Modeling effect of thermic amplitude on growing Chinese shrimp, Penaeus chinensis (Osbeck)

E(OLOGI(I|L mODELLInG ELSEVIER

Ecological Modelling 88 (1996) 93-100

Modeling effect of thermic amplitude on growing Chinese shrimp, Penaeus chinensis (Osbeck) Sha Miao

*, S h u n c h i T u

Department of Aquaculture, National Taiwan Ocean University, Keelung, Taiwan, ROC 20224 Received 13 September 1994; accepted 16 February 1995

Abstract

A 40-day study evaluating the effect of thermic amplitude on daily growth rate of Chinese shrimp was conducted. Three thermic regimes consisting of one constant temperature (31°C) and two daily thermocycles were selected. The temperatures of the two thermocycles increased from 29 to 33°C and from 27 to 35°C, respectively, on a 12-h cycle, and then decreased to their respective origins on the following 12-h cycle. The results indicated that the growth rate was a quadratic function of the thermic amplitude. Such a growth model may be described by

G=O.O2718846+O.OO23323775(TA) -0.000487611(TA) 2, where G represents the daily growth rate on a 40-day basis, and TA is thermic amplitude in centigrade. The optimal thermic amplitude was estimated to be 2.39°C. That is, the maximum daily growth rate would be 0.0299779 at daily temperatures fluctuating between 31°C _+ 1.195°C; or practically, the optimal daily temperatures would be fluctuating between 30 and 32°C.

Keywords: Growth; Quadratic models; Shrimp; Temperature

I. Introduction Metabolic energy expenditure is a major cost factor of food energy intake and it varies in relation to interacting environmental factors. Crustaceans may adjust their rates of food consumption and energy expenditure for maintenance in relation to environmental changes and may also conserve energy by metabolic rate com* Corresponding author. Fax: ( + 886-2)463-1388.

pensation to temperature, in order to maintain a positive energy balance necessary for development (Sastry, 1979). Rates of development of larval stages are differentially sensitive to constant and daily cyclic temperatures, and these responses are specific of each species (Sastry, 1980). The amplitude and rate of change of the daily temperature cycle also affects differently the rate of larvae development (Sastry, 1983). Miao and Tu (1993) reported that the amplitude of temperature variation may significantly affect

0304-3800/96/$15.00 © 1996 Elsevier Science B.V. All rights reserved SSDI 0 3 0 4 - 3 8 0 0 ( 9 5 ) 0 0 0 7 2 - 0

S. Miao, S. Tu / Ecological Modelling 88 (1996) 93-100

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Table 1 Weight, daily growth rate, and survival as influenced by varied thermic amplitudes on a 40-day basis Thermic amplitude a (oc) Measured variable b Statistics on five aquaria (replicates) 0

W0

W4o 4

8

G S W0 W40 G S W0 W4o G S

Minimum

Maximum

Mean

Standard deviation

1.34 3.97 0.0243325 1.00 1.52 4.60 0.0251480 0.80 1.48 2.26 0.0086640 0.80

1.76 5.80 0.0317319 1.00 1.84 6.36 0.0332810 1.00 1.89 4.00 0.0212450 1.00

1.594 4.754 0.0271885 1.00 1.694 5.368 0.0287126 0.96 1.700 3.124 0.0146404 0.92

0.1757 0.7640 0.0028861 0 0.1212 0.7048 0.0029521 0.0894427 0.1463 0.7755 0.0053788 0.1095445

a If the thermic fluctuation on a daily basis was 31°C + 4°C, then the thermic amplitude was 8°C. Likewise, if the temperature was controlled at 31°C, then thermic amplitude was zero. b W0 is the total weight in grams of five shrimp for each aquarium on day zero. W40 is the total weight in grams of five shrimp for each aquarium on day 40. G is daily growth rate on a certain aquarium computed by ln(W4o/Wo)/40. S is survival rate on a certain aquarium computed by N4o/No, where NO is the number of shrimp being stocked in each aquarium on day 0 and N40 is the number of shrimp survived on day 40.

