The Welfare Aggregation and Guidance (WAG) Tool: A New Method to Summarize Global Welfare Assessment Data for Equids

Abstract

Animal welfare can be represented by an array of indicators. There is, however, increasing demand for concise welfare assessments that can be easily communicated and compared. Previous methods to aggregate welfare assessments have focused on livestock systems and produced a single welfare score, which may not represent all aspects of welfare. We propose an aggregation method for the recently developed Equid Assessment Research and Scoping (EARS) welfare assessment tool that results in grades for five welfare categories: housing conditions, working conditions, health, nutrition, and behavior. We overcome the problems associated with existing approaches by using a single aggregation method (decision trees) that incorporates the most important welfare indicators in a single step. The process aims to identify equids with the poorest welfare and aid decision-making when allocating resources. We demonstrate its application using a case study of over 6000 equids across Europe and Asia, where equids in India and Pakistan had the poorest welfare status in terms of health (respiratory disease and open wounds) and behavior (signs of fear and distress, and limb tethering practices). We recommend identification of the specific causes of these issues, using either existing detailed welfare data or through issue-specific assessments by an appropriate professional, to guide the development of appropriate interventions and, ultimately, improve equid welfare.

Keywords

• welfare aggregation, equid welfare, methodology, resource allocation