THE ADAPTIVE CAPACITY OF SMALLHOLDER FARMERS TO CLIMATE CHANGE IN THE NORTHERN REGION OF GHANA

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Abstract

Climate change is expected to adversely affect agricultural production, particularly in sub-Saharan Africa where the agricultural sector forms the backbone of most countries’ economies. This thus holds true for the agriculture sector of the Northern Region of Ghana which is largely rain-fed and dominated by smallholder farmers with minimal livelihood alternatives. The main research question of this paper is how the adaptive capacity to climate change of smallholder farmers in the Northern Region of Ghana can be characterised? The paper proposes an indicator-based framework for assessing the adaptive capacity of smallholder farmers in the Northern Region of Ghana along six main determinants of adaptive capacity: economic resources, social capital, awareness and training, technology, infrastructure and institutions. Based on a thorough literature review and qualitative interviews with experts for rural livelihoods and agriculture in the study region, the determinants were ranked and three to five indicators per determinant were selected. The results of the expert interviews show that economic resources, awareness and training as well as technological capacities seem most relevant for smallholder farmers’ adaptive capacity while infrastructure, social capital, and institutions were ranked least important. The study operationalized the indicators in a standardized survey questionnaire and tested it in two agrarian communities in the Northern Region of Ghana. The survey results show the aggregate adaptive capacity of respondents is low. However, disparities in adaptive capacity were recorded among respondents in terms of gender and education. Differentiating between the determinants women farmer show significantly lower capacities in fields of economic resources, technology and knowledge and awareness. This paper recommends resilience building interventions in the study area that target individuals with low adaptive capacities, especially women and farmers without formal education.

1. Introduction

Over the past few decades, climate change has adversely affected both physical and biological systems in most continents across the globe (Rosenzweig et al., 2007). According to Porter et al. (2014), in the past 30 years climate change has contributed to global agricultural production declining by 1–5% per decade. Its effects are also predicted to manifest in severe consequences for the global agricultural sector, especially in tropical and sub-tropical regions (Dewi, 2009, Thornton, 2012).

Where the economies of a majority of countries are largely driven by the agricultural sector, such as in sub-Saharan Africa, the impacts of climate change are particularly severe. The rapid and uncertain changes in temperature and rainfall pattern in the subcontinent deepens the vulnerability of the agricultural systems, especially food production already today (AGRA, 2014). This trend is expected to intensify in the future with the predicted climate change in tropical regions as it is expected to cause a significant decline in the production of important and staple food crops in such regions (Nelson et al., 2009, Porter et al., 2014). In response to expected changes, governments supported by international cooperation have intensified their efforts to empower the agricultural sector to effectively adapt to climate change at both national and local levels.

This holds particularly true for the Northern region of Ghana, one of the driest savannah regions of Ghana, where an increasing number of droughts, floods and bushfires heavily affect nature and humans (Dazé, 2013, Akudugu and Alhassan, 2012). It is found to be one of the most vulnerable and exposed regions to climate change and variability in Ghana (Etwire et al., 2013, Stanturf et al., 2011). At the receiving end of these impacts are millions of poor smallholder farmers with minimal livelihood alternatives who are already marginalised, poor and largely rely on nature for food and income (Frank and Penrose Buckley, 2012, Morton, 2007). Their rain-fed agriculture, forming the dominant economic activity in the region (Antwi-Agyei et al., 2012), relies heavily on a single and already modified rainy season. Over the past decade, there have been growing number of studies on possible ways of increasing the resilience of these farmers against climate change impacts in the region. Most of these studies are largely centred on farm-level adaptation methods and strategies (Wossen et al., 2014, Al-Hassan et al., 2013, Kuwornu et al., 2013, Laube et al., 2012, Armah et al., 2011). There are only a few studies on the adaptive capacity of smallholder farmers towards the new climate variabilities in the region (Nantui et al., 2012). However, knowing who among those we expect to be the most vulnerable to climate change have a higher respective lower adaptive capacity to climate change and what the relevant determinants for these capacities are provides a basis to find more effective ways for supporting smallholder farmers in the Northern region of Ghana in their attempt to sustain their agricultural production and consequently the basis of their livelihoods and urban centres in the region. Therefore, the adaptive capacity assessments bring to the decision table fundamental information for the development of climate change adaptation policy (Adger et al., 2007, Juhola and Kruse, 2015). Thus, specific assessments focussing on the adaptive capacities of smallholder farmers deliver critical information in relation to key strengths and weaknesses and help to inform policy development and interventions on climate change adaptation.

Against this backdrop, this paper fills a fundamental knowledge gap related to a comprehensive and applicable framework for assessing the adaptive capacity of smallholder farmers in context Sub-saharan Africa. It also applies the framework to the case of the Northern region of Ghana to explore the adaptive capacity of smallholder farmers to climate change and variability.

This paper answers the following research questions:•

How can the adaptive capacity of smallholder farmers in the Northern region of Ghana be characterised?•

What is the capacity level of smallholder farmers in the Northern region of Ghana to adapt to climate change and which are the specific determinants of higher or lower adaptive capacities?

