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WATER QUALITY AND PHOSPHORUS BUDGET MODEL FOR ESTIMATING
THE CARRYING CAPACITY FOR FISH REARING AT BATANG AI
RESERVOIR, LUBOK ANTU, SARAWAK
Leong Chui Kit
Bachelor of Science with Honours
(Aquatic Resource Science and Management)
2012
Faculty of Resource Science and Technology
Water Quality and Phosphorus Budget Model for Estimating the Carrying Capacity for
Fish Rearing at Batang Ai Reservoir, Lubok Antu, Sarawak
Leong Chui Kit
This dissertation is submitted in partial fulfillment of the requirements for the degree of
Bachelor of Science with Honours
Aquatic Resource Science and Management Programme Department of Aquatic Science
Faculty of Resource Science and Technology Universiti Malaysia Sarawak
2012
I
ACKNOWLEDGEMENT
First and foremost, I would like to express special appreciation and deepest gratitude to my
supervisor, Professor Dr. Lee Nyanti, co-supervisors, Associated Professor Dr. Ling Teck
Yee, and Dr. Aazani Mujahid who have dedicated his time and guided me from the
beginning until the completion of this project.
Secondly, I would like to thanks all lab assistants who have been involved in the planning,
laboratory and fieldtrip for this project, especially Mr. Zaidi Ibrahim, Mr Mohd Norazlan
Bujang Belly, Mr. Mustafa Kamal @ Harris Norman, Mr. Richard Toh, and Mr. Syaifudin
Haji Bojeng.
My appreciation also goes to my supportive friends, especially Khoo Yen Nee, who help
me during fieldtrip, Lee Xue Li, Ng Chiew Tyiin, Liaw Sze Chieng, and Nurrin Nabilah
Teoh bt Ali Teoh, Hor Jun Yen, and all my other coursemates who had advice and help me
during this project.
Last but not least, my gratefulness to my family members, namely Leong Heng Kai, Yong
Yoon Chan, Leong Chui Mun, and Leong Chui Wah for their love, and endlessly
supported me in order for me to complete my final year project.
II
DECLARATION
I, Leong Chui Kit, final year student of Aquatic Resource Science and Management hereby
declare that this thesis is my own work and effort with the guidance of my supervisor,
Professor Dr. Lee Nyanti. No part of the thesis has previously been submitted for any other
degree, university or institution of higher learning.
………………………………
(Leong Chui Kit)
Aquatic Resource Science and Management
Faculty of Resource Science and Technology
Universiti Malaysia Sarawak
III
TABLE OF CONTENTS
Acknowledgement ……...………………………………………………….. I
Declaration ………………………………………………………………….
II
Table of Contents …………………………………………………………... III
List of Abbreviations ……………………………………………………….
V
List of Tables and Figures …………………………………………………..
VI
Abstract / Abstrak …………………………………………………………..
1
1.0 Introduction …………………………………………………………….
2
2.0 Literature Review……………………………………………………….
2.1 Overview of aquaculture ……………………...……………………..
2.1.1 Importance of aquaculture and cage culture .…………………..
2.1.2 Impacts of aquaculture and cage culture ……………………….
2.1.3 Problems of aquaculture and cage culture
in other countries………………………………………………..
