SOCIO-ECONOMIC VULNERABILITY TO CLIMATE CHANGE: IMPACT ASSESSMENT
ON AQUACULTURE FARMERS IN SARAWAK, MALAYSIA.
Rosita Hamdan
Fatimah Kari
Nurulhuda Mohd Satar
Faculty of Economics and Administration
University of Malaya
Kuala Lumpur
Since the past two decades, the climate projection has revealed the occurrence of climate change by the
extreme warming trends of the mean surface temperature. Malaysia has experienced the highest mean
surface temperature in 1997 and 1998 and the frequent El-Nino Southern Oscillation (ENSO) events.
These scenarios have influence to the abnormal patterns of precipitation and also increase the droughts,
storms and floods in some areas and states including Sarawak. Besides the physical and financial drivers,
climate is a major driver that enhances the aquaculture sector growth and sustainability. The variability of
temperature, air humidity and total rainfall in Sarawak shows negative signs to aquaculture production in
both ponds and cages systems. Moreover, the climate change also degrades the water source quality for
aquaculture activities such as rivers and water spring where the problems of water stratification and
decrease of dissolved oxygen affects aquaculture activities. These problems have contributed to major
loss of production and increase in the socio-economic and income vulnerability among farmers. The small
scale or individual farmers are among the highest vulnerable to climate change. With the low assetsowned, they are unable to cope with the impacts with their income falling below the national poverty line.
Thus, this study attempts to assess the consequences of climate change to aquaculture farmers in Sarawak
based on environment and poverty linkages as well as vulnerability and adaptation framework. The
impacts and implication of climate change and the strategies by the farmers in coping with the impacts
will be discussed further in this paper.
Keywords: climate change, aquaculture, impacts, vulnerability, socio-economic.
Overview of aquaculture sector development in Malaysia.
Aquaculture sector had been developed since 1920’s in Malaysia started with the freshwater
aquaculture and then brackish water aquaculture in the late 1930. The brackish water aquaculture on that
time situated in the mangrove area and concentrated on the shrimp farming by using trapping ponds and
also cockle culture in mud flats. The cages aquaculture sector is started around seventies (Tan,1998). This
sector has significantly expanded in the last two decades.
Aquaculture sector has a great potential to be developed and play a significant role to overcome
the decreasing of fish stock due to over exploitation fishing activities in coastal area by the commercial
fishery (Tan, 1998; CICS, 2000). According to Shariff et. al. (1997), aquaculture sector has been
transform greatly to more technological activities and drive to the high market contribution. Aquaculture
has been identified has the strategic industry to fulfill the domestic demand of high protein resources and
export demand of fish products. This will help the government to achieve the growth of food production
for 33.4 percent or 1.8 million metric tonnes for fisheries and accomplish 103% in self sufficiency level
by 2010 as mentioned in mid-term review of the Ninth Malaysia Plan (Malaysia, 2008). The aquaculture
sector benefits the national and local level by perform the demand for fish and endorse the private sector
technical and research capability for the economic development (CICS, 2000).
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The aquaculture sector in Malaysia is still small as compared to the neighbour countries such as
Thailand and Indonesia. However, Malaysia is also supply the aquaculture products by export activities to
the other countries. The main Malaysia’s exported aquaculture products are shrimps (Penaeus monodon
and P. merguiensis), sea-perch (Lates calcarifer), grouper (Epinephelus spp), crabs (Scylla serrata),
cockles (Anadara granosa) and other freshwater species (Tan, 1998). Food and Agriculture Organization
(FAO) reveal that aquaculture production is going to be more economically important way of increasing
local fish production for food security and contribute less than 0.2 percent of GDP. Other evidences are
stated that contribution of aquaculture to GDP in terms of production value as percent of GDP is 0.283 in
2003 (Lungren et. al., 2006) and increase to 0.366 in 2004 (Sugiyama, et. al., 2004). Thus, this sector has
been targeted by the government in the Third National Agriculture Policy (1998-2010) to become the
major area of concentration to enhance the competitiveness of agriculture sector in Malaysia. The
aquaculture activities are believed will able to supply the local demand of fisheries products and also for
export to other countries. The policy envisions for steady growth of aquaculture production from the
current total production to 120,000 tons of total production by the year 2010 (Tan, 1998).
With respect to socio-economic, aquaculture involves in improving food supply, employment and
income. Aquaculture activities help to reduce the poverty problem especially in rural areas although by
the traditional aquaculture practices such as in China and Indonesia. Aquacultures activities benefit the
poor livelihoods by supply the nutritional foods, own-job and generate income (Edwards,). In 1990, out of
18,143 people are employed under this sector and occupied with the various level of operation activities
including harvesting, processing and marketing (Tan, 1998). Besides, the development of aquaculture
activities in the rural area will benefit the farmers and nearby community due to the allocation of
infrastructure such as electricity, communication and road access that help to improve the quality of life
(Mohd. Fariduddin, 2006]). Safa (2004) elaborated that the fishery sector are important in Malaysia
because it supply the demand of main source of protein and develop rural development through
employment creation.
