- Email: [email protected]
A feeding model of oyster larvae (Crassostrea angulata)
Physiology & Behavior 147 (2015) 169–174
Contents lists available at ScienceDirect
Physiology & Behavior journal homepage: www.elsevier.com/locate/phb
A feeding model of oyster larvae (Crassostrea angulata) Tianlong Qiu a, Ying Liu a,⁎, Jimeng Zheng a, Tao Zhang a, Jianfei Qi b a b
National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, PR China Fujian Fisheries Research Institute, Xiamen 361013, PR China
H I G H L I G H T S • • • •
We established a feeding model that describes the oyster larva feeding behavior. The defined filtration coefficient explains the larval feeding feature. We found a relationship between feeding and morphological, motive features. Larval length is the only parameter needed for ingestion rate estimation.
a r t i c l e
i n f o
Article history: Received 8 February 2015 Accepted 23 April 2015 Available online 24 April 2015 Keywords: Oyster larva Feeding behavior Swimming speed Ingestion rate Filtration rate Filtration coefficient Feeding model
a b s t r a c t There is a need to develop more efficient rearing systems for the aquaculture of economically important bivalves, such as oysters. Here, we constructed a model that describes the feeding behavior of larval Crassostrea angulata oysters and tested it in an experimental setting. Larval ingestion rate is closely correlated with larval length. Based on our model, we showed that larval swimming speed, velum diameter and the filtration coefficient, which also determine the ingestion rate, are also correlated with larval length. Our model integrates morphological, locomotory and feeding behavior parameters to establish a relation between them and so provides a mathematical way to describe variation in the feeding behavior of bivalve larvae. The results of this study could facilitate the precise management of the aquaculture of bivalve larvae, in particular the optimum prey density and feeding rate of these important organisms. © 2015 Published by Elsevier Inc.
1. Introduction There are several rearing systems in use in the aquacultural industry, with the recirculating aquaculture system (RAS) having a superior performance compared with traditional culture methods in many aquacultural fields [3,6]. In aquacultural settings, shellfish larvae are currently hatched and reared using a high energy-consuming method that requires frequent renewal of seawater and tank cleaning, which is far from ideal. The feeding behavior of oyster larvae is the basis on which larval hatcheries have been developed. Although there have been some studies on the feeding characteristics of oyster larvae, including diet selection, ingestion rate, and filtration rate [1,8,11,15], the resulting information remains inadequate for the development of an efficient
⁎ Corresponding author. E-mail address: [email protected] (T. Qiu), [email protected] (Y. Liu), [email protected] (J. Zheng), [email protected] (T. Zhang), [email protected] (J. Qi).
http://dx.doi.org/10.1016/j.physbeh.2015.04.043 0031-9384/© 2015 Published by Elsevier Inc.
and, therefore, more economically viable, high-density larval breeding system. In addition, determination of the filtration and ingestion rates of larval oysters is limited to the population level because of the traditional study methods used, which mainly depend on the measurement of variation in microalgal concentration of the surrounding water. These results cannot fully explain the difference in filtration rate among different larval species and unexpected declines in the filtration rate of competent larvae. Therefore, results on a larval scale would increase our understanding of oyster larval feeding behavior, and would facilitate the precise management of high-density breeding of such larvae. In the current study, we developed a model that integrated the morphological, locomotory, and feeding behavior parameters of larval oyster and established the relations between these parameters. As we illustrate here, our model could be used to describe mathematically larval feeding behavior and the variation in ingestion and filtration rates. Such information would be useful to not only the aquacultural industry, but also marine ecologists, given the importance of larval bivalves to the zooplankton component of marine ecosystems.
170
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
2. Material and methods 2.1. Concepts and feeding model formulation Oyster larvae filter microalgae and swim by beating their cilia [4,15], and a complete cilial-beating circle of oyster larvae is similar to that of Vorticella, based on our observation and the description of Strathmann & Leise [15] and Blake & Otto [4] and as shown in Fig. 1. The effective and recovery strokes of the cilia propel the surrounding water through the oral groove and move the body of the larva. Thus, waterborne microalgae are transported to the oral groove, where some of them are caught by the oral groove cilia. Therefore, when filtering water (Fig. 2), oyster larvae can both move and capture microalgae. Suppose that the velum diameter is d, the velum area is s (approximately represented by the circular area in diameter d) and the swimming speed of larvae when feeding is v. When larvae filter water, they remove microalgae from the water. However, the filtering organ (i.e., velum) is not the only point at which microalgae are captured, because the oral groove cilia are also involved. Thus, the fraction of microalgae captured by the larval oral cilia compared with the total amount of microalgae filtered by the velum cilia is represented by k, which we define in the current study as the filtration coefficient. To construct the feeding model, we assumed that, when the larvae filter water they are also swimming, and the water volume calculated by velum area times the trajectory length (shown in Fig. 2 as s × vt) is equal to the volume of water that they filtered (i.e., total amount of water handled). Based on this assumption, the filtration rate (FR), which is defined as the volume of water swept clear in unit time [5] can be expressed as Eq. (1): −1 2 ¼ πkd v=4 FR μl larva−1 h
ð1Þ
ingestion rate (IR) can be expressed as Eq. (2): −1 IR cells larva−1 h ¼ C FR
ð2Þ
where C represents the microalgal concentration. If filtration is complete (k = 1), the filtration rate will equal the total water volume handled in unit time (TV).
Fig. 2. Oyster larva filtering water in a time unit. d, s, v represent the velum diameter, the velum area and the swimming speed of larvae respectively, dotted area represents the total water volume filtered by the larva.
aquarium, and flowed out from the aquarium via a drum filter upstream of the aquarium. The water flow velocity was set at 20 L/h, the larval densities (n) were set at approximately 10 to approximately 120 larvae mL− 1. By using this system, the microalgal concentration before entering and after leaving the aquarium (C1 and C2, respectively) could be measured. The average retaining time (tr) of microalgae was calculated using Eq. (3): t r ¼ V=Q
ð3Þ
where V (in L) represents the volume of the aquarium, and Q (in L/h) represents the flow velocity through the aquarium. We assumed that an infinitesimal amount of water (ΔV) moved from the inlet pipe to the outlet pipe and that any waterborne microalgae in that flow were fed on by the larvae in the aquarium. Therefore, we concluded that (Eq. (4)): Z 2 ðC1 –C2 ÞΔV ¼ ΔVnkvπd =4
tr 0
dt Ct :
ð4Þ
Under a continuous feeding system, the amount and flow of microalgae through the aquarium was constant enough to enable the larvae to catch their prey; therefore, the variation in microalgal concentration
2.2. Feeding character determination with a recirculating aquaculture system (RAS) To better describe the feeding behavior of larvae, we constructed a RAS (Fig. 3): larvae were cultured in a 6-L cylindroconical aquarium and microalgae were added from the inlet pipe downstream of the
Fig. 1. An example of a ciliary beat cycle showing the effective and recovery strokes, labels ①–⑦ show the ciliary beat sequence. Based on Blake & Otto [4] and Strathmann & Leise [15].