2.2 Water quality for aquaculture activity………………………………..
2.2.1 Temperature …………………………………………………….
2.2.2 pH ………………………………………………………………
2.2.3 Dissolved oxygen (DO) ………………………………………...
2.3 Phosphate loading ……………………………………………………
2.3.1 Phosphorus from fish feed and sediments ……………………...
2.3.2 Relationship between phosphorus and chlorophyll a ……….....
2.3.3 Carrying capacity model ………………………………………..
2.3.4 Phosphorus modelling…………………………………………..
4
4
4
5
6
6
6
7
7
8
8
9
9
10
3.0 Materials and Methods ………………………………………………….
3.1 Sampling location…………………………………………………….
3.2 In-situ parameter measurement ……………………………………...
3.3 Water sample collection ……………………………………………..
3.3.1 Biochemical oxygen demand in five days (BOD5) …………….
3.3.2 Total suspended solids (TSS) …………………………………..
3.3.3 Chlorophyll a …………………………………………………...
3.3.4 Total phosphorus ……………………………………………….
3.3.5 Orthophosphate …………………………………………………
3.4 Modelling carrying capacity …………………………………………
3.5 Statistical analysis …………………………………………………...
10
10
11
12
12
13
13
14
15
15
17
18
IV
4.0 Results ………...………………………………………………………...
4.1 Water quality…………………………………………………………
4.1.1 In-situ parameters ………………………………………………
4.1.2 Ex-situ parameters ……………………………………………...
4.2 Modelling carrying capacity………………………………………….
18
18
35
46
5.0 Discussion ………………………………………………………………
5.1 Water quality ………………………………………………………..
5.2 Carrying capacity model……………………………………………..
6.0 Conclusion and Recommendation ……………………………………...
7.0 References ………………………………………………………………
49
49
53
55
56
8.0 Appendix ……………………………………………………………….. 60
V
LIST OF ABBREVIATIONS
BOD5 Biochemical Oxygen Demand in 5 Days
DO Dissolved Oxygen
GPS Global Positioning Unit
NTU Nephelometric Turbidity Unit
PO43-
Orthophosphate
TP Total Phosphorus
TSS Total Suspended Solids
TDS Total Dissolved Solids
mg/L Milligram per Litre
mgm-3
Milligram per cubic meter
µS MicroSiemen
VI
LIST OF TABLES
Table No. Title
Page
1 The information of each sampling station
10
2 Some of the morphometric and hydrologic characteristics in
Batang Ai reservoir
16
3 Depth and transparency for October, November 2011, and April
2012
18
4 Comparison of mean pH by depth for three sampling months
19
5 Comparison of mean pH by sampling months
20
6 Comparison of mean temperature by depths
20
7 Comparison of mean temperature by sampling months
22
8 Comparison of mean BOD5 by stations for two sampling months
26
9 Comparison of mean BOD5 by depths for two sampling months
26
10 Comparison of mean orthophosphate by stations and depths for
three sampling months
41
11 Comparison of mean orthophosphate by depths for three sampling
months
42
12 Comparison of mean orthophosphate among station for three
sampling months
42
13 The data for carrying capacity model
46
14 Carrying capacity model based on Boyd and Beveridge percentage
of phosphorus in feed and fish
48
VII
LIST OF FIGURES
Figure No.
Title Page
1 Sampling stations at Batang Ai, Lubok Antu, Sarawak
11
2 Temperature profile at Station 4 in November 2011
22
3 Temperature profile at Station 4 in April 2012
22
4 Comparison of mean dissolved oxygen in October 2011 (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
25
5 Comparison of mean dissolved oxygen in November 2011 (Bar
from same group with same alphabet are not significantly different
at 5% level of significant)
25
6 Comparison of mean dissolved oxygen in April 2012 (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
25
7 Comparison of mean dissolved oxygen by sampling months (Bar
from same group with same alphabet are not significantly different
at 5% level of significant)
25
8 Comparison of mean conductivity in October 2011 (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
29
9 Comparison of mean conductivity in November 2011 (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
29
10 Comparison of mean conductivity in April 2012 (Bar from same
group with same alphabet are not significantly difference at 5%
level of significant)
29
11 Comparison of mean conductivity by sampling months (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
29
12 Comparison of mean TDS in October 2011 (Bar from same group
with same alphabet are not significantly different at 5% level of
significant)
31
VIII
13 Comparison of mean TDS in November 2011 (Bar from same group
with same alphabet are not significantly different at 5% level of
significant)
31
