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These impacts are likely to be widespread. However, they will be difficult to quantify due to the uncertain and complex interactions between agriculture, climate, the surrounding environment and the economy (Kurukulasuriya and Rosenthal, 2003; Randolph, 2008).

Livestock’s vulnerability to climate shocks depends first on their exposure, which is determined by the duration, frequency and severity of the shocks, and the location of the stocks and related assets (e.g. feedstock, housing, water points). It also depends on their sensitivity, which is determined by the breed (see module B8-3.1 for the impact of climate change on animal genetic resources), the housing or feeding system, status of animal health (e.g. vaccination rate) and the importance of livestock to the household in terms of food security and livelihoods (ICEM, 2013). A number of other factors can increase livestock’s vulnerability to climate change, especially in semi-arid and arid regions. These factors include rangeland degradation, the fragmentation of grazing areas, changes in land tenure, conflicts and insecure access to land and markets (e.g. crop residues and by-products for feed, animal products). Socio-economic factors that specifically affect disease prevalence include changes in land use, host abundance, international trade, migration and public health policy.

Infectious diseases in animals and their transmission cycles represent complex interactions between hosts, pathogens and the environment (Peterson, 2006) and mainly occur following changes in the host-pathogen-environment system (Jones et al., 2008). Most of these diseases are zoonotic, i.e. may be transmitted to humans, and can have serious consequences for public health, the economy of the livestock sector and biodiversity conservation (Pinto et al., 2008).  

Climate change, in particular global warming, likely affects animal health by influencing the host-pathogen-environment system both directly and indirectly. The direct effects are more likely to influence diseases that are associated with vector transmission, water or flood, soil, rodents, or air temperature and humidity (Abdela and Jilo, 2016). Indirect impacts of climate change are more complex to disentangle and include those deriving from changes in land use and biodiversity and the attempt of animals to adapt to these climatic and environmental changes or from the influence of climate on microbial populations, distribution of vector-borne diseases and host resistance to infectious agents, feed and water scarcity, or food-borne diseases. In particular, prolonged droughts determine water and pasture shortages, which decrease livestock immunity against infectious diseases, as well as trigger livestock movements to areas at higher risk of animal diseases, determining the congregation of domestic animals around few available watering points and grazing areas in proximity to wildlife reserves. Here the risk of disease transmission is increased by the increased contact among domestic animals and between domestic and wild animals (Pinto et al., 2008). Grazing areas resulting from deforestation and changes in land use may expose livestock to novel pathogens due to increased interface between livestock and wildlife (Lubroth, 2012). These direct and indirect effects of climate change may be spatial, i.e., affecting the geographical distribution of the pathogen, host or vector, or temporal, i.e., affecting the timing of an outbreak and its intensity (Lubroth, 2012; Abdela and Jilo, 2016). However, not all organisms will respond similarly to climate change. In general, disease agents with external stages (e.g., non-host) of their life cycles, such as parasites, food-, water- and vector-borne diseases are most influenced by climatic and environmental changes. For instance, temperature increases feeding intervals and development rates of blood-feeding arthropods, while rainfall increases the availability of habitat for breeding sites. In general, global warming and changes in rainfall patterns and intensity are expected to expand the geographical and altitudinal distribution of vectors, allowing them to cross mountain ranges that currently limit their distribution (Abdela and Jilo, 2016). Furthermore, climate change can also influence livestock health through the survival of pathogens in the environment. A pathogen may emerge in new territories and host landscapes; become more aggressive, and perform a host-species jump, possibly in relation to increased host species mixing or contacts (Lubroth, 2012). 

Vector-borne diseases that are strongly associated with vector amplification due to climate variability include Rift Valley fever (RVF), West Nile Virus (WNV), Bluetongue (BTV) and Trypanosomosis. For instance, RVF in East Africa is strongly associated with extreme events, such as heavy rains and floods, caused by the El Niño Southern Oscillation events, which are expected to occur more frequently in the future as an effect of global climate change (FAO et al., 2015). On the contrary, West Nile Virus (WNV), Bluetongue (BTV) and Trypanosomosis appear to be strongly influenced by global warming and raise in temperature (Paz, 2015). Soil-borne diseases, such as Anthrax, are also affected by precipitation variability. Livestock and wildlife likely get infected with Anthrax while grazing and ingesting forage or soil contaminated with Anthrax spores, browsing on vegetation contaminated by carrion flies, or by percutaneous exposure from biting flies, and possibly spore inhalation (WHO, 2008). Anthrax outbreaks mainly occur after heavy rains and floods followed by a dry period or with the onset of rains ending a period of drought (Blackburn et al., 2007; Patassi 2016). These climatic conditions favor the concentration of spores in the upper level of the soil, increasing the risk of spore ingestion by herbivores. Climate change can also impact animal health in the Arctic region. The Anthrax outbreak that affected the reindeer population and humans in the Yamalo-Nenets region of Siberia in July 2016 is suspected to be associated with global warming and the abnormal warm temperatures observed in 2016, which may have substantially reduced the snow cover, water ice and permafrost in the area (FAO, 2017a). The previous reported outbreak in the area occurred in 1941, about 75 years ago. Time-series analyses of satellite-derived climate data over the past decades suggested that the observed changes in climate and livestock production system in the region may have increased animal exposure to Anthrax infected soil (FAO, 2017a).

Disease agents whose transmission depends primarily on close host-to-host contact can also be favored by extreme weather events that may increase contacts between naive and infected populations. For instance, prolonged droughts can increase the risk of occurrence of foot and mouth disease, hemorrhagic fevers, and tuberculosis (Abdela and Jilo, 2016).

