Validation of key indicators in cattle farms at high risk of animal welfare problems: a qualitative case-control study

An analysis of substantiated complaints made about incidents of poor livestock welfare, in Victoria, Australia

Incidents of poor welfare on farm in Victoria, Australia, are generally identified during an investigation that follows receipt of a complaint. Using deidentified records of complaints received by the Victoria State Government between 2011 and 2020, this study aimed to describe the source, number and the relationship between rainfall/stock prices and substantiated welfare complaints (SWC). Only incidents involving non-dairy cattle, sheep and goats in extensive farming systems will be considered. The main source of complaints received by the Victorian Government is the general public. Almost half of all complaints were made for cattle (48%), 39% for sheep, 11% for mixed species, and 2% for goats. The number of SWC varied between months, each year and across the different regions of Victoria. The ratio of the actual mean rainfall of the last three seasons to the long-term mean of the last three seasons of rainfall (RL3SR) and livestock prices together were the best predictors of the total number of SWC (adjusted R square value for heavy lamb-RL3SR was highest (0.590), followed by merino lamb-RL3SR (0.588), goat-RL3SR (0.545) and steer-RL3SR (0.478) all were significant (p ≤ 0.05)). The rainfall by region and town were not good predictors of the number of SWC. There was a correlation between rainfall and the number of SWC, possibly due to changes in pasture availability. Favorable seasonal conditions however, were not protective of livestock welfare and it is likely a number of factors may be implicated.

Data-Based Variables Used as Indicators of Dairy Cow Welfare at Farm Level: A Review

Simple Summary

In recent years, the interest in the use of data from routine herd records in the monitoring of dairy welfare at farm level has increased. This review compiles 13 papers to outline the current potential of data-based variables for animal welfare monitoring. All the identified studies showed associations between data-based variables and farm-level dairy cow welfare and therefore provide a first indication of the possible use and suitability of data-based variables for welfare monitoring. However, we found that the definitions of animal welfare, its assessment on the farm, and the data-based variables varied considerably. Consequently, the current state of research does not allow a conclusive assessment of the potential of data-based variables for animal welfare monitoring. Therefore, future research is needed to clarify the potential of data-based variables. Harmonisation of the data-based variables and the use of valid measurements that reflect the multidimensionality of welfare could contribute to increased comparability between the studies.

Abstract

During the last years, the interest in data-based variables (DBVs) as easy-to-obtain, cost-effective animal welfare indicators has continued to grow. This interest has led to publications focusing on the relationship between DBVs and animal welfare. This review compiles 13 papers identified through a systematic literature search to provide an overview of the current state of research on the relationship between DBVs and dairy cow welfare at farm level. The selected papers were examined regarding their definition of animal welfare and classified according to this definition into three categories: (a) papers evaluating DBVs as predictors of animal welfare violations, (b) papers investigating the relationship between DBVs and animal-based measurements, and (c) papers investigating the relationship of DBVs to scores of welfare assessments like the Welfare Quality protocol or to overall welfare scores at farm level. In addition, associations between DBVs and indicators of animal welfare were extracted, grouped by the type of DBV, and examined for replications that may confirm the associations. All the identified studies demonstrated associations between DBVs and animal welfare. Overall, the first indications of a possible suitability of DBVs for predicting herds with animal welfare violations as well as good or poor animal welfare status were given. The evaluation of relationships between DBVs and animal-based measurements (ABMs) found mortality-based DBVs to be frequently associated with ABMs. However, owing to varying definitions of animal welfare, the use of different variants of DBVs, and different methods used to assess DBVs, the studies could only be compared to a limited extent. Future research would benefit from a harmonisation of DBVs and the use of valid measurements that reflect the multidimensionality of welfare. Data sources rarely investigated so far may have the potential to provide additional DBVs that can contribute to the monitoring of cow welfare at farm level.

