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7/25/2019 Modelling Fish Production in Los Banos Laguna - EnS 211 WX Revised - Final
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ENS 211 - WX
MODELING FISH PRODUCTION INLOS BAOS, LAGUNA
DEZILYN JOY MARI M. DOMIMAE ANNE P. GARDON
ERWIN P. QUILLOY
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The Nature and Science City of Los Baos is a first class
urban municipality in the province of Laguna. Based
from the latest census of the National Statistics Office,
the 56.5 sq.km. land area of Los Baos has beenpopulated by 101,884 individuals. The growing
population of the town put pressure to the local fisheries
resulting for the local fisherman to start putting up fish
cages along the shorelines to enhance fish productivity.
Aquaculture or fish farming is an age-long industry in
the Philippines that dates back to the pre-colonial period
in the 1500s (Rabanal, 2000). The Philippines was a net
exporter of fisheries products where in almost fifty percent of the total production came from the
aquaculture sector of the country. Having a portion of access to Laguna de Bay, fish farming hasbecome one of the main economic activities of the people in Los Baos. It was considered as a
major industry, contributing significantly to food security and livelihood of the people. Los Baos
has a total production area of 2.05 sq.km.
There are several ways of raising tilapia for production. Tilapias may be grown for fry production.
Others are used as breeders. For fish food production, tilapias are raised through grow-out methods
where the tilapia fingerlings are grown up to the market size of at least 100 g. Grow-out tilapia
production makes use of ponds, tanks, pens or cages to hold the fish until these are ready for
harvest. Fish are harvested through aquaculture and commercial fishing. In the municipality of
Los Baos, the BFAR IV-As extension office in Barangay Bambang houses nursing tanks where
fish particularly tilapia stock are stored for dispersal.
As the fish cages expanded over the lakeshore, the need for artificial feeds for growing the fish in
order to maximize their yield made such operation as a major contributor of nutrient enrichment
in the water therefor accelerating deterioration of the water quality. High concentration
ofnutrients in the water body leads to eutrophication of the lake. Nutrient such as nitrogen that
can be attributed from the excess fish food and waste, promotes excessive growth of algae in the
lake ecosystem and as the algae die and decompose, high level of organic matter and the
decomposing organisms deplete the dissolved oxygen in the water which eventually results to
death of the aquatic organisms primarily the fishes.
Rapid growth in the population results to an increase in demand for food. This applies to all food
sectors including the aquaculture industry. To be able to meet the demand, fish farmers tend to
engage in a more extensive fish farming practices.
Like any other body of water, its carrying capacity is determined by its biochemical
INTRODUCTION
http://en.wikipedia.org/wiki/Philippine_provincehttp://en.wikipedia.org/wiki/Laguna_(province)http://toxics.usgs.gov/definitions/nutrients.htmlhttp://toxics.usgs.gov/definitions/nutrients.htmlhttp://en.wikipedia.org/wiki/Laguna_(province)http://en.wikipedia.org/wiki/Philippine_province7/25/2019 Modelling Fish Production in Los Banos Laguna - EnS 211 WX Revised - Final
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characteristics. However, such efforts to increase production could results to increased fish
stocking thus increasing contribution to water pollution and eventually eutrophication and fish
kills.
The fish production is dependent on climate, feeding and fish stocking rate. With the changes on
these variables, fish productivity will be at risk and can affect the fish sufficiency of the
municipality and the carrying capacity of the lake. An appropriate stocking density of fish should
be determined to ensure sustainable fish production.
The main objective of the study is to develop a model of the fish production in Los Baos.Specifically, the study aims to:
1. Determine the sufficiency of tilapia supply in Los Baos based on the forecast of the model
2. Determine whether there is a need in fish importation
3. Determine the maximum stocking density that would not cause degradation of environment
Due to time constraints of the study specifically for data gathering, the model was not able toincorporate other factors of population growth such as influx of people from other neighboring
communities. Moreover, knife fish was the only species used to represent the predatory factor. In
addition, only nitrogen load from the feeds and fertilizer input for the fish stock was considered in
assessing the carrying capacity of the lake. Absorption of nitrogen by other aquatic flora and faunawere also not considered in the design and simulation of the model. Only Tilapia was focused on
the absorption of nitrogen.