the growth rate of redtail shrimp, Penaeus penicillatus A., in c o m p a r i s o n with c o n s t a n t t e m p e r a ture at the average value of the fluctuation. C h i n e s e shrimp, Penaeus chinensis 0 . , is the most i m p o r t a n t species c u l t u r e d in China, a n d comprises a b o u t 80% of the total yield of cult u r e d shrimps in C h i n a (Liu, 1990). T h e o p t i m a l t e m p e r a t u r e for m a x i m u m growth rate was rep o r t e d to be 31.26°C (Miao a n d Tu, 1995). T h e objective of the p r e s e n t work was to m o d e l the effect of t h e r m i c a m p l i t u d e c o n t a i n i n g the optimal p a r a m e t e r o n the growth of C h i n e s e shrimp. As a result, b e t t e r u n d e r s t a n d i n g of the factors affecting growth a n d p r o d u c t i o n of C h i n e s e shrimp may be achieved.

levels of t r e a t m e n t s are equally spaced a n d replication is b a l a n c e d (Gill, 1978; P e t e r s e n , 1985). Based o n the r e f e r r e d o p t i m a l t e m p e r a t u r e s a n d available facilities, three t h e r m i c regimes consisting of o n e c o n s t a n t t e m p e r a t u r e a n d two daily thermocycles were e m p l o y e d for the experiment. C o n s t a n t t e m p e r a t u r e in a q u a r i a was controlled by t h e r m o s t a t s at 31°C d u r i n g the study. T o gene r a t e the two thermocycle t r e a t m e n t s , a t h e r m i c a p p a r a t u s was set u p for each a q u a r i u m . E a c h t h e r m i c a p p a r a t u s consisted of two t i m e r - c o n trolled t h e r m o s t a t s with each t h e r m o s t a t conn e c t e d to a heater. F o r the t h e r m i c t r e a t m e n t with a n a m p l i t u d e of 4°C, o n e t h e r m o s t a t was set at 33°C, while the o t h e r was at 29°C. T h e power supply was automatically t u r n e d o n a n d off by the timers with a 12-h setting. Such o n - a n d - o f f activi-

2. Materials and methods W h e n the fixed t r e a t m e n t s of a set are q u a n t i tative, o n e may characterize the form of r e s p o n s e ( l i n e a r or in some degree curvilinear) of the primary variable Y to the level of t r e a t m e n t imposed. P o l y n o m i a l curves are c o n v e n i e n t approxim a t i o n s for n o n l i n e a r relationships a n d are particularly easy to use in o r t h o g o n a l form if the

Table 2 Analysis of variance on daily growth rate influenced by thermic amplitude Source

DF SS

Total 14 Thermic amplitude 2 Error 12

MS

F-ratio P > F

0.00078 0.00060 0.00030 19.46 0.0002 0.00018 0.00002

S. Miao, S. Tu / Ecological Modelling 88 (1996) 93-100

95

Table 3 Sequential test of polynomial thermic amplitude effect on daily growth rate Source

DF

SS

MS

F-ratio a

P > F

Thermic amplitude Linear Quadratic Deviation from linear and quadratic

2 1 1 1

0.00060 0.00039 0.00020 0.00001

0.00030 0.00039 0.00020 0.00001

19.46 19.50 10.00 0.50

0.0002 < 0.001 < 0.01 > 0.50

MSE = 0.00002, with 12 D F (Table 2), is the divisor for obtaining F-ratios.

Table 4 Parameter estimates and significance tests of polynomial thermic amplitude effect on daily growth rate Parameter

DF

Parameter estimate

Standard error

T-testforH0: parameter = 0

P > [TI

Intercept Linear coefficient Quadratic coefficient

1 1 1

0.027188 0.002332 - 0.000488

0.0017507 0.0011159 0.0001340

15.53 2.09 - 3.64

0.0001 0.0586 0.0034

ties created the designed thermocycle which increased aquarium t e m p e r a t u r e from 29 to 33°C during 0700 to 1900 hours daily, and then declined to its origin on the following 12-h cycle. The thermic treatment with an amplitude of 8°C was managed in the same way except that the temperatures were cycled with an oscillation between 27 and 35°C. The room t e m p e r a t u r e was

controlled at 2 0 ° C + 1°C. The three thermic treatments were randomly assigned to 15 aquaria, five aquaria (replicates) for each treatment. Each aquarium was 60 cm length, 30 cm width, and 36 cm height and contained a stock of five shrimp. An orthogonal polynomial model (Gill, 1978; Petersen, 1985) calculated by the SAS software system ( S A S / S T A T , 1990) was applied to describe the experimental system as follows:

