Heliyon 7 (2021) e08280Contents lists available at ScienceDirect
Heliyon
journal homepage: www.cell.com/heliyonResearch articleAdaptation, coping strategies and resilience of agricultural drought in South
Africa: implication for the sustainability of livestock sector
Yonas T. Bahta *, Vuyiseka A. Myeki
Department of Agricultural Economics, University of the Free State, Bloemfontein, South AfricaA R T I C L E I N F O
Keywords:
Sustainability
Resilience
Adaptation
Agricultural drought
Coping strategy
Smallholder farmer
Livestock* Corresponding author.
E-mail address: Bahtay@ufs.ac.za (Y.T. Bahta).
https://doi.org/10.1016/j.heliyon.2021.e08280
Received 2 April 2021; Received in revised form 2
2405-8440/© 2021 The Author(s). Published by ElsA B S T R A C T
Agricultural drought has put sub-Saharan African under significant pressure, and without adaptation, will
negatively influence a future generation. Hence, it is crucial to assess the adaptation and coping strategies, the
resilience of agricultural drought, its implication on the sustainability of the livestock sector, and developing
future interventions. Data of 217 smallholder livestock farmers were used in a principal component analysis to
estimate the agricultural drought resilience index as an outcome variable against social wellbeing, economic
outcome, environmental variable and adaptive capacity variables. The results found that 21% of the livestock
farming households sold their livestock as an adaptation and coping strategy. In contrast, 20% of the farming
households used alternative land use as an adaptation, and coping strategy, 20% stored food, 17% asked for
animal feed, 6% sought employment, 6% migrated, 5% kept drought-tolerant breeds, 3% received relief grants,
2% used their savings and investments, and 1% leased their farms. When natural, economic and social sustain-
ability was viewed as a resilience process, the three pillars positively and significantly impacted households'
agricultural drought resilience. This implied that the more smallholder farmers participated in social networks
and cooperatives, the higher the resilience to agricultural drought. Further, the more resources, income, access to
land, access to water, access to credit, and additional types of farming, the higher the households’ resilience to
agricultural drought and adaptive capacity. Thus, the three pillars of sustainability are crucial for enhancing the
resilience and adaptability of smallholder livestock farmers. The study recommends that government aid reduce
vulnerability to agricultural drought via access to agricultural credit and encourage farmers to be part of social
networks and cooperatives. Additionally, the government could improve access to land and water rights to boost
the resilience of smallholder farmers to agricultural drought. This could be achieved through collaboration and
coordination among all role players.1. Introduction
In comparison to floods, hurricanes, tornadoes, and earthquakes,
agricultural drought is the costliest natural disaster on the planet.
Drought affects the livelihood of the developing world's farmers and
economies, where an estimated 166 billion USD loss was recorded from
three-quarters of the global cropped area of 454 million hectares. Glob-
ally averaged, one drought event decreases agricultural gross domestic
production by 0.8%, with varying magnitudes by country (Kim et al.,
2019). The impact of agricultural drought puts additional strain on
already scarce resources and their long-term sustainability. Africa is the
most vulnerable to adapt to the effects of agricultural drought due to
limited resources. In developing countries, agricultural drought causes
80% of economic losses and affects the sustainability of agriculture by6 August 2021; Accepted 25 Octo
evier Ltd. This is an open accessreducing social wellbeing as well as decreasing economic and environ-
mental resources (Desanker et al., 2001; IPCC, 2001; Wilhite, 2007).
Agricultural drought-induced changes to social, economic, and environ-
mental resources affect the livelihoods of smallholder farmers unless
adequate measures are taken through adaptation and coping strategies
(Osbhar, 2007). The adaptation and coping strategies, agricultural
drought resilience, and the sustainability of the agricultural sector,
including livestock sectors, depend on economic, social, institutional,
environmental, and community factors (Fahad et al., 2017).
Smallholder livestock farmers mainly depend on natural resources
such as rainfall, which are directly affected due to climate variability.
