Are dairy cows with a more reactive temperament less efficient in energetic metabolism and do they produce more enteric methane?

It remains unknown whether dairy cows with more reactive temperament produce more enteric methane (CH₄) and are less bioenergetically efficient than the calmer ones. The objectives of this study were (a) to evaluate the relationship between cattle temperament assessed by traditionally used tests with energetic metabolism and enteric CH₄ emissions by crossbred dairy cows; (b) to assess how cows’ restlessness in respiration chambers affects energetic metabolism and enteric CH₄ emissions. Temperament indicators were evaluated for 28 primiparous F1 Holstein-Gyr cows tested singly in the handling corral (entrance time, crush score, flight speed, and flight distance) and during milking (steps, kicks, defecation, rumination, and kick the milking cluster off). Cows’ behaviors within respiration chambers were also recorded for each individual kept singly. Digestibility and calorimetry trials were performed to obtain energy partitioning and CH₄ measures. Cows with more reactive temperament in milking (the ones that kicked the milking cluster off more frequently) spent 25.24% less net energy on lactation (P = 0.04) and emitted 36.77% more enteric CH₄/kg of milk (P = 0.03). Furthermore, cows that showed a higher frequency of rumination at milking parlor allocated 57.93% more net energy for milk production (P < 0.01), spent 50.00% more metabolizable energy for milk production (P < 0.01) and 37.10% less CH₄/kg of milk (P = 0.04). Regarding the handling temperament, most reactive cows according to flight speed, lost 29.16% less energy as urine (P = 0.05) and tended to have 14.30% more enteric CH₄ production (P = 0.08), as well as cows with a lower entrance time (most reactive) that also lost 13.29% more energy as enteric CH₄ (P = 0.04). Temperament and restless behavior of Holstein-Gyr cows were related to metabolic efficiency and enteric CH₄ emissions. Cows’ reactivity and rumination in the milking parlor, in addition to flight speed and entrance time in the squeeze chute during handling in the corral, could be useful measures to predict animals more prone to metabolic inefficiency, which could negatively affect the sustainability of dairy systems.     

Prediction of enteric methane production,yield, and intensity in dairy cattle using an intercontinental database

Enteric methane (CH₄) production from cattle contributes to global greenhouse gas emissions. Measurement of enteric CH₄ is complex, expensive, and impractical at large scales; therefore, models are commonly used to predict CH₄ production. However, building robust prediction models requires extensive data from animals under different management systems worldwide. The objectives of this study were to (1) collate a global database of enteric CH₄ production from individual lactating dairy cattle; (2) determine the availability of key variables for predicting enteric CH₄ production (g/day per cow), yield [g/kg dry matter intake (DMI)], and intensity (g/kg energy corrected milk) and their respective relationships; (3) develop intercontinental and regional models and cross‐validate their performance; and (4) assess the trade‐off between availability of on‐farm inputs and CH₄ prediction accuracy. The intercontinental database covered Europe (EU), the United States (US), and Australia (AU). A sequential approach was taken by incrementally adding key variables to develop models with increasing complexity. Methane emissions were predicted by fitting linear mixed models. Within model categories, an intercontinental model with the most available independent variables performed best with root mean square prediction error (RMSPE) as a percentage of mean observed value of 16.6%, 14.7%, and 19.8% for intercontinental, EU, and United States regions, respectively. Less complex models requiring only DMI had predictive ability comparable to complex models. Enteric CH₄ production, yield, and intensity prediction models developed on an intercontinental basis had similar performance across regions, however, intercepts and slopes were different with implications for prediction. Revised CH₄ emission conversion factors for specific regions are required to improve CH₄ production estimates in national inventories. In conclusion, information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction. For enteric CH₄ yield and intensity prediction, information on milk yield and composition is required for better estimation.     

