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The Vietnamese Mekong Delta is comprised of deposited alluvium from the Mekong River. Based on favorable conditions of soil, climate, and hydrology, farmers have developed this region as an area specializing in food crops. In particular, rice is a major crop, and its cultivation is the main livelihood of millions of farmers.
AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 ASSESSMENT OF RICE FARMERS’ ADAPTIVE CAPACITY TO ENVIRONMENTAL CHANGE IN AN GIANG PROVINCE Duong Truong Phuc1 University of Social Sciences and Humanities, VNU - HCM Information: Received: 29/09/2018 Accepted: 06/12/2018 Published: 11/2019 Keywords: Adaptation, Rice Farmer, Livelihood, Climate Change, Vulnerability ABSTRACT The Vietnamese Mekong Delta is comprised of deposited alluvium from the Mekong River Based on favorable conditions of soil, climate, and hydrology, farmers have developed this region as an area specializing in food crops In particular, rice is a major crop, and its cultivation is the main livelihood of millions of farmers It has Vietnam’s highest level of exposure and dependence on natural and socio-economic factors.Simultaniously, the production environment has hosted specific changes due to the interaction between climate change (natural) and human activity (socio-economic), which creates risks that can make agricultural livelihoods vulnerable In this context, the adaptation of farmers' livelihoods has attracted widespread attention This article aims to assess the adaptive capacity of farmers through an adaptive capacity index using a case study in An Giang province The results showed that farmers are unable to diversify their income as well as to adapt to changes Consequently, they are vulnerable to external shocks On this basis, the article proposes some solutions to improve adaptive capacity, which is "enhancing livelihood asset" and multifunctional agricultural transformation Klein, & Wandel, 2000; Smit & Pilifosova, 2003) INTRODUCTION Adaptation is essential to external environmental change (Adger et al., 2009) The term derives from natural science, especially evolutionary biology, through Charles Darwin's studies of natural evolution and selection (Smit & Wandel, 2006) In the context of environmental change, adaptation is the behavioral modification of groups and organizations to reduce vulnerability to climate change (Pielke, 1998) or the adjustment of socio-ecological responses to climate stimuli and effects (Adger et al., 2009; Smit, Burton, Agricultural production is the primary source of income for most rural communities Consequently, adapting to the adverse effects of environmental change is necessary to stabilizing livelihoods and ensuring food security (Bryan, Deressa, Gbetibouo, & Ringler, 2009) Agricultural adaptation to climate/environmental change is a complex and multi-dimensional process (Bryant et al., 2000), involving a wide range of stakeholders, including policymakers, extension agents, non- 85 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 governmental organizations, researchers, and local communities (Bryan et al., 2009) livelihood The level of vulnerability depends in part on the adaptability of farmers through access to and ownership of livelihood assets that support livelihood strategies Therefore, the understanding and assessment of the status of household livelihood assets are necessary for the context of many changes in the production environment From there, some strategies for improving livelihoods have been proposed, with implications for farmers to reduce vulnerability and poverty There are many measures to adapt to climate change in agriculture (Bradshaw, Dolan, & Smit, 2004; Kurukulasuriya & Mendelsohn, 2008; Mertz, Mbow, Reenberg, & Diouf, 2009) and various factors affecting the use of any adaptation measures (Deressa, Hassan, Ringler, Alemu, & Yesuf, 2009) Some research suggests that individual characteristics affect adaptation, while others suggest that production experience, access to information, credit, and agricultural extension services strengthen the ability to apply adaptive measures (Maddison, 2007; Nhemachena & Hassan, 2007) METHOD The paper is based on i) Secondary data studies on farmer’s livelihood and livelihood