An analysis of the impact of the Gaia Theory on Ecology and Evolutionary Theory

This paper investigates the impact of ideas published within the Gaia theory (as set out by James Lovelock in 1979), on the study of Ecology and Evolutionary Theory. Developments within both disciplines have been influenced, and shaped by the Gaia theory and the paper discusses these. The development of the Daisyworld model, which highlighted for ecologists the importance of interactions within an ecosystem between the biota and the abiotic world, contributed to the understanding of biodiversity. The Gaia theory also predicted the causal link between increased biodiversity and increasing stability of populations. The Gaian influence on the development of Evolutionary theory can be found in the idea that life on earth works with the abiotic environment as a self-regulatory system. This idea became the foundation of Earth System Science. These developments have had a wider significance to the study and understanding of science in general. The theory has demonstrated the need for a new way of looking at the development and sustainability of life on earth

Analysis of the Management and Costs Associated with Rearing Pregnant Dairy Heifers in the UK from Conception to Calving

Good management of the pregnant heifer is crucial to ensure that she is well grown and healthy and calves down easily before joining the milking herd. This study collected primary data on all aspects of heifer management on 101 UK farms during heifer pregnancy from conception to calving including farm factors and associated costs of system inputs. A cost analysis workbook was developed to calculate the cost of rearing per heifer for each of the study farms. Associations between cost of rearing and farms factors were determined using linear regression and analysis of variance. Heifers had a mean age of conception of 509 d (range 365 - 700 d) and an age at first calving of 784 d (range 639 - 973 d). The mean total cost of rearing during pregnancy was £450.36 (range £153.11 to £784.00) with a mean daily cost of £1.64 (range £0.56 to £2.86). The inputs contributing the most to cost were feed (32.7%), labour (23.8%) and slurry disposal (11.2%). Total purchased and homegrown feed and grazing contributed between 25.5% and 65.4% of total costs with a mean contribution of 43.6%. The cost of rearing was lowest in spring calving herds and highest in all year round calving herds with intermediate values in autumn and multi block calving herds. The main variables influencing the cost were the number of days spent at grass, age at first calving, calving pattern, breed, herd size and region. Each extra day in age at first calving increased the mean cost of rearing during pregnancy by £0.33/d whereas every extra day at grass reduced the cost by £1.75/d

A Study of Dairy Heifer Rearing Practices from Birth to Weaning and Their Associated Costs on UK Dairy Farms

There are many inputs into the dairy replacement herd which impact not only on the cost of rearing heifers from birth to first calving, but also on their future longevity and production potential. This study determined the current cost of rearing dairy heifers in the UK through the calculation and analysis of individual costs on a subset of 102 UK dairy farms. Each farm was visited and an extensive heifer rearing questionnaire was completed. Current heifer rearing practices were recorded to provide insight into critical management decisions. A cost analysis workbook was developed to calculate the costs of inputs in the pre-weaning period for labour, calving, feed, housing, health treatments and vaccinations, waste storage, machinery and equipment, and utilities. The average age at weaning was 62 d. The mean cost of rearing from birth to weaning was £195.19 per heifer with a mean daily cost of £3.14 (excluding the opportunity cost of the calf). This ranged from £1.68 to £6.11 among farms, reflecting major differences in management strategies and efficiency. The highest contribution to total costs came from feed (colostrum, milk, starter and forage) at 48.5% with milk feeding making up the greatest proportion of this at 37.3%. The next major expenses were bedding and labour, contributing 12.3% and 11.2% respectively. Unsurprisingly, delaying age at weaning increased total cost by £3.53 per day. Total costs were on average 45% higher on organic farms than conventional due to higher feed costs and later weaning. Calving pattern also had a strong association with the total cost being lowest with spring calving, intermediate with autumn calving and highest in multi block and all year round calving herds.fals

The management and associated costs of rearing heifers on UK dairy farms from weaning to conception

Dairy heifers only start to produce a return on investment at first calving. The length of the nonproductive rearing period is largely governed by farmer decisions on plane of nutrition and reproduction management. Primary data were collected from 101 dairy farms and a cost analysis workbook developed to calculate individual inputs in each of three periods to determine which management decisions and farm factors have the greatest influence on the total costs associated with rearing. This paper covers weaning until conception. Heifers were weaned at 62 d (range 42 - 112 d) and conceived by 509 d (range 365 - 700 d) giving an average weaning to conception period of 447 ± 60 d (range 253 to 630 d). The mean daily cost of rearing during this period was £1.65 (range £0.75 to £2.97 on different farms) giving a mean total cost of £745.94 per heifer (range £295.32 to £1745.85). This large variation was mostly due to the duration, which was mainly determined by age at first breeding (mean 476 days, range 365 - 700 d). The main contributors to total costs were feed (35.6%), labour (24.7%) and bedding (8.9%). The variables most strongly associated with the total costs were age at conception, calving pattern and breed. A multivariable model predicted an increase in mean cost of £2.26 for each extra day in age at conception. The total cost was highest in herds with all year round calving, intermediate in multi-block and lowest in spring and autumn calving herds, with Friesian x and Jersey herds having the lowest cost of rearing.falsePublished onlin