Besides the shortage of rain, other factors also contribute to the vulner-
ability of smallholder farmers, such as frequent disasters, poverty, envi-
ronmental degradation, limited formal safety nets, limited adaptiveber 2021
article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Y.T. Bahta, V.A. Myeki Heliyon 7 (2021) e08280capacity, limited resources, and weak infrastructure (Shiferaw et al.,
2014; Myeki and Bahta, 2021).
Existing international and national studies focused on crops, grass
yield, the productivity of meat, milk, and wool, and the fertility of large
livestock (Sheaffer et al., 1992; De Rensis and Scaramuzzi, 2003; Parry
et al., 2005; Alves et al., 2013; Bodner et al., 2015; Rey et al., 2017;
Salmoral et al., 2020). There are limited studies on the livestock sector,
especially from the three pillars of sustainability (natural, economic, and
social). Therefore, this study assessed adaptation coping strategies and
resilience of agricultural drought in South Africa for the sustainability of
the livestock sector.
2. Adaptation, resilience, and sustainability
Adaptation refers to improving resilience and reducing households'
vulnerability when responding to agricultural drought impacts. Burton
et al. (2002) defined adaptation as the ability of economic, environ-
mental, and social systems to adjust to change and cope with the con-
sequences of agricultural drought. Agriculture, including livestock,
sustainability refers to the state in which agricultural production levels
are maintained within the ecosystem's capacity, while also supporting
and utilizing sustainability indicators that cover the three pillars of sus-
tainable development (environmental, economic, and social) (Kajikawa,
2008). Resilience thinking, on the other hand, sees sustainability as a
process of studying how to keep a system running in the face of adversity,
such as agricultural drought (Folke et al., 2002; Duru and Therond,
2015).
Following Van de Kerk and Manuel (2012); Carruthers and Hood
(2004), and Diener and Biswas-Diener (2002), the three pillars of sus-
tainability, namely social wellbeing variables (relatives, social network
and part of cooperative), economic variables (access to resources (credit),
other business beside farming, and types of enterprise), and environ-
mental variables (access to land, access to water and climate change
occurrence and intensity) were incorporated in this study. Besides the
three pillars of sustainability, adaptive capacity variables (perception,
source of income, and migration) were included. The theoretical and
empirical framework applied in this study is explained in Figure 1.Agricultural 
drought 
(disturbance)
Adaptation & 
coping strategy
Agricultural 
Drought Resilience 
Index (ADRI)
Figure 1. Analytical framework of the s
2
3. Methodology
3.1. Study area
The research was carried out in South Africa's Northern Cape Prov-
ince. The Northern Cape Province is located in South Africa's north-
western corner. Frances Baard (12 800 km2), John Taolo Gaetsewe (27
300 km2), Namakwa (126 900 km2), Pixley Ka Seme (103 500 km2), and
ZF Mgcawu (102 500 km2) are the province's five district municipalities.
The research was carried out in the Frances Baard district municipality
(FBDM) in the eastern part of the Northern Cape Province (Figure 2).
Dikgatlong (2 377.6 km2), Magareng (1 541.6 km2), Phokwane (833.9
km2), and Sol Plaatje (1 877.1 km2) are the four local municipalities that
make up the Frances Baard District Municipality (FBDM, 2018).
The province is divided into semi-desert and desert sections, with a
hot and arid climate. Summers in the Northern Cape is hot (between 34
and 40 
C) while winters are cold (nightfall temperatures below 0 
Cwith
frost). The climate is dry and unforgiving due to minimal rainfall
(average annual precipitation of 200mm) (VonMaltitz and Bahta, 2021).
Due to the considerable differences in climate throughout the district
municipalities, the Northern Cape Province produces a diverse range of
agricultural products. Livestock production continues to be the most
popular business, with over 75% of agricultural households focusing only
on animal production (Statistics South Africa, 2016). According to the
Department of Agriculture, Forestry and Fisheries (DAFF) (2018), the
Northern Cape produces 7% of the country's goats, 1.4% chickens, 24%
sheep, and 4% cattle.