Fig. 3. Illustration of a recirculating aquaculture system (RAS) used in the larval feeding experiments.
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
171
was linear. Thus Ct, which represents the variation in microalgal concentration variation of ΔV during time tr, can be replaced by (C2 + C1) / 2, simplifying Eqs. (4) to (5): 2
C2 –C1 ¼ t r ðC2 þ C1 Þnkvπd =8:
ð5Þ
Given that C2, C1, n, v, d, and tr can be measured using the RAS set-up, only k needs to be calculated separately. 2.3. Experimental protocol for parameter estimation 2.3.1. Larvae collection and rearing conditions The larvae of the oyster Crassostrea angulata were collected by artificial fertilization using more than ten female and ten male oysters. The eggs and sperms were well mixed before fertilization. Resulting fertilized eggs were hatched and reared in sea water with a salinity of 30 ppt, at 24–29 °C in 400-L aquariums for use in the RAS experiments and also to determine swimming speed and velum diameter. In the 400L aquarium, the larvae were cultured at a density of 6–10 larvae mL−1 and fed with live Chlorella sp. (3.10 ± 0.4 μm in diameter, n = 30) and Isochrysis sp. (4.42 ± 0.6 μm in diameter, n = 30). In the RAS feeding experiments, Isochrysis sp. were mainly used because they are a suitable food for oyster larvae [1,11], Chlorella sp. were used when there was a shortage of Isochrysis sp. If this was the case, then we used the conversion of 1 Isochrysis sp. cell =2.9 Chlorella sp. cells based on their volume. The concentration of microalgae at the inlet and outlet pipes and also the larval cultural density for each treatment were sampled simultaneously; 3% formalin was added to the sample to maintain the microalgal concentrations for measurement. Precise C1 and C2 concentrations were measured using a 0.5-mL phytoplankton-counting grid manufactured by HYDRO-BIOS, and at least ten grids were counted for each sample. 2.3.2. Swimming speed of oyster larvae (v) Computer-assisted sperm analysis (CASA) has been used in previous studies to assess the swimming speed of trochophore and D-shaped larvae [9,16,17]. However, the locomotory behavior of the larger veliger larvae is more complex compared with these smaller larvae. In the current study, larvae were placed in a horizontal counting grid (380 mm2 and 1.32 mm deep) and the locomotory behavior of the oyster larvae were then recorded with a microscope (40 ×) and a camera. Observations showed that, by adjusting the beating frequency, oyster larvae can feed while swimming, feed without swimming, or swim fast with or without feeding. The swimming pattern is known to vary with the satiation of the larvae by our observation, in that the larvae swam more actively when hungry, whereas when they were fully fed, they preferred to remain still. Therefore, the larval swimming speed was measured after the larvae had been fully fed 1–2 h previously.
Fig. 4. Larval velum diameter and shell length measurements.
to ~320 μm (eyed larvae). Observations also showed that, under certain water conditions (pH 8.1–8.3, dissolved oxygen 6.–6.8 mg L−1, temperature 24–30 °C, salinity 29–32), larval swimming speed was influenced by the degree of stomach satiation. Larvae remained still when they were fully fed or if there was sufficient food present (e.g. 106 microalgae cells mL−1), but swam at a moderate speed when they were filtering microalgae (~ 0.5 mm s− 1 to ~ 6 mm s−1; Fig. 5). Basing on these data, we determined the relation between larval length l (μm) and the swimming speed v (μm s−1) to be (Eq. (6)): 2 v ¼ –0:1004 l þ 59:699 l–2887; l∈ð70; 320 μmÞ R2 ¼ 0:9895 :
3.2. Velum diameter (d) of C. angulata By measuring more than 100 anesthetized C. angulata larvae, a linear relation was found between velum diameter d (μm) and larval length l (μm), which can be expressed by Eq. (7) (Fig. 6): d ¼ 0:9243 l–20:223 R2 ¼ 0:9615 :
ð7Þ
3.3. Parameter estimation of filtration coefficient (k) For each of the experimental results shown in Table 1, the filtration coefficient k was determined basing on Eqs. (5)–(7) and the relation between k and l is shown in Fig. 7. The filtration coefficient ranged from approximately 0.05 to 0.6 according to the calculated results.
2.3.3. Measurement of velum diameter (d) The larvae of different developmental stages were anesthetized by magnesium chloride (MgCl2) and the velum diameter of more than 100 larvae as shown in Fig. 4 was measured. The velum is not exactly circular, varying from nearly circular during the early developmental stages to elliptical in the late pelagic stage; therefore, for convenience, the diameter of the velum (d) was measured as the main parameter of the larval velum in all larval developmental stages. 3. Results 3.1. Swimming speed (v) of C. angulata Analysis of more than 200 larval videos showed that the swimming speed of larval C. angulata varied from 0.0 mm s−1 to ~9.5 mm s−1, with the corresponding shell length varying from ~70 μm (D-shaped veliger)
ð6Þ
Fig. 5. Swimming speed of oyster larvae (mean ± SD).
172
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
Fig. 7. Relation between the filtration coefficient k and larval length. Fig. 6. Relation between velum diameter and shell length.
