Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus
dairy genotypes under diverse production
environments in Kenya
RESEARCH PAPER

No. 23

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

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ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

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Vulnerability and adaptation strategies
to climate variability and change of the
Bos-taurus dairy genotypes under diverse
production environments in Kenya

Kiplangat Ngeno
Animal Breeding and Genetics Group,
Department of Animal Sciences,
Egerton University, Egerton, Kenya.
Bockline O. Bebe
Livestock Production Systems Group,
Department of Animal Science, Egerton
University, Egerton, Kenya.

	
  ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

3This paper should be cited as:
African Technology Policy Studies Network, ATPS 2013: Vulnerability and adaptation
strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya [Kiplangat Ngeno, Bockline O. Bebe], ATPS RESEARCHPAPER No. 23© 2013Published by the African Technology Policy Studies Network

ISBN: 978-9966-030-67-2

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

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Table of Contents
Acknowledgements						

6Abstract								

7

1Introduction						

8

2Literature Review						

10

3Methodology						

15

4Results and Findings					

16

5Conclusion and Recommendations				25

References							

27ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
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Acknowledgement
This report was produced as part of the implementation of the African Technology Policy
Studies Network (ATPS) Phase VI Strategic Plan, 2008 – 2012 funded by ATPS Donors
including the Ministerie van Buitenlandse Zaken (DGIS) the Netherlands, amongst others.
The authors hereby thank the ATPS for the financial and technical support during theimplementation of the program. The Authors specially thank Prof. Kevin Chika Urama, the
ATPS Executive Director for his visionary leadership as Program Director; Prof. Atieno
Ndede-Amadi, Program Coordinator; Dr. Nicholas Ozor, Senior Research Officer, ATPS;
Mr. Ernest Nti Acheampong, ATPS Research Officer and the ATPS Team for the technicalsupport during the research process.

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

6Abstract
The study assessed the vulnerability and adaptation strategies to climate variability andchange (CVC) of the Bos-taurus dairy genotypes (DBG) under three diverse production
environments (PEDs); Rongai (lowland), Kipkelion (moderate altitude) and Nandi South(highland) districts. The PED’s were selected from lowland to highland to represent varying
degree of CVC in Kenya. The changes observed in the study area are declining rainfall trend
and ascending trend in temperature. In terms of vulnerability of DBG to CVC impacts, Friesian
was the most vulnerable breed for all climatic stress types and to different levels (medium
to high stress) under all circumstances in the identified PEDs. For instance, vulnerabilities
to heat stress were from moderate to high for Friesian (2.79-3.70) as compared to Ayrshire(1.15-2.0), Guernsey (1.0-2.0), and Jersey (1.13-2.0) in Nandi South district. Under low heatstress, Friesians were not vulnerable (1.00) in highland (Nandi south district) and undermoderate altitude of Kipkelion district (1.08) but different in Rongai district (3.08). Acrossthe three PEDs, Friesian was also the most vulnerable breed to feed stress and disease
infection under medium and high stress levels. Vulnerability levels to high feed stress were;high for Friesian (3.88-4.00) as compared to Ayrshire (2.38-3.88), Guernsey (3.00-3.75),
Jersey (3.00-3.75) and Dairy crosses (2.08-3.75). Susceptibility levels to high disease stresswere high for Friesian (3.74-4.00), Ayrshire (2.12-3.88), Guernsey (3.25-3.75), Jersey (2.004.00) and Dairy crosses (2.17-3.92). Information based on performance history was the mostfrequently used during selection of breeding stock; Nandi South (3.14), Kipkelion (3.17) andRongai (3.15). The results from the study indicate that the DBGs are vulnerable to impactsof CVC and a susceptibility level varies with both DBG and PEDs. Inferences generated
from this study can provide a strong basis for mitigating CVC and improving productivity bydesigning breeding and adaptation strategies for specific production environment.

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1. Introduction
1.1 Background information
Climate change in Sub-Saharan Africa is already impacting negatively on rain-fed agriculture
and livestock systems. Kenya is already experiencing a number of hazards of climate change
and climate variability (CVC) including more frequent droughts, prolonged dry spells, intense
rainfall and flush floods, increased heat stress and disease outbreaks (IPCC, 2007). These
climatic hazards are accompanied with more changes in the productivity of rain-fed crops andforage, reduced water availability and more widespread water shortages, changing severity
and distribution of important human, livestock and crop diseases.
Dairy farming is a key component of livestock industry in Kenya and is dominated by Bostaurus dairy breeds/genotypes (DBG) comprising Friesian, Ayrshire, Guernsey, Jersey
and crosses amongst themselves (Muriuki et al., 2004). The DBG are raised in different
agro-ecological zones under diverse production environments (PEDs) and are classified asvulnerable to poor feeding, heat load and disease incidences, which are projected to increasein frequency, intensity and magnitude with the increasing climate variability and change. The
PEDs thus has both direct and indirect climate effects on DBG, which will adversely impact
on the DBG performance and therefore limit their potential for providing food, nutrition, andincome and job securities to the farmer (Muriuki et al., 2004). This does raise concerns of
securing livelihoods for the farmer, creating the necessity to identify options and strategies
for CVC adaptation by poor dairy farmers. Intervention measures are needed to contributetowards building adaptive capacity and resilience to climate variability in the short-term andclimate change in the long-term, but are currently deficient in Kenya.
One approach to this problem is to characterize the PEDs in which a breed has been kept
over time. Several technology practices and strategies have been suggested for mitigation
and adaptation to CVC stress. However, breeding strategies targeted at improving theirproductivity have been applied uniformly disregarding the adaptability level of DBG. Thereis an urgent need for detailed performance assessment of DBGs under PEDs to guide theidentification of appropriate breeding strategies that can help dairy farmers mitigate CVC andimprove productivity and adaptation for secured livelihoods to the poor.
1.2 Cause and Effects
Increasing hazards of CVC are already being experienced and the increased scientific evidence
for CVC has significantly raised the level of uncertainty about future climate conditions. The
DBG are vulnerable to increasing hazards of CVC already being experienced in Kenya.
The CVC hazards are accompanied with changes in disease outbreaks, forage productivity
and, reduced water quantity and quality. These changes are projected to increase and DBG
raised in diverse PEDs will likely suffer some impacts of increasing CVC since they are themost vulnerable to climate stresses and yet least adapted compared to Bos-indicus. These
impacts of climatic stress on DBG performance have not been assessed and adaptations tooffset these impacts have not been assessed in detail. Nevertheless, appropriate breeding
strategies that can help dairy farmers stabilize production under changing CVC are unknown.
1.3 Objectives
1. To characterize the diverse production environments (PED) for dairy production bydegree of vulnerability to climate variability (CVC).
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

82. To rank vulnerability of the dairy breeds/genotypes (DBG) to CVC in the identified PEDs
based on farmers’ experience.
3. To identify adaptive traits of importance to stresses of CVC in the specific PEDS.
4. To identify breeding strategies for DBG to CVC for improved productivity and adaptation.
1.4 Rationale
Comprehensive information on the PEDs of the DBG will; (a) facilitate better understandingof the potential impacts and consequences of CVC, (b) Increase industry capability to
manage the implications of CVC, (c) Inform and engage industry stakeholders to improveunderstanding of CVC issues, (d) Facilitate better understanding of the likely impacts
and opportunities associated with reducing and/or offsetting CVC for the dairy industry (e)enhance understanding needed of the likely impacts of CVC on the vulnerability of the DBG
and (f) facilitate understanding of the resilience to current CVC and (g) enables the risks
associated with longer-term CVC to be gauged, and appropriate actions set in place toincrease or restore resilience where this is threatened. All these action combined contributeto securing livelihood assets for the poor.

