Dairy farming is deeply affected by climate change, especially by rising temperatures and heat waves, poorer availability of quality food and water, and the spread of new diseases and pests outside their original ecological niche. Their impact can be mitigated not only by changes in technologies, management and treatment, but also by breeding and selection of more resilient cows. General resilience encompasses the animal’s capacity to cope with environmental, social and disease challenges. It is described as the capacity of the animal to be minimally affected by a disturbance or to rapidly return to the physiological, behavioural, cognitive, health, affective and production states that pertained before exposure to a disturbance. As disturbances can be of different natures, general resilience is a composite trait consisting of different resilience types according to the nature of the disturbance. Resilience can be quantified through time series data that capture fluctuations in the daily performance. Recent studies have worked with deviations in the daily milk yield and daily live weight from optimal performance or have focused on the assessment of the daily activity in terms of the daily step count. To observe the duration and magnitude of the response to perturbance, two indicators were suggested: the autocorrelation (rauto) and the natural logarithm of deviations (LnVar). Based on the daily milk yield deviations, both indicators have shown sufficient genetic variabilities with the estimated heritability ~0.1 for rauto and ~0.2 for LnVar. Low values of both indicators were genetically related to better udder health, better hoof health, better longevity, better fertility, higher body condition score, less ketosis but also lower milk yield level. The selection for improved resilience could benefit from the use of genomic information as several genes and biological pathways associated with disease resilience and resilience to heat stress have already been identified. The presented results suggest that the integration of resilience into the cattle breeding programmes would improve the capacity of the dairy industry to cope with global climate change.
Adriaens I, Friggens NC, Ouweltjes W, Scott H, Aernouts B, Statham J. 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. J Dairy Sci. 2020 Aug;103(8):7155-71.
https://doi.org/10.3168/jds.2019-17826
Albers GAA, Gray GD, Piper LR, Barker JSF, Le Jambre LF, Barger IA. The genetics of resistance and resilience to Haemonchus contortus in young Merino sheep. Int J Parasitol. 1987 Oct;17(7):1355-63.
Ben Abdelkrim A, Tribout T, Martin O, Boichard D, Ducrocq V, Friggens NC. Exploring simultaneous perturbation profiles in milk yield and body weight reveals a diversity of animal responses and new opportunities to identify resilience proxies. J Dairy Sci. 2021 Jan;
https://doi.org/10.3168/jds.2020-18537
104(1):459-70.
Berghof TVL, Poppe M, Mulder HA. Opportunities to improve resilience in animal breeding programs. Front Genet. 2019 Jan 14;9: 15 p.
Bezdicek J, Nesvadbova A, Makarevich A, Kubovicova E. Negative impact of heat stress on reproduction in cows: Animal husbandry and biotechnological viewpoints: A review. Czech J Anim Sci. 2021 Jul 27;66(8):293-301.
https://doi.org/10.17221/44/2021-CJAS
Bisset SA, Morris CA. Feasibility and implications of breeding sheep for resilience to nematode challenge. Int J Parasitol. 1996 Aug-Sep;26(8-9):857-68.
https://doi.org/10.1016/S0020-7519(96)80056-7
CENIA. Zprava o zivotnim prostredi Ceske republiky 2020 [Report on the environment of the Czech Republic 2020] [Internet]. Prague: Czech Environmental Information Agency; 2021. 312 p. Available from: https://www.cenia.cz/wp-content/uploads/2021/11/Zprava2020.pdf. Czech.
Cheruiyot EK, Haile-Mariam M, Cocks BG, MacLeod IM, Xiang R, Pryce JE. New loci and neuronal pathways for resilience to heat stress in cattle. Sci Rep. 2021 Aug 17;11(1): 16 p.
https://doi.org/10.1038/s41598-021-95816-8
Colditz IG, Hine BC. Resilience in farm animals: Biology, management, breeding and implications for animal welfare. Anim Prod Sci. 2016 Dec;56(12):1961-83.
Elgersma GG, do Jong G, van der Linde R, Mulder HA. Fluctuations in milk yield are heritable and can be used as a resilience indicator to breed healthy cows. J Dairy Sci. 2018 Feb;101(2):1240-50.
https://doi.org/10.3168/jds.2017-13270
Fang H, Kang L, Abbas Z, Hu l, Chen Y, Tan X, Wang Y, Xu Q. Identification of key genes and pathways associated with thermal stress in peripheral blood mononuclear cells of Holstein dairy cattle. Front Genet. 2021 Jun 10;12: 15 p.
https://doi.org/10.3389/fgene.2021.662080
FAO, GDP. Climate change and the global dairy cattle sector – The role of the dairy sector in low-carbon future. Rome: Food and Agriculture organization of the United Nations and Global Dairy Platform Inc.; 2018. 36 p.