3.4. A feeding model for larval C. angulata oysters Pearson correlation analysis showed that the filtration coefficient k has a negative correlation with larval length (r = − 0.739, P b 0.001) compared with microalgal concentration (r = − 0.597, P = 0.001) and cultural density (r = 0.546, P = 0.003). From the data of larval length and the filtration coefficient k, we can obtain an exponential relation (Eq. (8)):
Using the relation determined between larval length and larval swimming speed, velum diameter, and filtration coefficient, we constructed a feeding model for larval C. angulata based only larval length data. The FR and IR of one oyster larva with larval length l can be expressed by Eqs. (9) and (10), respectively: 2
ð9Þ
FR ¼ kd vπ=4
k ¼ 1:1358e−0:01l R2 ¼ 0:4944
ð8Þ
Although k is a parameter affected mainly by a larva itself, it varied when the microalgal concentration and environmental factors changed. Eq. (8) was established in a moderate microalgal concentration of 4000–12,000 cells mL−1. This concentration was determined based on our previous experimental results that a concentration of ~10,000 cells mL−1 was a suitable concentration to use in RAS.
IR ¼ C FR
ð10Þ
and the other parameters can be calculated using Eqs. (11)–(13): 2 v ¼ –0:1004 l þ 59:699 l–2887 R2 ¼ 0:9895
ð11Þ
d ¼ 0:9243 l–20:223 R2 ¼ 0:9615
ð12Þ
k ¼ 1:1358e−0:01l R2 ¼ 0:4944 :
ð13Þ
Thus, Table 1 Results of larval culture in RAS. No.
C1 cells mL−1
C2 cells mL−1
Q L h−1
n larvae mL−1
l μm
k
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
4655 4655 4655 6555 6555 6555 4655 4655 9025 10,070 4655 10,070 11,500 10,070 9025 7000 7000 9025 7000 11,500 12,160 12,160 11,500 11,000 11,000 3046a 5634a
2280 2470 2470 2860 2620 2375 1520 2755 5795 5795 1680 4990 3800 6600 6650 4933 6433 7980 4500 6700 8600 9880 6760 6600 8000 1801* 4232*
20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 30
123 121 87 67 75 95 87 77 36 45 65 90 90 54 24 36 8 10 24 54 34 18 45 34 18 7 14
114 114 114 124 124 124 126 126 139 139 146 152 152 153 159 164 164 165 171 177 191 195 212 221 230 240 241
0.33 0.30 0.42 0.50 0.49 0.42 0.47 0.27 0.34 0.33 0.34 0.15 0.23 0.15 0.22 0.15 0.16 0.19 0.24 0.12 0.10 0.10 0.08 0.09 0.10 0.36 0.15
a
Converted data of Isochrysis sp. from Chlorella sp.
IR ¼ 1:1358e−0:01l ð0:9243 l−20:223Þ ð70blb320 μmÞ:
2
2 −0:1004 l þ 59:699 l−2887 πC=4;
C represents the microalgal concentration in the cultural system RAS, which should be ~ 4000 to ~ 12,000 cells mL− 1 in this model. The ingestion rate based on this model is shown in Fig. 8 and varies from ~ 25 cells larva−1 h−1 to ~ 680 cells larva−1 h−1 when the larva is fed with ~ 10,000 cells mL− 1 Isochrysis sp. Therefore, this model
Fig. 8. Predicted ingestion rate of C. angulata larvae with a microalgal concentration of 104 cells mL−1.
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
173
suggests a method to construct a feeding management strategy for bivalve larvae rearing in RAS, and will help in the automatic management of larval rearing. 4. Discussion and conclusion 4.1. The filtration coefficient k The filtration coefficient k is directly determined by the filtrating ability of velum cilia and the ability of oral cilia to capture microalgae. Based on the size and morphology of the oral groove, there is likely to be a threshold number of cells that a larva can catch in unit time. If the microalgal concentration exceeds that threshold, the larva would be unable to capture all the algae that pass through the oral groove, and so k would decrease. On the other hand, an excessively high culture density of larvae would cause a more frequent collision between individuals and influence their swimming and feeding behavior [2,13], which would then influence the filtration coefficient. During larval development, the size of the oral groove does not grow proportionally with velum diameter. Basing on data from photos of five larvae that clearly showed the oral groove and velum, the ratio of oral groove width to velum diameter varies from 0.35 to 0.20 as larval length increases from 150 μm to 220 μm; this morphological feature could be one explanation for the decreasing trend in filtration coefficient. Strathmann & Leise [15] calculated the fraction of particles caught out of the total number of particles by larvae of the oyster Crassostrea gigas (larval length ~ 90 μm) to be 0.44, which is close to our result (~0.46) based on Eq. (8). Strathmann and Leise [15] also found that in the three species C. gigas, Tritonia diomedea, and Nassarius obsoletus, one with longer pre-oral cilia cleared particles at a higher rate but with less efficiency in capturing prey. This phenomenon is in accordance with our result that larger larvae (which have longer pre-oral cilia) have a smaller filtration coefficient. Our results also show that, as the microalgal concentration increased, the filtration coefficient did not, but instead leveled out when the microalgal concentration was approximately 4000–10,000 cells mL−1. This suggests that, although the concentration of filtered microalgae increases, the number of ingested microalgae does not above a certain density threshold, as previously shown by Rico-Villa et al. [10]. This indicates that, when developing a RAS, the concentration of microalgae should be maintained at a level that not only facilitates larval feeding, but also can keep a low requirement for the cultural system itself. This concentration should be ~ 10,000 cells mL−1 for C. angulata fed with Isochrysis sp., balancing the larval feeding and the requirement of RAS. 4.2. Filtration rate and ingestion rate of oyster larvae During the pelagic larval period, the filtration rate (FR) increases with larval size, whereas it decreases approaching metamorphosis [8, 12]; a similar situation is seen with the ingestion rate (IR), which is obtained by IR = C FR. Oyster larvae, similar to adult oysters, can regulate their feeding activity according to the surrounding food concentration [8]. In our experiments, larvae that fed on high-density microalgae, ceased feeding once they were satiated. The morphological change approaching metamorphosis, which is likely to reduce the ability to filter, was thought to explain this decrease in filtration rate [8]. In our model, the combination of decreasing filtration coefficient and decreasing swimming speed during metamorphosis explained this phenomenon. The FR results from Eq. (9) (shown in Fig. 9) are within the range of ~ 2.5–~ 67 μl larva− 1 h− 1. This result approximates that of Gerdes [8], who studied C. gigas (0.5–100 μl larva− 1 h− 1) and also those of Sprung [14], who studied Mytilus edulis (10–61 μl larva−1 h− 1) with a larval length of 120–250 μm. The rate of total water volume filtered by the larvae calculated based on the velum diameter and swimming speed (TV = π d2 v/4) varied from 5 μl larva− 1 h− 1
Fig. 9. Predicted filtration rate of, and the total water volume filtered by, a larval C. angulata oyster.