adaptation; ii) Primary data from a survey of 240 rice farmers in Tri Ton, An Giang on the status of livelihood assets and awareness of flood and drought Also, in order to quantify access to livelihood assets in support of adaptive strategies, the paper also provides an index to measure it adapt to (Hahn, Riederer, & Foster, 2009) through several steps as follows: An Giang farmers choose rice as the main crop for their agricultural livelihood from the time of reclamation as a behavior due to a natural environment with a favorable climate, hydrology, and soil However, under the impact of climate change and human activities, the production environment has provided many adverse changes for farmers Besides, commodity-oriented farmers need to ensure livelihood security and survival levels have led to market risks Step 1: Overviewing of rice cultivation livelihood research for the selection of indicators Step 2: Classifying the selected indicators into five types of livelihood assets For environmentally sensitive livelihoods such as rice cultivation, changes in flood and drought levels create risks that could lead to vulnerable Step 3: Weighting for each criterion of an indicator as follows: Table Weight for Criteria Serial First Second Third Weight 0.33 0.67 1.00 Step 4: Providing a set of official Indicators: Table The Indicator of Measuring Livelihood Assets Capital Human Capital (H) Indicator Education Criteria Weight Lowest through primary school 0.33 Secondary school 0.67 High school through highest 1.00 86 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 Capital Indicator Criteria Weight Frequently get disease 0.33 Sometimes get disease 0.67 Not get disease 1.00 5 people 1.00 Based on experience 0.33 Apply science and technology 0.67 Combination of both 1.00 Never 0.33 Sometimes (=3 times/year) 1.00 Never Weather and pest information Sometimes (=3 times/year) 0.33 Health Household size Farming method Agricultural training 0.33 Sometimes (=3 times/year) 1.00 Never 0.33 Sometimes (=3 times/year) 1.00 Never 0.33 Sometimes (=3 times/year) 1.00 Never Local government's Sometimes (=3 times/year) 0.33 Neighbors’ support Relationship’s support (S) 1.00 Never Market information update Social Capital 0.67 Local government's support Never life Sometimes (=3 times/year) Agricultural center’s support extensionNever Sometimes (=3 times/year) 1.00 Underfunding 0.33 Little, need other loans 0.67 Much, no need other loans 1.00 Not loan 0.33 Loan from friends, neighbors Low-interest rate loan 0.67 No need 1.00 Not loan 0.33 Loan 0.67 No need 1.00 Not loan Non-official loan (blackLoan market, trade credit ) No need 0.33 Official loan Financial Capital (bank, credit fund ) (F) Only rice cultivation Income 0.67 1.00 0.33 More income than rice cultivation (=2 1.00 livelihoods) Housing Running water Physical Capital (P) Traffic vehicle Means of production Traffic road Temporary 0.33 Semi-durable 0.67 Durable 1.00 River-water, well-water 0.33 Rain-water 0.67 Tap-water 1.00 Bicycle 0.33 Bicycle, motorcycle 0.67 Bicycle, motorcycle, car 1.00 Rent 0.33 Work exchange 0.67 Own 1.00 Dirt road 0.33 Gravel road 0.67 Asphalt road 1.00 88 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 Capital Indicator Rice variety Land area Land quality Natural Capital (N) Water supply Water quality Criteria Weight Not access 0.33 Access, little diversity 0.67 Access, diversity 1.00 Small (0,0ha≤S≤0,9ha) 0.33 Average (1,0ha≤S≤1,9ha) 0.67 Large (2,0ha≤S≤3,0ha) 1.00 Bad (Alkaline) 0.33 Average (Conditioning) 0.67 Good (Alluvium) 1.00 Shortage 0.33 Full 0.67 Copious 1.00 Bad (Pollution beyond standards) 0.33 Average (Simple process) 0.67 Good (Direct use) 1.00 Step 5: Setting the Calculated Formula Table The Calculated Formula Human capital H = (Wi1+…+Wi7)/7 Social capital S = (Wi1+…+Wi5)/5 Financial capital F = (Wi1+…+Wi5)/5 Physical capital P = (Wi1+…+Wi6)/6 Natural capital N = (Wi1+…+Wi4)/4 Adaptive Capacity Index ACI= (H+S+F+P+N)/5 Calculated results are divided into three levels Table Classifying the Calculated Result Level Low Moderate High Value 0.00-0.49 0.50-0.69 0.70-1.00 RESULTS AND DISCUSSIONS prerequisite for adaptation (Nelson, Adger, & Brown, 2007) This process requires an understanding of the farmer's perceptions of environmental change, internal and external