Gauly M, Bollwein H, Breves G, Brugemann K, Danicke S, Das G, Demeler J, Hansen H, Isselstein J, Konig S, Loholter M, Martinsohn M, Meyer U, Potthoff M, Sanker C, Schroder B, Wrage N, Meibaum B, von Samson-Himmelstjerna G, Stinshoff H, Wrenzycki C. Future consequences and challenges for dairy cow production systems arising from climate change in Central Europe – A review. Animal. 2013 May;7(5):843-59.
https://doi.org/10.1017/S1751731112002352
Hermesch S, Dominik S. Breeding focus 2014 – Improving resilience. Armidale, Australia: University of New England, Animal Genetics and Breeding Unit; 2014. 141 p.
Klopcic M, Reents R, Philipsson J, Kuipers A. Breeding for robustness in cattle. (EAAP publication No. 126). Wageningen Academic Publishers; 2009. 281 p.
Knap PW, Doeschl-Wilson A. Why breed disease-resilient livestock, and how? A review. Genet Sel Evol. 2020 Oct 14;52(1): 18 p.
https://doi.org/10.1186/s12711-020-00580-4
Kok A, Tsousis G, Niozas G, Kemp B, Kaske M, van Knegsel ATM. Short communication: Variance and autocorrelation of deviations in daily milk yield are related with clinical mastitis in dairy cows. Animal. 2021 Oct;15(10): 100363.
https://doi.org/10.1016/j.animal.2021.100363
Konig S, May K. Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle. Animal. 2019 May;13(5):897-908.
https://doi.org/10.1017/S1751731118003208
Krupova Z, Krupa E, Zavadilova L, Kasna E, Zakova E. Current challenges for trait economic values in animal breeding. Czech J Anim Sci. 2020 Dec;65(12):454-62.
https://doi.org/10.17221/161/2020-CJAS
Liu S, Yue T, Ahmad MJ, Hu X, Zhang X, Deng T, Hu Y, He C, Zhou Y, Yang L. Transcriptome analysis reveals potential regulatory genes related to heat tolerance in Holstein dairy cattle. Genes. 2020 Jan 7;11(1): 12 p.
https://doi.org/10.3390/genes11010068
Llonch P, Hoffmann G, Bodas R, Mirbach D, Verwer C, Haskell MJ. Opinion paper: Measuring livestock robustness and resilience: Are we on the right track? Animal. 2020 Apr;14(4):667-9.
https://doi.org/10.1017/S1751731119003306
Mulder HA. Genomic selection improves response to selection in resilience by exploiting genotype by environment interactions. Front Genet. 2016 Oct 13;7: 11 p.
https://doi.org/10.3389/fgene.2016.00178
Poppe M, Veerkamp RF, van Pelt ML, Mulder HA. Exploration of variance, autocorrelation, and skewness of deviations from lactation curves as resilience indicators for breeding. J Dairy Sci. 2020 Feb;103(2):1667-84.
https://doi.org/10.3168/jds.2019-17290
Poppe M, Mulder HA, van Pelt ML, Mullaart E, Hogeveen H, Veerkamp RF. Development of resilience indicator traits based on daily step count data for dairy cattle breeding. Genet Sel Evol. 2022 Mar 14;54(1): 16 p.
https://doi.org/10.1186/s12711-022-00713-x
Samy AM, Peterson AT. Climate change influences on the global potential distribution of bluetongue virus. PLoS One. 2016 Mar 9;11(3): 12 p.
https://doi.org/10.1371/journal.pone.0150489
Scheffer M, Carpenter SR, Dakos V, van Nes EH. Generic indicators of ecological resilience: Inferring the chance of a critical transition. Annu Rev Ecol Evol Syst. 2015 Dec;46(1):145-67.
https://doi.org/10.1146/annurev-ecolsys-112414-054242
Scheffer M, Bolhuis JE, Borsboom D, Buchman TG, Gijzel SMW, Goulson D, Kammenga JE, Kemp B, van de Leemput IA, Levin S, Martin CM, Melis RJF, van Nes EH, Romero LM, Olde Rikkert MGM. Quantifying resilience of humans and other animals. PNAS. 2018 Nov 20;115(47):11883-90.
https://doi.org/10.1073/pnas.1810630115
Silpa MV, Konig S, Sejian V, Malik PK, Nair MRR, Fonseca VFC, Maia ASC, Bhatta R. Climate-resilient dairy cattle production: Applications of genomic tools and statistical models. Front Vet Sci. 2021 Apr 29;8: 16 p.
https://doi.org/10.3389/fvets.2021.625189
Strandberg E, Felleki M, Fikse WF, Franzen J, Mulder HA, Ronnegard L, Urioste JI, Windig JJ. Statistical tools to select for robustness and milk quality. Adv Anim Biosci. 2013 Jul;4(3):606-11.
https://doi.org/10.1017/S2040470013000162
Wiggans GR, Cole JB, Hubbard SM, Sonstegard TS. Genomic selection in dairy cattle: The USDA Experience. Annu Rev Anim Biosci. 2017 Feb 8;5:309-27.
https://doi.org/10.1146/annurev-animal-021815-111422
, Jan Vařeka, Jitka Kyselová
