The composition of mixed dechlorinating communities varies considerably in field and laboratory conditions. Dechlorinators thrive alongside with distinctive populations that help or hinder dechlorination. The variability of the composition of dechlorinating communities inevitably precludes a firm consensus regarding the optimal strategies for biostimulation. This lack of consensus motivated a model-based approach for the investigation of how the variability of the composition of a microbial community impacts the electron donor supply strategies for accelerating chloroethene removal. To this end, a kinetic model accounting for dechlorination in conjunction with cooperative and competing processes was developed. Model parameters were estimated using a multi-experiment, multi-start algorithm and data from research previously performed with two generations of a methane-producing, Dehalococcoides mccartyi-dominated consortium. The two generations of the consortium functioned comparably under maintenance conditions but performed divergently under high electron donor surpluses. The multi-experiment, multi-start algorithm overcame the hurdles of poor parameter identifiability and offered a probable cause for the different behaviors exhibited by each of the two generations of the chloroethene-degrading consortium: modest differences in the make-up of non-dechlorinators, which were minority populations, significantly influenced the fate of the offered electron donor.

混合脱氯群落的组成在现场和实验室条件下差异很大。脱氯者与有助于或阻碍脱氯的独特种群一起茁壮成长. 脱氯群落组成的可变性不可避免地排除了关于生物刺激最佳策略的坚定共识。这种缺乏共识激发了一种基于模型的方法来研究微生物群落组成的可变性如何影响加速氯乙烯去除的电子供体供应策略。为此，开发了结合合作和竞争过程的脱氯动力学模型。模型参数是使用多实验、多开始算法和先前对两代产甲烷Dehalococcoides mccartyi进行的研究数据估算的-主导的财团。该联盟的两代人在维护条件下的功能相当，但在高电子供体盈余下表现不同。多实验、多开始的算法克服了参数可识别性差的障碍，并为两代氯乙烯降解财团的每一代表现出的不同行为提供了可能的原因：非脱氯剂组成的适度差异是少数群体，显着影响了所提供电子供体的命运。