Raw Zoe, Rodrigues Joao B, Rickards Karen, Ryding Joe, Norris Stuart L, Judge Andrew, Kubasiewicz Laura M, Watson Tamlin L, Little Holly, Hart Ben, Sullivan Rebekah, Garrett Chris, Burden Faith A
The Donkey Sanctuary, Sidmouth, Devon, EX10 0NU, UK.
Animals (Basel). 2020 Feb 13;10(2):297. doi: 10.3390/ani10020297.
The assessment of animal welfare poses numerous challenges, yet an emerging approach is the consolidation of existing knowledge into new frameworks which can offer standardised approaches to welfare assessment across a variety of contexts. Multiple tools exist for measuring the welfare of equids, but such tools have typically been developed for specific contexts. There is no 'one size fits all' which means that resulting datasets are generally non-comparable, creating a barrier to knowledge-sharing and collaboration between the many organisations working to improve equid welfare around the globe. To address this, we developed the Equid Assessment, Research and Scoping (EARS) tool, which incorporates pre-existing validated welfare assessment methods alongside new welfare indicators to deliver a larger and more comprehensive series of welfare indicators than currently exists, creating a single resource that can be used to assess equid welfare in any context. We field-trialled three welfare assessment protocols within the EARS tool, and applied these to welfare assessment of equids in a variety of contexts across nineteen countries. The EARS tool proved a useful, versatile and rapid method for collecting welfare assessment data and we collected 7464 welfare assessments in a period of fifteen months. We evaluate the EARS tool and provide ideas for future development.
动物福利评估面临诸多挑战，但一种新兴方法是将现有知识整合到新框架中，这些框架可为各种情况下的福利评估提供标准化方法。有多种工具可用于衡量马属动物的福利，但此类工具通常是针对特定情况开发的。不存在“一刀切”的方法，这意味着由此产生的数据集通常不可比，为全球众多致力于改善马属动物福利的组织之间的知识共享与合作造成了障碍。为解决这一问题，我们开发了马属动物评估、研究与范围界定（EARS）工具，该工具将预先存在的经过验证的福利评估方法与新的福利指标相结合，提供了比现有指标更大、更全面的一系列福利指标，创建了一个可用于在任何情况下评估马属动物福利的单一资源。我们在EARS工具中对三种福利评估方案进行了实地试验，并将其应用于19个国家各种情况下的马属动物福利评估。EARS工具被证明是一种有用、通用且快速的收集福利评估数据的方法，我们在15个月的时间里收集了7464份福利评估。我们对EARS工具进行了评估，并为其未来发展提供了思路。