Farmer household adaptability assessment is the process that corresponds to vulnerability assessment and is considered a base-line 89 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 resources, the ability to combine these resources, and some factors affecting the adaptive capacity Such as assessing the adaptability of rice farmers based on i) perceptions of environmental change (flood and drought); and sustainable access to livelihood assets such as human capital, social capital, financial capital, physical capital, and natural capital Floods bring a large amount of sediment to improve the fertility of the soil and clean the fields They also create income for people through fishing and tourism services (Đào Cơng Tiến, 2001; Nguyễn Thế Bình, 2011) However, construction works such as closed dikes and hydro-electric dams have reduced their benefits, causing a significant impact on production The monitoring results from the MODIS satellite image show that the period 2009-2015 saw a severe decline in the flooded areas in An Giang province, especially in the research-targeted areas such as Tri Ton (Fig 1) 3.1 Farmers’ Perceptions of Environmental Change 3.1.1 Floods Floods are a natural phenomenon occurring from July to November in An Giang province Figure Distribution of Flooded Area in An Giang province During 2009-2015 Source: (Phạm Duy Tiễn, 2016) In Tri Ton, the percentage of farmers who think that the flood level has decreased significantly compared to previous floods accounted for 87.31% while only 49.46% think flood level decrease had an impact on rice cultivation Thus, although farmers perceive that flooding decreases, they not think that the change has affected production (Table 5) Table Perceptions of farmers about flood change Impact Perception No (%) Yes (%) Total (%) More decrease 49.46 37.85 87.31 Less decrease 4.48 4.42 8.90 Unchanged 0.95 2.85 3.80 Total 54.89 45.12 100.00 Source: Survey data in May 2017 90 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 3.1.2 Droughts monitoring results from the period 2010-2015 showed an expanded tendency in drought areas, especially semi-mountainous areas such as Tinh Bien-Tri Ton (Fig 2) Droughts can occur year-round in the Mekong Delta, mainly meteorological droughts However, climate change has increased the area, intensity, and frequency of droughts The Figure Distribution of Drought Areas in An Giang During 2010-2015 Source: (NRED, 2016) the notion of possible risks affecting rice yields and postharvest consumption resulting in adaptive measures to mitigate losses such as the transfer of crop plants, the storage of production water, and a reduction of chemical fertilizer use However, in the study area, 58.33% of farmers agreed that the production environment had changed but had not yet taken adaptive measures (Table 7) Based on production experience, most of the respondents said that drought had increased over the previous period (87.46%) and had a negative impact on production (62.11%) (Table 6) Local farmers are relatively well aware of environmental changes, agreeing that there has been decreasing flood and increasing drought activity Based on that perception, farmers form Table Perceptions of Farmers About Drought Change Impact Yes (%) No (%) Total (%) Increase 62.11 25.35 87.46 Unchanged 3.97 3.77 7.74 Decrease 1.80 3.00 4.80 Total 67.88 32.12 100.00 Perception Source: Survey data in May 2017 Table Farmers' Perceptions of the Implementation of Adaptation Measures Perception Adaptive measures 91 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 Proceed (%) Not proceed (%) Total (%) Yes (%) 36.88 58.33 95.21 No (%) 1.66 3.13 4.79 Total (%) 38.54 61.46 100.00 Source: Survey data in May 2017 Therefore, although farmers may have access to the information on environmental change through the media and have agreed in theory, very few farmers have taken adaptive measures to mitigate their livelihood risks achieve the desired livelihood outcomes (DFID, 1999) Evaluation of human capital is based on indicators such as education, health, household size, farming techniques, and access to information From the calculation results, the human capital in the study area was moderate (H = 0.52) Among them, the lowest was householder’s education (0.25), and the highest was