Contemporary zoos house polar bears (Ursus maritimus) to serve the conservation efforts of these institutions. However, evidence of behavioural problems in captivity has highlighted the need for methods to assess polar bear welfare, why valid and feasible animal-based welfare indicators are a prerequisite. Qualitative Behaviour Assessment (QBA) has been used to assess emotional state in various species. This study therefore aimed to assess the ability of QBA to discern emotional state in zoo-housed polar bears, and further to investigate its validity through associations to behavioural and health-related indicators, as well as intra- and inter-day consistency of QBA scores. A list of 24 terms was developed by reviewing the literature and on-site assessments. Reliability of the list was tested through Kendall’s W between two assessors (Inter-OR), as well as over time (Intra-OR), based on videos. QBAs and behavioural observations were collected on 22 polar bears from nine zoos in four European countries, repeated within days (three times) and across days (four days). Behavioural observations were summarized as percentage of time spent in the respective categories, whereas behavioural diversity was expressed by the Shannon Index. Health-related indicators were expressed as an overall dichotomous value (presence/absence). Principal component analysis revealed two main components categorised as valence (PC1, 29.5%) and arousal (PC2, 15.1%). Reliability was met for both PCs, with a W of 0.82 for PC1 and 0.68 for PC2 for Inter-OR, and 0.92 for PC1 and 0.89 for PC2 for Intra-OR. PC1 was significantly positively associated with behavioural diversity (p = 0.006), environmental interaction (p = 0.006) and rest (p = 0.005), and inversely with stereotypic behaviour (p < 0.001) and general activity level (p = 0.003). PC2 was significantly positively associated with stereotypic behaviour (p < 0.001), environmental interaction (p = 0.040) and general activity level (p < 0.001), and inversely with awake inactivity (p = 0.002). Valence scores revealed no significant effect of time of day nor day, however a significant effect was found between early to mid-day on arousal scores (p = 0.015). The results provide evidence of sensitivity and some evidence of validity by associations of QBA with other welfare indicators. QBA may therefore potentially serve to assess emotional state in polar bears, needing only to be carried out once in the short term. Although the proposed list may benefit from additional validation and reliability testing, this study takes the first step towards a standardised QBA for polar bears.

After several years of implementation, the original Welfare Quality scoring model for dairy cows appears to be highly sensitive to the number and cleanliness of drinkers and not enough to the prevalence of diseases, and as a consequence may not fit the opinion of some animal welfare experts. The present paper aims to improve the Welfare Quality calculations for the criteria 'Absence of prolonged thirst' and 'Absence of disease' in dairy cows, so that the results are more sensitive to input data and better fit experts' opinion. First, we modified the calculation of 'Absence of prolonged thirst' by linearising the calculation for drinkers' availability to avoid threshold effects. Second, we modified the calculation of 'Absence of disease' by applying a Choquet integral on the three lowest spline-based scores for each health disorder to limit compensation between health disorders. Third, we performed a global sensitivity analysis of the original and the alternative scoring models. Fourth, we compared the results obtained with the original and the alternative models with eight experts' opinions on two subsets composed of 44 and 60 farms, respectively, inspected using the Welfare Quality protocol and on which experts gave their opinion on the overall level of animal welfare. Results show that the alternative model significantly reduced the 'threshold effects' related to the number of drinkers and the compensation between health disorders. On the first subset, the alternative model fits the experts' opinion slightly better than the original model (P = 0.061). On the second subset, the models performed equally. In conclusion, the proposed refinements for calculating scores are validated since they significantly reduced 'threshold effects' and the influence of measures related to drinkers. It also reduced the compensation between health disorders by considering only the three lowest scores and thus increasing the influence of measures related to health disorders, and slightly improve at overall score level the accordance with experts' opinion.

