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Ecology and forestry sciences are using an increasing amount of data to address a wide variety of technical and research questions at the local, continental and global scales. However, one type of data remains rare: fine-grain descriptions of large landscapes. Yet, this type of data could help address the scaling issues in ecology and could prove useful for testing forest management strategies and accurately predicting the dynamics of ecosystem services. Here we present three datasets describing three large European landscapes in France, Poland and Slovenia down to the tree level. Tree diameter, height and species data were generated combining field data, vegetation maps and airborne laser scanning (ALS) data following an area-based approach. Together, these landscapes cover more than 100 000 ha and consist of more than 42 million trees of 51 different species. Alongside the data, we provide here a simple method to produce high-resolution descriptions of large landscapes using increasingly available data: inventory and ALS data. We carried out an in-depth evaluation of our workflow including, among other analyses, a leave-one-out cross validation. Overall, the landscapes we generated are in good agreement with the landscapes they aim to reproduce. In the most favourable conditions, the root mean square error (RMSE) of stand basal area (BA) and mean quadratic diameter (Dg) predictions were respectively 5.4 m 2 .ha -1 and 3.9 cm, and the generated main species corresponded to the observed main species in 76.2% of cases., Competing Interests: No competing interests were disclosed., (Copyright: © 2023 Aussenac R et al.)

Process-based models and empirical modelling techniques are frequently used to (i) explore the sensitivity of tree growth to environmental variables, and (ii) predict the future growth of trees and forest stands under climate change scenarios. However, modelling approaches substantially influence predictions of the sensitivity of trees to environmental factors. Here, we used tree-ring width (TRW) data from 1630 beech trees from a network of 70 plots established across European mountains to build empirical predictive growth models using various modelling approaches. In addition, we used 3-PG and Biome-BGCMuSo process-based models to compare growth predictions with derived empirical models. Results revealed similar prediction errors (RMSE) across models ranging between 3.71 and 7.54 cm 2 of basal area increment (BAI). The models explained most of the variability in BAI ranging from 54 % to 87 %. Selected explanatory variables (despite being statistically highly significant) and the pattern of the growth sensitivity differed between models substantially. We identified only five factors with the same effect and the same sensitivity pattern in all empirical models: tree DBH, competition index, elevation, Gini index of DBH, and soil silt content. However, the sensitivity to most of the climate variables was low and inconsistent among the empirical models. Both empirical and process-based models suggest that beech in European mountains will, on average, likely experience better growth conditions under both 4.5 and 8.5 RCP scenarios. The process-based models indicated that beech may grow better across European mountains by 1.05 to 1.4 times in warmer conditions. The empirical models identified several drivers of tree growth that are not included in the current process-based models (e.g., different nutrients) but may have a substantial effect on final results, particularly if they are limiting factors. Hence, future development of process-based models may build upon our findings to increase their ability to correctly capture ecosystem dynamics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

A special feature of organic production systems is the cows' significantly lower productivity, which is adapted to environmental conditions. The quantity and quality of colostrum is negatively correlated, high amounts of colostrum are associated with low amounts of immunoglobulins. Cows' parity is also a modulating factor, and studies have shown an increase in colostral IgG corresponds with increasing parity. This study's aim was to determine the effect of cows' parity on colostrum quality, in an organic farm setting. From a basic organic herd of dairy cattle, 40 Polish Holstein-Friesian cows were selected: 10 cows each of primiparous, second lactation, fourth lactation, and fifth lactation. Colostrum and transition milk samples were taken from each cow seven times: twice daily on the 1st and 2nd days after calving (every 12 h), and once daily on the 3rd to 5th days. Multiparous cows' colostrum had higher levels of total proteins, casein, and non-fat dry matter, versus primiparous. Only cows in the second and fourth lactations produced very good quality colostrum (with immunoglobulins over 50 g/L), meeting standards for immunoglobulin concentration. In conclusion, the production of very good quality colostrum is limited during the first lactation, which may suggest the mammary gland is poorly developed, and, thus, immunoglobulin transport is limited. Variability in the colostrum's immunoglobulin content from first and second collections post-calving was higher in multiparous versus primiparous cows. Therefore, it should be good practice to freeze colostrum from multiparous cows in case of poor-quality primiparous colostrum.

In this perspective analysis, we strive to answer the following question: how can we advance integrative biology research in the 21st century with lessons from animal science? At the University of Ljubljana, Biotechnical Faculty, Department of Animal Science, we share here our three lessons learned in the two decades from 2002 to 2022 that we believe could inform integrative biology, systems science, and animal science scholarship in other countries and geographies. Cultivating multiomics knowledge through a conceptual lens of integrative biology is crucial for life sciences research that can stand the test of diverse biological, clinical, and ecological contexts. Moreover, in an era of the current COVID-19 pandemic, animal nutrition and animal science, and the study of their interactions with human health (and vice versa) through integrative biology approaches hold enormous prospects and significance for systems medicine and ecosystem health.

