  The aim of this study was to evaluate the performance of a classical method
of fractal analysis, Detrended Fluctuation Analysis (DFA), in the analysis of
the dynamics of animal behavior time series. In order to correctly use DFA to
assess the presence of long-range correlation, previous authors using
statistical model systems have stated that different aspects should be taken
into account such as: 1) the establishment by hypothesis testing of the absence
of short term correlation, 2) an accurate estimation of a straight line in the
log-log plot of the fluctuation function, 3) the elimination of artificial
crossovers in the fluctuation function, and 4) the length of the time series.
Taking into consideration these factors, herein we evaluated the presence of
long-range correlation in the temporal pattern of locomotor activity of
Japanese quail ({\sl Coturnix coturnix}) and mosquito larva ({\sl Culex
quinquefasciatus}). In our study, modeling the data with the general ARFIMA
model, we rejected the hypothesis of short range correlations (d=0) in all
cases. We also observed that DFA was able to distinguish between the artificial
crossover observed in the temporal pattern of locomotion of Japanese quail, and
the crossovers in the correlation behavior observed in mosquito larvae
locomotion. Although the test duration can slightly influence the parameter
estimation, no qualitative differences were observed between different test
durations.