In addition, the model was designed to project how long will a fixed stock of fish which are
already at market weight last considering that no restocking will be implemented and coupled with
the effects of external factors such as climatic variability and predatory factors.
zy
Theoretical fr amework
The conceptual model (Fig.1) illustrates the relationships among the locale dynamics, fish
population as well as nitrogen sedimentation. It can be noted that the population of locale puts
pressure on the demand for fish supply. This demand also pushes fish farmers to produce more to
STATEMENT OF THE PROBLEM
OBJECTIVES
METHODOLOGY
LIMITATIONS
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reach the quota for the fish considering the factors that could lead to losses in production.
However, such efforts to increase production could affect the sedimentation rate of nitrogen in the
lake since the feed input is dependent on the total fish biomass. The same goes for the nitrogen
absorption, which also depends on the biomass of the fish. The sedimentation of nitrogen, coupled
with other nutrients in the lake puts the lake at risk of eutrophication once the carrying capacity
for the nutrient is reached.
Figure 1. Conceptual Model
Fish Population
Locale Dynamics Nitrogen Sedimentation
Birth
rate
Death
rate
Total fish
demand
Locale
PopulationExcess Nitrogen
N removal
Carrying
capacity
Fish Stock
Eutrophication
N additionTotal fish
supply
Fish
weight
Birth rate Death rate Predation
Climate
N
conversion
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Var iables and assumptions
Locale Dynamics sector (on daily basis)
Variable Value Reference
Locale population 101,884 Socio-economic Profile of Los Baos,2010
Birth rate 3.30% Socio-economic Profile of Los Baos,2010Death rate 0.59% Socio-economic Profile of Los Baos,2010
Per capita tilapia
demand
2.74 g Pascual, 1993
Fish Production sector (on daily basis)
Production area 2,050,000 sq.m Socio-economic Profile of Los Baos,2010
Production methid Growout Assumed
Fish species Tilapia Assumed
Stocking density 4 per sq.m BFAR
Stocking type No restocking Assumed
Fish death rate 100% - eutrophied20% - typhoon
30% - predation20% - natural
BFAR
Initial fish weight 100 g Marketable size, BFAR
Growth rate 1.35 g per day (linear
phase)
Yi and Kwei Lin, 1996
Climatic variability 2% Assumed
Carrying capacity fornitrogen
2.26 mg per liter LLDA
Volume of lake 2,550,800,000 liters LLDA
Nitrogen Sedimentation sector (on daily basis)
Initial nitrogen 0 g Assumed
Nitrogen absorption
by fish
0.24 g per kg fish Avnimelech and Kochba, 2008
Other nitrogen loss 12.5% Boyd, 2001
Feeding rate 3% of the fish bodyweight at 32%
protein rating
Boyd,2004
Feed formulation 156.2 mg nitrogen
per kg protein in feed
Assumed
Feeding days 6 days a week Assumed
*Secondary data from BFAR and LGU were used for the variables and assumptions.
