|The effect of size on the response of Pacific oysters (Crassostrea gigas) to changes in water temperature and air exposure|
|Song, L.; Li, X.; Clarke, S.; Wang, T.; Bott, K. (2007). The effect of size on the response of Pacific oysters (Crassostrea gigas) to changes in water temperature and air exposure. Aquacult. Int. 15(5): 351-362. dx.doi.org/10.1007/s10499-007-9098-x|
|In: Aquaculture International. Springer: London. ISSN 0967-6120, more|
Air exposure; Lysosomes; Size; Temperature; Crassostrea gigas (Thunberg, 1793) [WoRMS]; Marine
|Authors|| || Top |
To further improve the technology used in Pacific oyster farming, information is required on the response of different sized and aged oysters to various environmental changes. In this study a neutral red retention (NRR) assay was used to investigate the effects of size and age on the response of Pacific oysters to changes in water temperature and their recovery after exposure to different air temperatures. Results from moving oysters directly between water temperatures of 5°C and 15°C, 10°C and 20°C and 15°C and 25°C demonstrated that different water temperature change affect the lysosomal membrane integrity differently. The NRR times of large and small oysters transferred directly between 10°C and 20°C initially decreased significantly, and then increased to levels corresponding to the new temperature. In addition, NRR times in large oysters responded at a significantly slower rate than small oysters when they were transferred from 5°C and 25°C to 15°C water and between 10°C and 20°C water. Results from the air exposure experiments showed that, after exposure to air temperatures of 5°C, 15°C or 25°C, the lysosomal membrane integrity of large oysters recovered at a slower rate in 15°C water compared to small oysters. It therefore appears necessary to develop different management strategies for large (old) and small (young) oysters. Results from this and previous research also indicate that the NRR assay could potentially be used to develop a model to monitor and predict the performance of oysters on farms.