DYNAMIC ENERGY BUDGET MODELS FOR STUDYING THE THERMAL TOLERANCE OF EUROPEAN SEA BASS Dicentrarchus labrax AND MEAGRE Argyrosomus regius

Introduction

 Developing tools to describe temperature induced effects on fish becomes increasingly important for aquaculture in the context of climate change. Dynamic Energy Budget models can describe the bioenergetics of individual fish as a function of temperature and food availability and, thus,  offer means of studying the effects of temperature on relevant fish parameters and traits . In particular, temperature effects in DEB models are quantified via the parametrization and use of the Arrhenius function (Kooijman, 2010 ). Simulations can then be performed under different temperature conditions to study the effects on fish  traits, while the patterns in parameter values may be used to compare the bioenergetics and the thermal tolerance of different species (Freitas et al., 2010) . Here, we have parametrized DEB models with particular focus on higher temperatures for two aquaculture species, the European sea bass and the meagre, and developed a preliminary module for describing changes in body composition.

Materials and methods

 The DEB models were parametrized according to Marques et al . (2018) using experimental data and data from literature  and are provided in Stavrakidis Zachou et al .  (2019, 2021) . In addition, growth performance and respiration data at temperatures close to the edges of the species thermal tolerance range were included to parametrize the Arrhenius function and thus calculate a correction factor to describe  changes in the various physiological rates across the entire thermal tolerance range.

Moreover , a module is being developed to  model changes in the proximate composition of the fish reared under different temperature conditions.  This is done by simulating temperature driven changes in the model state variables such as reserve (E) and structure (V), which in DEB context comprise the fish biomass, and subsequently translating them to changes in proximate composition. 

Results and Discussion

 The two models were parametrized and validated against datasets from farms as well as experimental data at high temperatures.  The derivation of  parameters for the Arrhenius function revealed differences in the thermal tolerance patterns of the two species in terms of the optimal temperature as well as the decline of performance towards the edges of the tolerance range . As depicted by the calculated correction factor , a factor that compares the various metabolic rates to a reference temperature (here 20 oC , where it equals 1) (figure 1), the width of the tolerance range was similar for E. seabass and meagre . However, the peak (which represents the highest metabolic activity) was higher for the former and also shifted to the right, occurring at a higher temperature compared to meagre. . Moreover, the reduction of performance  at the upper end of the tolerance range  was sharper for E. seabasss.

 Compared to experimental data, the models could capture the decline in the voluntary feed intake and growth at temperature close to the upper end of the tolerance range, reasonably well. Provided that no shrinking occurs (reduction of structural mass) the energetic demands in DEB models are fueled only by the energy reserves. Consequently, p reliminary simulations  have shown that as temperature increases beyond the thermal optimum, the contribution of structure relative to that of reserve in the total biomass also increases. As a result, the model can depict some trends in body composition namely the increase in moisture content and the concomitant decrease in protein and lipid contents. Such trends are typically observed under low feeding or starvation conditions (Shirvan et al., 2020), which is also the case for high temperature regimes due to the reduction in appetite. Therefore, application of such DEB models in aquaculture not only offers means of elucidating and comparing thermal tolerance patterns across species, but may also provide tools to quantify thermal effects on growth and body composition.

References

Freitas, V., Cardoso J., Lika ,  K.,  Peck,  M.,  Campos,  J., Kooijman ,  S.A.L.M, van der Veer , H. (2010).  Temperature Tolerance and Energetics: A Dynamic Energy Budget-Based Comparison of North Atlantic Marine Species.” Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 365: 3553–65.

Kooijman , S.A.L.M. (2010) . Dynamic Energy Budget Theory for Metabolic Organisation. Cambridge University Press.

Marques, G.M. , Lika, K., Augustine, S. , Pecquerie, L. , Kooijman, S.A.L.M. (2019) Fitting multiple models to multiple  data sets. Journal of Sea Research, 143 , 48–56.

Shirvan , S., Falahatkar , B., Noveirian , H.A., Abbasalizadeh , A., 2020. Physiological responses to feed restriction and starvation in juvenile Siberian sturgeon  Acipenser baerii (Brandt, 1869): effects on growth, body composition and blood plasma metabolites. Aquaculture Research , 51, 282–291.

Stavrakidis-Zachou , O., Lika , K., Anastasiadis, P., Papandroulakis , N. (2021). Projecting climate change impacts on Mediterranean finfish production: a case study in Greece. Climatic Change, 165,  67.

Stavrakidis-Zachou , O., Papandroulakis , N., Lika, K. (2019). A DEB model for European sea bass (Dicentrarchus labrax ): parameterisation and application in aquaculture . Journal of Sea Research , 143, 262–271.