Movement Patterning of Daphnia magna Treated with Copper Based on Self-Organizing Map

A heavy metal, copper, was exposed to indicator species, Daphnia magna in fresh water. Response behaviors were accordingly monitored by using models for pattern recognition. With computer interfacing techniques movement of indicator species was continuously observed in response to Cu2+ at low concen...

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Bibliographic Details
Published in:Procedia environmental sciences 2012, Vol.13, p.994-1002
Main Authors: Liu, Y.D., Wu, F.C., Ji, C.W., Chon, T.S.
Format: Article
Language:English
Subjects:
Artificial neural network
Behavioral monitoring
Motion segmentation
Movement patterning
Pattern recognition
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Summary:A heavy metal, copper, was exposed to indicator species, Daphnia magna in fresh water. Response behaviors were accordingly monitored by using models for pattern recognition. With computer interfacing techniques movement of indicator species was continuously observed in response to Cu2+ at low concentrations before (24hours) and after (24hours) the treatments. The movement tracks in 2-dimension were segmented into a short unit (30s). The parameters (e.g., speed, stop number and meander) in the movement data were trained with Self-Organizing Map (SOM) to classify behavioral patterns under the stressful condition of chemical treatments. The patterns in the designated time unit accordingly revealed the structural properties of movement data under the chemical stress. This study further suggested that models of pattern recognition such as SOM could be a useful tool in analyzing complex behavioral patterns of indicator species and in monitoring heavy metal exposure in environment in situ.
ISSN:1878-0296
1878-0296
DOI:10.1016/j.proenv.2012.01.092