to ~1200 μl larva−1 h−1 as shown in Fig. 9. Unlike FR, TV continues to increase during the pelagic period until metamorphosis. In a set larval developmental period, the filtration rate is approximately a constant value in a low microalgal-concentration environment (b 10,000 cells mL−1) with stable environmental factors. However, the filtration rate tested in the laboratory always fluctuates: as the cell concentration increases, the filtration rate usually decreases [8,5,7]. There are several factors that could influence measuring the filtration rate, including microalgae size and concentration, and satiation of the larval gut [8,14,5]. Therefore, to reduce this effect, measurement of filtration rate has to be done quickly (usually several hours). When previously starved larvae were exposed to an environment with highdensity microalgae, the ingestion rate increased to above the ingestion capacity level, leading to misestimation of both the ingestion and filtration rates [14].
4.3. Model adaptation Environmental factors (e.g., temperature, pH, and salinity) could have effects on the beating frequency of cilia and, thus, affect the swimming speed of larvae. However, some studies have shown these factors to have little effect if in a moderate range: for example, Strathmann & Leise [15] found that the mean angular velocity of the pre-oral cilia of C. gigas at ~ 20 °C was only slightly greater than at 12–13 °C, and the difference was not significant. Suquet et al. [16] found that adjusting the pH of seawater to values from 5.10 to 9.08 had no effect on the swimming characteristics of C. gigas trochophores. This would facilitate the application of the model to a wider range of environmental conditions; however, we did not have enough data to investigate whether this relation would hold true under extreme environmental change.
5. Conclusion The results of this study increase current knowledge of larval feeding and, by describing larval feeding features directly, the ingestion and filtration rates can be calculated mathematically. In addition, this study provides a new way of determining larval feeding and locomotory behavior, which could help develop more efficient bivalve aquacultural systems.
Acknowledgments This study was funded by the 56th China Postdoctoral Science Foundation, Postdoctoral Innovation Project Special Funds of Shandong Province (2014), the National Key Technologies R&D Program (2014BAD08B09) and an earmarked fund for Modern Agro-industry Technology Research Systems (CARS-48).
174
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
References [1] S. Acarli, A. Lok, Comparison of Isochrysis galbana and Chlorella sp. Microalgae on growth and survival rate of European flat oyster (Ostrea edulis, Linnaeus 1758) larvae, Indian Journal of Marine Sciences 40 (1) (2011) 55–58. [2] C. Avila, S. Grenier, C. Tamse, A. Kuzirian, Biological factors affecting larval growth in the nudibranch mollusc Hermissenda crassicornis (Eschscholtz, 1831), Journal of experimental marine biology and ecology. 218 (2) (1997) 243–262. [3] M. Badiola, D. Mendiola, J. Bostock, Recirculating Aquaculture Systems (RAS) analysis: main issues on management and future challenges, Aquac. Eng. 26-35 (2012). [4] J. Blake, S. Otto, Ciliary propulsion, chaotic filtration and a ‘blinking’ stokeslet, Journal of engineering mathematics. 30 (1–2) (1996) 151–168. [5] D.J. Crisp, A.B. Yule, K.N. White, Feeding of oyster larvae: the functional response, energy budget and a comparison with mussel larvae, Journal of the Marine Biological Association of the United Kingdom. 65 (3) (1985) 759–783. [6] J.M. Ebeling, M.B. Timmons, Recirculating Aquaculture Systems, in: J. Tidwell (Ed.), Aquaculture Production Systems, John Wiley&Sons, Inc. 2012, pp. 245–277. [7] J. Fang, H. Sun, S. Kuang, X. Liang, X. Niu, Z. Liu, F. Li, Study on the filtration and ingestion rate of bloody clam larvae tegillarca granosa, Oceanologia Et Limnologia Sinica. 30 (1999) 170–178. [8] D. Gerdes, The Pacific oyster Crassostrea gigas: part I. Feeding behaviour of larvae and adults, Aquaculture 31 (2) (1983) 195–219. [9] T.J. Hilbish, K. Sasada, L.S. Eyster, J.A. Pechenik, Relationship between rates of swimming and growth in veliger larvae: genetic variance and covariance, Journal of Experimental Marine Biology and Ecology. 239 (2) (1999) 183–193.
[10] B. Rico-Villa, S. Pouvreau, R. Robert, Influence of food density and temperature on ingestion, growth and settlement of Pacific oyster larvae, Crassostrea gigas, Aquaculture 287 (3) (2009) 395–401. [11] B. Rico-Villa, J.-R. Le Coz, C. Mingant, R. Robert, Influence of phytoplankton diet mixtures on microalgae consumption, larval development and settlement of the Pacific oyster Crassostrea gigas (Thunberg), Aquaculture 256 (1) (2006) 377–388. [12] B. Rico-Villa, P. Woerther, C. Mingant, D. Lepiver, S. Pouvreau, M. Hamon, R. Robert, A flow-through rearing system for ecophysiological studies of Pacific oyster (Crassostrea gigas) larvae, Aquaculture 282 (1) (2008) 54–60. [13] M. Sprung, Physiological energetics of mussel larvae (Mytilus edulis), I. Shell growth and biomass. Marine Ecology-Progress Series. 17 (9) (1984) 283–293. [14] M. Sprung, Physiological energetics of mussel larvae (Mytilus edulis). II. Food uptake, Marine Ecology-Progress Series 17 (9) (1984) 295–305. [15] R. Strathmann, E. Leise, On feeding mechanisms and clearance rates of molluscan veligers, The Biological Bulletin. 157 (3) (1979) 524–535. [16] M. Suquet, F. Rimond, J. Cosson, J. Wilson-Leedy, L. Lebrun, I. Queau, C. Mingant, C. Fauvel, Effect of age and environmental conditions on the movement characteristics of Pacific oyster (Crassostrea gigas) trochophores, Journal of Applied Ichthyology. 29 (5) (2012) 1145–1148. [17] J.G. Wilson-Leedy, R.L. Ingermann, Development of a novel CASA system based on open source software for characterization of zebrafish sperm motility parameters, Theriogenology 67 (3) (2007) 661–672.
