Institute for Marine and Antarctic Studies, University of Tasmania, Private Bag 49, Hobart, TAS 7001, Australia.
Mar Pollut Bull. 2013 Aug 15;73(1):263-72. doi: 10.1016/j.marpolbul.2013.04.032. Epub 2013 Jun 26.
Mercury contamination of fish is dependent upon a system's ability to transform inorganic Hg into biologically available forms; however, fish biometrics also play an important role. To assess long term trends in Hg concentrations in sand flathead (Platycephalus bassensis) a polynomial model, corrected for fish length, was used to evaluate temporal trends and spatial variability, while growth rates were estimated using the Von Bertalanffy length-at-age model. Hg concentrations showed no decrease over time, and generally remained near recommended consumption levels (0.5 mg kg(-1)). Previously reported spatial differences in Hg concentrations were not supported by the data once the models were corrected for fish length. Growth rate variation accounted for a large part of the previously published spatial differences. These results suggest that inclusion of fish biometrics is necessary to facilitate an accurate interpretation of spatial and temporal trends of contaminant concentrations in long term estuarine and marine monitoring programs.
鱼类的汞污染取决于系统将无机汞转化为生物可利用形式的能力；然而，鱼类生物统计学也起着重要作用。为了评估砂平鲷（Platycephalus bassensis）中汞浓度的长期趋势，使用多项式模型（校正了鱼的长度）来评估时间趋势和空间变异性，同时使用 Von Bertalanffy 体长年龄模型估计生长率。汞浓度没有随时间下降，并且通常保持在推荐的食用水平（0.5 毫克/千克）附近。一旦根据鱼的长度对模型进行校正，就不再支持先前报告的汞浓度的空间差异。生长率的变化解释了先前发表的空间差异的很大一部分。这些结果表明，在长期的河口和海洋监测计划中，为了准确解释污染物浓度的时空趋势，必须包括鱼类生物统计学。
