Livestock plays an important role in the global economy. Climate change effects are not only limited to crop production, but also affect livestock production, for example reduced milk yields and milk quality, reduced meat production and reduced fertility. Therefore, livestock-based food security is threatened in many parts of the world. Furthermore, multiple stressors are a common phenomenon in many environments, and are likely to increase due to climate change. Among these stresses, heat stress appears to be the major factor which negatively influences livestock production. Hence, it is critical to identify agro-ecological zone-specific climate resilient thermo-tolerant animals to sustain livestock production. Livestock responds to the changing environments by altering their phenotypic and physiological characters. Therefore, survivability of the animal often depends on its ability to cope with or adapt to the existing conditions. So to sustain livestock production in an environment challenged by climate change, the animals must be genetically suitable and have the ability to survive in diversified environments. Biological markers or biomarkers indicate the biological states or alterations in expression pattern of genes or state of protein that serve as a reference point in breeding for the genetic improvement of livestock. Conventionally, identification of animals with superior genetic traits that were economically beneficial was the fundamental reason for identifying biomarkers in animals. Furthermore, compared with the behavioural, morphological or physiological responses in animals, the genetic markers are important because of the possibility of finding a solution to animal adaptability to climate change.

There is growing evidence on the extent to which projected changes in climate, including increases in atmospheric levels of carbon dioxide, higher temperatures, changes in amount, seasonality and variability of precipitation and increases in extreme weather events, may affect future availability of ruminant animal products. Elements of climate change affect livestock systems through direct impacts on animal physiology, behaviour, production and welfare and indirectly through feed availability, composition and quality. These impacts may be positive or negative and will vary across geographical regions, animal species and with adaptive capacity. However, adverse impacts are likely to be greatest in tropical and sub-tropical regions including countries where both current need and future growth in demand for nutrition is greatest. The complexity of effects means that effective adaptation strategies to mitigate negative impacts on ruminant production systems to climate changes will need to be multi-dimensional. Although predictions of future climate, particularly on regional and local scales, have a degree of uncertainty, adaptation planning is starting to be informed by changes already being observed and adjustments in management being made by farmers to maintain productivity and profitability. Regional case studies illustrate the benefits and limitations of adaptive management: potential mitigation through heightened awareness of heat stress-related mortality in French cattle; evidence of a drop in milk production in south-eastern Australian dairies during a January 2014 heat wave, from the theoretical potential of 53% to only 10% across the state; and limitations in response options to climate-induced thermal, nutritional and water stress for sheep and goat farmers in northern Ethiopia. Review of research on climate change impacts on ruminant livestock and effective adaptation together with evidence of practical adaptive management provide insights into potential strategies and gaps in knowledge to address challenges and improve future decisions.

Improving milk nitrogen efficiency through a reduction of CP supply without detrimental effect on productivity requires usage of feeding systems estimating both the flows of digestible protein, the exported true proteins and from these predict milk protein yield (MPY). Five feeding systems were compared in their ability to predict MPY v. observed MPY in two studies where either protein supply or protein and energy supply were changed. The five feedings systems were: Cornell Net Carbohydrate and Protein System (v6.5.5), Dutch protein evaluation system (1991 and 2007), Institut National de la Recherche Agronomique in France (INRA), National Research Council and NorFor. The key characteristic of the systems with the best predicted MPY was the inclusion of a variable efficiency of utilisation of protein supply taking into account the supply of both protein and energy. The systems still using a fixed efficiency had the highest slope bias in their prediction of MPY. Therefore, the development of new feeding systems or improvement of existing systems should include a variable efficiency of utilisation of the protein related to both the protein and energy supply. The limitation of the current comparison did not allow determining if additional factors, as used in INRA, were beneficial. This concept should also probably be transferred to essential amino acids.