Contents lists available at ScienceDirect
Physiology & Behavior journal homepage: www.elsevier.com/locate/phb
A feeding model of oyster larvae (Crassostrea angulata) Tianlong Qiu a, Ying Liu a,⁎, Jimeng Zheng a, Tao Zhang a, Jianfei Qi b a b
National & Local Joint Engineering Laboratory of Ecological Mariculture, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, PR China Fujian Fisheries Research Institute, Xiamen 361013, PR China
H I G H L I G H T S • • • •
We established a feeding model that describes the oyster larva feeding behavior. The defined filtration coefficient explains the larval feeding feature. We found a relationship between feeding and morphological, motive features. Larval length is the only parameter needed for ingestion rate estimation.
a r t i c l e
i n f o
Article history: Received 8 February 2015 Accepted 23 April 2015 Available online 24 April 2015 Keywords: Oyster larva Feeding behavior Swimming speed Ingestion rate Filtration rate Filtration coefficient Feeding model
a b s t r a c t There is a need to develop more efficient rearing systems for the aquaculture of economically important bivalves, such as oysters. Here, we constructed a model that describes the feeding behavior of larval Crassostrea angulata oysters and tested it in an experimental setting. Larval ingestion rate is closely correlated with larval length. Based on our model, we showed that larval swimming speed, velum diameter and the filtration coefficient, which also determine the ingestion rate, are also correlated with larval length. Our model integrates morphological, locomotory and feeding behavior parameters to establish a relation between them and so provides a mathematical way to describe variation in the feeding behavior of bivalve larvae. The results of this study could facilitate the precise management of the aquaculture of bivalve larvae, in particular the optimum prey density and feeding rate of these important organisms. © 2015 Published by Elsevier Inc.
1. Introduction There are several rearing systems in use in the aquacultural industry, with the recirculating aquaculture system (RAS) having a superior performance compared with traditional culture methods in many aquacultural fields [3,6]. In aquacultural settings, shellfish larvae are currently hatched and reared using a high energy-consuming method that requires frequent renewal of seawater and tank cleaning, which is far from ideal. The feeding behavior of oyster larvae is the basis on which larval hatcheries have been developed. Although there have been some studies on the feeding characteristics of oyster larvae, including diet selection, ingestion rate, and filtration rate [1,8,11,15], the resulting information remains inadequate for the development of an efficient
⁎ Corresponding author. E-mail address: [email protected] (T. Qiu), [email protected] (Y. Liu), [email protected] (J. Zheng), [email protected] (T. Zhang), [email protected] (J. Qi).
http://dx.doi.org/10.1016/j.physbeh.2015.04.043 0031-9384/© 2015 Published by Elsevier Inc.
and, therefore, more economically viable, high-density larval breeding system. In addition, determination of the filtration and ingestion rates of larval oysters is limited to the population level because of the traditional study methods used, which mainly depend on the measurement of variation in microalgal concentration of the surrounding water. These results cannot fully explain the difference in filtration rate among different larval species and unexpected declines in the filtration rate of competent larvae. Therefore, results on a larval scale would increase our understanding of oyster larval feeding behavior, and would facilitate the precise management of high-density breeding of such larvae. In the current study, we developed a model that integrated the morphological, locomotory, and feeding behavior parameters of larval oyster and established the relations between these parameters. As we illustrate here, our model could be used to describe mathematically larval feeding behavior and the variation in ingestion and filtration rates. Such information would be useful to not only the aquacultural industry, but also marine ecologists, given the importance of larval bivalves to the zooplankton component of marine ecosystems.
170
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
2. Material and methods 2.1. Concepts and feeding model formulation Oyster larvae filter microalgae and swim by beating their cilia [4,15], and a complete cilial-beating circle of oyster larvae is similar to that of Vorticella, based on our observation and the description of Strathmann & Leise [15] and Blake & Otto [4] and as shown in Fig. 1. The effective and recovery strokes of the cilia propel the surrounding water through the oral groove and move the body of the larva. Thus, waterborne microalgae are transported to the oral groove, where some of them are caught by the oral groove cilia. Therefore, when filtering water (Fig. 2), oyster larvae can both move and capture microalgae. Suppose that the velum diameter is d, the velum area is s (approximately represented by the circular area in diameter d) and the swimming speed of larvae when feeding is v. When larvae filter water, they remove microalgae from the water. However, the filtering organ (i.e., velum) is not the only point at which microalgae are captured, because the oral groove cilia are also involved. Thus, the fraction of microalgae captured by the larval oral cilia compared with the total amount of microalgae filtered by the velum cilia is represented by k, which we define in the current study as the filtration coefficient. To construct the feeding model, we assumed that, when the larvae filter water they are also swimming, and the water volume calculated by velum area times the trajectory length (shown in Fig. 2 as s × vt) is equal to the volume of water that they filtered (i.e., total amount of water handled). Based on this assumption, the filtration rate (FR), which is defined as the volume of water swept clear in unit time [5] can be expressed as Eq. (1): −1 2 ¼ πkd v=4 FR μl larva−1 h
ð1Þ
ingestion rate (IR) can be expressed as Eq. (2): −1 IR cells larva−1 h ¼ C FR
ð2Þ
where C represents the microalgal concentration. If filtration is complete (k = 1), the filtration rate will equal the total water volume handled in unit time (TV).
Fig. 2. Oyster larva filtering water in a time unit. d, s, v represent the velum diameter, the velum area and the swimming speed of larvae respectively, dotted area represents the total water volume filtered by the larva.
aquarium, and flowed out from the aquarium via a drum filter upstream of the aquarium. The water flow velocity was set at 20 L/h, the larval densities (n) were set at approximately 10 to approximately 120 larvae mL− 1. By using this system, the microalgal concentration before entering and after leaving the aquarium (C1 and C2, respectively) could be measured. The average retaining time (tr) of microalgae was calculated using Eq. (3): t r ¼ V=Q
ð3Þ
where V (in L) represents the volume of the aquarium, and Q (in L/h) represents the flow velocity through the aquarium. We assumed that an infinitesimal amount of water (ΔV) moved from the inlet pipe to the outlet pipe and that any waterborne microalgae in that flow were fed on by the larvae in the aquarium. Therefore, we concluded that (Eq. (4)): Z 2 ðC1 –C2 ÞΔV ¼ ΔVnkvπd =4
tr 0
dt Ct :
ð4Þ
Under a continuous feeding system, the amount and flow of microalgae through the aquarium was constant enough to enable the larvae to catch their prey; therefore, the variation in microalgal concentration
2.2. Feeding character determination with a recirculating aquaculture system (RAS) To better describe the feeding behavior of larvae, we constructed a RAS (Fig. 3): larvae were cultured in a 6-L cylindroconical aquarium and microalgae were added from the inlet pipe downstream of the
Fig. 1. An example of a ciliary beat cycle showing the effective and recovery strokes, labels ①–⑦ show the ciliary beat sequence. Based on Blake & Otto [4] and Strathmann & Leise [15].
