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%.

Germination, emergence, and persistence of Sonchus oleraceus, a major crop weed in subtropical Australia.

Sonchus oleraceus (common sowthistle) is a dominant weed and has increased in prevalence in conservation cropping systems of the subtropical grain region of Australia. Four experiments were undertaken to define the environmental factors that favor its germination, emergence, and seed persistence. Seeds were germinated at constant temperatures between 5 and 35C and water potentials between 0 and -1.4 MPa. The maximum germination rate of 86-100% occurred at 0 and -0.2 MPa, irrespective of the temperature when exposed to light (12 h photoperiod light/dark), but the germination rate was reduced by 72% without light. At water potentials of -0.6 to -0.8 MPa, the germination rate was reduced substantially by higher temperatures; no seed germinated at a water potential >-1.0 MPa. Emergence and seed persistence were measured over 30 months following seed burial at 0 (surface), 1, 2, 5, and 10 cm depths in large pots that were buried in a south-eastern Queensland field. Seedlings emerged readily from the surface and 1 cm depth, with no emergence from below the 2 cm depth. The seedlings emerged during any season following rain but, predominantly, within 6 months of planting. Seed persistence was short-term on the soil surface, with 2% of seeds remaining after 6 months, but it increased with the burial depth, with 12% remaining after 30 months at 10 cm. Thus, a minimal seed burial depth with reduced tillage and increased surface soil water with stubble retention has favored the proliferation of this weed in any season in a subtropical environment. However, diligent management without seed replenishment will greatly reduce this weed problem within a short period.

Population genetic structure and genetic diversity of three critically endangered Pristis sawfishes in Australian waters.

Northern Australia is considered to be one of the last strongholds for three critically endangered sawfishes, Pristis zijsron, Pristis clavata, and Pristis microdon, making these populations of global significance. Population structure and levels of genetic diversity were assessed for each species across northern Australia using a portion of the mitochondrial control region. Statistically significant genetic structure was detected in all three species, although it was higher in P. microdon (F-ST = 0.811; N = 149) than in either P. clavata (F-ST = 0.419; N = 73) or P. zijsron (F-ST = 0.202; N = 49), possibly due to a much higher and/or localized level of female philopatry in P. microdon. The overall levels of haplotype diversity in P. zijsron (h = 0.555), P. clavata (h = 0.489), and P. microdon (h = 0.650) were moderate, although it appears to be reduced in the assemblages of P. zijsron and P. clavata in the Gulf of Carpentaria (h = 0.342 and h = 0.083, respectively). Since female migration (replenishment) between regions is unlikely, conservation plans should strive to maintain current levels of diversity and abundances in the regional assemblages of each species.

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.

Harvest strategy evaluation to optimise the sustainability and value of the Queensland scallop fishery. Queensland scallop fishery - FRDC Project No 2006/024 Final Report

Objective 1. Measure spatial and temporal trawl frequency of scallop grounds using VMS data. This will provide a relative measure of how often individual undersized scallops are caught and put through a tumbler 2. Estimate discard mortality and growth rates for saucer scallops using cage experiments. 3. Evaluate the current management measures, in particular the seasonal closure, rotational closure and seasonally varying minimum legal sizes using stock assessment and management modeling models. Recommend optimal range of management measures to ensure long-term viability and value of the Scallop fishery based on a formal management strategy evaluation. Outcomes acheived to date: 1. Improved understanding of the survival rates of discarded sub-legal scallops; 2. Preliminary von Bertalanffy growth parameters using data from tagged-and-released scallops; 3. Changing trends in vessels and fishing gear used in the Queensland scallop fishery and their effect on scallop catch rates over time using standardised catch rates quantified; 4. Increases in fishing power of vessels operating in the Queensland scallop fishery quantified; 5. Trawl intensity mapped and quantified for all Scallop Replenishment Areas; 6. Harvest Strategy Evaluations completed.

Potential Distribution and Risk Assessment of an Invasive Plant Species: A Case Study of Hymenachne amplexicaulis in Australia

Given the limited resources available for weed management, a strategic approach is required to give the best bang for your buck. The current study incorporates: (1) a model ensemble approach to identify areas of uncertainty and commonality regarding a species invasive potential, (2) current distribution of the invaded species, and (3) connectivity of systems to identify target regions and focus efforts for more effective management. Uncertainty in the prediction of suitable habitat for H. amplexicaulis (study species) in Australia was addressed in an ensemble-forecasting approach to compare distributional scenarios from four models (CLIMATCH; CLIMEX; boosted regression trees [BRT]; maximum entropy [Maxent]). Models were built using subsets of occurrence and environmental data. Catchment risk was determined through incorporating habitat suitability, the current abundance and distribution of H. amplexicaulis, and catchment connectivity. Our results indicate geographic differences between predictions of different approaches. Despite these differences a number of catchments in northern, central, and southern Australia were identified as high risk of invasion or further spread by all models suggesting they should be given priority for the management of H. amplexicaulis. The study also highlighted the utility of ensemble approaches in indentifying areas of uncertainty and commonality regarding the species invasive potential.

