Tilapia in Australia – Development of management strategies for the control and eradication of feral tilapia populations in Australia

This report presents a culmination of different research projects on two species of tilapia (Oreochromis mossambicus and Tilapia mariae) and provides recommendations for the future management and research of these pest fish. Feral populations of O. mossambicus and T. mariae are now widely distributed in tropical northeastern Queensland, with O. mossambicus also occurring in southeastern Queensland and river systems of Western Australia. O. mossambicus is known to have existed in impoundments in southeastern Queensland, as well as urban drains and ornamental ponds in the Townsville region of north Queensland from about the late 1970s, while T. mariae became established in some easternflowing tropical streams by the early 1990s. In Australia, feral stocks of tilapia are widely regarded as pests that potentially threaten both native fish stocks and biodiversity.

Interactions between two naturalised invasive predators in Australia: are feral cats suppressed by dingoes?

Top-predators can play important roles in terrestrial food webs, fuelling speculation that top-predators might be used as biocontrol tools against invasive mesopredators. Feral cats are believed to be largely responsible for the current declines of native fauna across tropical northern Australia, where substantial beef cattle production occurs. Dingoes are known to impact cattle production there and are predicted to impact native fauna also. However, dingoes are forecasted to curtail the impacts of cats and reverse native fauna declines. We review (1) empirical studies investigating the relationships between dingoes and cats, and dingo control and cats, (2) records of cat remains in dingo diets, and (3) historical records of lethal dingo control using 1080-poisoned baits across Australia between 1999 and 2008 to show how two naturalised invasive species can interact in dynamic agro-ecological landscapes. From the 35 studies assessed, most reported no detectable relationship between dingoes and cats; negative or positive relationships were seldom detected. Dingoes do not appear to exclude cats beyond fine scales, but may alter cat activity periods under certain conditions. Cat remains were found in only 0.63 % of over 31,000 dingo diet records. Lethal dingo control occurs (in varying degrees) across about two-thirds of Australia and does not appear to substantially influence dingo-cat relationships. We conclude that the presently available data provides little evidence that bolstering dingo populations will reduce the impacts of cats. Much more work is needed to identify situations where top-predators might be used as effective biocontrol tools against invasive mesopredators in agro-ecological systems.

On Systems Thinking, Systems Biology, and the in Silico Plant

The recent summary report of a Department of Energy Workshop on Plant Systems Biology (P.V. Minorsky [2003] Plant Physiol 132: 404-409) offered a welcomed advocacy for systems analysis as essential in understanding plant development, growth, and production. The goal of the Workshop was to consider methods for relating the results of molecular research to real-world challenges in plant production for increased food supplies, alternative energy sources, and environmental improvement. The rather surprising feature of this report, however, was that the Workshop largely overlooked the rich history of plant systems analysis extending over nearly 40 years (Sinclair and Seligman, 1996) that has considered exactly those challenges targeted by the Workshop. Past systems research has explored and incorporated biochemical and physiological knowledge into plant simulation models from a number of perspectives. The research has resulted in considerable understanding and insight about how to simulate plant systems and the relative contribution of various factors in influencing plant production. These past activities have contributed directly to research focused on solving the problems of increasing biomass production and crop yields. These modeling approaches are also now providing an avenue to enhance integration of molecular genetic technologies in plant improvement (Hammer et al., 2002).

Growth and Carcase Characters of Progeny from Caprine Feral Does Mated to Boer or Feral Bucks in Western Queensland

In recent years significant numbers of Australian goats have been harvested from the feral population to supply a strong demand for export of meat. In addition large numbers of feral does have been domesticated to increase breeding herds in western Queensland. Introduction of the Boer breed to Australia as a specialist meat goat may provide a genetic means for improving the productive performance of the Australian feral. The present paper reports growth and carcase attributes of feral and Boer x feral genotypes born in 1998 and birthweight of those born in 1999. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

