Population increases and unsustainable development in recent years have affected the health of freshwater ecosystems and their performance. In order to preserve and improve the biodiversity and ecological health of these ecosystems, it is necessary to have a documented program for monitoring aquatic ecosystems. The main goal of this research was to develop a multi-metric indices (MMIs) based on macroinvertebrate communities in order to eva‎luate the water quality of the streams of the Karun River basin. Moreover, we aimed at unravelling i) how seasonal changes affect the structure of benthic macroinvertebrate communities and, as a consequence, the performance of the developed MMIs, ii) how incorporating functional trait-based metrics affects the performance of MMIs, and iii) how the performance of MMIs using a metric-based approach compares with MMIs developed based on an index-based approach. In order to achieve these goals, 53 stations were selected in the streams of the Karun. Sampling was done in four seasons: autumn of 2017 and winter, spring and summer of 2018. In each station, the physical characteristics of the habitat and physical and chemical variables were measured. In addition, macroinvertebrate communities were sampled and identified (mainly at the genus level). Principal components analysis (based on physical and chemical variables of water and physical characteristics of the habitat) was used to determine sites with minimum pollution. The first principal component (PC1) was selected as the gradient of human disturbance in each season. In the second chapter of this study, the effectiveness of three common methods to include the effect of seasonal changes in the development of multi-metric indices including 1) developing a multi-metric index for each season, 2) aggregating the data collected in different seasons and developing a multi-metric index, and 3) using the signal/noise ratio to select metrics with low seasonal changes compared to spatial changes; were eva‎luated. The results indicated the seasonal changes in the Karun affect the composition of the final metrics of MMIs, as well as the performance of the MMIs. Developing a MMI for each season was the best method to include the effects of seasonal changes in the development of MMIs. The best seasons for the development of multi-metric index in the Karun were the summer and autumn. This might be related to the stability of the main natural environment factors affecting the structure of macroinvertebrate communities (including temperature and current velocity) during these seasons. In the third chapter, the simultaneous use of functional and taxonomic diversity indices in the development of multi-metric indices significantly increased the performance of the developed MMIs. Moreover, the adjusted MMIs had a higher efficiency compared to the non-adjusted MMIs. In the fourth chapter, the efficiency of the two main methods in the development of a multi-metric index for the Karun was eva‎luated. The results showed that index-based MMIs had a higher performance in terms of precision, bias, sensitivity and responsiveness than metric-based MMIs. In general, the obtained results indicated that the MMIs developed based on macroinvertebrate communities have the ability to effectively detect the presence of various anthropogenic stressors in the streams of the Karun and can be used as a tool for biomonitoring of this vital ecosystem.

عيسي ابراهيمي درچه

آندرياس برودر , سباستين برك

نصرالله محبوبي صوفياني , محمودرضا همامي , اميد بيرقدار كشكولي