Risk management strategies using seasonal climate forecasting in irrigated cotton production: a tale of stochastic dominance.

Decision-making in agriculture is carried out in an uncertain environment with farmers often seeking information to reduce risk. As a result of the extreme variability of rainfall and stream-flows in north-eastern Australia, water supplies for irrigated agriculture are a limiting factor and a source of risk. The present study examined the use of seasonal climate forecasting (SCF) when calculating planting areas for irrigated cotton in the northern Murray Darling Basin. Results show that minimising risk by adjusting plant areas in response to SCF can lead to significant gains in gross margin returns. However, how farmers respond to SCF is dependent on several other factors including irrigators’ attitude towards risk.

Climate information needs of Gascoyne-Murchison pastoralists: a representative study of the Western Australian grazing industry

The Gascoyne-Murchison region of Western Australia experiences an arid to semi-arid climate with a highly variable temporal and spatial rainfall distribution. The region has around 39.2 million hectares available for pastoral lease and supports predominantly catle and sheep grazing leases. In recent years a number of climate forecasting systems have been available offering rainfall probabilities with different lead times and a forecast period; however, the extent to which these systems are capable of fulfilling the requirements of the local pastoralists is still ambiguous. Issues can range from ensuring forecasts are issued with sufficient lead time to enable key planning or decisions to be revoked or altered, to ensuring forecast language is simple and clear, to negate possible misunderstandings in interpretation. A climate research project sought to provide an objective method to determine which available forecasting systems had the greatest forecasting skill at times of the year relevant to local property management. To aid this climate research project, the study reported here was undertaken with an overall objective of exploring local pastoralists' climate information needs. We also explored how well they understand common climate forecast terms such as 'mean', median' and 'probability', and how they interpret and apply forecast information to decisions. A stratified, proportional random sampling was used for the purpose of deriving the representative sample based on rainfall-enterprise combinations. In order to provide more time for decision-making than existing operational forecasts that are issued with zero lead time, pastoralists requested that forecasts be issued for May-July and January-March with lead times counting down from 4 to 0 months. We found forecasts of between 20 and 50 mm break-of-season or follow-up rainfall were likely to influence decisions. Eighty percent of pastoralists demonstrated in a test question that they had a poor technical understanding of how to interpret the standard wording of a probabilistic median rainfall forecast. this is worthy of further research to investigate whether inappropriate management decisions are being made because the forecasts are being misunderstood. We found more than half the respondents regularly access and use weather and climate forecasts or outlook information from a range of sources and almost three-quarters considered climate information or tools useful, with preferred methods for accessing this information by email, faxback service, internet and the Department of Agriculture Western Australia's Pastoral Memo. Despite differences in enterprise types and rainfall seasonality across the region we found seasonal climate forecasting needs were relatively consistent. It became clear that providing basic training and working with pastoralists to help them understand regional climatic drivers, climate terminology and jargon, and the best ways to apply the forecasts to enhance decision-making are important to improve their use of information. Consideration could also be given to engaging a range of producers to write the climate forecasts themselves in the language they use and understand, in consultation with the scientists who prepare the forecasts.

Near-global impact of the Madden-Julian Oscillation on rainfall

The accuracy of synoptic-based weather forecasting deteriorates rapidly after five days and is not routinely available beyond 10 days. Conversely, climate forecasts are generally not feasible for periods of less than 3 months, resulting in a weather-climate gap. The tropical atmospheric phenomenon known as the Madden-Julian Oscillation (MJO) has a return interval of 30 to 80 days that might partly fill this gap. Our near-global analysis demonstrates that the MJO is a significant phenomenon that can influence daily rainfall patterns, even at higher latitudes, via teleconnections with broadscale mean sea level pressure (MSLP) patterns. These weather states provide a mechanistic basis for an MJO-based forecasting capacity that bridges the weather-climate divide. Knowledge of these tropical and extra-tropical MJO-associated weather states can significantly improve the tactical management of climate-sensitive systems such as agriculture.

