This paper aims to investigate shrimp income losses of farmers in the four farming systems in the research areas of Ca Mau, Vietnam, and determine the vulnerability of shrimp farming income to climate change events.
Field research interviews were conducted with 100 randomly selected households across the four farming systems to access shrimp income status and vulnerability levels to climate change events. Four focus groups, each aligned to a particular farming system, were surveyed to categorise likelihood and consequences of climate change effects based on a risk matrix worksheet to derive levels of risk, adaptive capacity and vulnerability levels.
Shrimp farmers in the study areas have been facing shrimp income reduction recently and shrimp farming income is vulnerable to climate change events. There are some differences between farmers’ perspectives on vulnerability levels, but some linkages are evident among shrimp farmer characteristics, ramifications for each farming system, shrimp income losses and shrimp farmers’ perspectives on vulnerability levels of shrimp incomes. From an income perspective, farmers operating in intensive shrimp farming systems appear to be less vulnerable to existing and expected climate change effects relative to those in mixed production or lower density systems.
Having identified the vulnerability level of shrimp farming income to climate change events in different farming systems based on shrimp farmers’ perspectives, the paper adds new knowledge to existing research on vulnerability of the aquaculture sector to climate change. The research findings have implications for policymakers who may choose to encourage intensive shrimp farming to enhance shrimp farmer resilience to the effects of climate change as well as improving cultivation techniques for shrimp farmers. The findings could thus guide local government decision-making on climate change responses and residents of Ca Mau as well as within the wider Mekong Delta in developing suitable practical adaption measures.
1. Introduction
With the largest shrimp farming area in Vietnam (Ca Mau Statistic Office, 2011), shrimp production in Ca Mau has become a vital component of the province’s economy (SIWRP, 2008) and the major income source for shrimp farmers themselves (Hung, 2012). However, Ca Mau has been recognised as the most vulnerable province in Vietnam to possible damage by climate change (Actionaid and CRES, 2010). Climate change events are increasing and exacerbating pressure on shrimp production (DONRE, 2011) and directly affecting shrimp farmer income in the region.
A range of climate change effects are occurring with adverse effects being experienced by Ca Mau shrimp farmers (Quach et al., 2015) Farmers are particularly vulnerable to increasing intensity and frequency of extreme weather events (Oxfam, 2008). High temperature and irregular weathers cause massive losses for shrimp production (NACA, 2011). Shrimp farmers have been adapting to adverse effects of these bad weather events. However, there is an income cost associated with adaptation measures whereby shrimp farmers generate less profit and with critical affects on their income (RIA2, 2014).
This paper explores shrimp farming income status and the vulnerability to climate change events in terms of farmers’ perspectives. The study mainly concentrated on farmers involved in four farming systems: rice-shrimp rotation (RSRF), integrated shrimp-mangrove shrimp (ISMF), separated shrimp-mangrove (SSMF) and intensive shrimp farming (ISF). The research results give a better understanding of shrimp income status of farmers and their vulnerability to climate change events. This knowledge could help local governments and inhabitants to gain a better sense of the measures needed for adaptation to climate change to sustain shrimp production.
2. Review of aquaculture and shrimp farming vulnerability to climate change events
Based on the definition of climate change vulnerability of IPCC (2007), Allison et al. (2009) developed the notion of aquaculture vulnerability and a number of studies since then have focused on this. Aquaculture vulnerability to climate change in developing countries may increase (De Silva and Soto, 2009) with Vietnam being one of the most vulnerable nations in this regard. Spatial assessment identified climate change vulnerability at the local level (Anh et al., 2012) and a district-based assessment by Hung (2012) displayed the vulnerability of important sectors. The Ca Mau farming sector overall is ranked at a high-risk level to climate change and the aquaculture sector is expected to be impacted most heavily (SIWRP, 2008).
Shrimp farming systems are often associated with coastal areas where shrimp farmers have already perceived the impacts of climate change (Halder et al., 2012). Vulnerability to climate change is also intimately linked to poverty (Chaudhry and Ruysschaert, 2007). While local inhabitants are particularly at risk and more vulnerable to climate change (Oxfam, 2008), they simultaneously are less able to cope with current climate variability (Huxtable and Yen, 2009) and are expected to suffer greatly from adverse impacts of climate change in the future (Tuan and Hong, 2012). To date, most impacts have been identified as extreme climate events, sea level rise, temperature increase and rainfall change (de Silva and Soto, 2009). These are addressed briefly in turn.
Firstly, the frequency of extreme weather events has increased dramatically over the past five decades (IPCC, 2007) with increasing of frequency and intensity hitting Vietnam (MONRE, 2009; Tan, 2010), trending to move to the Vietnam southern coast (Tan, 2010) and posing a serious threat to Ca Mau Province (NEDECO, 2003). For example, Typhoon Linda which struck Ca Mau in 1997 caused thousands of people loss and destroyed more than 200,000 homes. Extreme climate events will lead to aquaculture productivity reduction and have serious consequences for the local economy.
