The hypersaline wetland of Meighan located in western Iran is an important habitat for Artemia parthenogenetica. The habitat condition of this native zooplankton is facing with various problems in the wetland, so its abundance has been reduced in the wetland in the recent years. The study aimed to optimize decision tree model with an optimizer (greedy stepwise) to predict the species abundance in 10 different sampling sites over one-year study period (2017–2018). The model output was the species abundance categorized into 4 classes (poor: 5–20; fair: 21–50; good: 51–100; very good:101–255 individuals) and measured with abiotic variables. The optimizer method improved the model performance leading to easy interpretation of the model. According to the model’s prediction, high abundance of species in the wetland is associated with high concentration of specific conductivity, dissolved oxygen and total dissolved solids. In contrast, increased concentration of chloride, total suspended solids, nitrate and precipitation might decrease the abundance of zooplankton. Chi-square test showed a significant difference between the species abundance and spatio-temporal patterns in the wetland (x² = 160.2, p = 0.001) so that warm seasons (spring and summer) had more contribution to the zooplankton sampling than cold seasons (autumn and winter).

位于伊朗西部的Meighan高盐湿地是孤雌生殖卤虫的重要生境。这种原生浮游动物的生境在湿地中面临各种问题，因此近年来其在湿地中的丰度有所降低。该研究旨在使用优化程序（逐步进行贪婪优化）优化决策树模型，以预测在一年的研究期内（2017-2018年）10个不同采样点的物种丰富度。模型输出是将物种丰度分为4类（贫困：5–20；一般：21–50；良好：51–100；非常好：101–255个个体），并使用非生物变量进行测量。优化器方法改善了模型性能，从而易于解释模型。根据模型的预测，湿地中物种的丰富与高浓度的比电导率，溶解氧和总溶解固体有关。相反，氯化物，总悬浮固体，硝酸盐和降水的浓度增加可能会降低浮游动物的丰度。卡方检验表明，湿地物种丰富度和时空格局之间存在显着差异（x ²  = 160.2，p  = 0.001），因此温暖季节（春季和夏季）对浮游动物采样的贡献要大于寒冷季节（秋季和冬季）。