climate variability cannot be altered by policy in the short term.

44. Failures and risks • The artificial division of climate variability and climate change gets in the way of better decision making. • The focus of the climate change community on mitigation bears the danger of overlooking some obvious and immediate adaptation strategies that should from part of any sound climate risk management approach.

45. Failures and risks • A problem rather than a disciplinary focus will require some scientists to stop doing what comes naturally (addressing simple issues such as rainfall variability, with increasingly complex analytical tools). • Instead, they need to take a broader perspective to addresses not only exposure to risk, but also the people’s ability to cope and the system’s ability to bounce back after times of stress (resilience)

46. Other impediments • institutional and disciplinary fragmentation prevails • difficult to ‘gain simplicity on the far side of complexity’ • R&D funding agencies reluctant to resource genuinely multi-disciplinary, cross institutional projects

47. Some suggestions • public / private partnership models need to be explored further in order to ‘mainstream’ climate risk management • public / private policy concerns need to be explicitly addressed • communicate climate risk management knowledge through functional, existing communication networks of farmers and other landholders

48. First key lesson from several decades of experience • Climate knowledge needs to deliver true societal benefits. • We need to expand the systems boundaries and fully explore the scientific and socio-economic tensions and interactions - the system is bigger than most of us thought. • We need to include the socio-economic dimensions important to rural communities and policy makers, but without abandoning science. • We need to achieve true integration of disciplinary knowledge, rather than focusing on certain aspects of the system at the exclusion of others.

49. Second key lesson from several decades of experience • True integration without abandoning science takes real resourcing. • The capacity to think and act beyond disciplinary boundaries is rare and difficult to nurture in the established institutional context. • Existing institutional arrangements often act as a disincentive to true integration. • Strong leadership is required to induce cultural change in established institutional arrangements.