Secondly, sea levels in Vietnam have risen by 20 cm during the past 50 years (MONRE, 2009), and the experience of local inhabitants with this issue has been noted by Actionaid and CRES (2010). Sea levels are expected to rise 28-33 cm by 2050 and 65-100 cm by the end of this century (IMHEM, 2010). Impacts of this issue could include damage and loss of ponds because of increased coastal erosion, loss of suitable land area and rising feed costs (Smyle and Cooke, 2011).
Thirdly, average air temperature in Ca Mau has increased by 1°C over the past 40 years with greatest increase in recent years (DONRE, 2011). IMHEN (2010) estimated that air temperature will increase up to 0.7°C in 2030, 1.4°C in 2050 and 2.6°C by the end of this century. An increase of the air temperature will correspondingly result in increased water temperature (Hammond and Pryce, 2007). Adverse impacts of increased water temperature would become more severe (de Silva and Soto, 2009): exacerbating the occurrence of algal blooms (Najjar et al., 2010), releasing toxin, reducing dissolved oxygen concentrations and threatening fish health and growth (WFC, 2009). As a result, high water temperature may increase shrimp disease and mortality in larvae production systems (Mackay and Russell, 2011).
Finally, the average annual rainfall in Ca Mau increased by 97 mm during the period of 1972-2007. However, rainfall has shown large fluctuations in the past 15 years, e.g. increased by 45 per cent in 1999 and decreased by 21 per cent in 2004 (DONRE, 2011). Extreme rainfall events would increase by 6 per cent in 2030 and 10 per cent in 2050 (IMHEN, 2010) with a trend of decreases during the dry season and increases in the rainy season (MONRE, 2012). Therefore, the dry seasons will get drier and rainfall in the rainy seasons will be more intense. This will exacerbate flooding and drought conditions (Mackay and Russell, 2011) affecting shrimp farmers’ production.
Shrimp farmers are vulnerable to climate change that would lead to a further reduction of profitability, and as a result, higher cost will be required to invest in shrimp farming production (Kam et al., 2012; Smyle and Cooke, 2011; WB, 2010). Sea level rise, high temperature, irregular weather and too much rain were the most important factors and made the greatest impact on small-scale shrimp farming with the improved extensive shrimp farming (IESF) system (Hai et al., 2011). The adverse effects of climate change on shrimp production have been recognised by Ca Mau farmers in different farming systems. For example, climate change events were perceived to have increased shrimp diseases and negatively affected shrimp productivity in the past 10 years (Quach et al., 2015). More intense or irregular rainfall was ranked by farmers as having the most impact on RSRF, ISMF and ISF, while sea level rise most for SSMF.
Overall, there is evidence of substantial climate change events being experienced in Ca Mau Province. While there is important literature available that discusses negative impacts of climate change events on farming industry and shrimp production, presently there is little understanding of the shrimp farming vulnerability to climate change events. This paper seeks to understand shrimp farming vulnerability as perceived by shrimp farmers, with particular focus on shrimp income vulnerability to climate change events in the four farming systems. The research results could help local government and Ca Mau residents gain a better understanding of how climate change poses a risk to the farming livelihood of shrimp farmers and what adaptation measures might be put in place to reduce these risks and increase resilience to the adverse effects of climate change events.
3. Methodology
3.1 Theoretical concepts
Vulnerability to climate change is a combination of the potential impacts and adaptive capacity (IPCC, 2007). The basic concepts of vulnerability assessment used to develop frameworks for climate change vulnerability, impact and adaptation assessment are well-established (Adger, 1999; Adger et al., 2004; Fussel and Klein, 2006; Fussel, 2007; IPCC, 2007, 2004; Moss et al., 2001; O’Brien and Liechenko, 2000; O’Brien et al., 2004; Turner et al., 2003; Wolf, 2011). Although approaches may vary depending on the specific local context and factors under examination, every assessment needs to consider the key components (Metternicht et al., 2014). Macfadyen and Allison (2009) have clarified definitions of vulnerabilities for aquaculture assessment, and FAO (2013) derived a vulnerability analysis framework for fisheries and aquaculture systems. The World Bank and United Nations Environment Programme (UNEP) developed procedures for economic vulnerability assessment in Vietnam, followed by the comparative vulnerability risk assessment framework based on vulnerability assessment in combination with a risk-based approach for assessing the impacts of climate change and its hazards (ADB, 2013, 2011; Mackay and Russell, 2011). Because of large uncertainties regarding the rate of change, the scale and the distribution of impacts, the adopted risk assessment approach is based on a “risk matrix” to identify the impacts, adaptive capacity, risk and vulnerability associated with climate change (Brundell et al., 2011; Mackay and Russell, 2011).