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

92. Literature Review
2.1 Impacts associated with climate variability and changes
2.1.1 Changes in quantity and quality of feeds
The most important environmental constraint to improved dairy productivity is nutrition.
Nutritional stress in dairy cows reduces herd productivity and profitability through mortality,
reduced growth and reproduction, which can be of substantial economic loss to producers
utilising less adaptable breeds. The quantity and quality of the forage component of dairy
cattle diet is likely to be affected by CVC. The CVC changes are associated with changes
in herbage growth, quality and dry matter (DM) yield. Decline in rainfall accompanied withgreater variability in rainfall patterns (IPCC, 2007; Thornton et al., 2006, 2008) is likely toincrease the risk that DBGs will suffer lengthy periods of nutritional stress. If mean rainfall
decreases, this would lead to soil moisture deficits which reduces DM yield and affect also
the stage of maturity for forage. The stage of maturity at which the forage is cut is a major
determinant of the quality (Rowlinson, 2008).
Changes in temperature also compromise the quantity and quality of forage. It has been
known that increased temperatures, increases lignification of plant tissues and therefore
reduces the digestibility and the rates of degradation (Pilling and Hoffmann, 2011). An
increase in temperature tends to favour C4 forage plants (which generally produce hugeamounts of low-quality DM with low nutritive value as compared to C3 plants (Christensen etal., 2004; Morgan et al., 2007; Pilling and Hoffmann, 2011). The C4 forage plants are plantsthat produce the 4-carbon compound oxalocethanoic acid as the first stage of photosynthesis.
A C3 is a plant that utilizes the C3 carbon fixation pathway as the sole mechanism to convert
CO2 into an organic compound (Biology dictionary, 2008). A C3 plant must however be inareas where CO2 concentration is high, temperature and light intensity are moderate, andground water is abundant. A C4 plant is better adapted than a C3 plant in an environment withhigh daytime temperatures, intense sunlight, drought, or nitrogen or CO2 limitation (Biology
dictionary, 2008). Consequently, an increase in C4 forage might lead to decline on DBGs
performance because of poor quality. Conversely, Christensen et al. (2004) and Morgan etal. (2007) reported that CVC may increase shrub cover and such shrub encroachment will
reduce the quantity of forage available. Although the browses from shrubs are of superior
quality in terms of protein content than the grasses, their digestibilities are lower than that ofgrasses due to the presence of secondary metabolites (Illius, 1997). This leads to reduced
nutrient availability for DBG and ultimately to a reduction in dairy production.
2.1.2 Changes in forage species composition
Different forage species may have different capacities in responds to CVC. There is a possibility
that CVC will lead to a shift in the forage species grown and these will indirectly affects DBG
performance. As temperature and CO2 levels change due to CVC, optimal growth range fordifferent forage species also changes which will alter their competition dynamics, and thecomposition (Thornton et al., 2007). For example, the proportion of browse in rangelands will
increase in the future as a result of increased growth and competition of browse species due
to increased CO2 levels (Morgan et al., 2007). Rowlinson (2008) reported that, an elevationof temperatures may lead to an increase in the hectarage of maize grown for silage and
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of alfalfa for hay. It is also predicted that CVC will induce a shift from C3 to C4 plants aswell as grasses to shrubs (Christensen et al., 2004; Morgan et al., 2007) and these have
implications on forage supply. Pilling and Hoffmann (2011) observed that there is a possibilityof new regions being invaded by weeds which are generalist or colonizing species because
they may take advantage of CVC to expand their ranges. The forage species dynamics canbe related to the CVC hazards which often interact with those of other physical aspects ofthe environment such as soil characteristics to influence the distribution of other various
biological components of the agro-ecosystem such as pests, diseases, herbivorous animals,
pollinators, soil micro-organisms, which in turn will influence plant communities (Pilling andHoffmann, 2011). The interactions may favour or disadvantage some forage plant species in
specific environments depending on the climate-related agro-ecosystem changes (Foden etal., 2008).
2.1.3 Changes in quantity and quality of water
Climate variability and change is expected to increase the number of extreme meteorologicalevents. The frequency and severity of both droughts and floods is already high and is
expected to increase in future (Ojwang et al., 2010) and is expected to impact negatively
on smallholder dairy farmer’s activities due to their dependence on the availability of rainfall.
2.1.4 Changes in temperatures
Temperature is predicted to increase globally (FAO, 2007; IPCC, 2007) and it is expected to
impact negatively on the levels of livestock production. Direct effects involve heat exchanges
between the animal and the surrounding environment that are related to radiation, temperature,humidity and wind speed. Dairy cattle performance is best at temperatures between 4 to 24
0C, however, temperatures frequently rise above this thermal comfort zone in the smallholder
dairy production environments (King et al., 2006; Thornton et al., 2009) due to CVC. Dairy
cattle show signs of heat stress when temperature humidity index (THI) is higher than 72(Armstrong, 1994). The comfort limit depends on the level of production. Animals presenting
higher level of production like exotic DBGs are more sensitive to heat stress (Hahn, 1989).
High ambient temperature, relative humidity and radiant energy compromise the ability ofanimals to dissipate heat and provoke heat stress. Heat stress has a variety of detrimental
effects on feed intake, mortality, growth, maintenance, milk production and reproduction indairy cows (Johnson, 1987; Valtorta, 1996b). Hot dry conditions during the grazing period
can reduce the quality and consistency of the feeds and feeding, which may lead to animal
welfare and productivity problems (DEFRA, 2009). Under high temperature and solar
radiation, dairy cows feed intake decreases in order to reduce digestive heat production andavoid grazing in hot mid-day hours, consequently reducing grazing time which translate topoor productivity. High temperatures and humidity put an upper bound on milk production,
regardless of feed intake and also may affect conception rates.
2.1.5 Changes in livestock diseases and disease vectors
Climatic restrictions on vectors, environmental habitats and disease causing agents areimportant for keeping many animal diseases in check (Stem et al., 1989). Alterationsof temperature and precipitation regimes may result to spread of diseases and parasites
into new region or produce increased incidences of diseases, which, in turn, would reduceanimal productivity and possibly increase animal mortality (Baker et al., 1998). The link
between CVC and disease risks from various pathogens has been increasingly recognized.
Diseases currently thought of as “exotic” may become of importance (Lancelot, 2008) whilst
existing diseases may become more widespread with increased costs of control and risksof immunity developing (Skuce et al., 2008). Climate change has effects on; (a) Pathogens;
Higher temperatures increases the development rate of pathogens whereas changes inwinds may affect the spread of certain pathogens and vectors, (b) Epidemiology; By alteringtransmission rates between hosts, survival of the pathogen or parasite or intermediate vector
is likely to be affected, (c) Hosts; CVC changes might suppress cellular immunity of the host,conversely affecting genetic resistance to diseases, (d) Disease distribution; Substantial
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