14 Comparison of mean TDS by station for two sampling months (Bar
from same group with same alphabet are not significantly different
at 5% level of significant)
31
15 Comparison of mean turbidity in October 2011 (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
34
16 Comparison of mean turbidity in November 2011 (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
34
17 Comparison of mean turbidity in April 2012 (Bar from same group
with same alphabet are not significantly different at 5% level of
significant)
34
18
Comparison of mean turbidity by sampling months (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
34
19 Comparison of mean TSS in October 2011 (Bar from same group
with same alphabet are not significantly different at 5% level of
significant)
37
20 Comparison of mean TSS in November 2011 (Bar from same group
with same alphabet are not significantly different at 5% level of
significant)
37
21 Comparison of mean TSS in April 2012 (Bar from same group with
same alphabet are not significantly different at 5% level of
significant)
37
22 Comparison of mean TSS by sampling months (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
37
23 Comparison of mean chlorophyll a in October 2011 (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
40
IX
24 Comparison of mean chlorophyll a in November 2011 (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
40
25 Comparison of mean chlorophyll a in April 2012 (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
40
26 Comparison of mean chlorophyll a by sampling months (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
40
27 Comparison of mean total phosphorus in October 2011 (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
45
28 Comparison of mean total phosphorus in November 2011 (Bar from
same group with same alphabet are not significantly different at 5%
level of significant)
45
29 Comparison of mean total phosphorus in April 2012 (Bar from same
group with same alphabet are not significantly different at 5% level
of significant)
45
30 Comparison of mean total phosphorus by sampling months (Bar
from same group with same alphabet are not significantly different
at 5% level of significant
45
1
Water Quality and Phosphorus Budget Model for Estimating the Carrying Capacity for
Fish Rearing at Batang Ai Reservoir, Lubok Antu, Sarawak
Leong Chui Kit
Aquatic Resource Science and Management Faculty of Resource Science and Technology
Universiti Malaysia Sarawak
ABSTRACT
Fish cage culture in reservoir developed rapidly in order to meet the demand of fish for consumption. Phosphorus
loading from fish cage culture activities could cause adverse impacts on the surrounding water bodies.
Phosphorus budget model was used to estimate the maximum production from fish culture activities. The aims of
this study were to determine the water quality and estimate the carrying capacity for fish rearing activities in
Batang Ai reservoir, Sarawak. Carrying capacity of the reservoir was calculated based on Dillon and Rigler’s
phosphorus budget model. Water quality parameters were measured at 5 stations, at subsurface, 10 m, and 20 m
depths in October, November 2011 and April 2012 and at subsurface for station 6 in October, November 2011,
and April 2012. Results show that chlorophyll a ranged from 0.38 to 6.02 mgm-3, orthophosphate ranged from
0.01 to 0.27 mg/L, and total phosphorus from 0.03 to 0.24 mg/L. The higher concentration of orthophosphate and
chlorophyll a at station 4 and 5 is due to sewage from longhouse community flushed by rain water in station 4
and effluent from fish culture in station 5. The carrying capacity was estimated at 5,948 and 10,641 tonnes per year based on the different phosphorus content in fish and feed. The estimated value was about 8 to 14 times
higher than the current fish production at Batang Ai reservoir in 2011. Therefore, it is concluded that future
expansion of cage culture activities in Batang Ai reservoir is still feasible.
Key words: Fish cage culture, phosphorus loading, carrying capacity
ABSTRAK
Ternakan sangkar ikan di takungan berkambang pesat untuk menampung permintaan ikan sebagai makanan.
Pemuatan fosforus dari ternakan sangkar ikan boleh memberi impak negatif kepada perairan berdekatan. Model
bajet fosforus digunakan untuk menganggar hasil pengeluaran ikan maksimum dari aktiviti ternakan ikan.