Animal welfare is of increasing public interest, and the pig industry in particular is subject to much attention. The aim of this study was to identify and compare areas of animal welfare concern for commercial pigs in four different production stages: (1) gestating sows and gilts; (2) lactating sows; (3) piglets; and (4) weaner-to-finisher pigs. One welfare assessment protocol was developed for each stage, comprising of between 20 and 29 animal welfare measures including resource-, management- and animal-based ones. Twenty-one Danish farms were visited once between January 2015 and February 2016 in a cross-sectional design. Experts (n = 26; advisors, scientists and animal welfare controllers) assessed the severity of the outcome measures. This was combined with the on-farm prevalence of each measure and the outcome was used to calculate areas of concern, defined as measures where the median of all farms fell below the value defined as ‘acceptable welfare.’ Between five and seven areas of concern were identified for each production stage. With the exception of carpal lesions in piglets, all areas of concern were resource- and management-based and mainly related to housing, with inadequate available space and the floor type in the resting area being overall concerns across all production stages. This means that animal-based measures were largely unaffected by perceived deficits in resource-based measures. Great variation existed for the majority of measures identified as areas of concern, demonstrating that achieving a high welfare score is possible in the Danish system.

Nearly 5 billion farm animals, including waterfowl, cattle, sheep, goats, and alpacas, are being affected by the fashion industry. There is an urgent need for a system that evaluates their welfare. The rise in public interest on the topic of animal welfare is leading to the creation of different textile standards or certification schemes, which can give us an overview of the general state of expectations in terms of animal welfare within the textile industry. We therefore created a risk assessment tool and applied it to 17 different textile standards. Our results showed that only one of the standards reached a score in the “Acceptable” animal welfare risk category, and the rest of the standards had even lower scores of risks for animal welfare. In general, industry standards have not demanded sufficient requirements for higher levels of animal welfare. While the current risk assessment gave us a good idea of what is considered acceptable within the industry, it is also not necessarily representative of the risks for the majority of farm animals that are part of the textile industry. Only a small number of animal-derived materials are certified with some form of animal welfare standards, even though these standards can play an important role in improving the standard of care for animals. To evaluate the actual welfare states of the animals in fibre production, further research is needed to apply the proposed tool to actual farms.

Captive polar bears (Ursus maritimus) are well-documented as being prone to behavioural disorders and, as a result, their welfare is the cause of increasing concern. There is therefore a need for an evidence-based approach to the assessment of the welfare of this species and identification of valid welfare indicators is the first step towards achieving this. To this end, a critical evaluation of peerreviewed literature was undertaken. Searches of Web of Science and Scopus took place in May 2020 for publications relevant to the welfare of captive polar bears which met inclusion criteria. Further, validity of extracted indicators was assessed via investigation of evidence of content, construct and criterion validity along with strength of evidence at publication-level. Database searches and snowballing unearthed 46 publications included for review. Identified indicators were sorted into nine behavioural, four physiological (based on physiological or biological sampling) and five physical (based on visual inspection) categories. Among behavioural indicators, the strongest evidence of validity was found for abnormal behaviour. For the physiological indicators, validity was only established for faecal glucocorticoid metabolite concentration. Content validity was assumed for all physical indicators. Generalisability and strength of evidence was generally compromised by low sample sizes and experimental limitations, and only a small number of papers investigated welfare indicators directly, resulting in a paucity of validated indicators. Potential welfare indicators that warrant further validation are highlighted. Overall, this review provides an overview of current valid and promising welfare indicators along with identified gaps in knowledge, relevant for the provision of a methodology for assessing and monitoring welfare of captive polar bears.