householder’s health (0.64) In general, there were 59.17% of farmers with low human capital and 36.83% of them with moderate human capital (Table 8) 3.2 Farmers’ Access to Livelihood Assets 3.2.1 Human Capital The first livelihood asset which affects farmer household livelihood outcome is human capital This is a significant asset within a farmer's internal resources; a resource which effectively governs the use of the remaining assets to Table The Status of Human Capital Level Percentage (%) Low 59.17 Moderate 36.83 High 4.00 Total 100.00 Source: Survey data in May 2017 3.2.2 Social Capital their friends and neighbors, as well as government and social organizations Locally, the results showed that social capital was low (S = 0.45) In particular, the local government's support (policy) was lowest (0.37), and the agricultural extension center’s support was highest (0.68) In terms of distribution, 59.17% of farmers had low social capital, 36.04% of them had moderate social capital (Table 9) The second livelihood asset, which affects farmer household livelihood outcomes is social capital This is considered a safety net and compensates for the shortage of other types of capital to ensure livelihoods (DFID, 1999) The assessment of social capital is an examination of the ability of external support to develop the adaptive capacity for the farmer household through aspects such as support among farmers, Table 9.The Status of Social Capital Level Percentage (%) Low 59.17 92 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 Moderate 36.04 High 4.79 Total 100.00 Source: Survey data in May 2017 3.2.3 Financial Capital study area, the results show that financial capital was low (F = 0.39), with the lowest being starting capital (0.30) and the highest being conventional loans (0.67) Also, 63.13% of farmers had low financial capital, and 33.12% of them had moderate financial capital (Table 10) The third livelihood asset, which affects the farmers’ household livelihood outcomes is financial capital This is the most flexible asset and can be converted to the remaining assets (DFID, 1999), evaluating financial capital through ownership and access to capital for production and income diversification In the Table 10 The Status of Financial Capital Level Percentage (%) Low 63.13 Moderate 33.12 High 3.75 Total 100.00 Source: Survey data in May 2017 3.2.4 Physical Capital water, vehicles, production means, and roadways The fourth livelihood asset, which affects the farmers’ household livelihood outcome is physical capital This is an asset that enhances farmers' access and connectivity and actively supports livelihood strategies (DFID, 1999) The assessment of physical capital can be made through the consideration of housing, running From the results of the calculation, physical capital was moderate (P = 0.53), of which the lowest value was production means (0.14), and the highest value was housing ( 0.67) Also, in the local residents, 50.92% of farmers had moderate physical capital, and 43.88% of them had low physical capital (Table 11) Table 11 The Status of Physical Capital Level Percentage (%) Low 43.88 Moderate 50.92 High 5.21 Total 100.00 Source: Survey data in May 2017 93 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 production From the calculation results, the natural capital in the study area was low (N = 0.48), in which the lowest value was the land area (0.32) and the highest value was water quality (0.67) According to the results from Table 12, 54.58% of farmers had low natural capital, and 43.13% of them had moderate natural capital 3.2.5 Natural Capital The final livelihood asset, which affects the farmers’ household livelihood outcome is natural capital This is an essential input source for agricultural livelihood, not only in regards to ownership but also exposure (DFID, 1999) The assessment of natural capital can be made through area and quality of cultivated land, supply, and quality water sources for Table 12 The Status of Natural Capital Level Percentage (%) Low 54.58 Moderate 43.13 High 2.29 Total 100.00 Source: Survey data in May 2017 capital (P = 0.53) (Fig 3) In future, as production risks increase, farmers will not improve their livelihood assets; their adaptive capacity will decline, and their livelihoods will be