11shifts in disease distribution, and outbreaks of severe disease could occur in previously
unexposed animal populations.
Climate variability and changes generally affect distribution and abundance of predators,
competitors, disease vectors and parasites of vectors themselves. The effects influencediseases patterns, causing the emergence of new diseases through exposure of hosts to
new and/or mixture pathogens and vectors. The ability of some insect vectors to becomeor remain infected with viruses (such as blue tongue) varies with temperature. The feeding
frequency of arthropod vectors is known to increase with the rise in temperature. In the
country of Mali, Diarra (2008) noted a significant drop in the spread of glossines linked todrought, the drying up of permanent rivers and the intensive land clearing. In Sudan andin Sudan-Guinea regions, a progressive decline of tsetse flies and their prevalence rates
has been reported by Gouro et al. (2008). Lacaux and Tourre, (2008) has also reported
geographical extension of Lyme disease (Borrelia crocidurae) within the Sahara and Sahelsince the vector Alectorobius sonrai has found a ‘good environment’ attributed by the West
African drought experienced in the last three decades. In Rongai (lowland), Kipkelion(moderate altitude) and Nandi South (highland) districts of Kenya, an increase of houseflies,
ticks, crabs and frogs has been observed by farmers. Furthermore, rainfall and humidity
are often considered as the necessary key parameters which modulate the emergence ofvarious human, animal and plant diseases. For example, mosquitoes and other ‘vectors’ thatfacilitate the transmission and diffusion of diseases such as Rift Valley Fever (RVF), Blue
Tongue, Malaria, Dengue Fever and Chikungunya among others, responds to the spatiotemporal distribution of seasonal rainfall (Lacaux and Tourre, 2008).
In addition, the DBGs bred with imported semen are geographically restricted and thus
could be less adaptable to outbreaks of CVC induced diseases, especially the Rift Valley
Fever, Foot and Mouth Disease and East Coast Fever. The outbreaks can cause increasing
productivity losses as well as low product qualities and raise safety concerns on the healthof the DBGs. Consequently these may translate into barriers to trading opportunities for the
dairy products in the domestic and export markets. Despite the fact that some diseases areaccelerated by climate change and variability, the impacts of the diseases on livestock andfarmers’ income is widely un-documented. Therefore, understanding how CVC affects thetransmission of these diseases will lead to enhanced preparedness for early and effective
interventions.
2.2 Adaptation strategies
Adaptation and mitigation are inextricably linked; mitigation policies can affect the range ofadaptation options available to practitioners, whilst adaptation has the potential to “buy time”
until effective mitigation responses can be implemented. Adaptation is concerned with copingwith the unavoidable changes that will occur, even if mitigation is successful at minimising
or avoiding the worst impacts (DEFRA, 2009). According to IPCC (2001), adaptation is the‘adjustment in natural or human systems in response to actual or expected climatic stimuli
or their effects, which moderates harm or exploits beneficial opportunities’. Adaptation
may therefore be used to inform both the magnitude and timing of mitigation (World Bank,
2008). Identifying and evaluating various adaptation strategies as well as mitigation options
is of fundamental value to determining a set of dynamic climate policy options (World Bank,
2008). Farm level analyses have shown that large reductions in adverse impacts fromclimate change are possible when adaptation is fully implemented (Mendelsohn and Dinar,1999). Numerous adaptation strategies in the livestock sector have been identified by several
experts. These include;
2.2.1 Breeding
There are many ways in which producers can adapt to CVC. Producers can either modify
their animals’ genetics to the changed environment or modify the production environment tosuit the genetics (Hoffmann, 2008 Climate change and variability has effects on cattle genetic
diversity by determining the cattle breed most adapted to each agro-ecological zone. Many
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

12local breeds are already adapted to their harsh conditions. Adaptation include not only theirtolerance to heat, but also their ability to survive, grow and reproduce in conditions of poor
nutrition, parasites and diseases (Hoffmann, 2008). Zebu (indigenous cattle breed) has beenreported not only capable of utilizing poor quality feeds but they are more resilient to climaticstress, and are more resistant to local parasites and diseases. When animals are genetically
adapted to specific/extreme conditions, they will be more productive (Simm et al., 2004). To
increase productivity, farmers have been advised to adapt their dairy genetics to the changed
PEDs through; (a) Increasing gene flow and introduction of breeds more adapted to theenvironment (Hoffmann, 2008)., (b) breeding for improved adaptation to heat, disease andharsh conditions using tropically adapted breeds/genes or insert specific genes via strategic
crossbreeding or biotechnology, and (c) use adaptive traits of indigenous animal genetic
resources (Thornton et al., 2007).
2.2.2 Structural Interventions
Structural interventions aim at the rehabilitation of sustainable productive assets through the
improvement of processes, institutions or policies that have a direct influence on a target
population’s assets/liabilities. The interventions which have been suggested are; (a) Enabling
dairy farmers to participate in decision-making at policy level. Farmers should have key roles
in determining what adaptation strategies they support, (b) development of collaborative
learning processes to support the adaptation of livestock systems to better cope with theimpacts of CVC, and (c) Introduction and integration of adaptation and mitigation concepts
into regular development activity.
2.2.3 Technology Integration
Successful adaptation is about the quality of both scientific and indigenous knowledge,
local social capital and willingness to act. Science and technology development will aid in
better understanding of the causes and impacts of CVC on livestock. The integration of
new technologies into the research and technology transfer systems potentially offers many
opportunities to further the development of CVC adaptation strategies (MacOpiyo et al.,2008). Access to technologies will determine the ability of producers to adapt their herds
to the physiological stress of CVC. If CVC exceeds the adaptive capacity of local breeds inextensive or pastoral systems, where the rate of technology adoption is generally low, therisk of breed displacement or loss might increase. Intensive livestock production systems
have more potential for adaptation through the adoption of technological changes and maysustain the high-output breeds (Hoffmann, 2008). A variety of technologies which have been
proposed in animal husbandry include; (a) Development of new breeds and genetic types(Thornton, et al., 2008; Sidahmed et al., 2008), and (b) improved animal health technology(Kurukulasuriya and Rosenthal, 2003).
2.2.4 Cattle re-distribution
It is an adopted coping mechanism which consists of displacement of livestock into areas
where natural resources are available. Consequently, affecting the distribution of rearedanimal species in different agro-ecological zones. There has been a displacement of flocks
from arid and semi-arid zones, mainly to the sub-humid zones. This in fact explains the upward
trend in the number of animals to humid zones where the environment is still unfavourable
for livestock farming (Gouro et al., 2008). These changes have been observed in Niger andin the arid country of Mauritania.
2.2.5 Feeding approaches
New feeding approaches, supplementary feeding and adoption of either new feeds or otherforms of rangeland management have been adopted as is the case in Senegal (Gouro, et al.,2008). Highly digestible feeds are recommended because poor quality roughage generates a
lot more heat than highly digestible rations (Stewart, 2005). To minimize exposure of cattle toheat stress, Stewart (2005) suggested feeding under the shade if feeding is done in midday.

