A general approach to assessing the anthropogenic impact on lake ecosystems is proposed and exemplified for the case of Lake Shira (Republic of Khakasia, Russia). The impact strength is estimated by applying neural network-based methods to samples of data on interdependent marking features of autochthonous and allochthonous bacteria isolated from the lake in 1997-2001. The proposed combination of analysis methods makes it possible to determine the state of an ecosystem from both small- and large-size samples of data having complex interrelations.