The agricultural sector has been decimated by the recent drought in
the Northern Cape Province, and recovery has been delayed or non-
existent. The livestock business has been put under tremendous strain
due to a scarcity of fodder and water (DAFF, 2018). Smallholder farmers'
suffering was exacerbated by a number of reasons, including insufficient
grazing, a shortage of water, a scarcity of resources, and a lack of land
ownership. Most smallholder farmers, according to Matlou and Bahta
(2019), are vulnerable to agricultural drought. Lack social networks, lack
of cooperatives, lack of access to financing, and lack of government help
during droughts, contributed to their lack of drought resilience.Social wellbeing 
Variables 
Sustainability
Economic 
outcome
Variables
Environmen
tal 
Variables
tudy. Source: Author's Compilation.
Y.T. Bahta, V.A. Myeki Heliyon 7 (2021) e08280
Figure 2. Maps of South Africa highlighting the Northern Cape Province, District municipalities of the Northern Cape, and the four local municipalities of Frances
Baard District Municipality. Source: FBDM (2019).3.2. Study design
Mixed-method approach combines both qualitative and quantitative
research approaches to collect relevant data employed. Through this
mixed method, the following information collected socio-economics
characteristics, adaptive capacity, consumption, production, social
wellbeing, economic and environmental variables. According to Lieber
(2009), qualitative approaches offer the advantage of giving researchers
the context of the research environment and the human element,
resulting in comprehensive data that quantitative methods cannot
establish. Quantitative approaches, on the other hand, are concerned3
with gathering information and determining the relationship between
variables. The combination of the two approaches gives comprehensive,
in-depth study data with relevant conclusions and recommendations. As
part of the standard protocol for conducting the study, meetings were
held with stakeholders in the Northern Cape Province, which included
smallholder livestock farmers, the African Farmers Associations of South
Africa (AFASA), Northern Cape Department of Agriculture, Forestry and
Fisheries, and the Department of Rural Development and Land Reform.
The study's objective was explained at the meeting, and all participants
agreed to participate voluntarily. A questionnaire was used and included
continuous and categorical data, which comprised socio-economics
Y.T. Bahta, V.A. Myeki Heliyon 7 (2021) e08280characteristics, adaptive capacity, consumption, production, social
wellbeing, economic and environmental variables. Face-to-face in-
terviews with smallholder livestock producers in the Northern Cape
Province of South Africa were conducted from October to December
2020, using a structured questionnaire to acquire primary data. The
University of the Free State provided ethical clearance. Ethical clearance
was obtained from the University of the Free State.
3.3. Sampling procedure and analytical technique
A multi-stage sampling technique was used to perform the survey.
The Northern Cape Province was purposefully picked in the first round
because it represented South Africa's primary livestock-producing prov-
ince. The province was also declared a disaster region by the South Af-
rican government (Mar
e et al., 2018; Tandwa, 2018). The FBDM was
chosen at random in the second stage of the sample via balloting.
Phokwane, Magareng, Sol Plaatjie, and Dikgatlong were purposefully
chosen as the key livestock-producing municipalities within FBDM.
Finally, the sample frame was drawn from a list of smallholder farmers
identified and aided throughout the 2015/2016 crop season (Table 1).
According to the Northern Cape Department of Agriculture, Forestry and
Fisheries (2020), the four local municipalities assisted 878 smallholder
livestock farmers registered for assistance from the local government.
The government helped by providing animal feed and medication,
improving access to agricultural loans and farm input, and increasing
smallholder farmers' participation in agricultural drought resilience ef-
forts by providing training and disseminating information. Based on a
simple random sampling formula of Cochran (1997) and Bartlett et al.
(2001), 217 smallholder livestock farmers were selected from the 878
assisted farmers.
The Cochran's (1997) sample size formula was applied to determine
the correct sample size (Equation 1):
ðzÞ2¼ *ðwÞðmÞSample size ðxÞ2 (1)
where z is the level of confidence/Alpha level, w and m are the estimates
of the variance of the population, and x the margin of error (5% (0.05)).
