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Vulnerability of livestock based
communities to climate variability
and change: insights from Mid-Benin
Donald HOUESSOU
[email protected] / [email protected]
www.aced-benin.org
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Outline
 Introduction
 Research objectives
 Concept of vulnerability
 Methodology
 Results
 Implications
 Conclusion & suggestions
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Introduction
 The sub-Saharan Africa is one of the most vulnerable regions to
the effects of climate change due to the strong dependence
between rural communities and natural resources (IPCC, 2007)
 In Benin, these climate changes are already evident and will
negatively impact agriculture in general (Afouda, 1990 ; MEPN
and PNUD, 2008; MEHU, 2011)
 In livestock sector, due to higher temperatures, we could notify a
profound disturbance in the physiology of cattle, particularly in
milk and meat production
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Introduction
 In addition, livestock may be affected by the decline in pasture
productivity due to climate change induced degradation,
through overgrazing for example (MEHU, 2011)
 Now, livestock contribution to GDP in West Africa is estimated
between 8 et 15% (Kamuanga et al., 2004)
 In Benin, it contribute at 5,8% to GDP (INSAE, 2007)
 Although the vulnerability of livestock based communities to
climate change is accepted, there is very little quantitative
evidence on the impacts of climate variability and change on
livestock based communities.
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Research objectives
 This study aims to assess the vulnerability of livestock based
communities to climate variability and change.
 Specifically, it aims:
To develop a vulnerability index of livestock based communities
to climate variability and change;
To compare and explain the different levels of
between municipalities and livestock systems.
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vulnerability
Concept of vulnerability
 Recently, the vulnerability is understood as not only function of
biophysical variations but also function of environmental and
human systems that build communities sensitivity and adaptive
capacity (Vincent, 2004 and Gbetibouo et al., 2010).
 This approach uses then the vulnerability as « starting point » of the
analysis and considers it as a state that exists within a system before
it undergoes a climatic stress (Piya et al., 2012).
 The vulnerability is function of the character, magnitude, and rate
of climate variation to which a system is exposed, its sensitivity, and
its adaptive capacity” (IPCC 2001 ; 2007).
 Thus as per this definition, vulnerability has three components widely
used in this research: exposure, sensitivity and adaptive capacity.
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Methodology
Developing an index of vulnerability
Data collection
•
•
•
Exposure
Sensitivity
Adaptive capacity
Calculating subindex
𝑆𝑖 =
𝑝
𝑖=1 𝑃𝑖 𝑉𝑖
𝑝
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Data normalization
•
•
Taking into account functional
relationship between Indicator
and Vulnerability
Between 0 and 1
Calculating
vulnerability
index
𝑉 = (𝐸 + 𝑆 + 𝐶𝐴)/3
Weightening
indicators
𝑊𝑒𝑖𝑔ℎ𝑡 =
(𝐸𝑖𝑗 )2
Test t of Student
Investigating significance
Eij = Factorial weight of indicator i
on component j
Pi = Weight of indicator i
Vi = Mean of indicator i
p = Length of indicators
Results
0.5
0.46
0.4
0.4
0.3
0.24
0.28
0.22
0.29
0.25
0.33
0.2
0.1
0
Exposure
Sensitivity
Dassa-Zoumè
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Adaptive capacity
Tchaourou
Vulnerability
Results
Dassa-Zoumè
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
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Tchaourou
Agropastora
lism
Pastoralism
0.6
0.5
0.4
0.3
0.2
0.1
0
Agropastora
lism
Pastoralism
Results
 Gradual changes in climate (temperature and rainfall) and
extreme manifestations of climate change (long droughts and
excessive heat) are keys elements of exposure.
 The sensitivity of these livestock based communities to climate
variability and change is determined by their dependence on
livestock activities.
 The difference between their sensitivity is significantly explained by
the size of the camp, the time spent in the activity and the share
of livestock in annual revenue (p< 0,001).
 Adaptive capacity depends on the context of each herder and
the community.
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Results
 The herder gains in experience with age increasing allowing him to
well cope with extreme events of climate change. This factor is
further strengthened when there are indigenous climate prediction
systems that facilitate the planning of livestock activities.
 Diversification in animals and the use of veterinary care are two
other important factors that also strengthen adaptive capacity. For
example, vaccination is an effective solution in early drought to
fight against diseases caused by excessive heat.
 Thus, age, diversification in animals, the use of veterinary care (all
p<0.001) and existence of indigenous climate prediction systems
(p<0.01) explained the difference between the adaptive capacity
of the livestock based communities.
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Implications
 This research revealed that climate change has different impacts
on livestock based communities. For example, those who are the
most exposed are not necessarily the most sensitive or the least
able to adapt.
 The findings also highlight how socioeconomic inequalities may
influence vulnerability to climate variability and change (Dyson
2006; Laska and Morrow, 2006). This implies then the need to
support the communities in diversifying their livelihoods, through
off-farm or farm income generating activities.
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Implications
 Policies should also focus first on sensitivity and adaptive capacity
where they have great influence than exposure in a short term.
This policy option is consistent in the fact that the communities
that are already practicing agriculture (agropastoralism) are less
sensitive/more able to adapt (therefore less vulnerable)
compared to those practicing pastoralism.
 Finally, efforts to reduce the vulnerability must be integrated to act
simultaneously on exposure, sensitivity and adaptive capacity.
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Conclusion & suggestions
 This research has allowed the quantification of the vulnerability of
livestock based communities to climate variability and change.
 Understanding how the three components of vulnerability
influence the vulnerability is a starting point for future research
and policies development that could support these communities.
 This study has suggested:
The fostering of future research on the subject;
The strengthening of data and information collection systems;
The diversification of livestock based communities livelihoods.
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Thanks
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