Poisoning for production: how effective is fox baiting in south-eastern Australia?

1. The European red fox Vulpes vulpes represents a continuing threat to both livestock and native vertebrates in Australia, and is commonly managed by setting ground-level baits impregnated with 1080 (sodium fluoroacetate) poison. However, the long-term effectiveness of such control campaigns is likely to be limited due to the ability of foxes to disperse over considerable distances and to swiftly recolonize areas from where they had been removed. 2. To investigate the effectiveness of fox baiting in a production landscape, we assessed the potential for foxes to reinvade baited farm property areas within the jurisdiction of the Molong Rural Lands Protection Board (RLPB), an area of 815 000 ha on the central tablelands of New South Wales, Australia. The spatial distribution and timing of fox baiting campaigns between 1998 and 2002 was estimated from RLPB records and mapped using Geographical Information System software. The effectiveness of the control campaign was assessed on the basis of the likely immigration of foxes from non-baited farms using immigration distances calculated from published relationships between dispersal distance and home range size. 3. Few landholders undertook baiting campaigns in any given year, and the area baited was always so small that no baited property would have been sufficiently far from an unbaited property to have been immune from immigrating individuals. It is likely, therefore, that immigration onto farms negated any long-term effects of baiting operations. This study highlights some of the key deficiencies in current baiting practices in south-eastern Australia and suggests that pest management programmes should be monitored using such methods to ensure they achieve their goals.

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.

Laboratory information management software for genotyping workflows: Applications in high throughput crop genotyping

Background: With the advances in DNA sequencer-based technologies, it has become possible to automate several steps of the genotyping process leading to increased throughput. To efficiently handle the large amounts of genotypic data generated and help with quality control, there is a strong need for a software system that can help with the tracking of samples and capture and management of data at different steps of the process. Such systems, while serving to manage the workflow precisely, also encourage good laboratory practice by standardizing protocols, recording and annotating data from every step of the workflow Results: A laboratory information management system (LIMS) has been designed and implemented at the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that meets the requirements of a moderately high throughput molecular genotyping facility. The application is designed as modules and is simple to learn and use. The application leads the user through each step of the process from starting an experiment to the storing of output data from the genotype detection step with auto-binning of alleles; thus ensuring that every DNA sample is handled in an identical manner and all the necessary data are captured. The application keeps track of DNA samples and generated data. Data entry into the system is through the use of forms for file uploads. The LIMS provides functions to trace back to the electrophoresis gel files or sample source for any genotypic data and for repeating experiments. The LIMS is being presently used for the capture of high throughput SSR (simple-sequence repeat) genotyping data from the legume (chickpea, groundnut and pigeonpea) and cereal (sorghum and millets) crops of importance in the semi-arid tropics. Conclusions: A laboratory information management system is available that has been found useful in the management of microsatellite genotype data in a moderately high throughput genotyping laboratory. The application with source code is freely available for academic users and can be downloaded from http://www.icrisat.org/bt-software-d-lims.htm

Internet based spatial data delivery and reporting system for cotton industry

Development of an internet based spatial data delivery and reporting system for the Australian Cotton Industry.

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.