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Equations
Fish population
fish_stock(t) = fish_stock(t - dt) + (- fish_daily_death) * dtINIT fish_stock = 2050000*4
OUTFLOWS:
fish_daily_death = if (time=0) then 0 else (fish_stock*fish_death_rate)total_fish_death(t) = total_fish_death(t - dt) + (fish_daily_death) * dtINIT total_fish_death = 0
INFLOWS:
fish_daily_death = if (time=0) then 0 else (fish_stock*fish_death_rate)
carrying_cap = 2550800000*0.0022589666300567
climatic_variability = int(RANDOM(1, 50))
eutrophication = if(excess_N>carrying_cap)then 1 else 0
fish_death_rate = if (eutrophication = 1) then 1 else
if (climatic_variability = 1) then 0.2 else
if (predation_factor =1) then 0.3 else
0.175
fish_weight = if (time=0)then (fish_stock*0.1) else ((fish_stock*0.1)+(fish_stock*0.005*time))
predation_factor = int(random(1,10))
locale_population(t) = locale_population(t - dt) + (births - deaths) * dtINIT locale_population =
101884
INFLOWS:
births = locale_population*birth_rate
OUTFLOWS:
deaths = death_rate*locale_population
birth_rate = 0.0329815169672821
death_rate = 0.0059
fish_supply = fish_weight
total_fish_demand = if (time=0) then 0 else (0.0027397260273973*locale_population)
total_import = if(fish_supply>total_fish_demand)then (0) else (total_fish_demand-fish_supply)
total_supply = if(fish_supply>total_fish_demand)then(fish_supply)else (fish_supply+total_import)
excess_N(t) = excess_N(t - dt) + (N_addition - N_removal - conversion_to_volatile_form) * dtINIT
excess_N = 14000
INFLOWS:
N_addition = if (time=0) then 0 else
if (fish_weight = 0) then 0
else (feed_input)
OUTFLOWS:
N_removal = if (time=0) then 0 else (fish_weight*N_absorption)
conversion_to_volatile_form = 0.03*excess_N
feed_input = if (fertilizer_multiplier = 0.1) then
(fish_weight*1000*0.03*(6/7)*0.32*(.25/1.6))else (fish_weight*1000*fertilizer_multiplier*(6/7)*0.32*(.25/1.6))
fertilizer_multiplier = 0
N_absorption = 0.24
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F ish Production Model
The fish production in the municipality of Los Baos is represented by the Figure 2. The model is
designed to simulate the production of grow-out tilapia on the latter part of growing to finishing
stage where the average weight of the fish at tois 100 g (BFAR). A Tilapia which already reached
this weight can still be grown to a larger size, which could last for two months. The simulation isset to run on a daily basis. The forecast of this model will determine the day when fish importation
is needed. Moreover, this will also determine the amount of nitrogen being accumulated in the
lake. The model has three sectors: locale dynamics, fish production and nitrogen sedimentation.
The locale dynamics sector shows the population growth and mortality, as well as the daily
demand for fish. The total import for fish is also included to determine the amount of fish needed
to supply the insufficiency. An indicator is placed to show the status of tilapia sufficiency in the
municipality.
The fish production sector shows the stocking density of grow-out tilapia. It was assumed that the
tilapia production that the model will simulate is a semi-intensive culture, with a stocking densityranging from 3 to 5 fish per sq.meter (BFAR). Furthermore, a stocking density of 4 per sq.meter
was assumed for the simulation. Furthermore, the fish is said to be on its linear phase as it reaches
100g (Americulture, Inc.), where the growth is also linear with 1.35g per day growth rate (Yi and
Kwei Lin, 1996). Fish death rate is shown to be a function of predation factor, climatic variability
and eutrophication occurrence dealing 30%, 20% and 100% damage respectively (BFAR). Natural
death rate in the tilapia production may reach up to 20% (BFAR). For the model, it was assumed
that no restocking was done despite the losses.
Carrying capacity used in the model was based on the classification of the lake set by the Laguna
Lake Development Authority, in which the lake was determined as class C with a limit of 2.26 mgnitrogen per liter. An indicator for the eutrophication is placed to yield the current status of the
lake.
On the other hand, the nitrogen sedimentation sector shows the level of nitrogen that the tilapia
industry releases to the lake. The amount of nitrogen absorbed by the tilapia as well as the amount
of feed input to the cages or pens is determined by the fish weight from the fish production sector.
The total amount of feed for tilapia at the latter part of growing to finishing stage is about 2 % to
3 % of the fish biomass (BFAR). The excess nitrogen that goes to the lake is the difference of the
total feed input and the total absorbed nitrogen by the fishes, minus the amount of nitrogen
converted to volatile forms which goes to atmosphere.
It was noted that the amount of nitrogen that can be absorbed by tilapias is 24g nitrogen per
kilogram fish (Avnimelech and Kochba, 2008). Moreover, feed input is a function of a variable
feed multiplier. By default, the amount of feed is set at 3% of the body weight of the fish. Other
feed nitrogen loss attributed to conversion to volatile form is found to be around 12.5% (Boyd,
2001).
