Climate Risk Management 19 (2018) 83–93
Contents lists available at ScienceDirect
Climate Risk Management
journal homepage: www.elsevier.com/locate/crm
Adaptation opportunities and maladaptive outcomes in climate
T
vulnerability hotspots of northern Ghana
Philip Antwi-Agyeia,⁎, Andrew J. Dougillb, Lindsay C. Stringerb,
Samuel Nii Ardey Codjoec
aDepartment of Environmental Science, College of Science, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
b Sustainability Research Institute, School of Earth and Environment, University of Leeds, West Yorkshire, LS2 9JT Leeds, UK
c Regional Institute for Population Studies, University of Ghana, Legon, Ghana
A R T I C L E I N F O A B S T R A C T
Keywords: How climate change adaptation practices can constrain development and deliver maladaptive
Maladaptation outcomes in vulnerability hotspots is yet to be explored in-depth using case study analyses. This
Climate change and variability paper explores the effects of climate change coping and adaptation responses in three case study
Livelihoods villages across the Central Gonja district of northern Ghana. The study addresses the following
Mixed methods research questions: i) What are the key climatic and non-climatic stressors confronting house-
Africa
holds in northern Ghanaian communities? ii) How are households adapting to climatic and non-
climatic stressors? and iii) What are the outcomes of these coping and adaptation responses on
development? The study employs a mixed-method approach including key informant interviews,
focus group discussions and household questionnaire surveys. Data identified socioeconomic
stressors including a lack of access to (and high cost of) farm inputs, labour shortages and po-
pulation growth. Climatic stressors include erratic rainfall, high temperature, droughts and
floods. Climatic and non-climatic stressors interact to affect agricultural practices and related
livelihoods. The study identified various adaptation measures including extensification and in-
tensification of agriculture, temporary migration, planting of drought resistant varieties, irriga-
tion, and livelihood diversification. We show that many coping measures (e.g. livelihood di-
versifications activities such as selling of firewood and charcoal production) and adaptation
responses (including intensification, extensification and irrigation) currently deliver maladaptive
outcomes, resulting in lock-ins that could exacerbate future climate vulnerabilities. The paper
contributes to the growing literature on adaptation and climate risk management by providing
empirical evidence showing how coping and adaptations measures can deliver maladaptive
outcomes in vulnerable communities.
1. Research problem and justification
Sub-Saharan Africa is highly vulnerable to the adverse impacts of climate change and variability (Niang et al., 2014). Increased
temperatures coupled with erratic rainfall and uncertainties about the onset of the rains have significant implications for the live-
lihoods of hundreds of millions of people (Dube et al., 2016). Without appropriate adaptation, climate change will exacerbate current
vulnerabilities and present significant challenges for many rural households (IPCC, 2014). This paper examines how local coping and
⁎ Corresponding author at: Department of Environmental Science, College of Science, Kwame Nkrumah University of Science and Technology, PMB, University Post
Office, Kumasi, Ghana.
E-mail address: pantwi-agyei.sci@knust.edu.gh (P. Antwi-Agyei).
https://doi.org/10.1016/j.crm.2017.11.003
Received 28 April 2017; Received in revised form 27 September 2017; Accepted 23 November 2017
Available online 27 November 2017
2212-0963/ Crown Copyright © 2017 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license 
(http://creativecommons.org/licenses/BY-NC-ND/4.0/).
P. Antwi-Agyei et al. Climate Risk Management 19 (2018) 83–93
adaptation opportunities can provide multiple development benefits in an identified vulnerability hotspot region of northern Ghana.
The paper provides empirical evidence to examine the typologies of maladaptation proposed by Juhola et al. (2016), where adap-
tation action may deliver negative outcomes that: (i) affect target groups or sectors (rebounding vulnerability); (ii) compromise the
ability of different groups or sectors to respond to climate change (shifting vulnerability); and, (iii) fail to promote sustainable de-
velopment and result in environmental degradation (eroding sustainable development).
A rise in temperature and extreme weather events has been projected across all ecological zones of Ghana (EPA, 2007). Based on
General Circulation Models and using 1960s as the baseline, the country’s temperature has been projected to increase by 2.0 °C,
whilst rainfall is projected to decrease by 10.9%, by 2050 (EPA, 2007). Such changes will shorten the growing season with im-
plications for the agricultural and fisheries sectors as well as hydropower generation (Williams et al., 2017, Asante and Amuakua-
Mensah, 2015; Kabo-Bah et al., 2016). The agriculture sector is the mainstay of the Ghanaian economy, contributing significantly to
Gross Domestic Product and providing a source of livelihood to many low-income families (GSS, 2010). Yet, the agricultural sector is
dominated by poor small-scale farmers and remains one of the most climate sensitive sectors. Ghana’s economic growth and poverty
reduction efforts are centred on the modernisation of the agricultural sector. Therefore, unless carefully managed, climate change
could have adverse impacts on the country’s poverty reduction, economic growth and social development efforts. Northern Ghana has
been identified as a particularly vulnerable region to the changing climate (Antwi-Agyei et al., 2012).