Captive polar bears (Ursus maritimus) are well-documented as being prone to behavioural disorders and, as a result, their welfare is the cause of increasing concern. There is therefore a need for an evidence-based approach to the assessment of the welfare of this species and identification of valid welfare indicators is the first step towards achieving this. To this end, a critical evaluation of peer-reviewed literature was undertaken. Searches of Web of Science and Scopus took place in May 2020 for publications relevant to the welfare of captive polar bears which met inclusion criteria. Further, validity of extracted indicators was assessed via investigation o f evidence of content, construct and criterion validity along with strength of evidence at publication-level. Database searches and snowballing unearthed 46 publications included for review. Identified indicators were sorted into nine behavioural, four physiological (based on physiological or biological sampling) and five physical (based on visual inspection) categories. Among behavioural indicators, the strongest evidence of validity was found for abnormal behaviour. For the physiological indicators, validity was only established for faecal glucocorticoid metabolite concentration. Content validity was assumed for all physical indicators. Generalisability and strength of evidence was generally compromised by low sample sizes and experimental limitations, and only a small number of papers investigated welfare indicators directly, resulting in a paucity of validated indicators. Potential welfare indicators that warrant further validation are highlighted. Overall, this review provides an overview of current valid and promising welfare indicators along with identified gaps in knowledge, relevant for the provision of a methodology for assessing and monitoring welfare of captive polar bears.

The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14–17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI ( R 2 = 0.91). The WI allows both numerical (0–100) as a qualitative (“not classified” to “excellent”) evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorable effects that cannot be detected adequately by the current selection of measures.

This study aimed to identify current weak points in animal welfare in Danish dairy production at herd level using the Welfare Quality (R) (WQ) protocol, and at national level using the Danish Animal Welfare Index (DAWIN) protocol. The DAWIN was developed as a monitoring tool for the welfare of the Danish dairy cow population, derived from the aggregation of DAWIN assessments at herd level. The DAWIN dairy cow protocol covers 29 measures (13 resource- and 16 animal-based measures) that were weighted and aggregated into a final overall population welfare score. A total of 3,591 cows from 60 dairy herds were assessed throughout 2015. Results from both the WQ and DAWIN were presented at six criteria levels in order to identify specific areas of concern relating to animal welfare at herd versus population level. Both protocols indicated a good general level of welfare across study herds, but also identified insufficient water supply as the main area of concern. In addition, resting comfort (ie time needed to lie down, collisions with barn equipment, cleanliness of rear body parts, animals lying outside of the designated lying area) and disease (in terms of the proportion of cows with chronically elevated somatic cell counts) were identified as problematic areas. The two assessment protocols both identified behavioural deficits, but in the WQ it was due to zero-grazing systems in contrast to the insufficient numbers of cow brushes in the DAWIN protocol. Despite differences in the aggregation, similar areas of concern were identified at criteria level.

Assessing emotional states of dairy calves is an essential part of welfare assessment, but standardized protocols are absent. The present study aims at assessing the emotional states of dairy calves and establishing a reliable standard procedure with Qualitative Behavioral Assessment (QBA) and 20 defined terms. Video material was used to compare multiple observer results. Further, live observations were performed on 49 dairy herds in Denmark and Italy. Principal Component Analysis (PCA) identified observer agreement and QBA dimensions (PC). For achieving overall welfare judgment, PC1-scores were turned into the Welfare Quality (WQ) criterion 'Positive Emotional State'. Finally, farm factors' influence on the WQ criterion was evaluated by mixed linear models. PCA summarized QBA descriptors as PC1 'Valence' and PC2 'Arousal' (explained variation 40.3% and 13.3%). The highest positive descriptor loadings on PC1 was Happy (0.92) and Nervous (0.72) on PC2. The WQ-criterion score (WQ-C12) was on average 51.1 ± 9.0 points (0: worst to 100: excellent state) and 'Number of calves', 'Farming style', and 'Breed' explained 18% of the variability of it. We conclude that the 20 terms achieved a high portion of explained variation providing a differentiated view on the emotional state of calves. The defined term list proved to need good training for observer agreement.

