Climatic-requirements models of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae) to prioritise areas for exploration and release of biological control agents

Climate matching software (CLIMEX) was used to prioritise areas to explore for biological control agents in the native range of cat's claw creeper Macfadyena unguis-cati (Bignoniaceae), and to prioritise areas to release the agents in the introduced ranges of the plant. The native distribution of cat's claw creeper was used to predict the potential range of climatically suitable habitats for cat's claw creeper in its introduced ranges. A Composite Match Index (CMI) of cat's claw creeper was determined with the 'Match Climates' function in order to match the ranges in Australia and South Africa where the plant is introduced with its native range in South and Central America. This information was used to determine which areas might yield climatically-adapted agents. Locations in northern Argentina had CMI values which best matched sites with cat's claw creeper infestations in Australia and South Africa. None of the sites from where three currently prioritised biological control agents for cat's claw creeper were collected had CMI values higher than 0.8. The analysis showed that central and eastern Argentina, south Brazil, Uruguay and parts of Bolivia and Paraguay should be prioritised for exploration for new biological control agents for cat's claw creeper to be used in Australia and South Africa.

Modelling the potential spread of Solenopsis invicta Buren (Hymenoptera: Formicidae) (red imported fire ant) in Australia

Quantifying the potential spread and density of an invading organism enables decision-makers to determine the most appropriate response to incursions. We present two linked models that estimate the spread of Solenopsis invicta Buren (red imported fire ant) in Australia based on limited data gathered after its discovery in Brisbane in 2001. A stochastic cellular automaton determines spread within a location (100 km by 100 km) and this is coupled with a model that simulates human-mediated movement of S. invicta to new locations. In the absence of any control measures, the models predict that S. invicta could cover 763 000–4 066 000 km2 by the year 2035 and be found at 200 separate locations around Australia by 2017–2027, depending on the rate of spread. These estimated rates of expansion (assuming no control efforts were in place) are higher than those experienced in the USA in the 1940s during the early invasion phases in that country. Active control efforts and quarantine controls in the USA (including a concerted eradication attempt in the 1960s) may have slowed spread. Further, milder winters, the presence of the polygynous social form, increased trade and human mobility in Australia in 2000s compared with the USA in 1940s could contribute to faster range expansion.

Patterns in the distribution and abundance of female eastern king prawns, Melicertus plebejus (Hess, 1865), capable of spawning and reproductive potential in waters off

Linear mixed models were used to test the null hypothesis that there were no differences between seasons and locations in the reproductive potential of female eastern king prawns, Melicertus plebejus along the east coast of Australia. Three samples were collected in each season between autumn 1991 and winter 1992 (inclusive). Females capable of spawning were found at all locations but proportions were greater in lower than higher latitudes. Females capable of spawning were not found at the southern (highest latitude) most location in all seasons. There was a significant interaction in reproductive potential between seasons and locations suggesting that patterns among seasons differed between locations and vice versa. Reproductive potential was greatest amongst the northern (lower latitudes) most locations and was greatest in autumn at these locations. Seasonal patterns were less pronounced further south (higher latitudes). The length composition of females in catches differed between locations with more larger prawns found in samples from northern locations. The challenge that remains is to quantify the oceanic sources of larvae that contribute to recruitment in each nursery area and the estuarine sources of juveniles that contribute adults back to the effective spawning stock. Maintaining the effective spawning stock and important nursery areas are crucial to the sustainability of this resource.

Parameter estimation and sensitivity analysis of fat deposition models in beef steers using acslXtreme.

The Davis Growth Model (a dynamic steer growth model encompassing 4 fat deposition models) is currently being used by the phenotypic prediction program of the Cooperative Research Centre (CRC) for Beef Genetic Technologies to predict P8 fat (mm) in beef cattle to assist beef producers meet market specifications. The concepts of cellular hyperplasia and hypertrophy are integral components of the Davis Growth Model. The net synthesis of total body fat (kg) is calculated from the net energy available after accounting tor energy needs for maintenance and protein synthesis. Total body fat (kg) is then partitioned into 4 fat depots (intermuscular, intramuscular, subcutaneous, and visceral). This paper reports on the parameter estimation and sensitivity analysis of the DNA (deoxyribonucleic acid) logistic growth equations and the fat deposition first-order differential equations in the Davis Growth Model using acslXtreme (Hunstville, AL, USA, Xcellon). The DNA and fat deposition parameter coefficients were found to be important determinants of model function; the DNA parameter coefficients with days on feed >100 days and the fat deposition parameter coefficients for all days on feed. The generalized NL2SOL optimization algorithm had the fastest processing time and the minimum number of objective function evaluations when estimating the 4 fat deposition parameter coefficients with 2 observed values (initial and final fat). The subcutaneous fat parameter coefficient did indicate a metabolic difference for frame sizes. The results look promising and the prototype Davis Growth Model has the potential to assist the beef industry meet market specifications.

The potential geographic distribution of the invasive weed Senna obtusifolia in Australia

Senna obtusifolia (sicklepod) is an invasive weed of northern Australia, where it significantly impacts agricultural productivity and alters natural ecosystem structure and function. Although currently restricted to northern regions, the potential for S. obtusifolia to spread south is not known. Using the eco-climatic model CLIMEX, this study simulated the potential geographic distribution of S. obtusifolia in Australia under two scenarios. Model parameters for both scenarios were derived from the distribution of S. obtusifolia throughout North and Central America. The first scenario used these base model parameters to predict the distribution of S. obtusifolia in Australia, whilst the second model predicted the distribution of a cold susceptible S. obtusifolia ecotype that is reported to occur in the USA. Both models predicted the potential for an extensive S. obtusifolia distribution, with the first model indicating suitable climatic conditions occurring predominantly in coastal regions from the Northern Territory, to far north Queensland and into northern Victoria. The cold susceptible ecotype displayed a comparatively reduced distribution in the southern parts of Australia, where inappropriate temperatures, a lack of thermal accumulation and cold stress restrict the invasion south to the coastal regions of central New South Wales. The extent of the predicted distribution of both ecotypes of S. obtusifolia reinforces the need for strategic management at a national scale.

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.

Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.