Effects of dietary addition of cellulase and a Saccharomyces cerevisiae fermentation product on nutrient digestibility,rumen fermentation and enteric methane emissions in growing goats

This study was designed to assess the effectiveness of dietary cellulase (243 U/g, derived from Neocallimastix patriciarum) and a Saccharomyces cerevisiae fermentation product (yeast product) on ruminal fermentation characteristics, enteric methane (CH₄) emissions and methanogenic community in growing goats. The experiment was conducted in a 5 × 5 Latin square design using five Xiangdong black wether goats. The treatments included a Control and two levels of cellulase (0.8 g and 1.6 g/kg dry matter intake (DMI), i.e. 194 U/kg and 389 U/kg DMI, respectively) crossed over with two levels (6 g or 12 g/kg DMI) of the yeast product. There were no significant differences regarding feed intake, apparent digestibility of organic matter, neutral detergent fibre and acid detergent fibre among all the treatments. In comparison with the Control, the ruminal ammonia N concentration was decreased (p = 0.001) by cellulase and yeast product addition. The activities of carboxymethylcellulase and xylanase were decreased after cellulase addition. Moreover, dietary cellulase and yeast product addition led to a significant reduction (p < 0.05) of enteric CH₄ emissions although the diversity and copy numbers of methanogens among treatments were not dissimilar. The present results indicate that the combination of cellulase and yeast fermentation product can reduce the production of CH₄ energy and mitigate the enteric CH₄ emissions to a certain degree.     

Methane emissions from two breeds of beef cows offered diets containing barley straw with either grass silage or brewers’ grains

Increasing the concentration of dietary lipid is a promising strategy for reducing methane (CH₄) emissions from ruminants. This study investigated the effect of replacing grass silage with brewers’ grains on CH₄ emissions of pregnant, non-lactating beef cows of two breeds. The experiment was a two×two factorial design comprising two breeds (LIMx, crossbred Limousin; and LUI, purebred Luing) and two diets consisting of (g/kg diet dry matter (DM)) barley straw (687) and grass silage (301, GS), or barley straw (763) and brewers’ grains (226, BG), which were offered ad libitum. Replacing GS with BG increased the acid-hydrolysed ether extract concentration from 21 to 37 g/kg diet DM. Cows (n=48) were group-housed in equal numbers of each breed across two pens and each diet was allocated to one pen. Before measurements of CH₄, individual dry matter intake (DMI), weekly BW and weekly body condition score were measured for a minimum of 3 weeks, following a 4-week period to acclimatise to the diets. CH₄ emissions were subsequently measured on one occasion from each cow using individual respiration chambers. Due to occasional equipment failures, CH₄ measurements were run over 9 weeks giving 10 observations for each breed×treatment combination (total n=40). There were no differences between diets for daily DMI measured in the chambers (9.92 v. 9.86 kg/day for BG and GS, respectively; P>0.05). Cows offered the BG diet produced less daily CH₄ than GS-fed cows (131 v. 156 g/day: P<0.01). When expressed either as g/kg DMI or kJ/MJ gross energy intake (GEI), BG-fed cows produced less CH₄ than GS-fed cows (13.5 v. 16.4 g/kg DMI, P<0.05; 39.2 v. 48.6 kJ/MJ GEI, P<0.01). Breed did not affect daily DMI or CH₄ expressed as g/day, g/kg DMI or kJ/MJ GEI (P>0.05). However, when expressed as a proportion of metabolic BW (BW^0.75), LUI cows had greater DMI than LIMx cows (84.5 v. 75.7 g DMI/kg BW^0.75, P<0.05) and produced more CH₄ per kg BW^0.75 than LIMx cows (1.30 v. 1.05 g CH₄/kg BW^0.75; P<0.01). Molar proportions of acetate were higher (P<0.001) and propionate and butyrate lower (P<0.01) in rumen fluid samples from BG-fed compared with GS-fed cows. This study demonstrated that replacing GS with BG in barley straw-based diets can effectively reduce CH₄ emissions from beef cows, with no suppression of DMI.     