The Welfare Quality((R)) (WQ) protocol for on-farm dairy cattle welfare assessment describes 33 measures and a step-wise method to integrate the outcomes into 12 criteria scores, grouped into four principle scores and into an overall welfare categorisation with four possible levels. The relative contribution of various welfare measures to the integrated scores has been contested. Using a European dataset (491 herds), we investigated: i) variation in sensitivity of integrated outcomes to extremely low and high values of measures, criteria and principles by replacing each actual value with minimum and maximum observed and theoretically possible values; and ii) the reasons for this variation in sensitivity. As intended by the WQ consortium, the sensitivity of integrated scores depends on: i) the observed value of the specific measures/criteria; ii) whether the change was positive/negative; and iii) the relative weight attributed to the measures. Additionally, two unintended factors of considerable influence appear to be side-effects of the complexity of the integration method. Namely: i) the number of measures integrated into criteria and principle scores; and ii) the aggregation method of the measures. Therefore, resource-based measures related to drinkers (which have been criticised with respect to their validity to assess absence of prolonged thirst), have a much larger influence on integrated scores than health-related measures such as 'mortality rate' and 'lameness score'. Hence, the integration method of the WQ protocol for dairy cattle should be revised to ensure that the relative contribution of the various welfare measures to the integrated scores more accurately reflect their relevance for dairy cattle welfare.

The aim of this study was to investigate management and feeding practices associated with on-farm loss rate (mortality) on 63 beef cattle farms in Austria, Germany and Italy with housing systems other than fully slatted pens. Information on mortality and 56 categorised factors relating to the cleanliness of animal facilities, health and feeding management, animal-human interaction, cattle transport and origin were gathered during on-farm visits. Samples of total mixed rations (TMRs) were collected and analysed for chemical composition and particle size distribution. Twenty-eight categorised factors were removed from the initial 56 due to exclusion criteria (missing data≥20% and/or monolevel factors with≥80% answers in one category). Mortality was the response variable in the risk factor analysis and the remaining 10 continuous covariates from TMR analyses and 28 categorised factors were independent predictors. Mean (±standard deviation) mortality, representing the proportion of dead, euthanased and early culled animals over the total number of animals bought in or reared in the previous year, was 2.8±3.5%. Fourteen factors were significantly associated with mortality in the bivariable analyses; seven factors were not considered further in the multivariable analysis due to collinearity. None of the factors related to TMR were associated with mortality. Four categorical factors, referring to biosecurity measures and management, were retained in the final multivariable model, with country effect. Buying cattle from only one farm, no mixing of animals during transport, presence of a dedicated sick pen and keeping production records were associated with lower percentage mortality.

This review presents first ever literature survey on historical development of farm animal welfare indicators and assessment in the Danube region. This area, encompassing European Eastern countries and the Balkans, is to a large extent heterogeneous in terms of culture and language. However, international (English) publications were disproportionally small compared to the amount of research institutions and animal welfare activities present in the region. Therefore, the authors aimed at investigating the published literature, focusing on country level and on native languages. Data were collected for the 1980–2015 period referring to scientific papers published in international and national journals, papers and abstracts in proceedings of the international and national conferences, reviews, monographs, short communications, Ph.D., Master and Graduation theses. Welfare assessment of all farm animal species was observed including fish. Over 180 papers were in line with the preselected index. Data collected showed that publishing dynamics grew rapidly towards the last decade. Most of the studies were focused on animal welfare indicators such as stress, injuries and mutilations, behaviour, body condition and management practices. Cattle, chickens, pigs and sheep were the predominant species investigated. The study revealed that experts from the region were greatly involved in the studies of animal welfare indicators and assessment, contributing to development of the currently most widely used animal welfare assessment protocols, thus having an important role in animal welfare research and protection.