To answer these questions we developed an indicator framework in a deductive and expert-driven way: a heuristic was developed grounded on a systematic review of scientific literature considering both previous approaches assessing generic adaptive capacity, specific adaptive capacity of farmers with particular focus on smallholder farmers as well as approaches focussing particularly on sub-Saharan Africa. Before applying the indicator based assessment to two communities in Northern Ghana, this deductive heuristic has been validated by expert interviews. The outcomes of this study are twofold: first, we developed a sector and region specific index for assessing the adaptive capacity of smallholder farmers in sub-Saharan context; and second, we explored the adaptive capacity of smallholder farmers in two rural communities in Northern Ghana and provide insights in the specific capacities’ determinants and options for capacity building for smallholder farmers.

This paper is composed of six sections. The second section reviews literature on key concepts related to assessing adaptive capacity. The third section looks at the background of the study area and methods employed in collecting and analysing the data. Section four presents the developed Smallholder Farmers’ Adaptive Capacity Index that has been revalidated by expert interviews. Section five includes results from the application of the developed indicator in the study area. The last section discusses the findings of this paper in the light of existing literature and presents a conclusive overview of the paper with recommendations for capacity building and further research.

2. Assessing adaptive capacity

The concept of adaptive capacity has been used differently in varying contexts. One of the most recently used definition in relation to climate change is taken from the Fifth Assessment Report of IPCC which defines it as “The ability of systems, institutions, humans and other organisms to adjust to potential damage, to take advantage of opportunities, or to respond to consequences” (IPCC, 2014. p118). The concept of adaptive capacity is highly used in relation to the vulnerability of socio-ecological systems. Vulnerability in this sense is often conceptualised as being composed of the exposure and sensitivity of a system to external stresses and the adaptive capacity (McCarthy et al., 2001, Adger, 2006, Smit and Wandel, 2006) or the coping capacity of the system to such stresses (Turner et al., 2003). The concepts of ‘adaptive capacity’ and ‘coping capacity’ are respectively used to denote long-term and short-term adjustments (Smit and Wandel, 2006, Gallopín, 2006).

The adaptive capacity of a system is determined by an array of factors which are neither independent nor mutually exclusive but a result of a combination of these factors (McCarthy et al., 2001). However, much of its current determinants are driven from vulnerability research. In the fourth assessment report of the IPCC, Adger et al. (2007) identified two dimensions of what constitutes adaptive capacity, namely, the generic and impact-specific dimensions. While the generic dimension of adaptive capacity looks at the ability of the system to respond to the general climate change stimuli, the impact-specific dimension by its name denotes the ability of the system to respond to a particular climate change stimulus. As a third dimension Schneiderbauer et al. (2013) proposed the sector-specific dimension of adaptive capacity, which is related to the capacity of a particular economic sector within a model region to adapt to the general impacts of climate change.

Generic adaptive capacity of a system is determined by factors that influence the functioning of the system. Some studies have identified economic development, education, technology, knowledge, infrastructure, institutions, equity and social capital as generic determinants of adaptive capacity (Adger et al., 2007, Jones et al., 2010, Kruse et al., 2013). Brooks and Adger (2005) also classify what determines the capacity of socio-ecological systems to adapt based on whether the factors are internal or external to the capacity of the system; these factors are also predetermined by the scale of analysis. Some determinants of adaptive capacity are also scale-specific and at the local level the capacity to undertake adaptation is influenced by factors such as managerial ability; access to financial, technological and information resources; infrastructure; the institutional environment within which adaptations take place; political influence and kinship networks (Smit and Wandel, 2006).

When assessing sector-specific adaptive capacity of smallholder farmers, social capital tends to determine the ability of local farmers to access labour resources. According to Yaro et al. (2015) this is directly linked to the farmers’ capacity to cope or adapt to climate change stresses. In relation to farmers at the local level, Asante et al. (2009) and Nakuja et al. (2012) assessed their adaptive capacities by using attributes such as knowledge, use, availability, accessibility and consultation. According to Defiesta and Rapera (2014) indicators used in recent times are largely based on the Sustainable Livelihood Framework which comprises five assets categories – human, social, natural, physical and financial capital – from which livelihoods of people are built (Serrat, 2010).

Adaptive capacity at various contexts and spatial scales is assessed using the indicators of its determinants. Some of the indicators used in assessing adaptive capacity are regional, local or sector-specific. Therefore, the construction and replication of such indicators in other spatial contexts is critical and needs to be adjusted to the specific spatial and societal context (Wall and Marzall, 2006). Therefore, to develop an indicator-based assessment of the adaptive capacity of smallholder farmers in the Northern Region of Ghana, this study developed a sector and region-specific assessment designed with indicators adjusted for small-scale agriculture in Sub-Saharan Africa taking into account the regional, socio-economic and cultural context of the Northern Region of Ghana. It also calculated adaptive capacity using a composite index approach which has been applied in previous adaptive capacity assessments at the local level (Defiesta and Rapera, 2014; Nelson et al., 2010; Cuesta and Rañola, 2009).