Objektif kajian ini adalah untuk menentukan kualiti air dan menganggar kadar daya tampungan untuk aktiviti ternakan ikan di takungan Batang Ai, Sarawak. Kadar daya tampungan di takungan Batang Ai dikira
berdasarkan Dillon dan Rigler model bajet fosforus. Parameter kualiti air diukur pada Oktober dan November
2011 dan April 2012 di 5 stesen, di permukaan air, kedalaman 10 m, dan 20 m dan pada stesen 6 diukur di
permukaan air. Keputusan menunjukkan bahawa klorofil a adalah berjulat diantara 0.38 hingga 6.02 mgm-3,
orthofosfat berjulat diantara 0.01 hingga 0.27 mg/L, dan jumlah fosforus berjulat diantara 0.03 hingga 0.24
mg/L. Orthofosfat dan klorofil a adalah tinggi di stesen 4 and 5 disebabkan kumbahan dari komuniti di hulu
megalir bersama air hujan di stesen 4 dan kumbahan dari sangkar ikan di stesen 5. Berdasarkan kandungan
fosforus dalam ikan dan makanan ikan yang berlainan, kadar daya tumpagan adalah dianggarkan sebanyak
5,948 dan 10,641 tan metric setahun. Pengaggaran ini adalah 8 hingga 14 kali lebih tinggi daripada hasil
pengeluaran ikan di takungan Batang Ai pada tahun 2011. Kesimpulannya, pengembangan aktiviti ternakan
sangkar ikan pada masa depan di takungan Batang Ai masih boleh dilaksanakan.
Kata kunci: Ternakan sangkar ikan, pemuatan fosforus, kadar daya tumpangan
2
1.0 Introduction
Batang Ai reservoir is one of the Aquaculture Industrial Zone (AIZ) in Sarawak.
Batang Ai was dammed in 1984 for the hydro power generation (Pusin, 1995). After the
construction of the dam, the resulting reservoir was developed for fish culture activities (Pusin,
1995). Water quality is the main factor that should be monitored consistently in an aquaculture
system. The input of artificial feeds in cage aquaculture site may cause water pollution (Guo &
Li, 2003).
During the past 20 years, cage aquaculture has been developed rapidly, but the high
global demand and globalization caused the changes in cage aquaculture subsector (FAO,
2007). The export of aquaculture production aids in foreign currency earnings and provide
food security, which ensure the food safety for human (FAO, 2010). Aquaculture sector is
beneficial to society in terms of economic, tourism, and protein source supply. However,
aquaculture has produced negative impacts on the environment, for example, the metabolic
waste from fish and the untreated effluent has polluted the water.
Phosphorus is important for growth and reproduction in fish (Martin, 1998). However,
the indigestible phosphorus from fish’s feed will be excreted as feces and the uneaten feed
which contains phosphorus will also be washed into water bodies. Eutrophication is a
phenomenon caused by the enrichment of nutrients such as nitrogen and phosphorus in water
body (Zhang et al., 2006). Phosphorus is known to be the main nutrient for lake eutrophication
to occur (Liu et al., 2006). This causes the blooms of phytoplankton and increase of respiration
rate by phytoplankton especially during night time. Dissolved oxygen in water will be reduced
3
during night time when photosynthesis is absent (Pusin, 1995). Therefore, eutrophication
occurs and changes the productivity in the lake.
Deterioration of water quality will affect the fish growth and feed conversion in
cultured species (De Silva & Amarasinghe, 2009). Therefore, water quality analysis will be
determined to ensure the safe production of fish culture. In terms of aquaculture, carrying
capacity can be defined as the maximum production from a particular species without
affecting the growth rates (Buyukcapar & Alp, 2006). The rapid development of aquaculture
sector in China caused adverse impact to environment, especially eutrophication in many
inland water bodies (De Silva & Amarasinghe, 2009). Besides that, the lack of awareness and
study on reservoir ecology and trophic dynamics, inadequate stocking and high exploitation
affected the overall fish yields from reservoirs in India (De Silva & Amarasinghe, 2009).
Assessment of carrying capacity not only can estimate the maximum production of
aquaculture, but it can be applied to ecosystem, watershed, and to the global extent (Byron &
Costa-Pierce, 2010). The reason for modelling total phosphorus level in Batang Ai reservoir is
to predict the impact from cage culture on the environment (Pusin, 1995). Carrying capacity
was calculated based on the Dillon and Rigler’s phosphorus budget model (Pulatsu, 2003).
