Formative evaluation to benchmark and improve climate-based decision support for graziers in Western Queelsland

Researchers developing climate-based forecasts, workshops, software tools and information to aid grazier decisions undertook an evaluation study to enhance planning and benchmark impact. One hundred graziers in Western Queensland were randomly selected from 7 shires and surveyed by mail and telephone (43 respondents) to explore levels of knowledge and use of climate information, practices and information needs. We found 36% of respondents apply the Southern Oscillation Index to property decisions but 92% were unaware El Niño Southern Oscillation’s predictive signal in the region is greater for pasture growth than rainfall, suggesting they may not recognise the potential of pasture growth forecasts. Almost 75% of graziers consider they are conservative or risk averse in their attitude to managing their enterprise. Mail respondents (n= 20) if given a 68%, on average, probability of exceeding median rainfall forecast may change a decision; almost two-thirds vary stocking rate based on forage available, last year’s pasture growth or the Southern Oscillation Index; the balance maintain a constant stocking rate strategy; 90% have access to a computer; 75% to the internet and 95% have a fax. This paper presents findings of the study and draws comparisons with a similar study of 174 irrigators in the Northern Murray-Darling Basin (Aust. J. Exp. Ag. 44, 247-257). New insights and information gained are helping the team better understand client needs and plan, design and extend tools and information tailored to grazier knowledge, practice, information needs and preferences. Results have also provided a benchmark against which to measure project impact and have influenced the team to make important changes to their project planning, activities and methods for transferring technology tailored to grazier preferences.

Predicting wood value in Queensland Caribbean pine plantations using a decision support system

A decision support system has been developed in Queensland to evaluate how changes in silvicultural regimes affect wood quality, and specifically the graded recovery of structural timber. Models of tree growth, branch architecture and wood properties were developed from data collected in routine Caribbean pine plantations and specific silvicultural experiments. These models were incorporated in software that simulates the conversion of standing trees into logs, and the logs into boards, and generates detailed data on knot location and basic density distribution. The structural grade of each board was determined by simulating the machine stress-grading process, and the predicted graded recovery provided an indicator of wood value. The decision support system improves the basis of decision-making by simulating the performance of elite genetic material under specified silvicultural regimes and by predicting links between wood quality and general stand attributes such as stocking and length of rotation.

Post capture necrosis of the feet caused by soft-catch traps – incidents, cause and prevention.

When recapturing satellite collared wild dogs that had been trapped one month previous in padded foothold traps, we noticed varying degrees of pitting on the pads of their trapped paw. Veterinary advice, based on images taken of the injuries, suggests that the necrosis was caused by vascular compromise. Five of six dingoes we recaptured had varying degrees of necrosis restricted only to the trapped foot and ranging from single 5 mm holes to 25% sections of the toe pads missing or deformed, including loss of nails. The traps used were rubber-padded, two–coiled, Victor Soft Catch #3 traps. The springs are not standard Victor springs but were Beefer springs; these modifications slightly increase trap speed and the jaw pressure on the trapped foot. Despite this modification the spring pressure is still relatively mild in comparison to conventional long spring or four-coiled wild dog traps. The five wild dogs developing necrosis were trapped in November 2006 at 5-6 months of age. Traps were checked each morning so the dogs were unlikely to have been restrained in the trap for more than 12 hours. All dogs exhibited a small degree of paw damage at capture which presented itself as a swollen paw and compression at the capture point. In contrast, eight wild dogs, 7-8 month-old, were captured two months later in February. Upon their release, on advice from a veterinarian, we massaged the trapped foot to get blood flow back in to the foot and applied a bruise treatment (Heparinoid 8.33 mg/ml) to assist restoring blood flow. These animals were subsequently recaptured several months later and showed no signs of necrosis. While post-capture foot injuries are unlikely to be an issue in conventional control programs where the animal is immediately destroyed, caution needs to be used when releasing accidentally captured domestic dogs or research animals captured in rubber-padded traps. We have demonstrated that 7-8 month old dogs can be trapped and released without any evidence of subsequent necrosis following minimal veterinary treatment. We suspect that the rubber padding on traps may increase the tourniquet effect by wrapping around the paw and recommend the evaluation of offset laminated steel jaw traps as an alternative. Offset laminated steel jaw traps have been shown to be relatively humane producing as few foot injuries as rubber-jawed traps.