Diarrhea and respiratory disease are major health problems for dairy calves, often causing calf mortality. Previous studies have found calf mortality to be higher in organic dairy herds compared to conventional herds. The aim of this study was to investigate the association between production system (conventional/organic), season (summer/winter) and calf mortality risk, diarrhea, signs of respiratory disease and ocular discharge, respectively, for dairy heifer calves aged 0-180 days. Sixty Danish dairy herds, 30 conventional and 30 organic, were visited once during summer and once during winter. During the herd visits, calves were clinically examined for signs of diarrhea, hampered respiration, nasal discharge, coughing and ocular discharge. Data on mortality were obtained from the Danish Cattle Database. Data were analyzed using logistic regression models, with mortality risk and disease measures as outcome variables for each of three calf age groups: 0-28, 29-90 and 91-180 days. In organic herds, odds of mortality among calves aged 0-28 days were 2.09 (95% confidence interval (CI): 1.38-3.15) times higher during winter compared to summer. Odds of nasal discharge for calves 0-28 days in organic herds were 10.3 (95% CI: 2.27-46.6), 10.7 (95% CI: 2.40-40.0) and 5.97 (95% CI: 1.29-27.6) times higher for organic and conventional herds during winter (OW and CW) and conventional herds during summer (CS) respectively, compared to organic herds during summer (OS). For calves aged 29-90 days, odds of nasal discharge were 8.22 (95% CI: 3.88-17.4), 8.06 (95% CI: 3.18-20.4) and 2.86 (95% CI: 1.08-7.55) times higher for OW, CW and CS respectively, compared to OS. Odds of nasal discharge for calved aged 91-180 days were 7.03 (95% CI: 3.95-12.5) and 4.27 (95% CI: 1.81-10.1) times higher for OW and CW respectively compared to OS. For calves aged 29-90 days, odds of coughing were 2.23 (95% CI: 1.06-4.71) and 3.82 (95% CI: 1.76-8.21) times higher for OW and CW compared to OS, while odds of coughing for calves aged 91-180 days were 2.09 (95% CI: 1.19-3.67) and 2.55 (95% CI: 1.39.4.67) times higher for OW and CW compared to OS. Odds of ocular discharge for calves aged 29-90 days were 0.22 (95% CI: 0.10-0.52), 0.27 (95% CI: 0.11-0.66) and 0.42 (95% CI: 0.18-0.99) times higher for OW, CW and CS compared to OS. In conclusion, mortality and morbidity of Danish dairy heifer calves are, for some variables and in certain age groups, dependent on production system and season.

Against the background of divergent political developments across Europe, farm animal welfare (FAW) science has evolved during the last three decades as an inter-disciplinary research area. Recent achievements include pan-European research projects and the implementation of animal welfare assessment systems on-farm. The aim of this study was mapping activities for FAW science and investigating geographical differences in FAW research in Europe (EU28 + candidate countries and the European Economic Area) with regard to available resources (e.g. human resources, infrastructure, funding) and research output (e.g. collaborations and publications). Further, we enquired if economic attributes such as the Coefficient of National Innovation Capacity (NIC) were associated with the reported available resources and research output factors (publications and collaborations) of FAW research. Based on questionnaires sent out to a wide researcher network in regions of an enlarged Europe, we found differences with regard to ‘input factors’ such as human resources, animal and laboratory facilities and national and international research funding and ‘output factors’ such as inter/national collaboration, participation in EU-funded projects related to FAW and number of publications. Respondents were allocated to 4 Western and 4 Eastern geographical clusters of countries (‘hubs’). There were a larger number of researchers, students and technical staff per laboratory in Western compared to Eastern hubs. A pronounced difference was found for funding, as 35% of respondents in the Eastern hubs stated that they lack funded FAW projects compared to 4% in the West. In general, respondents from the Western hubs stated significantly more often that they run projects in the field of FAW research (p = 0.034). Furthermore they were significantly more involved in EU-funded schemes, such as FP7 (EU’s Research and Innovation Funding Programme for 2007–2013) with 24% (p = 0.013) and in ERA-NET Cofund projects (European Research Area—Coordination of Research Programmes) with 5.7% (p = 0.042). The average sum of impact factors from 5 self-named citations was 3.0 ± 2.8 (mean, SD) in the Eastern hubs and 7.5 ± 4.4 in the Western Hubs. When investigating associations of the economic status of EU countries with resource factors and achievements in FAW research, the ‘Coefficient of National Innovation Capacity (NIC)’ was moderately correlated with the input factors for FAW research such as the average number of PhDs currently employed in the institutions (r s = 0.66; p < 0.001) and the total number of employed researchers (r s = 0.56; p < 0.01). Stronger associations were found between the scientific output and the economic ranking, here represented by the cumulative impact factor of their published papers (r s = 0.74; p < 0.001), and between the number of EC-project reports published in CORDIS 2015 with NIC (r s = 0.67; p < 0.001). We conclude that due to economic disadvantages as represented by the lower NIC or rare participation in EU-funding schemes, the Eastern Hubs could not reach the same level of output factors as the Western Hubs, which negatively impacts on the number of young researchers (PhDs) and impact factors, thus resulting in lower visibility and influence.

