P. G. Theron, T. S. Brand, S. W. P. Cloete, J. H. C. van Zyl
{"title":"Evaluating potential direct and carry-over weather effects on production performance in a divergently selected Merino flock","authors":"P. G. Theron, T. S. Brand, S. W. P. Cloete, J. H. C. van Zyl","doi":"10.1007/s00484-025-02946-z","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>Climate change and the associated changing weather patterns provide a global challenge to livestock producers. Due to the lack of information on the exact relationship between weather patterns and production output, livestock producers may struggle to adjust to these changing environmental conditions. This study therefore evaluated the feasibility of modelling the impact of weather conditions both within and across production seasons on production output in two divergently selected lines of Merino ewes. Production data collected from the high and low line of the Elsenburg Merino flock between 1993 and 2021 were related to weather data recorded by a weather station on the farm. The weather data included temperature, relative humidity and rainfall readings. Multiple linear regressions between uncorrelated weather variables and production parameters (conception, lambing, multiple offspring and survival percentages, average weaning weight and weight weaned per ewe) were derived to quantify the relationship between weather and production. Within production season, weather conditions during mating significantly affected lambing (R<sup>2</sup> = 0.332) and multiple offspring percentages (R<sup>2</sup> = 0.316) in the high line and lambing percentage (R<sup>2</sup> = 0.205) in the low line. Lambing period weather affected average weaning weight in the high line (R<sup>2</sup> = 0.230) and survival percentage in the low line (R<sup>2</sup> = 0.193). Significant amounts of the variation (R<sup>2</sup> = 0.180–0.306) in various production traits for both lines were also accounted for by the fitting of regression models of weather conditions in the preceding year to current production performance. This indicates the presence of weather-related carry-over effects. It therefore appears that using weather data to predict production output, both within and between production seasons, may be a viable management tool to aid producers in decision making. More work is required before these models are suitable for general uptake.</p>\n </div>","PeriodicalId":588,"journal":{"name":"International Journal of Biometeorology","volume":"69 8","pages":"1999 - 2012"},"PeriodicalIF":2.6000,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12287222/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Biometeorology","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1007/s00484-025-02946-z","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Climate change and the associated changing weather patterns provide a global challenge to livestock producers. Due to the lack of information on the exact relationship between weather patterns and production output, livestock producers may struggle to adjust to these changing environmental conditions. This study therefore evaluated the feasibility of modelling the impact of weather conditions both within and across production seasons on production output in two divergently selected lines of Merino ewes. Production data collected from the high and low line of the Elsenburg Merino flock between 1993 and 2021 were related to weather data recorded by a weather station on the farm. The weather data included temperature, relative humidity and rainfall readings. Multiple linear regressions between uncorrelated weather variables and production parameters (conception, lambing, multiple offspring and survival percentages, average weaning weight and weight weaned per ewe) were derived to quantify the relationship between weather and production. Within production season, weather conditions during mating significantly affected lambing (R2 = 0.332) and multiple offspring percentages (R2 = 0.316) in the high line and lambing percentage (R2 = 0.205) in the low line. Lambing period weather affected average weaning weight in the high line (R2 = 0.230) and survival percentage in the low line (R2 = 0.193). Significant amounts of the variation (R2 = 0.180–0.306) in various production traits for both lines were also accounted for by the fitting of regression models of weather conditions in the preceding year to current production performance. This indicates the presence of weather-related carry-over effects. It therefore appears that using weather data to predict production output, both within and between production seasons, may be a viable management tool to aid producers in decision making. More work is required before these models are suitable for general uptake.
期刊介绍:
The Journal publishes original research papers, review articles and short communications on studies examining the interactions between living organisms and factors of the natural and artificial atmospheric environment.
Living organisms extend from single cell organisms, to plants and animals, including humans. The atmospheric environment includes climate and weather, electromagnetic radiation, and chemical and biological pollutants. The journal embraces basic and applied research and practical aspects such as living conditions, agriculture, forestry, and health.
The journal is published for the International Society of Biometeorology, and most membership categories include a subscription to the Journal.