3.2 Vulnerability assessment
The process of vulnerability[1] assessment of shrimp farming income in this paper is based on the impact risk and the vulnerability matrix approach. The impact risk matrix uses the qualitative measures of likelihood and consequence of climate change impacts to access the risk levels based on the probability of a particular climate outcome (likelihood) multiplied by its consequences. Likelihood and consequence classifications were drawn from the work of Mackay and Russell (2011) using scores and ratings as presented in Tables I and II. Levels of risk[2] derived by combining likelihood and consequence in the impact risk matrix are presented in Figure 1 (Brundell et al., 2011; Mackay and Russell, 2011).
Livelihood category for climate change impacts
| Score | Rating | Recurrent events | Single event |
|---|---|---|---|
| 5 | Almost certain | Could occur several times/year | More likely than not – Probability (P) greater than 50% |
| 4 | Likely | May arise about once per year | As likely as not – 50/50 change |
| 3 | Possible | May arise once in 10 years | Less likely than not but still appreciable – P less than 50% but quite high |
| 2 | Unlikely | May arise once in 10-25 years | Unlikely but not negligible – P low but noticeably greater than 0 |
| 1 | Rare | Unlikely during the next 25 years | Negligible – P very small, close to 0 |
Consequence category for climate change impacts
| Score | Rating | Profitability and growth (shrimp production) |
|---|---|---|
| 5 | Catastrophic | Shrimp production would be unprofitable, contract markedly, making it unviable. It would need to be wound up |
| 4 | Severe | Shrimp production would be unprofitable, contract markedly and likely unviable even with significant remedial action |
| 3 | Major | Shrimp production would be unprofitable, contract and require significant remedial action to remain viable |
| 2 | Moderate | Shrimp production would be only marginally profitable with growth stagnant |
| 1 | Minor | Shrimp production would be profitable, with growth is achieved but fails to meet expectations |
The vulnerability matrix identifies adaptive capacity to the risks of climate change and determines the level of vulnerability. First, adaptive capacity – the ability of a system to adjust to climate change, to moderate potential changes, to take advantage of opportunities or to cope with negative consequences – is categorised as “low”, “medium” or “high” (Brundell et al., 2011). Groups of farmers (focus groups) were asked to assign the appropriate category for their farming system on a consensus basis. A low level of adaptive capacity is very difficult and costly for shrimp production to implement adaptation activities that are effective. A medium level of adaptive capacity perceives some difficulty and expense in implementing change; however, it is possible. A high level of adaptive capacity is where adaptation is feasible and practical. Finally, vulnerability levels derived from combining impact risk and adaptive capacity (Figure 2) assigned by shrimp farmers and utilising a similar approach as that of Brundell et al. (2011) through the abovementioned vulnerability matrix.
3.3 Data collection and analysis
The field study was undertaken in Ca Mau Province, Vietnam, from November 2012 to February 2013. Four communes were selected for interview surveys and focus groups representing the four shrimp farming systems: RSRF, ISMF, SSMF and ISF. All shrimp farmers investigated cultivate the same type of shrimp species – the black tiger shrimp.
3.3.1 Interview surveys.
The status of shrimp farmer income in the four systems was obtained through interviewing shrimp farmers. Farmer household selection was determined through: selection of four communes representing the four farming systems by consulting with local key informants; choosing a list of complying households in the selected communes; selecting a target number of households from 20 to 25 shrimp farmers to be interviewed in each commune; and finally, a systematic random selection was used in the surveys (Leedy and Ormrod, 2001). In total, 100 shrimp farmers were interviewed, comprising 22 in RSRF, 31 in ISMF, 26 in SSMF and 21 in ISF. This sample, although not necessarily representative of the Ca Mau population of shrimp farmers, is sufficient to provide valuable insight on shrimp farmer perceptions of climate change in the four farming systems. Interviews were conducted with one adult shrimp farmer who responded on behalf of each household, following the approach of Few and Tran (2010). All interviews were semi-structured and interview questionnaires were composed of both open-ended and closed questions (Kolb, 2008; Leedy and Ormrod, 2001). Interviewers and participants communicated in Vietnamese during face-to-face interviews (Kvale, 2007; Leedy and Ormrod, 2001). All collected data and information was transcribed into the Excel worksheets; the qualitative data were summarised, categorised and grouped according to the techniques of Fielding and Fielding (1986) and Leedy and Ormrod (2001).
