Eawag: Swiss Federal Institute of Aquatic Science and Technology, Department Systems Analysis, Integrated Assessment and Modelling, Überlandstrasse 133, Dübendorf, Switzerland.
UFZ - Helmholtz Centre for Environmental Research, Department of System-Ecotoxicology, Permoserstraße 188, Leipzig, Germany.
Environ Sci Technol. 2016 Mar 15;50(6):3165-73. doi: 10.1021/acs.est.5b04068. Epub 2016 Mar 4.
Modeling community dynamics of aquatic invertebrates is an important but challenging task, in particular in ecotoxicological risk assessment. Systematic parameter estimation and rigorous assessment of model uncertainty are often lacking in such applications. We applied the mechanistic food web model Streambugs to investigate the temporal development of the macroinvertebrate community in an ecotoxicological mesocosm experiment with pulsed contaminations with the insecticide thiacloprid. We used Bayesian inference to estimate parameters and their uncertainty. Approx. 85% of all experimental observations lie within the 90% uncertainty intervals indicating reasonably good fits of the calibrated model. However, a validation with independent data was not possible due to lacking data. Investigation of vital rates and limiting factors in the model yielded insights into recovery dynamics. Inclusion of the emergence process and sub-lethal effects turned out to be potentially relevant model extensions. Measurements of food source dynamics, individual body size (classes), and additional knowledge on sub-lethal effects would support more accurate modeling. This application of a process-based, ecotoxicological community model with uncertainty assessment by Bayesian inference increased our process understanding of toxicant effects in macroinvertebrate communities and helped identifying potential improvements in model structure and experimental design.
水生无脊椎动物群落动态建模是一项重要但具有挑战性的任务，特别是在生态毒理学风险评估中。在这类应用中，系统的参数估计和严格的模型不确定性评估往往缺乏。我们应用基于机制的食物网模型 Streambugs 来研究昆虫杀虫剂噻虫啉脉冲污染的生态毒理学中试实验中大型无脊椎动物群落的时间发展。我们使用贝叶斯推断来估计参数及其不确定性。大约 85%的所有实验观测值都落在 90%的不确定性区间内，表明校准模型的拟合度相当好。然而，由于缺乏数据，无法进行独立数据的验证。对模型中的关键生命率和限制因素的调查提供了对恢复动态的深入了解。纳入出现过程和亚致死效应被证明是潜在相关的模型扩展。食物源动态、个体体型（类）的测量以及关于亚致死效应的其他知识将支持更准确的建模。这种基于过程的、具有不确定性评估的生态毒理学群落模型的应用，通过贝叶斯推断增加了我们对有毒物质对大型无脊椎动物群落影响的过程理解，并有助于确定模型结构和实验设计的潜在改进。
