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Marine Biology

, Volume 137, Issue 3, pp 379–392 | Cite as

Effects of chronic copper exposure on the green mussel Perna viridis

  • P. W. C. Sze
  • S. Y. Lee

Abstract

The effects of chronic copper exposure on growth and physiological responses of the green mussel Perna viridis were investigated by exposing the mussels to 50 μg l−1 Cu for 3 mo at 17 and 25 °C. These temperatures represent, respectively, the winter and summer seawater temperatures in Hong Kong. Differences in the level of response between mussels exposed for 3 mo to 50 μg Cu l−1 generally increased with duration of exposure. The tissue concentration of copper had increased by 280 and 450% after 3 mo exposure at 17 and 25 °C, and growth performances were reduced, with the 25 °C sets suffering from larger negative impact of copper in most responses. The inhibitory effects of copper on production of the various body components generally followed the order linear shell growth (greatest) > tissue production > byssus production > shell production. There were also decreases in the condition index (43 and 35% reductions at 17 and 25 °C), clearance rates (10.3 and 18.5%), faeces production (11 and 16.3%), assimilation efficiency (6.8 and 9.2%) and oxygen consumption rate (12.8 and 24.8%). In contrast, the organic content of the faeces (9.2 and 13.2% increases at 17 and 25 °C) and rate of ammonia excretion (21 and 28.6%), increased upon chronic copper exposure. Many of the responses (e.g. changes in tissue copper content, body dry wt, shell organic content, clearance rate and oxygen consumption rate) exhibited fluctuating levels of impact during prolonged copper exposure, while others (e.g. faecal production rate, assimilation efficiency, tissue organic content) demonstrated steady decreasing trends with increasing exposure time.

Keywords

Organic Content Oxygen Consumption Rate Shell Growth Ammonia Excretion Assimilation Efficiency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • P. W. C. Sze
    • 1
  • S. Y. Lee
    • 1
  1. 1.The Swire Institute of Marine Science and Department of Ecology and Biodiversity, The University of Hong Kong, Pokfulam Road, Hong KongCN

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