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.

Phosphorus concentrations in the leaves of cotton in tropical Australia are determined by temperature.

Previous research on P leaf analysis for detecting deficiencies in cotton (Gossypium hirsutum L.) has not considered temperature as a determining factor. This is despite correlations between leaf P content and temperature being observed in other crops. As part of research into a new cotton farming system for the semi-arid tropics of Australia, we conducted two P fertiliser rate experiments on recently cleared un-cropped (bicarbonate P < 5 mg kg- 1) and previously cropped (bicarbonate P 26 mg kg- 1) soil. They aimed to develop P requirements and more importantly to determine if temperature affects the leaf P concentrations used to diagnose P deficiencies. In 2002, optimal yield on un-cropped, low P soil was achieved with a 60 kg P ha- 1 rate. In 2003, residual P from the 40 kg P ha- 1 treatment produced optimal yield. On cropped, high P soil there was no yield response to treatments up to 100 kg P ha- 1. On low P soil, a positive correlation was observed between P concentration in the youngest fully-unfurled leaf (YFUL), fertiliser rate, and mean diurnal temperature in the seven days prior to sampling. On high P soil, a positive correlation was observed between the YFUL and mean diurnal temperature however there was no correlation with fertiliser rate. These results show that YFUL analysis can be used to diagnose P deficiencies in cotton, provided the temperature prior to sampling is considered.

CIMMYT-selected derived synthetic bread wheats for rainfed environments: Yield evaluation in Mexico and Australia.

Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the Northwest of Mexico at Centro de Investigaciones Agrícolas del Noroeste (CIANO) and sites across Australia during three seasons. During three consecutive years Australia received “shipments” of different SBWs from CIMMYT for evaluation. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. These consisted of approximately 100 advanced lines (F7) per year. SBWs had been top and backcrossed to CIMMYT cultivars in the first two shipments and to Australian wheat cultivars in the third one. At CIANO, the SBWs were trialled under receding soil moisture conditions. We evaluated both the performance of each line across all environments and the genotype-by-environment interaction using an analysis that fits a multiplicative mixed model, adjusted for spatial field trends. Data were organised in three groups of multienvironment trials (MET) containing germplasm from shipment 1 (METShip1), 2 (METShip2), and 3 (METShip3), respectively. Large components of variance for the genotype × environment interaction were found for each MET analysis, due to the diversity of environments included and the limited replication over years (only in METShip2, lines were tested over 2 years). The average percentage of genetic variance explained by the factor analytic models with two factors was 50.3% for METShip1, 46.7% for METShip2, and 48.7% for METShip3. Yield comparison focused only on lines that were present in all locations within a METShip, or “core” SBWs. A number of core SBWs, crossed to both Australian and CIMMYT backgrounds, outperformed the local benchmark checks at sites from the northern end of the Australian wheat belt, with reduced success at more southern locations. In general, lines that succeeded in the north were different from those in the south. The moderate positive genetic correlation between CIANO and locations in the northern wheat growing region likely reflects similarities in average temperature during flowering, high evaporative demand, and a short flowering interval. We are currently studying attributes of this germplasm that may contribute to adaptation, with the aim of improving the selection process in both Mexico and Australia.

Patterns of release of the secondary conidia of Claviceps africana, the sorghum ergot pathogen in Australia

Trials were conducted in southern Queensland, Australia between March and May 2003, 2004 and 2005 to study patterns of hourly and daily release of the secondary conidia of Claviceps africana and their relationships with weather parameters. Conidia were trapped for at least one hour on most (> 90%) days in 2003 and 2004, but only on 55% of days in 2005. Both the highest daily concentration of conidia, and the highest number of hours per day when conidia were trapped, were recorded 1-3 days after rainfall events. Although the pattern of conidial release was different every day, the highest hourly conidial concentrations occurred between 10.00 hours and 17.00 hours on 73% of all days in the three trials. Hours when conidia were trapped were characterized by higher median values of temperature, windspeed and vapour pressure deficit, lower relative humidity, and leaf wetness values of 0%, than hours when no conidia were recorded. The results indicate that fungicides need to be applied to the highly ergot-susceptible male sterile (A-) lines of sorghum in hybrid seed production blocks and breeders' nurseries as soon as possible after rainfall events to minimize ergot severity.

A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits

Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations.