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Though the model can provide forecast of the daily supply of fish, it does not account the
consumption of the locale. Only the gross supply of tilapia for each day is yielded by the model.
Moreover, the model does not take into account other nitrogen sinks which may be attributed to
absorption of benthic species and aquatic plants. Indication of eutrophication as yielded by the
model implies that at that level of nitrogen, the lake may undergo eutrophication, provided that
the levels of other nutrients are high enough to induce algal blooms.
Figure 2. Fish production model
Simulation
The model was set to run from 0 to 60 simulation days at a simulation speed of 0.01902 real sec :
1 unit time. The duration time of 60 simulation days was based on the harvesting period of tilapiaculture where tilapia can be harvested for about two months from day of reaching marketable size
(Guerrero III, 2008). The stocking density was set to 4 fish per sq.m. as prescribed by the BFAR.
The fertilizer multiplier which represents the percentage of body weight of fish to be used in
determining feed input was set to 3%. Given a stocking density of 4 per sq.m, and fertilizer
multiplier of 3% data were collected. Table 1 presents the data for the entire simulation.
DISCUSSION
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Table 1. Data for stocking density of 4 fish per sq.m. and fertilizer multiplier of 3%.
Days Fish stockFish daily
death
Total fish
death
Fish supply
(kg)
Total fish
demand
(kg)
Locale
population
Total
import
(kg)
Eutrophication
status
Excess N
(kg)
N
addition
(kg)
N
remov
(kg)
0 8,200,000 0 0 820,000.00 0.00 101,884 0 0 14.00 0.00 0.0
1 8,200,000 1,435,000 0 861,000.00 286.69 104,643 0 0 13.58 1107.00 206.6
2 6,765,000 1,183,875 1,435,000.00 744,150.00 294.46 107,477 0 0 913.53 956.76 178.6
3 5,581,125 976,697 2,618,875.00 641,829.38 302.43 110,388 0 0 1664.29 825.21 154.04 4,604,428 805,775 3,595,571.88 552,531.38 310.62 113,377 0 0 2285.54 710.40 132.6
5 3,798,653 664,764 4,401,346.80 474,831.65 319.03 116,448 0 0 2794.76 610.50 113.9
6 3,133,889 548,431 5,066,111.11 407,405.56 327.67 119,601 0 0 3207.46 523.81 97.7
7 2,585,458 452,455 5,614,541.66 349,036.88 336.55 122,840 0 0 3537.26 448.76 83.7
8 2,133,003 373,276 6,066,996.87 298,620.44 345.66 126,167 0 0 3796.14 383.94 71.6
9 1,759,728 307,952 6,440,272.42 255,160.50 355.02 129,584 0 0 3994.52 328.06 61.2
10 1,451,775 254,061 6,748,224.75 217,766.29 364.64 133,093 0 0 4141.51 279.99 52.2
11 1,197,715 209,600 7,002,285.42 185,645.76 374.51 136,697 0 0 4244.99 238.69 44.5
12 988,115 172,920 7,211,885.47 158,098.33 384.66 140,399 0 0 4311.77 203.27 37.9
13 815,194 142,659 7,384,805.51 134,507.09 395.07 144,202 0 0 4347.74 172.94 32.2
14 672,535 117,694 7,527,464.55 114,331.03 405.77 148,107 0 0 4357.97 147.00 27.4
15 554,842 97,097 7,645,158.25 97,097.31 416.76 152,118 0 0 4346.79 124.84 23.3
16 457,744 80,105 7,742,255.56 82,394.00 428.05 156,237 0 0 4317.92 105.94 19.7
17 377,639 66,087 7,822,360.83 69,863.25 439.64 160,468 0 0 4274.54 89.82 16.7
18 311,552 62,310 7,888,447.69 59,194.94 451.55 164,814 0 0 4219.36 76.11 14.2
19 249,242 43,617 7,950,758.15 48,602.16 463.77 169,278 0 0 4154.68 62.49 11.6
20 205,625 35,984 7,994,375.47 41,124.91 476.33 173,862 0 0 4080.87 52.87 9.8
21 169,640 29,687 8,030,359.77 34,776.25 489.23 178,570 0 0 4001.45 44.71 8.3