Fig. 3. Illustration of a recirculating aquaculture system (RAS) used in the larval feeding experiments.
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
171
was linear. Thus Ct, which represents the variation in microalgal concentration variation of ΔV during time tr, can be replaced by (C2 + C1) / 2, simplifying Eqs. (4) to (5): 2
C2 –C1 ¼ t r ðC2 þ C1 Þnkvπd =8:
ð5Þ
Given that C2, C1, n, v, d, and tr can be measured using the RAS set-up, only k needs to be calculated separately. 2.3. Experimental protocol for parameter estimation 2.3.1. Larvae collection and rearing conditions The larvae of the oyster Crassostrea angulata were collected by artificial fertilization using more than ten female and ten male oysters. The eggs and sperms were well mixed before fertilization. Resulting fertilized eggs were hatched and reared in sea water with a salinity of 30 ppt, at 24–29 °C in 400-L aquariums for use in the RAS experiments and also to determine swimming speed and velum diameter. In the 400L aquarium, the larvae were cultured at a density of 6–10 larvae mL−1 and fed with live Chlorella sp. (3.10 ± 0.4 μm in diameter, n = 30) and Isochrysis sp. (4.42 ± 0.6 μm in diameter, n = 30). In the RAS feeding experiments, Isochrysis sp. were mainly used because they are a suitable food for oyster larvae [1,11], Chlorella sp. were used when there was a shortage of Isochrysis sp. If this was the case, then we used the conversion of 1 Isochrysis sp. cell =2.9 Chlorella sp. cells based on their volume. The concentration of microalgae at the inlet and outlet pipes and also the larval cultural density for each treatment were sampled simultaneously; 3% formalin was added to the sample to maintain the microalgal concentrations for measurement. Precise C1 and C2 concentrations were measured using a 0.5-mL phytoplankton-counting grid manufactured by HYDRO-BIOS, and at least ten grids were counted for each sample. 2.3.2. Swimming speed of oyster larvae (v) Computer-assisted sperm analysis (CASA) has been used in previous studies to assess the swimming speed of trochophore and D-shaped larvae [9,16,17]. However, the locomotory behavior of the larger veliger larvae is more complex compared with these smaller larvae. In the current study, larvae were placed in a horizontal counting grid (380 mm2 and 1.32 mm deep) and the locomotory behavior of the oyster larvae were then recorded with a microscope (40 ×) and a camera. Observations showed that, by adjusting the beating frequency, oyster larvae can feed while swimming, feed without swimming, or swim fast with or without feeding. The swimming pattern is known to vary with the satiation of the larvae by our observation, in that the larvae swam more actively when hungry, whereas when they were fully fed, they preferred to remain still. Therefore, the larval swimming speed was measured after the larvae had been fully fed 1–2 h previously.
Fig. 4. Larval velum diameter and shell length measurements.
to ~320 μm (eyed larvae). Observations also showed that, under certain water conditions (pH 8.1–8.3, dissolved oxygen 6.–6.8 mg L−1, temperature 24–30 °C, salinity 29–32), larval swimming speed was influenced by the degree of stomach satiation. Larvae remained still when they were fully fed or if there was sufficient food present (e.g. 106 microalgae cells mL−1), but swam at a moderate speed when they were filtering microalgae (~ 0.5 mm s− 1 to ~ 6 mm s−1; Fig. 5). Basing on these data, we determined the relation between larval length l (μm) and the swimming speed v (μm s−1) to be (Eq. (6)): 2 v ¼ –0:1004 l þ 59:699 l–2887; l∈ð70; 320 μmÞ R2 ¼ 0:9895 :
3.2. Velum diameter (d) of C. angulata By measuring more than 100 anesthetized C. angulata larvae, a linear relation was found between velum diameter d (μm) and larval length l (μm), which can be expressed by Eq. (7) (Fig. 6): d ¼ 0:9243 l–20:223 R2 ¼ 0:9615 :
ð7Þ
3.3. Parameter estimation of filtration coefficient (k) For each of the experimental results shown in Table 1, the filtration coefficient k was determined basing on Eqs. (5)–(7) and the relation between k and l is shown in Fig. 7. The filtration coefficient ranged from approximately 0.05 to 0.6 according to the calculated results.
2.3.3. Measurement of velum diameter (d) The larvae of different developmental stages were anesthetized by magnesium chloride (MgCl2) and the velum diameter of more than 100 larvae as shown in Fig. 4 was measured. The velum is not exactly circular, varying from nearly circular during the early developmental stages to elliptical in the late pelagic stage; therefore, for convenience, the diameter of the velum (d) was measured as the main parameter of the larval velum in all larval developmental stages. 3. Results 3.1. Swimming speed (v) of C. angulata Analysis of more than 200 larval videos showed that the swimming speed of larval C. angulata varied from 0.0 mm s−1 to ~9.5 mm s−1, with the corresponding shell length varying from ~70 μm (D-shaped veliger)
ð6Þ
Fig. 5. Swimming speed of oyster larvae (mean ± SD).
172
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
Fig. 7. Relation between the filtration coefficient k and larval length. Fig. 6. Relation between velum diameter and shell length.
