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Livestock production profoundly intersects with global climate dynamics, contributing to greenhouse gas emissions and confronting vulnerability to climate impacts. In addressing these challenges, imperative adjustments are requisite to fortify the climate robustness of livestock systems. Notably, the prevalent reliance on commercial breeds with limited genetic diversity exposes production strategies to disruption, especially if these breeds are confined to environments that may lose economic viability under future climate scenarios. Consequently, understanding the adaptability of animal populations to forthcoming environmental conditions is paramount for sustaining livestock production. Assessing the genetic underpinnings of climate adaptation necessitates the exploration of tailored genomic selection techniques encompassing both production traits, presumed to have moderate heritability, and adaptation traits, presumed to have low heritability. Through a nuanced examination of genomic selection dynamics, insights into the genetic mechanisms fostering resilience in livestock populations amidst shifting environmental contexts are garnered. Employ genomic analysis to pinpoint genetic markers associated with traits like heat tolerance, disease resistance, and feed efficiency in livestock. Collaborate across disciplines to develop tailored breeding programs integrating these markers, and validate their effectiveness through rigorous field trials and ongoing monitoring to enhance livestock resilience and productivity in varied climatic conditions. Elucidating these mechanisms and their application in breeding programs offers a comprehensive understanding of how genetic advancements can enhance both production efficiency and climate resilience in livestock. This discourse aims to bridge the chasm between scientific inquiry and pragmatic implementation, thereby facilitating informed decision-making in livestock breeding strategies tailored to mitigate the ramifications of climate change.
Arya et al. (Sat,) studied this question.