G = ~o + [3t(TA) + ~ , ( T A ) : 0.035

o

0.030

0.025

\ \

c II CI

0.020

\\

\

\, \\,

0,015

0,010

\

where G = daily growth rate on a 40-day basis; TA = thermic amplitude in °C; /3o = intercept on G axis; and /3t and /3, = regression coefficients. Variable G in the model represents a daily growth rate equal to ln(Wno/Wo)/t. W o and W40 denote the total shrimp weight in each aquarium at day zero and day 40, respectively, and t is a duration of 40 days. Shrimp for the experiment were provided by Tainan Marine Laboratory. Shrimp were acclima-

i

I 0,005ii 0

r 4

THERMAL AMPLITUDE (° C) Fig. 1. The symbols ( A ) represent the daily growth rates observed from individual aquaria subjected to a given thermic amplitude.

Table 5 Analysis of variance on survival influenced by thermic amplitude Source

DF

SS

MS

F-ratio

P> F

Total Thermic amplitude Error

14 2 12

0.09600 0.01600 0.08000

0.00800 0.00667

1.20

0.3349

S. Miao, S. Tu /Ecological Modelling 88 (1996) 93-100

96

tized at 31°C during two weeks before the experi-

s h r i m p a v e r a g e d 0 . 3 8 + 0 . 0 7 2 g ( m e a n _+ S D ) , a n d

ment

l a s t e d f o r 40

w e i g h t r a n g e d f r o m 0 . 2 3 t o 0 . 4 8 g. A d a i l y f e e d i n g

initial fresh weights of these Chinese

r a t i o n o f 1 5 % o f b o d y w e i g h t w a s d i v i d e d in t w o

took place. The

days. The

experiment

Table 6 Statistics of water quality involving dissolved oxygen (D.O., mg/1), pH, and ammonia-N (A-N, mg/l) at varied thermic amplitudes on a 40-day basis Days of measuring

Statistics of five aquaria

Thermic amplitude Ooc D.O.

pH

A-N

D.O.

pH

A-N

D.O.

pH

A-N

0

Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD Minimum Maximum Mean SD

6.4 6.7 6.56 0.1140 6.5 6.7 6.60 0.1000 6.5 6.8 6.66 0.1517 6.5 6.6 6.58 0.0447 5.9 6.5 6.26 0.2510 6.4 6.6 6.52 0.0837 6.1 6.6 6.48 0.2168 6.5 6.7 6.62 0.0837 6.6 6.8 6.72 0.0837 6.6 6.7 6.62 0.0447 6.6 6.7 6.68 0.0447

8.10 8.16 8.122 0.0228 8.07 8.12 8.104 0.0207 8.01 8.13 8.062 0.0497 8.49 8.51 8.502 0.0084 8.56 8.61 8.588 0.0192 8.44 8.57 8.476 0.0532 8.43 8.47 8,446 0.0152 8.32 8.35 8.336 0.0114 8.41 8.45 8.430 0.0158 8.41 8.44 8.426 0.0134 8.40 8.43 8.416 0.0114

0.019 0.025 0.0218 0.0022 0.020 0.023 0.0218 0.0013 0,019 0.023 0.0212 0.0015 0.021 0.024 0.0224 0.0011 0.023 0.026 0.0244 0.0011 0,025 0.027 0.0258 0.0008 0,026 0,029 0.0276 0,0011 0,030 0,032 0,0310 0,0007 0,032 0,034 0,0332 0,0008 0,027 0,031 0.0292 0.0015 0.028 0.031 0.0298 0.0013

6.6 6.8 6.70 0.0707 6.4 6.9 6.70 0.1871 6.9 7.0 6.92 0.0447 6.5 6.7 6.56 0.0894 6.5 6.7 6.64 0.0894 6.5 6.6 6.58 0.0447 6.5 6.6 6.56 0.0548 6.5 6.6 6.56 0.0548 6.7 6.8 6.76 0.0548 6.5 6.7 6.60 0.1000 6.6 6.8 6.68 0.0837