The objectives of this study were to: (1) determine the upstream water quality that
flows into Batang Ai reservoir and the downstream water which flows out from reservoir, (2)
determine the suitability of the existing water body for cage culture activities, and (3) estimate
the carrying capacity for the fish rearing activity in Batang Ai reservoir.
4
2.0 Literature review
2.1 Overview of aquaculture
Aquaculture sector are growing rapidly worldwide. For example in Vietnam, more than half a
million people are involves in aquaculture sector (FAO, 2010). The dominated cage culture in
China was the culture of silver carp (Hypophthalmichthys molitrix), bighead carp (Aristichthys
nobilis) and polyculture practice (FAO, 2007). On the other hand, Sri Lanka was dominated in
semi-intensive monoculture practice, which is started in early 1980s (Bergquist, 2007). In
Malaysia, floating cage culture is well developed, especially for monoculture of grass carp
(Ctenopharyngodon idellas), river catfish (Mystus sp. and Pangasius sp.), and tilapia
(Oreochromis sp.) (Pusin, 1995). Sarawak has high potential in aquaculture activities since it
is drained by rivers and streams (Kusuadi, 2005), as well as the newly formed reservoir such
as Bakun. The potential freshwater area for aquaculture activities is large in Sarawak. The
existing Batang Ai reservoir has an area of 8,400 ha and Bakun Dam has an area of 70,000 ha.
The upcoming hydroelectric projects such as Murum Dam, Baleh Dam, and Baram Dam have
a reservoir area of 24,500 ha, 51,500 ha, and 38,900 ha respectively (Nyanti, 2010).
2.1.1 Importance of aquaculture and cage culture
Cage culture involves the activities of raising fish from juvenile to marketable size in the
water body which is enclosed for all sides (Pusin, 1995). The world supplied of captured
fisheries and aquaculture were about 142 million tonnes of fish in 2008, which is 46 percent of
the total food fish supply (FAO, 2010). Aquaculture is the fastest-growing sector with per
capita supply increasing from 0.7 kg in 1970 to 7.8 kg in 2008, with average annual growth
rate of 6.6 percent (FAO, 2010). Aquaculture sector provided job opportunities not only in
5
developing, but also in developed countries, as claim by international organizations such as
World Bank, WWF, and FAO 2002 (Bergquist, 2007). The production from aquaculture in
international trade as food and feed yield increased from 25 percent in 1976 to 39 percent in
2008 (FAO, 2010). In 2009, the production from aquaculture sector in Malaysia was
472,306.44 tonnes, that is 25.26 % of the total fish production in the country (Jabatan
Perikanan Malaysia, 2011). Besides that, aquaculture which includes cage culture also
provided large seafood supply, reduced poverty, and improved the nutrition value of human
(FAO, 2007). Aquaculture in Malaysia supply protein food, increase fish production, and
enhance the socio-economic development in the country (Kusuadi, 2005).
2.1.2 Impacts of aquaculture and cage culture
Despite the benefits from aquaculture sector, there are some impacts of aquaculture on our
surrounding environment. The worldwide mangrove forests have been exploited for about
one-third of its area because of urban development and the construction of aquaculture site
(Alongi, 2002). As a result, the operations of aquaculture farms caused habitat destruction or
alteration, water quality degradation, and negative impacts on wildlife (Mazur & Curtis, 2008).
The productivity of phytoplankton in lakes and reservoir is affected by phosphorus (Beveridge,
2004). The metabolic waste increased the blooms of phytoplankton and caused the depletion
of dissolved oxygen during night time (Pusin, 1995). The input of artificial feed and waste
matter caused eutrophication not only in the cages but in the entire lake (Guo & Li, 2003). In
addition, the high stocking densities in cage culture will increase the loading of organic matter
and nutrients (Bergquist, 2007).