基于IPCC Tier 1层级的中国反刍家畜胃肠道甲烷排放格局变化分析

依据政府间气候变化委员会(IPCC)2006年公布的反刍家畜胃肠道CH4排放系数(奶牛61 kg CH4头-1a-1,肉役牛47 kg CH4头-1a-1,绵羊和山羊均为5 kg CH4头-1a-1)和IPCC Tier 1计算方法,结合《中国统计年鉴》和《中国畜牧业统计年鉴》,估算了中国以及各个省份1990—2010年CH4的排放总量,绘制出中国反刍家畜胃肠道CH4排放格局及历史变化图。研究结果表明:11990—2010年期间,中国反刍家畜胃肠道CH4排放量(5.90—7.65 Tg)总体呈现先上升(1995年最高)后下降的趋势,其中肉役牛(主要是黄牛和水牛)胃肠道CH4排放量(4.33 Tg)及其所占比例(65%)最大。奶牛胃肠道CH4排放量及其比例呈现逐年增加的趋势,2006年(0.83 Tg,12.7%)超过山羊和绵羊胃肠道CH4排放量及其比例,成为中国反刍家畜胃肠道CH4排放第二大源。但是,奶牛单位产奶量所排放的CH4量逐年降低,表明中国奶牛饲养技术与生产性能不断提高。2中国反刍家畜胃肠道CH4排放格局呈现区域集中特点,主要集中在中西部和北部的各个省份,其中四川、内蒙古、新疆、河南、西藏、山东、河北、黑龙江、云南和甘肃等10个省份的排放量占中国排放总量的50%以上。总之,1990—2010年间,中国反刍家畜胃肠道CH4排放总量为(6.77±0.46)Tg(肉役牛为主要排放源),随时间推移呈现先上升后下降的趋势;中国反刍家畜胃肠道CH4排放的格局呈区域集中分布,中西部和北部的各个省份占60%以上。     

Predictions of methane emission levels and categories based on milk fatty acid profiles from dairy cows

Milk fatty acid (MFA) have already been used to model methane (CH₄) emissions from dairy cows. However, the data sets used to develop these models covered limited variation in dietary conditions, reducing the robustness of the predictions. In this study, a data set containing 140 observations from nine experiments (41 Holstein cows) was used to develop models predicting CH₄ expressed as g/day, g/kg dry matter intake (DMI) and g/kg milk. The data set was divided into a training (n=112) and a test data set (n=28) for model development and validation, respectively. A generalized linear mixed model was fitted to the data using the marginal R²_(m) and the Akaike information criterion to evaluate the models. The coefficient of determination of validation (R²_(v)) for different models developed ranged between 0.18 and 0.41. Form the intake-related parameters, only inclusion of total DMI improved the prediction (R²_(v)=0.58). In addition, in an attempt to further explore the relationships between MFA and CH₄ emissions, the data set was split into three categories according to CH₄ emissions: LOW (lowest 25% CH₄ emissions); HIGH (highest 25% CH₄ emissions); and MEDIUM (50% remaining observations). An ANOVA revealed that concentrations of several MFA differed for observations in HIGH compared with observations in LOW. Furthermore, the Gini coefficient was used to describe the MFA distribution for groups of MFA in each CH₄ emission category. The relative distribution of the MFA, particularly of the odd- and branched-chain fatty acids and mono-unsaturated fatty acids of observations in category HIGH differed from those in the other categories. Finally, in an attempt to validate the potential of MFA to identify cases of high or low emissions, the observations were re-classified into HIGH, MEDIUM and LOW according to the proportion of each individual MFA. The proportion of observations correctly classified were recorded. This was done for each individual MFA and for the calculated Gini coefficients, finding that a maximum of 67% of observations were correctly classified as HIGH CH₄ (trans-12 C18:1) and a maximum of 58% of observations correctly classified as LOW CH₄ (cis-9 C17:1). Gini coefficients did not improve this classification. These results suggest that MFA are not yet reliable predictors of specific amounts of CH₄ emitted by a cow, while holding a modest potential to differentiate cases of high or low emissions.     