The IPCC defines adaptation as a “process of adjustment to actual or expected climate and its effects. In human systems, adap-
tation seeks to moderate harm or exploit beneficial opportunities” (IPCC, 2014, p. 118). Adaptation involves medium- to long-term
adjustments in socio-ecological systems (Smit and Pilifosova, 2001). Alternatively, coping strategies relate to short-term measures
taken by households to moderate the adverse impacts of climate variability on their livelihoods over a time frame usually less than
one year (Engle, 2011). In some cases, coping and adaptation strategies may exert greater pressure on households’ abilities to
withstand future vulnerabilities (Brown 2007), and this can lead to maladaptation.
Maladaptation is used to describe “actions or inactions that may lead to increased risk of adverse climate-related outcomes,
increased vulnerability to climate change, or diminished welfare, now or in the future” (Noble et al., 2014; p. 857). Maladaptation
either increases the vulnerability of the target group or another group to existing or future climate variability (Barnett and O’Neill,
2010). Magnan et al. (2016) presented case studies from the Maldives, Ethiopia, South Africa, and Bangladesh and highlighted four
main dimensions in assessing the risk of maladaptation – i) process, ii) multiple drivers, iii) temporal scales, and iv) spatial scales.
Juhola et al. (2016) advanced the scholarship by providing a typology for assessing maladaptation. This paper extends the literature
on adaptation and maladaptation by providing empirical evidence to enhance understanding of how coping and adaptation practices
can deliver maladaptive outcomes in vulnerability hotspots using in-depth case study analyses in northern Ghana.
An increasing body of work has focused on identifying and assessing specific adaptation and coping strategies employed by
farming households to reduce the adverse impacts of drought linked to climate change on livelihoods of households (see examples
Bawakyillenuo et al., 2016; Antwi-Agyei et al., 2014; Codjoe et al., 2012). Other studies including Yaro et al. (2014) and Berman
et al. (2012) have explored how local institutions can be strengthened to facilitate climate change adaptation in dryland farming
systems. Further studies have focused on the role of local indigenous knowledge in reducing the adverse impacts of climate change on
the livelihoods of farming households (see Codjoe et al., 2014; Speranza et al., 2010; Nyong et al., 2007). Whilst these studies
document a growing body of knowledge on appropriate adaptation strategies, studies relating to how these adaptation practices can
be framed to deliver development benefits and improve adaptive capacities of households to respond to future climatic vulnerabilities
remain limited.
Some adaptation/coping strategies potentially compromise the ability of households to respond to existing and future climate
change and lead to lock-in effects, which can “shoehorn communities into positive or negative pathways of change” (Wilson, 2014, p.
1). Using a social resilience framework, Wilson (2014, p.11) identified structural lock-in effects such as moral codes that “define the
philosophical basis upon which community actions take place and usually find expression through traditions and specific rites”.
Political lock-ins relate to power structures and decision making within a community and reflect the political pathways of individuals
or groups in the community, which can lead to implementation of superior alternative community pathways (Davidson, 2010).
Economic lock-in effects are directly linked to economic capital within the community and the effects of globalisation on a com-
munity’s resilience (Wilson, 2014). Socio-psychological lock-ins are closely associated with “community-level endogenous social and
psychological factors” (Wilson, 2014, p. 16). As yet, there is a lack of empirical evidence about how and to what extent farming
households’ livelihood responses to climate change provide development benefits and avoid potential lock-in effects. This dimension
of adaptation decision-making is considered in this study.
This paper addresses the identified research needs by exploring the effects of climate change adaptation responses in three case
study villages across northern Ghana. Specifically, it addresses the following research questions: i) What are the key climatic and non-
climatic stressors confronting households in northern Ghanaian communities? ii) How are households adapting to climatic and non-
climatic stressors? and iii) What are the outcomes (or effects) of these coping and adaptation responses on development?
2. Research design and methods
2.1. Research design and study area
The study was conducted in the northern region of Ghana, where previous studies have identified agricultural livelihoods as
vulnerable to the adverse impacts of climate change (e.g. Acheampong et al., 2014; Antwi-Agyei et al., 2012). Northern Ghana is a
region where relatively minor rainfall variability or perturbations can lead to significant impacts on crops yield, because of limited
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Fig. 1. Study district showing study villages.
Source: Antwi-Agyei et al. (2016)
adaptive capacity (Antwi-Agyei et al., 2012). The northern region has been characterised by extreme events such as floods and
droughts and these have often resulted in extensive damage to crops and livestock leading to famine (EPA, 2007). These extreme
events have been projected to increase due to climate change, particularly increasing temperature and erratic rainfall, and these are
likely to further worsen livelihoods in this region (World Bank, 2010).
Three farming communities (Lito, Kusawgu and Yapei-Yipala) in the Central Gonja district of the northern region (Fig. 1) were
selected based on consultation and advice from Agricultural Development Officers at the Central Gonja district of the Ghana’s
Ministry of Food and Agriculture. The Central Gonja district has a population of 87,877 people and lies in the tropical continental
zone (GSS, 2010). The district experiences a uni-modal rainfall pattern that permits only one growing season. Rainfall generally starts
in May/June and ends August/September (Nkrumah et al. 2014). Average household size for this district is 7.6; slightly above the
national average of 4.5 people (GSS, 2010). Of the population above 15 years old, subsistence crop farming employs about 77.7% of
the population, with only a few farmers engaged in livestock rearing (GSS, 2010).