3.3.2 Focus groups.
Participants recruited for the surveys were drawn from the sample of interviewees who had been individually interviewed previously (as per Section 3.3.1). The participants involved in the focus groups were senior shrimp farmers who had been living in the communes for a long time and experienced in shrimp production. The selection process was based on that of Morgan and Krueger (1998) and Krueger (2015), comprising between 10 and 20 farmers for each focus group of each farming system. Four focus groups were facilitated comprising 16 participants in RSRF, 21 in ISMF, 14 SSMF and 16 in ISF. Face-to-face focus groups were conducted (Chase and Alvarez, 2000) in Vietnamese, and note taking occurred during the focus group meetings (Krueger and King, 1998). The focus group members discussed each climate change impact in turn with the discussions facilitated by the lead researcher. They were asked to individually categorise ratings by using a predetermined scale (Krueger, 2015) and then to work as a group to arrive at a collective value for each point (as per measures in Tables I). Finally, the results were collected and analysed (Krueger, 1998) according to risks and vulnerability levels of shrimp farming income to climate change events, based on scores and ratings utilising the matrix worksheets (Mackay and Russell, 2011; Brundell et al., 2011).
A limitation of this research approach is that the interview surveys and the focus groups rely on the opinions and views of shrimp farmers who can be expected to have biases and/or lack of understanding of climate change events. The perspectives of the shrimp farmers are qualitative and may be influenced by other non-climate change-related factors.
4. Study sites and shrimp farming systems
4.1 Ca Mau province overview
Ca Mau is a flat and low-lying coastal province in the southernmost extent of the Mekong River Delta (SWIRP, 2008). The province occupies 5,392 km2, making up more than 13 per cent of the Mekong Delta and equal to 1.6 per cent of the whole country (Actionaid and CRES, 2010). It has two faces to the sea and is regulated by the tidal regimes of both the West Sea and the East Sea with 245 km of coastline and only 0.75 m of elevation relative to sea level. The climate is tropical monsoon with two distinct seasons. The area supports more than 1.2 million people with the provincial gross domestic product growth rate around 12 per cent over the past decade. The majority of Ca Mau households are engaged in aquaculture (Mackay and Russell, 2011) where shrimp farming dominates the entire sector (Ca Mau Statistic Office, 2011). Shrimp farming is not only a key component of Ca Mau’s economy (Mackay and Russell, 2011), but it also represents over 40 per cent of the shrimp farming area of all the coastal provinces in the Mekong Delta (VASEP, 2011). There are two main types of shrimp species (Letopenaeus vannamei and Penaeus monodon (P. monodon)) cultivated in Ca Mau, but the black tiger shrimp (Penaeus monodon) is dominant and farmed across the province (DARD, 2010). Shrimp farming is the major livelihood and an important income base for farmers (Hung, 2012). The Ca Mau shrimp area and production characteristics for the past decade are illustrated in Figure 3.
Shrimp farming area (hectare: ha) and shrimp production (ton: tn) in Ca Mau province of Vietnam from 1999 to 2014
Shrimp farming area (hectare: ha) and shrimp production (ton: tn) in Ca Mau province of Vietnam from 1999 to 2014
4.2 Shrimp farming systems in Ca Mau province
Generally, shrimp farming systems in Vietnam are classified as extensive, improved-extensive, semi-intensive and intensive (Nhuong et al., 2002; Thi, 2007). The Ca Mau shrimp farming categories are based on pond size, method of water exchange, feed and chemical use and stocking density (Anh et al., 2012), as well as land holding rights, harvest and farming practices (Ha, 2012). Furthermore, in addition to the black tiger shrimp, farmers normally also cultivate crabs or fish and apply extensive, improved-extensive, and/or semi-intensive methods in different systems, such as mangrove-shrimp combinations or rice-shrimp rotation. Thus, combination models and poly aquaculture are popular in Ca Mau. The locations of farming systems targeted in this research are shown in Figure 4, and a brief description of each of the four shrimp farming systems investigated follows.
4.2.1 Integrated shrimp-mangrove farming system (ISMF).
ISMF is a traditional extensive farming method with farm size varying from 2 to 17 ha. It relies on wild stock trapped during high tides with no feed supply provided (Minh, 2001; Clough et al., 2002). Legally, the mangrove area required to be conserved should be 70 per cent of the pond area, but in reality, shrimp farmers typically violate this rule with ditched shrimp pond areas of up to 33-43 per cent of the total pond area (Binh et al., 1997). However, fewer shrimp farmers now practise this model because of natural stock reduction (de Graadf and Xuan, 1998). Currently, most shrimp farmers practise ISMF based on artificial stock with a density of 1-3 individuals/m2 and yielding 300-400 kg/ha/year.
4.2.2 Separated Shrimp-Mangrove Farming (SSMF).
SSMF is similar to ISMF, but the mangrove area (around 60 per cent of the farmland area) is separated from the shrimp ponds. SSMF in the Tam Giang Dong commune has farm sizes varying from 3.5 to 20 ha. Beside the black tiger shrimp, both ISMF and SSMF also harvest other products such as wild shrimp species, fish, crab and cockles (Nhuong et al., 2002). Shrimp productivity fluctuates between 333 and 400 kg/ha/year.
