شناسایی جوامع ماکروبنتیک و وضعیت شاخص‌های BMWP و HFBI برای ارزیابی کیفی رودخانه مارون

Introduction
About 99% of the Earth's water reserves are located in oceans and glaciers that are saline or inaccessible. But rivers, despite having one of the smallest volumes of water reserves, have long been easily exploited by humans. Even the first foundations of the formation of human civilization can be found around rivers (Pahlavani et al., 2015). Therefore, paying attention to the quality of rivers is of special importance. Iran is located in the dry belt of the earth and considering that the water entering from the borders to our country is not significant, so it can be said that all Iranian water is supplied by rainfall and 70% of this rainfall is out of reach through evaporation, which is three times It is a global statistic, which doubles the importance of paying attention to the quality of fresh water in our country. River water pollution can in fact be considered as an indicator of environmental pollution due to human activities, because rivers are the only water resources that travel a long way through cities, villages and industrial and agricultural areas (Shokri Saravi et al., 2014). In this study, we tried to investigate the water quality of Maroon River using benthic invertebrates. The most important source of water for industry, agriculture, drinking and health and the creator of Shadegan wetland in the south and southeast of Khuzestan province is the Maroon-Allah-Jarahi river. (Hosseini Zare and Barati Gandomkar, 2006).


Methodology
This study was conducted in 2019 during two seasons of summer and autumn in 6 designated stations in Maroon River. This catchment is located in the southern and southwestern slopes of the Middle Zagros between the eastern longitude of 50 degrees and 5 minutes and 51 degrees and 11 minutes and the northern latitude of 30 degrees and 39 minutes to 31 degrees and 21 minutes (Shafiee Motlagh et al., 2016). The location of the studied stations is specified in Table 1. In the BMWP system, the resistance of each family of benthos to contamination is the basis for scoring. So that the families that are less resistant to infection have the highest score and the most resistant family member, which is dominant in the region, has the lowest score. Finally, the scores of the households are added together in the sample to obtain the BMWP score of that station (Table 2) (Karami et al., 2017). The FBI Index was introduced in 1988 by Hilsenhoff to determine the tolerance of macrobenthos living in freshwater. In this index, the tolerance of macrobenthos organisms varies between 0 and 10, which increases with decreasing water quality. (Pahlavani et al., 2015). Guidelines for determining water quality based on this index are given in Table 3.
In this study, Spss and Excel software were used for statistical calculations, data analysis and drawing tables and graphs. Normal data distribution was performed based on Kolmogorov-Smirnov test. Data analysis was performed by one-way analysis of variance. Pearson correlation coefficient with significant levels of 0.05 and 0.01 was used to show the correlation between macrobenthos groups and biomarkers. Map Source and AutoCAD software were used to map the study area and determine the location of study stations. In the study conducted in Maroon River, 4 genera, 8 families and 9 genera of macrobenthos were identified. Among these categories, Oligochaeta with 54.16% and Hirudinea with 2.11% had the highest and lowest frequency in the whole study period, respectively. Among the families identified in this sampling, Insecta and Gastropoda categories each included 3 families and Oligochaeta and Hirudinea categories each included 1 family. The frequency of macrobenthos was recorded at 3100 per square meter in autumn and 2452 per square meter in summer. During two sampling periods, a total of 2776 units per square meter of macrobenthos were collected. In total, the highest frequency of macrobenthos in the two study chapters was related to station 4 (water channel) with 2922 units per square meter and the lowest frequency of macrobenthos was related to Fajr town station with 98 units per square meter. (Table 5) and (Figure 1). Among the groups identified in autumn, summer and in the whole study period, on average, the highest frequency was related to the category of low-larvae and the lowest frequency in autumn was related to the category of insects and in summer and the whole study period was related to the category of leeches. (Figures 2, 3 and 4). In the fall, 8 species from 7 macrobenthic families were identified and counted. In this season, the highest frequency of macrobenthos belongs to the family Tubificidae and the lowest frequency belongs to the family Hydropsychidae and the family Tabanidae. In the insect category, both families identified in this study had equal frequencies. In the lower abdomen category, the highest frequency belongs to the family Physidae Physella acuta species and the lowest abundance belonged to the family Bithyniidae.
In summer, 6 species from 5 macrobenthic families were identified and counted. In this season, the highest frequency of macrobenthos belongs to the family Tubificidae and the lowest frequency belongs to the family Glossiphoniidae of Placobdella sp. In the insect category, no individuals from the families Hydropsychidae and Tabanidae were observed compared to winter. In the lower abdomen category, the highest frequency was related to the family Physidae of the species Physella acuta. No members of the Bithyniidae family were observed this season. (Table 4). According to the results of Kolmogro-Smirnov test and the value (p = 0.486), the values of bi-wd index are normal and using LSD test between the values of w-w index in summer in stations 3 and 5 with other stations and in autumn in two stations. Significant differences were observed between 1 and 3 (P <0.05). According to the results of t-test, there is no significant difference between the values of bio-indices in summer and autumn (P> 0.05). The highest rate of bile duct index was recorded with a mean (5.06 81 0.81) in autumn and the lowest with a mean (4.33 24 1.24) was recorded in summer. Based on the bio-development index, the water quality of the area in both summer and autumn was recorded in a very poor quality category (Table 6) (Figure 5). According to the results of Kolmogro-Smirno test and the value of p (0.001), the values of Hilsenhoff index were abnormal and using Kruskal-Wallis test, a significant difference was observed between the values of Hilsenhof index in summer study stations (P <0.05). No significant difference was observed in autumn (P> 0.05) (Table 5). According to the results of Mann-Whitney test, there is no significant difference between the values of Hilsenhoff index in summer and autumn (P> 0.05). (7.98 06 0.064) was recorded in summer and its lowest level with average (7.70 18 0.18) was recorded in autumn. Very poorly recorded, and in the fall, the water quality of the study stations was in very poor quality (Table 7) (Figure 6).


Conclusion
The results of the present study showed that during 2 sampling periods in the study area, a total of 10 species from 8 families and 4 macrobenthic categories were identified and counted. The highest frequency of macrobenthos was recorded in autumn with 3100 units per square meter and the lowest frequency in summer with 2452 units per square meter. In winter, more favorable environmental conditions such as lower temperatures and water turbulence and as a result of increased dissolved oxygen as well as high self-purification power of the river, have created favorable conditions to increase the diversity and abundance of benthos. In summer, with increasing temperature, the amount of dissolved oxygen decreases and because oxygen is one of the vital needs of animals for proper nutrition and metabolism, it has a direct and indirect effect on the frequency of all macrobenthos groups. Based on the results of calculating the unpredictability index in the study area, the water quality of the area in both summer and autumn was recorded in a very poor quality category. According to the findings of the BII index, in the summer, Cham Nezami, Ab-e-Kharvar and Behbahan water treatment plants were classified in the critical damage quality category, and Chahar Asyab and Maroon dam stations were classified in the high damage category. Also in the fall, Cham Nezami stations, four mills and water canals were in the critical damage category, and the stations of Maroon Dam, Behbahan Refinery and Fajr town were in the severe damage category. In calculating the BMW WP index, the most resilient families get the lowest score. As mentioned earlier, the scoring process is such that the most vulnerable families are given a score of 10, and the lower the sensitivity of the family, the lower the score of that family until the most resilient family is given a score of 1.