Climate change and aquaculture
Environmental problems are one of the major issues that challenge the sustainable growth of
aquaculture sector (CICS, 2000; Shariff, et. al. (1997); Hambal, et. al. (1994)). The effects of climate
change to social and economic aspects can be seen in the interaction between environment, aquaculture
and socioeconomics can be assessing through social-ecology system concept. This concept promotes the
evaluation practices that include the entire exposure unit in system to identify the best solution to solve
the problem.
The climate change hazards affect the worldwide aquaculture production although the
productions are expected to growth due to the demand of fish consumption. The humans and environment
have to acclimatize with the ecosystem pressure and failure, biodiversity thrashing, variability of time
length for growing season, coastal corrosion and aquifer salinization, acidification of river and sea water
and also uneven series for pests and disease. The physical impacts of climate change are different
between one to another place and also effect vary to human and environment (World Bank, 2010).
Climate change is a natural climatic event (production risk) that influences the quality and quantity of
aquaculture production (Beach and Viator, 2008). The climate change has contribute to the climatic
variability such as rising temperature, sea level rise (Ong, 2001), exposure to extra violet radiation,
unbalanced rainfall pattern and force of severe weather (CICS, 2000; Akegbejo-Samsons, 2009). The
changes of temperature and precipitation were the major causes of failure to ponds culture production. It
leads to drought and flood seasons and implicate the water stratification that harms to culture species
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especially in shrimp production. Moreover, the rising temperature caused the oxygen depletion that
persuades the growth of algae blooms which affect toxins to the water (World Bank, 2010).
The climate change also will cause the modification to evaporation and precipitation cycle and
harm mostly to the salt water aquaculture. The most dangerous effects for aquaculture production and
other coastal activities are the occurrence of storm surges, waves, and coastal erosion. The severe storm
will results high loss to the farmers due to the serious and high damage of farm and cost high for
recovering the destroyed (CICS, 2000, Schjolden, 2004). In Malaysia, the difference climate and natural
conditions between states seems influenced to their aquaculture production. The increasing temperature
and changes in rainfall caused vulnerable especially to the northern peninsular Malaysia and also the
coastal of Sarawak and Sabah (Mustafa, 2007).
The climate change is also caused the disease outbreaks to the cultured fish and shrimp in all
stages of its growth (Chamhuri, et. al., 2009). White Spot Disease or White Spot Syndrome Virus
(WSSV) is among the common disease that effect to the cultured species especially to the shrimp farming
(Mazuki and Subramaniam, 2005). The deteriorating water escalate the disease eruptions and infectivity
of aquaculture products that affect the high economic lost which happen in Penang in 1992 (Hambal, et.
al., 1994) and the flood and water stratification caused fish death in Sungai Semarak, Kelantan in 2008
(Utusan Malaysia, 2008). The ‘El Nino Southern Oscillation (ENSO) which is the major climatic threat in
agriculture sector in 1997/1998 especially in Selangor, Sarawak and Sabah (Mustafa, 2007) and recently
informed as the threat to the agriculture sector (Utusan Malaysia, 2009).
The growth of aquaculture sector is importance in economic growth. However, this condition will
degrade the natural ecology system of the fish and shrimp where it is fully dependent on the given feed.
Moreover, it also raises the environmental problem which leads increase to climate change impacts
(World Bank, 2010). Aquaculture sector is negatively effect on coastal resources (Sulit, et. al., 2005)
through the loss of mangroves (Hambal, et. al., 1994) and threatened and degraded the rivers’ water
quality including Santubong River in Sarawak (Lee, et. al., 2002; Miod, et. al., 2009).
The extreme climate change impacts conditions will diminish the growth of development,
destroying lives and livelihood. In indicating the issue of climate change, the environmental and social
aspects are important to ensure the sustainable and safety aquaculture production (Anon, 2003). The
climate change risk affect increase to production cost in managing the farm efficiently (Sulit, et. al., 2005)
and minimize the production from the aquaculture farm. Thus, the small farmers are unable to survive in
this sector due to rising cost of production and lack of support system to cover the cultured fish and
shrimp from the impacts of production risk. The farmers failure in production and decline in food
production will lead to problem of famine (Sen, 1981) and poverty trap because of the permanent losses
of human and physical capital (Heltberg, et. al., 2009). The sensitivity of culturing procedures to the
climate change variability in terms of type, scale, intensity and culture location has a bad outcome to the
aquaculture farmers’ livelihood and also various socioeconomic costs (Oguntuga, et. al., 2009). The
pressures on access the finest water quality for aquaculture production raised the competition among the
farmers and other sectors’ farmers. The operation of industrial development near to the aquaculture
potential are has neglected the potential of the sectors’ growth (Hambal, et.al., 1994).
The social dimension is important to the improvement of policy and practice in coping with the
climate shocks (Kelly and Adger, 2000). The existing studies on the environmental issues on aquaculture
development in Malaysia need to be concentrated on the solution of the environmental problems in terms
of the assessment in good management, technical improvement and strategic planning (Hambal et. al.,
1994). FAO (2008) indicated that there are insufficient of studies done that able to provide understanding
of the vulnerability of fisheries and aquaculture to climate change which affect the constraint for
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prioritizing adaptive strategies. Besides, there is lack of research that focus on identify the relationship
between biophysical impacts of climate change and livelihood vulnerability of poor fishing communities
(Akegbejo-Samsons, 2009). The response of market to these changes and the implications for prices,
economic returns and sector investment will have major impacts on sector performance, employment,
food security and longer-term development impact. The farmers, consumers or dependent people to
aquaculture are vulnerable to the direct and indirect impacts of predicted climatic changes. Thus, this
study attempts to highlight the problem of climate change and its impact on aquaculture production and
socio-economic of farmers in the aspect of environmental economic based. Moreover, this study will also
indicate the option of adaptation by aquaculture farmers to cope with the risk of climate change.