4.2.3 Rice-Shrimp Rotation Farming (RSRF).
RSRF has been practised for many decades in the saline-affected areas of the coastal provinces of the Mekong Delta (Vuong, 2011). It is an integrated rice–shrimp system within the same fields with alternative cropping of rice in the wet season when water salinity is suitable and shrimp during the dry season when water salinity is high (Brennan et al., 2002). Rice fields are designed with a trench, providing a refuge for the shrimps during rice production with a protective dike around the periphery of each field (Brennan et al., 2002). Shrimp productivity of this system is 200-300 kg/ha/year for extensive farming and 250-500 kg/ha/year for IESF. This model has been expanding and has been considered as a sustainable farming system in recent times (Tran, 1997; Brennan et al., 2002).
4.2.4 Intensive shrimp farming.
Intensive shrimp farming started in Khanh Hoa province in central Vietnam in 1989. The pond size for this system varies from 0.2 to 1.0 ha, with a stocking density of 15-30 post larvae per m2, and shrimp productivity of 2,500-4,000 kg/crop/ha/year (Nhuong et al., 2002). The farming system reached 3,428 ha in 2011 with pond size 1,000-6,500 m2, stocking density 14-40 post larvae per m2 and productivity varying 3,500-6,600 kg/crop/ha in Ca Mau Province (Chinh, 2012).
5. Shrimp farming income losses
The data and information collected from the interview surveys include household characteristics and status of shrimp farming income and losses.
5.1 Respondent and household characteristics in the four farming systems
A summary of characteristics of the shrimp farmers interviewed in the research and their households is presented in Table III. The average age of interviewees from the four farming systems ranges from 49 to 53 years with the majority being male. The average family size varies from 5 to 6 persons/household with the majority of household members achieving secondary schooling. The highest percentage of household members unable to read or write is in SSMS (14 per cent) and RSRF (13 per cent). The majority of family members fell within the normal labour-age (16-60 years) with just over half of all family members engaged in shrimp farming (50-58 per cent) for each of the four farming systems.
Basic information about respondents and households in the four farming systems
| Respondents/Households | Age | Gender | Family size | Education of household members (Year-%) | Labour distribution (%) | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| M (%) | F (%) | Unable to read/write | 1-5 | 6-9 | 10-12 | Higher education | Labour age | Aquaculture Labour | |||
| RSRF (n = 22) | 52.8 | 77.3 | 22.7 | 5.6 | 13.0 | 6.5 | 51.2 | 16.3 | 14.6 | 76.4 | 54.5 |
| ISMF (n = 31) | 49.6 | 77.4 | 22.6 | 5.3 | 6.1 | 12.8 | 50.0 | 22.6 | 8.5 | 67.1 | 56.1 |
| SSMF (n = 26) | 50.6 | 65.4 | 34.6 | 6.1 | 13.8 | 10.1 | 38.4 | 27.7 | 10.1 | 64.2 | 49.7 |
| ISF (n = 21) | 52.1 | 85.7 | 14.3 | 5.1 | 3.7 | 9.3 | 45.8 | 28.0 | 7.5 | 71.0 | 57.9 |
| Total (n = 100) | 51.1 | 76 | 24 | 5.5 | 9.4 | 9.9 | 46.1 | 23.7 | 8.5 | 69.1 | 54.2 |
5.2 Status of shrimp farming income and losses
The characteristics of farmers’ income sources are presented in Figure 5. Although farmers in the four systems were mostly concerned with shrimp cultivation, they engaged in different activities to generate income. The main income–generating activities of farmers include shrimp farming, poultry and pigs, wages from hired labour, vegetables, aquatic exploitation and local trading (such as shrimp middlemen, shrimp feeds, nurseries and hatcheries). The number of activities to generate income for ISMF farmers is more than those farmers in the other systems.
Number of main activities to generate incomes for shrimp farmers in four farming systems
Number of main activities to generate incomes for shrimp farmers in four farming systems
The characteristics of shrimp farming areas and income vary considerably among the four systems (Table IV). SSMF farmers have around twice the area of the others, while ISF farmers earn on average about twice that of SSMF and ISMF, and nearly five times that of RSRF. The shrimp income/farming area of ISF farmers is about two-and-a-half times that of ISMF farmers and about four times that of RSRF and SSMF, respectively. Irrespective of the farming system type, shrimp farming income is the most important contribution to total income for the farmer families and the proportion is largest (93 per cent) for SSMF; that is, greater by 20-30 per cent than the other three systems.