Exploring farmers' attitudes and determinants of dairy calf welfare in an expanding dairy sector

The 2015 European Union milk quota abolition initiated considerable expansion in the dairy sector in many European Union countries, most significantly in Ireland. However, this major production increase also had wider societal implications, such as negative environmental and animal welfare consequences. In this article, we used survey data of 441 Irish dairy farmers to assess farmers' attitudes toward the welfare of farmed animals and dairy calves, as well as the reputation of the Irish dairy sector. We also explored how expansion, breeding, calf management, and farmer characteristics relate to calf welfare outcomes (i.e., calf mortality, calf export, and premature culling). In relation to attitudes, farmers expressed a general concern toward animal welfare, while views toward dairy calves and industry reputation were mixed. We used Ward's linkage hierarchical cluster analysis to group farmers based on their attitudes. The cluster analysis revealed 3 distinct groups relating to high, medium, and low animal welfare concern. Herd expansion was negatively associated with being in a higher animal welfare concern cluster, whereas beef trait-focused breeding was positively associated with it. In relation to dairy calf welfare outcomes, our econometric analyses based on multiple regression and binary choice models revealed that expansion was positively associated with calf mortality, whereas improved breeding and calf management factors had a negative association. In addition, being in the high animal welfare concern cluster was negatively associated with calf mortality. Furthermore, breeding decisions were significantly associated with whether calves were exported, and being in the high animal welfare concern cluster was negatively associated with the probability that calves were sent for live export. Finally, farmers' breeding and calf management decisions were associated with premature culling of calves. Overall, this article revealed strategies worth promoting to improve dairy calf welfare, such as beef trait-focused breeding leading to greater dairy-beef integration.

Evaluation of the association between the introduction of data-driven tools to support calf rearing and reduced calf mortality in dairy herds in the Netherlands

Between 2009 and 2017, calf mortality in the Dutch dairy sector showed a slight but steady increase. The Dutch dairy industry decided to act and supported the development of several data-driven tools that were implemented from 2018 on. The tools informed farmers about their calf mortality rates and stimulated them to improve. The Trend Analysis Surveillance Component of the Dutch cattle Health Surveillance System provided the possibility to evaluate the calf mortality in Dutch dairy herds before and after implementation of these tools. The aim of this study was to evaluate the association between calf mortality and i) all actions that were taken by the Dutch dairy industry to improve the quality of calf rearing and ii) other potential management or environmental factors associated with calf mortality in Dutch dairy herds. Census data from approximately 98 % of all Dutch dairy herds were available from July 2014 until June 2019. Four different calf mortality indicators were defined: perinatal calf mortality risk (i.e., mortality before, during, or shortly after the moment of birth up to the moment of ear-tagging), postnatal calf mortality risk (ear-tagging till 14 d), preweaned calf mortality rate (15 d-55 d) and weaned calf mortality rate (56 d-1 yr.). All data were aggregated to herd and monthly level and were analysed using Population-Averaged Generalized Estimating Equations (PA GEE models) with a Poisson distribution and log link function. When the period before implementation of the tools (2016-2017) was compared to the period thereafter (2018-2019), all four calf mortality indicators decreased. The relative decrease varied from 3 % (postnatal calves) and 10 % (perinatal calves) up to 18 % and 30 % in preweaned and weaned calves, respectively. Registrations of veterinary treatments such as antimicrobial use, vaccinations (calf or cow) and antiparasitic treatments were associated with calf mortality. Additionally, herds with a higher level of metabolic problems in transition cows had a higher calf mortality and also extreme outside temperatures were associated with higher calf mortality. Given that the different tools were implemented nation-wide and a control group was lacking, we could not prove that implementing the different tools caused the reduction in calf mortality. We do however, believe that all the actions and communication towards improvement of calf rearing in dairy herds led to an increased awareness among farmers towards the importance of calf rearing management and therefore a reduction in calf mortality on national level.