Therefore (Equation 2):
¼ð1:65Þ
2*ð0:515Þð0:515Þ
Sample size ð (2)0:05Þ2
Sample size¼ 288:83
However, Sample size when exceeding 5% of the population,
Cochran's (1997) correctional formula should be applied (Eqs. (3) and
(4)):Table 1. Sampling procedure and smallholder livestock farmers received
assistance.
Municipalise Number smallholder Share (number Sample (Percentage
farmers farmers/total)% *total sample size [217])
Dikgatlong 351 40 87
Magareng 120 14 30
Sol Plaatje 141 16 35
Phokwane 266 30 65
Total 876 100 217
Note: The asterisk (*) represents multiplication.
Sources: Northern Cape Department of Agriculture, Forestry, and Fisheries
(NDAFF) (2020).
4
¼ Sample sizeN1 (3)
1þ ðN0=populationÞ¼ 288:83N1 (4)
1þ ð288:83=878Þ
N1¼ 217
3.4. Analytical procedures
3.4.1. Agricultural drought resilience index (ADRI)
The agricultural drought resilience indices (ADRI) were calculated
using the concept and scale of Walsh-Dilley et al. (2013). The ADRI was
calculated in four steps: (i) selecting resilience indicators; (ii) normal-
izing the selected indicators; (iii) creating weights; and (iv) aggregating
the final resilience index. Principal Component Analysis (PCA) was used
to calculate the weights for each resilience indicator. According to the
proportion variance explained by each indicator, we assigned weights
based on PCA. We also used expert judgment to assess the PCA weights.
The weighting was done to see any possible association between the
indicators and avoid overlapping components (Cutter et al., 2008; Matlou
et al., 2021). The ADRI has been applied for crops by Banda et al. (2016)
and the livestock sector by Matlou and Bahta (2019), Matlou et al.
(2021), and Myeki and Bahta (2021).
The ADRI was constructed using the following resilience indicators:
livestock production in a normal year (WnPn), livestock production in
agricultural drought (WdPd), the number of months a household con-
sumes food produced by the household in a normal year (WcnMn), and
the number of months a household consumes food produced by the
household in agricultural drought (WcdMd). PCA considers the variation
in the original data or variables to reduce a large number of variables to
smaller variables (Holland, 2008; Beaumont, 2012).
The four indicators (WnPn, WdPd, WcnMn, WcdMd) are aggregated into
an Agricultural Drought Resilience Index (ADRI) expressed as (Equation
5):
ADRI ¼ WnPn þ WdPd þ WcnMn þ WcdMd (5)
where: W- each component of Eq. (5) is a weighted linear combination of
the variables determined from principal components' loadings with a
zero mean and unit variance.
As presented in Table 2, due to variables that measure the same
construct, a high correlation among variables was observed. When
considering the communalities and the initial communalities, it is clear
that they are all greater than 0.30, which is a good sign. Based on the
analysis of eigenvalues, one factor was extracted. The total variance
explained indicates that 94.402% of the component explains the total
variance. The results of the Bartlett test of sphericity are demonstrated.
The results show that the null hypothesis is that the inter-correlationTable 2. PCA analysis of ADRI.
Variables Communalities Component factors Corrr.ADRI
Initial Extraction 1
WnPn 1 0.935 0.967 0.894
WdPd 1 0.958 0.979 0.995
WcnMn 1 0.280 0.963 0.890
WcdMd 1 0.955 0.977 0.984
Cumulative (%) 94.402.
KMO sampling adequacy test ¼ 0.636.
Bartlett's sphericity test is significant at p ¼ 0.0000; chi-square ¼ 2224.837.
Source: Author's Estimation (2020).
Y.T. Bahta, V.A. Myeki Heliyon 7 (2021) e08280matrix is an identity matrix. The reduction of variables is rejected since
the inter-correlation matrix did not drive from a population. The KMO
statistics for the model amounted to 0.636, and the Bartlett test of
sphericity was significant (p-value ¼ 0.000 chi-square ¼ 2224.837).