6
2.1.3 Problems of aquaculture and cage culture in other countries
In Sri Lanka, the water quality in coastal and estuarine areas becomes deteriorate after the
coastal area is converted for shrimp farming (Bergquist, 2007). The government in Sri Lanka
has implemented a program of Best Management Practices (BMPs) in order to improve water
quality monitoring and management practice (Bergquist, 2007). In the mid-1970s, the Danube
Delta in Romania experienced high phosphorus loading of 100 - 150 mgm-3
and this caused
the growth of algae to destroy the habitat of pike (Esox lucius) and tench (Tinca tinca) (FAO,
2010). On the other hand, the accumulation of feces and uneaten feed from cage culture also
triggered the pollution of water (FAO, 2007). In Gaobazhou Reservoir, the water quality
deteriorated due to the large increase in large scale culture of the American channel catfish
(De Silva & Amarasinghe, 2009). For most of the Indian reservoirs, the abundance of plankton
and benthos are affected by the high fluctuations in water level (De Silva & Amarasinghe,
2009).
2.2 Water quality for aquaculture activity
2.2.1 Temperature
The optimal temperature for fish species to survive and live healthy is 25 ˚C to 30 ˚C
(Hilbrands & Yzerman, 2004). The reservoirs in the western part of China and Loess Plateau
have low productivity and slow fish growth due to low water temperature, high turbidity and
high salinity in water (De Silva & Amarasinghe, 2009). Water temperature in a temperate lake
undergoes rapid change in the depth of metalimnion, which is the intermediate layer between
cold hypolimnion bottom water and warm epilimnion surface water (Martin, 1998). However,
for tropical water, the difference in temperature between the surface and bottom layer is
7
smaller (Auluck, 2009). Most of the reservoirs in India do not show stable thermal
stratification, where temperature only decreased by 1 – 2 ˚C from surface to bottom layer (De
Silva & Amarasinghe, 2009). Previous study by Auluck (2009) in Batang Ai resevoir showed
that the decrement of temperature from 9 m to 19 m depth was 3.42 ˚C, while the depth below
19 m indicated only miniature changes in temperature. Previous study by Pusin (1995) showed
that thermocline in Batang Ai reservoir is approximately at 10 m depth.
2.2.2 pH
The optimal pH value for fish production is 6.5 to 9.0 (Masser, 1997). The pH value in the
bottom water, which is hypolimnion layer may be affected by hydrogen sulfide (Auluck,
2009). The low pH indicated high hydrogen sulfide content (Lawson, 1995). The un-ionized
hydrogen sulfide is toxic to fish, concentration which is less than 0.01 mg/L will inhibit
reproduction in fish (Lawson, 1995). Previous study by Auluck (2009) in Batang Ai reservoir
showed that pH for surface water is approximately 7.30 - 7.52 while at 27 m depth, the pH
value is approximately 7.06 - 7.10.
2.2.3 Dissolved oxygen (DO)
Normally, DO requirement for warm water species such as catfish (Clarias sp. and Mystus sp.)
and tilapia (Oreochromis mossambicus) are 4 mg/L and above (Masser, 1997). The gas
exchange of oxygen at the surface caused the lakes to absorb oxygen from the atmosphere
(Martin, 1998). In the bottom layer of lake which is hypolimnion, DO level is lower than
surface water epilimnion layer because the lack of photosynthesis activities and the high
respiration rate by decomposers which consume DO (Auluck, 2009). In India, DO level in the
reservoirs are higher during pre- and post-monsoon because of heavy rain fall (De Silva &
8
Amarasinghe, 2009). Previous study by Auluck (2009) in Batang Ai reservoir showed that DO
reading in surface water is around 6.63 mg/L to 8.03 mg/L and DO reading in 27 m depth is
around 4.23 mg/L to 5.68 mg/L.
2.3 Phosphate loading
Phosphorus is present in a variety of forms. In some of the fish farming activities, phosphorus
is the prominent factor that caused effects on the lake environment (Buyukcapar & Alp, 2006).