These farming communities are exposed to rainfall variability which has already adversely impacted on the livelihoods of the
households. These communities share common features regarding population, ethnicity and ecological problems. The ethnicity of the
majority of people in these communities is mainly Gonjas and Dagombas. The average landholding (ha) is 1.93 ha, 2.26 ha and
2.25 ha for Lito, Kusawgu and Yapei-Yipala, respectively (Antwi-Agyei et al., 2016). Smallholder farmers rely on rudimentary
agricultural technologies with rainfall determining crop productivity. Those lacking resources rely on natural soil fertility to support
agricultural production, including the use of poultry manure (MoFA, 2007). Food crops of importance include maize, rice, groundnut,
sorghum, millet, yam, soyabean and cowpea. The three study communities are served by the Buipe and Yapei markets, where
households sell any excess farm produce. Bush burning and land degradation are widespread in this district (MoFA, 2007). Patterns of
under-development, poor road networks, and lack of infrastructural development, have characterised these communities and the
northern region in general (GSS, 2010).
2.2. Research Methods
Household data were collected during April–June 2015. A household is defined as “a group of people who own the same pro-
ductive resources, live together and feed from the same pot” (Yaro 2006, p. 129). A mixed-method research design was used to
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capture households’ livelihood responses to changing environmental and climatic conditions in study villages. Methods including key
informant interviews, focus group discussions and household questionnaire surveys were adopted to gain local insights into the
complexity of climate variability and how it affects rural livelihoods.
In all, 219 household surveys were conducted in the three study communities, containing both open and closed ended questions.
To ensure a representative sample in the study communities, households were selected through stratified random sampling based on
age, gender and social standings. This stratification was based on observable social groups, informed by key informants in these
communities. Data collection proceeded with a rapid rural appraisal using transect walks, providing an overview of the significant
social and physical features, as well as household characteristics, in the study communities. The survey contained questions relating
to livelihood strategies, stressors on livelihoods, coping and adaptation mechanisms as well as the type of farming and land tenure
issues which are important in shaping resource access and livelihood option (Antwi-Agyei et al., 2015). Information on social net-
works, gender issues, values and belief systems, and traditional knowledge which may affect their capacity to adapt to climate change
and variability were collected to enable assessment of any ‘lock-in’ effects. Questionnaire administration was face-to-face with re-
spondents. Household respondents were asked to limit their answers to the last 40 years or since their childhood.
Six focus group discussions (FGDs) were also conducted (2 in each community) with an average of 14 participants drawn from
different socio-economic backgrounds, considering age, gender and social standing. Selecting participants with different socio-
economic backgrounds provided the opportunity to capture the different dimensions and complexity of climate change and livelihood
challenges. Participants included some of the farmers who took part in the household surveys and demonstrated considerable
knowledge on livelihood challenges. To improve participation of women, separate FGDs were held with female farmers and women’s
groups.
Nine key informant interviews were conducted with opinion leaders, purposefully selected based on their past experience and
knowledge on environmental change and livelihood challenges. The key informants included chiefs, chief farmers, and youth and
women’s group leaders. The purpose of the key informant interviews was to capture key temporal dimension of household responses
to climatic and socioeconomic drivers of change. Conducting these after the household surveys permitted the research team to further
probe any discrepancies in household responses arising from the household survey. The key informant interviews were also used to
triangulate information obtained from the FGDs.
To assess the long-term effects of coping and adaptation responses on development, focus group participants assessed the benefits
and risks of each of the adaptation options identified in the study communities. In analysing the data, adaptation outcomes were
classified as either: (i) rebounding vulnerability, (ii) shifting vulnerability and (iii) eroding sustainable development. Rebounding
vulnerability is a “simple connection implying an adaptation action that increases current or future climate change vulnerability of
the implementing actor” (Juhola et al., 2016; p. 136). Shifting vulnerability increases current or future vulnerability for one or
several external actors. Eroding sustainable development occurs when adaptation action “increases greenhouse gases (GHG) emis-
sions and negatively impacts environmental conditions and/or social and economic values” (Juhola et al., 2016, p. 136).
Quantitative data from the household questionnaire were analysed with SPSS using basic descriptive statistics. Qualitative data
from key informant interviews and FGDs were analysed using an inductive coding method, which allowed patterns and themes in
interview responses to be derived.