Evaluation of nitrogen excretion equations for ryegrass pasture-fed dairy cows

Accurate and precise estimates of nitrogen (N) excretion in faeces and urine of dairy cattle may provide direct tools to improve N management and thus, to mitigate environmental pollution from dairy production. Empirical equations of N excretion have been evaluated for indoor dairy cattle but there is no evaluation for cows fed high proportions of fresh forage. Therefore, the objective of the current study was to evaluate N excretion equations with a unique data set of zero-grazing experiments. Through literature searches, 89 predictive equations were identified from 13 studies. An independent data set was developed from seven zero-grazing experiments with, in total, 55 dairy Holstein-Friesian cows. Models’ performance was evaluated with statistics derived from a mixed-effect model and a simple regression analysis model. Squared sample correlation coefficients were used as indicators of precision and based on either the best linear unbiased predictions (R²_BLUP) or model-predicted estimates (R²_MDP) derived from the mixed model and simple regression analysis, respectively. The slope (β₀), the intercept (β₁) and the root mean square prediction error (RMSPE_m%) were calculated with the mixed-effect model and used to assess accuracy. The root mean square prediction error (RMSPE_sr%) and the decomposition of the mean square prediction error were calculated with the simple regression analysis and were used to estimate the error due to central tendency (mean bias), regression (systematic bias), and random variation. Concordance correlation coefficient (CCC) were also calculated with the simple regression analysis model and were used to simultaneously assess accuracy and precision. Considering both analysis models, results suggested that urinary N excretion (UN; R²_MDP = 0.76, R²_BLUP = 0.89, RMSPE_m% = 17.2, CCC = 0.82), total manure N excretion (ManN; R²_MDP = 0.83, R²_BLUP = 0.90, RMSPE_m% = 11.0, CCC = 0.84) and N apparently digested (NAD; R²_MDP = 0.97, R²_BLUP = 0.97, RMSPE_m% = 5.3, CCC = 0.95) were closely related to N intake. Milk N secretion was better predicted using milk yield as a single independent variable (MilkN; R²_MDP = 0.77, R²_BLUP = 0.97, RMSPE_m% = 6.0, CCC = 0.74). Additionally, DM intake was a good predictor of UN and ManN and dietary CP concentration of UN and ManN. Consequently, results suggest that several evaluated empirical equations can be used to make accurate and precise predictions concerning N excretion from dairy cows being fed on fresh forage.     

Diet supplementation with cinnamon oil,cinnamaldehyde, or monensin does not reduce enteric methane production of dairy cows

This study was conducted to evaluate the effect of dietary addition of cinnamon oil (CIN), cinnamaldehyde (CDH), or monensin (MON) on enteric methane (CH₄) emission in dairy cows. Eight multiparous lactating Holstein cows fitted with ruminal cannulas were used in a replicated 4×4 Latin square design (28-day periods). Cows were fed (ad libitum) a total mixed ration ((TMR); 60 : 40 forage : concentrate ratio, on a dry matter (DM) basis) not supplemented (CTL), or supplemented with CIN (50 mg/kg DM intake), CDH (50 mg/kg DM intake), or monensin (24 mg/kg of DM intake). Dry matter intake (DMI), nutrient digestibility, N retention, and milk performance were measured over 6 consecutive days. Ruminal degradability of the basal diet (with no additive) was assessed using in sacco incubations (0, 2, 4, 8, 16, 24, 48, 72 and 96 h). Ruminal fermentation characteristics (pH, volatile fatty acids (VFA), and ammonia (NH₃)) and protozoa were determined over 2 days. Enteric CH₄ emissions were measured over 6 consecutive days using the sulfur hexafluoride (SF₆) tracer gas technique. Adding CIN, CDH or MON to the diet had no effects on DMI, N retention, in sacco ruminal degradation and nutrient digestibility of the diet. Ruminal fermentation characteristics and protozoa numbers were not modified by including the feed additives in the diet. Enteric CH₄ emission and CH₄ energy losses averaged 491 g/day and 6.59% of gross energy intake, respectively, and were not affected by adding CIN, CDH or MON to the diet. Results of this study indicate that CIN, CDH and MON are not viable CH₄ mitigation strategies in dairy cows.     

Coalescing molecular evolution and DNA barcoding

The DNA barcoding concept (Woese et al. 1990 ; Hebert et al. 2003 ) has considerably boosted taxonomy research by facilitating the identification of specimens and discovery of new species. Used alone or in combination with DNA metabarcoding on environmental samples (Taberlet et al. 2012 ), the approach is becoming a standard for basic and applied research in ecology, evolution and conservation across taxa, communities and ecosystems (Scheffers et al. 2012 ; Kress et al. 2015 ). However, DNA barcoding suffers from several shortcomings that still remain overlooked, especially when it comes to species delineation (Collins & Cruickshank 2012 ). In this issue of Molecular Ecology, Barley & Thomson ( 2016 ) demonstrate that the choice of models of sequence evolution has substantial impacts on inferred genetic distances, with a propensity of the widely used Kimura 2‐parameter model to lead to underestimated species richness. While DNA barcoding has been and will continue to be a powerful tool for specimen identification and preliminary taxonomic sorting, this work calls for a systematic assessment of substitution models fit on barcoding data used for species delineation and reopens the debate on the limitation of this approach.     