Phosphorus in water exists in the form of phosphate (PO43-
). Phosphate also exists as simple
form, which is orthophosphate. A lake with less than 10 mgm-3
of total phosphorus
concentration is categorized as oligotrophic, and total phosphorus concentration of more than
25 mgm-3
is categorized as eutrophic lake (Martin, 1998). Total phosphorus concentration
losses to environment are from uneaten fish feed pellet being washed out from fish cages
(Pusin, 1995). On the other hand, digestibility of nutrients in diet influences fish’s waste
(Lazzari & Baldisserotto, 2008). The phosphorus content in tilapia’s feed is 1.2 % (Boyd,
2004) and 1.3 % (Beveridge 2004). Phosphorus content of tilapia is 3.01 % (Boyd & Green,
1998) and 0.34 % (Beveridge, 2004). Deficiency of phosphorus in fish will affects metabolism
and growth of the fish (Sugiura et al., 2004).
2.3.1 Phosphorus from fish feed and sediments
The solid deposition from uneaten feed pellet will be retained on sediments or released into
water column (Shakouri, 2003). The release of phosphorus from uneaten fish food and feces
are influenced by temperature and pH (Kibria et al., 1997). The higher temperature and pH of
4.0 is the condition in which maximum release of phosphorus from fish food and feces (Kibria
9
et al., 1997). Phosphorus will be released into water column in anoxic sediments (Santos et al.,
2010). However, organic phosphorus tends to be absorbed by acidic soils (Liu et al., 2008).
2.3.2 Relationship between phosphorus and chlorophyll a
The increased of nutrient loading such as phosphorus and nitrogen in a lake caused the high
phytoplankton abundance. This will resulted in eutrophication in a lake. According to Dillon
and Rigler (1974), chlorophyll a can be used as a simple estimator to estimate phytoplankton
standing crop. The phosphorus easily integrated into biological cycles of lake if the
phosphorus loading into water is in soluble reactive phosphorus form, while it is less available
to phytoplankton if it is in the form of particulate and incorporated into inorganic particles
(Brett & Benjamin, 2008).
2.3.3 Carrying capacity model
Carrying capacity model is used to estimate the maximum fish production and reduce the
impact of cage culture on the lake (Buyukcapar & Alp, 2006). Besides that, from the carrying
capacity estimation, the population dynamics of fish or organism can be reviewed (Cross et al.,
2011). The nutrient loading model is widely used in predicting the impacts of phosphate
concentration on the water environment, as stated by Dillon & Rigler (1974). In the study on
the application of a phosphorus budget model estimating the carrying capacity of Kesikkopru
Dam Lake by Pulatsu (2003), the phosphorus budget model established by Dillon & Rigler
was used. This model basically predicts the increase of phosphate level on water from fish
culture activity (Pusin, 1995). The previous study was done by Pusin (1995) on cage culture
development in Batang Ai reservoir, Sarawak, Malaysia. This study will allow us to compare
carrying capacity and the maximum phosphate loading from aquaculture activity.
10
2.3.4 Phosphorus modelling
Phosphorus concentration in the lake or reservoir is mostly retained through sedimentation.
The concentration that we measured may not reflect the overall phosphorus concentration
(Saunders, 2008). The phosphorus concentration may be affected by the volume of the
reservoir. The large volume of reservoir can dilute the concentration (Saunders, 2008).
Phosphorus concentration in the outflow is almost stable and it is appropriate to be used to
estimate phosphorus concentration in reservoir (Saunders, 2008). Dillon & Rigler model was
widely used for modelling of phosphorus (Saunders, 2008).
3.0 Materials and Methods
3.1 Sampling location
Water samples were collected in October and November 2011 and April 2012 at Batang Ai
reservoir. The water quality was measured and water samples were collected at six stations
(Figure 1). All water samples were collected in triplicates at subsurface, mid layer (10 m) and
bottom layer (20 m). For station 6, depth and transparency were only measured in October
2011. Total Dissolved Solids (TDS) was measured in October and November 2011. The
information about each of the station is given in Table 1.