The adaptation strategy in reducing climate change risk in aquaculture sector
The joint of mitigation and adaptation aspect in risk reduction management will maximize the
social welfare under the climate change conditions. The adaptations seems applicable to the community
especially for the lower income farmers due to the less implementation cost as compared to the cost of
mitigation. The rigorous mitigation target will increase if the adaptation processes are scarce to reduce
vulnerability. However, adaptation is ongoing process and performs as the complement solutions within
time until the mitigation response increase. (Howden, et. al., 2007).
The adaptation is observed for the context of impact analysis where the society adaptive capacity
helps to explain the cost of rising climate change (Fankhauser, et. al., 1999). The adaptation action is
worked with the purpose to reduce harm and not to avoid the severe climate change. Adaptation should be
a continuous action and starting with the change in normal conditions and also prepare for the extreme
events. The study in Canada in 1995 regarding to the adaptation costs in adapting the normal variability of
climate and extreme climate shows that Canada benefit larger by the expense to adapt with changes in
climate and less benefit due to the tremendous events (Burton, 1997).
The perception of risk is important in identifying the best application of risk management practice
(Meuwissen et. al., 2001). The factors that influence perception of risks are geographic areas, farm types
(Patrick, et. al., 1985); institutional and other factors that influence the farmers’ environment (Patrick and
Musser, 1997). The decision for implementing the risk management options can be taken by assessing the
information of limited resource farmers. The study in Mississippi shows that the limited resource farmers
practice low input and output production for adapting the production risks. Due to income constraint, the
farmers are also do the off-farm job to add the income and at the same time used the social security and
other government funds. The farm diversification activities are doubtful as the best solution for reduce the
farm risk. The improvement in high production quality would the alternatives for reducing farm risk. The
farmers also preferred the incentives rather than involve in the crop insurance program especially from
the farmers who gain low production. The educational program and training on the farm management
aspect would help the farmers to improve in their activities (Coble, et. al., 2001).
Adaptation is comprised the step of adjusting practices, processes and capital reaction to the
existent or peril of climate change as well as the reaction in the decision environment including social,
institutional structures and modification of technical options that can affect the potential or capacity for
realization of adaptation. The knowledge of adaptation will help to effectual handle climate risk for the
future. It helps in delivering the feedbacks from the related agents and policy makers in making the
decision of adaptation for short term and long-term duration. It help in giving the clear relationship
between the short term and long term alternatives so the management and policy decision will able to
prepare for any consequences of future risk (Howden, et. al., 2007).
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Data and model specification
The data for economic indicators such as total estimated production, total wholesale value and the
size of aquaculture areas are gathered from the Agricultural Statistics of Sarawak, Department of
Agriculture Sarawak and the Annual Fisheries Statistics, Department of Fisheries Malaysia from 1992
until 2008. The climate data comprises of mean maximum temperature, mean minimum temperature,
mean total rainfall, mean relative humidity and total sunshine hours had been collected from the
Yearbook of Statistics, Department of Statistics Malaysia and also from Agricultural Statistics of
Sarawak, Department of Agriculture Sarawak. The interview was conducted on 41 aquaculture farmers in
Kuching district (including Santubong, Sematan, Lundu, Bau and Siburan) to indicate the adaptation
option by them in coping with the climate change. The data covered four different system of aquaculture
systems known as freshwater ponds, freshwater cages, brackish water ponds and brackish water cages
systems.
The models are analyzed using two common techniques, known as Ordinary Least Square (OLS)
parametric estimation and Chi-square test for two unrelated non-parametric samples. Ordinary Least
Square is used to find a good estimation of parameters that fit a function, f(x), of a set of data, x 1….xn in
identifying the significant of climate and aquaculture area to aquaculture production, wholesale and retail
value. The econometric model of this study is;
Yt    1 max temp   2 min temp   3totrain   4 humidity   5 sunshine   6 area
where,
Y1
Y2
maxtemp
mintemp
totrain
humidity
sunshine
area
(1)
= total estimated production
= total wholesale value
= mean of maximum temperature in degree celcius
= mean of minimum temperature in degree celcius
= mean of total rainfall in millimeter/day
= mean relative humidity in percentage
= total sunshine hours
= size of aquaculture ponds or cages
Chi-square test for two unrelated samples is used to evaluate the existence of relationship
between two variables (Green and Salkind, 2008) or whether the difference between the observed and
expected frequencies is bigger than the expected by chance (Wheater and Cook, 2000). This technique is
used to identify the adaptation option of farmers to climate change risk. The Chi-square can be calculated
as;
X2 
(O  E ) 2
E
(2)
Where, O is the observed (measured) value and E the expected (calculated) value.
