Liady M N D, Tangou T T, Fiogbe E D, Cauchie H-M, Vasel J-L
Unité: Assainissement et Environnement, Département Sciences et Gestion de l'Environnement, Université de Liège, Avenue de Longwy, 185-B 6700 Arlon, Belgium E-mail:
Unité de recherche sur les zones humides, Département de Zoologie, Université d'Abomey-Calavi, 01 B.P. 526 Cotonou, Benin.
Water Sci Technol. 2015;71(10):1436-43. doi: 10.2166/wst.2015.107.
A reliable characterization of cladocerans' growth kinetic on their substrates is crucial for the estimation of their biochemical conversion rate in pond models. Although many studies reported cladocerans' growth inhibitions by high chlorophyceae contents, their growth kinetics had continued to be described in many pond system models by Monod-type kinetic, which describes growth saturation by high substrate contents, but fails to explain the disappearance of cladocerans observed during chlorophyceae's bloom periods. This study aimed to develop a methodology and assess whether growth-inhibition-type models used to describe microbial growth kinetics can be applicable to cladocerans. Experiments were carried out using Daphnia pulex populations and Scenedesmus sp. First, biomass of D. pulex was measured through digital image processing (DIP) during growth experiments. Then, three candidate models (i.e., Andrews, Edward and Haldane models), along with the Monod model, were fitted to the observed data and compared. The results showed that the DIP technique provided reliable results for estimating the biomass of D. pulex. Our findings show that the candidate growth inhibition-type models satisfactorily described D. pulex's growth kinetic (86% variance accounted for). Scenesdemus sp. were not strong inhibitors of the growth of D. pulex (high inhibition constant and low half-saturation constant found).
可靠地表征枝角类在其底物上的生长动力学对于估算其在池塘模型中的生化转化率至关重要。尽管许多研究报告了高绿藻含量对枝角类生长的抑制作用,但在许多池塘系统模型中,它们的生长动力学仍继续用莫诺德型动力学来描述,该动力学描述了高底物含量下的生长饱和,但无法解释在绿藻大量繁殖期观察到的枝角类消失现象。本研究旨在开发一种方法,并评估用于描述微生物生长动力学的生长抑制型模型是否适用于枝角类。使用大型溞种群和栅藻进行了实验。首先,在生长实验期间通过数字图像处理(DIP)测量大型溞的生物量。然后,将三个候选模型(即安德鲁斯模型、爱德华模型和霍尔丹模型)与莫诺德模型一起拟合到观测数据并进行比较。结果表明,DIP技术为估算大型溞的生物量提供了可靠的结果。我们的研究结果表明,候选生长抑制型模型令人满意地描述了大型溞的生长动力学(方差解释率为86%)。栅藻对大型溞的生长不是强抑制剂(发现抑制常数高且半饱和常数低)。