Reducing seed viability of flaxleaf fleabane, feathertop Rhodes grass and awnless barnyard grass

In the sub-tropical grain region of Australia, cotton and grains systems are now dominated by flaxleaf fleabane (Conyza bonariensis (L.) Cronquist), feathertop Rhodes grass (Chloris virgata Sw.) and awnless barnyard grass (Echinochloa colona (L.) Link). While control of these weed species is best achieved when they are young, previous studies have shown a potential for reducing seed viability and minimising seed bank replenishment by applying herbicides when plants are reproductive. Pot trials were established over two growing seasons to examine the effects of 2,4-D, 2,4-D + picloram, glyphosate and glufosinate which had been successful on other species, along with paraquat and haloxyfop (grasses only). Herbicides were applied at ¾ field rates in an attempt not to kill the plants. Flaxleaf fleabane plants were sprayed at two growth stages (budding and flowering) and the grasses were sprayed at two stages (late tillering/booting and flowering). Spraying flaxleaf fleabane at flowering reduced seed viability to 0% (of untreated) in all treatments except glyphosate (51%) and 2,4-D + picloram (8%). Seed viability was not reduced with the first and second regrowths with the exception of 2,4-D + picloram where viability was reduced to 20%. When sprayed at budding only 2,4-D + picloram reduced seed viability in both trials. Spraying the grasses at late tillering/booting did not reduce viability except for glufosinate on awnless barnyard grass (50%). Applying herbicides at flowering resulted in 0% seed viability in awnless barnyard grass from glufosinate, paraquat and glyphosate and 0% viability in feathertop Rhodes grass for glufosinate. These herbicides were less effective on heads that emerged and flowered after spraying, only slightly reducing seed viability. These trials have shown that attempts to reduce seed viability have potential, however flaxleaf fleabane and feathertop Rhodes grass are able to regrow and will need on-going monitoring and control measures.

Seed bank longevity and age to reproductive maturity of Calotropis procera (Aiton) W.T. Aiton in the dry tropics of northern Queensland

Understanding the reproductive biology of Calotropis procera (Aiton) W.T. Aiton, an invasive weed of northern Australia, is critical for development of effective management strategies. Two experiments are reported on. In Experiment 1 seed longevity of C. procera seeds, exposed to different soil type (clay and river loam), pasture cover (present and absent) and burial depth (0, 2.5, 10 and 20 cm) treatments were examined. In Experiment 2 time to reach reproductive maturity was studied. The latter experiment included its sister species, C. gigantea (L.) W.T. Aiton, for comparison and two separate seed lots were tested in 2009 and 2012 to determine if exposure to different environmental conditions would influence persistence. Both seed lots demonstrated a rapid decline in viability over the first 3 months and declined to zero between 15 and 24 months after burial. In Experiment 1, longevity appeared to be most influenced by rainfall patterns and associated soil moisture, burial depth and soil type, but not the level of pasture cover. Experiment 2 showed that both C. procera and C. gigantea plants could flower once they had reached an average height of 85 cm. However, they differed significantly in terms of basal diameter at first flowering with C. gigantea significantly smaller (31 mm) than C. procera (45 mm). On average, C. gigantea flowered earlier (125 days vs 190 days) and set seed earlier (359 days vs 412 days) than C. procera. These results suggest that, under similar conditions to those that prevailed in the present studies, land managers could potentially achieve effective control of patches of C. procera in 2 years if they are able to kill all original plants and treat seedling regrowth frequently enough to prevent it reaching reproductive maturity. This suggested control strategy is based on the proviso that replenishment of the seed bank is not occurring from external sources (e.g. wind and water dispersal).