Distribution of shrimp area (ha) and household income (HH) in the four farming systems
| Farming systems | Shrimp area (ha) | Shrimp income (VND M/Ha/Year) | Shrimp income (VND M/HH/Year) | Household income (VND M/HH/Year) | ||||
|---|---|---|---|---|---|---|---|---|
| Average | SD | Average | SD | Average | SD | Average | SD | |
| RSRF (n = 22) | 1.8 | 0.8 | 16.8 | 12.9 | 25.3 | 15.7 | 40.8 | 30.6 |
| ISMF (n = 31) | 2.0 | 1.1 | 32.2 | 17.7 | 73.3 | 81.1 | 73.3 | 81.1 |
| SSMF (n = 26) | 3.5 | 1.5 | 20.3 | 12.7 | 74.4 | 65.1 | 80.3 | 65.1 |
| ISF (n = 21) | 2.1 | 1.3 | 79.8 | 126.8 | 154.7 | 318.1 | 235.7 | 424.1 |
Family income as well as shrimp income fluctuate considerably with the biggest fluctuation among ISF shrimp families. It is likely that the shrimp farmers are facing economic risk based on income characteristics (Figure 6). For example, about one-third of ISF farmers (33 per cent) received no shrimp income and only ISMF farmers were exempt from this lack of shrimp income. As also shown in Figure 6, net shrimp income decreased in all systems between 2010 and 2012; again, this is especially the case for ISF (77 per cent decrease), compared with SSMF (40 per cent), RSRF (6 per cent) and ISMF (6 per cent) experiencing the least decreases.
Increase of shrimp income and percentage of farmers who earned no shrimp income from 2010 to 2012
Increase of shrimp income and percentage of farmers who earned no shrimp income from 2010 to 2012
6. The vulnerability of shrimp farming income to climate change events
The important climate change events ranked by shrimp farmers that adversely affected shrimp production in the four farming systems (Quach et al., 2015) were discussed in the focus groups. Participants were asked to categorise the likelihood of occurrence and consequence to obtain the level of risk of climate change impacts on shrimp income by multiplying the scores of livelihood and consequence (see Tables I, II and Figure 1 in Section 3.2). Results of the risk priority matrix of each climate change impact on farmers’ shrimp income in each farming system are presented in Table V. Overall, all shrimp farmers considered “greater intensity of or irregular rains” as “high risk”, and all other climate change events as a “medium risk” to shrimp farming income.
Risk priority matrix of climate change impacts on shrimp farming income
| Climate change impact | Farming systems | Consequence | Likelihood | Risk |
|---|---|---|---|---|
| Greater intensity of or irregular rains | RSRF | 4 | 5 | 20 |
| ISMF | 3 | 5 | 15 | |
| SSMF | 4 | 4 | 16 | |
| ISF | 2 | 5 | 10 | |
| Average | 3.3 | 4.8 | 15.4 | |
| Seasonal pattern changes | RSRF | 4 | 4 | 16 |
| ISMF | 3 | 3 | 9 | |
| SSMF | 3 | 3 | 9 | |
| ISF | 2 | 2 | 4 | |
| Average | 3 | 3 | 9 | |
| Increased intensity of high tides | RSRF | 3 | 4 | 12 |
| ISMF | 3 | 4 | 12 | |
| SSMF | 4 | 5 | 20 | |
| ISF | 1 | 2 | 2 | |
| Average | 2.8 | 3.8 | 10.3 | |
| Sea level rise | RSRF | 2 | 3 | 6 |
| ISMF | 3 | 4 | 12 | |
| SSMF | 5 | 5 | 25 | |
| ISF | 1 | 1 | 1 | |
| Average | 2.8 | 3.3 | 8.9 | |
| Drier dry season | RSRF | 1 | 4 | 4 |
| ISMF | 1 | 3 | 1 | |
| SSMF | 2 | 3 | 6 | |
| ISF | 2 | 5 | 10 | |
| Average | 1.5 | 3.8 | 5.6 | |
| Increased fluctuations of water temperature | RSRF | 2 | 4 | 8 |
| ISMF | 1 | 3 | 3 | |
| SSMF | 1 | 4 | 4 | |
| ISF | 4 | 5 | 20 | |
| Average | 2 | 4 | 8 | |
| Extreme climate events | RSRF | 4 | 3 | 12 |
| ISMF | 4 | 2 | 8 | |
| SSMF | 4 | 2 | 8 | |
| ISF | 3 | 1 | 3 | |
| Average | 3.8 | 2.0 | 7.5 |
Other perceived risk levels of climate change impacts in each farming system on shrimp farming income are summarised in Figure 7. It is noted that RSRF, ISMF and SSMF farmers considered greater intensity of or irregular rains as a high risk; seasonal pattern changes were also considered as a high risk by RSRF farmers; increased intensity of high tides was judged by SSMF people as a high risk; ISF farmers considered increased fluctuations of water temperature as a high risk; while SSMF farmers considered sea level rise as an extreme risk to their shrimp income. Although risk levels of shrimp farming income are different among climate change events and shrimp farming systems, the risk level overall to shrimp farming income for all climate change impacts is highest in SSMF, then in RSRF and ISMF, while the lowest risk is in ISF.
