Use of somatic cell count as an indicator of colostrum quality

The impact of cow mammary gland diseases on the quality of colostrum is not conclusively defined; research results are conflicting. However, it is widely believed that mastitis lowers the level of immunoglobulins and the quality of the colostrum produced. Therefore, the aim of this study was to determine the influence of somatic cell counts (SCC) on the colostrum immuno-stimulating and chemical components. The experiment was conducted on an experimental organic dairy farm in which a herd of approximately 250 cows was kept in a freestall housing system, with the average performance exceeding 6,000 kg of milk per lactation. Colostrum and milk samples were taken individually from each cow seven times during the experiment: from the first to second day after calving–twice per day, and from the third to fifth day after calving–once per day. Therefore, after preliminary analyses, the cows were divided into two groups based on the cytological quality of their colostrum at the first collection: 1. SCC �400,000 cells/ml (good quality colostrum; GCC– 18 cows), 2. SCC � 400,000 cells/ml (low quality colostrum; LCC– 22 cows). The study found almost double the concentration of immunoglobulins and essential fatty acids in first milking colostrum in the GCC group than in colostrum from the LCC group. In addition, an increase in the concentration of lysozyme in first milking colostrum was associated with a decrease in the concentration of immunoglobulins. In addition, the increase in the level of lysozyme was associated with a decrease in the concentration of immunoglobulins. In conclusion, the SCC of first milking colostrum can be used as an indicator of colostrum quality

European beech stem diameter grows better in mixed than in mono-specific stands at the edge of its distribution in mountain forests

Recent studies show that several tree species are spreading to higher latitudes and elevations due to climate change. European beech, presently dominating from the colline to the subalpine vegetation belt, is already present in upper montane subalpine forests and has a high potential to further advance to higher elevations in European mountain forests, where the temperature is predicted to further increase in the near future. Although essential for adaptive silviculture, it remains unknown whether the upward shift of beech could be assisted when it is mixed with Norway spruce or silver fir compared with mono-specific stands, as the species interactions under such conditions are hardly known. In this study, we posed the general hypotheses that the growth depending on age of European beech in mountain forests was similar in mono-specific and mixed-species stands and remained stable over time and space in the last two centuries. The scrutiny of these hypotheses was based on increment coring of 1240 dominant beech trees in 45 plots in mono-specific stands of beech and in 46 mixed mountain forests. We found that (i) on average, mean tree diameter increased linearly with age. The age trend was linear in both forest types, but the slope of the age–growth relationship was higher in mono-specific than in mixed mountain forests. (ii) Beech growth in mono-specific stands was stronger reduced with increasing elevation than that in mixed-species stands. (iii) Beech growth in mono-specific stands was on average higher than beech growth in mixed stands. However, at elevations > 1200 m, growth of beech in mixed stands was higher than that in mono-specific stands. Differences in the growth patterns among elevation zones are less pronounced now than in the past, in both mono-specific and mixed stands. As the higher and longer persisting growth rates extend the flexibility of suitable ages or size for tree harvest and removal, the longer-lasting growth may be of special relevance for multi-aged silviculture concepts. On top of their function for structure and habitat improvement, the remaining old trees may grow more in mass and value than assumed so far.The authors would like to acknowledge networking support by the COST (European Cooperation in Science and Technology) Action CLIMO (Climate-Smart Forestry in Mountain Regions—CA15226) financially supported by the EU Framework Programme for Research and Innovation HORIZON 2020. This publication is part of a project that has received funding from the European Union’s HORIZON 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No 778322. Thanks are also due to the European Union for funding the project ‘Mixed species forest management. Lowering risk, increasing resilience (REFORM)’ (# 2816ERA02S under the framework of Sumforest ERA-Net). Further, we would like to thank the Bayerische Staatsforsten (BaySF) for providing the observational plots and to the Bavarian State Ministry of Food, Agriculture, and Forestry for permanent support of the Project W 07 ‘Long-term experimental plots for forest growth and yield research’ (#7831-26625-2017). We also thank the Forest Research Institute, ERTI Sárvár, Hungary, for assistance and for providing observational plots. Furthermore, our work was partially supported by the SRDA via Project No. APVV-16-0325 and APVV-15-0265, the Ministry of Science and Higher Education of the Republic of Poland, the Project “EVA4.0” No. CZ.02.1.01/0.0/0.0/16_019/0000803 funded by OP RDE and the Project J4-1765 funded by the Slovenian Research Agency and also by the Bulgarian National Science Fund (BNSF) and the Project No. DCOST 01/3/19.10.2018

Multi-breed genome-wide association studies across countries for electronically recorded behavior traits in local dual-purpose cows.