Table 1: The information of each sampling station
Station No. Coordinates Description of station
1 N 01˚ 12’ 45.8” E 111˚ 55’ 24.6” Approximately 500 m from Engkari River
2 N 01˚ 12’ 09.5” E 111˚ 56’ 50.3” Approximately 500 m from Batang Ai
3 N 01˚ 12’ 05.6” E 111˚ 55’ 47.9” The confluence between Engkari River
and Batang Ai
4 N 01˚ 10’ 43.1” E 111˚ 55’ 20.0” Approximately 500 m from station 3
5 N 01˚ 09’ 43.1” E 111˚ 50’ 09.7” In one of the cage culture site
6 N 01˚ 08’ 31.2” E 111˚ 52’ 14.5” Near the water outlet for power house
11
Figure 1: Sampling stations at Batang Ai, Lubok Antu, Sarawak
3.2 In-situ parameters measurement
The in-situ parameters such as pH, temperature, conductivity, TDS, and dissolved oxygen,
water depth, transparency, and turbidity were measured at five stations and at each station at
three depths. At station 6, all in-situ and ex-situ parameters were measured only at subsurface,
because this station was shallow and the water was well mixed. The pH, temperature,
conductivity, TDS, and dissolved oxygen were measured by using Eutech Multiparameter
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Series 600. Water depth was measured by using depth finder, transparency was measured by
Secchi Disc, turbidity was measured by Eutech turbidity instrument TN-100. Each of the
parameter was measured in triplicates.
3.3 Water sample collection
3.3.1 Biochemical oxygen demand in five days (BOD5)
BOD5 were measured in November 2011 and April 2012. Water samples at six stations were
collected by using Van Dorn Water Sampler. Water samples were collected at three depths.
The water samples in volume of 600 mL were mixed with distilled water in volume of 600 mL
to make dilution of water samples. The mixed water was shaken vigorously, and the initial
dissolved oxygen was recorded. The water was poured into BOD glass bottles in triplicates.
The bottles were filled completely and stopper was inserted into the BOD bottles. While
filling the bottles, special care has to be taken to avoid trapping of air bubbles. Then, the
bottles were wrapped with aluminium foil to avoid direct sunlight and prevent any
photosynthetic process. The bottles were placed in a cooler box for 5 days. The DO readings
were recorded again on the 5th day. Finally, BOD5 was calculated by using the following
formula (APHA, 1998):
BOD5 (mg/L) = D1 – D5
V
where:
D1 = Initial in-situ DO reading
D5 = Day 5 DO reading
V = Dilution factor
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3.3.2 Total suspended solids (TSS)
Water samples at six stations were collected by using Van Dorn Water Sampler and put into
1L of plastic bottle. Water samples at three depths were collected in triplicates. The bottles
were placed in a cooler box and brought back to the lab for total suspended solids analysis.
Prior to the analysis of TSS, the filter paper was dried in oven at 103 – 105 ˚C for overnight
and then weighted. Total suspended solids were calculated by deducting the final weight with
initial weight and divide by volume of water used in filtration.
3.3.3 Chlorophyll a
Water samples were collected at the six stations by using Van Dorn Water Sampler and put
into 1L of acid washed plastic bottle. Water samples were collected at three depths in
triplicates. In the lab, water samples were filtered by using vacuum filtration system after the
glass fiber filter 47mm diameter was placed on the top section of filter unit. Then, the filtered
substances were grinded by pestle and mortar, and 5-6 mL of acetone 90% was added. Then,
the sample was transferred into a capped centrifuge tube and 90% acetone was added to make
total volume to 10 mL. Next, the sample was centrifuged for 10 minutes under 3000 rpm.
After that, the chlorophyll a content was measured by using spectrophotometer. The extract
was transferred into a 1 cm cuvette and the extraction was measured at wavelength 750 nm,
664 nm, 647 nm, and 630 nm. Chlorophyll a concentrations in water samples were calculated
based on the following formula (APHA, 1998):
The concentrations of pigment in the extract were calculated as follows:
Ca = 11.85 (E664 – E750) – 1.54 (E647 - E750) – 0.08 (E630 – E750)