Estimation Results and Discussions
The results from OLS estimation are presented in the table 1 for brackish water aquaculture and
table 2 for fresh water aquaculture system. The findings are compared by the types of water (freshwater
and brackish water) results and different systems of aquaculture known as ponds and cages aquaculture
systems. Moreover, the findings also covered different relationship between total production and total
wholesale value as the independent variables. The two independent variables, total production and
wholesale value indicate the physical and monetary value of production. In the neo-classical sense,
5
physical output and monetary value differs because the assumption about market structure in aquaculture
production (Beattie and Taylor, 1995). Thus, the findings will help to identify and assess the critical
factors that affecting production risk in Sarawak’s aquaculture sector. In general, the estimated residuals
of all systems are normally distributed. There are also showed no evidence of autocorrelation from the
Breusch-Godfrey LM test and no evidence of heteroskedasticity from the White test in all aquaculture
systems.
5.1 Brackish water aquaculture systems
The coefficient of all explanatory variables (see table 1) shows that only the size of aquaculture
areas has a significant positive impact on aquaculture production for brackish water cages system. The
increase of 1 percentage point in the size of aquaculture area will increase total production by 0.0002
percentage point. In brackish water aquaculture ponds, mean relative humidity is significant negative
where the increase of 1 percentage point of the mean relative humidity will decrease 0.0976 percentage
point of the total production. The size of aquaculture area is significant positive on aquaculture production
where the increase of 1 percentage point in the size of aquaculture area will increase 0.003 percentage
point of total production. The positive impacts of the size of aquaculture area in brackish water ponds and
cages suggest that the additional numbers of cages and ponds will result the high production in this sector.
Table 1: Regression results (brackishwater aquaculture system)
CAGES
Ytprod = - 20.6252 - 0.5954maxtempt + 0.8084mintempt + 0.0164totraint + 0.2027humidityt + 0.9932sunshinet + 0.0002areat
(-0.54)
(-0.51)
(1.31)
(0.15)
(1.42)
(0.70)
(2.61)**
Ytwholesale = 1.7327 – 1.2460maxtempt + 0.8160mintempt + 0.0410totraint + 0.2055 humidityt + 0.9139 sunshinet + 0.0002areat
(0.04)
(-0.99)
(1.21)
(0.35)
(1.33)
(0.91)
(2.53)**
PONDS
Ytprod = - 14. 8685 + 1.0611maxtempt + 0.1784mintempt - 0.0664totraint - 0.0976humidityt – 1.4490sunshinet + 0.0030areat
(-0.41)
(1.10)
(0.32)
(-0.84)
(-2.28)**
(-1.37)
(5.04)***
Ytwholesale = - 41.9285 + 2.0775maxtempt + 0.2567mintempt - 0.0974totraint – 0.1174humidityt - 1.7608sunshinet + 0.0033areat
(-0.82)
(1.54)
(0.33)
(-0.88)
(-1.96) *
(-1.19)
(3.87)***
R-squared
Adjusted R-squared
Standard error of regression
F-statistic
Breusch-Godfrey LM test
White test
Jarque-Bera normality test
Sum of squared residuals
Note: figures in paratheses are t-statistics.
* significant at the 10% level
** significant at the 5% level
*** significant at the 1% level
Brackishwater Cages
Ytprod
Ytwholesale
0.76
0.77
0.62
0.62
0.94
1.02
5.29
5.43
3.00
2.10
1.32
1.33
1.06
0.85
8.75
10.37
Brackishwater Ponds
Ytprod
Ytwholesale
0.90
0.86
0.85
0.78
0.72
1.01
15.75
10.53
0.55
0.93
0.44
0.36
0.61
0.80
5.17
10.11
The observation on 41 aquaculture farms showed that the farmers had expended their incomes to
open the new ponds or cages through the additional operating periods due to the market demand and the
benefits gain from the aquaculture activities. While the negative impacts of mean relative humidity is
6
consistent to the study by Kutty (1987). The air humidity has significant relation to the level of
evaporation of the water in the ponds and cages. If the degree of humidity increases, the evaporation will
decrease. This will cause the increase in moisture of the cultured species, the volume of fish foods and use
of chemicals in aquaculture activities.
In term of the total wholesale value, the operation size has significant effects whereby the size of
aquaculture area is important to the both systems where the increase of 1 percentage point in the size of
aquaculture area will increase 0.0002 percentage points and 0.0033 percentage points on the total
wholesale value in brackish water cages and brackish water ponds. The mean relative humidity shows the
negative significant effects to the brackish water ponds where the increase of 1 percentage point of mean
relative humidity will affect of 0.1174 percentage point reduce in aquaculture returns. The increase of
mean relative humidity will affect the high expenditure on maintenance and management cost on the
aquaculture production. Thus, it contributes to the loss of returns from aquaculture to the farmers.
The R2 from estimated regression in total production and total wholesale of brackish water cages
is 0.76 and 0.77. These imply that about 76 percent and 77 percent of the variation in Y tprod and Ytwholesale
are explained by the variation in the independent variables included in the models. The brackish water
ponds estimated regression results explain that 90 percent and 86 percent of the variation Ytprod and
Ytwholesale are explained by the variation in the independent variables included in the model.