Crop and environmental attributes underpinning genotype by environment interaction in synthetic-derived bread wheat evaluated in Mexico and Australia

Synthetic backcrossed-derived bread wheats (SBWs) from CIMMYT were grown in the north-west of Mexico (CIANO) and sites across Australia during 3 seasons. A different set of lines was evaluated each season, as new materials became available from the CIMMYT crop enhancement program. Previously, we have evaluated both the performance of genotypes across environments and the genotype x environment interaction (G x E). The objective of this study was to interpret the G x E for yield in terms of crop attributes measured at individual sites and to identify the potential environmental drivers of this interaction. Groups of SBWs with consistent yield performance were identified, often comprising closely related lines. However, contrasting performance was also relatively common among sister lines or between a recurrent parent and its SBWs. Early flowering was a common feature among lines with broad adaptation and/or high yield in the northern Australian wheatbelt, while yields in the southern region did not show any association with the maturity type. Lines with high yields in the southern and northern regions had cooler canopies during flowering and early grain filling. Among the SBWs with Australian genetic backgrounds, lines best adapted to CIANO were tall (>100 cm), with a slightly higher ground cover. These lines also displayed a higher concentration of water-soluble carbohydrates in the stem at flowering, which was negatively correlated with stem number per unit area when evaluated in southern Australia (Horsham). Possible reasons for these patterns are discussed. Selection for yield at CIANO did not specifically identify the lines best adapted to northern Australia, although they were not the most poorly adapted either. In addition, groups of lines with specific adaptation to the south would not have been selected by choosing the highest yielding lines at CIANO. These findings suggest that selection at CIMMYT for Australian environments may be improved by either trait based selection or yield data combined with trait information. Flowering date, canopy temperature around flowering, tiller density, and water-soluble carbohydrate concentration in the stem at flowering seem likely candidates.

Modelling climatic risks of aflatoxin contamination in maize

Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM's maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.

Relative contributions of light interception and radiation use efficiency to the reduction of maize productivity under cold temperatures

Maize (Zea mays L.) is a chill-susceptible crop cultivated in northern latitude environments. The detrimental effects of cold on growth and photosynthetic activity have long been established. However, a general overview of how important these processes are with respect to the reduction of productivity reported in the field is still lacking. In this study, a model-assisted approach was used to dissect variations in productivity under suboptimal temperatures and quantify the relative contributions of light interception (PARc) and radiation use efficiency (RUE) from emergence to flowering. A combination of architectural and light transfer models was used to calculate light interception in three field experiments with two cold-tolerant lines and at two sowing dates. Model assessment confirmed that the approach was suitable to infer light interception. Biomass production was strongly affected by early sowings. RUE was identified as the main cause of biomass reduction during cold events. Furthermore, PARc explained most of the variability observed at flowering, its relative contributions being more or less important according to the climate experienced. Cold temperatures resulted in lower PARc, mainly because final leaf length and width were significantly reduced for all leaves emerging after the first cold occurrence. These results confirm that virtual plants can be useful as fine phenotyping tools. A scheme of action of cold on leaf expansion, light interception and radiation use efficiency is discussed with a view towards helping breeders define relevant selection criteria. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Summative evaluation of climate application activities with pastoralists in western Queensland

Survey methods were engaged to measure the change in use and knowledge of climate information by pastoralists in western Queensland. The initial mail survey was undertaken in 2000-01 (n=43) and provided a useful benchmark of pastoralists climate knowledge. Two years of climate applications activities were completed and clients were re-surveyed in 2003 (n=49) to measure the change in knowledge and assess the effectiveness of the climate applications activities. Two methods were used to assess changes in client knowledge, viz., self-assessment and test questions. We found that the use of seasonal climate forecasts in decision making increased from 36% in 2001 (n=42) to 51% in 2003 (n=49) (P=0.07). The self-assessment technique was unsatisfactory as a measure of changing knowledge over short periods (1-3 years), but the test question technique was successful and indicated an improvement in climate knowledge among respondents. The increased levels of use of seasonal climate forecasts in management and improved knowledge was partly attributed to the climate applications activities of the project. Further, those who used seasonal forecasting (n=25) didn't understand key components of forecasts (e.g. probability, median) better than those who didn't use seasonal forecasts (n=24) (P>0.05). This identifies the potential for misunderstanding and misinterpretation of forecasts among users and highlights the need for providers of forecasts to understand the difficulties and prepare simply written descriptions of forecasts and disseminate these with the maps showing probabilities. The most preferred means of accessing climate information were internet, email, 'The Season Ahead' newsletter and newspaper. The least preferred were direct contact with extension officers and attending field days and group meetings. Eighty-six percent of respondents used the internet and 67% used ADSL broadband internet (April 2003). Despite these findings, extension officers play a key role in preparing and publishing the information on the web, in emails and newsletters. We also believe that direct contact with extension officers trained in climate applications is desirable in workshop-like events to improve knowledge of the difficult concepts underpinning climate forecasts, which may then stimulate further adoption.