3. Results
3.1. Key stressors of changing agricultural practices and their impacts on livelihoods
Both household surveys and FGDs show that agriculture-dependent households in the study communities identified both socio-
economic and climatic factors as stressors influencing change in agricultural systems (Table 1). In terms of socioeconomic stressors,
high cost and poor access to farm inputs, labour shortages and population growth were reported. About 68% of respondents in the
household survey cited high cost and poor access to farm inputs as drivers of changing agricultural practices in the study commu-
nities. High cost and poor access to farm inputs was linked to economic decision making by focus group participants. They argued
that high costs made it difficult for small-holders farmers to purchase farm inputs and that leads to declining soil fertility. About 30%
of the household survey participants reported a lack of labour especially during the peak farming season in June/July. Labour
shortages were attributed mainly to migration of able-bodied men, especially the youth, to southern Ghana. “Most of our youth and
able-bodied men migrate to the south to look for employment opportunities. Many of them do not return at the start of the farming season and
this affects availability of farm labour. This affects farm operations and crop yield, which has implications for food security in this community
[Male farmer, focus group participant, Lito, April 2015]. Population growth, according to focus group participants, has also resulted
in less farmland available to farming households. One respondent noted: “when I started farming in this village, farmland was never an
issue. However, in recent years increased population pressure means that we have limited farmlands and do not have the luxury of allowing
farmlands to fallow” [Male farmer, focus group participant, Yapei-Yipala, April 2015].
Drought, high temperature, floods and erratic rainfall were the key climatic stressors identified by focus group participants. Most
(64%) of the respondents in the household survey reported erratic rainfall patterns as one of the key drivers of changing agricultural
practices in the study communities. There was consensus that it is now difficult to predict the onset of the rains using indigenous agro-
ecological knowledge. They reported that erratic rainfall makes it difficult to plan farm operations. Focus group participants at-
tributed the increasingly erratic pattern of the rainfall to farm practices and livelihood strategies pursued locally. Felling of trees for
charcoal production and farming around water bodies were considered to play an important role. As one farmer noted: “we are cutting
all the trees around our river bodies and this is causing the rivers to dry up and we bear the consequences of such actions” [Male farmer,
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Table 1
Socioeconomic and climatic stressors of changing agricultural practices based on focus group participants and household surveys.
Socioeconomic stressors Respondents citing this stressor Illustrative quote
(n=219)
a. Lack of access/high cost of farm 150 (68%) We do not have appropriate soil amendments to improve yields. Even when these farm inputs
inputs including fertilizers and drought resistant varieties of crops are there we do not have money
to purchase them. As a result, our soils are no longer as productive as they used to be.” [Key
informant interview, Lito, April 2015]
Labour shortages 66 (30%) “…gradually, farm labour is becoming a major problem for most farmers in this community.
Sometimes, you may have the rains and money but you cannot get the farm labour to work
on the farm. This affects various farm operations and eventually crop yield. This has become
more critical in recent times when certain farming practices such as planting should be done
at the appropriate time in order to avoid the dry spells that characterise most of the season”
[Female farmer, Focus group discussion, Lito, April 2015]
Population growth 26 (12%) “…increasing population growth is a major driver of changing agricultural practice in this
village. Having large population means that you cannot practice some of the agricultural
systems that you once practiced that allowed the soil to regain its lost fertility” [Male
farmer, focus group participants, Lito, April 2015]
Climatic stressors
Erratic rainfall 140 (64%) “You can no longer predict when the rains will come in this village. The start to the farming
season has become so unpredictable. You just have to prepare your lands and hope that the
rains will come for you to start the sowing process. What is more worrying is the erratic
distribution of the rains during the farming season. It rains today and then the rains stop for
a few weeks and this negatively affects crop growth” [Female farmer, Yapei-Yipala, May
2015]
Drought 36 (16%) “…prolonged periods without rains have become a common occurrence in this community
and surrounding villages. The farming season is shortening due to drought. When I started
farming in this village over 25 years ago, farmers could start the sowing process by late
March or early April. In recent times, we now start planting in mid-May because of drought”
[Male farmer, Kusawgu, May 2015]
High temperatures 105 (48%) The weather has become hotter and this affects our crops. When crops begin to grow and the
temperature is high, they wither, and this adversely affects yield. This affects food security
for my family [Female farmer, Kusawgu, May 2015]
Flood 13 (6%) “…it is becoming too depressing that sometimes, you wait too long for the rains to come and
after the planting process and the crops begin to bear fruits, suddenly you have excessive
rains and this destroys field crops. The last time it happened all our crops were flooded and
this seriously affected food for households in this community. When there are no rains, there
is trouble and when there are rains, too, you have it in excess and this creates problem for
crops” [Female farmer, focus group participant, Yapei-Yipala, May 2015]
Kusawgu, May 2015). Trees and forests play important role in regulating temperatures as well as the flow of fresh water resources.
Hence, indiscriminate cutting of trees can have a devastating effect on water resources, adversely affecting crop productivity and
related livelihoods in the study communities (Ellison et al., 2017). Such quotes show that farmers are aware of the key climatic and
non-climatic stressors underpinning changes in livelihood and agricultural practices in the study communities.
