Angela M. Lees

Enhancing the Teaching and Learning of Biometeorology in Higher Education

This meeting was the result of a 2015 proposal to the Tromp Foundation (foundation for biometeorological research) within the International Society of Biometeorology (ISB) where opportunities were identified for gaining critical insight into the prospects of the incorporation of biometeorology into higher education. Specific topics were highlighted regarding how to effectively integrate biometeorological concepts, learning modules, and pedagogical techniques into undergraduate and graduate courses and curricula worldwide—and to learn the best practices by which to do so.

Isolation of Nocardia mexicana from focal proliferative tenosynovitis and arthritis in a steer

CASE REPORT An 18-month-old Charolais steer was presented with lameness and fluctuant swelling of the right stifle joint, which yielded neutrophils on fine-needle aspiration. A diagnosis of bacterial proliferative tenosynovitis and arthritis was made on postmortem and histological examination. Culture and 16S rRNA sequencing identified a Nocardia sp. with 99% homology with the corresponding DNA fragment of N. mexicana DSM 44952. Antimicrobial susceptibility testing revealed the isolate was susceptible to co-trimoxazole and third-generation cephalosporins. CONCLUSION We report the first case, both in Australia and internationally, of proliferative tenosynovitis and arthritis caused by Nocardia spp. infection in a bovine and the first report of pathology attributed to N. mexicana in a veterinary patient. Given the limited susceptibility of the bacteria, the poor antimicrobial penetration that would be expected and the morphological changes that had taken place in the joint; the steer would have required protracted antimicrobial treatment in addition to invasive debridement of the lesion. This case emphasises the importance of routinely performing cytology and extended incubation of cultures in cases of arthritis in order to make ethical and economically viable treatment decisions.

Assessment of the carbon footprint of four commercial dairy production systems in Australia using an integrated farm system model

ABSTRACT Integrated farm system model (IFSM) is a cost effective and efficient method of estimating greenhouse gas (GHG) emissions from dairy farms and analyzing how management strategies affect these emissions. An IFSM (DairyGHG model) was employed in this study to predict the GHG emission and assess the carbon footprints of four dairy farms in Southeast Queensland, Australia. Four representative commercial farms were selected: Farm 1 (220 cows; Jersey), Farm 2 (460 cows; Holstein Friesian), Farm 3 (850 cows; Holstein Friesian) and Farm 4 (434 cows; Holstein Friesian). The animal emission contribution to carbon footprints for Farm 1, 2, 3 and 4 were 54.2, 60.0, 59.6 and 38.6 % respectively for total output. Likewise the manure emission contribution to carbon footprints for Farm 1, 2, 3 and 4 were 30.6, 29.0, 29.0 and 58.3 % respectively. On the basis of per kg of energy corrected milk the amount of GHG produced for Farm 1, 2, 3 and 4 are 0.39 kg CO2Eq, 0.64 kg CO2Eq, 0.54 kg CO2Eq and 1.35 kg CO2Eq respectively. The method and database developed for these dairy farm GHG assessments may be considered an important step towards a harmonized methodology for the quantification of emissions in dairy farms.

Adaptive Mechanisms of Sheep to Climate Change

Sheep rearing is the most integral part of animal production particularly in tropical regions. Climate change is observed to have devastating effects on sheep farming through constraints such as heat stress, lower grazing lands, water scarcity and higher pest and disease incidences. These environmental constraints may lead to compromised productive functions in sheep. The cumulative effects of heat, nutritional and walking stress occurring in the hotter parts of the year compromise the productive and reproductive performances of the sheep through reduced feed intake, modified endocrine profile, lower rumination and nutrient absorption and higher maintenance demands.

Management Strategies to Reduce Heat Stress in Sheep

Sheep are an important socio-economic activity in many countries, where sheep are produced for the production of protein and fibre resources. Heat stress is a worldwide phenomenon that is associated with reduced animal productivity and welfare, particularly during the summer months. Animal responses to their thermal environment are extremely varied. Given the socio-economic role of sheep in developing nations, it is important to ensure sustainable production during all seasons. However, it is clearly evident that the thermal environment plays a significant role in influencing livestock productivity and well-being. The impact of heat stress on sheep production is likely to continue into the future due to climate change. The impact of climate change on sheep populations will be somewhat confounded by producer selection for increased growth and production traits. However with improved management the impact of heat stress on sheep can be minimised. The purpose of this chapter is to provide information regarding the management of sheep to reduce the negative impact of heat stress.

Measurement of Severity of Heat Stress in Sheep

Animals show optimum growth, health, and productivity within a range of environmental temperatures. Exposure of the sheep to higher temperature leads to heat stress, which negatively affects their well-being and productivity. In addition to ambient temperature (AT), other climatic factors like humidity (RH), wind speed (WS), and solar radiation (SR) also influence the degree of heat stress in sheep. Further, climate change caused a higher rate of temperature increase in the tropical region. Hence, there is an urgent necessity to develop a simple, reliable, and easy method to assess the degree of heat stress in sheep particularly during summer. In the mid-twentieth century, temperature-humidity index (THI) was introduced to evaluate the severity of summer stress and was extended to dairy animals as a tool to explain the welfare of the animals. Moreover, several THI equations were developed by various scientists based on prevailing AT and RH. However, the main drawback of the THI was that it did not account for other weather parameters like WS and SR, even though they also equally influenced the level of heat stress in animals. Research efforts pertain to establishing a suitable thermal index by incorporating all cardinal weather parameters. With this background, heat load index (HLI) was developed as an alternative to THI relating RH, WS, and black-globe temperature (accounts both AT and SR). The few other modern indices available to assess the severity of heat stress in sheep are black-globe temperature-humidity index (BGTHI), thermal comfort index (TCI), and global comprehension index (GCI). In addition to weather indices, some physiological indices are also used to assess heat stress in sheep. Physiological responses like rectal temperature and respiration rate are considered as good indicators of heat stress in sheep. Moreover, strong correlations between blood parameters like hemoglobin, packed cell volume, and endocrine parameters such as cortisol and thyroid hormones production are well established in sheep. Further, genomics and proteomics tools are providing advanced options to evaluate the adaptation processes of sheep. Some of the genes identified in sheep during heat stress are heat shock protein, heat shock factor-1, thyroid hormone receptor, and prolactin receptor genes. Besides, the identified thermo-tolerant genes could be used as an ideal marker for assessing the level of heat stress and may be further utilized for marker-assisted selection breeding programs to develop superior thermo-tolerant breeds.

Modeling of Greenhouse Gas Emission from Livestock

The effects of climate change on humans and other living ecosystems is an area of on-going research. The ruminant livestock sector is considered to be one of the most significant contributors to the existing greenhouse gas (GHG) pool. However the there are opportunities to combat climate change by reducing the emission of GHGs from ruminants. Methane (CH4) and nitrous oxide (N2O) are emitted by ruminants via anaerobic digestion of organic matter in the rumen and manure, and by denitrification and nitrification processes which occur in manure. The quantification of these emissions by experimental methods is difficult and takes considerable time for analysis of the implications of the outputs from empirical studies, and for adaptation and mitigation strategies to be developed. To overcome these problems computer simulation models offer substantial scope for predicting GHG emissions. These models often include all farm activities while accurately predicting the GHG emissions including both direct as well as indirect sources. The models are fast and efficient in predicting emissions and provide valuable information on implementing the appropriate GHG mitigation strategies on farms. Further, these models help in testing the efficacy of various mitigation strategies that are employed to reduce GHG emissions. These models can be used to determine future adaptation and mitigation strategies, to reduce GHG emissions thereby combating livestock induced climate change.