Using morphological traits to identify persistent lucernes for dryland agriculture in NSW, Australia

This paper reports on several studies conducted to better understand the variability between lucerne cultivars and lines, and use this to predict persistence in dryland grazing pastures in eastern Australia. Morphological traits of 20 cultivars/lines were measured in irrigated and dryland spaced plant experiments. Studies were also conducted to describe variation among lucernes in their utilisation of starch and responses to water deficit, pests and diseases. Multiple regression analyses were used to develop simple models where the measured traits could be used to predict persistence of lucerne lines in dryland evaluation experiments. Although there was significant variation among cultivars/lines in most measured traits, no single trait reliably predicted persistence of cultivars/lines in dryland evaluation experiments. However, variation in persistence at both sites could be explained by models developed by multiple regression using differences in the mean lengths of the longest stems at 10% flower in summer and winter. Persistent lucernes were those that had relatively long stems in summer and short stems in winter. Water use efficiencies, starch utilisation patterns and resistances to pests and diseases of different lucernes provided some improvement to this simple model, but these improvements were not consistent.

Annual forecasting of the Australian macadamia crop - integrating tree census data with statistical climate-adjustment models

To facilitate marketing and export, the Australian macadamia industry requires accurate crop forecasts. Each year, two levels of crop predictions are produced for this industry. The first is an overall longer-term forecast based on tree census data of growers in the Australian Macadamia Society (AMS). This data set currently accounts for around 70% of total production, and is supplemented by our best estimates of non-AMS orchards. Given these total tree numbers, average yields per tree are needed to complete the long-term forecasts. Yields from regional variety trials were initially used, but were found to be consistently higher than the average yields that growers were obtaining. Hence, a statistical model was developed using growers' historical yields, also taken from the AMS database. This model accounted for the effects of tree age, variety, year, region and tree spacing, and explained 65% of the total variation in the yield per tree data. The second level of crop prediction is an annual climate adjustment of these overall long-term estimates, taking into account the expected effects on production of the previous year's climate. This adjustment is based on relative historical yields, measured as the percentage deviance between expected and actual production. The dominant climatic variables are observed temperature, evaporation, solar radiation and modelled water stress. Initially, a number of alternate statistical models showed good agreement within the historical data, with jack-knife cross-validation R2 values of 96% or better. However, forecasts varied quite widely between these alternate models. Exploratory multivariate analyses and nearest-neighbour methods were used to investigate these differences. For 2001-2003, the overall forecasts were in the right direction (when compared with the long-term expected values), but were over-estimates. In 2004 the forecast was well under the observed production, and in 2005 the revised models produced a forecast within 5.1% of the actual production. Over the first five years of forecasting, the absolute deviance for the climate-adjustment models averaged 10.1%, just outside the targeted objective of 10%.

New annual and short-lived perennial pasture legumes for Australian agriculture--15 years of revolution

Fifteen years ago subterranean clover (Trifolium subterraneum) and annual medics (Medicago spp.) dominated annual pasture legume sowings in southern Australia, while limited pasture legume options existed for cropping areas of subtropical Australia. Since then a number of sustainability and economic challenges to existing farming systems have emerged, exposing shortcomings in these species and the lack of legume biodiversity. Public breeding institutions have responded to these challenges by developing 58 new annual and short-lived perennial pasture legumes with adaptation to both existing and new farming systems. This has involved commercialisation of new species and overcoming deficiencies in traditional species. Traits incorporated in legumes of Mediterranean Basin origin for the Mediterranean, temperate and southern subtropical climates of Australia include deeper root systems, protection from false breaks (germination-inducing rainfall events followed by death from drought), a range of hardseed levels, acid-soil tolerant root nodule symbioses, tolerance to pests and diseases and provision of lower cost seed through ease of seed harvesting and processing. Ten new species, French serradella (Ornithopus sativus), biserrula (Biserrula pelecinus), sulla (Hedysarum coronarium), gland (Trifolium glanduliferum), arrowleaf (Trifolium vesiculosum), eastern star (Trifolium dasyurum) and crimson (Trifolium incarnatum) clovers and sphere (Medicago sphaerocarpos), button (Medicago orbicularis) and hybrid disc (Medicago tornata x Medicago littoralis) medics have been commercialised. Improved cultivars have also been developed of subterranean (T. subterraneum), balansa (Trifolium michelianum), rose (Trifolium hirtum), Persian (Trifolium resupinatum) and purple (Trifolium purpureum) clovers, burr (Medicago polymorpha), strand (M. littoralis), snail (Medicago scutellata) and barrel (Medicago truncatula) medics and yellow serradella (Ornithopus compressus). New tropical legumes for pasture phases in subtropical cropping areas include butterfly pea (Clitoria ternatea), burgundy bean (Macroptilium bracteatum) and perennial lablab (Lablab purpureus). Other species and cultivars of Mediterranean species are likely to be released soon. The contributions of genetic resources, rhizobiology, pasture ecology and agronomy, plant pathology, entomology, plant chemistry and animal science have been paramount to this success. A farmer survey in Western Australia has shown widespread adoption of the new pasture legumes, while adoption of new tropical legumes has also been high in cropping areas of the subtropics. This trend is likely to increase due to the increasing cost of inorganic nitrogen, the need to combat herbicide-resistant crop weeds and improved livestock prices. Mixtures of these legumes allows for more robust pastures buffered against variable seasons, soils, pests, diseases and management decisions. This paper discusses development of the new pasture legumes, their potential use and deficiencies in the current suite. 'Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Needs for applied climate education in agriculture

