Economics and other knowledge of the adaptation component of CSA

As adaptation is a highly contextual and multi-dimensional concept, this section presents literature related to not only the economics of adaptation to CC, but also local knowledge related to it. The latter will be discussed first to lay out the need of multiple approaches for dealing with adaptation in this research. This also reflects the logical framework in a large body of literature on adaptation to CC that captures indigenous knowledge at the first stage in order to better understand communities’ experience with CC-associated risks and their responsive measures.

Taking this as a foundation, scientific knowledge can firmly go further.

Local knowledge

Although climate variability is a global phenomenon, its impact is local with more vulnerability posed to developing countries. As a result, farmers and rural communities are likely suffer the most from and bear the costs of CC (Adger et al., 2003; Kibue et al., 2016). Understanding locally embedded knowledge about climate extremes and variability is crucial to build both short-and long-term resilience capacity. Recognizing this vital role, the Fourth Assessment Report of IPCC also acknowledges that traditional knowledge and past experience can support capacity building for CC adaptation and resilience (IPCC, 2007b).

Local knowledge, interchangeably known as indigenous knowledge or traditional knowledge, is acquired, accumulated and shared by communities and societies over generations. The knowledge is an outcome from interactions between local people and their external environment based in a set of technologies, skills and beliefs which are practiced in various livelihood activities such as agriculture and natural resource management (Kasali, 2011). Since the knowledge is closely connected to local biophysical features and social systems, it will be helpful for setting an effective adaptation strategy in which scientific knowledge is not always sufficient (Lebel, 2013).

In this sense, integration of farmers’ perception into adaptation studies has been growing considerably worldwide, particular in Africa. However, there has not been much systematic exploration in Asia or Southeast Asia, where EWEs and seasonal monsoon variability are key climate factors (Dang et al., 2014; Francisco, 2008; IPCC, 2007b; Lebel, 2013). Exploring

farmers’ perception about climate variability and potential barriers is key for adaptation to CC because this is the initial step for a success adaptation process (Deressa et al., 2009; Kibue et al., 2016). Local farmers often interpret changes through past experience or repeated observation of changes and immediate biophysical impacts to farm activities. Farmers’ experience with the reactions of plants and livestock to climate extremes could be used as biophysical indicators to anticipate extreme weather, changes in season or variety selection (Lebel, 2013). The viability and utility value of local knowledge could be improved when it is integrated with scientific knowledge (Kasali, 2011).

In light of this literature, Dang et al. (2014) have employed focus group discussions (FGD) and in-depth interviews in exploring farmers’ perceptions about climate variability and barriers to adaption in the Mekong River Delta in Viet Nam. The combined analysis of local perceptions with meteorological data has revealed that both farmers, agricultural officers and climate data have basically presented a consistent trend of local CC. Farmers’ perceptions about CC have been shaped by the most recent and direct experiences with climate extremes. They also stressed that psychological factors are also the key barriers, besides resource and socio-economic factors, to adaptation, and thus those factors should be carefully considered in preparing a successful adaptation policy.

Similarly, these approaches have also been used in many other regions to capture farmers’

perception on changes in rainfall and temperature and their responsive measures, or influencing factors to such changes. Studies on such topics have taken place in states of Maharashtra and Andhra Pradesh, India (Banerjee, 2015), Anhui and Jiangsu regions, China (Kibue et al., 2016), Ha Tinh Province, Viet Nam (Hoang et al., 2014), Pailin and Samlout regions, Northwest Cambodia (Touch et al., 2016), and in Nandi and Keiyo Districts, Kenya (Songok et al., 2011).

They share common findings and most of them reaffirm that what farmers perceived about climate variability are often consistent with weather records. Indigenous knowledge is viable to develop an adaptation strategy at the initial stage. However, hybridizing local with scientific knowledge is highly recommended for improving the robustness of adaptation to CC in the long run, where only local knowledge is insufficient (Kasali, 2011).

Diversification

The basic theories in economics suggest that diversification is one of the most fundamental strategies to maximize one’s utility in the face of risk and imperfect information. Diversification

is a potential pathway in building HH, village, landscape and national adapting capabilities to CC (Arslan et al., 2017). At the HH level, adoption of diversification leads to better management of risk as well as adjustment to smooth consumption aftermath. The empirical evidence also suggests that more diversified HHs have higher incomes and greater consumption per capita.

Diversification can be driven by push and/or pull factors. While push factors often refer to the presence of high transaction costs and adverse shocks or the absence of perfect credit and insurance markets, pull factors depend on the attractiveness of non-farm income or availability of new technologies in the farm sector (Reardon, 1997).

Diversification can be measured either by simple count indices such as farm activity count (Jones et al., 2014), HH income portfolios (Lay et al., 2009) or complex indices e.g. accounting for evenness and/or abundance (Smale, 2006). Arslan et al. (2017) use the Gini-Simpson index to analyze various dimensions of crop, livestock and income diversification in Zambian rural HHs under increased rainfall variability and shocks. Their evidence shows that diversification in crop and livestock have increased incomes and in the same time, decreased rural poverty. Therefore, this type of diversification has been demonstrated as a potential CSA strategy in responding to CC. The long run rainfall variation is a push factor for crop, livestock and income diversification.

Similarly, enterprise mix diversification are often practiced by HHs in rural economies and farming systems around the world as an effective strategy to mitigate the adverse impact of CC.

Kandulu et al. (2012) have combined Agricultural Production Simulator modeling with Monte Carlo simulation, probability theory, and finance techniques to study the benefits that mix enterprise strategy could provide to Australian rain-fed agriculture. They conclude that diversification has significantly improved the climate-induced variability of long term net returns by reducing the standard deviation by up to A$200 ha^-1, or 52% of means of net returns, and increasing the probability of breaking even by up to 20%. A multinomial discrete choice model has been used to analyze the determinants of farm-level adaptation measures in 11 African countries. The result shows that mono-cropping is the most vulnerable to CC and hence, diversifying into multiple crops, mixed crop-livestock systems, and switching from crops to livestock and from dryland to irrigation is highly encouraged (Hassan and Nhemachena, 2008).

Household resilience

By definition, HH adaptation is built from both capacity to cope with and rebound from shocks.

While shock effects on HH well-being have been paid great attention, recovery from such events

has been discussed occasionally in the literature of vulnerability. Thus, it’s worthwhile to understand the resilient pathways in which HHs could recover from climate extremes. Recently, Tran (2015) has employed the theory on income shocks and resilience paths (Carter et al., 2007) to assess post-shock resilience in 2000 rural HHs in Viet Nam. In his study, climate extreme events such as droughts or cold spells are referred to as agricultural shocks. Once faced by such adverse events, rural poor HHs suffer much more than wealthier ones because they are more dependent on their own resources (e.g. savings, livestock) than on external limited credit or insurance. Wealthier households, who possess higher levels of income and stocks of assets, are therefore able to buffer better and recover quicker from shocks, and follow a smoother consumption than their counterparts.

This review has shown that both of scientific and local knowledge are playing a role in building HH resilience and hence, should be hybridized in studying CSA adaptation. Each branch of this knowledge could supplement the other. In this research, local knowledge will be used to explore farmer’s perceptions. These are then compared with high resolution climate data and HH level data to understand the adaptation potential of tea practices to NMR’s agricultural production systems.

CHAPTER 3. METHODOLOGY