There was strong agreement amongst respondents in the household survey that the stressors identified were negatively influ-
encing their livelihoods and food security. Almost all the respondents who cited erratic rainfall as a climatic stressor indicated that it
was affecting their farm operations and leading to lower yields. This was affirmed by participants in the FGDs who indicated that
stressors, especially erratic rainfall, adversely affected their livelihoods. One focus group participant stated: “Our livelihoods are
predominantly dependent on the extent and distribution of the rains during the farming season. Any shift or variation in the rainfall during the
farming season causes lots of distress to families in this community” [Focus group participant, Lito, April 2015]. The high cost of farm
inputs leading to the declining soil fertility was seen as responsible for low yield. A farmer reported: “Our soils are no longer as
productive as they used to be. When I started farming in this village 25 years ago, I could harvest almost thrice in terms of maize compared to
what I get in recent years” [Male farmer, focus group participant, Lito, April 2015]. Excessive heat linked to increasing temperature and
dry spells during the farming season were also reported to adversely affect households’ livelihoods. A farmer remarked: “excessive heat
makes farm crops wither, which eventually affects crop yield. Lower yields from our farms have devastating consequences for our families”
[Male farmer, focus group participant, Kusawgu, April 2015].
One key impact of climate variability on farming households was the inability of farmers to use their indigenous agro-ecological
knowledge to forecast rainfall patterns. One farmer noted: “when I started farming in this village about 40 years ago, one could tell when
the rains would come and therefore be able to plan their planting appropriately. In recent years, we have to prepare the lands and wait in
anticipation of the rains. The start of the farming season is also not constant and this affects farming operations which leads to lower crop
yields” [Female farmer, focus group participant, Yapei-Yipala, May 2015]. There was also a consensus among focus group participants
and key informants that rainfall variability during the farming season in recent years has become more pronounced. This demon-
strates that farming households are adversely affected by both socioeconomic and climatic-related stressors.
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Table 2
Climate change coping and livelihood diversification activities according to gender.
Strategy Male-headed households (n= 132) Female-headed households (n=87) Total (n= 219)
a. Selling livestock 63 (47.7) 16 (18.4) 79 (36.1)
b. Firewood harvesting 44 (33.3) 35 (40.2) 79 (36.1)
c. Basket weaving 7 (5.3) 2 (2.3) 9 (4.1)
d. Wage labour 32 (24.2) 13 (14.9) 45 (20.5)
e. Fishing 24 (18.2) 0 (0.0) 24 (11.0)
f. Shea nut picking 35 (26.5) 45 (51.7) 80 (36.5)
g. Petty trading 48 (36.4) 35 (40.2) 83 (37.9)
h. Gari processing 11 (8.3) 26 (29.9) 37 (16.9)
i. Charcoal burning 26 (19.7) 26 (29.9) 52 (23.7)
j. Changing diet 70 (53.0) 43 (49.4) 113 (51.6)
k. Reduce consumption 68 (51.5) 52 (59.8) 120 (54.8)
l. Rely on remittances 41 (31.1) 36 (41.4) 77 (35.2)
m. Rely on social networks 33 (25.0) 33 (37.9) 66 (30.1)
Numbers in parentheses indicate percentages and those not in parentheses are counts of households.
3.2. Household coping and adaptation strategies to socioeconomic and climatic drivers
Table 2 shows the key measures for coping with climate change and socioeconomic stressors including selling firewood, livestock,
petty trading and wage labour. It needs to be stressed that some of these coping measures including selling firewood involve in-
discriminate cutting of trees that can lead to destruction of important fauna and flora and erosion of other adaptation options.
Additional coping measures included changing diet and reducing the number of meals and amount of food consumed by the
household. The presence of the Black and White Volta and its tributaries in the Central Gonja district provides fishing opportunities,
with 11% of households reporting using fishing as a coping strategy. Reliance on remittances by 35% of households was also noted to
play a crucial role. Such remittances are linked to family members who migrate to the south during the lean season (December–April/
May) to look for better job opportunities. Further, 30% of the households relied on their social networks including family and friends
to cope with drought and other stressors. There were clear differences between the livelihood diversification strategies preferred by
male and female farmers. Selling livestock was a predominantly male preferred strategy whilst shea nut picking was mostly reported
by female farmers.
Table 3 presents results on the key adaptation strategies identified. Both male and female farmers reported using different farm
management practices, notably, planting early to avoid dry spells and planting early maturing varieties of crops. Intercropping and
the planting of drought tolerant varieties were also frequently reported. Focus group participants noted additional adaptation
practices including increased use of fertilizers and changing tillage practices. Households reported that mulching was used to
moderate high temperatures that increase evaporation. Households also reported temporary migration to southern Ghana to sell
labour as an adaptation. Tables 2 and 3 show that gender influences the choice of different responses to socioeconomic and climate
stressors. For instance, whilst the majority of male farmers (65%) reported using extensification of agriculture as a strategy, only 21%
of the sampled female farmers indicated using extensification.
3.3. Outcomes of households’ responses to climatic and socioeconomic stressors
Table 4 shows the various benefits and risks associated with the responses. With regard to agricultural intensification and ex-
tensification, benefits include enhanced availability of food for households and the opportunity to improve livelihoods. In terms of
risks, results showed that agricultural intensification results in a less diverse agro-ecosystem. Agricultural intensification, through
Table 3
Climate change adaptation activities according to gender.
