Department of Natural Resource Ecology and Management, Iowa State University, 339 Science Hall II, Ames, IA, 50011, USA.
Iowa Department of Natural Resources, 15053 Hatchery Pl., Moravia, IA, 52571, USA.
Ecotoxicology. 2021 Mar;30(2):323-330. doi: 10.1007/s10646-020-02326-w. Epub 2021 Jan 13.
Identifying waterbodies where fish methylmercury concentrations are elevated is critical for development of consumption guidelines. However, mercury concentrations vary among waterbodies and fishes due to a suite of environmental conditions and detection of elevated mercury concentrations is imperfect, resulting in inaccurate consumption guidelines. Occupancy models may be a useful approach for addressing these issues but have not been used for these purposes. Our objectives were to use occupancy modeling to (1) estimate number of samples needed to detect mercury levels surpassing >0.30 mg/kg wet weight in fish at a waterbody (2) identify individual fish-level factors associated with detection probability, and (3) identify environmental-level factors linked to elevated mercury levels in fish at a waterbody. Mercury concentrations were estimated from >500 largemouth bass Micropterus salmoides and walleye Sander vitreus from 30 waterbodies throughout Iowa, USA to identify individuals with concentrations > or <0.30 mg/kg. Probability of detecting mercury concentrations >0.30 mg/kg varied between species and increased with fish length; consequently, more samples were needed to detect elevated mercury concentrations in small versus large fish. The probability of a waterbody having fish with elevated mercury levels increased with the percent grassland and declined with percent agriculture in the watershed, providing prioritization metrics for mercury surveillance programs. Our results demonstrate that occupancy models can be a valuable tool for mercury surveillance due to their ability to estimate necessary sample sizes and identify fish sizes and waterbodies with elevated mercury concentrations while accounting for imperfect detection probabilities.
确定鱼类甲基汞浓度升高的水体对于制定消费指南至关重要。然而,由于一系列环境条件的影响,水体和鱼类中的汞浓度存在差异,并且对汞浓度升高的检测并不完善,导致消费指南不准确。占据模型可能是解决这些问题的一种有用方法,但尚未用于这些目的。我们的目标是使用占据模型来:(1)估计在一个水体中检测到鱼类中汞含量超过>0.30mg/kg 湿重所需的样本数量;(2)确定与检测概率相关的个体鱼类因素;(3)确定与水体中鱼类中汞含量升高相关的环境因素。从美国爱荷华州 30 个水体中采集了超过 500 只大口黑鲈 Micropterus salmoides 和大眼梭鲈 Sander vitreus 的样本,以确定浓度>或<0.30mg/kg 的个体。检测>0.30mg/kg 汞浓度的概率因物种而异,并随鱼的长度增加而增加;因此,与小鱼相比,需要更多的样本才能检测到高浓度的汞。水体中鱼类汞含量升高的概率随流域内草地百分比的增加而增加,随农业百分比的增加而降低,为汞监测计划提供了优先排序指标。我们的结果表明,由于占据模型能够估计所需的样本量,并识别出具有高汞浓度的鱼类和水体,同时考虑到不完善的检测概率,因此该模型可以成为汞监测的一种有价值的工具。