The influence of grass silage-to-maize silage ratio and concentrate composition on methane emissions,performance and milk composition of dairy cows

It is well-established that altering the proportion of starch and fibre in ruminant diets can alter ruminal and post-ruminal digestion, although quantitative evidence that this reduces enteric methane (CH₄) production in dairy cattle is lacking. The objective of this study was to examine the effect of varying grass-to-maize silage ratio (70 : 30 and 30 : 70 DM basis), offered ad libitum, with either a concentrate that was high in starch or fibre, on CH₄ production, intake, performance and milk composition of dairy cows. A total of 20 cows were allocated to one of the four experimental diets in a two-by-two factorial design run as a Latin square with each period lasting 28 days. Measurements were conducted during the final 7 days of each period. Cows offered the high maize silage ration had a higher dry matter intake (DMI), milk yield, milk energy output and lower CH₄ emissions when expressed per kg DMI and per unit of ingested gross energy, but there was no difference in total CH₄ production. Several of the milk long-chain fatty acids (FA) were affected by forage treatment with the most notable being an increase in 18:0, 18:1 c9, 18:2 c9 c12 and total mono unsaturated FA, observed in cows offered the higher inclusion of maize silage, and an increase in 18:3 c9 c12 c15 when offered the higher grass silage ration. Varying the composition of the concentrate had no effect on DMI or milk production; however, when the high-starch concentrate was fed, milk protein concentration and milk FAs, 10:0, 14:1, 15:0, 16:1, increased and 18:0 decreased. Interactions were observed for milk fat concentration, being lower in cows offered high-grass silage and high-fibre concentrates compared with the high-starch concentrate, and FA 17:0, which was the highest in milk from cows fed the high-grass silage diet supplemented with the high-starch concentrate. In conclusion, increasing the proportion of maize silage in the diets of dairy cows increased intake and performance, and reduced CH₄ production, but only when expressed on a DM or energy intake basis, whereas starch-to-fibre ratio in the concentrate had little effect on performance or CH₄ production.     

Bacteriophage exclusion,a new defense system

The ability to withstand viral predation is critical for survival of most microbes. Accordingly, a plethora of phage resistance systems has been identified in bacterial genomes (Labrie et al, 2010 ), including restriction‐modification systems (R‐M) (Tock & Dryden, 2005 ), abortive infection (Abi) (Chopin et al, 2005 ), Argonaute‐based interference (Swarts et al, 2014 ), as well as clustered regularly interspaced short palindromic repeats (CRISPR) and associated protein (Cas) adaptive immune system (CRISPR‐Cas) (Barrangou & Marraffini, 2014 ; Van der Oost et al, 2014 ). Predictably, the dark matter of bacterial genomes contains a wealth of genetic gold. A study published in this issue of The EMBO Journal by Goldfarb et al ( 2015 ) unveils bacteriophage exclusion (BREX) as a novel, widespread bacteriophage resistance system that provides innate immunity against virulent and temperate phage in bacteria.     

Nitrogen utilisation,energy utilisation and methane emissions of sheep grazing in two types of pasture

Livestock grazing plays a significant role in maintaining grasslands and promoting animal production globally. To understand the livestock performance in sown pasture (SP) vs native pasture (NP) is important to ensure more effective grassland-livestock interactions with minimal environmental impact. A 2 (treatment) * 2 (period) Latin Square design experiment was conducted with 10 growing Hu sheep ♂ × thin-tailed Han sheep ♀ rams grazed perennially SP vs NP in an inland arid region of China. The objectives were to evaluate the effects of grazing management on nutrient digestibility, nitrogen (N) and energy utilisation and methane (CH₄) emission. The N intake, N retained and energy intake (gross energy (GE), and digestible and metabolisable energy) of sheep grazing in SP were significantly increased compared with those grazing in NP. There were significant linear relationships between DM intake (DMI) (g/kg BW or g/kg BW^0.75) or CH₄ (g/kg BW or g/kg BW^0.75) emissions and forage nutrient and GE concentrations within each grassland type. The linear regression analysis indicated that forage CP or ether extract concentration was a good predictor for DMI (g/kg BW or g/kg BW^0.75) (R² = 0.756 or 0.752), and CH₄ emission could be predicted using forage nutrient and GE concentrations (R² = 0.381–0.503). These results suggest that DMI and CH₄ emissions per unit metabolic BW were accurately predicted by multiple-factor combinations of forage nutrients, including ether extract and CP paired with GE. The present output could provide useful information for the development of sustainable sheep grazing systems in the inland arid regions of the world.     