A Practitioner-Oriented Decision Support Process for Forestry Pest Management

The article discusses a new decision support process for forestry pest management. Over the past few years, DSS have been introduced for forestry pest management, providing forest growers with advice in areas such as selecting the most suitable pesticide and relevant treatment. Most of the initiatives process knowledge from various domains for providing support for specific decision making problems. However, very few studies have identified the requirements of developing a combined process model in which all relevant practitioners can contribute and share knowledge for effective decision making; such an approach would need to include the decision makers’ perspective along with other relevant attributes such as the problem context and relevant policies. We outline a decision support process for forestry pest management, based on the design science research paradigm, in which a focus group technique has application to acquire both expert and practical knowledge in order to construct the DSS solution.

Giant mud crab (Scylla serrata): Relative efficiencies of common baited traps and impacts on discards

This study was initiated in response to a scarcity of data on the efficiency, selectivity and discard mortality of baited traps to target Scylla serrata. Five replicates of four traps, including "hoop nets", rigid "wire pots", and collapsible "round" and "rectangular" pots were deployed for 3, 6 and 24 h in two Australian estuaries. Trapped S. serrata were "discarded" into cages and monitored with controls over 3 d. All S. serrata were assessed for damage, while subsets of immediately caught and monitored individuals had haemolymph constituents quantified as stress indices. All traps retained similar-sized (8.119.1 cm carapace width) S. serrata, with catches positively correlated to deployment duration. Round pots were the most efficient for S. serrata and fishmostly Acanthopagrus australis (3 mortality). Hoop nets were the least efficient and were often damaged. No S. serrata died, but 18 were wounded (biased towards hoop nets), typically involving a missing swimmeret. Physiological responses were mild and mostly affected by biological factors. The results validate discarding unwanted S. serrata for controlling exploitation, but larger mesh sizes or escape vents in pots and restrictions on hoop nets would minimise unnecessary catches, pollution and ghost fishing. © 2012 International Council for the Exploration of the Sea. Published by Oxford University Press. All rights reserved.

AQUAMAN: a web-based decision support system for irrigation scheduling in peanuts

Peanut (Arachis hypogaea L.) is an economically important legume crop in irrigated production areas of northern Australia. Although the potential pod yield of the crop in these areas is about 8 t ha(-1), most growers generally obtain around 5 t ha(-1), partly due to poor irrigation management. Better information and tools that are easy to use, accurate, and cost-effective are therefore needed to help local peanut growers improve irrigation management. This paper introduces a new web-based decision support system called AQUAMAN that was developed to assist Australian peanut growers schedule irrigations. It simulates the timing and depth of future irrigations by combining procedures from the food and agriculture organization (FAO) guidelines for irrigation scheduling (FAO-56) with those of the agricultural production systems simulator (APSIM) modeling framework. Here, we present a description of AQUAMAN and results of a series of activities (i.e., extension activities, case studies, and a survey) that were conducted to assess its level of acceptance among Australian peanut growers, obtain feedback for future improvements, and evaluate its performance. Application of the tool for scheduling irrigations of commercial peanut farms since its release in 2004-2005 has shown good acceptance by local peanuts growers and potential for significantly improving yield. Limited comparison with the farmer practice of matching the pan evaporation demand during rain-free periods in 2006-2007 and 2008-2009 suggested that AQUAMAN enabled irrigation water savings of up to 50% and the realization of enhanced water and irrigation use efficiencies.

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.

Exploring the Potential Impacts of Climate Variability on Spring Wheat Yield with the APSIM Decision Support Tool

Assessing the impacts of climate variability on agricultural productivity at regional, national or global scale is essential for defining adaptation and mitigation strategies. We explore in this study the potential changes in spring wheat yields at Swift Current and Melfort, Canada, for different sowing windows under projected climate scenarios (i.e., the representative concentration pathways, RCP4.5 and RCP8.5). First, the APSIM model was calibrated and evaluated at the study sites using data from long term experimental field plots. Then, the impacts of change in sowing dates on final yield were assessed over the 2030-2099 period with a 1990-2009 baseline period of observed yield data, assuming that other crop management practices remained unchanged. Results showed that the performance of APSIM was quite satisfactory with an index of agreement of 0.80, R2 of 0.54, and mean absolute error (MAE) and root mean square error (RMSE) of 529 kg/ha and 1023 kg/ha, respectively (MAE = 476 kg/ha and RMSE = 684 kg/ha in calibration phase). Under the projected climate conditions, a general trend in yield loss was observed regardless of the sowing window, with a range from -24 to -94 depending on the site and the RCP, and noticeable losses during the 2060s and beyond (increasing CO2 effects being excluded). Smallest yield losses obtained through earlier possible sowing date (i.e., mid-April) under the projected future climate suggested that this option might be explored for mitigating possible adverse impacts of climate variability. Our findings could therefore serve as a basis for using APSIM as a decision support tool for adaptation/mitigation options under potential climate variability within Western Canada.