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.

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.

Effective Use in Livestock Feeds of Mouldy and Weather-damaged Grain Containing Mycotoxins-Case Histories and Economic Assessments Pertaining to Pig and Poultry Industries of Queensland

Mould growth in field crops or stored grain reduces starch and lipid content, with consequent increases in fibre, and an overall reduction in digestible energy; palatability is often adversely affected. If these factors are allowed for, and mycotoxin concentrations are low, there are sound economic reasons for using this cheaper grain. Mycotoxins are common in stock feed but their effects on animal productivity are usually slight because either the concentration is too low or the animal is tolerant to the toxin. In Australia, aflatoxins occur in peanut by-products and in maize and sorghum if the grain is moist when stored. Zearalenone is found in maize and in sorghum and wheat in wetter regions. Nivalenol and deoxynivalenol are found in maize and wheat but at concentrations that rarely affect pigs, with chickens and cattle being even more tolerant. Other mycotoxins including cyclopiazonic acid, T-2 toxin, cytochalasins and tenuazonic acid are produced by Australian fungi in culture but are not found to be significant grain contaminants. Extremely mouldy sorghum containing Alternaria and Fusarium mycotoxins decreased feed conversion in pigs and chickens by up to 14%. However, E moniliforme- and Diplodia maydis-infected maize produced only slight reductions in feed intake by pigs and Ustilago- infected barley produced no ill effects. Use of these grains would substantially increase profits if the grain can be purchased cheaply.

The mycotoxins 4-deoxynivalenol, zearalenone and aflatoxin in weather-damaged wheat harvested 1983-1985 in south-east Queensland

A survey for various mycotoxins was carried out on samples of all wheat delivered to nine storage and marketing depots in south-eastern Queensland, selected as most likely to receive mycotoxin-contaminated grain. All wheat was surveyed during 1983, when the degree of weather damage was high. Samples of the poorest grade of wheat from these depots were also surveyed in 1984 and 1985. The surveys included all regions where head scab of wheat caused by Fusariurn graminearurn Schwabe Group 2 had been reported to occur at significant levels. 4-Deoxynivalenol was detected in nearly all pooled samples representing bulk wheat at concentrations ranging from traces of <0.01 up to 1.7 mg kg-1. The highest concentration of zearlenone detected in a pooled wheat sample was 0.04 mg kg-1. In a few samples representing individual wheat deliveries and with up to 2.8% by weight of pink grains, 4-deoxynivalenol concentrations ranged up to 11.7 mg kg-' and zearalenone up to 0.43 mg kg-l. Aflatoxins B,, B2, G1 and G2 were detected in only one pooled sample of wheat, at a total aflatoxin concentration of 0.003 mg kg-'. Ochratoxin A, sterigmatocystin and T-2 toxin were not detected. Higher concentrations of mycotoxins were found in the poorer grades of wheat.

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.

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%.

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.

Historical demography of Lantana camara L. reveals clues about the influence of land use and weather in the management of this widespread invasive species

Weather is a general stochastic influence on the life history of weeds. In contrast, anthropogenic disturbance (e.g. land use) is an important deterministic influence on weed demography. Our aim with this study was to investigate the relative contributions of land use and weather on the demography of Lantana camara (lantana), a weed of agricultural and natural habitats, based on the intensive monitoring of lantana populations under three land uses (viz. farm[pasture], and burnt and grazed forests) in subtropical Australia. Lantana populations were growing vigorously across all land uses (asymptotic population growth rate, lambda > 3). Examination of historical demography using retrospective perturbation analyses showed that weather was a strong influence on lantana demography with the transition from an El Nino (2008-09) to a La Nina (2009-10) year having a strong positive effect on population growth rate. This effect was most marked at the grazed site, and to a lesser extent at the burnt site, with seedling-to-juvenile and juvenile-to-adult transitions contributing most to these effects. This is likely the result of burning and grazing having eliminated/reduced interspecific competition at these sites. Prospective perturbation analyses revealed that lambda was most sensitive to proportionate changes in growth transitions, followed by fecundity and survival transitions. Examination of context-specific patterns in elasticity revealed that growth and fecundity transitions are likely to be the more critical vital rates to reduce lambda in wet years at the burnt and grazed forest sites, compared to the farm/pasture site. Management of lantana may need to limit the transition of juveniles into the adult stages, especially in sites where lantana is free from competition (e.g. in the presence of fire or grazing), and this particularly needs to be achieved in wet years. Collectively, these results shed light on aspects of spatial and temporal variation in the demography of lantana, and offer insights on its context-specific management.

Historical demography of Lantana camara L. reveals clues about the influence of land use and weather in the management of this widespread invasive species

Weather is a general stochastic influence on the life history of weeds. In contrast, anthropogenic disturbance (e.g. land use) is an important deterministic influence on weed demography. Our aim with this study was to investigate the relative contributions of land use and weather on the demography of Lantana camara (lantana), a weed of agricultural and natural habitats, based on the intensive monitoring of lantana populations under three land uses (viz. farm[pasture], and burnt and grazed forests) in subtropical Australia. Lantana populations were growing vigorously across all land uses (asymptotic population growth rate, λ > 3). Examination of historical demography using retrospective perturbation analyses showed that weather was a strong influence on lantana demography with the transition from an El Niño (2008–09) to a La Niña (2009–10) year having a strong positive effect on population growth rate. This effect was most marked at the grazed site, and to a lesser extent at the burnt site, with seedling-to-juvenile and juvenile-to-adult transitions contributing most to these effects. This is likely the result of burning and grazing having eliminated/reduced interspecific competition at these sites. Prospective perturbation analyses revealed that λ was most sensitive to proportionate changes in growth transitions, followed by fecundity and survival transitions. Examination of context-specific patterns in elasticity revealed that growth and fecundity transitions are likely to be the more critical vital rates to reduce λ in wet years at the burnt and grazed forest sites, compared to the farm/pasture site. Management of lantana may need to limit the transition of juveniles into the adult stages, especially in sites where lantana is free from competition (e.g. in the presence of fire or grazing), and this particularly needs to be achieved in wet years. Collectively, these results shed light on aspects of spatial and temporal variation in the demography of lantana, and offer insights on its context-specific management.