  By using low-dimensional chaos maps, the power law relationship established
between the sample mean and variance called Taylor's Law (TL) is studied. In
particular, we aim to clarify the relationship between TL from the spatial
ensemble (STL) and the temporal ensemble (TTL). Since the spatial ensemble
corresponds to independent sampling from a stationary distribution, we confirm
that STL is explained by the skewness of the distribution. The difference
between TTL and STL is shown to be originated in the temporal correlation of a
dynamics. In case of logistic and tent maps, the quadratic relationship in the
mean and variance, called Bartlett's law, is found analytically. On the other
hand, TTL in the Hassell model can be well explained by the chunk structure of
the trajectory, whereas the TTL of the Ricker model have a different mechanism
originated from the specific form of the map.