Eigenvalues are the variances of the principal components. The size of
the eigenvalue is used to determine the number of principal components. A
scree plot was used to compare the size of the eigenvalues visually
(Figure 3). The first principle component has an eigenvalue greater than 1,
explain 94.402% on the variation in the data. The scree plot shows that the
eigenvalue starts to form a straight line after the first principle component.
Therefore, 94.402% is an adequate amount of variation explained in the
data. As a result, the first principle component was utilized.
ADRI can be written as:
ADRI ¼ WnPn * 0.967 þ WdPd * 0.979 þ WcnMn * 0.963 þ WcdMd *
0.977 (6)
Based on Eq. (8), ADRI calculated incorporating the data obtained
from the interview related to production and consumption.
3.4.2. Structural equation modeling
A structural equation model was applied in this study (Table 3). The
model applies a factor analysis-style model to measure latent variables
via observed variables while also utilizing a regression-style model to
characterize the connection between the latent variables (Bollen, 1989;
Alinovi et al., 2010a, 2010b). Using ADRI as an outcome variable, ADRI
regressed against the three pillars of sustainability (social wellbeing
variables, economic outcome variables, and environmental economy
variables) with adaptive capacity, empirically expressed as (Equation 7):
ADRI ¼ f (social wellbeing variables, economic variables, environment
variables) (7)
Eq. (7) is disaggregated in Eq. (8), and the detailed description of the
variables is also illustrated in Table 3.
ADRIi ¼f(SWV ( relative, social network, part of cooperative); ADC
(Perception; Source of income; migration; credit), EOV (resource, multiple
sources of income, agripreneurship); EV (access to land, drought Occurrence,
and intensity, access to water)) (8)
4. Results and discussion
4.1. Adaptation and coping strategies
Farmers must have an adaptation and coping strategy when they deal
with drought. Figure 4 shows that selling livestock is the most commonFigure 3. Scree plot of ADRI. Sourc
5
adaptation and coping strategy; 20.96% of the farming households sold
their livestock as an adaptation and coping strategy. These findings
concurred with Bahta (2020). Further, Clements et al. (2011) highlighted
that farmers could get money whenever they wanted by selling their
animals during droughts.
In contrast, 20.2% of the farming households utilized alternative land
use (such as horticulture) as an adaptation and coping strategy, 19.81%
stored food, 16.67% asked for animal feed (assistance from government/
department of agriculture supplied fodder or vouchers to buy fodder),
5.72% sought employment, 5.71% migrated, 4.97% farmed with
drought-tolerant breeds, 3.22% obtained relief grants, 1.79% used their
savings and investments, and 0.95% leased their farms (Figure 4).4.2. The three pillars of sustainability with adaptive capacity
The resilience of the livestock sector to agricultural drought in the
Northern Cape Province of South Africa was assessed using adaptive
capacity (ADC) as well as the three pillars of sustainability, namely social
wellbeing (SWV), economic wellbeing (EOV), and environmental well-
being (EV); Table 4 shows the regression results. The results indicated
that all three pillars of sustainability with adaptive capacity have a
positive and significant impact on households' ADRI. Social wellbeing (ß
¼ 0.976), economic outcome (ß ¼ 0.144), environmental (ß ¼ 0.155),
and adaptive capacity (ß¼ 0.008) variables contributed to the regression
model. The Variance Inflation Factor (VIF) statistics for all the models
indicated no multicollinearity problem in the analysis (Table 4). This
meant that the greater the participation of smallholder farmers in social
networks and cooperatives, the greater their resilience to agricultural
drought.
Furthermore, the stronger a farming household's resilience to agri-
cultural drought and adaptive capacity was the more resources, income,
access to land, water, credit, and additional types of the farm they
possessed. These findings are consistent with Matlou and Bahta (2019),
who found that belonging to a cooperative positively impacted farmers'
resilience to agricultural drought. Keil et al. (2008) found involvement in
a number of village organizations positively impacted farmers' resilience
to agricultural drought. Furthermore, the literature suggests that resil-
ience is essential for improving adaptive capacity (Folke et al., 2002).