Anti-microbial Use in Animals: How to Assess the Trade-offs

Antimicrobials are widely used in preventive and curative medicine in animals. Benefits from curative use are clear – it allows sick animals to be healthy with a gain in human welfare. The case for preventive use of antimicrobials is less clear cut with debates on the value of antimicrobials as growth promoters in the intensive livestock industries. The possible benefits from the use of antimicrobials need to be balanced against their cost and the increased risk of emergence of resistance due to their use in animals. The study examines the importance of animals in society and how the role and management of animals is changing including the use of antimicrobials. It proposes an economic framework to assess the trade-offs of anti-microbial use and examines the current level of data collection and analysis of these trade-offs. An exploratory review identifies a number of weaknesses. Rarely are we consistent in the frameworks applied to the economic assessment anti-microbial use in animals, which may well be due to gaps in data or the prejudices of the analysts. There is a need for more careful data collection that would allow information on (i) which species and production systems antimicrobials are used in, (ii) what active substance of antimicrobials and the application method and (iii) what dosage rates. The species need to include companion animals as well as the farmed animals as it is still not known how important direct versus indirect spread of resistance to humans is. In addition, research is needed on pricing antimicrobials used in animals to ensure that prices reflect production and marketing costs, the fixed costs of anti-microbial development and the externalities of resistance emergence. Overall, much work is needed to provide greater guidance to policy, and such work should be informed by rigorous data collection and analysis systems

Integration of production and financial models to analyse the financial impact of livestock diseases: a case study of Schmallenberg virus disease on British and French dairy farms

AIMS AND OBJECTIVES: The aim of the study was to investigate and compare the financial impact of Schmallenberg disease for different dairy production types in the United Kingdom and France. MATERIALS AND METHODS: Integrated production and financial models for dairy cattle were developed and applied to Schmallenberg virus (SBV) disease in a British and French context. The five main production systems that prevail in these two countries were considered. Their respective gross margins measuring the holding's profitability were calculated based on public benchmarking, literature and expert opinion data. A partial budget analysis was performed within each production model to estimate the impact of SBV in the systems modelled. Two disease scenarios were simulated: low impact and high impact. RESULTS: The model gross margin obtained per cow space and year ranged from £1014 to £1484 for the UK and from £1037 to £1890 for France depending on the production system considered. In the UK, the net SBV disease costs in £/cow space/year for an average dairy farm with 100 milking spaces were estimated between £16.3 and £51.4 in the high-impact scenario and between £8.2 and £25.9 in the low-impact scenario. For France, the net SBV disease costs in £/cow space/year ranged from £19.6 to £48.6 in the high-impact scenario and £9.7 to £22.8 in the low-impact scenario, respectively. CONCLUSION: The study illustrates how the combination of production and financial models allows assessing disease impact taking into account differing management and husbandry practices and associated price structures in the dairy sector. It supports decision-making of farmers and veterinarians who are considering disease control measures as it provides an approach to estimate baseline disease impact in common dairy production systems in the UK and France

The transmission of nosocomial pathogens in an intensive care unit: a space–time clustering and structural equation modelling approach

We investigated the incidence of cases of nosocomial pathogens and risk factors in an intensive treatment unit ward to determine if the number of cases is dependent on location of patients and the colonization/infection history of the ward. A clustering approach method was developed to investigate the patterns of spread of cases through time for five microorganisms [methicillin-resistant Staphylococcus aureus (MRSA), Acinetobacter spp., Klebsiella spp., Candida spp., and Pseudomonas aeruginosa] using hospital microbiological monitoring data and ward records of patient-bed use. Cases of colonization/infection by MRSA, Candida and Pseudomonas were clustered in beds and through time while cases of Klebsiella and Acinetobacter were not. We used structural equation modelling to analyse interacting risk factors and the potential pathways of transmission in the ward. Prior nurse contact with colonized/infected patients, mediated by the number of patient-bed movements, were important predictors for all cases, except for those of Pseudomonas. General health and invasive surgery were significant predictors of cases of Candida and Klebsiella. We suggest that isolation and bed movement as a strategy to manage MRSA infections is likely to impact upon the incidence of cases of other opportunist pathogen