Optimal management of agricultural systems

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

Sorghum stay-green QTL individually reduce post-flowering drought-induced leaf senescence

Sorghum is an important source of food, feed, and biofuel, especially in the semi-arid tropics because this cereal is well adapted to harsh, drought-prone environments. Post-flowering drought adaptation in sorghum is associated with the stay-green phenotype. Alleles that contribute to this complex trait have been mapped to four major QTL, Stg1-Stg4, using a population derived from BTx642 and RTx7000. Near-isogenic RTx7000 lines containing BTx642 DNA spanning one or more of the four stay-green QTL were constructed. The size and location of BTx642 DNA regions in each RTx7000 NIL were analysed using 62 DNA markers spanning the four stay-green QTL. RTx7000 NILs were identified that contained BTx642 DNA completely or partially spanning Stg1, Stg2, Stg3, or Stg4. NILs were also identified that contained sub-portions of each QTL and various combinations of the four major stay-green QTL. Physiological analysis of four RTx7000 NILs containing only Stg1, Stg2, Stg3, or Stg4 showed that BTx642 alleles in each of these loci could contribute to the stay-green phenotype. RTx7000 NILs containing BTx642 DNA corresponding to Stg2 retained more green leaf area at maturity under terminal drought conditions than RTx7000 or the other RTx7000 NILs. Under post-anthesis water deficit, a trend for delayed onset of leaf senescence compared with RTx7000 was also exhibited by the Stg2, Stg3, and Stg4 NILs, while significantly lower rates of leaf senescence in relation to RTx7000 were displayed by all of the Stg NILs to varying degrees, but particularly by the Stg2 NIL. Greener leaves at anthesis relative to RTx7000, indicated by higher SPAD values, were exhibited by the Stg1 and Stg4 NILs. The RTx7000 NILs created in this study provide the starting point for in-depth analysis of stay-green physiology, interaction among stay-green QTL and map-based cloning of the genes that underlie this trait.

From inferential statistics to climate knowledge

Climate variability and change are risk factors for climate sensitive activities such as agriculture. Managing these risks requires "climate knowledge", i.e. a sound understanding of causes and consequences of climate variability and knowledge of potential management options that are suitable in light of the climatic risks posed. Often such information about prognostic variables (e.g. yield, rainfall, run-off) is provided in probabilistic terms (e.g. via cumulative distribution functions, CDF), whereby the quantitative assessments of these alternative management options is based on such CDFs. Sound statistical approaches are needed in order to assess whether difference between such CDFs are intrinsic features of systems dynamics or chance events (i.e. quantifying evidences against an appropriate null hypothesis). Statistical procedures that rely on such a hypothesis testing framework are referred to as "inferential statistics" in contrast to descriptive statistics (e.g. mean, median, variance of population samples, skill scores). Here we report on the extension of some of the existing inferential techniques that provides more relevant and adequate information for decision making under uncertainty.

Effects of environmental heat on conception rates in lactating dairy cows: Critical periods of exposure

Environmental heat can reduce conception rates (the proportion of services that result in pregnancy) in lactating dairy cows. The study objectives were to identify periods of exposure relative to the service date in which environmental heat is most closely associated with conception rates, and to assess whether the total time cows are exposed to high environmental heat within each 24-h period is more closely associated with conception rates than is the maximum environmental heat for each 24-h period. A retrospective observational study was conducted in 25 predominantly Holstein-Friesian commercial dairy herds located in Australia. Associations between weather and conception rates were assessed using 16,878 services performed over a 21-mo period. Services were classified as successful based on rectal palpation. Two measures of heat load were defined for each 24-h period: the maximum temperature-humidity index (THI) for the period, and the number of hours in the 24-h period when the THI was >72. Conception rates were reduced when cows were exposed to a high heat load from the day of service to 6 d after service, and in wk -1. Heat loads in wk -3 to -5 were also associated with reduced conception rates. Thus, management interventions to ameliorate the effects of heat load on conception rates should be implemented at least 5 wk before anticipated service and should continue until at least 1 wk after service. High autocorrelations existed between successive daily values in both measures, and associations between day of heat load relative to service day and conception rates differed substantially when ridge regression was used to account for this autocorrelation. This indicates that when assessing the effects of heat load on conception rates, the autocorrelation in heat load between days should be accounted for in analyses. The results suggest that either weekly averages or totals summarizing the daily heat load are adequate to describe heat load when assessing effects on conception rates in lactating dairy cows.