3. Materials and methods

3.1. The study area

The Northern region of Ghana, which is the largest administrative region in Ghana in terms of land mass, occupies an area of 70,384 km2. With an aggregate population of almost 2.5 million inhabitants, the region is comprised of 26 districts (Ghana Statistical Service, 2013). It is located in the Guinea Savannah ecological zone of Ghana which is largely characterised by a stretch of lowland and grassland. The region has a relatively dry climate characterised by a single rainy season that begins in May and ends in October with an annual rainfall that ranges between 750 mm and 1050 mm (Ghana Statistical Service, 2013). The annual mean temperature ranges between 22.4 °C and 33.9 °C (Acheampong et al., 2014). The region is characterised by a prolonged dry season between November and March/April.

Climate change and its impacts, such as recurring floods, drought and frequent bush fires are common in the Northern region of Ghana (Darko and Atazona, 2013, Asante and Amuakwa-Mensah, 2014). Over the period between 1960 and 2010, the observed rise in minimum temperature in the northern Savannah ecological zones of Ghana was estimated at 3.7%. Over the same period, a decrease of 120 mm in annual mean precipitation was also observed in the Guinea Savannah ecological zone in which the Northern Region is located (Environmental Protection Agency, 2015). The region is said to be one of the highly vulnerable regions to climate change in Ghana, both ecologically and socially, and the vulnerability is intensified by other biophysical and human-related issues in the region such as deforestation, overgrazing and human-induced bush fires (Stanturf et al., 2011).

Agriculture is the main economic activity of the Northern Region and it is done mostly on subsistent basis. The agricultural sector, which is predominantly rain-fed, employs about 74% of the working population in the region (Ghana Statistical Service, 2013). For our research question, we chose West Mamprusi district because, according to Stanturf et al. (2011), it is one of the most socially vulnerable districts to climate change in the Northern Region of Ghana. According to the Ghana Statistical Service (2013), agriculture employs 78% of the working population of the district which is similar to the overall region’s average of 74%.

With a population of about 120,000 inhabitants, the West Mamprusi district is one of the 26 districts in the Northern Region of Ghana. About 63% of the population in the district live in rural areas and 85.5% of households depend on agriculture as main economic activity (Ghana Statistical Service, 2013). Crop production, which is largely rainfall dependent, dominates other forms of agricultural production. Hjelm and Dasori (2013) reports that, 99.1% of farming households in the district depend on rain-fed agriculture.

3.2. Research methods

3.2.1. Data collection

For developing a sectoral and regionally specific indicator based framework for assessing the adaptive capacity of smallholder farmers and for its application in West Mamprusi, data was gathered from both secondary and primary sources. Grounded on a systematic review of scientific literature, a heuristic framework of determinants and related indicators for assessing the adaptive capacity of smallholder farmers was developed.

The systematic literature review was realized using ‘Web of Knowledge’ and ‘Google Scholar’ to explore available research from 1990 to 2015 using the search strings “TITLE: (adaptive capacity) AND TOPIC: (smallholder farmers OR agriculture OR smallholders OR farming OR farmers)” and “allintitle: “adaptive capacity AND smallholder farmers OR farmers OR smallholders OR agriculture OR farming”. Combining the two search engines enhanced the inclusion of both indexed and grey literature. The inclusion criteria was based on relevance and study cases with socioeconomic and political conditions similar to Ghana. The number of articles reviewed was 51 comprising 23 out of 63 articles from ‘Google scholar’ and 28 out of 51 articles from web of Knowledge.

The primary data on the other hand, was obtained in two consecutive phases of data collection. The first phase involved a determinants ranking and indicator selection process. Expert interviews were used in ranking the determinants of adaptive capacity and selecting their respective indicators. Through a thorough review of the websites of the Agriculture and Food Ministry of Ghana, and projects and initiatives geared towards agriculture, food security and climate change in the study region, ten experts were identified. Six of the experts were successfully contacted and interviewed through mobile phone using a semi-structured interview guide between August and September 2015 (see Appendix A for profiles of interviewees). The ranking exercise involved the use of pen and a piece of paper by an interviewee to arrange and score the determinants in order of importance to the adaptive capacity of smallholder farmers (c.f. Section 4.2). The results from the interviews were then used to finalise the Smallholder Farmers’ Adaptive Capacity Framework.

For the application of the framework in West Mamprusi in the second phase of the research, a structured questionnaire was developed based on the indicators selected from the expert interviews. The survey questionnaire was then administered to smallholder farmers between September and October 2015 to solicit primary data from the study region. For the survey, two agrarian communities Bugiya Pala (population: 1663, No. of households: 174) and Zangum (population 2191, No. of households 234) were purposefully selected from the district based on the fact that they have similar physical, socio-economic and political characteristics (Ghana Statistical Service, 2014; cf. Fig. 1). These communities had not been piloted for any climate change adaptation project at the time of the study. This sampling criterion ensures that data acquired from the field are relatively free from the impacts of capacity development projects.

THE ADAPTIVE CAPACITY OF SMALLHOLDER FARMERS TO CLIMATE CHANGE IN THE NORTHERN REGION OF GHANA