Elsevier

Journal of Sea Research

Volume 66, Issue 4, November 2011, Pages 349-360
Journal of Sea Research

Effect of phytoplankton and temperature on the reproduction of the Pacific oyster Crassostrea gigas: Investigation through DEB theory

https://doi.org/10.1016/j.seares.2011.07.009Get rights and content

Abstract

DEB theory can be used to obtain a detailed description of energy allocation in organisms and the control of this allocation by temperature and food concentration. In this study, we modified the model of Bourlès et al. (2009) developed for the Pacific oyster, Crassostrea gigas, to improve the description of reproductive effort. The model was amended in two ways: a new set of parameters was incorporated and a full description of gonad construction in spring was added, with a new state variable. The application of this model to a dataset for oyster growth measured in four bays over two years showed that this model better described reproductive effort, without modifying overall growth dynamics. We then explored the reproductive responses of oysters to their environment in greater detail, by applying this new version of the model with the theoretical forcing variables of phytoplankton concentration and temperature. Spawning time was found to be driving principally by yearly mean temperature, and reproductive effort was found to depend mostly on the half-saturation coefficient of the functional response. These results highlight the importance of the half-saturation coefficient and provide additional support for field research on the food preferences of oysters.

Highlights

► We developed an improved version of the DEB model for Pacific oyster, C. gigas. ► This model is used to give a deep insight into the ecophysiology of reproduction and the ecology of this species. ► It gives another utilization of the DEB theory as a tool to better understand ecology processes.

Introduction

The link between larval stage and subsequent population dynamics, known as supply-side ecology (Grosberg and Levitan, 1992, Underwood and Fairweather, 1989), has been investigated in detail, in studies of the recruitment of marine benthic invertebrates. The relationship between the supply of oocytes from adults and the abundance of larvae for subsequent recruitment has been investigated less thoroughly, and much remains unclear, particularly for bivalves (MacKenzie, 1996, Marshall et al., 2009). The principal reason for this may be the difficulties involved in simultaneously obtaining data for stock size, fecundity – defined as the number of eggs produced per individual – and recruitment over a long time period or a broad geographical range.

Although conclusive studies are lacking, some previous work stresses the fact that oocyte supply may, under certain conditions, influence subsequent recruitment. For corals, Hughes et al. (2000) found a link between spatial fecundity and recruitment, defined in this study as the percentage of colonies with ripe oocytes. For the blue crab, links between spawning stock and larval abundance and between spawning stock and recruitment were shown by Lipcius and Stockhausen (2002). In studies on bivalves, Honkoop et al. (1998) found no link between fecundity and recruitment for Macoma balthica, but did report a relationship between winter temperature and subsequent recruitment. Using stock size, Kraeuter et al. (2005) showed a stock recruitment relationship at low stock densities for Mya arenaria. There may thus be a link between oocyte supply and subsequent recruitment, but available studies do not allow us to derive a general pattern.

In Pacific oyster, variability in reproductive effort has already been proposed as a possible reason for recruitment variability (Deslous-Paoli et al., 1982). The authors of this previous study suggested that unfavourable food and temperature conditions might lead to abnormal gametogenesis and delayed spawning. Temperature is, effectively, an important driver of gametogenesis in C. gigas populations. A minimum temperature seems necessary to initiate gametogenesis (Chavez-Villalba et al., 2002a, Fabioux et al., 2005). Temperature also influences the speed of gamete development, making day degrees a useful measure to indicate when oysters in hatcheries are ripe (Mann, 1979). Once gametogenesis is complete, there is a minimum temperature requirement for spawning. Castaños et al. (2009) estimated this minimum temperature threshold at 17 °C. Pouvreau et al. (2006) used 20 °C in their model, but many other studies have been carried out and have given different values.

Food availability is thought to regulate the number of gametes produced (Chavez-Villalba et al., 2002b) and Auby and Maurer (2004) found a positive correlation between the condition index of C. gigas oysters before spawning, reflecting fecundity, and mean chlorophyll a concentration in spring. They also found that this condition index was related to larval supply, suggesting that fecundity may play a role in larval supply. However, feeding is not always necessary for the completion of gametogenesis, which may instead depend on prior storage (Cannuel and Beninger, 2005, Muranaka and Lannan, 1984). The fact that oysters with large energy reserves at the start of gametogenesis ripen before oysters with smaller reserves (Chavez-Villalba et al., 2002b), indicates an important contribution of feeding conditions before gametogenesis.

