Response behaviors of indicator species have been used for monitoring environmental disturbances. Markov processes were applied to elucidation of behavioral changes of animals. Movement of Daphnia magna in two dimensions was continuously observed before and after the treatments of an insecticide, diazinon, at low concentration. The Self-Organizing Map (SOM) was initially used to train complex ment data to classify different ment states. Subsequently, a hidden Markov model (HMM) was applied to sequencing the ment states identified by the SOM. Transition probability matrix (TPM) and emission probability matrix (EPM) were efficiently estimated by HMM. Markov processes were separately observed before and after the treatments, and the changes in the response behaviors of indicator organisms were demonstrated in stressful conditions