22 139,953 24,492 8,060,046.81 29,390.17 502.48 183,406 0 0 3917.77 37.79 7.0
23 115,461 34,638 8,084,538.62 24,824.20 516.09 188,373 0 0 3830.97 31.92 5.9
24 80,823 14,144 8,119,177.03 17,781.05 530.07 193,475 0 0 3742.00 22.86 4.2
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25 66,679 11,669 8,133,321.05 15,002.76 544.42 198,714 0 0 3648.33 19.29 3.6
26 55,010 9,627 8,144,989.87 12,652.33 559.17 204,096 0 0 3554.57 16.27 3.0
27 45,383 7,942 8,154,616.64 10,665.09 574.31 209,623 0 0 3461.16 13.71 2.5
28 37,441 11,232 8,162,558.73 8,985.91 589.86 215,300 0 0 3368.48 11.55 2.1
29 26,209 4,587 8,173,791.11 6,421.18 605.84 221,130 0 0 3276.82 8.26 1.5
30 21,622 3,784 8,178,377.67 5,405.58 622.24 227,119 0 0 3185.23 6.95 1.3
31 17,838 3,122 8,182,161.57 4,548.80 639.10 233,270 0 0 3095.33 5.85 1.0
32 14,717 2,575 8,185,283.30 3,826.34 656.40 239,587 0 0 3007.23 4.92 0.9
33 12,141 2,125 8,187,858.72 3,217.44 674.18 246,075 0 0 2921.01 4.14 0.7
34 10,017 1,753 8,189,983.45 2,704.47 692.44 252,739 0 0 2836.75 3.48 0.6
35 8,264 1,446 8,191,736.34 2,272.51 711.19 259,584 0 0 2754.47 2.92 0.5
36 6,818 1,193 8,193,182.48 1,908.90 730.45 266,614 0 0 2674.21 2.45 0.4
37 5,624 984 8,194,375.55 1,602.97 750.23 273,834 0 0 2595.98 2.06 0.3
38 4,640 1,392 8,195,359.83 1,345.65 770.55 281,250 0 0 2519.78 1.73 0.3
39 3,248 568 8,196,751.88 958.20 791.42 288,867 0 0 2445.59 1.23 0.2
40 2,680 804 8,197,320.30 803.91 812.85 296,690 9 0 2373.23 1.03 0.1
41 1,876 328 8,198,124.21 572.12 834.86 304,725 263 0 2302.87 0.74 0.1
42 1,548 271 8,198,452.47 479.73 857.47 312,977 378 0 2234.38 0.62 0.1
43 1,277 223 8,198,723.29 402.16 880.69 321,453 479 0 2167.85 0.52 0.1
44 1,053 184 8,198,946.71 337.05 904.54 330,158 567 0 2103.24 0.43 0.0
45 869 152 8,199,131.04 282.41 929.04 339,099 647 0 2040.49 0.36 0.046 717 125 8,199,283.11 236.57 954.2 348,283 718 0 1979.58 0.30 0.0
47 591 104 8,199,408.56 198.13 980.04 357,715 782 0 1920.44 0.25 0.0
48 488 146 8,199,512.07 165.90 1,006.58 367,402.00 841 0 1863.03 0.21 0.0
49 342 60 8,199,658.45 117.84 1,033.84 377,352.00 916 0 1807.31 0.15 0.0
50 282 49 8,199,718.22 98.62 1,061.84 387,571.00 963 0 1753.22 0.13 0.0
51 232 41 8,199,767.53 82.53 1,090.60 398,067.00 1,008 0 1700.72 0.11 0.0
52 192 58 8,199,808.21 69.04 1,120.13 408,848.00 1,051 0 1649.79 0.09 0.0
53 134 23 8,199,865.75 49.00 1,150.47 419,920.00 1,101 0 1600.37 0.06 0.0
54 111 19 8,199,889.24 40.98 1,181.62 431,292.00 1,141 0 1552.41 0.05 0.0
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55 91 16 8,199,908.62 34.27 1,213.62 442,972.00 1,179 0 1505.88 0.04 0.0
56 75 13 8,199,924.62 28.65 1,246.49 454,968.00 1,218 0 1460.74 0.04 0.0
57 62 12 8,199,937.81 23.94 1,280.25 467,290.00 1,256 0 1416.94 0.03 0.0
58 50 9 8,199,950.25 19.40 1,314.92 479,944.00 1,296 0 1374.46 0.02 0.0
59 41 7 8,199,958.95 16.21 1,350.53 492,942.00 1,334 0 1333.25 0.02 0.0
Final 34 8,199,966.14 13.55 1,387.10 506,292.00 1,374 0 1293.27
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With the locale population reaching up to 506,292 after 60 days, the total fish demand was
observed to reach 1387.10 kg. However, the fish supplied by the tilapia industry can supply only
4.75 kg of Tilapia. To address the insufficiency, the municipality will need to import a total of
1,382.35 kg from other municipalities. The indicator changed from red to green state asimportation is being required.