Reproductive Performance of Caprine Feral Does Mated to Boer or Feral Bucks in Semi-Arid Queensland

A strong world demand and current firm prices for goat meat provides opportunities for some wool/beef production enterprises in western Queensland to increase farm viability through diversification. In particular, there is rising interest in the use of Boer goats to improve productive performance of the Australian feral goat. Pastoral graziers have noted the high prolificacy of feral goats grazed in semi-arid areas, but there is no information on the breeding ability of feral does mated to Boer bucks. Animal production for a consuming world : proceedings of 9th Congress of the Asian-Australasian Association of Animal Production Societies [AAAP] and 23rd Biennial Conference of the Australian Society of Animal Production [ASAP] and 17th Annual Symposium of the University of Sydney, Dairy Research Foundation, [DRF]. 2-7 July 2000, Sydney, Australia.

Evaluating legume species as alternative trap crops to chickpea for management of Helicoverpa spp. (Lepidoptera: Noctuidae) in central Queensland cotton cropping systems

Mounting levels of insecticide resistance within Australian Helicoverpa spp. populations have resulted in the adoption of non-chemical IPM control practices such as trap cropping with chickpea, Cicer arietinum (L.). However, a new leaf blight disease affecting chickpea in Australia has the potential to limit its use as a trap crop. Therefore this paper evaluates the potential of a variety of winter-active legume crops for use as an alternative spring trap crop to chickpea as part of an effort to improve the area-wide management strategy for Helicoverpa spp. in central Queensland’s cotton production region. The densities of Helicoverpa eggs and larvae were compared over three seasons on replicated plantings of chickpea, Cicer arietinum (L.), field pea Pisum sativum (L), vetch, Vicia sativa (L.) and faba bean, Vicia faba (L.). Of these treatments, field pea was found to harbour the highest densities of eggs. A partial life table study of the fate of eggs oviposited on field pea and chickpea suggested that large proportions of the eggs laid on field pea suffered mortality due to dislodgment from the plants after oviposition. Plantings of field pea as a replacement trap crop for chickpea under commercial conditions confirmed the high level of attractiveness of this crop to ovipositing moths. The use of field pea as a trap crop as part of an areawide management programme for Helicoverpa spp. is discussed.

Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model. A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Inferential, non-parametric statistics to assess quality of probabilistic forecast systems

Many statistical forecast systems are available to interested users. In order to be useful for decision-making, these systems must be based on evidence of underlying mechanisms. Once causal connections between the mechanism and their statistical manifestation have been firmly established, the forecasts must also provide some quantitative evidence of `quality’. However, the quality of statistical climate forecast systems (forecast quality) is an ill-defined and frequently misunderstood property. Often, providers and users of such forecast systems are unclear about what ‘quality’ entails and how to measure it, leading to confusion and misinformation. Here we present a generic framework to quantify aspects of forecast quality using an inferential approach to calculate nominal significance levels (p-values) that can be obtained either by directly applying non-parametric statistical tests such as Kruskal-Wallis (KW) or Kolmogorov-Smirnov (KS) or by using Monte-Carlo methods (in the case of forecast skill scores). Once converted to p-values, these forecast quality measures provide a means to objectively evaluate and compare temporal and spatial patterns of forecast quality across datasets and forecast systems. Our analysis demonstrates the importance of providing p-values rather than adopting some arbitrarily chosen significance levels such as p < 0.05 or p < 0.01, which is still common practice. This is illustrated by applying non-parametric tests (such as KW and KS) and skill scoring methods (LEPS and RPSS) to the 5-phase Southern Oscillation Index classification system using historical rainfall data from Australia, The Republic of South Africa and India. The selection of quality measures is solely based on their common use and does not constitute endorsement. We found that non-parametric statistical tests can be adequate proxies for skill measures such as LEPS or RPSS. The framework can be implemented anywhere, regardless of dataset, forecast system or quality measure. Eventually such inferential evidence should be complimented by descriptive statistical methods in order to fully assist in operational risk management.