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production environments in Kenya. ATPS Research Paper No. 23

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2.2.6 Livestock management systems
Efficient and affordable adaptation practices which have been developed for rural poor
who are not able to buy expensive adaptation technologies include; (a) shading, sprinklingand ventilation to reduce heat stress from increased temperature. It involves setting up an
irrigation line in the pasture, and run it for sometimes until all the cows have enjoyed a cooloff (Stewart, 2005), (b) modification of the grazing times. Mostly, farmers in CVC hotspots
are encouraged to maximise on night grazing. Cattle tend to graze two thirds of their intake
during the day and a third at night, but in hot weather this need to be changed to half during
the day and half at night (Stewart, 2005), (c) changing herd composition such as shifting fromlarge animal to small animal, etc., (d) improve management of water resources through theintroduction of simple techniques for localized irrigation (e.g. drip and sprinkler irrigation),
accompanied with infrastructure to harvest and store rainwater, such as small superficial
and underground dams, tanks connected to the roofs of houses, etc. (Kurukulasuriya andRosenthal, 2003; FAO, 2008; Thornton, et al., 2008; Sidahmed et al., 2008), (e) matchingstocking rates with pasture production, altering the rotation of pastures, altering forage andanimal species/breeds, altering the integration within mixed livestock and crop systems
including the use of adapted forage crops (Howden, et al., 2007; World Bank, 2008), and (f)early milking so that the herd can get out to graze while the day is still cool and milk early inthe afternoon so that the cows can cool down when the day is still very hot (Stewart, 2005).
In addition, lactating cows need enough rest before milking to enable them cool down andfarmers are advised to bring the cows early in the afternoon.

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3. Methodology
3.1 Study areas
The study was carried out in Rongai district which lies in the latitude and longitude of 0°
10’ 0” S and 35° 51’ 0”, Kipkelion district which lies in the latitude and longitude 0° 13’ 45”
S and 35° 27’ 23” and Nandi South District with latitudes 0° and 0°34 North and longitudes
34° 44″ and 35° 25″ East. These are administrative districts in Kenya. The PED’s wereselected from lowland (Rongai district), moderate altitude (Kipkelion district) and highland(Nandi South district) to represent varying degrees of CVC in Kenya. Nandi South district
altitude ranges from 1,400m-2,400m above sea level, with average temperatures of 18-25oC
and annual rainfall between 1,200mm-2000mm. Kipkelion district lies at an altitude rangeof 1700m-2000m above sea level, with an average temperature of 17-25oC .and annual
rainfall between 900mm-1300mm. Rongai district receives annual precipitation of 927mm
and average temperatures ranging from 25-37oC.
3.2 Data Collection Procedure
Quantitative research approach was employed in this study. Quantitative data was obtained
through interviews. A pretested structured questionnaire was used to gather information.
During pre-visits, local enumerators were recruited in each location and trained by the
researchers. Local enumerators were employed for ease of acceptability and communication
within the communities. The objectives of the survey and the benefits were explained to
the farmers during visits. At each household, interviews were done using the questionnaire.
The specific objective of the questionnaire was to explore the farmers’ available knowledge
on general information, cattle breeds, cattle performance, production systems, vulnerabilityof the DBG based on farming experience, constraints to dairy production and response
strategies. Research methods embraced a participatory approach, following the guidelines
presented by FAO/WAAP (2008). Scoring, ranking, seasonal calendar analysis and seasonal
trend analysis techniques were used.
3.3 Sampling Method
In each district, one location with three sub-locations was chosen in consultation with
officers from the ministry of agriculture, local community based organizations, and the local
provincial administration (chiefs and their assistants) for the survey. Three sub-locations per
district prominent in dairy production were selected on the basis that they have the highest
populations of the DBGs. Two pairs of major landmarks were selected in each sub-locationand transect lines were drawn between each pair. Interviewed households were selectedusing simple random sampling technique by randomly picking the 5th households. These
regions included Boito, Lengenet and Mogotio sub-locations in Rongai, Mosombor, Toretmoi,
and Kimolwo sub-locations in Nandi South district and Kipsirichet, Kedowa and Chakoror
sub-locations in Kipkelion district. Data were analyzed using the SPSS (Version 17) computer
software.
3.4 Data analysis
The data collected was analyzed descriptively using frequencies, percentages, means andcross tabulation using the SPSS (Version 17) computer software.

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4. Results and Findings
4.1. Characterization of the diverse production environments (PEDs)
Generally, rainfall trend is on decline with a high variability as shown by the zigzag patternin figure 1 to 3. Total annual precipitation for Nandi South district ranged from 821.1mm1647.7mm (figure1), 407.0mm-1407.5 mm (figure 2) was recorded in Rongai district and685.2mm -1458.8mm (figure 3) in Kipkelion. Findings of this study are in agreement to IPCC
report, (2007) which noted that the Kenyan arid and semi-arid lands (ASAL) are expected
to experience an overall decrease in precipitation due to CVC. According to Ojwang et al.
(2010), declining rainfall trend is caused by rising temperature levels which inevitably lead tohigher rates of evapo-transpiration. Fluctuation in rainfall pattern was prominent among thestudied PEDs.
Although the variability of rainfall pattern and intensity is a common feature in Kenya due tovariations in topography, the spatial and temporal changes in recent years point to the general
CVC (Ojwang et al., 2010). In the last five decades, Kenya has experienced serious droughts
more than thirteen times including the worst episodes witnessed in 1971, 1975, 1977,
1980, 1983/1984, 1991/1992, 1995/1996, 1999/2000, 2007/2008 (Kenya Meteorological
Department, 2008; Ojwang et al., 2010). On the other hand, serious periodical flooding havebeen observed such as 1982, 1985, 1997/1998 (El-Nino), 2002, 2003, 2004/2005, 2007 and2012 incidences. More flooding is expected in future as the mean annual temperatures in
the country are expected to increase (IPCC, 2007). Expected temperature increase of 1.34.0°C by the year 2100 is likely to be accompanied by an increase in mean annual rainfall
of up to 48 percent, with the increase in the total rainfall greatest from October to December
while the proportional change is largest in January and February (Ojwang et al., 2010). The
magnitude and frequency of CVC impacts have increased for the last four decades with morethan 103 weather-related disasters observed of which more than half occurred after the year
2000. Trend increased sharply in the last one decade for drought and from the beginning of2009 for flooding (Ojwang et al., 2010). According to UNEP/GoK, (2005), drought frequency
used to be every nine to ten years. However, the pattern seemed to have changed to five
years (GoK, 2009) and currently to every two to three years (The Economist on East Africa
Drought, 2009).
Temperature trend in the Nandi south and Rongai districts are shown in figure 4 and 5.
The trend was slightly on an ascending trend with average temperatures ranging between
8.340C and 24.010C for Nandi South district (figure 4), and between 16.660C and 36.40C
for Rongai district (figure 5). Constant increase in temperatures reported in this study are
consistent with GoK report (2009), the IPCC report (2007) and FAO report (2007), all ofwhich predict that by the year 2100 the increase in global average surface temperature
may be between 1.5 and 4.0°C. An increase by 1°C over the last five decades have beenrecorded in Kenya (GoK, 2009) and a further 1-2.50C is expected by 2030 (IPCC, 2007). The
phenomenon and direction of trends in temperature has become increasingly deviant fromnormal, with more hot and fewer cold days and nights, also warmer and more frequent hotdays and nights over most land areas (IPCC, 2007). This increase has been observed tobe higher from March to May and expected to lead to an overall increase of around 7 % inannual rainfall over the same period, although this change will not be experienced uniformly
across the region or throughout the year (Ojwang et al., 2010). The impact of the temperature
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

16change has manifested through detrimental effects associated with changes in; quantityand quality of feeds, quantity of water, forage species composition, livestock diseases anddisease vectors and other effects. The recent rise in temperature and prolonged and severe
droughts in Kenya are widely perceived to be symptomatic of the changing climate (Kenya
Meteorological Department, 2008). Rainfall and temperature changes observed in the study
suggest the three studied PEDs are hotspots of CVC.