The Welfare Quality (WQ) protocol for on-farm dairy cattle welfare assessment describes 27 measures and a stepwise method for integrating values for these measures into 11 criteria scores, grouped further into 4 principle scores and finally into an overall welfare categorization with 4 levels. We conducted an online survey to examine whether trained users' opinions of the WQ protocol for dairy cattle correspond with the integrated scores (criteria, principles, and overall categorization) calculated according to the WQ protocol. First, the trained users' scores (n = 8-15) for reliability and validity and their ranking of the importance of all measures for herd welfare were compared with the degree of actual effect of these measures on the WQ integrated scores. Logistic regression was applied to identify the measures that affected the WQ overall welfare categorization into the "not classified" or "enhanced" categories for a database of 491 European herds. The smallest multivariate model maintaining the highest percentage of both sensitivity and specificity for the "enhanced" category contained 6 measures, whereas the model for "not classified" contained 4 measures. Some of the measures that were ranked as least important by trained users (e.g., measures relating to drinkers) had the highest influence on the WQ overall welfare categorization. Conversely, measures rated as most important by the trained users (e.g., lameness and mortality) had a lower effect on the WQ overall category. In addition, trained users were asked to allocate criterion and overall welfare scores to 7 focal herds selected from the database (n = 491 herds). Data on all WQ measures for these focal herds relative to all other herds in the database were provided. The degree to which expert scores corresponded to each other, the systematic difference, and the correspondence between median trained-user opinion and the WQ criterion scores were then tested. The level of correspondence between expert scoring and WQ scoring for 6 of the 12 criteria and for the overall welfare score was low. The WQ scores of the protocol for dairy cattle thus lacked correspondence with trained users on the importance of several welfare measures.

32 The Welfare Quality® (WQ) protocol for on-farm dairy cattle welfare assessment describes 33 27 measures and a step-wise method to integrate values for these measures into 12 criteria 34 scores, grouped further into four principle scores and finally into an overall welfare 35 categorization with four levels. We conducted an online survey to examine whether trained 36 users’ opinions of the WQ protocol for dairy cattle correspond with the integrated scores 37 (criteria, principles and overall categorization) calculated according to the WQ protocol. First, 38 the trained users’ scores (n = 8 15) for reliability, validity and their ranking of the 39 importance of all measures for herd welfare were compared to the degree of actual impact of 40 these measures on the WQ integrated scores. Logistic regression was applied to identify the 41 measures that affected the WQ overall welfare categorization into the ‘not classified’ or 42 ‘enhanced’ categories for a database of 491 European herds. The smallest multivariate model 43 whilst maintaining the highest % of both sensitivity and specificity for the ‘enhanced’ 44 category contained six measures, the model for not-classified contained four measures. Some 45 of the measures that were ranked as least important by trained users (e.g. measures relating to 46 drinkers) had the highest influence on the WQ overall welfare categorization. Conversely, 47 measures rated as most important by the trained users (e.g. lameness and mortality) had a 48 lower impact on the WQ overall category. In addition, trained users were asked to allocate 49 3 ‘criterion’ and ‘overall’ welfare scores to seven focal herds selected from the database (n = 50 491 herds). Data on all WQ measures for these focal herds relative to all other herds in the 51 database were provided. The degree to which expert scores corresponded to each other, the 52 systematic difference and the correspondence between median trained-user opinion and the 53 WQ criterion scores were then tested. The level of correspondence between expert scoring vs. 54 WQ scoring for 6 of the 12 criteria and for the overall welfare score was low. The WQ scores 55 of the protocol for dairy cattle thus lacked correspondence with trained users on the 56 importance of several welfare measures. 57