Shrimp farmers in the four systems classified levels of adaptive capacity to negative impacts of climate change events (Figure 8). Generally, the adaptive capacity levels of ISF and ISMF farmers were perceived to be higher than those of SSMF and RSRF farmers. This is because they earned a higher family income and had higher levels of shrimp cultivation, as previous results have revealed. More specifically, ISF farmers have a high adaptive capacity to the climate change events of increased intensity of high tides, sea level rise and increased fluctuation of water temperature; however, as might be expected, all shrimp farmers in all systems have a low adaptive capacity to seasonal pattern changes. In ISMF, farmers have low adaptive capacity to seasonal pattern changes and sea level rise, but have a medium adaptive capacity in relation to all other climate change events. Finally, farmers in SSMF and RSRF recorded a medium adaptive capacity to increased intensity of high tides and increased fluctuation of water temperature, and a low adaptive capacity to the remaining climate change effects on the list.
Levels of adaptive capacity to climate change impacts for each shrimp farming system
Levels of adaptive capacity to climate change impacts for each shrimp farming system
Combining risk levels and adaptive capacity derived the vulnerability levels of shrimp farming income of farmers in each farming system in relation to climate change impact (Figure 9). Both RSRF and SSMF show mostly high and moderate levels of shrimp farming income vulnerability to climate change events, with ISMF and ISF fairly evenly split between moderate and low vulnerability levels.
Vulnerability level of shrimp farming income derived from combining risk level and adaptive capacity
Vulnerability level of shrimp farming income derived from combining risk level and adaptive capacity
7. Discussion
The literature review findings and original data collected show the vulnerability of shrimp farming income to climate change events in the research areas of Ca Mau Province. This is borne out by evidence of shrimp farming income losses recently and ranking of shrimp farmers in the four systems on shrimp income vulnerability to the climate change events. However, it is apparent that the perceived vulnerability of shrimp farmers to actual or expected climate change impacts varies considerably according the farming system utilised.
The research results show that shrimp farming is the most important contribution for farmer incomes in the four farming systems, with the majority of shrimp families depending on this income stream to sustain livelihoods. However, shrimp income in all systems has decreased in the three years preceding the survey interview. Shrimp farmers considered that this reduction is likely related to the negative impacts of climate change events in the past 10 years (Quach et al., 2015). Previous research conducted in IESF supports this view that the adverse effects of sea level rise, high temperatures, irregular weather and too much rain have had the most impact on shrimp production with losses of 10-30 per cent or even 100 per cent of shrimp income (Hai et al., 2011). Similarly in the present research, it was evident that shrimp farming income is at risk, with evidence of ISF, RSRF and SSMF farmers who received no shrimp income. Chinh (2012) further identifies some problematic issues regarding cultivation techniques in ISF in Ca Mau (Table VI).
Perspective of shrimp farmers in the four farming systems that adverse effects of climate change events on shrimp farming in the research areas in the past 10 years
| Respondents | Yes | No | Not sure | |||
|---|---|---|---|---|---|---|
| Frequency (F) | (%) | Frequency (F) | (%) | Frequency (F) | (%) | |
| RSRF (n = 22) | 17 | 77.3 | 0 | 0.0 | 5 | 22.7 |
| ISMF (n = 31) | 29 | 93.5 | 0 | 0.0 | 2 | 6.5 |
| SSMF (n = 26) | 21 | 80.8 | 2 | 7.7 | 3 | 11.5 |
| ISF (n = 21) | 15 | 71.4 | 5 | 23.8 | 1 | 4.8 |
| Total (n = 100) | 82 | 82.0 | 7 | 7.0 | 11 | 11.0 |
An interesting way to understand the shrimp income vulnerability to climate change in the research areas in light of the results presented previously is to consider the characteristics and ramifications for each farming system in turn, doing this by combining individual results from Tables III, IV and Figures 5, and 6 and 9.
7.1 RSRF
RSRF income registers as being at high risk from the greater intensity of or irregular rains and seasonal pattern changes that could result in high levels of vulnerability. This is because farmers have low adaptive capacity to these climate change events. The household survey results show that RSRF farmers have the lowest shrimp income (VND17M/ha/year) and the smallest shrimp farming area (1.8 ha/household) relative to farmers in the other systems. They also have a comparatively large family size (six persons/household on average) and a high percentage of farmers (13 per cent) who are unable to read and write. While RSRF farmers have three income streams on average, some 35 per cent of them depend entirely on the shrimp farming income stream.
7.2 ISMF
ISMF income registers as being at high risk from greater intensity of or irregular rains, and medium to low risk from the other climate change events. As a result, ISMF farmers have a moderate to low vulnerability level of shrimp farming income to all climate change events and a medium level of adaptive capacity to most of the climate change impacts. The survey results illustrate that ISMF farmers have a higher shrimp income (VND32M/ha/year), smaller family size (five persons/household) and a lower percentage of farmers (6 per cent) who are unable to read and write relative to those in the RSRF and SSMF. Moreover, ISMF farmers have up to four income streams compared with the rest of the farming systems, which have just three. As the ISMF farms contain mangroves integrated with the shrimp ponds this would presumably provide shrimp shelter and thereby offer some natural or inbuilt climate change resilience.