3.4. A feeding model for larval C. angulata oysters Pearson correlation analysis showed that the filtration coefficient k has a negative correlation with larval length (r = − 0.739, P b 0.001) compared with microalgal concentration (r = − 0.597, P = 0.001) and cultural density (r = 0.546, P = 0.003). From the data of larval length and the filtration coefficient k, we can obtain an exponential relation (Eq. (8)):
Using the relation determined between larval length and larval swimming speed, velum diameter, and filtration coefficient, we constructed a feeding model for larval C. angulata based only larval length data. The FR and IR of one oyster larva with larval length l can be expressed by Eqs. (9) and (10), respectively: 2
ð9Þ
FR ¼ kd vπ=4
k ¼ 1:1358e−0:01l R2 ¼ 0:4944
ð8Þ
Although k is a parameter affected mainly by a larva itself, it varied when the microalgal concentration and environmental factors changed. Eq. (8) was established in a moderate microalgal concentration of 4000–12,000 cells mL−1. This concentration was determined based on our previous experimental results that a concentration of ~10,000 cells mL−1 was a suitable concentration to use in RAS.
IR ¼ C FR
ð10Þ
and the other parameters can be calculated using Eqs. (11)–(13): 2 v ¼ –0:1004 l þ 59:699 l–2887 R2 ¼ 0:9895
ð11Þ
d ¼ 0:9243 l–20:223 R2 ¼ 0:9615
ð12Þ
k ¼ 1:1358e−0:01l R2 ¼ 0:4944 :
ð13Þ
Thus, Table 1 Results of larval culture in RAS. No.
C1 cells mL−1
C2 cells mL−1
Q L h−1
n larvae mL−1
l μm
k
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
4655 4655 4655 6555 6555 6555 4655 4655 9025 10,070 4655 10,070 11,500 10,070 9025 7000 7000 9025 7000 11,500 12,160 12,160 11,500 11,000 11,000 3046a 5634a
2280 2470 2470 2860 2620 2375 1520 2755 5795 5795 1680 4990 3800 6600 6650 4933 6433 7980 4500 6700 8600 9880 6760 6600 8000 1801* 4232*
20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 30
123 121 87 67 75 95 87 77 36 45 65 90 90 54 24 36 8 10 24 54 34 18 45 34 18 7 14
114 114 114 124 124 124 126 126 139 139 146 152 152 153 159 164 164 165 171 177 191 195 212 221 230 240 241
0.33 0.30 0.42 0.50 0.49 0.42 0.47 0.27 0.34 0.33 0.34 0.15 0.23 0.15 0.22 0.15 0.16 0.19 0.24 0.12 0.10 0.10 0.08 0.09 0.10 0.36 0.15
a
Converted data of Isochrysis sp. from Chlorella sp.
IR ¼ 1:1358e−0:01l ð0:9243 l−20:223Þ ð70blb320 μmÞ:
2
2 −0:1004 l þ 59:699 l−2887 πC=4;
C represents the microalgal concentration in the cultural system RAS, which should be ~ 4000 to ~ 12,000 cells mL− 1 in this model. The ingestion rate based on this model is shown in Fig. 8 and varies from ~ 25 cells larva−1 h−1 to ~ 680 cells larva−1 h−1 when the larva is fed with ~ 10,000 cells mL− 1 Isochrysis sp. Therefore, this model
Fig. 8. Predicted ingestion rate of C. angulata larvae with a microalgal concentration of 104 cells mL−1.
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
173
suggests a method to construct a feeding management strategy for bivalve larvae rearing in RAS, and will help in the automatic management of larval rearing. 4. Discussion and conclusion 4.1. The filtration coefficient k The filtration coefficient k is directly determined by the filtrating ability of velum cilia and the ability of oral cilia to capture microalgae. Based on the size and morphology of the oral groove, there is likely to be a threshold number of cells that a larva can catch in unit time. If the microalgal concentration exceeds that threshold, the larva would be unable to capture all the algae that pass through the oral groove, and so k would decrease. On the other hand, an excessively high culture density of larvae would cause a more frequent collision between individuals and influence their swimming and feeding behavior [2,13], which would then influence the filtration coefficient. During larval development, the size of the oral groove does not grow proportionally with velum diameter. Basing on data from photos of five larvae that clearly showed the oral groove and velum, the ratio of oral groove width to velum diameter varies from 0.35 to 0.20 as larval length increases from 150 μm to 220 μm; this morphological feature could be one explanation for the decreasing trend in filtration coefficient. Strathmann & Leise [15] calculated the fraction of particles caught out of the total number of particles by larvae of the oyster Crassostrea gigas (larval length ~ 90 μm) to be 0.44, which is close to our result (~0.46) based on Eq. (8). Strathmann and Leise [15] also found that in the three species C. gigas, Tritonia diomedea, and Nassarius obsoletus, one with longer pre-oral cilia cleared particles at a higher rate but with less efficiency in capturing prey. This phenomenon is in accordance with our result that larger larvae (which have longer pre-oral cilia) have a smaller filtration coefficient. Our results also show that, as the microalgal concentration increased, the filtration coefficient did not, but instead leveled out when the microalgal concentration was approximately 4000–10,000 cells mL−1. This suggests that, although the concentration of filtered microalgae increases, the number of ingested microalgae does not above a certain density threshold, as previously shown by Rico-Villa et al. [10]. This indicates that, when developing a RAS, the concentration of microalgae should be maintained at a level that not only facilitates larval feeding, but also can keep a low requirement for the cultural system itself. This concentration should be ~ 10,000 cells mL−1 for C. angulata fed with Isochrysis sp., balancing the larval feeding and the requirement of RAS. 4.2. Filtration rate and ingestion rate of oyster larvae During the pelagic larval period, the filtration rate (FR) increases with larval size, whereas it decreases approaching metamorphosis [8, 12]; a similar situation is seen with the ingestion rate (IR), which is obtained by IR = C FR. Oyster larvae, similar to adult oysters, can regulate their feeding activity according to the surrounding food concentration [8]. In our experiments, larvae that fed on high-density microalgae, ceased feeding once they were satiated. The morphological change approaching metamorphosis, which is likely to reduce the ability to filter, was thought to explain this decrease in filtration rate [8]. In our model, the combination of decreasing filtration coefficient and decreasing swimming speed during metamorphosis explained this phenomenon. The FR results from Eq. (9) (shown in Fig. 9) are within the range of ~ 2.5–~ 67 μl larva− 1 h− 1. This result approximates that of Gerdes [8], who studied C. gigas (0.5–100 μl larva− 1 h− 1) and also those of Sprung [14], who studied Mytilus edulis (10–61 μl larva−1 h− 1) with a larval length of 120–250 μm. The rate of total water volume filtered by the larvae calculated based on the velum diameter and swimming speed (TV = π d2 v/4) varied from 5 μl larva− 1 h− 1
Fig. 9. Predicted filtration rate of, and the total water volume filtered by, a larval C. angulata oyster.
to ~1200 μl larva−1 h−1 as shown in Fig. 9. Unlike FR, TV continues to increase during the pelagic period until metamorphosis. In a set larval developmental period, the filtration rate is approximately a constant value in a low microalgal-concentration environment (b 10,000 cells mL−1) with stable environmental factors. However, the filtration rate tested in the laboratory always fluctuates: as the cell concentration increases, the filtration rate usually decreases [8,5,7]. There are several factors that could influence measuring the filtration rate, including microalgae size and concentration, and satiation of the larval gut [8,14,5]. Therefore, to reduce this effect, measurement of filtration rate has to be done quickly (usually several hours). When previously starved larvae were exposed to an environment with highdensity microalgae, the ingestion rate increased to above the ingestion capacity level, leading to misestimation of both the ingestion and filtration rates [14].