It can be noted that the highest value of excess nitrogen during the simulation was 4,294.16 kg
which occurred in day 13. This is below the carrying capacity of the lake for nitrogen for the lake
which is 5762.17 kg, thus the indicator remained on off state.
The status of nitrogen in relation with the fish weight within the duration of the simulation is
presented in Figure 3. There is an increasing trend observed for the graph of excess nitrogen from
the first 14 days. It may be attributed to the constant addition of feed for the tilapia population. As
the fish grows, the feed input becomes greater. However, the tilapia population decreasescontinuously, thus yielding a decrease in the absorption of nitrogen.
The total excess nitrogen remained high even though the fish weight dropped due to the
accumulation of the nitrogen in the lake. The slight decrease in the excess nitrogen may be
attributed to the very low fish weight and the conversion of the nitrogen into a volatile form,
ammonia. Since the feed input depends on the fish weight, the nitrogen addition is almost zero.
The graphs of nitrogen addition, nitrogen removal as well as the fish weigh exhibited an almost
the same pattern having differences only with the values.
Figure 3. Nitrogen status and fish weight
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In Figure 4, fish stock was observed to drop as fish deaths occurred due to either predation or
climatic variability. Since the carrying capacity of the lake for nitrogen was not reached, the model
did not express occurrence of eutrophication.
Figure 4. Fish production and eutrophication status
It can be noted from the graph below (Fig.5) that the total fish demand increased as time increased.
This can be attributed to increasing locale population, with increasing fish demands. During the
first 41 days, the total import was observed to be zero. However, the fish supply became
insufficient after this day, thus, the municipality needs to import.
Figure 5. Fish supply, demand and import
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Sensit ivi ty Analysis Part 1- Stocking density
The model generated from STELLA was tested on various stocking densities for sensitivity
analysis. This is done to project the possible outcome for a given scenario, such as what if the
fish farmer stocked this much fish, thinking he would obtain a higher yield? The scenarios are
presented in Table 2. Each scenario was run 30 times to verify the average values.
Table 2. Sensitivity analysis using stocking density as the modifier.
Stocking
density
Eutrophication
status
Day of
eutrophication
Max excess
nitrogen (kg)
Final fish import
(kg)
Day of
importation
4 no n/a 4357.97 1374.00 40
5 no n/a 4271.08 1374.53 39
6 66% yes 12 5932.81 1375.00 12
7 yes 8 6,635.01 1,387.10 8
8 yes 7 6,437.80 1387.10 7
It can be observed from Table 2 that stocking density higher than the recommended stocking
density by BFAR results to a higher risk of yielding eutrophication. Stocking density of 6 fish per
sq.m. had 66% chance of resulting to eutrophication of the lake. Table 2 also illustrates that the
day that the stocking density is inversely related to the day that the lake reaches eutrophication.