8.10 8.18 8.140 0.0339 8.06 8.11 8.094 0.0230 8.11 8.20 8.156 0.0351 8.49 8.51 8.500 0.0071 8.55 8.64 8.618 0.0383 8.57 8.59 8.582 0.0084 8.43 8.51 8.458 0.0311 8.32 8.35 8.340 0.0122 8.41 8.47 8.424 0.0261 8.40 8.43 8.418 0.0110 8.42 8.44 8.430 0.0100

0.018 0.026 0.0210 0.0035 0.019 0.023 0.0212 0.0015 0.019 0.023 0.0218 0.0016 0.022 0.025 0.0238 0.0013 0.024 0.026 0.0248 0.0008 0.024 0.027 0.0258 0.0013 0.026 0.029 0.0274 0.0011 0.029 0.033 0.0314 0.0015 0.032 0.035 0.0332 0.0013 0.028 0.031 0.0296 0.0011 0.029 0.032 0.0302 0.0013

6.5 6.9 6.68 0.1643 6.7 7.0 6.82 0.1095 6.8 7.0 6.88 0.0837 6.5 6.7 6.58 0.0837 6.1 6.8 6.54 0.2702 6.2 6.6 6.52 0.1789 7.1 7,4 7.22 0,1095 6.6 6,8 6,70 0,0707 6,5 6,7 6,62 0,0837 6,6 6,6 6.60 0.0000 6,7 6.8 6.74 0.0548

8.10 8.19 8.158 0.0349 8.04 8.11 8.090 0.0283 8.15 8.17 8.154 0.0089 8.50 8.55 8.522 0.0192 8.60 8.66 8.632 0.0217 8.48 8.59 8.560 0.0453 8.47 8.58 8.550 0.0453 8.33 8.34 8.332 0.0045 8.39 8.44 8.418 0.0192 8.39 8.48 8.456 0.0371 8.47 8.48 8.476 0.0055

0.016 0.023 0.0192 0.0026 0.019 0.021 0.0196 0.0009 0.020 0.023 0.0214 0.0011 0.021 0.024 0.0226 0.0011 0.023 0.026 0.0250 0.0012 0.024 0.027 0.0258 0.0013 0,026 0.029 0.0274 0.0011 0.030 0.033 0.0314 0.0011 0.031 0.034 0.0326 0.0011 0.028 0.031 0.0294 0.0011 0.029 0.031 0.0300 0.0010

4

8

12

16

20

24

28

32

36

40

4°C

8°C

97

S. Miao, S. Tu / Ecological Modelling 88 (1996) 93-100

Table 7 Analysis of variance on dissolved oxygen(D.O.) with repeated measurements (as a time effect) throughout 40 days Source DF SS MS F-ratio P>F Thermic amplitude (TA) Aquaria/TA

Repeated measurements (R) TA × R Error

2 12 10 20 120

0.7343344 3.7658184 0.194032 0.325472 1.50218182

equal parts and fed at 0900 and 1600 hours. A commercial shrimp pellet diet (manufactured by President Enterprises Corp., Taiwan), with protein content no less than 36%, was used for this feeding schedule and was kept refrigerated. Illumination consisted of four fluorescent light fixtures with two 40-watt bulbs, each regulated to a light period from 0600 to 1800 hours. To prevent the shrimp from jumping out, each aquarium was screen covered. Filtered sea water, collected in the nearby coast and provided by the National Taiwan Ocean University, was used to fill the aquaria. U n d e r the static system, the aerated aquaria were cleaned by replacing one third of the aquarium water on a weekly basis. The physicochemical parameters of pH, salinity, dissolved oxygen, and ammonia-N, corresponding to monitoring of aquaria, were recorded every four days during the experiment. A portable digital p H meter ( J E N C O Electronics Ltd., Taiwan) and a salinity refractometer (s/Mill, A T A G O Co. Ltd., Japan) were used to measure pH and salinity, respectively. T h e s p e c t r o p h o t o m e t e r

0.3671672 0.3138182 0.0194032 0.0162736 0.0125182

1.17

> 0.25

1.55 1.30

> 0.10 > 0.10

( D R / 2 0 0 0 , H A C H Company, USA) was applied to measure dissolved oxygen and ammonia-N.