compromised, leading to lower incomes and a rising risk of poverty Through the process of understanding and assessing the status of livelihood assets of rice farmers in the Tri Ton district, An Giang province, most of the livelihood assets are evaluated from low to moderate, lowest financial capital (F = 0.41) and highest physical Figure The Status of Farmers’ Household Livelihood Assets Source: Survey data in May 2017 94 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 3.3 Assessment of Farmers’ Adaptive Capacity Household assessment of livelihood assets combined with farmers' perceptions of changes in floods and droughts The results show that the adaptive capacity of the area is generally low (ACI = 0.47) (Table 13) The assessment of the adaptability of rice farmers based on the adaptive capacity index was synthesized from the results of the Table 13 The Result of Adaptive Capacity in the Study Area Livelihood assets Value Human capital H 0.52 Social capital S 0.47 Financial capital F 0.41 Physical capital P 0.53 Natural capital N 0.45 Adaptive Capacity Index ACI 0.47 Source: Survey data in May 2017 Concerning distribution, 95.87% of households have low to moderate adaptive capacity, and only 4.13% of farmers are highly adaptable to the risks of environmental change (Table 14) In the future, when the risks and environmental risks increase If the adaptive capacity of farmers is not improved, the level of livelihoods will be increased Table 14 The Status of Adaptive Capacity Adaptive capacity Percentage (%) Low 64.81 Moderate 31.06 High 4.13 Total 100.00 Source: Survey data in May 2017 CONCLUSIONS RECOMMENDATIONS AND adaptive measures Besides, the status of household livelihood assets in the study area is low to moderate, so the adaptive capacity of households is not high In the future , when the risks from environmental change crease, farmers will need to strengthen their adaptive capacity Based on the survey results, this paper proposes some measures which can support adaptation for farmers as strengthening the livelihood assets and encouraging multifunctional agricultural transformation In order to assess the adaptability of rice farmers in An Giang province it is essential to understand their perceptions of changes in the production environment, their intent to implement adaptation measures and the status of livelihood assets which can support livelihood strategies Research results showed that although farmers perceive the production environment as having many changes and adverse effects few households implement 95 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 For strengthening access to livelihood assets, the paper deals with i) enhancing access to information (farmers should actively refer to the information from media, agricultural training, agricultural conference, agricultural extension officers, and local governments); ii) expanding social networks (farmers should maintain relationships with other farmers, especially good farmers, build relationships with rice traders, regularly attend agricultural training sessions, and discuss issues related to rice production with agricultural extension officers); iii) diversifying incomes (farmers should select suitable varieties and apply science-technology to increasing productivity, diversifying income by expanding their skillsets (agriculture + non-agriculture), decreasing production costs maximal, saving the production cost, selecting preferential loans, (low-interest rates); and accumulating land (farmers should borrow more money to buy or rent more land) collaborating with neighboring farmers to expand production areas, preparing appropriate administrative procedures to streamline land accumulation is not obstructed) adaptation to climate change? Climatic Change, 93(3–4), 335–354 Bradshaw, B., Dolan, H., & Smit, B (2004) Farm-level adaptation to climatic variability and change: crop diversification in the Canadian prairies Climate Change, 67(1), 119–141 Bryan, E., Deressa, T T., Gbetibouo, G A., & Ringler, C (2009) Adaptation to Climate Change in Ethiopia and South Africa: Options and constraints Environmental Science & Policy, 12(4), 413–426 Bryant, C R., Smit, B., Brklacich, M., Johnston, T R., Smithers, J., Chiotti, Q., & Singh, B (2000) Adaptation in Canadian