Figure 1: Rainfall trend in Nandi South district

Figure 2: Rainfall trend in Rongai district
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

17

Figure 3: Rainfall trend in Kipkelion district

Figure 4: Maximum and minimum temperature for Nandi South district

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

18

Figure 5: Maximum and minimum temperature for Rongai District
4.2. Vulnerability ranking of the dairy breeds/genotypes (DBG) to CVC in the identified
PEDs based on farming experience
A relative vulnerability ranking of DBGs to CVC impacts in the diverse production environments
were done in a four scale ranking order; 1 = not vulnerable; 2 = mild vulnerable; 3 = moderately
vulnerable and 4 = highly vulnerable. The DBGs were ranked under three varying levels of
CVC stress (low, medium and high stress levels). Friesian was the most vulnerable breed
under both medium and high climatic stress under all circumstances in the three PEDs
compared to other DBGs (Table 1). Under high heat stress, vulnerabilities were moderate
to high for Friesian (2.79-3.70) whereas Ayrshire (1.15-2.0), Guernsey (1.0-2.0), and Jersey(1.13-2.0) were less affected. Under low heat stress, Friesians were not vulnerable (1.00)
in Nandi south district and can do better than the same Friesian under low heat stress inmoderate altitude of Kipkelion district (1.08) but different in Rongai district (3.08) (Table
1). Across the three districts, Friesian was also the most vulnerable breed to feed stressand disease infection under medium and high stress levels. Vulnerability levels to high feedstress were; high for Friesian (3.88-4.00) as compared to Ayrshire (2.38-3.88), Guernsey(3.00-3.75), Jersey (3.00-3.75) and Dairy crosses (2.08-3.75) (Table 1). Susceptibility levels
to high disease stress were high for Friesian (3.74-4.00), Ayrshire (2.12-3.88), Guernsey(3.25-3.75), Jersey (2.00-4.00) and Dairy crosses (2.17-3.92).
Findings of this study indicated that the zebu breed (indigenous cattle breed) and its crosses
were the most adapted breed to climatic conditions in all the PEDs than exotic counterparts,
which is in agreement with the report by McManus et al. (2009) on heat tolerance of local
breeds. Zebu breed and its crosses like most local breeds in the tropics and subtropics arecomparatively well adapted to high temperatures. Their adaptation is attributed to different
hereditary characteristics that have resulted in differences in reactions to environmental stimuli.
These reactions are intimately associated with anatomical-physiological characteristics.
According to Romanov et al. (1996), locally adapted breeds possess genes and alleles
that are pertinent to their adaptation to the local environments. Genes that confer thermotolerance at the physiological and cellular levels were acquired during the evolution and
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

19natural selection process. Superiority of zebu breed and their crosses over other DBGs inability to regulate body temperature during heat stress is the result of lower metabolic rates
and larger sweat glands which increased sweating capacity for heat loss. Furthermore, Zebu
posses lower tissue resistance to heat flow from the body core to the skin compared to exotic
breeds (Hansen, 2004).
In general, the high-output exotic DBGs are not well adapted to heat stress. For example,
milk production, fertility and longevity in Holstein-Friesian cattle decline as temperature
increases (St-Pierre et al. 2003; West 2003). Therefore, Rongai district which are currently
characterised by high temperatures and low rainfall may be expected to lead to a shift towards
more highly adaptive species such as dairy-zebu crosses and zebu breeds. In such hot anddry environment of Rongai district, selecting DBGs adapted to this PED or incorporation oftolerance genes from zebu breed into Bos-taurus while avoiding undesirable genes may be
an alternative scheme. The zebu genotype has been utilized in crossbreeding systems todevelop cattle for dairy production systems in hot climates. For example, mapping of specificgenes responsible for thermo-tolerance in zebu can be explored through breeding strategies
such as marker-assisted selection and transgenics (Hansen, 2004).

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
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ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

21

Zebu

Dairy-zebucrossesDairycrosses

JerseyGuernsey

Ayrshire

Friesian

DBG

-

2.25

Kipkelion

Rongai-2.90

Rongai

Nandi
South

-

Kipkelion

3.83

Rongai-

2.05

Kipkelion

Nandi
South

2.08

3.75

Rongai

Nandi
South

2.00

Kipkelion

3.50

Rongai

2.00

2.00

Kipkelion

Nandi
South

2.00

3.75

Rongai

Nandi
South

2.07

Kipkelion

3.92

Rongai

2.07

3.73

Kipkelion

Nandi
South

3.72

High

Nandi
South

District

2.00

-

-

2.67

-

-

3.33

1.14

1.13

3.25

1.00

1.00

3.25

1.00

1.00

3.50

1.19

1.15

3.38

2.76

2.79

MediumHeat stress

1.75

-

-

2.67

-

-

2.82

1.08

1.02

2.50

1.00

1.00

2.75

1.00

1.00

3.13

1.00

1.00

3.08

1.08

1.00

Low

2.75

-

-

3.00

-

-

3.75

2.14

2.08

3.75

3.00

3.00

3.75

3.00

3.00

3.88

2.30

2.38

4.00

3.89

3.88

High

2.25

-

-

3.00

-

-

3.08

1.43

1.40

2.75

2.00

2.00

3.00

2.00

2.00

3.38

1.42

1.50

3.23

3.59

3.65

MediumFeed stress

2.00

-

-

2.89

-

-

3.18

1.03

1.00

3.25

1.00

1.00

3.00

1.00

1.00

2.88

1.00

1.00

2.92

1.16

1.16

Low

3.00

-

-

3.40

-

-

3.58

2.19

2.15

3.75

3.00

3.00

3.75

3.00

3.00

3.88

2.14

2.13

3.92

3.73

3.67

High

2.25

-

-

2.78

-

-

3.17

1.59

1.58

3.75

2.00

2.00

4.00

2.00

2.00

3.63

2.28

2.13

3.54

3.43

3.40

MediumWater stress

2.50

-

-

2.60

-

-

3.00

1.08

1.02

3.00

1.00

1.00

3.75

1.00

1.00

3.25

1.05

1.03

2.77

1.08

1.00

Low

3.25

-

-

3.50

-

-

3.92

2.27

2.17

4.00

2.00

2.00

3.75

2.00

2.00

3.88

2.19

2.12

4.00

3.81

3.74

High

2.50

-

-

2.80

-

-

3.42

2.00

1.98

3.25

1.00

1.00

3.25

1.50

1.20

3.38

1.93

1.90

3.38

3.54

3.53

MediumDisease stress

2.25

-

-

2.70

-

-

3.25

1.51

1.38

3.25

1.00

1.00

3.25

1.00

1.00

3.14

1.35

1.30

3.17

1.16

1.05

Low

3.00

-

-

3.60

-

-

3.67

2.73

2.62

3.50

2.00

2.00

3.75

2.00

2.00

3.50

2.77

2.65

3.85

3.73

3.67

High

2.25

-

-

2.80

-

-

2.91

1.97

1.90

2.75

1.00

1.00

3.25

1.00

1.00

3.13

1.98

1.95

3.62

2.78

2.84

Medium

Vector stress

2.25

-

-

2.30

-

-

2.73

1.14

1.04

2.75

1.00

1.00

3.25

1.00

1.00

3.13

1.07

1.03

3.08

1.22

1.14

Low

Table 1: Relative vulnerability ranking of DBG to climate change impacts now in the production environment