Alternative housing systems for dairy cattle have recently emerged, such as compost-bedded packs and artificial floor ones. To determine their acceptability among categories of people with a connection to animal husbandry, this study aimed to identify and compare the acceptability of (alternative) housing systems and attitudes to aspects of housing systems for dairy cattle among Slovenian consumers, farmers, and stakeholders. Farmers (N = 306), consumers (N = 508), and stakeholders (N = 40) were interviewed about their views on the main aspects (animals, farmers, products, environment) of housing systems for dairy cattle, the acceptance of four housing systems, and important housing features. The results show that consumers, stakeholders, and conventional farmers preferred housing systems with an artificial floor, while organic farmers preferred a housing system with a compost-bedded pack. Consumers and organic farmers expressed the greatest acceptance of almost every aspect of the housing system, except for a sufficient income for farmers and a low workload. Conventional farmers and stakeholders hold similar views, except for the expectation that the animals have enough space to move around, the image of the landscape, and the animals' health and wellbeing, where stakeholders showed more acceptance than conventional farmers. The results imply that systematically planned information aimed at different target categories is needed to increase the acceptance of (alternative) housing systems for cattle.

The purpose of this study was to compare animal health in compost-bedded pack (CBP) and cubicle housing (CH) systems using data from dairy herd improvement associations. Thirty-two commercial dairy farms located in Austria, Germany, Italy, The Netherlands, Slovenia, and Sweden were included in the study. A matching design (pairing CBP and CH within country) according to herd selection criteria was used. We explored the following health indicators: somatic cell counts (SCC), high SCC, new high SCC, ketosis risk, prolonged calving intervals, dystocia, and stillbirth. Traits for culling and culling-related issues, such as length of life and length of productive life, were also included. We used multivariable (mixed) linear and logistic regression models to evaluate differences between the systems. Udder health, as measured by SCC, was inferior in CBP, although the geometric means were low in both systems. The incidence of stillbirths was higher in CBP, while prolonged calving intervals were fewer, indicating that there were fewer reproductive disorders. There were no differences in longevity between the systems, although CBP had lower proportions of first calvers. Overall, we conclude that there were few and minor differences in health and longevity between the CBP and CH systems in the European context.

The bedding material used in barns for dairy cows has a significant effect on animal welfare and performance. Bedding influences the duration in which animals remain lying down and, consequently, the processes of rumination and milk production. It is crucial to have a complete understanding of the properties of bedding materials and the effects of alternative bedding materials on dairy cattle. This paper aims to evaluate the physical, chemical, and biological properties of various alternative and conventional bedding materials for dairy cattle for use in compost bedded pack or freestall barn systems. We analyzed 50 samples of 17 bedding materials produced in 3 European countries. We analyzed physical properties including the water holding capacity, porosity, moisture content, bulk density, dry bulk density, and particle size. Chemical analyses were performed to determine the total N, total organic C, and C:N ratio. In the biological analyses, the Escherichia coli count, total bacteria count, coliform count, and Klebsiella spp. count were assessed. The results demonstrated how the physical properties of the bedding materials may influence the chemical and biological properties. All of the materials presented adequate chemical properties to be used as bedding material. The physical properties of the bedding materials differed widely among the materials except for the dry bulk density, which presented no difference. Moreover, the contamination of each studied microorganism was observed for each bedding material to determine which material had the lowest level of contamination. Posidonia oceanica, Miscanthus grass, and spelt husks could be considered as a potential alternative material for use as bedding material for dairy cows in both systems (i.e., composted bedded pack and freestall). This experiment illustrated the importance of performing thorough physical, chemical, and biological analyses before implementing a material as bedding for dairy cattle., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).)

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 immunostimulating 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., Competing Interests: The authors have declared that no competing interests exist.

The bedding materials used in dairy cow housing systems are extremely important for animal welfare and performance. A wide range of materials can be used as bedding for dairy cattle, but their physical properties must be analysed to evaluate their potential. In the present study, the physical properties of various bedding materials for dairy cattle were investigated, and different fuzzy clustering algorithms were employed to cluster these materials based on their physical properties. A total of 51 different bedding materials from various places in Europe were collected and tested. Physical analyses were carried out for the following parameters: bulk density (BD), water holding capacity (WHC), air-filled porosity (AFP), global density (GD), container capacity (CC), total effective porosity (TEP), saturated humidity (SH), humidity (H), and average particle size (APS). These data were analysed by principal components analysis (PCA) to reduce the amount of data and, subsequently, by fuzzy clustering analysis. Three clustering algorithms were tested: k-means (KM), fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. Furthermore, different numbers of clusters (2-8) were evaluated and subsequently compared using five validation indexes. The GK clustering algorithm with eight clusters fit better regarding the division of materials according to their properties. From this clustering analysis, it was possible to understand how the physical properties of the bedding materials may influence their behaviour. Among the materials that fit better as bedding materials for dairy cows, Posidonia oceanica (Cluster 6) can be considered an alternative material.

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., Competing Interests: The authors have read the journal's policy and the authors of this manuscript have the following competing interest: BB is a paid employee of Qualitas AG. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development, or marketed products to declare.