These studies suggest that the quantification of both temperature and food availability is required to describe the energetic pathway leading to gametogenesis in the Pacific oyster. Biochemical studies have already provided insight into this pathway (Deslous-Paoli and Héral, 1988). These authors showed that C. gigas lost up to 70% of its energy during spawning. DEB theory, based on a multi-specific and axiomatic approach (Kooijman, 2010, Sousa et al., 2008), provides a general description of energy allocation based on these two forcing variables (temperature and food). Several studies have already been carried out on Pacific oysters and have built the parameter set for this species (Ren and Ross, 2001, van der Veer et al., 2006), which has been tested in various environments (Alunno-Bruscia et al., 2011, this issue; Bacher and Gangnery, 2006, Bourlès et al., 2009, Pouvreau et al., 2006).

Following on from previous work on the oyster DEB model, the objective of this study was to focus on the influence of both food and temperature on reproductive effort and spawning. More precisely, we wanted to quantify how reproductive effort – in terms of the number of gametes produced – and spawning date could be altered by forcing variables. In order to validate the oyster DEB model over a wide range of phytoplankton concentrations and temperatures, we used datasets for four sites along a latitudinal gradient corresponding to the French Atlantic coast, in 2008 and 2009. We used phytoplankton concentration as a proxy for food, because it has been shown to describe oyster growth more precisely than chlorophyll-a concentration (Bourlès et al., 2009).

To improve simulation, we modified the original version of the C. gigas DEB model published by Bourlès et al. (2009). We altered the model to improve its description of the observed reproductive effort, in terms of dry flesh mass, for all sites and years, by changing the values of several parameters and adding a new state variable for the specific description of gonad allocation. For each site and each year, the new model reproduced the observed reproductive effort more accurately than the previous model. At the end of this paper, we provide a theoretical description of the variation of reproductive effort as a function of temperature and phytoplankton concentration, based on this improved model of energy allocation in oyster.

Section snippets

Standard DEB model

The model used here is derived from the standard DEB model presented by Kooijman (2010). A detailed description of the initial model for Pacific oyster can be found in Pouvreau et al. (2006) and a modified version can be found in Bourlès et al. (2009). We therefore provide only a brief overview of this model here. It uses three energetic state variables expressed in joules: the energy stored in reserves, E, the energy used in the building of the structure, EV, and the energy used for

Field simulations with the two versions of the model

The simulations obtained with the model of Bourlès et al. (2009) is consistent with observations for both the spring and summer periods, but show a low fit for the autumn period (Fig. 4). In spring, an exception was identified for the bay of Brest in 2009, for which the growth observed in April and May is not reproduced by the model, whatever the Xk parameter chosen. However, despite these reasonably good descriptions of spring growth, simulations with this version of the DEB model do not

Improvement of the model

In this study, we modified the value of five important parameters in the oyster DEB model: {p˙Am}, [p˙M], [EG], [Em] and μE. We also increased the complexity of the description of energy allocation to reproduction by adding one state variable EGo and three related parameters: dGo, [EGo] and YGo. These changes do not fundamentally alter the dynamics of the model, as only slight differences are detected between the two sets of simulations we made, but our modifications improve the estimation of

Conclusion

In conclusion, our results highlight the sensitivity of this DEB model to the parameters of the functional response. We show here that a change in the value of the maximum assimilation rate, {p˙Am}, allowed a better respect of experimental information concerning the energy content of the flesh, without changing the overall dynamics, if we also simultaneously change three fundamental parameters: [p˙M], [EG] and [Em]. In theoretical simulations, it appears that spawning date is driven by mean

Acknowledgements

This research was part of the VeLyGer project supported by the French Ministry of Agriculture (DPMA), the European Community (FEP) and IFREMER (conv. no. 30 114–2008). This study benefited from intensive discussions with D. Maurer, I. Auby and members of the AquaDEB group led by M. Alunno-Bruscia. It was made possible by the assistance of the personnel from IFREMER LER, who carried out biometric measurements of oysters in the field: F. d'Amico for the bay of Arcachon, S. Robert, P. Guilpain,

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