Quantifying calf mortality on dairy farms: Challenges and solutions

In the Netherlands, the mortality rate of ear-tagged calves <1 yr is one of the indicators that is continuously monitored in census data and is defined as the number of deceased calves relative to the number of calf-days-at-risk. In 2017, yearly calf mortality rates were published in the lay press and resulted in discussions about the calculation of this parameter among stakeholders because the same parameter appeared to be calculated in many different ways by different organizations. These diverse definitions of calf mortality answered different aims such as early detection of deviations, monitoring trends, or providing insight into herd-specific results, but were difficult to understand by stakeholders. The aim of this study was to evaluate several definitions of calf mortality for scientific validity, usefulness for policymakers, and comprehensibility by farmers. Based on expert consultations, 10 definitions for calf mortality were evaluated that assessed different age categories, time periods, and denominators. Differences in definitions appeared to have a large effect on the magnitude of mortality. For example, with the original mortality parameter, the mortality rate was 16.5% per year. When the first year of life was subdivided into 3 age categories, the mortality rate was 3.3, 4.5, and 3.1% for postnatal calves (≤14 d), preweaned calves (15-55 d), and weaned calves (56 d-1 yr), respectively. Although it was logical that these mortality rates were lower than the original, the sum of the 3 separate mortality rates was also lower than the original mortality rate. The reason was that the number of calves present in a herd and the risk of mortality are not randomly distributed over a calf's first year of life and the conditional nature of mortality rates when calculated for different age categories. Ultimately, 4 parameters to monitor calf mortality in Dutch dairy herds were chosen based on scientific value, usefulness for monitoring of trends, and comprehensibility by farmers: perinatal calf mortality risk (i.e., mortality before, during, or shortly after the moment of birth up to the moment of ear-tagging), postnatal calf mortality risk (≤14 d), preweaned calf mortality rate (15-55 d), and weaned calf mortality rate (56 d-1 yr). Slight differences in definitions of parameters can have a major effect on results, and many factors have to be taken into account when defining an important health indicator such as mortality. Our evaluation resulted in a more thorough understanding of the definitions of the selected parameters and agreement by the stakeholders to use these key indicators to monitor calf mortality.

Management factors associated with mortality of dairy calves in Finland: A cross sectional study

Mortality at herd level is an indicator of overall calf welfare on dairy farms. The aim of this cross sectional study was to identify management factors associated with calf mortality on dairy farms in Finland. Calf mortality data and information on management practices collected during farm visits and farmer interviews were analysed using linear models. The average size of 82 herds enrolled in the study was 125 ± 41 cows. The mortality risk of calves <7 days of age was 5 (or 5.2) ± 2.3% and was associated with larger herd size and the practice of not separating sick calves from other calves (6.0 ± 0.4 vs. 4.7 ± 0.3%; P < 0.05). The mortality risk of calves aged 7-180 days was 6 (or 5.7) ± 6.2% and increased with a shorter whole milk feeding period, longer period in the calving pen and lower average herd production level (P < 0.05). The mortality risk of calves was lower on farms where a veterinarian disbudded calves instead of farmer. Longer milk feeding and improved management of sick calves are recommended to reduce calf mortality. Specific management practices associated with lower mortality risk should be emphasised when advising farmers on how to enhance calf welfare.

Dilemmas experienced by government veterinarians when responding professionally to farm animal welfare incidents in Ireland

OBJECTIVES

This paper identifies the dilemmas experienced by government veterinarians during their investigations of farm animal welfare incidents that involve herd owner social, health, and/or psychological difficulties. The paper builds on exploratory qualitative research into the impact of these difficulties on farm animal welfare.

DESIGN

The study used a qualitative research approach. Focus groups were conducted.

SETTING

In Ireland, an Early Warning System (EWS), which brings together relevant agencies, is in place to identify and prevent farm animal welfare problems before they become critical. This study is concerned with the experiences of government veterinarians who respond to farm animal welfare incidents. Specific focus is on incidents that involve herd owner social/psychological/health-related difficulties.

PARTICIPANTS

In total, n=18 government veterinarians (representing 15 per cent of the population sample), all with a keen interest in farm animal welfare, participated. These were selected on the basis of their interest, experience, and involvement in farm animal welfare. One government veterinarian declined to participate. Four focus groups were conducted with government veterinarians. These took place in the south (S), south-west (SW), midlands (M), and north-west region of Ireland (NW). All 16 District Veterinary Offices (DVOs) were represented in the focus groups.

RESULTS

The results reveal three professional dilemmas that exist for government veterinarians: (1) defining professional parameters; (2) determining the appropriate response; (3) involvement versus detachment. Participants reported not wanting any additional training. Instead, it was agreed that a formal bridge to social service providers who have the professional capability to respond appropriately and with confidence, was required.

CONCLUSIONS

Clearly defined guidelines are required for government veterinarians in their encounters with farm animal welfare incidents where there is a complex human component. A coordinated multiagency approach that is flexible enough to meet the needs of individual farm animal welfare cases is required.