Pen parameters for improving the performance of sheep imported from Australia to Persian Gulf feedlots

Summer in the Persian Gulf region presents physiological challenges for Australian sheep that are part of the live export supply chain coming from the Australian winter. Many feedlots throughout the Gulf have very high numbers of animals during June to August in order to cater for the increased demand for religious festivals. From an animal welfare perspective it is important to understand the necessary requirements of feed and water trough allowances, and the amount of pen space required, to cope with exposure to these types of climatic conditions. This study addresses parameters that are pertinent to the wellbeing of animals arriving in the Persian Gulf all year round. Three experiments were conducted in a feedlot in the Persian Gulf between March 2010 and February 2012, totalling 44 replicate pens each with 60 or 100 sheep. The applied treatments covered animal densities, feed-bunk lengths and water trough lengths. Weights, carcass attributes and health status were the key recorded variables. Weight change results showed superior performance for animal densities of ≥1.2 m2/head during hot conditions (24-h average temperatures greater than 33 °C, or a diurnal range of around 29–37 °C). However the space allowance for animals can be decreased, with no demonstrated detrimental effect, to 0.6 m2/head under milder conditions. A feed-bunk length of ≥5 cm/head is needed, as 2 cm/head showed significantly poorer animal performance. When feeding at 90% ad libitum 10 cm/head was optimal, however under a maintenance feeding regime (1 kg/head/day) 5 cm/head was adequate. A minimum water trough allowance of 1 cm/head is required. However, this experiment was conducted during milder conditions, and it may well be expected that larger water trough lengths would be needed in hotter conditions. Carcass weights were determined mainly by weights at feedlot entry and subsequent weight gains, while dressing percentage was not significantly affected by any of the applied treatments. There was no demonstrated effect of any of the treatments on the number of animals that died, or were classified as unwell. However, across all the treatments, these animals lost significantly more weight than the healthy animals, so the above recommendations, which are aimed at maintaining weight, should also be applicable for good animal health and welfare. Therefore, best practice guidelines for managing Australian sheep in Persian Gulf feedlots in the hottest months (June–August) which present the greatest environmental and physical challenge is to allow feed-bunk length 5 cm/head on a maintenance-feeding program and 10 cm/head for 90% ad libitum feeding, and the space allowance per animal should be ≥1.2 m2/head. Water trough allocation should be at least 1 cm/head with provision for more in the summer when water intake potentially doubles.

Estimation and evaluation of multi-decadal fire severity patterns using Landsat sensors

Retrospective identification of fire severity can improve our understanding of fire behaviour and ecological responses. However, burnt area records for many ecosystems are non-existent or incomplete, and those that are documented rarely include fire severity data. Retrospective analysis using satellite remote sensing data captured over extended periods can provide better estimates of fire history. This study aimed to assess the relationship between the Landsat differenced normalised burn ratio (dNBR) and field measured geometrically structured composite burn index (GeoCBI) for retrospective analysis of fire severity over a 23 year period in sclerophyll woodland and heath ecosystems. Further, we assessed for reduced dNBR fire severity classification accuracies associated with vegetation regrowth at increasing time between ignition and image capture. This was achieved by assessing four Landsat images captured at increasing time since ignition of the most recent burnt area. We found significant linear GeoCBI–dNBR relationships (R2 = 0.81 and 0.71) for data collected across ecosystems and for Eucalyptus racemosa ecosystems, respectively. Non-significant and weak linear relationships were observed for heath and Melaleuca quinquenervia ecosystems, suggesting that GeoCBI–dNBR was not appropriate for fire severity classification in specific ecosystems. Therefore, retrospective fire severity was classified across ecosystems. Landsat images captured within ~ 30 days after fire events were minimally affected by post burn vegetation regrowth.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.