Prat-Benhamou A, Meuwissen M P M, Slijper T, Bernués A, Gaspar-García P, Lizarralde J, Mancilla-Leytón J M, Mandaluniz N, Mena Y, Soriano B, Martín-Collado D
Departamento de Ciencia Animal, Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA), Av. Montañana, 930, Zaragoza 50059, Spain; Instituto Agroalimentario de Aragón-IA2 (CITA-Universidad de Zaragoza), C. Miguel Servet, 177, 50013 Zaragoza, Spain.
Business Economics Group, Wageningen University & Research, Hollandseweg, 1, Wageningen 6706KN, the Netherlands.
Animal. 2025 Jul;19(7):101566. doi: 10.1016/j.animal.2025.101566. Epub 2025 Jun 9.
There is a growing interest in studying farm resilience. Typically, resilience assessments focus on crisis outcomes, with less attention paid to assess the system characteristics that contribute to building resilience, i.e. resilience attributes. This is partly due to a lack of practical approaches to assess these attributes. The objective of this paper is to develop a practical approach to assess and compare the status of livestock farms' resilience attributes in different farming systems. We identified 21 resilience attributes that generally contribute to farm resilience based on a literature review. We operationalised resilience attributes into 85 indicators quantifiable through primary farm data, such percentage of feed produced on the farm. We assessed three small ruminant case studies in Spain: (i) meat sheep farms in Aragón; (ii) dairy sheep farms in the Basque Country and Navarre; (iii) dairy goat farms in Andalusia. We conducted farmer surveys (n = 144) to measure the indicators, and organised three workshops with farmers and other local stakeholders (n = 20) to assess the importance of the resilience attributes in the three case studies. We aggregated indicators into resilience attribute scores using a minimum-maximum normalisation procedure. Using stakeholders' assessments, we calculated attribute weights by a budget allocation process. Attribute scores and weights were then used to calculate an overall resilience score (ranging from 0 to 100). The comparison of attribute scores revealed strengths and weaknesses for resilience in each case study. In the meat sheep system, honours legacy was a major strength, while work and quality of life was a weakness. In the dairy sheep system, sector organisation was a major strength, while the redundance of productive alternatives was a weakness. For dairy goat farms, the infrastructure of the areas where farmers live was a major strength, but feed autonomy and the attributes related to the access and use of natural resources were weaknesses. The perceived importance of attributes (weights) differed across cases. Particularly, human capital emerged as one of the most relevant ones across case studies. Farms' overall resilience scores were significantly lower in the dairy goat system. Our approach allows to find what attributes build resilience in farms and to highlight areas of improvement to strengthen their resilience. Our findings are of importance to farmers, technicians and policymakers who are interested in assessing resilience as we provide a practical approach to quantify and compare resilience of farms.
对农场恢复力的研究兴趣与日俱增。通常，恢复力评估聚焦于危机结果，而较少关注评估有助于构建恢复力的系统特征，即恢复力属性。部分原因在于缺乏评估这些属性的实用方法。本文的目的是开发一种实用方法，以评估和比较不同养殖系统中畜牧场恢复力属性的状况。基于文献综述，我们确定了21个通常有助于农场恢复力的恢复力属性。我们将恢复力属性转化为85个可通过农场原始数据量化的指标，例如农场自产饲料的比例。我们评估了西班牙的三个小型反刍动物案例研究：（i）阿拉贡的肉羊养殖场；（ii）巴斯克地区和纳瓦拉的奶羊养殖场；（iii）安达卢西亚的奶山羊养殖场。我们开展了农民调查（n = 144）以测量这些指标，并与农民和其他当地利益相关者（n = 20）组织了三次研讨会，以评估恢复力属性在这三个案例研究中的重要性。我们使用最小 - 最大归一化程序将指标汇总为恢复力属性得分。通过预算分配过程，利用利益相关者的评估来计算属性权重。然后使用属性得分和权重来计算总体恢复力得分（范围从0到100）。属性得分的比较揭示了每个案例研究中恢复力的优势和劣势。在肉羊系统中，荣誉传承是主要优势，而工作和生活质量是劣势。在奶羊系统中，行业组织是主要优势，而生产替代方案的冗余性是劣势。对于奶山羊养殖场，农民居住地区的基础设施是主要优势，但饲料自主性以及与自然资源获取和使用相关的属性是劣势。不同案例中属性的感知重要性（权重）有所不同。特别是，人力资本在各个案例研究中都是最相关的因素之一。奶山羊系统中农场的总体恢复力得分明显较低。我们的方法能够找出农场中构建恢复力的属性，并突出需要改进的领域以增强其恢复力。我们的研究结果对于有兴趣评估恢复力的农民、技术人员和政策制定者具有重要意义，因为我们提供了一种量化和比较农场恢复力的实用方法。
