Typha latifolia (broadleaf cattail) as bioindicator of different types of pollution in aquatic ecosystems-application of self-organizing feature map (neural network).

Abstract

The contents of Cd, Cu, Fe, Mn, Ni, Pb, and Zn in leaves of Typha latifolia (broadleaf cattail), water and bottom sediment from 72 study sites designated in different regions of Poland were determined using atomic absorption spectrometry. The aim of the study was to evaluate potential use of T. latifolia in biomonitoring of trace metal pollution. The self-organizing feature map (SOFM) identifying groups of sampling sites with similar concentrations of metals in cattail leaves was able to classify study sites according to similar use and potential sources of pollution. Maps prepared for water and bottom sediment showed corresponding groups of sampling sites which suggested similarity of samples features. High concentrations of Fe, Cd, Cu, and Ni were characteristic for industrial areas. Elevated Pb concentrations were noted in regions with intensive vehicletraffic, while high Mn and Zn contents were reported in leaves from the agricultural area. Manganese content in leaves of T. latifolia was high irrespectively of the concentrations in bottom sediments and water so cattail can be considered the leaf accumulator of Mn. Once trained, SOFMs can be applied in ecological investigations and could form a future basis for recognizing the type of pollution in aquatic environments by analyzing the concentrations of elements in T. latifolia.