2.25

-

-

2.89

-

-

3.27

2.38

2.41

3.00

2.00

2.00

2.75

2.00

2.00

3.38

2.70

2.47

3.54

3.57

3.52

High

2.50

-

-

2.44

-

-

2.91

1.54

1.41

3.00

1.00

1.00

3.25

1.00

1.00

2.88

1.70

1.53

3.31

2.86

2.90

MediumFlooding stress

1.75

-

-

2.11

-

-

2.40

1.13

1.06

2.25

2.00

1.00

2.75

1.00

1.00

2.38

1.07

1.03

2.62

1.15

1.10

Low

4.3. Adaptive traits to stresses of CVC in the specific PEDS
A range of traits ranked in terms of their relevance to animal adaptability to environmental
stress as perceived by the farmers across the three districts are presented in Table 2. A
ranking scale of 5= very important, 4= moderately important, 3 = (averagely important), 2 =mildly important and 1 = least important) were used. Body condition, survival, rehydration,coat colour and foraging ability traits were considered most relevant to animal adaptability
to CVC stress (P<0.05) whereas fertility, calving interval and calf survival were not (Table2). The fact that some traits were critical indicates that selection for these traits had an
impact in that environment. Body condition may be useful to assess in relation to climate
variation. Body condition is an assessment of weight in relation to length and is a commonlyused indicator of the overall fitness of individuals (Lowe, 2003). Efficient dairy production isdependent on the management of the cows’ energy reserves. Monitoring body condition is a
useful management tool to assess these energy reserves Cow’s body condition is positively
correlated with the ability to reproduce (Reading, 1986), and declines in body condition havebeen directly linked to declines in annual survivorship (Jørgensen 1986). Ward and Tiffin(1975) observed that body condition is important at the time of breeding. For example, toobtain a reasonable compromise between milk yield and fertility, a target condition score of
3 at calving, and a target score of 2 at service is needed (Merwe, 2005). It is expected that
CVC stresses, would result in a poor body condition and, investigating DBG’s body condition
in relation to climate variables will increase our understanding of how CVC variation might
indirectly affect their population over multiple years by directly affecting energy stores. In
addition, if survival is predicted by body condition, it would provide a response variable thatreacts to climate variables and may be indicative of survival. Therefore, most farmers arelikely to prefer DBGs that maintain body condition under stressful periods. Coat colour is an
important trait across the three PEDs. Bright coloured or shiny coats have been reported toreflect sunlight thus reduce too much heat stress. Brown coat colour is adaptive trait that
may well suit harsh environment conditions with greater climate variability. For example in
Zebu, their hair coat enhances conductive and convective heat loss and reduces absorptionof solar radiation.
Fertility in cattle is affected by environmental, genetic, disease and management factors.
Fertility may be defined as the ability to conceive and produce a viable calf. Under harshenvironmental conditions, generally, most cows develop important strategies to modulate
the timing of conception to take advantage of resource abundance. Fertility is generally
highest in the cold-dry season compared to hot-wet season and hot-dry season. Therefore,
as rainfall declines accompanied by rise in temperature, fertility is likely to be affected
negatively. The CVC may impact bulls’ fertility in several ways, including delayed puberty due
to feed associated stress, depressed immune system under heat stress (Chakravarty et al.,2012), and poor quantity and quality of the sperm produced. Under the CVC stress, fertility is
expected to vary with DBGs depending on individual and breed coping mechanisms. Fertility
rates are generally high in Bos-taurus compared to Bos-indicus, particularly under ideal
management (Mugerwa, 1989.). However, the trend might become reversible under stressful
conditions. It has been observed that, the hot-wet season, characterized by high humidity, hightemperatures and low wind speed, seem to exert some stress on the Holstein Friesian cows.
Effect of stress normally varies and calving interval probably reflects the adaptation levels.
The long calving interval of the cattle probably reflects lack of adaptation to the environment(Mugerwa, 1989). In studies conducted by Jochle (1972) and Mugerwa (1989), they also
found direct linear correlations between conception rate in cows and precipitation, pressure
and temperature. Good foraging ability under seasonal fluctuations in fodder availability andquality are important in the context of CVC as it will make DBGs less vulnerable to CVC.
The ability of some organisms to survive extreme dehydration conditions has been reported
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

22

by many authors. In the last 5 decades, it has been known that many animal species seemto possess this remarkable ability to overcome dehydration. They are able to withstandremoval of essentially all their intracellular water without suffering irreversible structural andfunctional damage (Crowe et al. 1987). Their adaptations include morphological changes
and a reduction in metabolic rate (Womersley, 1981a; Freckman and Womersley, 1983). Thisability to withstand dehydration and rehydrate is increasingly becoming important in PEDs
where rainfall is declining accompanied with increasing temperature.
These findings are in agreement with, report by Hoffmann (2008), who suggested that
producers can either adapt their animals’ genetics to the changed environment or modify
the production environment to suit the genetics. Genetic make-up influences fitness andadaptation and determines an animal’s tolerance to shocks from temperature extremes,
drought, flooding, pest and disease challenges. A number of commentators, such as Yarwood
and Evans (2002), noted that many Bos-indicus genotypes are more resilient to CVC stressand host unique traits which may be useful for improving health and performance traits infuture. In Kenya, local breeds such as zebu are already adapted to their harsh conditions.
However, neglect of adaptive traits and lack of technology in cattle breeding programmes
which might help to speed the adaptation have not been addressed.
Table 2: Traits ranking in terms of their relevance to animal adaptability to environmental
stressDistrict

Fertility

Calving
interval

Body
condition

Survival

Rehydration

CoatcolourCalf sur- Foragvival
ing
ability

Nandi
South

4.59

4.57

4.86

4.99

3.28

3.49

4.32

4.95

Kipkelion

4.52

4.51

4.85

4.90

3.24

3.48

4.32

4.94

Rongai

4.50

4.60

3.77

3.80

3.90

3.13

4.63

3.90

Sig
.567
.611
.000
.000
.000
.050
.215
.000
(p=0.05)[Scale: 5=very important, 4=moderately important, 3 = (averagely important), 2 = mildly important, 1 =least important)]