Assessing the significance of climate and community factors on urban water demand

Ensuring adequate water supply to urban areas is a challenging task due to factors such as rapid urban growth, increasing water demand and climate change. In developing a sustainable water supply system, it is important to identify the dominant water demand factors for any given water supply scheme. This paper applies principal components analysis to identify the factors that dominate residential water demand using the Blue Mountains Water Supply System in Australia as a case study. The results show that the influence of community intervention factors (e.g. use of water efficient appliances and rainwater tanks) on water demand are among the most significant. The result also confirmed that the community intervention programmes and water pricing policy together can play a noticeable role in reducing the overall water demand. On the other hand, the influence of rainfall on water demand is found to be very limited, while temperature shows some degree of correlation with water demand. The results of this study would help water authorities to plan for effective water demand management strategies and to develop a water demand forecasting model with appropriate climatic factors to achieve sustainable water resources management. The methodology developed in this paper can be adapted to other water supply systems to identify the influential factors in water demand modelling and to devise an effective demand management strategy.

Ecology, population genetics and conservation of the African violet

The ongoing rapid fragmentation of tropical forests is a major threat to global biodiversity. This is because many of the tropical forests are so-called biodiversity 'hotspots', areas that host exceptional species richness and concentrations of endemic species. Forest fragmentation has negative ecological and genetic consequences for plant survival. Proposed reasons for plant species' loss in forest fragments are, e.g., abiotic edge effects, altered species interactions, increased genetic drift, and inbreeding depression. To be able to conserve plants in forest fragments, the ecological and genetic processes that threaten the species have to be understood. That is possible only after obtaining adequate information on their biology, including taxonomy, life history, reproduction, and spatial and genetic structure of the populations. In this research, I focused on the African violet (genus Saintpaulia), a little-studied conservation flagship from the Eastern Arc Mountains and Coastal Forests hotspot of Tanzania and Kenya. The main objective of the research was to increase understanding of the life history, ecology and population genetics of Saintpaulia that is needed for the design of appropriate conservation measures. A further aim was to provide population-level insights into the difficult taxonomy of Saintpaulia. Ecological field work was conducted in a relatively little fragmented protected forest in the Amani Nature Reserve in the East Usambara Mountains, in northeastern Tanzania, complemented by population genetic laboratory work and ecological experiments in Helsinki, Finland. All components of the research were conducted with Saintpaulia ionantha ssp. grotei, which forms a taxonomically controversial population complex in the study area. My results suggest that Saintpaulia has good reproductive performance in forests with low disturbance levels in the East Usambara Mountains. Another important finding was that seed production depends on sufficient pollinator service. The availability of pollinators should thus be considered in the in situ management of threatened populations. Dynamic population stage structures were observed suggesting that the studied populations are demographically viable. High mortality of seedlings and juveniles was observed during the dry season but this was compensated by ample recruitment of new seedlings after the rainy season. Reduced tree canopy closure and substrate quality are likely to exacerbate seedling and juvenile mortality, and, therefore, forest fragmentation and disturbance are serious threats to the regeneration of Saintpaulia. Restoration of sufficient shade to enhance seedling establishment is an important conservation measure in populations located in disturbed habitats. Long-term demographic monitoring, which enables the forecasting of a population s future, is also recommended in disturbed habitats. High genetic diversities were observed in the populations, which suggest that they possess the variation that is needed for evolutionary responses in a changing environment. Thus, genetic management of the studied populations does not seem necessary as long as the habitats remain favourable for Saintpaulia. The observed high levels of inbreeding in some of the populations, and the reduced fitness of the inbred progeny compared to the outbred progeny, as revealed by the hand-pollination experiment, indicate that inbreeding and inbreeding depression are potential mechanisms contributing to the extinction of Saintpaulia populations. The relatively weak genetic divergence of the three different morphotypes of Saintpaulia ionantha ssp. grotei lend support to the hypothesis that the populations in the Usambara/lowlands region represent a segregating metapopulation (or metapopulations), where subpopulations are adapting to their particular environments. The partial genetic and phenological integrity, and the distinct trailing habit of the morphotype 'grotei' would, however, justify its placement in a taxonomic rank of its own, perhaps in a subspecific rank.

Understanding urban rail travel for improved patronage forecasting

Improved forecasting of urban rail patronage is essential for effective policy development and efficient planning for new rail infrastructure. Past modelling and forecasting of urban rail patronage has been based on legacy modelling approaches and often conducted at the general level of public transport demand, rather than being specific to urban rail. This project canvassed current Australian practice and international best practice to develop and estimate time series and cross-sectional models of rail patronage for Australian mainland state capital cities. This involved the implementation of a large online survey of rail riders and non-riders for each of the state capital cities, thereby resulting in a comprehensive database of respondent socio-economic profiles, travel experience, attitudes to rail and other modes of travel, together with stated preference responses to a wide range of urban travel scenarios. Estimation of the models provided a demonstration of their ability to provide information on the major influences on the urban rail travel decision. Rail fares, congestion and rail service supply all have a strong influence on rail patronage, while a number of less significant factors such as fuel price and access to a motor vehicle are also influential. Of note, too, is the relative homogeneity of rail user profiles across the state capitals. Rail users tended to have higher incomes and education levels. They are also younger and more likely to be in full-time employment than non-rail users. The project analysis reported here represents only a small proportion of what could be accomplished utilising the survey database. More comprehensive investigation was beyond the scope of the project and has been left for future work.

Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.

Evaluation and modelling of the spatial and temporal variability of particulate matter in urban areas

This thesis contains three subject areas concerning particulate matter in urban area air quality: 1) Analysis of the measured concentrations of particulate matter mass concentrations in the Helsinki Metropolitan Area (HMA) in different locations in relation to traffic sources, and at different times of year and day. 2) The evolution of traffic exhaust originated particulate matter number concentrations and sizes in local street scale are studied by a combination of a dispersion model and an aerosol process model. 3) Some situations of high particulate matter concentrations are analysed with regard to their meteorological origins, especially temperature inversion situations, in the HMA and three other European cities. The prediction of the occurrence of meteorological conditions conducive to elevated particulate matter concentrations in the studied cities is examined. The performance of current numerical weather forecasting models in the case of air pollution episode situations is considered. The study of the ambient measurements revealed clear diurnal variation of the PM10 concentrations in the HMA measurement sites, irrespective of the year and the season of the year. The diurnal variation of local vehicular traffic flows seemed to have no substantial correlation with the PM2.5 concentrations, indicating that the PM10 concentrations were originated mainly from local vehicular traffic (direct emissions and suspension), while the PM2.5 concentrations were mostly of regionally and long-range transported origin. The modelling study of traffic exhaust dispersion and transformation showed that the number concentrations of particles originating from street traffic exhaust undergo a substantial change during the first tens of seconds after being emitted from the vehicle tailpipe. The dilution process was shown to dominate total number concentrations. Minimal effect of both condensation and coagulation was seen in the Aitken mode number concentrations. The included air pollution episodes were chosen on the basis of occurrence in either winter or spring, and having at least partly local origin. In the HMA, air pollution episodes were shown to be linked to predominantly stable atmospheric conditions with high atmospheric pressure and low wind speeds in conjunction with relatively low ambient temperatures. For the other European cities studied, the best meteorological predictors for the elevated concentrations of PM10 were shown to be temporal (hourly) evolutions of temperature inversions, stable atmospheric stability and in some cases, wind speed. Concerning the weather prediction during particulate matter related air pollution episodes, the use of the studied models were found to overpredict pollutant dispersion, leading to underprediction of pollutant concentration levels.

Studies on Binary Time Series Models with Applications to Empirical Macroeconomics and Finance

This thesis studies binary time series models and their applications in empirical macroeconomics and finance. In addition to previously suggested models, new dynamic extensions are proposed to the static probit model commonly used in the previous literature. In particular, we are interested in probit models with an autoregressive model structure. In Chapter 2, the main objective is to compare the predictive performance of the static and dynamic probit models in forecasting the U.S. and German business cycle recession periods. Financial variables, such as interest rates and stock market returns, are used as predictive variables. The empirical results suggest that the recession periods are predictable and dynamic probit models, especially models with the autoregressive structure, outperform the static model. Chapter 3 proposes a Lagrange Multiplier (LM) test for the usefulness of the autoregressive structure of the probit model. The finite sample properties of the LM test are considered with simulation experiments. Results indicate that the two alternative LM test statistics have reasonable size and power in large samples. In small samples, a parametric bootstrap method is suggested to obtain approximately correct size. In Chapter 4, the predictive power of dynamic probit models in predicting the direction of stock market returns are examined. The novel idea is to use recession forecast (see Chapter 2) as a predictor of the stock return sign. The evidence suggests that the signs of the U.S. excess stock returns over the risk-free return are predictable both in and out of sample. The new "error correction" probit model yields the best forecasts and it also outperforms other predictive models, such as ARMAX models, in terms of statistical and economic goodness-of-fit measures. Chapter 5 generalizes the analysis of univariate models considered in Chapters 2 4 to the case of a bivariate model. A new bivariate autoregressive probit model is applied to predict the current state of the U.S. business cycle and growth rate cycle periods. Evidence of predictability of both cycle indicators is obtained and the bivariate model is found to outperform the univariate models in terms of predictive power.