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.

Responses in carcass lean pH at 24 hours post-mortem in lines of Large White pigs selected for growth rate on a fixed ration over a set time

A restricted maximum likelihood analysis applied to an animal model showed no significant differences (P > 0.05) in pH value of the longissimus dorsi measured at 24 h post-mortem (pH24) between high and low lines of Large White pigs selected over 4 years for post-weaning growth rate on restricted feeding. Genetic and phenotypic correlations between pH24 and production and carcass traits were estimated using all performance testing records combined with the pH24 measurements (5.05-7.02) on slaughtered animals. The estimate of heritability for pH24 was moderate (0.29 ± 0.18). Genetic correlations between pH24 and production or carcass composition traits, except for ultrasonic backfat (UBF), were not significantly different from zero. UBF had a moderate, positive genetic correlation with pH24 (0.24 ± 0.33). These estimates of genetic correlations affirmed that selection for increased growth rate on restricted feeding is likely to result in limited changes in pH24 and pork quality since the selection does not put a high emphasis on reduced fatness.

A review of Australian classical biological control of weeds programs and research activities over the past 12 years

Considerable progress has been made towards the successful classical biological control of many of Australia’s exotic weeds over the past decade. Some 43 new arthropod or pathogen agents were released in 19 projects. Effective biological control was achieved in several projects with the outstanding successes being the control of rubber vine, Cryptostegia grandiflora, and bridal creeper, Asparagus asparagoides. Significant developments also occurred in target prioritization, procedures for target and agent approval, funding, infrastructure and cooperation between agencies. Scientific developments included greater emphasis on climate matching, plant and agent phylogeny, molecular diagnostics, agent prioritization and agent evaluation.

CRC30032 Enhancing surveillance with remotely controlled aircraft

Detecting spores with UAV.

Bacterial and fungal community composition over time in chicken litter with high or low moisture content

1. Changes in bacterial and fungal communities in chicken litter with high and low moisture content over a five week period during a single chicken grow out cycle in a poultry shed in subtropical Australia were investigated to study the association between specific microbes and odour production. 2. Microbial biomass, as indicated by DNA yields, was higher and community composition was more dynamic over time in moist compared with dry chicken litter. 3. Bacillus, Atopostipes and Aspergillus species increased in relative abundance in moist chicken litter samples over time reflecting the relatively high fitness and hence activity of these specific bacteria and this specific fungus in this environment.

Variation in the hindgut microbial communities of the Florida manatee, Trichechus manatus latirostris over winter in Crystal River, Florida

The Florida manatee, Trichechus manatus latirostris, is a hindgut-fermenting herbivore. In winter, manatees migrate to warm water overwintering sites where they undergo dietary shifts and may suffer from cold-induced stress. Given these seasonally induced changes in diet, the present study aimed to examine variation in the hindgut bacterial communities of wild manatees overwintering at Crystal River, west Florida. Faeces were sampled from 36 manatees of known sex and body size in early winter when manatees were newly arrived and then in mid-winter and late winter when diet had probably changed and environmental stress may have increased. Concentrations of faecal cortisol metabolite, an indicator of a stress response, were measured by enzyme immunoassay. Using 454-pyrosequencing, 2027 bacterial operational taxonomic units were identified in manatee faeces following amplicon pyrosequencing of the 16S rRNA gene V3/V4 region. Classified sequences were assigned to eight previously described bacterial phyla; only 0.36% of sequences could not be classified to phylum level. Five core phyla were identified in all samples. The majority (96.8%) of sequences were classified as Firmicutes (77.3 ± 11.1% of total sequences) or Bacteroidetes (19.5 ± 10.6%). Alpha-diversity measures trended towards higher diversity of hindgut microbiota in manatees in mid-winter compared to early and late winter. Beta-diversity measures, analysed through permanova, also indicated significant differences in bacterial communities based on the season.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.