4.4. Breeding strategies for DBGs under diverse production environments
A relative ranking of farmers’ indigenous knowledge in animal breeding across the three
districts were scaled in order of; 1= No, 2= occasionally, 3=always and 4= frequently.
Information on selection criteria of breeding animal including use of individual merit,family history, performance history and external sourcing of breeding stock were captured.
Information based on performance history was the most frequently used when selection forbreeding or replacement purposes in the three districts; Nandi South (3.14), Kipkelion (3.17)
and Rongai (3.15). Information based on individual merit was always practiced; Nandi South(2.21), Kipkelion (2.28) and Rongai (2.45) (Table 3). Few farmers outsourced breeding stock;Nandi South (1.78), Kipkelion (1.61) and Rongai (1.90). From the results, it is clear thatmost farmers across the three districts did selection based on the information that they know
about the family and the performance history. Indigenous livestock management practices
under natural selection through social and rational breeding mechanisms contributed tobreed adaptation and fitness to harsh environments (Sansthan and Rollefson, 2005; CGRFA,
2009). Such traditional knowledge can contribute to solving serious global problems throughpractices such as sustainable use of DBGs to address issues such as CVC impacts. Farmers
in different PEDs have clear-cut breeding objectives which are multi-faceted, and include
the DBG’s ability to survive. Understanding indigenous practices and processes among
farmers are essential for the design of intervention strategies for adaptation. Their traditional
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 2323knowledge however, provides a key for successful local level adaptation and advice onsustainable mitigation activities.
Table 3: Indigenous knowledge in animal breeding
District

Individual merit

Family history

Performance
history

External sourcing ofbreeding stock

Nandi South

2.21

2.68

3.14

1.78

Kipkelion

2.28

2.74

3.17

1.61

Rongai

2.45

1.93

2.70

3.14

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

24

5. Conclusions and Recommendations
The paper presented the vulnerabilities and adaptation strategies to CVC of the Bos-taurus
dairy genotypes under diverse production environments. The results from the study indicatethat the DBGs are vulnerable to impacts of CVC and their susceptibility levels vary withboth DBG and PEDs. Inferences generated from this study can provide a strong basis for
mitigating CVC and improving productivity by designing breeding and adaptation strategies
for specific production environment. For DBGs, developing the traits needed to cope with CVC
is promising. Bos-indicus genotypes such as Zebu breed contain a wide genetic diversity oftolerance traits which can be exploited. Though largely neglected in modern breeding, such
Bos-indicus genotypes could play a vital role in helping farmers adapt to CVC, despite thechallenges of compromising the yield.
Traits and tools need to be developed and applied to help dairy industries mitigate impactsof CVC using genetic tools. Broader breeding goals have become the norm in the dairy,usually incorporating production and “fitness”(health, fertility, longevity) traits in developed
world. However, exotic cattle produced from such breeding programmes faces challenges
of genotype by environment interactions, hence there is a need to develop local breeding
programme for specific production environment to address the adaptation challenges.
Selection for breeds such as zebu breed with effective thermoregulatory control may be
exploited and incorporated into DBGs to boost their heat tolerance levels. Some opportunities
exist to improve DBG adaptation through manipulation of genetic mechanisms at cellularlevel. Inclusion of traits associated with body condition, survival, rehydration, coat colour andforaging ability traits which are considered most relevant to animal adaptability to CVC stressas well as temperature, disease and parasite tolerance in breeding indices for species/breeds
under threat e.g. genetics of CVC stress and G*E interactions are of paramount. For example,
selection for heat tolerance based on rectal temperature measurements and inclusion ofa temperature-humidity-index in the genetic evaluation models can be a promising option.
However, in dairy cattle, it may be difficult to combine the desirable traits of heat tolerancewith high reproduction and production potential.
In spite, lack of scientifically back up information, indigenous knowledge about cattle genetic
diversity has been revealed to offer an important knowledge base for selective breeding.
Indigenous knowledge on animal breeding is a valuable resource about the existence of cattle
breeds and their adaptive traits. . Integrating indigenous knowledge into selective breeding
programmes can be an opportunity for the development of low-cost, locally-appropriate CVC
adaption strategies.
Therefore, attaining sustainable dairy productivity requires utilizing DBGs adapted to thevariable and changing climate. In all of the areas discussed above, greater benefits could
likely be achieved through identification of adaptive DBGs and strengthen their adaptive
capacity. In all of the areas discussed above, greater benefits could likely be achieved
through identification of adaptive DBGs and strengthen their adaptive capacity. Dairy breeds
genotypes that are already well-adapted and can survive the changing climatic conditions
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

25

need to be promoted in the suitable production environments together with appropriate
management interventions. This will effectively reduce animal stresses and enable
smallholder dairy farmers mitigate and adapt to effects of changing climate thus promote andsustain their livelihood assets.
Recommendations• More interaction is required at all levels among breeders, farmers, climatologists, tradersand consumers to develop robust breeding program to curb the CVC threats.
• In the presence of breed by environment interactions, specific DBG need to be soughtfor particular environments in order to optimize performance total merit of production.
Therefore, frequent assessment of the magnitude of G*E interaction is needed.
• Increased training to farmers on how to handle the DBGs is also necessary.
• Frequent documentation of the farmer’s indigenous knowledge about PEDs, DBGs andbreeding. It can be a source of information that scientists have overlooked and which
may have unrecognised advantages and potential.

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

26

References
Armstrong, D.V. (1994) Heat stress interaction with shade and cooling. Journal of Dairy
Baker B., Viglizzo, J.F. (1998) Rangelands and livestock. Chapter 9 in: Feenstra, J.F; Burton I; Smith,
J.B.; Tol, R.S.J. (eds.) Handbook of methods for climate change impact assessment and adaptation
strategies. IVM/UNEP Version 2.0.
Bebe, B. O., Udo, H. M. J, Rowlands, G. J., Thorpe, W. (2003) Smallholder dairy systems in the Kenya
highlands: cattle population dynamics under increasing intensification. Livestock Production Science,
82:211-221.
Biology-Online dictionary (2008) C4 plants and C3 plants.
Chakravarty, R., Upadhyay, R. C., Sohanvir S., Ranga J. (2012) Increasing farm and livestock resilience
to climate change. National dairy research institute. Karnal, India.
Christensen, L., Coughenour, M.B., Ellis, J.E., Chen, Z. Z. (2004) Vulnerability of the Asian typical
steppe to grazing and climate change. Climatic Change, 63: 351–368.
Commission on Genetic Resources for Food and Agriculture (CGRFA). (2009) Contributions ofsmallholder farmers and pastoralists to the development, use and conservation of animal genetic
resources. CGRFA/WG-AnGR-5/09/Inf.4.
Crowe, J. H., Crowe, L. M., Carpenter, J. F., Wistrom, C. A. (1987) Stabilization of dry
Department for Environment, Food and Rural Affairs (DEFRA) (2009) Climate change impacts onlivestock sector. The Farm Animal Genetics and Genomics Faraday P’ship Ltd (Genesis Faraday),
Roslin BioCentre.
Diarra, B., (2008) Presentation at the regional workshop on “impact of climate on livestock-environment
interactions” 9-15 February 2008, Niamey 2008.
Economist. 2009. East Africa’s Drought: A Catastrophe is Brewing. http://www.economist.com/ world/
middleeast-africa/displaystory. Accessed on January 17 2012.
Foden, W., Mace, G., Vié, J.-C., Angulo, A., Butchart, S., DeVantier, L., Dublin, H., Gutsche, A., Stuart,S., Turak, E. (2008) Species susceptibility to climate change impacts. In J.-C. Vié, C. Hilton-Taylor
and S.N. Stuart, eds. The 2008 review of the IUCN red list of threatened species. Gland,Switzerland.
International Union for Conservation of Nature.
Food and Agriculture Organization (FAO) (2007). The State of the World’s Animal Genetic Resources
for Food and Agriculture, edited by B. Rischkowsky and D. Pilling. Rome, Italy
Food and Agriculture Organization (FAO)/ World Association of Animal Production (WAAP). (2008)
Production environment descriptors for animal genetic resources. PED Worksheet. Report of FAO/
WAAP Workshop, Caprarola, Italy, 6-8 May, 2008, 97 pp.
Freckman, D. W., Womersley, C. (1983). Physiological adaptation of nematodes in Chihuahuan desert
soils. In New Trends in Soil Biology (ed. Ph. Lebrun, H. M. Andre, A. De Medts, C. Gregoire-Wibo and
G. Wauthy), pp. 395-403.
Gouro, S. Hamadou, A., Soara, O., and Guerrini, L, (2008) Climate Change in West Africa: Impact
on livestock and strategies of adaptation. A Centre International de Recherche-Développement sur
l’Elevage, Burkina Faso.
ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