4.2.1. Social wellbeing
Social networks can be either informal (e.g., church groups) or formal
(e.g., farmers' associations) (Wongbusarakum and Loper, 2011). Iglesias
et al. (2007) and Hassen (2008) highlighted that when farmers partici-
pate in local institutions, their resilience to agricultural drought ise: Author's Estimation (2020).
Y.T. Bahta, V.A. Myeki Heliyon 7 (2021) e08280
Table 3. Description of variables.
Variables Descriptions
Outcome variable
Agricultural Drought Resilience Index (ADRI)
Explanatory variables Sub-variables Descriptions
Social wellbeing variable (SWV) Relationship (Relative) Interpersonal relationship (neighbours, family and other
relationships) (How many members of your family/relatives are
you staying with?)
Social farm actualization (social network) Positive comfort level with society (What role does social
network play in the fight against drought?)
Social farm integration (part of cooperation) Feeling like a part of the farming community (Are you part of a
cooperative? (Yes/No)).
Economic outcome variables (EOV) Resources Assets (Do you own any of the following: assets, land, livestock,
house? (Yes/No)
Multiple streams of income Generating income from additional business/property (Do you
have additional property/business that generates extra income to
recover during drought years? (Yes/No).
Agripreneurship (other additional types of a farm) Entrepreneurship in agriculture (What kind of agriculture
business do you run? (only animals ¼ 1, only crops ¼ 2, mixed
farming ¼ 3, other ¼ 4))
Environmental variable (EV) Land (access) Land availability for grazing, crop production, and livestock
grazing (land ownership (customary ¼ 1, rented ¼ 2, purchased
¼ 3, other ¼ 4))
Climate (drought occurrence and intensity Occurrence and intensity (When did the last time drought occur?
(less than 12 months ¼ 1, less than 5 years ¼ 2, and more than 5
years ¼ 3), (Do you think the intensity of this drought is: (worse
than the previous droughts ¼ 1; similar to the previous droughts
¼ 2; better than previous droughts ¼ 3)
Access to water Availability of sources of water (dams, rivers) (Is there a nearby
water supply (river/dam) for the household? (Yes/No)).
Adaptive capacity Perception Perceptions regarding risk, rainfall variation (Do you believe that
the climate is changing to the extent that it will affect your
livestock production? (Yes/No))
Source of income Off-farm activities generate additional income from employment
and business (How many members of your household are
employed?/Is there any other business the household is doing
besides farming? Yes/No), If yes, please specify
Migration Scarcity of employment, natural resource depletion, and
deterioration of food and rural livelihoods (Is migration an
adaptive option during the drought? Yes/No- what pushes them
to migrate?)
Credit Access to credit (Do you have access to credit when you need
them? (Yes/No)
Source: Author's observation (2020).enhanced because members of the social network could help each other
and access additional resources. The lack of effective social networks
contributes to social vulnerability during agricultural drought. As shown
in Table 5, assistance from relatives or being part of cooperatives posi-
tively impacted households' ADRI. This finding is consistent with Matlou
and Bahta (2019), Andersen and Cardona (2013), Banda et al. (2016),
and Keil et al. (2008). They found that households receiving support from
relatives or cooperatives tend to be more resilient than those not
receiving support or were not members of cooperatives. However, social
networks had a negative and significant effect irrespective of the negative
signs. Social networks contributed more (ß ¼ -0.202) to the regression
model than cooperatives (ß ¼ 0.123) or relatives (ß ¼ 0.007) (Table 5).
4.2.2. Economic outcome
Regarding economic outcome, resources, multiple streams of income,
and agripreneurship indicators positively impacted households' ADRI. As
shown in Table 5, resource (ß ¼ 0.193), multiple streams of income (ß ¼
0.053), and agripreneurship (ß ¼ 0.093) contributed to the regression
model. The marginal effect values for resource, multiple income, and
agripreneurship indicated that up to a certain point, for one increase in
economic outcome variables, the probability of the household becoming
resilient to agricultural drought increased by 0.193, 0.053, and 0.093,6
respectively, while holding all other factors constant. Ciani and Romano
(2004) and Melketo et al. (2021) found similar results. The authors
discovered that economic variables are positively and significantly
associated with the resilience index. If a household has numerous
appropriate resources, the impact of a shock is decreased because not all
resources are affected simultaneously. According to Iglesias et al. (2007),
agricultural drought may lower forage production in animal production,
resulting in changes in ideal farming systems and a loss of rural income.