Strategy Male-headed households (n= 132) Female-headed households (n= 87) Total (n= 219)
a. Intensification of agriculture 49 (37.1) 66 (75.9) 115 (52.5)
b. Extensification of agriculture 86 (65.2) 18 (20.7) 104 (47.5)
c. Temporary migration 41 (31.1) 16 (18.4) 57 (26.0)
d. Changing land management practices
i. Planting early maturing crops 85 (64.4) 59 (67.8) 144 (65.8)
ii. Planting drought tolerant crops 56 (42.4) 42 (48.3) 98 (44.7)
iii. Mixed cropping 71 (53.8) 47 (54.0) 118 (53.9)
iv. Mixed farming 35 (26.5) 0 (0.0) 35 (15.9)
v. Irrigation 7 (5.3) 28 (32.1) 35 (16.0)
vi. Mulching 25 (18.9) 17 (19.5) 42 (19.2)
vii. Indigenous agro-ecological knowledge 28 (21.2) 37 (42.5) 65 (29.7)
Numbers in parentheses indicate percentages and those not in parentheses are counts of households.
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Table 4
Evaluation of benefits and risks associated with households’ coping and adaptations strategies to climatic and socioeconomic stressors in study communities.
Adaptation strategy Benefits Risks Overall outcomes
a. Agricultural • Intensification includes the use of improved • The intensive use of agro-chemicals Eroding sustainable
intensification varieties and breeds, more efficient use of especially nitrogen based fertilizers releases development
labour, and better farm management that greenhouse gases (Stehfest et al., 2010)
leads to increased productivity (Dixon et al. • The move toward agricultural intensification
2001) has resulted in less diverse, less
• Improves household food security (Godfray physiologically efficient (because of the need
and Garnett, 2014) for external inputs), and less adaptable
systems (Lin et al., 2008)
Agricultural extensification • Contributes to preservation of the • Extensification is a significant contributor to Eroding sustainable
environment by reducing the inputs of deforestation in many dryland farming development
chemical fertilizers and pesticides systems (Hosonuma et al., 2012)
• Improves soil and water conservation, • Slash and burn practices result in reduced
promote better stewardship of the land itself, biodiversity.
and enhance the appreciation of land values • Using natural biological processes and cycles
in controlling pest (in lieu of pesticides), and
fewer external inputs such as chemical
fertilizers may result in lower crop
production
Temporary Migration • Reduces pressure on household food reserves • Increases pressure on inadequate social Rebounding
(McLeman and Hunter, 2010) services provision (Ionesco and Chazalnoel, vulnerability; Shifting
• Improves livelihoods and minimizes harm to 2015) vulnerability
individuals (Ionesco and Chazalnoel, 2015). • Leads to reduced farm labour which affects• Helps to diversify incomes and enhances farm operations
capacities to deal with environmental and • Farmers can miss critical periods including
climatic changes (Kelpsaite and Mach, 2015) sowing if they do not return on time
• Migration every season reduces ability to
plan household farm operations
b. Changing land Overall: Shifting
management practices vulnerability;
(strategy) rebounding
vulnerability
i. Irrigation (activity) • Contributes to the reduction of poverty since • Irrigation could potentially result in conflict Eroding sustainable
it can facilitate many farmers to cultivate because of competing demands for water in development; Shifting
high value crops such as paddy, fruits and these villages vulnerability
vegetables (Shongwe, 2013) • Requires a good and reliable water source
ii. Planting drought • It increases the water-use efficiency of not N/A N/A
tolerant plants only the plants but the whole farm
(activity)
iii. Planting of early • Early maturing seeds enable crops to escape • Early maturing crops can be affected by the N/A
maturing crops long dry spells towards the end of the long drought spell and lead to crop failure
(activity) growing season (Shongwe, 2013) (Kihupi et al., 2015)
• Early maturing crops (for instance hybrid
maize) is capital intensive in terms of seeds
and fertilizer (Shongwe, 2013)
iv. Mulching • Prevents erosion and increases soil fertility N/A N/A
(activity) thereby improving crop yield
• Protects the soil from excessive heat,
exposure to wind, and moisture loss (Recha
et al., 2014)
Livelihood diversification Overall: rebounding
(strategy) vulnerability; Shifting
vulnerability
i. Selling livestock • Selling livestock provides increased stability • Selling of livestock depletes the livestock Rebounding
(activity) in income for the family without disrupting stock and perpetuates poverty (Haggblade vulnerability
other food producing activities (FAO, 1999) et al., 2010)
ii. Selling wage labour • Provides opportunity for farmers to earn • Selling farm labour leaves farmers with Shifting vulnerability
(activity) income for food and other households’ needs limited time to work on their own farms,
(Laube et al., 2012; Bawakyillenuo et al., which affect farm operations and crop yield
2016)
c. Dietary management Overall: rebounding
(strategy) vulnerability
(continued on next page)
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P. Antwi-Agyei et al. Climate Risk Management 19 (2018) 83–93
Table 4 (continued)
Adaptation strategy Benefits Risks Overall outcomes
i. Reducing food • This ensures regular availability of food • Reducing food consumption will imply that Rebounding
consumption (activity) people will be fed less or endure some form of vulnerability
hunger
• Reducing food consumption can have
devastating consequences for health
especially for children and the elderly
ii. Changing diet (activity) N/A • Changing diets also erodes cultural identity Rebounding
of the households vulnerability
increased fertilizer input can result in biodiversity loss, pesticide poisoning, and decline of ecosystem services (Zhao et al., 2013,
Tilman et al. 2002). Similarly, the conversion of natural habitats for food production via agricultural extensification and intensive
agriculture reduces biodiversity which can affect capacity of the ecosystem to provide services such as flood prevention and water
purification (Frison et al., 2011). Results showed that diversification into non-farm livelihood activities provide opportunities for
employment that bring extra financial resources to support farm income (Table 4). The availability of abundant water resources
including the White and Black Volta provides another opportunity that farming households could exploit. Again, planting early
maturing varieties of crops allowed farmers to harvest crops early in the season to prevent starvation.