4.3. Model adaptation Environmental factors (e.g., temperature, pH, and salinity) could have effects on the beating frequency of cilia and, thus, affect the swimming speed of larvae. However, some studies have shown these factors to have little effect if in a moderate range: for example, Strathmann & Leise [15] found that the mean angular velocity of the pre-oral cilia of C. gigas at ~ 20 °C was only slightly greater than at 12–13 °C, and the difference was not significant. Suquet et al. [16] found that adjusting the pH of seawater to values from 5.10 to 9.08 had no effect on the swimming characteristics of C. gigas trochophores. This would facilitate the application of the model to a wider range of environmental conditions; however, we did not have enough data to investigate whether this relation would hold true under extreme environmental change.
5. Conclusion The results of this study increase current knowledge of larval feeding and, by describing larval feeding features directly, the ingestion and filtration rates can be calculated mathematically. In addition, this study provides a new way of determining larval feeding and locomotory behavior, which could help develop more efficient bivalve aquacultural systems.
Acknowledgments This study was funded by the 56th China Postdoctoral Science Foundation, Postdoctoral Innovation Project Special Funds of Shandong Province (2014), the National Key Technologies R&D Program (2014BAD08B09) and an earmarked fund for Modern Agro-industry Technology Research Systems (CARS-48).
174
T. Qiu et al. / Physiology & Behavior 147 (2015) 169–174
References [1] S. Acarli, A. Lok, Comparison of Isochrysis galbana and Chlorella sp. Microalgae on growth and survival rate of European flat oyster (Ostrea edulis, Linnaeus 1758) larvae, Indian Journal of Marine Sciences 40 (1) (2011) 55–58. [2] C. Avila, S. Grenier, C. Tamse, A. Kuzirian, Biological factors affecting larval growth in the nudibranch mollusc Hermissenda crassicornis (Eschscholtz, 1831), Journal of experimental marine biology and ecology. 218 (2) (1997) 243–262. [3] M. Badiola, D. Mendiola, J. Bostock, Recirculating Aquaculture Systems (RAS) analysis: main issues on management and future challenges, Aquac. Eng. 26-35 (2012). [4] J. Blake, S. Otto, Ciliary propulsion, chaotic filtration and a ‘blinking’ stokeslet, Journal of engineering mathematics. 30 (1–2) (1996) 151–168. [5] D.J. Crisp, A.B. Yule, K.N. White, Feeding of oyster larvae: the functional response, energy budget and a comparison with mussel larvae, Journal of the Marine Biological Association of the United Kingdom. 65 (3) (1985) 759–783. [6] J.M. Ebeling, M.B. Timmons, Recirculating Aquaculture Systems, in: J. Tidwell (Ed.), Aquaculture Production Systems, John Wiley&Sons, Inc. 2012, pp. 245–277. [7] J. Fang, H. Sun, S. Kuang, X. Liang, X. Niu, Z. Liu, F. Li, Study on the filtration and ingestion rate of bloody clam larvae tegillarca granosa, Oceanologia Et Limnologia Sinica. 30 (1999) 170–178. [8] D. Gerdes, The Pacific oyster Crassostrea gigas: part I. Feeding behaviour of larvae and adults, Aquaculture 31 (2) (1983) 195–219. [9] T.J. Hilbish, K. Sasada, L.S. Eyster, J.A. Pechenik, Relationship between rates of swimming and growth in veliger larvae: genetic variance and covariance, Journal of Experimental Marine Biology and Ecology. 239 (2) (1999) 183–193.
[10] B. Rico-Villa, S. Pouvreau, R. Robert, Influence of food density and temperature on ingestion, growth and settlement of Pacific oyster larvae, Crassostrea gigas, Aquaculture 287 (3) (2009) 395–401. [11] B. Rico-Villa, J.-R. Le Coz, C. Mingant, R. Robert, Influence of phytoplankton diet mixtures on microalgae consumption, larval development and settlement of the Pacific oyster Crassostrea gigas (Thunberg), Aquaculture 256 (1) (2006) 377–388. [12] B. Rico-Villa, P. Woerther, C. Mingant, D. Lepiver, S. Pouvreau, M. Hamon, R. Robert, A flow-through rearing system for ecophysiological studies of Pacific oyster (Crassostrea gigas) larvae, Aquaculture 282 (1) (2008) 54–60. [13] M. Sprung, Physiological energetics of mussel larvae (Mytilus edulis), I. Shell growth and biomass. Marine Ecology-Progress Series. 17 (9) (1984) 283–293. [14] M. Sprung, Physiological energetics of mussel larvae (Mytilus edulis). II. Food uptake, Marine Ecology-Progress Series 17 (9) (1984) 295–305. [15] R. Strathmann, E. Leise, On feeding mechanisms and clearance rates of molluscan veligers, The Biological Bulletin. 157 (3) (1979) 524–535. [16] M. Suquet, F. Rimond, J. Cosson, J. Wilson-Leedy, L. Lebrun, I. Queau, C. Mingant, C. Fauvel, Effect of age and environmental conditions on the movement characteristics of Pacific oyster (Crassostrea gigas) trochophores, Journal of Applied Ichthyology. 29 (5) (2012) 1145–1148. [17] J.G. Wilson-Leedy, R.L. Ingermann, Development of a novel CASA system based on open source software for characterization of zebrafish sperm motility parameters, Theriogenology 67 (3) (2007) 661–672.