Environmental-genotype responses in livestock to global warming: A southern African perspective

Abstract

Global warming will change Southern Africa’s environments from grass dominated vegetation to dry woodland and desert with a vegetation of C4 dominated grasses, whereas the grazing capacity is expected to decline by more than 30%. Animals will also be more exposed to parasites and diseases, mainly as a result of an increase in temperature. An improved understanding of the adaptation of livestock to their production environments is thus important, but the measurement of adaptation is complex and difficult. Proxy-indicators for adaptation, such as reproductive and production traits, can however be used. Adaptation can also be characterized indirectly by describing the production environment in which a breed or population has been kept over a period of time and to which it has become adapted. By describing production environments it will be possible to identify breeds or genotypes that may be adapted to the changed environment of an area. In respect of quantitative breeding technology, fixed and random effects that account for spatial and temporal variation in production environments will have to be identified and physiological breeding value estimations may be necessary. Tools will need to be developed to overlay geo-referenced data sets available onto the different production environments in order to quantify them. Gene or marker assisted selection may play an important role in selection for disease and parasite resistance or tolerance, since it is difficult to measure these traits directly. The development of a high-throughput SNP or gene chip (genomic selection based on Single Nucleotide Polymorphisms) may enhance the utilization of marker assisted selection. Recent research has indicated that the inclusion of information from DNA analysis into BLUP breeding values may result in substantial increases in genetic gain at reduced cost. Strategies that utilizes EBVs derived from genomic analyses (genomic EBVs), together with conventional mixed model methodology, may speed up the process of breeding animals that are adapted to the newly created environment as a result of global warming.

Keywords: Global warming, livestock production, adaptation, animal breeding