Genotype effects on body temperature in dairy cows under grazing conditions in a hot climate including evidence for heterosis

We compared diurnal patterns of vaginal temperature in lactating cows under grazing conditions to evaluate genotype effects on body temperature regulation. Genotypes evaluated were Holstein, Jersey, Jersey x Holstein and Swedish Red x Holstein. The comparison of Holstein and Jersey versus Jersey x Holstein provided a test of whether heterosis effects body temperature regulation. Cows were fitted with intravaginal temperature recording devices that measured vaginal temperature every 15 min for 7 days. Vaginal temperature was affected by time of day (P < 0.0001) and genotype x time (P < 0.0001) regardless of whether days in milk and milk yield were used as covariates. Additional analyses indicated that the Swedish Red x Holstein had a different pattern of vaginal temperatures than the other three genotypes (Swedish Red x Holstein vs others x time; P < 0.0001) and that Holstein and Jersey had a different pattern than Jersey x Holstein [(Holstein + Jersey vs Jersey x Holstein) x time, P < 0.0001]. However, Holstein had a similar pattern to Jersey [(Holstein vs Jersey) x time, P > 0.10]. These genotype x time interactions reflect two effects. First, Swedish Red x Holstein had higher vaginal temperatures than the other genotypes in the late morning and afternoon but not after the evening milking. Secondly, Jersey x Holstein had lower vaginal temperatures than other genotypes in the late morning and afternoon and again in the late night and early morning. Results point out that there are effects of specific genotypes and evidence for heterosis on regulation of body temperature of lactating cows maintained under grazing conditions and suggest that genetic improvement for thermotolerance through breed choice or genetic selection is possible.

An occupational view of the Australian labour force - Patterns of job growth and decline

Generally employment has been studied in terms of changes in the types of goods and services that the economy is purchasing. Far less attention has been given to the occupational aggregates that go into producing these goods and services. The few studies that did investigate this area found that the mix of tabour inputs appear to have been changing over time in a systematic pattern. The increasing prevalence of white-collar, information workers gave rise to the assertion that many societies had entered a post-industrial information age. Deals first of aff with some issues of measurement in the context of the Australian labour force, then looks at trends in various occupational groups using a non-standard four-sector classification of the labour force. Finally suggests an application in relation to the link between education and training and its ability to reduce structural unemployment.

Factors influencing job valuation: a comparative study of critical care and mon-critical care nurses

This study sought to identify the relationship between three predictor variables. perceived collaboration with medical staff, autonomy and independent actions and an outcome. the value hospital nurses placed on their work. In total 189 critical care and 366 non-critical care nurses completed a mailed survey. Critical cure nurses perceived themselves to have a mure collaborative relationship with the medical staff. described performing actions independent of medical orders more frequently and perceived their jobs to have more value than non-critical care nurses. However the latter group perceived themselves to have more autonomy in their work. Within both groups collaboration and autonomy were significantly, but weak to moderately correlated with job valuation. Simply expanding the work hospital nurses do is unlikely to result in nurses valuing their jobs more. however promoting an environment of respect and sharing between the medical and nursing staff and supporting nurses when they act in an autonomous fashion may positively influence nurses' perceptions of their work. (C) 2001 Elsevier Science Ltd. All rights reserved.

Autonomy: an important component for nurses' job satisfaction

This quantitative pilot study (n = 178), conducted in a large Brisbane teaching hospital in Australia, found autonomy to be the most important job component for registered nurses' job satisfaction. The actual level of satisfaction with autonomy was 4.6, on a scale of 1 for very dissatisfied to 7 for very satisfied. The mean for job satisfaction was 4.3, with the job components professional status and interaction adding most substantially to the result. There was discontentment with the other two job components, which were Cask requirements and organisational policies. Demographic comparisons showed that nurses who were preceptors had significantly less job satisfaction than the other nurses at the hospital. (C) 2001 Elsevier Science Ltd. All rights reserved.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

Aggregated personality, climate and demographic factors as predictors of departmental shrinkage

The present study investigated how demographic, personality, and climate variables act to predict departmental theft. Participants in the current field survey were 153 employees from 17 departments across two stores. The results of confirmatory factor analyses supported the construct validity of the Big Five Inventory (John, Donahue, & Kentle, 1991) and the Occupational Climate Questionnaire (Furnham & Gunter, 1997) in UK work settings. The results of regression analysis indicate that the variability in departmental theft is accountable in terms of a linear combination of demographic, personality, and climate factors. We concluded that an expanded theoretical perspective (utilizing demographic, personality, and climate variables) explained more variance than might otherwise be expected from any single perspective. Indeed, climate, personality, and demographic variables operated legitimately at the departmental level. Finally, we explained aggregated personality as a form of social interaction which is the by-product of individual differences.