Furthermore, excess nitrogen is noted to be higher in higher stocking densities. This can be
attributed to the increased feed input that depends on the fish biomass. In addition, the day of
importation is also inversely related to the stocking density. There is an earlier need to import if
the stocking density becomes higher.
Sensiti vity Analysis Part 2- Ferti li zer multi plier
Another sensitivity analysis was conducted on the model. The analysis now focused on the
scenario that a fish farmer can opt to do thinking that the yield would improve. The fertilizer
multiplier which denotes the formulation of the feed input is the variable used as the modifier. In
the original setup, the feed formulation makes use of the recommendation of BFAR for the grow-
out Tilapias, which is at 3% of the body weight of the fish. Several scenarios were simulated and
the data were presented in Table 3. The scenarios made use of the original stocking density of 4
fish per sq.m.
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Table 3. Sensitivity analysis using fertilizer multiplier as the modifier.
Fertilizer
multiplier (%)
Eutrophication
status
Day of
eutrophication
Max excess
nitrogen (kg)
Final fish
import (kg)
Day of
importation
3 no n/a 4357.97 1374.00 40
3.3 no n/a 4,227.95 1,372.54 403.6 no n/a 5,260.22 1,381.14 36
3.9 37% yes 13 5,898.60 1,387.10 14
4 40% yes 12 5,980.63 1,387.10 13
Based on Table 3, it can be noted that the fertilizer multiplier is inversely related to the day of
eutrophication and importation. Higher fertilizer multipliers yield earlier eutrophication and
importations. Moreover, it can be observed that at 3.9% results to 37% chance of reaching
eutrophication while having 4% fertilizer multiplier leads to 40% chance. The excess nitrogen
values were also noted to increase with the fertilizer multipliers. In addition, fish imports werealso observed to be higher in increased fertilizer multipliers. This may be attributed to the amount
of nitrogen that the fish can absorb. Absorption of nitrogen by fish is determined by its biomass.
The amount of nitrogen that were not absorbed will accumulate in the lake, which could later lead
to poisoning of fish or even eutrophication.
The developed model focused on tilapia (Oreochromis spp.) production in the town of Los Baos.
The model was able to exhibit the impact of population pressure, predatory species, deterioratingwater quality in relation to the nitrogen accumulation in the lake and climatic variability to the
production of tilapia. The carrying capacity of the lake with regards to nitrogen accumulation has
been deliberated from fish stocking density and feeding rate. With the continuous increase ofdemand imposed by the growing number of people, the model also included the volume of fish
import needed in the local market.
Given different scenarios and external pressures, results show that the model has proven to be
effective in simulating and predicting tilapia production in the town of Los Baos.The model can
be very useful for the local government with regards to fish supply and demand monitoring as
well as to various stakeholders primarily the fisher folk. Based on the sensitivity analysis, it can
be noted that the higher the stocking density and fertilizer multiplier, the more it will lead toeutrophication and earlier importation of fish. Excess nitrogen is also found to be higher as the
fertilizer multiplier and stocking density becomes higher.
Knowing the total amount of tilapia to be imported by the municipality in cases of insufficiency
as well as the day that would require importation, the model may help the LGUs in preparing for
early importation. This would allow the municipality to be self-sufficient in terms of Tilapiasupply.
SUMMARY
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Based from the results of the conceptual model, the following recommendations are hereby made:
1.
Fisherfolks should observe the recommended stocking density and feeding rate set by
BFAR.
2. The LGU should conduct constant monitoring of nutrient loads in the lake.
3. To secure production, fisherfolks are advised to have reserve fish to supplement loses.
4. The LGU should provide incentive for hunting of the predatory species.
5. Alternative growing environment such as artificial ponds could be provided by the LGU
to lessen nutrient accumulation in the lake.
6. Trainings or seminars must be provided for the local fishermen with regards to the adaptive
measures in securing fish production. These include construction of sturdy fish pen and
providing greater knowledge about fish farming.
Americulture, Inc. Growth Phases 101.