Climate change has already been shown to determine a mismatch between migratory bird nesting and peak food abundance (Both et al., 2006) as well as changes in migration routes and timing (Hurlbert and Liang, 2012). The scarce availability of food during nesting is a great stressor that increases disease prevalence. At the same time, climate change may reduce available habitats, determining higher congregation of birds of several species in smaller areas of remaining resources and increasing the chance of within-species and cross-species disease transmission. Changes in migration routes and timing may also favor the emergence and introduction of a pathogen carried by birds in novel areas. This scenario is a likely explanation for the recent spread of highly pathogenic H5N8 avian influenza in Africa (FAO, 2017b).

Climate variability in rainfall, temperature, humidity patterns and extreme weather events, such as floods, droughts, heatwave, are therefore considered important indicators for monitoring and predicting animal diseases occurrence. As shown by the FAO Emergency Prevention System (EMPRES) since its implementation in 1994, early warning, early detection and early response are key in the prevention and control of both old and new emerging animal diseases (Lubroth, 2012). The FAO’s Global Surveillance and Early Warning System (GLEWS) actively tracks and verifies diseases rumors and disseminates confirmed disease outbreaks through the EMPRES-i Global Animal Disease Information System. FAO’S GLEWS conducts regularly risk assessments and modelling activities to provide decision makers in animal health and other stakeholders with guidance and recommendations on how to identify disease pathways, predict and prevent areas at risk of disease emergence and spread and implement rapid response and control measures on the ground. FAO’S GLEWS regularly monitors climatic and environmental risk factors using near-real time satellite-derived climate data. Using an algorithm developed by NASA and partners, a near-real time early warning system prototype for RVF has been developed using Google Earth Engine to identify and predict areas at risk of RVF vector amplification in East and West Africa (FAO, 2017). 

Preventive veterinary medicine, together with adjustment of animal husbandry and social resilience represents a way of coping with the negative consequences of climate change (Lubroth, 2012).

The livestock sector is a major contributor to climate change, generating significant emissions of carbon dioxide (CO₂), methane and nitrous oxide. Livestock contribute to climate change by emitting greenhouse gases either directly (e.g. from enteric fermentation and manure management) or indirectly (e.g. from feed-production activities, the conversion of forest into pasture). Based on a life cycle assessment of the livestock sector, FAO estimates that it emits about 8.3 gigatonnes of CO₂ equivalent (CO₂ eq.) (GLEAM), distributed as follows. 

• Land use and land-use change accounts for 0.7 gigatonnes of CO₂ eq. per year (9 percent of the sector’s emissions). This figure refers to the carbon dioxide emitted from the replacement of forest and other natural vegetation by pasture and feed crops in Latin America and Soil Organic Carbon release (mineralization) from soils, such as pasture and arable land dedicated to feed production (see Box B7.3).
• Feed production releases 2.6 gigatonnes CO₂ eq. per year (33 percent of the sector’s emissions). It includes carbon dioxide emissions from fossil fuels used in manufacturing chemical fertilizer and pesticides for feed crops, and and nitrous dioxide emissions from chemical fertilizer application on feed crops (grasses and legumes. It does not include the carbon released by field operations (Soil Organic Carbon mineralization). 
• livestock production releases 3.7 gigatonnes CO₂ eq. per year (46 percent of the sector’s emissions), including from: enteric fermentation from ruminants (as methane) and on-farm fossil fuel use (in the form of carbon dioxide).
• Manure management (mainly manure storage, application and deposition) accounts for 0.8 gigatonnes CO₂ eq. per year (10 percent of the sector’s emissions) from methane and nitrous oxide.
• Processing and international transport produces 0.23 gigatonnes CO₂ eq. per year (3 percent of the sector’s emissions).

There are striking differences in global emission intensities among commodities. For example, on a global scale, the emission intensity^vii  of meat and milk, measured by output weight, corresponds on average to 46.8 kg CO₂ eq. per kg of carcass weight for beef; 72 kg CO₂ eq. per kg of carcass weight for pork; 5.1 kg CO₂ eq. per kg of carcass weight for chicken; and 2.9 kg CO₂ eq. per kg of milk (FAO, 2013a and 2013b). Box B2.2 illustrates the case of substituting meat intake from livestock with low feed-conversion efficiency with livestock with higher feed-conversion efficiency^viii, such as insects.

There is significant variability in emissions across the different regions. For example, the FAO Life Cycle Assessment of greenhouse gas emissions from the global dairy sector estimated the global average at 3.0 kg CO₂ eq. However it also found emissions per unit of milk products varied greatly among different regions. Emissions from Europe and North America range between 1.6 and 1.9 kg CO₂ eq. per kg Fat and Protein Corrected Milk (FPCM). The highest emissions are estimated for sub-Saharan Africa with an average of 6.5 kg CO₂ eq./kg of Fat and Protein Corrected Milk. Greenhouse gas emissions for Latin America and the Caribbean, Near East and North Africa and South Asia, range between 3.5 and 5.6 kg CO₂ eq./kg Fat and Protein Corrected Milk (FAO, 2013a). 

Results from the same study of the global dairy sector also found greenhouse gas emissions to be inversely related to productivity. At very low levels of milk production (200 kg per cow per year) emissions were found to be 12 kg CO2 eq./kg FPCM compared to 1.1 kg CO2 eq./kg of Fat and Protein Corrected Milk for high production levels (about 8 000 kg of milk). This reflects the strong relationship between livestock intensification and greenhouse gas emissions across countries on a global scale (Gerber et al., 2011). This relationship is exponentially declining which means that small increases in productivity in the least intensive countries could provide the highest benefits in terms of emission intensity. 

However, beyond this strong relationship across countries, there is also a strong variability within countries, where production systems and management practices play an important role.