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 1964 individual cows across 21 farms were measured for at least 7 days/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 CV 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.     

Relationships between methane emission of Holstein Friesian dairy cows and fatty acids,volatile metabolites and non-volatile metabolites in milk

This study investigated the relationships between methane (CH₄) emission and fatty acids, volatile metabolites (V) and non-volatile metabolites (NV) in milk of dairy cows. Data from an experiment with 32 multiparous dairy cows and four diets were used. All diets had a roughage : concentrate ratio of 80 : 20 based on dry matter (DM). Roughage consisted of either 1000 g/kg DM grass silage (GS), 1000 g/kg DM maize silage (MS), or a mixture of both silages (667 g/kg DM GS and 333 g/kg DM MS; 333 g/kg DM GS and 677 g/kg DM MS). Methane emission was measured in climate respiration chambers and expressed as production (g/day), yield (g/kg dry matter intake; DMI) and intensity (g/kg fat- and protein-corrected milk; FPCM). Milk was sampled during the same days and analysed for fatty acids by gas chromatography, for V by gas chromatography–mass spectrometry, and for NV by nuclear magnetic resonance. Several models were obtained using a stepwise selection of (1) milk fatty acids (MFA), V or NV alone, and (2) the combination of MFA, V and NV, based on the minimum Akaike’s information criterion statistic. Dry matter intake was 16.8±1.23 kg/day, FPCM yield was 25.0±3.14 kg/day, CH₄ production was 406±37.0 g/day, CH₄ yield was 24.1±1.87 g/kg DMI and CH₄ intensity was 16.4±1.91 g/kg FPCM. The observed CH₄ emissions were compared with the CH₄ emissions predicted by the obtained models, based on concordance correlation coefficient (CCC) analysis. The best models with MFA alone predicted CH₄ production, yield and intensity with a CCC of 0.80, 0.71 and 0.69, respectively. The best models combining the three types of metabolites included MFA and NV for CH₄ production and CH₄ yield, whereas for CH₄ intensity MFA, NV and V were all included. These models predicted CH₄ production, yield and intensity better with a higher CCC of 0.92, 0.78 and 0.93, respectively, and with increased accuracy (C_b) and precision (r). The results indicate that MFA alone have moderate to good potential to estimate CH₄ emission, and furthermore that including V (CH₄ intensity only) and NV increases the CH₄ emission prediction potential. This holds particularly for the prediction model for CH₄ intensity.     

No significant nitrous oxide emissions during spring thaw under grazing and nitrogen addition in an alpine grassland

A recent study (Wolf et al., 2010) suggests that short—lived pulses of N₂O emission during spring thaw dominate the annual N₂O budget and that grazing decreases N₂O emissions during the spring thaw. To verify this we conducted year—round N₂O flux measurements from June 2010 to May 2011 in Tianshan alpine grassland in central Asia. No pulse emissions of N₂O were found at grazing management sites and nitrogen addition sites during the spring thaw. The contribution of the spring thaw to the total annual N₂O budget was small and accounted for only 6.6% of the annual fluxes, with winter emissions accounting for 16.7% and growing season emissions accounting for 76.7%. The difference in N₂O emissions attributable to grazing management was not significant (P > 0.05). Nitrogen input tended to increase N₂O emissions at N addition sites during the grass growing season compared with those at unfertilized sites. N₂O fluxes showed a significant correlation with air temperature and also with both soil temperature and soil water content at 10 cm depth.     