Global job satisfaction and facet description: The moderating role of facet importance

Recent research support sLocke's (1976) model of facet satisfaction in which the range of affect of objectively defined facet descriptions is moderated by subjective evaluations of facet importance (McFarlin & Rice, 1992). This study examined the utility of Locke's moderated model of face t satisfaction for the prediction of organizationally important global measures of job satisfaction. A large dataset of two groups of workers allowed testing over different time periods and across a broad range of satisfaction measures. The hypothesis derived from Locke's model, that global satisfaction would represent a linear function of facet satisfaction (i.e., facet description x facet importance), was not supported. Instead, a simple (have-want) discrepancy model (operationalized as facet description) provided the most consistent set of predictors. The results suggests that workers, when providing global measures of job satisfaction, may use cognitive heuristics to reduce the complexity of facet description x importance calculations. The implications of these data for Locke's model and directions for future research are outlined.

Do personality factors predict job satisfaction?

Two studies investigated the relationships between personality traits and aspects of job satisfaction. In Study 1, job applicants (n=250) completed the Eysenck Personality Profiler and the Work Values Questionnaire (WVQ), which requires respondents to rate various work-related facets according to the extent to which they contribute to their job satisfaction. These facets were combined into two composites (hygiene and motivator) based on previous research. The three personality superfactors accounted for a small percentage of the variance in importance ratings (about 5%). In Study 2, employees (n=82) completed a measure of the 'Big Five' personality traits and the Job Satisfaction Questionnaire (JSQ), which assesses both what respondents consider as important in their work environment as well as their satisfaction with their current job. Importance ratings were again combined into two composites while job satisfaction ratings were factor analyzed and three factors, differentiated along hygiene versus motivator lines, emerged. Personality traits again accounted for a small percentage of the total variance both in importance ratings and in levels of job satisfaction. It is concluded that personality does not have a strong or consistent influence either on what individuals perceive as important in their work environment or on their levels of job satisfaction. (C) 2002 Published by Elsevier Science Ltd.

Infusing the use of seasonal climate forecasting into crop management practice in North East Australia using discussion support software

Seasonal climate forecasting offers potential for improving management of crop production risks in the cropping systems of NE Australia. But how is this capability best connected to management practice? Over the past decade, we have pursued participative systems approaches involving simulation-aided discussion with advisers and decision-makers. This has led to the development of discussion support software as a key vehicle for facilitating infusion of forecasting capability into practice. In this paper, we set out the basis of our approach, its implementation and preliminary evaluation. We outline the development of the discussion support software Whopper Cropper, which was designed for, and in close consultation with, public and private advisers. Whopper Cropper consists of a database of simulation output and a graphical user interface to generate analyses of risks associated with crop management options. The charts produced provide conversation pieces for advisers to use with their farmer clients in relation to the significant decisions they face. An example application, detail of the software development process and an initial survey of user needs are presented. We suggest that discussion support software is about moving beyond traditional notions of supply-driven decision support systems. Discussion support software is largely demand-driven and can compliment participatory action research programs by providing cost-effective general delivery of simulation-aided discussions about relevant management actions. The critical role of farm management advisers and dialogue among key players is highlighted. We argue that the discussion support concept, as exemplified by the software tool Whopper Cropper and the group processes surrounding it, provides an effective means to infuse innovations, like seasonal climate forecasting, into farming practice. Crown Copyright (C) 2002 Published by Elsevier Science Ltd. All rights reserved.

Ecological responses to recent climate change

There is now ample evidence of the ecological impacts of recent climate change, from polar terrestrial to tropical marine environments. The responses of both flora and fauna span an array of ecosystems and organizational hierarchies, from the species to the community levels. Despite continued uncertainty as to community and ecosystem trajectories under global change, our review exposes a coherent pattern of ecological change across systems. Although we are only at an early stage in the projected trends of global warming, ecological responses to recent climate change are already clearly visible.