Selling labour could provide immediate relief to the households, nevertheless, there are risks associated with this coping me-
chanism. For instance, wage labour elsewhere through seasonal migration means less labour in these communities for farming
activities, and this can result in key deadlines for critical farming operations being missed, affecting crop yield and the ability of
subsistence farmers to feed their families. Focus group participants and key informants noted that selling farm labour could po-
tentially lead to less time on one’s own farm. A farmer provided a typical response during a FGD: “Selling farm labour as a coping
strategy could be counter-productive because it leaves one with less time to work on their own farm on time.” [Male farmer, focus group
participant, Lito, April 2015]. Selling livestock to cope with climate change induced food insecurity may be a good strategy in the
short term but in the long term may not contribute positively to development. This is reflected in the following remark: “I always
restock my livestock in the beginning of the season. This is because I sell most of my livestock to cope with [drought-induced] food shortages”
[Male farmer, key informant interview, Yapei-Yipala, May 2015]. Irrigation provides protection against drought and ensures
availability of food reserve but may also result in less water becoming available for domestic uses. Yet, irrigation involves high capital
investment, which can be a challenge to many rural households because of their poor financial backgrounds (Shongwe, 2013), and
erosion of the financial capital of poor households could limit their capacity to respond to future threats posed by climate change and
variability.
4. Discussion
Results in this study reveal that households employ a host of coping and adaptation strategies in responding to the threats of
climate change and variability. These strategies can be categorised into intensification of agriculture, extensification of agriculture,
migration, changing land management practices and livelihood diversification. The use of irrigation has been reported as one of the
key climate change adaptation strategies by households across northern Ghana (see Laube et al., 2012; Dovie, 2011). Irrigation has
been identified by development partners and the Government of Ghana as one of the key strategies for tackling the adverse impacts of
climate change on rural resource-poor marginalised farmers (GoG, 2011). Coping measures broadly related to livelihood diversifi-
cation activities including, selling of firewood, wage labour, shea nut picking and selling livestock to cushion marginalised house-
holds against climatic and non-climatic shocks. For instance, livestock represent a key asset and insurance mechanism for the farmers
as they can easily be sold to raise financial capital to purchase food (Hesselberg and Yaro, 2006). The use of drought resistant
varieties of crops and mixed farming practices are age-old agricultural practices, but which are assuming greater prominence in
households’ quest to find solutions to climate change (Yaro, 2013). Households reported using their indigenous agro-ecological
knowledge (including the flowering and fruiting of certain trees etc.) to indicate the onset of the rains. This helps households in
preparing their farms in anticipation of the rains. Such findings match other studies suggesting that farmers across sub-Saharan Africa
rely on their indigenous agro-ecological practices and knowledge to cope with climate change and variability (see Antwi-Agyei, 2012;
Nyong et al., 2007; Speranza et al., 2010). Yet, with temperatures projected to increase between roughly+ 2.0 °C and+4.5 °C by
2100 across sub-Saharan Africa (Muller, 2009), the reliability and sustainability of indigenous agro-ecological knowledge has been
questioned (Naess, 2013). This raises serious concerns with grave implications for climate change adaptation because these farmers
have limited capacity to employ other adaptation measures that may require high financial capital outlay such as the use of drought
resistant varieties of crops.
Results also highlight cases where negative outcomes are leading to maladaptation. Following Juhola et al. (2016), we highlight
three specific ways in which coping and adaptation actions can deliver maladaptive outcomes: rebounding vulnerability, shifting vul-
nerability and eroding sustainable development. The first type of maladaptive outcome is related to rebounding vulnerability. Despite the
potential of livelihood diversification to provide a pathway for adaptation to climatic change, Haggblade et al. (2010) have high-
lighted the complexity of disentangling the links between non-farm livelihood activities and poverty reduction. Some of the
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livelihood diversification activities deliver maladaptive outcomes which have the potential to either reduce the adaptive capacity of
the household or increase its sensitivity and exposure. For instance, selling livestock has been reported to offer opportunities for
households to cope with droughts in northern Ghana (see Laube et al., 2012; Bawakyillenuo et al., 2016). Yet, this reduces the
farmers’ stock and the capacity to use such assets to manage future climate vulnerabilities. Such measures potentially result in lock-in
effects (Wilson, 2014), and these may be detrimental to the capacity of households to respond to existing and future climate change.