4.2.3. Environmental variables
Saisana and Philippas (2012), Cruz and Manata (2020), and Com-
munity Tool Box Team (2021) highlighted that environmental factors
include water and land. Thus, access to land and water was included
under environmental variables. Access to land and duration and intensity
of drought positively impacted households' ADRI. Fellmann (2012)
highlighted that agricultural drought impacted the agricultural sector,
including the livestock sector, in multiple ways, such as frequency and
intensity of extreme weather events. As shown in Table 5, land (ß ¼
0.152), climate change (ß ¼ 0.059), and access to water (ß ¼ -0.001)
contributed to the regression model. Access to water nearby had a
negative and significant effect on resilience. In the face of water shortage,
this meant that agricultural diversification could have aided respondents
Y.T. Bahta, V.A. Myeki Heliyon 7 (2021) e08280
Sold livestock 20.96 
Alterna ve land use 20.2 
Storing food 19.81 
Asked for animal feed 16.67 
Migrate 5.71 
Sought employment 5.72 
Farm with drought-tolerant breeds 4.97 
Relief grant 3.22 
Savings and Investments 1.79 
Leased part of the farm 0.95 
0 5 10 15 20 25
Percentages  
Figure 4. Households' adaptation and coping strategies. Source: Author's compilation based on Survey Data (2020).
Table 4. Regression analysis smallholder livestock farmers’ agricultural drought Table 5. Estimation of smallholder livestock farmers’ agricultural drought
resilience index (ADRI) using adaptive capacity (ADC), social wellbeing (SWV), resilience with regard to adaptive capacity (ADC) social wellbeing (SWV), eco-
economic wellbeing (EOV) and environmental wellbeing (EV). nomic wellbeing (EOV) and environmental wellbeing (EV).
ADRI Unstandardized Standardized Sig. Indicators Unstandardized Standardized Sig.
Coefficients Coefficients Coefficients Coefficients
B ß Std. error VIF B Std. error ß
Constant 0.744 0.194 0.000*** Constant 0.744 0.194
SWV 1.015 0.976 0.009 0.000*** 1.55 SWV
EOV 0.848 0.144 0.050 0.000*** 1.67 Relative 0.002 0.021 0.007 0.920
EV 1.205 0.155 0.068 0.000*** 1.86 Social network -2.020 2.642 -0.202 0.445
ADC 0.025 0.008 0.028 0.000*** 1.90 Cooperatives 1.262 2.716 0.123 0.005*
R2 0.988 EOV
*** ¼ significant at 1% level. Resources/Wealth 0.504 0.197 0.193 0.011**
Source: Authors' estimation (2020). Multiple stream income 0.132 0.187 0.053 0.479
Agripreneurship 0.096 0.076 0.093 0.204
EV
Land 1.291 0.000 0.152 0.064*
Climate 0.022 0.030 0.059 0.465
Water -0.002 0.097 -0.001 0.001***
ADC
Perception -0.154 0.057 -0.181 0.007***
Income source -0.235 0.132 -0.122 0.077
Credit -0.541 0.155 0.250 0.001***
Migration 0.059 0.113 0.037 0.603
***¼ significant at 1% level; ** ¼ significant at 5% level; * ¼ significant at 10%.
Source: Authors' estimation (2020).
Strategies in coping better during the drought by providing additional income to
support their core farming enterprises. This was in line with Bahta's
findings (2020).
Agricultural drought, according to Gitz and Meybeck (2012), reduces
water availability and makes some pastures inaccessible, increasing the
demand for feed. As a result, feed prices rise, forcing livestock owners to
sell their animals. Cattle prices fall due to increased livestock sales during
a period of low demand, requiring farmers to sell even more to buy feed.