5.2 Fresh water aquaculture systems
In the fresh water cages (see table 2), the coefficient of all explanatory variables shows that the
mean maximum temperature is negative significant impact on aquaculture production and total wholesale
value. The mean maximum temperature has a highly significant (at 10 percent level) negative impact on
aquaculture production and total wholesale value. An increase of 1 percentage point of the mean
maximum temperature will decrease the aquaculture production by 3.068 and total wholesale value by
3.236 percentage points. However, the size of aquaculture area affect positive significant to the both
explanatory variables. The increase of 1 percentage point in the size of aquaculture area will increase
0.786 and 0.758 percentage point on aquaculture production and total wholesale value. The R2 results
show that 64 percent of Ytprod and 65 percent of Ytwholesale are explained by the variation in the observed
independent variables.
Meanwhile in the fresh water ponds, out of four coefficients of variables are statistically
significant in total production and exhibit their expected signs. The mean maximum temperature has
highly significant (at 10 percent level) positive impact on aquaculture production. An increase of 1
percentage point of the mean maximum temperature will increase 1.064 percentage points on aquaculture
production. The positive significant of coefficient are also showed by the mean minimum temperature and
the size of aquaculture area. If 1 percentage point increases in the mean minimum temperature and the
size of aquaculture, the total production will increase 0.873 and 0.827 percentage points. The mean
relative humidity shows negative significant (at 5 percent level) direction in its relationship to total
production. The increase of 1 percentage points in the mean relative humidity will decrease 0.006
percentage points in the total production.
In indicating the influence factors on aquaculture returns to the farmers, the findings show that
the mean minimum temperature and the size of aquaculture area have significant (at 10 percent level)
positive impact on the total wholesale value. The performance of total wholesale value is highly influence
by the mean minimum temperature. An increase of 1 percentage point in the mean minimum temperature
7
will increase 0.942 of total wholesale value. Nevertheless, the 1 percentage point increase in the size of
aquaculture area will contributes 0.742 percentage point increase in the total wholesale value. The
findings are also showing that 63 percent of Ytprod and Ytwholesale are explained by the variation in the
observed independent variables from the R2.
Table 2: Regression results (freshwater aquaculture system).
CAGES
Ytprod = 80.182 – 3.068maxtempt + 0.557mintempt + 0.203totraint + 0.080humidityt – 1.549sunshinet + 0.786areat
(1.61)
(-2.01)*
(0.76)
(1.62)
(1.10)
(-0.10)
(2.17)*
Ytwholesale = 86.724 – 3.236maxtempt + 0.686mintempt + 0.203totraint + 0.066 humidityt - 1.734 sunshinet + 0.758areat
(1.69)
(-2.07)*
(0.92)
(1.59)
(0.89)
(-1.08)
(2.04)*
PONDS
Ytprod = - 77.052 + 1.064maxtemp t + 0.873mintempt + 0.042totraint - 0.006humidityt + 1.474sunshinet + 0.827areat
(-2.46)
(2.00)*
(2.17)*
(0.66)
(-0.14)**
(1.62)
(2.28)**
Ytwholesale = - 69.015 + 1.554maxtempt + 0.942mintempt + 0.022 totraint – 0.037humidityt + 0.964sunshinet + 0.742areat
(-1.96)
(1.74)
(2.10)*
(0.30)
(-0.81)
(0.95)
(1.84)*
R-squared
Adjusted R-squared
Standard error of regression
F-statistic
Breusch-Godfrey LM test
White test
Jarque-Bera normality test
Sum of squared residuals
Note: figures in paratheses are t-statistics.
* significant at the 10% level
** significant at the 5% level
*** significant at the 1% level
Freshwater Cages
Ytprod
Ytwholesale
0.64
0.65
0.36
0.39
1.05
1.07
2.32
2.51
0.46
0.49
1.41
1.55
1.05
0.87
8.75
9.19
Freshwater Ponds
Ytprod
Ytwholesale
0.63
0.63
0.41
0.40
0.62
0.69
2.88
2.78
0.57
1.18
0.32
0.40
0.37
0.30
3.82
4.74
In freshwater aquaculture system, the climate indicators especially temperature was mostly
influence to the total production and the total wholesale value. The temperature of water affect directly to
the quantity of oxygen dissolved in the water, evaporation and aquaculture productivity (Kutty, 1987).
The aquaculture species are growing dynamically in the minimum and maximum tolerance limit of
temperature and survive in optimal temperature. However, the rapid temperature variation will affect
negative to the aquaculture species growth due to the less dissolved oxygen in the warm water. The
change of temperature will change the feeding pattern, nutrient and growth of fish because it doubles the
rate of metabolism, chemical reaction and oxygen consumption (Tidwell et. al., 1999). The fish will
experience stress and disease threat when the temperature increases to the maximum tolerance or
fluctuates suddenly. The modification of the biophysical condition due to the temperature will affect the
loss of production or unproductive growth of fisheries. It will reduce the returns of aquaculture production
to the farmers and increase the operation cost of the farm.
5.3 Adaptation options by the Sarawakian aquaculture farmers
A two way contingency table analysis was conducted to evaluate whether farmers education
background, income from aquaculture, income from off-farm and number of years operating aquaculture
8
had significant relationship to the willingness to pay for aquaculture insurance, the use of technology in
production and the importance of climate information.
