ارزیابی کیفی سرشاخه‌های اصلی رودخانه تجن با استفاده از بزرگ بی‌مهرگان کفزی

نوع مقاله : مقاله پژوهشی

نویسندگان

گروه شیلات، دانشکده علوم دامی و شیلات، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران

10.22034/AEJ.2021.281119.2500

چکیده

به منظور بررسی شاخص‌های جمعیتی بزرگ بی‌مهرگان کفزی و ارزیابی کیفیت آب، نمونه‌برداری از بزرگ بی‌مهرگان کفزی با استفاده از نمونه‌بردار سوربر سمپلر (30/5×30/5 سانتی‌متر و چشمه تور 360 میکرون) به صورت ماهانه از تیر ماه 1392 تا خرداد ماه 1393 و با سه تکرار در سرشاخه‌های اصلی رودخانه تجن انجام شد. بدین منظور به ترتیب 6 ایستگاه در مناطق شیرین‌رود (ایستگاه 1)، کرچا (ایستگاه 2)، سرخ ولیک (ایستگاه 3)، گلورد (ایستگاه 4)، زارم‌رود (ایستگاه 5) و کانال اصلی رودخانه تجن در منطقه دروپی (ایستگاه 6) انتحاب شدند. طی مدت نمونه‌برداری از ایستگاه‌های مختلف به طور کلی 39420 بزرگ بی‌مهره کفزی جداسازی، شناسایی و شمارش گردید که متعلق به 4 شاخه، 4 رده، 13 راسته و 43 خانواده و 46 جنس بودند. نتایج پارامترهای فیزیکوشیمیایی آب نشان داد کلیه پارامترها به غیر از pH تفاوت معنی‌داری را در ایستگاه‌های مختلف داشتند (0/05>P). نتایج تمامی شاخص‌های جمعیتی (شاخص‌های شانن- وینر، سیمپسون، مارگالف، غنای EPT، نسبت EPT/CHIR و شاخص یکنواختی پیلو) نشان داد، ایستگاه 1 بالاترین و ایستگاه 4 پایین‌ترین میزان تنوع و غنای گونه‌ای را در بین سایر ایستگاه‌ها داشتند. شاخص زیستی هیلسنهوف برای ایستگاه 1 کم ترین (3/16) و برای ایستگاه 4 بیش ترین (5/47) بود و برای شاخص ASPT ایستگاه 1 بیش ترین (6/36) و برای ایستگاه 4 کم ترین مقدار (3/81) را بین ایستگاه‌ها نشان داد. ایستگاه 1 بر اساس شاخص زیستی ASPT در دسته تمیز و ایستگاه‌های 3، 5 و 6 در دسته با آلودگی متوسط و ایستگاه‌های 2 و 4 در دسته با آلودگی شدید طبقه بندی شدند. نتایج این تحقیق نشان داد که جنس سنگ بستر، برداشت بیش از حد آب برای مصارف کشاورزی، ورود پساب کشاورزی، دامپروری و آبزی‌پروری به رودخانه مهم ترین عوامل تاثیرگذار در وضعیت کیفی آب هستند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Water quality assessment in the main tributaries of the Tajan River using large benthic invertebrates

نویسندگان [English]

  • Seyedeh Mahdis rekabi
  • Hossein Rahmani
  • Khosrow Janikhalili
Department of Fisheries, Faculty of Animal Sciences and Fisheries, Sari Agricultural Sciences and Natural Resources, Sari, Iran
چکیده [English]

To investigate the community indices of benthic macroinvertebrates and water quality assessment, sampling was carried out using surber sampler (30.5×30.5 cm with 360μ mesh size) monthly with 3 replications in the Tajan River and its main branches during July 2013 to June 2014. 6 stations were selected at Shirinrood, Korcha, Sorkhvalick, Golourd, Zaremrood (Alavicola) region and the main canal of the Tajan River (Daroupay) respectively. During this period, 39420 individuals of benthic macroinvertebrates were collected, identified and enumerated, which were blonged to 4 phyla, 4 classes, 13 orders, 43 families and 46 genera. Assessment of water physicochemical parameters among stations showed that all parameters, exept pH, had statistically significant differences among stations (p<0.05). Results of benthic macroinvertebrates community indices (Shanon-wiener diversity, Simpson diversity, Margalef richness, EPT richness, EPT/CHIR ratio and Pielou eveness index) showed stations 1 and 4 had the highest and the lowest diversity and richness indices, respectively. The Minimum (3.16) and the maximum values of Hilsenhoff biotc index (5.47) as well as the highest (6.36) and the lowest values of ASPT index (3.81) were calcuted in stations 1and 4 respectively. According to ASPT Biotic Index staion 1 (Shirinroud Branch) was classified in clean class, stations 3, 5 and 6 (Chardangeh, Zaremroud and main channel of Tajan River respectively) were classified in moderate pollution class and staions 2 and 4 (Korcha and Golvard Regions respectively) were classifieds in exterem pollution calss. The results showed that the most important factors influencing the quality of the Tajan River are bed material, uncontrolled water abstraction, the entry of agricultural, husbandry and aquaculture effluents into the river.

کلیدواژه‌ها [English]

  • Macroinvertebrates
  • Community indices
  • Hilsenhoff index
  • ASPT index
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