These price effects have a negative impact on farm and household income
and assets. Furthermore, they depreciate assets.
4.2.4. Adaptive capacity
Increasing adaptation ability and reducing household vulnerabilities
to agricultural drought are two ways to improve resilience (either envi-
ronmental, economic, or social). The results in Table 5 show that
migration and access to credit had a positive impact on households'
resilience. Migration (ß ¼ 0.037), credit (ß ¼ 0.250), perception (ß ¼
-0.181), and source of income contributed (ß ¼ -0.122) to the regression
model. The results of the marginal effect on the source of income
revealed that, up to a certain point, a decrease in the source of income7
reduces the likelihood of farming households' resilience to unfavourable
effects of agricultural drought by 0.122, while all other factors affecting
resilience remain constant.
According to the results of the marginal effect on the variable credit,
an increase in credit access raises the likelihood of a farming household
becoming resilient to agricultural drought by 0.250. This could be due to
the fact that finance allows smallholder farmers to diversify their liveli-
hood strategies beyond livestock production and provide better access to
Y.T. Bahta, V.A. Myeki Heliyon 7 (2021) e08280off-farm and non-farm income-generating activities, improving their
resilience. This finding is in line with Matlou and Bahta (2019), Andersen
and Cardona (2013), and Banda (2016), who found that credit-enabled
households were more resilient.
5. Conclusion and recommendations
The study aimed to assess the adaptation and coping strategies, the
resilience of agricultural drought, and its implication for the sustain-
ability of livestock farming in the Northern Cape Province of South Af-
rica. The study was crucial to elucidating production and sustainability
on a long-term basis and developing future interventions. The results
found that 21% of the livestock farming households sold their livestock,
20% used alternative land use, 20% stored food, 17% asked for animal
feed, 6% sought employment, 6% migrated, 5% farmed with drought-
tolerant breeds, 3% received relief grants, 2% used their savings and
investments, and 1% leased their farms as adaptation and the coping
strategies. When natural, economic and social sustainability was viewed
as a resilience process, the three pillars positively and significantly
impacted households' agricultural drought resilience. This implied that
the more smallholder farmers participated in social networks and co-
operatives, the higher the resilience to agricultural drought. Further, the
more resources, income, access to land, access to water, access to credit
and additional types of farming, the higher the households’ resilience to
agricultural drought and adaptive capacity. Thus, the three pillars of
sustainability are crucial for enhancing the resilience and adaptability of
smallholder livestock farmers. The study recommends that government
aid reduce vulnerability to agricultural drought via access to agricultural
credit and encourage farmers to be part of social networks and co-
operatives. Additionally, the government could improve access to land
and water rights to boost the resilience of smallholder farmers to agri-
cultural drought. This could be achieved through collaboration and co-
ordination among all role players.
The study used primary data to assess the adaptation and coping
strategies and agricultural drought resilience for only smallholder live-
stock farming households. There were some delays in collecting data
caused by the Covid-19 pandemic, and a language barrier was also a
limitation. Afrikaans and Setswana (local South African languages) are
the most widely spoken languages in the Northern Cape, making
communication challenging between the researcher and the respondents.
Future research could, for example, look into adaptation and coping
strategies, the resilience of agricultural drought on mixed farming, which
is outside the reach of this study. Such research could contribute to
identifying specific adaptation and coping strategies for both crop and
livestock farmers.
Declarations
Author contribution statement
Yonas T. Bahta: Analyzed and interpreted the data.
Vuyiseka A. Myeki: Contributed reagents, materials, analysis tools or
data.Funding statement
This work was supported by the project “Household resilience to
agricultural drought in the Northern Cape province of South Africa”
Contract Number/Project Number (TTK170510230380) of the National
Research Foundation (NRF), Thuthuka.Data availability statement
Data will be made available on request.8
Declaration of interests statement
The authors declare no conflict of interest.Additional information
No additional information is available for this paper.
Acknowledgements
We acknowledge and thank the anonymous reviewers for their
valuable comments and suggestions. We acknowledge Liesl van der
Westhuizen (Science Writer) for language editing this manuscript.
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