Relationship between rumen methanogens and methane production in dairy cows fed diets supplemented with a feed enzyme additive

Aims: To investigate the relationship between ruminal methanogen community and host enteric methane (CH₄) production in lactating dairy cows fed diets supplemented with an exogenous fibrolytic enzyme additive. Methods and Results: Ecology of ruminal methanogens from dairy cows fed with or without exogenous fibrolytic enzymes was examined using PCR–denaturing gradient gel electrophoresis (PCR–DGGE) analyses and quantitative real‐time PCR (qRT‐PCR). The density of methanogens was not affected by the enzyme additive or sampling times, and no relationship was observed between the total methanogen population and CH₄ yield (as g per head per day or g kg^?1 DMI). The PCR–DGGE profiles consisted of 26 distinctive bands, with two bands similar to Methanogenic archaeon CH1270 negatively correlated, and one band similar to Methanobrevibacter gottschalkii strain HO positively correlated, with CH₄ yield. Three bands similar to Methanogenic archaeon CH1270 or Methanobrevibacter smithii ATCC 35061 appeared after enzyme was added. Conclusions: Supplementing a dairy cow diet with an exogenous fibrolytic enzyme additive increased CH₄ yield and altered the composition of the rumen methanogen community, but not the overall density of methanogens. Significance and Impact of the Study: This is the first study to identify the correlation between methanogen ecology and host CH₄ yield from lactating dairy cows.     

Prediction of enteric methane emissions from Holstein dairy cows fed various forage sources

Milk fatty acid (FA) profile has been previously used as a predictor of enteric CH₄output in dairy cows fed diets supplemented with plant oils, which can potentially impact ruminal fermentation. The objective of this study was to investigate the relationships between milk FA and enteric CH₄ emissions in lactating dairy cows fed different types of forages in the context of commonly fed diets. A total of 81 observations from three separate 3×3 Latin square design (32-day periods) experiments including a total of 27 lactating cows (96±27 days in milk; mean±SD) were used. Dietary forages were included at 60% of ration dry matter and were as follows: (1) 100% corn silage, (2) 100% alfalfa silage, (3) 100% barley silage, (4) 100% timothy silage, (5) 50 : 50 mix of corn and alfalfa silages, (6) 50 : 50 mix of barley and corn silages and (7) 50 : 50 mix of timothy and alfalfa silages. Enteric CH₄output was measured using respiration chambers during 3 consecutive days. Milk was sampled during the last 7 days of each period and analyzed for components and FA profile. Test variables included dry matter intake (DMI; kg/day), NDF (%), ether extract (%), milk yield (kg/day), milk components (%) and individual milk FA (% of total FA). Candidate multivariate models were obtained using the Least Absolute Shrinkage and Selection Operator and Least-Angle Regression methods based on the Schwarz Bayesian Criterion. Data were then fitted into a random regression using the MIXED procedure including the random effects of cow, period and study. A positive correlation was observed between CH₄ and DMI (r=0.59,P<0.001), whereas negative associations were observed between CH₄ and cis9-17:1 (r=−0.58, P<0.001), and trans8, cis13-18:2 (r=−0.51,P<0.001). Three different candidate models were selected and the best fit candidate model predicted CH₄ with a coefficient of determination of 0.84 after correction for cow, period and study effects and was: CH₄ (g/day)=319.7−57.4×15:0−13.8×cis9-17:1−39.5×trans10-18:1−59.9×cis11-18:1−253.1×trans8, cis12-18:2−642.7×trans8, cis13-18:2−195.7×trans11, cis15-18:2+16.5×DMI. Overall and linear prediction biases of all models were not significant (P>0.19). Milk FA profile and DMI can be used to predict CH₄emissions in dairy cows across a wide range of dietary forage sources     

Ready,Set…Poised!: Polycomb target genes are bound by poised RNA polymerase II throughout differentiation

In embryonic stem cells (ESCs), silent genes with major developmental functions display a unique epigenetic state in which strong and broad binding by Polycomb repressive complexes (PRCs) is accompanied by the presence of poised RNA polymerase II (RNAPII) and activating histone marks (e.g. H3K4me3) (Azuara et al, 2006 ; Bernstein et al, 2006 ; Stock et al, 2007 ; Brookes et al, 2012 ). It has been suggested that the plasticity and broad differentiation potential of pluripotent cells might rely, at least partly, on this unique epigenetic state (Bernstein et al, 2006 ; Stock et al, 2007 ). In their recent study, Pombo and colleagues (Ferrai et al, 2017 ) show that a similar epigenetic state can be found at a subset of major developmental genes throughout the differentiation of ESCs into neurons, providing novel and exciting insights into the molecular basis of cellular plasticity in differentiated cells.     