7.3 SSMF
SSMF registers as being at high risk from greater intensity of or irregular rains and increased intensity of high tides, and extreme risk from sea level rise; all of which point to a high level of vulnerability. Although the survey results show that individual farms are large and contain mangroves separated from shrimp ponds, these aspects could be expected to provide some climate change resilience too. Meanwhile, SSMF farmers have a low adaptive capacity to most of the climate change events. This is because they have a lower shrimp farming income (VND20M/ha/year) compared with ISMF and ISF farmers, the biggest family size category (six persons/household), and the highest percentage of farmers (14 per cent) who are unable to read and write compared with the other systems. While there are up to three types of income in SSMF households, the majority of shrimp farmers (77 per cent) have only one income stream and are most dependent overall on shrimp farming income (97 per cent).
7.4 ISF
ISF income registers as being at high risk from increased fluctuations of water temperature, but at low risk from most of the remaining climate change impacts. The ISF farmers have low to moderate vulnerability levels of shrimp farming income to climate change and a high to moderate adaptive capacity to most climate change impacts. The survey results show that these farmers have the highest shrimp farming income (VND80M/ha/year), the smallest family size (five persons/household) and the lowest percentage of farmers (4 per cent) who are unable to read and write compared with the other systems. A large majority of farmers (78 per cent) in ISF have two or three income streams within their households to sustain livelihoods.
Overall, climate change impacts pose a high level of risk to shrimp farming income, which could result in high levels of vulnerability in each of the four farming systems. The risk level of shrimp farming income to each climate change impact found in this research is substantially different among the four farming systems and contrasts with the findings of RIA2 (2014). The level of adaptive capacity to each climate change impact on shrimp production also differs substantially among the four farming systems. ISF farmers have higher levels of adaptive capacity than farmers in the other systems for most of the climate change impacts, while RSRF and SSMF farmers alike register the lowest levels of adaptive capacity. Overall then, the vulnerability level of shrimp farming incomes in ISF to the effects of climate change would appear to be lower than in the other farming systems. This is because the ISF farmers not only have lower risk levels and a higher adaptive capacity to climate change events compared with the other shrimp farming systems, as explained previously, but their performance characteristics regarding number of income streams, total family income, family size and education levels are comparatively favourable.
8. Conclusion
Drawing upon the perspectives of shrimp farmers, this research shows that farmers in the research areas have experienced shrimp income losses in recent years and are vulnerable to climate change events. While there are some differences between farmers’ perspectives in the four systems concerning the vulnerability level of shrimp farming income to climate change events, important linkages between the characteristics and ramifications for each farming type and the farmers’ perspectives on the shrimp farming income vulnerability can be made. Shrimp farmers with a higher level of cultivation (ISF) earned more money than the other farmers and have lower levels of vulnerability; notwithstanding this, they have experienced reductions in shrimp income, which Chinh (2012) links, at least in part, to problems associated with cultivation techniques. In general, the results suggest that from an income perspective, farmers operating in the intensive shrimp farming systems appear to be less vulnerable to existing and expected climate change effects relative to those in the other systems. This finding contrasts with that of Tran (1997) and Brennan et al. (2002) who considered RSRF a sustainable model for shrimp production. This difference no doubt reflects different focus considerations within each study. Nevertheless, it has implications for policymakers who encourage ISF as a strategy for enhancing shrimp farmer resilience to the effects of climate change, as well as improving cultivation techniques for shrimp farmers. It also points to the value in further research of the relative resilience and vulnerabilities of different shrimp farming systems to climate change. Having identified an understanding of status and vulnerability levels of shrimp income for the different farming systems, it is intended that this information be used to help local government and residents of Ca Mau as well as shrimp farmers within the wider Mekong Delta gain a better understanding of shrimp income vulnerability to climate change events, which will assist them in developing suitable adaption options.
Notes
The vulnerability of shrimp farming income is a combination of potential impacts and adaptive capacity of shrimp farmers to climate change events on shrimp production based on a risk assessment process. The risk matrix is structured to identify the potential impacts, adaptive capacity and vulnerability to climate change events.
Risk is understood as a hazard or the chance of a loss. Risk is to be assessed by considering both the consequence of an event occurring and likelihood that the same event occurs. Risk is categorised as follow: Extreme risk (E ≥ 20) requires urgent attention to implement adaptation options immediately. High risk (H = 12-20) requires attention to develop adaptation options in the near term. Medium risk (M = 5-12): expects that existing controls will be sufficient in the short term but will require attention in the medium term and should be maintained under review. Low risk (L ≤ 5): requires maintenance under review by control measures, but it is expected that existing controls will be sufficient and no further action will be required unless circumstances become more severe.
