On the impact of the development of the Upper Sukhona river catchment area ( Vologda region) on the zoobenthos of its tributaries

For the first time in Vologda region, the impact of economic activities on the structure of zoobenthos communities was considered within the catchment area on the example of tributaries of the Upper Suchona River. The study was carried out on 10 catchments of 6 rivers in 2010-2013. A total of 292 samples were collected and examined. Aquatic macro-invertebrates were identified to the lowest detected taxon. To assess water quality, biodiversity indices of the selected groups of zoobenthos, biotic indices, saprobity were calculated. The delineation was made for every catchment with Hydrology ArcGis group tools. Population density and urban, agricultural, woodland and swamp surface areas were calculated within each watershed. With the approach to Vologda city, there is a decrease in species diversity with the loss of the most sensitive taxa. The change in benthos community structure is observed: quantitative indicators of oligochaetes increase, while those of all other taxa decrease. At that, there is a decrease in the diversity indices (Shannon - Weiner index, Simpson Index, Margalef Index), biotic indices (TBI, BBI) and an increase in saprobity, Goodnight - Whitley Index, FBI. Approaching Vologda, reducing forest area and increasing share of urban and agricultural lands as well as increasing population density were noted. Positive significant correlation of population density and settlement areas with quantitative indicators of oligochaetes and chiromomids, as well as with TBI and saprobity was noted. Whereas negative significant correlation was revealed with species wealth, biodiversity index, TBI and BBI biotic indices. Forest and farm lands don`t show the significant correlation with zoobenthos parameters because of high proportion of urbanization. The highest correlation values were noted for Goodnight-Whitley index and TBI. These indices are the most informative. Received regularities can be extrapolated to the relatively large territory. It is desirable to apply the used GIS methods at the preparation stage for biomonitoring studies.