27

Government of Kenya (GoK). (2009) Ministry of Environment and Mineral Resources, National Climate
Change Response Strategy (Republic of Kenya 2009).
Hahn, G.L. (1989) Bioclimatology and livestock housing: theoretical and applied aspects. Proc. Brazilian
Workshop on Animal Bioclimatology. Jaboticabal, Brazil 15pp.
Hansen P.J. (2004) Physiological and cellular adaptations of zebu cattle to thermal stress. Animal
Reproduction Science, 82–83: 349–360
Hatfield, O., Jonathan, D. (2006) Global Review of the Economics of Pastoralism IUCN, Nairobi,
headwater salamander system. Ecology, 84:2145–2154.
Hoffmann, I. (2008) Livestock genetic diversity and climate change adaptation. In Livestock and Global
Climate Change. P. Rowlinson, M. Steele and Y.A. Nefzaoui (Eds.). pp. 76– 80. BSAS Proceedings,
Cambridge University Press.
Howden ,S. M., Soussana, J.F., Tubiello, F. N., Chhetri, N., Dunlop, M., Meinke, H. (2007) “Adapting
Agriculture to Climate Change.” Proceedings of the National Academy of Sciences of the United Statesof America, 104 (50): 19691–19696.
http://www.biology-online.org/dictionary/
http://www.ipcc.cg/SPM13apr07.pdf. Accessed on October 23 2010.
Illius, A.W. (1997) Physiological adaptation in savanna ungulates. Proceedings of the Nutrition Society,56: 1041–1048.
Intergovernmental Panel on Climate Change (IPCC) (2001) Climate Change 2001: The
Intergovernmental Panel on Climate Change (IPCC) (2007) Climate 2007: Impacts, Adaptation and
Vulnerability. Summary for policy makers.
Jochle, W. (1972) Seasonal fluctuations of reproductive functions in zebu cattle. International Journalof Biometeorology (Netherlands), 16: 131-144.
Johnson, H. D. (1987) Bioclimatic effects on growth, reproduction and milk production. In: Bioclimatology
and the adaptation of livestock, Elsevier, Amsterdam, The Netherlands. Part II, Chapter 3.
Jørgensen, C.B. (1986) External and internal control of patterns of feeding, growth and gonadal function
in a temperate zone anuran, the toad Bufo bufo. Jounal of Zoology, 210:211–241.
Kenya Meteorological Department report (2008)
King, J.M., Parsons D. J., Turnpenny, J. R., Nyangaga, J., Baka, P., Wathes, C. M. (2006) Modellingenergy metabolism of Frisians in Kenya smallholdings shows how heat stress and energy deficit
constrain milk and cow replacement rate. Animal Science, 82: 705-716.
Kurukulasuriya, P., Rosenthal, S. (2003) Climate change and agriculture: a review of impacts andadaptations. Climate Change Series Paper No. 91, World Bank, Washington DC.
Lacaux, J. P., Tourre, Y. M. (2008) Climate Change: A conceptual approach for assessing healthimpacts. Proceedings of a BSAS Conference 17-20 May 2008, Hammamet, Tunisia,
Lancelot, R., de La Rocque, S., Chevalier, V. (2008) Bluetongue and Rift Valley fever in livestock: aclimate change perspective with a special reference to Europe, the Middle East and Africa. In Livestockand Global Climate Change. Proceedings of a BSAS Conference 17-20 May 2008, Hammamet,
Tunisia, p 87.
Leng, R. A. (1984) Supplementation of tropical and subtropical pastures for ruminant production. In:
F.M.C. Gilchrist and R.I. Mackie, eds. Herbivore nutrition in the tropics and subtropics. Graighall, South
Africa, The Science Press. Pp.129-144.

ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

28

Lowe, W. H. (2003) Linking dispersal to local population dynamics: a case study using a
MacOpiyo. L., Angerer, J., Dyke P., Kaitho, R. (2008) Experiences on mitigation or adaptation needs in
Ethiopia and East African rangelands. LINKS/LEWS Global Livestock-CRSP, Addis Ababa, Ethiopia.
McManus, C., Prescott, E., Paludo, G. R., Bianchini, E., Louvandini, H., Mariante, A.S. (2009) Heat
tolerance in naturalized Brazilian cattle breeds. Livestock Science, 120: 256-264.
Mendelsohn, R. and A. Dinar, (1999) “Climate Change, Agriculture, and Developing Countries: Does
Adaptation Matter?” The World Bank Research Observer, 14: 277-293.
Merwe, B. J. (2005) Condition scoring of dairy cows: Cedara Agricultural Development Institute.
Morgan, J. A., Milchunas, D. G., LeCain, D. R., West, M., Mosier, A. R. (2007) Carbon dioxide enrichment
alters plant community structure and accelerates shrub growth in the short grass steppe. Proceedingsof the National Academy of Sciences of the United States of America, 104: 14724–14729.
Mugerwa, E. M. (1989) A review of reproductive performance of female Bos Indicus (Zebu) cattle.
International Livestock Centre for Africa, Addis Ababa, Ethiopia.
Muriuki, H., Omore, A., Hooton, N., Waithaka, M., Ouma, R., Staal S.J., Odhiambo. P. (2004) The policy
environment in the Kenya dairy sub-sector: A review.
Nyong, A., Adesina, F., Osman, E. (2007) The value of indigenous knowledge in climate change
mitigation and adaptation strategies in the African Sahel. Mitigation Adaption Strategy Global Change,
12:787–797.
Oba, G. (1997) Pastoralists traditional drought coping strategies in Northern Kenya. A Report for theGovernment of The Netherlands and the Government of Kenya. Euroconsult BV, Arnheim and Acacia
Consultants Ltd, Nairobi.
phospholipid bilayers and proteins by sugars. Biochemistry Journal, 242: 1-10.
Science. 77: 2044-2050.
Scientific Basis (Cambridge Univ Press, New York).

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ATPS (2013): Vulnerability and adaptation strategies to climate variability and change of the Bos-taurus dairy genotypes under diverse
production environments in Kenya. ATPS Research Paper No. 23

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ISBN: 978-9966-030-67-2

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