agriculture to climatic variability and change Climate Change, 45(1), 181–201 Dao Cong Tien (2001) Natural conditions, resources and biodiversity of flooded areas In The Flooded area of Mekong Delta: Situation and Solutions (pp 58–68) HCM City: Ho Chi Minh City National Publishing House Deressa, T T., Hassan, R M., Ringler, C., Alemu, T., & Yesuf, M (2009) Determinants of Farmers’ Choice of Adaptation methods to Climate Change in the Nile Basin of Ethiopia Global Environmental Change, 19(2), 248–255 Multifunctional agriculture is becoming increasingly popular in developing countries Encouraging multifunctional agricultural transformation in rural areas not only produces food and fiber but also forms a range of social benefits The core of multifunctional agriculture is geared toward appropriate land use at multifunctional levels such as strong, moderate, and weak In some vulnerable areas, such as rural settings multifunctional agriculture is often chosen to reduce dependence on high productivity, diversify products, and absorb additional tourism functions that are necessary to mitigate environmental risks DFID (1999) Sustainable Livelihoods Guidance Sheets 1.1 London, UK: Department for International Development (DFID) Hahn, M B., Riederer, A M., & Foster, S O (2009) The Livelihood Vulnerability Index: A pragmatic approach to assessing risks from climate variability and change-A case study in Mozambique Global Environmental Change, 19(1), 74–88 REFERENCES Adger, W N., Dessai, S., Goulden, M., Hulme, M., Lorenzoni, I., Nelson, R., … Wreford, A (2009) Are there social limits to Kurukulasuriya, P., & Mendelsohn, R (2008) A Ricardian Analysis of the Impact of 96 AGU International Journal of Sciences – 2019, Vol (1), 85 – 97 Climate Change on African Cropland African Journal of Agricultural and Resource Economics, 2(1), 1–23 Policy Research Washington, DC Institute (IFPRI), NRED (2016) Zoning drought in An Giang for the period 2010-2015 Department of Natural Resources and Environment of An Giang Maddison, D (2007) The Perception of and Adaptation to Climate Change in Africa World Bank Policy Research, Working Paper 4308, World Bank, Washington D.C Pham Duy Tien (2016) Application of MODIS satellite images to monitor flood changes in An Giang province (from 2000 to 2013) and to create flood maps in 2013 An Giang University Science Review, 12 (4D), 72–80 Mertz, O., Mbow, C., Reenberg, A., & Diouf, A (2009) Farmers’ perceptions of climate change and agricultural adaptation strategies in rural Sahel Environmental Management, 43(5), 804–816 Pielke, R A (1998) Rethinking the role of adaptation in climate policy Global Environmental Change, 8(2), 159–170 Nelson, R., Adger, W N., & Brown, K (2007) Adaptation to environmental change: Contributions of a resilience framework Annual Review of Environment and Resources, 32, 395–419 Smit, B., Burton, I., Klein, R J T., & Wandel, J (2000) An anatomy of adaptation to climate change and variability Climatic Change, 45(1), 223–251 Nguyen The Binh (2011) Agriculture in the Mekong Delta, the situation, opportunities and challenges in the context of integration Scientific basis for regional development in the context of international integration of Vietnam (pp 223–235) Hanoi: World Publishing House Smit, B., & Pilifosova, O (2003) Adaptation to climate change in the context of sustainable development and equity Sustainable Development, 8(9), 1–9 Smit, B., & Wandel, J (2006) Adaptation, adaptive capacity and vulnerability Global Environmental Change, 16(3), 282–292 Nhemachena, C., & Hassan, R M (2007) Micro-level analysis of farmers’ adaptation to climate change in Southern Africa IFPRI Discussion Paper, 714 International Food 97 ... occurring from July to November in An Giang province Figure Distribution of Flooded Area in An Giang province During 2009-2015 Source: (Phạm Duy Tiễn, 2016) In Tri Ton, the percentage of farmers... incomes and a rising risk of poverty Through the process of understanding and assessing the status of livelihood assets of rice farmers in the Tri Ton district, An Giang province, most of the... encouraging multifunctional agricultural transformation In order to assess the adaptability of rice farmers in An Giang province it is essential to understand their perceptions of changes in the