The results in the table 3 show the importance of climate change information system was
significant related to the income from aquaculture and the number of operating years. The table shows
that 16 farmers from different level of aquaculture income answered that climate change information
system is important for them while 25 farmers answered not important. The Chi-squares analyses reveal a
significant association between the income from aquaculture to the importance of climate change,  2 (2,
N=41) = 14.6, p<.05. While for the number of operating years show the significant association to the
importance of climate information system where  2 (2, N=41) = 8.42, p< .10. The table shows that 13
farmers who involved in the range of 1-10 years and 3 farmers who involved in the range of 11-20 years
in aquaculture activities expect that climate change information system is important to their production.
However, the farmers who involved more than 20 years in aquaculture sector answered “no” to the
importance of climate change information system. The reason is their long experiences in aquaculture
activities enable them to predict the changing patterns of weather and climate seasons through the
personal observation.
The chi-square results were supported by the qualitative information given by the farmers during
the interview session. It is verified that the farmers who are intensively involved in aquaculture
production believed that the improvement of information system on climate warning is important to help
them prepare in any possible uncertainty. The farmers mostly observed the climate condition by using
their predictions where sometimes is not persistence. There are also few farmers reported experiencing
the severe loss of production in several times due to wrong prediction of weather and flooded events. As
similar to other elements, the numbers of operating years influenced to the awareness towards the
important of climate information by the related agencies.
However, the education and income from off-farm activities do not influence to any adaptation
options among the producers. The similar results are also shown by the income from aquaculture and the
number of operating years to the options of willingness to pay and technology used. These results are
contrast to the qualitative information gained from the interviews. The farmers who had been in the
industry for longer time demand production security programme which to protect the production risks and
cover the severe lost of production due to the climate change risk. Most of farmers had experienced the
severe loss of production due to the climate and disease threats. Thus, they believed the programme such
as agriculture insurance will help to at least maintain their welfare. There are also few farmers who
probably don’t understand the relationship between insurance and production loss and not willing to pay
for the agriculture insurance whereby they are exposed to risk. Thus, the education plays an important
role to increase the farmers’ perception and knowledge towards the function of agriculture insurance. The
experienced farmers believed that technology helps in increasing their production and reducing the risk
due to the fluctuation of climate. Most of the farmers who had long time involved in aquaculture sector
owned the technologies such as machine and equipment to manage their farms. The level of education is
also influencing to the farmers’ awareness towards the benefit of technology to their production. They are
also able to diversify their farm activities by producing the fertilizers for their farm used and also sell to
the market. However, some of them are at the same time still practicing the traditional ways to conserve
their production from the diseases and other environmental threats.
9
Table 3 Chi-square Results (adaptation option of the farmers)
Not WTP
WTP
Characteristics
Education
No school
Primary school
Religious school
Secondary school
Cert / diploma
Degree
Others
N
%
N
%
1
3
0
4
0
0
0
33.3
20.0
0
18.2
0
0
0
2
12
0
18
1
0
0
66.7
80.0
0
81.8
100
0
0
2
value
Not used
tech
N
%
used tech
N
%
2
6
0
5
1
0
0
1
9
0
17
0
0
0
33.3
60.0
0
77.3
0
0
0
66.7
40.0
0
22.7
100
0
0
0.63
Aquaculture
Income
< RM 500
RM 501-1000
RM 1001 - 2000
RM 2001 - 3000
RM 3001 - 4000
RM 4001 - 5000
>RM5001
0
0
0
0
0
0
8
0
0
0
0
0
0
30.8
0
4
5
2
3
1
18
0
100
100
100
100
100
69.2
5
0
1
1
0
0
0
1
55.6
0
11.1
20.0
0
0
0
20.0
4
7
8
4
1
2
3
4
0
1
0
2
1
0
10
44.4
100
88.9
80.0
100
100
100
80.0
value
Not impotant
of climate info
N
%
1
11
0
12
1
0
0
33.3
73.3
0
54.5
100
0
0
Important of
climate info
N
%
2
4
0
10
0
0
0
0
25.0
0
100
33.3
0
38.5
0
3
5
0
2
1
16
0
75.0
100
0
66.7
100
61.5
44.4
42.9
33.3
20.0
0
50
0
40.0
5
4
6
4
1
1
3
3
0
2
0
2
1
0
20
55.6
57.1
66.7
80.0
100
50
100
60.0
11.0
Value
2.95
0
50
0
100
33.3
0
76.9
0
2
5
0
2
1
6
0
50
100
0
66.7
100
23.1
7.33
4
3
3
1
0
1
0
2
2
66.7
26.7
0
45.5
0
0
0
4.84
5.73
Off-farm Income
Not applicable
< RM 500
RM 501-1000
RM 1001 – 2000
RM 2001 – 3000
RM 3001 – 4000
RM 4001 – 5000
>RM5001
2
14.6**
8
5
4
2
1
0
3
2
88.9
71.4
44.4
40.0
100
0
100
40.0
1
2
5
3
0
2
0
3
11.1
28.6
55.6
60.0
0
100
0
60.0
3.48
11.84
Operating years
1-10 years
11 – 20 years
21 – 30 years
31 – 40 years
>40 years
3
2
1
1
1
13.0
20.0
20.0
50
100
20
8
4
1
0
87.0
80.0
80.0
50
0
7
4
1
2
0
5.92
30.4
40.0
20.0
100
0
16
6
4
0
1
69.6
60.0
80.0
0
100
10
7
5
2
1
5.11
43.5
70.0
100
100
100
13
3
0
0
0
56.5
30.0
0
0
0
8.42*
Note: * p<0.10
**p<0.05
Conclusions
The results implicate that climate change increase the risks to aquaculture production and reduce
income livelihood among aquaculture producers. The maximum temperature and relative humidity
constitute major factors that affect Sarawak’s aquaculture sectors. Similarly, the results also show that
climate change have a more significant impact on ponds aquaculture system as compared to cages system.
