Arthropod vectors are responsible for the transmission of human pathogens worldwide. Several arthropod species are bird ectoparasites, however, no study to date has characterized their microbiota as a whole. We sampled hematophagous ectoparasites that feed on migratory birds and performed 16S rRNA gene metabarcoding to characterize their microbial community. A total of 194 ectoparasites were collected from 115 avian hosts and classified into three groups: a) Hippoboscidae diptera; b) ticks; c) other arthropods. Metabarcoding showed that endosymbionts were the most abundant genera of the microbial community, including Wolbachia for Hippoboscidae diptera, Candidatus Midichloria for ticks, Wolbachia and Arsenophonus for the other arthropod group. Genera including pathogenic species were: Rickettsia, Borrelia, Coxiella, Francisella, Bartonella, Anaplasma. Co-infection with Borrelia-Rickettsia and Anaplasma-Rickettsia was also observed. A global overview of the microbiota of ectoparasites sampled from migratory birds was obtained with the use of 16S rRNA gene metabarcoding. A novel finding is the first identification of Rickettsia in the common swift louse fly, Crataerina pallida. Given their possible interaction with pathogenic viruses and bacteria, the presence of endosymbionts in arthropods merits attention. Finally, molecular characterization of genera, including both pathogenic and symbiont species, plays a pivotal role in the design of targeted molecular diagnostics.

We compared in vivo and in vitro dry matter (DM) and neutral detergent fiber (NDF) digestibility in donkeys using feces as microbial inoculum. Four donkeys were used in a 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments. The animals were fed two types of hay, with or without flaked barley. For the in vivo procedure, total feces were collected for 6 days from each donkey; digestibility was calculated as the difference between ingested and excreted DM and NDF. For the in vitro procedure, donkey feces were buffered and used as microbial inoculum in an Ankom DaisyII Incubator; digestibility was estimated after 60 h of incubation. In vivo results showed that the addition of barley to hays did not change the digestibility values. In vivo estimates were higher than in vitro ones. The equations used to predict in vivo estimates from in vitro data were not reliable (R2 = 0.47 and 0.21; P = 0.003 and 0.078 for NDF and DM digestibility, respectively). Further studies need to evaluate different sample size and digestion times.

The aim of this study was to test the feasibility and reliability of the Animal Welfare Indicators (AWIN) protocol for welfare assessment of dairy goats when applied to semi-extensive farming conditions. We recruited 13 farms located in the NW Italian Alps where three assessors individually and independently applied a modified version of the AWIN welfare assessment protocol for goats integrated with some indicators derived from the AWIN welfare assessment protocol for sheep. The applied protocol consisted of nine individual-level (body condition score, hair coat condition, abscesses, overgrown claws, udder asymmetry, fecal soiling, nasal discharge, ocular discharge, and improper disbudding) and seven group-level (severe lameness, Qualitative Behavior Assessment-QBA, thermal stress, oblivion, Familiar Human Approach Test-FHAT, synchrony at grazing, synchrony at resting) animal-based indicators. On most farms, the level of welfare was good. Many of the considered welfare problems (overgrown claws, fecal soiling, discharges, and thermal stress) were never recorded. However, oblivion, severe lameness, hair coat condition and abscesses were detected on some farms, with percentages ranging from 5 to 35%. The mean percentage of animals with normal body condition was 67.9 ± 5.7. The level of synchronization during resting was on average low (14.3 ± 7.2%). The application of the whole protocol required more than 4 h/farm and 3 min/goat. The inter-observer reliability varied from excellent (udder asymmetry, overgrown claws, discharges, synchrony at resting, use of shelter) to acceptable (abscesses, fecal soiling, and oblivion), but insufficient for hair coat condition, improper disbudding, synchrony at grazing, QBA. Differences in background of the assessors and feasibility constraints (i.e., use of binoculars in unfenced pastures, individual-level assessment conducted during the morning milking in narrow and dark pens, difficulties when using the scan and instantaneous sampling method due to the high number of animals that moved at the same time) can affect the reliability of data collection. Extensive training seems necessary for properly scoring animals when applying the QBA, whereas the FHAT to evaluate the Human-Animal Relationship of goats at pasture seems promising but needs to be validated. Indicators that evaluate the synchrony of activities require to be validated to identify the best moment to perform the observations during the day.

This study focuses on the problem of assessing inter-observer reliability (IOR) in the case of dichotomous categorical animal-based welfare indicators and the presence of two observers. Based on observations obtained from Animal Welfare Indicators (AWIN) project surveys conducted on nine dairy goat farms, and using udder asymmetry as an indicator, we compared the performance of the most popular agreement indexes available in the literature: Scott’s π, Cohen’s k, kPABAK, Holsti’s H, Krippendorff’s α, Hubert’s Γ, Janson and Vegelius’ J, Bangdiwala’s B, Andrés and Marzo’s ∆, and Gwet’s γ(AC1). Confidence intervals were calculated using closed formulas of variance estimates for π, k, kPABAK, H, α, Γ, J, ∆, and γ(AC1), while the bootstrap and exact bootstrap methods were used for all the indexes. All the indexes and closed formulas of variance estimates were calculated using Microsoft Excel. The bootstrap method was performed with R software, while the exact bootstrap method was performed with SAS software. k, π, and α exhibited a paradoxical behavior, showing unacceptably low values even in the presence of very high concordance rates. B and γ(AC1) showed values very close to the concordance rate, independently of its value. Both bootstrap and exact bootstrap methods turned out to be simpler compared to the implementation of closed variance formulas and provided effective confidence intervals for all the considered indexes. The best approach for measuring IOR in these cases is the use of B or γ(AC1), with bootstrap or exact bootstrap methods for confidence interval calculation.

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