Methane emissions among individual dairy cows during milking quantified by eructation peaks or ratio with carbon dioxide

The aims of this study were to compare methods for examining measurements of CH4 and CO2 emissions of dairy cows during milking and to assess repeatability and variation of CH4 emissions among individual dairy cows. Measurements of CH4 and CO2 emissions from 36 cows were collected in 3 consecutive feeding periods. In the first period, cows were fed a commercial partial mixed ration (PMR) containing 69% forage. In the second and third periods, the same 36 cows were fed a high-forage PMR ration containing 75% forage, with either a high grass silage or high maize silage content. Emissions of CH4 during each milking were examined using 2 methods. First, peaks in CH4 concentration due to eructations during milking were quantified. Second, ratios of CH4 and CO2 average concentrations during milking were calculated. A linear mixed model was used to assess differences between PMR. Variation in CH4 emissions was observed among cows after adjusting for effects of lactation number, week of lactation, diet, individual cow, and feeding period, with coefficients of variation estimated from variance components ranging from 11 to 14% across diets and methods of quantifying emissions. No significant difference was detected between the 3 PMR in CH4 emissions estimated by either method. Emissions of CH4 calculated from eructation peaks or as CH4 to CO2 ratio were positively associated with forage dry matter intake. Ranking of cows according to CH4 emissions on different diets was correlated for both methods, although rank correlations and repeatability were greater for CH4 concentration from eructation peaks than for CH4-to-CO2 ratio. We conclude that quantifying enteric CH4 emissions either using eructation peaks in concentration or as CH4-to-CO2 ratio can provide highly repeatable phenotypes for ranking cows on CH4 output

Variation in enteric methane emissions among cows on commercial dairy farms

Methane (CH4) emissions by dairy cows vary with feed intake and diet composition. Even when fed on the same diet at the same intake, however, variation between cows in CH4 emissions can be substantial. The extent of variation in CH4 emissions among dairy cows on commercial farms is unknown, but developments in methodology now permit quantification of CH4 emissions by individual cows under commercial conditions. The aim of this research was to assess variation among cows in emissions of eructed CH4 during milking on commercial dairy farms. Enteric CH4 emissions from 1,964 individual cows across 21 farms were measured for at least 7 days per cow using CH4 analysers at robotic milking stations. Cows were predominantly of Holstein Friesian breed and remained on the same feeding systems during sampling. Effects of explanatory variables on average CH4 emissions per individual cow were assessed by fitting a linear mixed model. Significant effects were found for week of lactation, daily milk yield and farm. The effect of milk yield on CH4 emissions varied among farms. Considerable variation in CH4 emissions was observed among cows after adjusting for fixed and random effects, with the coefficient of variation ranging from 22 to 67% within farms. This study confirms that enteric CH4 emissions vary among cows on commercial farms, suggesting that there is considerable scope for selecting individual cows and management systems with reduced emissions

Measuring enteric methane emissions from individual ruminant animals in their natural environment

Ruminant livestock are an important source of meat, milk, fiber, and labor for humans. The process by which ruminants digest plant material through rumen fermentation into useful product results in the loss of energy in the form of methane gas from consumed organic matter. The animal removes the methane building up in its rumen by repeated eructations of gas through its mouth and nostrils. Ruminant livestock are a notable source of atmospheric methane, with an estimated 17% of global enteric methane emissions from livestock. Historically, enteric methane was seen as an inefficiency in production and wasted dietary energy. This is still the case, but now methane is seen more as a pollutant and potent greenhouse gas. The gold standard method for measuring methane production from individual animals is a respiration chamber, which is used for metabolic studies. This approach to quantifying individual animal emissions has been used in research for over 100 years; however, it is not suitable for monitoring large numbers of animals in their natural environment on commercial farms. In recent years, several more mobile monitoring systems discussed here have been developed for direct measurement of enteric methane emissions from individual animals. Several factors (diet composition, rumen microbial community, and their relationship with morphology and physiology of the host animal) drive enteric methane production in ruminant populations. A reliable method for monitoring individual animal emissions in large populations would allow (1) genetic selection for low emitters, (2) benchmarking of farms, and (3) more accurate national inventory accounting

Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990�2015: a systematic analysis for the Global Burden of Disease Study 2015

Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015. Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60�900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index SDI) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores. Findings We generated 9·3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17·2 billion, 95% uncertainty interval UI 15·4�19·2 billion) and diarrhoeal diseases (2·39 billion, 2·30�2·50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2·36 billion (2·35�2·37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20�30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo. Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

Determination of the 3D genome organization of bacteria using Hi-C

The spatial organization of genomes is based on their hierarchical compartmentalization in topological domains. There is growing evidence that bacterial genomes are organized into insulated domains similar to the Topologically Associating Domains (TADs) detected in eukaryotic cells. Chromosome conformation capture (3C) technologies are used to analyze in vivo DNA proximity based on ligation of distal DNA segments crossed-linked by bridging proteins. By combining 3C and high-throughput sequencing, the Hi-C method reveals genome-wide interactions within topological domains and global genome structure as a whole. This chapter provides detailed guidelines for the preparation of Hi-C sequencing libraries for bacteria.Macromolecular Biochemistr

The status of routine fishery data collection in Southeast Asia, central America, the South Pacific, and West Africa, with special reference to small-scale fisheries

The Food and Agriculture Organization (FAO) strategy for improving information on the status and trends of capture fisheries (FAO Strategy STF) was endorsed by Member States and the UN General Assembly in 2003. Its overall objective is to provide a framework, strategy, and plan to improve knowledge and understanding of the status and trends of fisheries as a basis for policy-making and management, towards conservation and sustainable use of resources within ecosystems. The FAO supports the implementation of FAO Strategy STF in developing countries through a project known as FAO FishCode–STF, and an initiative funded by the World Bank entitled the “BigNumbers project”. The BigNumbers project underscored the importance of small-scale fisheries and revealed that catches by and employment in this sector tend to be underreported. An inventory of data collection systems made under the FAO FishCode–STF project showed that small-scale fisheries are not well covered. Their dispersed nature, the weak institutional capacity in many developing countries, and the traditional methods used make routine data collection cumbersome. Innovative sampling strategies are required. The main priority is a sample frame for small-scale fisheries. Sustainable strategies are most likely to be found outside the sector through population and agricultural household censuses and inside the sector through the direct involvement of fishers