The ponds aquaculture system is more sensitive to the change of temperature and humidity because they
are conducted in controlled environment that depend on stored water which may be influenced by the
soils contents. As such, the problem of water quality is a major concern among pond based producer
while cages water systems are conducted in natural environment of fisheries ecology. Thus, the impacts
of climate change are mostly affecting ponds aquaculture system. Evident from the study indicate that
some of the farmers having limited capital resource may be unable to survive the impact of environmental
factors thorough higher fertilizers and feeding cost. Nevertheless, income stabilization as well as long
experience of farm operation forms the basis for adaptation strategy among the producers. In the long run,
10
an effective climate information system is needed to help the farmers in choosing appropriate adaptation
measures to reduce risk exposure to climate change variation.
References
Akegbejo-Samsons, Y. (2009) Climate Change Impacts on Fisheries production in Land-water Interface.
In IOP Conference series: Earth and Environmental Sciences 6(2009) 292022. 2009 IOP
Publishing Ltd.
Anon (2003) Annual Fisheries Statistics Volume 1, 2003. Department of Fisheries Malaysia, Malaysia:
Ministry of Agriculture and Afro-Based Industry.
Beach, R.H. and Viator, C.L. (2008) The Economics of Aquaculture Insurance: An Overview of the
U.S. Pilot Insurance Program for Cultivated Clams. Aquaculture Economics and Management,
12: 25-38.
Beattie, B.R. and Taylor, C. R. (1995) The Economics of Production. Florida: Krieger Publishing
Company.
Burton, I. (1997) Vulnerability and Adaptive Response in the Context of Climate and Climate Change.
Climatic Change, 36: 185-196.
Canadian Institute for Climate Studies (CICS) (2000) Aquaculture and Climate Change in Canada: A
Discussion
Paper.
Retrieved
on
February
6,
2009.
from
http://www.cics.uvic.ca/workshop/Aquaculture&climate -in-Cda.htm.
Chamhuri, S. Md. Mahmudul. A., Md. Wahid, M. and Abul Quasem, A. (2009) Impacts of Climate
Change on Agricultural Sustainability and Poverty in Malaysia.
Coble, K.H., Knight, T.O., Patrick, G.F. and Baquet, A.E. (2001) Understanding Limited Resource
Farmer’s Risk Management Decision Making: Summary and Preliminary Analysis. In A Report
from Understanding Farmer risk Management Decision Making and Educational Needs Research
Project. Research Report 2001-003. Department of Agricultural Economics, Mississippi State
University.
Edwards, P. (2000) Aquaculture, Poverty Impacts and Livelihoods. Natural Resource Perspectives, 56, 8.
FAO. (2008) Climate Change Adaptation and Mitigation in the Food and Agriculture Sector. Technical
Background Document from the Expert Consultation held on March 5-7, 2008. In High-level
Conference on Food Security: The Challenges of Climate Change and Bioenergy, June 3-5, 2008,
Rome.
Fankhauser, S., Smith, J. B., & Tol, R. S. J. (1999) Weathering Climate Change: Some Simple Rules
to Guide Adaptation Decisions. Ecological Economics, 30(1), 67-78.
Farabi Sheikh Said al Jabri (2009) "Bersedia hadapi El Nino." In Utusan Malaysia. Kuala Lumpur, 15th
June 2009.
11
Green, S. B., and Salkind, N. J. (2008) Using SPSS for Windows and Macintosh: Analyzing and
Understanding Data. United States: Pearson Prentice Hall.
Hambal, H., Mohd. Akhir, A. and Saniah, Y. (1994) Environmental Issues on Aquaculture Development
in Malaysia. Working papers of the Fisheries Research Institute, Department of Fisheries,
Malaysia.
Heltberg, R., Siegel, P. B., & Jorgensen, S. L. (2009) Addressing Human Vulnerability to Climate
Change: Toward a ‘no-regrets’ Approach. Global Environmental Change, 19(1), 89-99.
Howden, S. M., Soussana, J. F., Tubiello, F. N., Chhetri, N., Dunlop, M., and Meinke, H. (2007)
Adapting Agriculture to Climate Change. Proceedings of the National Academy of Sciences,
104(50), 19691.
Kelly, P. M., & Adger, W. N. (2000) Theory and Practice in Assessing Vulnerability to Climate Change
and Facilitating Adaptation. Climatic Change, 47(4), 325-352.
Kutty. M. N. (1987) Site Selection for Aquaculture: Climatic Factors. Paper presented at African
Regional Aquaculture Centre, Port Harcourt, Nigeria. Retrieved on July 21, 2010 from
http://www.fao.org/docrep/field/003/AC171E/AC171E00.HTM
Lee, N., Honh, T. C. and Ling, T. Y. (2002) Assessment of Brackish Shrimp Farming in Sarawak and Its
Impacts to the Environment. In Proceedings of Borneo Research Council Seventh Biennial
International Conference, 1-17.