Does the diurnal pattern of enteric methane emissions from dairy cows change over time?

Diet manipulation and genetic selection are two important mitigation strategies for reducing enteric methane (CH₄) emissions from ruminant livestock. The aim of this study was to assess whether the diurnal pattern of CH₄ emissions from individual dairy cows changes over time when cows are fed on diets varying in forage composition. Emissions of CH₄ from 36 cows were measured during milking in an automatic (robotic) milking station in three consecutive feeding periods, for a total of 84 days. In Periods 1 and 2, the 36 cows were fed a high-forage partial mixed ration (PMR) containing 75% forage, with either a high grass silage or high maize silage content. In Period 3, cows were fed a commercial PMR containing 69% forage. Cows were offered PMR ad libitum plus concentrates during milking and CH₄ emitted by individual cows was sampled during 8662 milkings. A linear mixed model was used to assess differences among cows, feeding periods and time of day. Considerable variation was observed among cows in daily mean and diurnal patterns of CH₄ emissions. On average, cows produced less CH₄ when fed on the commercial PMR in feeding Period 3 than when the same cows were fed on high-forage diets in feeding Periods 1 and 2. The average diurnal pattern for CH₄ emissions did not significantly change between feeding periods and as lactation progressed. Emissions of CH₄ were positively associated with dry matter (DM) intake and forage DM intake. It is concluded that if the management of feed allocation remains constant then the diurnal pattern of CH₄ emissions from dairy cows will not necessarily alter over time. A change in diet composition may bring about an increase or decrease in absolute emissions over a 24-h period without significantly changing the diurnal pattern unless management of feed allocation changes. These findings are important for CH₄ monitoring techniques that involve taking measurements over short periods within a day rather than complete 24-h observations.     

Using RAD‐seq to recognize sex‐specific markers and sex chromosome systems

Next‐generation sequencing methods have initiated a revolution in molecular ecology and evolution (Tautz et al. 2010 ). Among the most impressive of these sequencing innovations is restriction site‐associated DNA sequencing or RAD‐seq (Baird et al. 2008 ; Andrews et al. 2016 ). RAD‐seq uses the Illumina sequencing platform to sequence fragments of DNA cut by a specific restriction enzyme and can generate tens of thousands of molecular genetic markers for analysis. One of the many uses of RAD‐seq data has been to identify sex‐specific genetic markers, markers found in one sex but not the other (Baxter et al. 2011 ; Gamble & Zarkower 2014 ). Sex‐specific markers are a powerful tool for biologists. At their most basic, they can be used to identify the sex of an individual via PCR. This is useful in cases where a species lacks obvious sexual dimorphism at some or all life history stages. For example, such tests have been important for studying sex differences in life history (Sheldon 1998 ; Mossman & Waser 1999 ), the management and breeding of endangered species (Taberlet et al. 1993 ; Griffiths & Tiwari 1995 ; Robertson et al. 2006 ) and sexing embryonic material (Hacker et al. 1995 ; Smith et al. 1999 ). Furthermore, sex‐specific markers allow recognition of the sex chromosome system in cases where standard cytogenetic methods fail (Charlesworth & Mank 2010 ; Gamble & Zarkower 2014 ). Thus, species with male‐specific markers have male heterogamety (XY) while species with female‐specific markers have female heterogamety (ZW). In this issue, Fowler & Buonaccorsi ( 2016 ) illustrate the ease by which RAD‐seq data can generate sex‐specific genetic markers in rockfish (Sebastes). Moreover, by examining RAD‐seq data from two closely related rockfish species, Sebastes chrysomelas and Sebastes carnatus (Fig.  1 ), Fowler & Buonaccorsi ( 2016 ) uncover shared sex‐specific markers and a conserved sex chromosome system.