Modelling Fish Production in Los Banos Laguna - EnS 211 WX Revised - Final

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_province


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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



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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



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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

Modelling Fish Production in Los Banos Laguna - EnS 211 WX Revised - Final

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