Effects of forage type on diversity in bacterial pellets isolated from liquid and solid phases of the rumen content in sheep and goats.

Two sheep and two goats, fitted with a ruminal cannula, received two diets composed of 30% concentrate and 70% of either alfalfa hay (AL) or grass hay (GR) as forage in a two-period crossover design. Solid and liquid phases of the rumen were sampled from each animal immediately before feeding and 4 h post-feeding. Pellets containing solid associated bacteria (SAB) and liquid associated bacteria (LAB) were isolated from the corresponding ruminal phase and composited by time to obtain 2 pellets per animal (one SAB and one LAB) before DNA extraction. Denaturing gradient gel electrophoresis (DGGE) analysis of 16S ribosomal DNA was used to analyze bacterial diversity. A total of 78 and 77 bands were detected in the DGGE gel from sheep and goats samples, respectively. There were 18 bands only found in the pellets from sheep fed AL-fed sheep and 7 found exclusively in samples from sheep fed the GR diet. In goats, 21 bands were found only in animals fed the AL diet and 17 were found exclusively in GR-fed ones. In all animals, feeding AL diet tended (P < 0.10) to promote greater NB and SI in LAB and SAB pellets compared with the GR diet. The dendrogram generated by the cluster analysis showed that in both animal species all samples can be included in two major clusters. The four SAB pellets within each animal species clustered together and the four LAB pellets grouped in a different cluster. Moreover, SAB and LAB clusters contained two clear subclusters according to forage type. Results show that in all animals bacterial diversity was more markedly affected by the ruminal phase (solid vs. liquid) than by the type of forage in the diet.

Improving the low-wind performance of the AERMOD atmospheric dispersion model for predicting short-range impacts of livestock ammonia emissions.

Short-range impacts to sensitive ecosystems as a result of ammonia emitted by livestock farms are often assessed using atmospheric dispersion modelling systems such as AERMOD. These assessments evaluate mean annual atmospheric concentrations of ammonia and nitrogen deposition rates at the ecosystem location for comparison with ecosystem damage thresholds. However, predictions of mean annual atmospheric concentrations can be dominated by periods of stable night-time conditions, which can contribute significantly to mean concentrations. AERMOD has been demonstrated to overestimate concentrations in certain stable low-wind conditions and so the model could potentially overestimate the short-range impacts of livestock ammonia emissions. This paper tests several modifications to the parameterisation of AERMOD (v12345) that aim to improve model predictions in low-wind conditions. The modifications are first described and then are applied to three pig farm case studies in the USA, Denmark and Spain to assess whether the modifications improve long-term mean ammonia concentration predictions through improved model performance. For these three case studies, most of the modifications tested improved model performance as a result of reducing the long-term mean concentration predictions, with the largest effect for low- or ground-level sources (e.g. slurry lagoons or naturally ventilated housing).