3. Results The statistics on weight, daily growth rate, and survival under test conditions are summarized in Table 1. Analysis of variance of daily growth rate as influenced by the thermic amplitude is presented in Table 2. The F value of 19.46 with P = 0.0002 indicates that the effect of thermic amplitude was highly significant. Further analysis suggested that the daily growth rate was a quadratic polynomial function of the studied thermic amplitude (Table 3). Consequently, daily growth rate can be described by the equation (Table 4) G = 0.02718846 + 0.0023323775(TA) - 0.000487611(TA) 2, where G is the estimated daily growth rate on a 40-day basis, and TA denotes the daily thermic

Table 8 Analysis of variance on pH with repeated measurements (as a time effect) throughout 40 days Source DF SS MS F-ratio

P>F

Thermic amplitude (TA)

1.22

> 0.25

1.48 0.96

> 0.10 > 0.25

Aquaria/TA

Repeated measurements (R) TAx R Error

2 12 10 20 120

0.0024614 0.0121055 0.009839 0.012764 0.0797745

0.0012307 0.0010088 0.0009839 0.0006382 0.0006648

98

S. Miao, S. Tu / Ecological Modelling 88 (1996) 93-100

Table 9 Analysis of variance on a m m o n i a - N with repeated m e a s u r e m e n t s (as a time effect) throughout 40 days Source

DF

SS

MS

Thermic amplitude (TA)

2 12 10 20 120

0.00000789 0.00007371 0.00288918 0.00003304 0.00019469

0.00000395 0.00000614 0.00028892 0.00000165 0.00000162

Aquaria/TA Repeated m e a s u r e m e n t s (R) TAx R Error

amplitude ranging from 0 to 8°C. Additionally, Table 4 shows the T-test results for individual parameters of the polynomial equation. All the parameters were significantly different from zero at a = 10% (Table 4). Fig. 1 shows the trend of daily growth rate at different thermic amplitudes. The maximum daily growth rate was estimated to be 0.0299779 with a thermic amplitude of 2.39°C and an average of 31°C. Table 1 shows that the survival rate decreased from 100% to 92% when thermic amplitude increased from 0 to 8°C. However, the A N O V A showed that there was no effect of thermic amplitude on survival (F-ratio = 1.20 with P = 0.3349, Table 5). Salinity ranged from 34%o to 35%0 throughout the 40-day study period. The statistics on water quality involving dissolved oxygen (D.O.), pH, and ammonia-N are summarized in Table 6. Analyses of variance on dissolved oxygen and pH indicated that the single effect of thermic amplitude and time (repeated measurements) had no significant effect (Tables 7 and 8). Nor did the interactions of thermic amplitude and time ( Tables 7 and 8). Table 9 shows that the thermic amplitude had no effect on ammonia-N since the F-ratio was only 0.64 with P > 0.50. Effects due to interaction of thermic amplitude and time (repeated measurements) was not significant, which was expressed by a small F-ratio of 1.02 with P > 0.25 (Table 9). However, time had a significant effect on ammonia-N throughout 40-day period, which was expressed by an extremely high F-ratio (178.08) with P < 0.0001 (Table 9).

4. Discussion

A temperature fluctuating between 10 and 20°C, with an average of 15°C, does not necessar-

