Development of a new biomonitoring method to detect the abnormal activity of Daphnia magna using automated Grid Counter device

The aim of the present study was to develop a biological early warning system (BEWS), equipped with six monitoring channels to individually observe the activity of Daphnia magna, using a digital ‘Grid Counter’, which would trigger an alarm within an appropriate time, and examine the functional performance of the newly developed BEWS for detecting unusual water quality. In order to detect the changes in the activity of D. magna, six relative activity parameter values (Za) were computed from the 6 individual monitoring channels; with the activity data for D. magna calculated every 5 min. The Student's t-test was used to verify the difference between the mean value of the system in a steady state, as a control, and the exposure values during a sudden pollution event. The test results illustrate that the threshold value for the alarm can be at p = 0.0093 for 3 consecutive detections. The time period, defined as the average time taken from the detection of hyper to retarded activity of the organism, for Cu concentrations of 50, 100, 200 and 400 ppb were 7.17 ± 1.75, 3.94 ± 2.02, 1.85 ± 0.49 and 1.00 ± 0.18 h, respectively. Based on the results of this study, it is proposed that p values from the t-test, with Za, are more accurate, stable and predictable parameters for the detection of chemical exposures than the other values, such as the swimming speed and trajectory, etc. Consequently, it would be possible to reduce the number of false alarms and achieve confidence for a system, with the ability of highly accurate detection, such as with the six-channel monitoring system developed in this study.