Lungren, R., Staples, D., Funge-Smith, S., and Clausen, J. (2006) Status and Potential of Fisheries and
Aquaculture in Asia and the Pasific 2006, Bangkok: Food and Agriculture Organization of the
United Nations.
Malaysia (2008). Mid-Term Review of the Ninth Malaysia Plan 2006-2010. Putrajaya: The Economic
Planning Unit, Prime Minister’s Department.
Mazuki, H. and Subramaniam, K. (2005) Shrimp Farming in Malaysia. In Sulit, et. al (eds.), Regional
Technical Consultation on the Aquaculture of P. vannamei and Other Exotic Shrimps in
Southeast Asia. Manila, Philippines, 1-2 March 2005.
Meuwissen M.P.M., Huirne, R.B.M. and Hardaker, J.B. (2001) Risk and Risk Management: An
Empirical Analysis of Dutch Livestock Farmers. Livestock Production Science, 69, 43-53.
Miod, M. C., Ling, T. Y., Lee, N., Norhadi, I., Emang, J. J. J. (2009) Impacts of Aquaculture on the
Water Quality of Santubong River, Sarawak.
Mohd. Fariduddin, O. (2006) Recent Report on Coastal / Marine Aquaculture Status in Malaysia.
Country Report. Department of Fisheries Malaysia. Paper retrieved from http://library.enaca.org
on March 12, 2009.
Mustafa K. B. (2007) Climate Change – Its Effects on the Agricultural Sector in Malaysia. Retrieved
from: http://www.met.gov.my/files/ClimateChange2007/session1b/8%20MustafaKamal_a.doc.
12
Oguntuga, O. A., Adesina, B. T., & Akinwole, A. O. (2009) The Challenges of Climate Change in
Fisheries and Aquaculture: Possible Adaptation Measures in Nigeria. Capacity Development and
Career Prospects in Conservation Science, 56.
Ong, J.E. (2001) Vulnerability of Malaysia to Sea-level Change. Centre for Marine and Coastal Studies.
Paper retrieved from www.survas.mdx.ac.uk/pdfs/3ong.pdf on March 12, 2009.
Patrick, G. R., Wilson, P. N., Barry, P. J., Boggess, W. G., & Young, D. L. (1985) Risk Perceptions
and Management Responses: Producer-generated Hypotheses for Risk Modeling. Southern
Journal of Agricultural Economics, 17(2), 231-238.
Patrick, G. F., & Musser, W. N. (1997) Sources of and Responses to Risk: Factor Analyses of Largescale US Cornbelt Farmers. Risk management strategies in agriculture, 7.
Safa, M.S. (2004) Potential Fishery Industry Activities and Financial Aspects of East Malaysian Marine
Fisheries. Selangor: Universiti Putra Malaysia. Paper retrieved on March 8, 2009 from
http://mpra.ub.uni-muenchen.de/10887/1/Safa.pdf.
Sen, A. (1981) Poverty and Famines: An Essay on Entitlement and Deprivation. Oxford: Clarendon Press.
Schjolden, A. (2004) Towards Assessing Socioeconomic Impacts of Climate Change in Norway:
Sensitivity in the Primary Sectors: Fisheries, Agriculture and Forestry. CICERO Report 2004: 03.
Center for International Climate and Environmental Research.
Shariff, M., Yusoff, F.M. and Gopinath, N. (1997) Aquaculture in Malaysia: Current Trends and
Future Outlook. In Proceedings of Second International Seminar on Fisheries Science in Tropical
Area, Tokyo, August 19-22, Japan, 45-51.
Sugiyama, S., Staples, D., & Funge-Smith, S. (2004) Status and Potential of Fisheries and Aquaculture in
Asia and the Pacific. RAP Publication, 25, 2004–2025.
Sulit, V. T., Aldon, M. E. T., Tendencia, I. T., Ortiz, A. M. J., Alayon, S. B. and Ledesma, A. S. (2005)
Regional Technical Consultation on the Aquaculture of P. Vannamei and Other Exotic Shrimps in
Southeast Asia. Manila, Philippines, 1-2 March 2005.
Sulong, T. (2008) "100 penternak ikan rugi RM1 juta." In Utusan Malaysia Kuala Lumpur, 6th December
2008.
Tan, C. K. (1998) Overview of Aquaculture in Malaysia. In Nagaraj and Singh (eds.) Aquaculture
Practices in Malaysia. Occasional Publication No. 9. Kuala Lumpur: Malaysian Fisheries Society.
Tidwell, J. H., Coyle, S. D., Evans, J., Weibel, C., McKinney, J., Dodson, K., and Jones, H. (1999) Effect
of Culture Temperature on Growth, Survival and Biochemical Composition of Yellow Perch
Perca flavescens. Journal of the World Aquaculture Society, 30(3), 324-330.
Wheater, C. P., and Cook, P. A. (2000) Using Statistics to Understand the Environment. London:
Routledge.
World Bank. (2010) World Development Report 2010: Development and Climate Change. New York:
The World Bank.
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