Arboleda, N. A. (2011). A Fishy Story: Laguna, Quezon receive P30K-worth tilapia stock. The
LosBanos Times. Retrieved August 30, 20112, from http://lbtimes.ph/2011/2011/09/28/a-
fishy-story-laguna-quezon-fish-farmers-receive-30k-worth-tilapia-stock/
Avnimelech, Y. and M. Kochba, 2009. Evaluation of nitrogen uptake and excretion by tilapia in
bio floc tanks, using 15N tracing. Dept. of Civil & Environmental Engineering, Technion,
Israel Inst. Of Technology, Haifa, 32000 Israel. Aquaculture 287 (2009) 163168.
Boyd, C.E. 2001. Nitrogen, Phosphorus Loads Vary by System: USEPA Should Consider System
Variables in Setting New Effluent Rules. Global Aquaculture Alliance. The Advocate.
December 2001.
Boyd, C.E. 2004. Farm-Level Issues in Aquaculture Certification: Tilapia. Report commissioned
by WWF-US in 2004.
Guerrero III, R.D. 2008. Eco-Friendly Fish Farm Management and Production of Safe Aquaculture
Foods in the Philippines. Philippine Council for Aquatic and Marine Research and
Development.
Bureau of Fisheries and Aquatic Resources (BFAR). Tilapia grow-out.
Inquirer News. 2012.
REFERENCES
RECOMMENDATIONS
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Pascual, F.P. 1993. Aquafeeds and feeding strategies in the Philippines, p. 317-353. InM.B.
New, A.G.J. Tacon and I. Csavas (eds.) Farm-made aquafeeds. Proceedings of the FAO/
AADCP Regional Expert Consultation on Farm-Made Aquafeeds, 14-18 December 1992,
Bangkok, Thailand. FAO-RAPA/AADCP, Bangkok, Thailand, 434 p.
Socio-economic Profile of Los Baos,2010
Yang Yi and C. Kwei Lin. 1996. Finishing System for Large Tilapia. Fourteenth Annual Technical
Report. Pond Dynamics/Aquaculture Collaborative Research Support Program. 1 September
1995 to 31 July 1996.
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Annex 1. Nitrogen status and fish weight at 5 fish per sq.m. stocking density
Annex 2. Fish production and eutrophication statusat 5 fish per sq.m. stocking density
ANNEX
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Annex 3. Fish supply, demand and import at 5 fish per sq.m. stocking density
Annex 4. Nitrogen status and fish weight at 6 fish per sq.m. stocking density
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Annex 5. Fish production and eutrophication statusat 6 fish per sq.m. stocking density
Annex 6. Fish supply, demand and import at 6 fish per sq.m. stocking density
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Annex 7. Nitrogen status and fish weight at 7 fish per sq.m. stocking density
Annex 8. Fish production and eutrophication statusat 7 fish per sq.m. stocking density
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Annex 9. Fish supply, demand and import at 7 fish per sq.m. stocking density
Annex 10. Nitrogen status and fish weight at 8 fish per sq.m. stocking density
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Annex 11. Fish production and eutrophication statusat 8 fish per sq.m. stocking density
Annex 12. Fish supply, demand and import at 8 fish per sq.m. stocking density
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Annex 13. Nitrogen status and fish weight at 3.3% fertilizer multiplier
Annex 14. Fish production and eutrophication status at 3.3% fertilizer multiplier
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Annex 15. Fish supply, demand and import at 3.3% fertilizer multiplier
Annex 16. Nitrogen status and fish weight at 3.6% fertilizer multiplier
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Annex 17. Fish production and eutrophication status at 3.6% fertilizer multiplier
Annex 18. Fish supply, demand and import at 3.6% fertilizer multiplier
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Annex 19. Nitrogen status and fish weight at 3.9% fertilizer multiplier
Annex 20. Fish production and eutrophication status at 3.9% fertilizer multiplier
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Annex 21. Fish supply, demand and import at 3.9% fertilizer multiplier
Annex 22. Nitrogen status and fish weight at 4% fertilizer multiplier
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Annex 23. Fish production and eutrophication status at 4% fertilizer multiplier
Annex 24. Fish supply, demand and import at 4% fertilizer multiplier