Lock-ins lead to vicious cycles in which households resort to short-term ad-hoc measures in coping with climate change vulnerability
year after year. Adopting such an approach in managing the adverse impacts of climate change perpetuates vulnerability and pushes
households further into the poverty trap, making it difficult for households to get out of such lock-ins.
The second type of maladaptive outcome is shifting vulnerability. For instance, excessive use of agro-chemicals and inputs by
farmers through agricultural intensification, can then leach into nearby water bodies, compromising their use for human con-
sumption. A lack of water predisposes such households and community members to diseases and reduces their adaptive capacity to
climate change, thereby increasing their overall vulnerability. Such cases are in line with McEvoy and Wilder’s (2012) argument that
one group’s adaptation may constitute environmental hazards for another group. This shows that successful climate change adap-
tation actions at the household level can result in climate vulnerability at the community scale. Shifting vulnerability emphasises the
need to address spatial dimensions of climate change adaptations. Similarly, agricultural biodiversity is also critical for food and
nutritional security as well as enhancing adaptation to climate change and this too is placed at risk from intensification (Frison et al.,
2011). Using limited water resources for irrigation purposes in these dryland farming communities could potentially result in conflict
because of competing demands for water for domestic and agricultural purposes. With an estimated 75–250 million people in Africa
facing climate change related water scarcity by 2020s (Arnell, 2004), the long-term reliance on irrigation as an adaptation strategy
could be in jeopardy.
Results also indicated that some of these adaptation responses including agricultural intensification, agricultural extensification
and irrigation could erode sustainable development. For instance, expanding the amount of land used for agricultural production via
agricultural extensification can have devastating consequence for development through increased land degradation and deforesta-
tion. Agriculture is a significant contributor to deforestation in many dryland farming systems (Hosonuma et al., 2012). Agricultural
extensification involves the conversion of new land to agriculture which results in very significant releases of greenhouse gases into
the atmosphere and is particularly devastating when forests are converted into agriculture to feed the increasing population (Godfray
and Garnett, 2014). Cultivating more farmland in an attempt to adapt to climate change could also alter carbon fluxes and conse-
quently increase emissions, depending on the land management practices adopted (Stringer et al., 2012). Cutting trees to sell as
firewood could provide immediate relief to households but in the long-term could exacerbate their vulnerability to climate change by
reducing carbon sinks. Such adaptation actions have the potential to affect the attainment of Sustainable Development Goal 13,
which advocates for actions against climate change (UNDP, 2015). Adaptation outcomes resulting in maladaptation and lock-ins raise
serious concerns about equity, efficiency and legitimacy of adaptation actions (Paavola and Adger, 2006). Adaptation actions that
erode sustainable development also have the tendency to degrade the environment because they usually degrade common pool
resources. Findings relating to adaptation options that result in increased GHG emissions and environmental degradation are con-
sistent with reports in other studies (Beilin et al., 2011; Barnett and O’Neill, 2010; Andersson-Skold et al., 2015). This indicates the
need to reflect on the long-term impacts and temporal dimensions of climate change adaptations on development. Adaptation actions
should critically explore the relationship between adaptation and sustainable development and understand the context of vulner-
ability, including unravelling the feedbacks between multiple stressors (Eriksen et al., 2011), as well understanding the spatial and
temporal interplay that can potentially adversely influence adaptation outcomes.
5. Conclusions
This paper has explored how climate change coping and adaptation responses can sometimes lead to maladaptive outcomes.
Findings identified the key climatic and socioeconomic stressors that adversely influence agricultural systems in northern Ghana.
Socioeconomic stressors included lack of access and high cost of farm inputs, labour shortages and population growth whilst the
climatic stressors included erratic rainfall, high temperatures, droughts and floods. The paper demonstrated that climatic and non-
climatic factors interact to affect agricultural practices. In terms of coping and adaptation measures, the study identified various
options including extensification and intensification of agriculture, temporary migration, planting of drought resistant varieties,
mulching etc. Advancing the work of Juhola et al. (2016), the paper has demonstrated with empirical evidence three types of
maladaptive outcomes that are occurring in the study communities: rebounding vulnerability, shifting vulnerability and eroding sus-
tainable development.
These findings suggest that climate change adaptation policy should be devised in a manner that enhances household adaptive
capacity in the short term whilst promoting their development benefits in the long-term. It is vital that development partners and
policy makers develop appropriate and robust indicators to assess the long-term effects of various climate change adaptation actions
in order to reduce maladaptation. This paper contributes to the burgeoning literature on adaptation and climate risk management by
providing empirical evidence to enhance understanding of how coping and adaptations measures are delivering maladaptive out-
comes in vulnerable communities of northern Ghana.
Acknowledgements
This research was supported by funding from the Department for International Development (DfID) under the Climate Impact
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Research Capacity and Leadership Enhancement (CIRCLE) programme. The authors acknowledge the support of participating
communities in this study. The study also received additional funding from the UK ESRC’s Centre for Climate Change Economics and
Policy University of Leeds, UK (Grant number: ES/K006576/1).
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