Probabilistic forecasts of the onset of the north Australian wet season

The amount and timing of early wet-season rainfall are important for the management of many agricultural industries in north Australia. With this in mind, a wet-season onset date is defined based on the accumulation of rainfall to a predefined threshold, starting from 1 September, for each square of a 1° gridded analysis of daily rainfall across the region. Consistent with earlier studies, the interannual variability of the onset dates is shown to be well related to the immediately preceding July-August Southern Oscillation index (SOI). Based on this relationship, a forecast method using logistic regression is developed to predict the probability that onset will occur later than the climatological mean date. This method is expanded to also predict the probabilities that onset will be later than any of a range of threshold dates around the climatological mean. When assessed using cross-validated hindcasts, the skill of the predictions exceeds that of climatological forecasts in the majority of locations in north Australia, especially in the Top End region, Cape York, and central Queensland. At times of strong anomalies in the July-August SOI, the forecasts are reliably emphatic. Furthermore, predictions using tropical Pacific sea surface temperatures (SSTs) as the predictor are also tested. While short-lead (July-August predictor) forecasts are more skillful using the SOI, long-lead (May-June predictor) forecasts are more skillful using Pacific SSTs, indicative of the longer-term memory present in the ocean.

Evaluating temperate species for the subtropics. 1. Annual ryegrasses

In the subtropics of Australia, irrigated temperate species are the key to reliable cool season feed on dairy farms. Persistence of perennial species is a major limitation to achieving reliable production from irrigated areas and yearly sowings of annual ryegrasses have replaced them as the most productive cool season forage production system in the subtropics. This series of experiments evaluated the yield, and resistance to rust damage, of commercially available cultivars and breeders' lines of annually sown ryegrasses (Lolium multiflorum, L. rigidum, L. x boucheanum and L perenne) in pure, nitrogen-fertilised swards under irrigation in the subtropics over a 22-year period. Barberia and Aristocrat 2 were the most adapted cultivars for subtropical conditions, producing high yields (119 and 114% of mean yield, respectively) and demonstrating the least rust damage. Newer selections from New Zealand, South African, United States of America and European breeding programs are performing better under subtropical conditions than older cultivars, particularly if a component of the selection process has been conducted in that environment. Cultivars such as Passerei Plus, Crusader, Hulk, Status and Warrior are examples of this process, producing between 105 and 115% of mean yield. Yields of annual ryegrass cultivars, which have been available or still are available for sale in Australia, ranged from 14-30 t/ha DM, depending on cultivar, site and seasonal conditions. Yields were lower at the site, which had inferior soil structure and drainage. Up to 50% of yield was produced in the 3 winter months. There was a trend towards improved yields and better tolerance of crown rust from experimental lines in the subtropics, as breeders strive for wider adaptation. Around 70% of the variation in total yield of annual ryegrass and 50 and 60% of the variation in winter and spring yield, respectively, were significantly explained by cultivar, site and climatic variables in autumn, winter and spring. While level of rust damage had no effect on total or seasonal yields, it affected the amount of green leaf available in spring. Under subtropical conditions, winter, spring and overall (autumn to mid-summer) temperatures influenced the- development of rust, which along with cultivar, accounted for 46% of the variation in rust damage. Cultivars showed a range of adaptation, with some performing well only under adverse conditions, some being well adapted to all conditions and some which performed well only under favoured conditions. Cultivars with high winter yields were most suited to subtropical conditions and included Aristocrat 2 (now released as CM 108), Barberia, Warrior, Crusader, Status, Passerei Plus and Hulk. Short growing season types such as Winter Star and T Rex performed well in winter but achieved lower total production, and long season cultivars such as Flanker rarely achieved their potential because of unfavourable conditions in late summer.