This paper reports on a purposive survey study which aimed to identify needs for the development, delivery and evaluation of applied climate education for targeted groups, to improve knowledge and skills to better manage under variable climatic conditions. The survey sample consisted of 80 producers and other industry stakeholders in Australia (including representatives from consulting, agricultural extension and agricultural education sectors), with a 58% response rate to the survey. The survey included an assessment of (i) knowledge levels of the Southern Oscillation Index and sea surface temperatures, and (ii) skill and ability in interpreting weather and climate parameters. Results showed that despite many of the respondents having more than 20 years experience in their industry, the only formal climate education or training undertaken by most was a 1-day workshop. Over 80% of the applied climate skills listed in the survey were regarded by respondents as essential or important, but only 42% of educators, 30% of consultants and 28% of producers rated themselves as competent in applying such skills. Essential skills were deemed as those that would enable respondents or their clients to be better prepared for the next extended wet or dry meteorological event, and improved capability in identifying and capitalising on key decision points from climate information and a seasonal climate outlook. The complex issue of forecast accuracy is a confounding obstacle for many in the application of climate information and forecasts in management. Addressing this problem by describing forecast 'limitations and skill' can help to overcome this problem. The survey also highlighted specific climatic tactical and strategic information collated from grazing, cropping and agribusiness enterprises, and showed the value of such information from a users perspective.

Stakeholder expectations for environmental assurance in agriculture: Lessons from the pastoral industry

This paper outlines the expectations of a wide range of stakeholders for environmental assurance in the pastoral industries and agriculture generally. Stakeholders consulted were domestic consumers, rangeland graziers, members of environmental groups, companies within meat and wool supply chains, and agricultural industry, environmental and consumer groups. Most stakeholders were in favour of the application of environmental assurance to agriculture, although supply chains and consumers had less enthusiasm for this than environmental and consumer groups. General public good benefits were more important to environmental and consumer groups, while private benefits were more important to consumers and supply chains. The 'ideal' form of environmental assurance appears to be a management system that provides for continuous improvement in environmental, quality and food safety outcomes, combined with elements of ISO 14024 eco-labelling such as life-cycle assessment, environmental performance criteria, third-party certification, labelling and multi-stakeholder involvement. However, market failure prevents this from being implemented and will continue to do so for the foreseeable future. In the short term, members of supply chains (the people that must implement and fund environmental assurance) want this to be kept simple and low cost, to be built into their existing industry standards and to add value to their businesses. As a starting point, several agricultural industry organisations favour the use of a basic management system, combining continuous improvement, risk assessment and industry best management practice programs, which can be built on over time to meet regulator, market and community expectations.

Better Macadamia crop forecasting

Better Macadamia crop forecasting.

Better Macadamia Crop Forecasting - Part 2

The continually expanding macadamia industry needs an accurate crop forecasting system to allow it to develop effective crop handling and marketing strategies, particularly when the industry faces recurring cycles of unsustainably high and low commodity prices. This project aims to provide the AMS with a robust, reliable predictive model of national crop volume within 10% of the actual crop by 1 April each year by factoring known seasonal, environmental, cultural, climatic, management and biological constraints, together with the existing AMS database which includes data on tree numbers, tree age, variety, location and previous season's production.

Remote Sensing - based precision agriculture tool for the sugar industry

The project will produce practical and relevant benchmarks, protocols and recommendations for the adoption of remote sensing technologies for improved in season management and therefore production within the Australian sugar cane industry.

Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

ACIAR Feasibility of farmers managing climate related crop production risk in India

Validation of new Indian seasonal climate forecasting products. In the Indian state of Andhra Pradesh (AP) kharif crops are heavily dependent on summer monsoon rains, where the timing and intensity of the rains affects crop yield. The majority of farms in AP are small and marginal, making them very vulnerable to yield reductions. Farmers also lack access to relevant information that might enable them to respond to seasonal conditions. Enabling farmers to utilise seasonal climate forecasting would allow them to respond to seasonal variability. To do this, farmers need a forecasting system that indicates a specific management strategy for the upcoming season, and effective and timely communication of the forecast information. Current agro-meteorological advisories in AP are issued on a bi-weekly basis, and they are relevant to an agro-climatic zone scale which may not be sufficiently relevant at a village level. Also, the information in the advisories may not be necessarily packaged in way relevant to cropping decisions by farmers. The objectives of this project are to evaluate the skill of seasonal climate forecasts to be issued for the 2008 monsoon season, to assess crop management options in response to seasonal scenarios that capture the range of seasonal climatic variability, to develop and evaluate options for effective communication and adoption of climate forecasts and agricultural advisories, and to synthesise and report on options for future research investments into seasonal climate forecasting.

Relocation of Intensive Agriculture to Northern Australia: The Case of the Rice Industry

Development of new agricultural industries in northern Australia is seen as a way to provide food security in the face of reduced water availability in existing regions in the south. This report aims to identify some of the possible economic consequences of developing a rice industry in the Burdekin region, while there is a reduction of output in the Riverina. Annual rice production in the Riverina peaked at 1.7 M tonnes, but the long-term outlook, given climate change impacts on that region and government water buy-backs, is more likely to be less than 800,000 tonnes. Growers are highly efficient water users by international standards, but the ability to offset an anticipated reduction in water availability through further efficiency gains is limited. In recent years growers in the Riverina have diversified their farms to a greater extent and secondary production systems include beef, sheep and wheat. Production in north Queensland is in its infancy, but a potentially suitable farming system has been developed by including rice within the sugarcane system without competition and in fact contributing to the production of sugar by increasing yields and controlling weeds. The economic outcomes are estimated a large scale, dynamic, computable general equilibrium (CGE) model of the world economy (Tasman Global), scaled down to regional level. CGE models mimic the workings of the economy through a system of interdependent behavioural and accounting equations which are linked to an input-output database. When an economic shock or change is applied to a model, each of the markets adjusts according to the set of behavioural parameters which are underpinned by economic theory. In this study the model is driven by reducing production in the Riverina in accordance with relationships found between water availability and the production of rice and replacement by other crops and by increasing ride production in the Burdekin. Three scenarios were considered: • Scenario 1: Rice is grown using the fallow period between the last ratoon crop of sugarcane and the new planting. In this scenario there is no competition between rice and sugarcane • Scenario 2: Rice displaces sugarcane production • Scenario 3: Rice is grown on additional land and does not compete with sugarcane. Two time periods were used, 2030 and 2070, which are the conventional time points to consider climate change impacts. Under scenario 1, real economic output declines in the Riverina by $45 million in 2030 and by $139 million in 2070. This is only partially offset by the increased real economic output in the Burdekin of $35 million and $131 million respectively.

Relocation of Intensive Agriculture to Northern Queensland The Cotton Industry

Development of new agricultural industries in northern Australia is often perceived as a solution to changes in water availability that have occurred within southern Australia as a result of changes to government policy in response to and exacerbated by climate change. This report examines the likely private, social and community costs and benefits associated with the establishment of a cotton industry in the Burdekin. The research undertaken covers three spatial scales by modelling the response of cotton and to climate change at the crop and farm scale and linking this to regional scale modelling of the economy. Modelling crop growth as either a standalone crop or as part of a farm enterprise provides the clearest picture of how yields and water use will be affected under climate change. The alternative to this is to undertake very costly trials in environmental chambers. For this reason it is critical that funding for model development especially for crops being crop in novel environments be seen as a high priority for climate change and adaptation studies. Crop level simulations not only provide information on how the crop responds to climate change, they also illustrate that that these responses are the result of complex interactions and cannot necessarily be derived from the climate information alone. These simulations showed that climate change would lead to decreased cotton yields in 2030 and 2050 without the affect of CO2 fertilisation. Without CO2 fertilisation, yields would be decreased by 3.2% and 17.8%. Including CO2 fertilisation increased yields initially by 5.9%, but these were reduced by 3.6% in 2050. This still represents a major offset and at least ameliorates the impact of climate change on yield. To cope with the decreased in-crop rainfall (4.5% by 2030 and 15.8% in 2050) and an initial increase in evapotranspiration of 2% in 2030 and