Basic bovine behavior is a crucial parameter influencing cattle domestication. In addition, behavior has an impact on cattle productivity, welfare and adaptation. The aim of the present study was to infer quantitative genetic and genomic mechanisms contributing to natural dual-purpose cow behavior in grazing systems. In this regard, we genotyped five dual-purpose breeds for a dense SNP marker panel from four different European countries. All cows from the across-country study were equipped with the same electronic recording devices. In this regard, we analyzed 97,049 longitudinal sensor behavior observations from 319 local dual-purpose cows for rumination, feeding, basic activity, high active, not active and ear temperature. According to the specific sensor behaviors and following a welfare protocol, we computed two different welfare indices. For genomic breed characterizations and multi-breed genome-wide association studies, sensor traits and test-day production records were merged with 35,826 SNP markers per cow. For the estimation of variance components, we used the pedigree relationship matrix and a combined similarity matrix that simultaneously included both pedigree and genotypes. Heritabilities for feeding, high active and not active were in a moderate range from 0.16 to 0.20. Estimates were very similar from both relationship matrix-modeling approaches and had quite small standard errors. Heritabilities for the remaining sensor traits (feeding, basic activity, ear temperature) and welfare indices were lower than 0.09. Five significant SNPs on chromosomes 11, 17, 27 and 29 were associated with rumination, and two different SNPs significantly influenced the sensor traits "not active" (chromosome 13) and "feeding" (chromosome 23). Gene annotation analyses inferred 22 potential candidate genes with a false discovery rate lower than 20%, mostly associated with rumination (13 genes) and feeding (8 genes). Mendelian randomization based on genomic variants (i.e., the instrumental variables) was used to infer causal inference between an exposure and an outcome. Significant regression coefficients among behavior traits indicate that all specific behavioral mechanisms contribute to similar physiological processes. The regression coefficients of rumination and feeding on milk yield were 0.10 kg/% and 0.12 kg/%, respectively, indicating their positive influence on dual-purpose cow productivity. Genomically, an improved welfare behavior of grazing cattle, i.e., a higher score for welfare indices, was significantly associated with increased fat and protein percentages

Modelling future growth of mountain forests under changing environments

Models to predict the effects of different silvicultural treatments on future forest development are the best available tools to demonstrate and test possible climate-smart pathways of mountain forestry. This chapter reviews the state of the art in modelling approaches to predict the future growth of European mountain forests under changing environmental and management conditions. Growth models, both mechanistic and empirical, which are currently available to predict forest growth are reviewed. The chapter also discusses the potential of integrating the effects of genetic origin, species mixture and new silvicultural prescriptions on biomass production into the growth models. The potential of growth simulations to quantify indicators of climate-smart forestry (CSF) is evaluated as well. We conclude that available forest growth models largely differ from each other in many ways, and so they provide a large range of future growth estimates. However, the fast development of computing capacity allows and will allow a wide range of growth simulations and multi-model averaging to produce robust estimates. Still, great attention is required to evaluate the performance of the models. Remote sensing measurements will allow the use of growth models across ecological gradients

Assessment of indicators for climate smart management in mountain forests

This chapter addresses the concepts and methods to assess quantitative indicators of Climate-Smart Forestry (CSF) at stand and management unit levels. First, the basic concepts for developing a framework for assessing CSF were reviewed. The suitable properties of indicators and methods for normalization, weighting, and aggregation were summarized. The proposed conceptual approach considers the CSF assessment as an adaptive learning process, which integrates scientifc knowledge and participatory approaches. Then, climate smart indicators were applied on long-term experimental plots to assess CSF of spruce-fr-beech mixed mountain forest. Redundancy and trade-offs between indicators, as well as their sensitivity to management regimes, were analyzed with the aim of improving the practicability of indicators. At the management unit level, the roles of indicators in the different phases of forest management planning were reviewed. A set of 56 indicators were used to assess their importance for management planning in four European countries. The results indicated that the most relevant indicators differed from the set of Pan-European indicators of sustainable forest management. Finally, we discussed results obtained and future challenges, including the following: (i) how to strengthen indicator selections and CSF assessment at stand level, (ii) the potential integration of CSF indicators into silvicultural guidelines, and (iii) the main challenges for integrating indicators into climate-smart forest planning