Abstract

Simple SummaryTo give a complete picture of animal welfare on a farm, different welfare measures must be combined. The aim of this paper is to assess the method by which this is achieved within the EU-funded project Welfare Quality® (WQ). According to the protocols of WQ, individual animals with welfare problems contribute disproportionately more to a lower animal welfare score when they are associated with farms with an otherwise low prevalence of welfare problems compared to farms with a higher prevalence. As a consequence, the addition of a single lame cow on a farm with relatively few lame cows will have a greater consequence for the welfare score than on a farm with more lame cows. The stated aim of this aspect of the protocols is to prevent welfare problems being masked as a result of attaining better scores in other areas. By combining a case study of 44 Danish dairy farms and a questionnaire study of over 150 animal welfare experts, we test whether the system successfully prevents masking of problems that experts find to be unacceptable. Our findings indicate that this is not the case, and we conclude that better methods of summarizing farm-level animal welfare measures are required.Welfare Quality® proposes a system for aggregation according to which the total welfare score for a group of animals is a non-linear effect of the prevalence of welfare scores across the individuals within the group. Three assumptions serve to justify this: (1) experts do not follow a linear reasoning when they assess a welfare problem; (2) it serves to prevent compensation (severe welfare problems hidden by scoring well on other aspects of welfare); (3) experts agree on the weight of different welfare measures. We use two sources of data to examine these assumptions: animal welfare data from 44 Danish dairy farms with Danish Holstein Friesian cows, and data from a questionnaire study with a convenience sample of 307 experts in animal welfare, of which we received responses from over 50%. Our main results were: (1) the total group-level welfare score as assigned by experts is a non-linear function of the individual animal welfare states within the group; (2) the WQ system does not prevent what experts perceive as unacceptable compensation; (3) the level of agreement among experts appears to vary across measures. Our findings give rise to concerns about the proposed aggregation system offered by WQ.

Highlights

  • Welfare Quality® (WQ) proposes a system for aggregating animal welfare indicators that goes against a strong dogma in animal welfare science, i.e., that welfare is defined by the state of an individual animal [1], and that the welfare of a group is arguably equal to the sum of the welfare of the individual animals within that group

  • The WQ aggregation system appears to be based on three assumptions: (1) that experts view the total welfare score for a group of animals as a non-linear effect of the prevalence of welfare scores of the individuals within the group; (2) that this kind of system will prevent compensation, i.e., the opportunity to hide severe welfare problems by scoring well on other aspects of welfare; (3) that experts agree on the relative weight that should be assigned to different welfare indicators during aggregation

  • We have described the first step of the aggregation procedure, where an index for the occurrence of a certain kind of welfare problem is transformed into a welfare score

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Summary

Introduction

Welfare Quality® (WQ) proposes a system for aggregating animal welfare indicators that goes against a strong dogma in animal welfare science, i.e., that welfare is defined by the state of an individual animal [1], and that the welfare of a group is arguably equal to the sum of the welfare of the individual animals within that group. It was decided that mild lameness should be given a weight of 2 and severe lameness a weight of 7, so that in terms of welfare impact, one severely lame cow would be equal to three and a half mildly lame cows. On this basis, an index for lameness ranging from 0 to 100 was defined. An index for lameness ranging from 0 to 100 was defined This index score is a linear and additive function of the relative number of lame cows adjusted with the given weights

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