Measuring resilience in farm animals: theoretical considerations and application to dairy cows
Resilience: reference measures based on longer-term consequences are needed to unlock the potential of precision livestock farming technologies for quantifying this trait
Recommendation: posted 21 December 2021, validated 07 February 2022
Farm animals differ in their ability to respond to the many environmental challenges they face. Such challenges include infectious diseases, metabolic diseases resulting from inadequate coverage of dietary needs, as well as the diverse consequences of climate change. Various concepts exist to characterise the responses of animals to different types of challenges. This article by Friggens et al. (2022) focuses on resilience, providing a conceptual definition and proposing a method to quantify resilience in dairy cows.
The first part of the paper provides a definition of resilience and highlights its differences and relations with the related concepts of robustness, and, to a lesser extent, resistance and tolerance. In essence, resilience is the ability of an animal to bounce back quickly after a challenge of limited duration. On the other hand, robustness is the ability of an animal to cope with conditions that are overall unfavourable. From these conceptual and intuitive definitions, there are several difficulties precluding the design of concrete methods to measure resilience. First, there is some degree of overlap between the concepts of resilience, robustness, resistance and tolerance. Secondly, resilience is a multidimensional concept whereby resilience to a given perturbation does not imply resilience to other types of perturbation, e.g. resilience to a challenge by a specific pathogen does not imply resilience to a nutritional challenge. A further difficulty in the measure of resilience is the fact that different animals may be exposed to challenges that are different in nature and in number. The authors argue that although resilience cannot be measured directly (it should be seen as a latent construct), it is possible to quantify it indirectly through its consequences.
In the second part of the paper, the authors propose a method to quantify resilience of individual dairy cows. The method is based on the premise that resilient animals should be kept longer in their herd than non-resilient animals. The main criterion in the evaluation is therefore the ability of cows to re-calve. Each cow that is calving receives a certain number of points, to which, in each lactation, bonus points are added for higher milk production and penalty points are removed for each insemination after the first one, for each disease event and for each day of calving interval above some herd specific value. Therefore, cows have a resilience score in each lactation. They also have a lifetime resilience score obtained by summing the scores for all the lactations, that gets bigger as the cow has more calves, and that also takes the age at first calving into account. In a previous study, Adriaens et al. (2020) showed that higher resilience scores were associated with fewer drops in milk yield and more stable activity dynamics.
Starting from theoretical considerations on the notion of resilience, this paper describes a concrete method to quantify animal-level resilience on farm. Such quantification will be useful for breeding and culling decisions. Finally, the general framework to design resilience measures that is presented will be useful to researchers working on the quantification of farm animal resilience using new methods and data sources.
Adriaens I, Friggens NC, Ouweltjes W, Scott H, Aernouts B and Statham J 2020. Productive life span and resilience rank can be predicted from on-farm first-parity sensor time series but not using a common equation, across farms. Journal of Dairy Science 103, 7155-7171.https://doi.org/10.3168/jds.2019-17826
Friggens, N.C. , Adriaens, I., Boré, R., Cozzi, G., Jurquet, J., Kamphuis, C., Leiber, F., Lora, I., Sakowski, T., Statham, J., De Haas, Y. (2022). Resilience: reference measures based on longer-term consequences are needed to unlock the potential of precision livestock farming technologies for quantifying this trait. Zenodo, 5215797, ver. 5 peer-reviewed and recommended by Peer community in Animal Science. https://dx.doi.org/10.5281/zenodo.5215797
Aurélien Madouasse (2021) Measuring resilience in farm animals: theoretical considerations and application to dairy cows. Peer Community in Animal Science, 100010. https://dx.doi.org/10.24072/pci.animsci.100010
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article. The authors declared that they comply with the PCI rule of having no financial conflicts of interest in relation to the content of the article.
Evaluation round #1
DOI or URL of the preprint: https://doi.org/10.5281/zenodo.5215797
Author's Reply, 26 Nov 2021
Decision by Aurélien Madouasse, posted 26 Oct 2021
In this preprint the concept of resilience in livestock is discussed and operational measures of resilience in dairy cows are proposed. The article nicely mixes conceptual definitions, practical implications for the measure and an application.
Three experts in the field reviewed the article. They highlighted the relevance of the question addressed and the overall good quality of the work presented. However, they also raised a number of questions and made comments that I would like you to address.
From the different comments, it seems that some clarifications are needed, either in the definition section or in the discussion, on the relationships between resilience and other concepts such as robustness, productive efficiency or disease resilience. As part of this, careful consideration should be given to Figure 1.
Lastly, PCI requires authors to make the raw data, codes and scripts available. Reading the paper, the origin of the data used in the example (1800 lactations from Table 2) was not clear to me. Could you clarify this?
I invite you to respond to the reviewers' comments, and I look forward to receiving a revised version of your work.