F-ratio 0.64 178.08 1.02

P > F > 0.50 < 0.0001 > 0.25

ily have the same effect on organisms as a constant temperature of 15°C (Odum, 1983). Cyclic temperature changes are known to produce better growth and survival in larval forms (Costlow and Bookhout, 1971; Christiansen and Cost|ow, 1975; Sastry, 1975). Table 1 shows that the mean daily growth rate of Chinese shrimp, P. chinensis, increased with increasing thermic amplitude, from 0 to 4°C, but dropped rapidly from 4 to 8°C. Sastry (1983) concluded that thermic amplitude and rate of temperature change on a daily basis affect the rate of development of crustacean differently. Therefore, cyclic temperature changes may either produce higher or lower growth rates than that of a constant temperature depending on levels of thermic amplitude around that given temperature (Miao and Tu, 1993). Contrarily to what happens at constant environmental conditions, fluctuating temperatures affect the development and survival of larvae differently (Sastry, 1983). Larvae of the estuarine mud crab, Rhithropanopeus harrisii, survive better at the extreme 30-35°C daily temperature cycle than at constant 30 or 35°C temperatures (Costlow and Bookhout, 1971). In contrast, larvae of the sublittoral crab, Cancer irroratus, survive better at 10-20°C and 15-25°C daily temperature cycles than at constant 15 or 20°C (Sastry, 1976), whereas larvae of the grass shrimp, Palaemonetes pugio, show no significant difference in survival rate under both changeable or constant temperatures (Sastry, 1980). The present study displayed a pattern of slowly decreasing survival with increasing thermic amplitude (Table 1), although the statistical evidence suggested that survival rate was not affected by thermic amplitudes ranging from 0 to 8°C (Table 5). Miao and Tu (1995) reported that the daily growth rate of P. chinensis will increase linearly

S. Miao, S. Tu / Ecological Modelling 88 (1996)93-100

as temperature increases from 16 to 31°C. However, the effect of temperature ranging from 27 to 35°C on the daily growth followed a quadratic pattern (Miao and Tu, 1995). The mean daily growth rates at 31°C were reported to be 0.0273488 and 0.0273617, respectively (Miao and Tu, 1995). The minimum, maximum, and average daily growth rates at 31°C of the present study were 0.0243325, 0.0317319, and 0.0271885, with a standard deviation of 0.0028861 (Table 1). The survival rate at 31°C was 100% (Table 1) which agrees with that reported by Miao and Tu (1995). Water quality is a major concern for growing penaeid shrimps (Chen, 1990). Shrimps are stressed when dissolved oxygen falls below 2.0 mg/1 (Wickins, 1976). The required oxygen level for the best growth was reported to be higher than 4 ppm in China (Main and Fulks, 1990). Further, a pH ranging from 8.0 to 9.0 was considered to be optimal for growth in China (Main and Fulks, 1990). Table 6 indicates that dissolved oxygen and pH met both requirements during experimentation. Further analyses of variance on D.O. and pH data indicated that both single factors of thermic amplitudes and time sequences (when measured repeatedly) had no significant effect ( Tables 7 and 8), nor did the interaction of thermic treatment and time ( Tables 7 and 8). In contrast, the effect of time (when measured repeatedly) on ammonia-N was highly significant (Table 9). Ammonia originates from animal excretions and from ammonification of unconsumed food or organic detritus (Hartenstein, 1970; Kinne, 1976; Armstrong, 1979). Ammonia may deteriorate water quality and cause high mortality and low growth rate of penaeid shrimps (Colt and Armstrong, 1981). Therefore, the accumulation of ammonia and its toxic effect are primary concerns in aquaculture systems. However, the safe level of ammonia-N for growing P. chinensis was reported to be 0.62 m g / l (Chen and Lin, 1991). Consequently, the intensity of ammonia-N throughout the 40-day studied period (Table 6) probably had little effect on growth and mortality. P. chinensis is a eurythermic species (Wang and Ma, 1990). With modeling effect of temperatures ranging from 16 to 35°C on growing P.

99

chinensis, Miao and Tu (1995) pointed out that the maximum growth rate can be achieved only at a constant temperature of 31°C. The present study further indicated that daily temperatures fluctuating between 30 and 32°C can induce an even better growth. In nature, under seasonal and daily changes, environmental conditions fluctuate at different levels. The aquaculture industry in Taiwan is facing two major problems: limited land and limited ground water supply. Another problem is the heated effluent waters that are released from the cooling systems of power plants. They may cause deleterious impacts on some environments; yet to the shrimp mariculturist, heated effluents may prove to be beneficial. By moving cages back and forth or up and down, farmers may apply the thermocycle effect to cage culture and so increase production. In summary, a better growth may be obtained by inducing a daily thermocycle as here described by a quadratic polynomial of thermic amplitude. The predicted daily optimal thermocycle is 31°C + 1.195°C.

Acknowledgements The research on which this report is based was financed by a grant from the National Science Council of the Republic of China under project number NSC81-0409-B-019-505.

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