Table 1.

Common challenges and approaches.

challenges	approaches
data length and sampling interval
	simulations
	a priori information
	movement scale
	optimization routines
discretization	binning optimization
	Kraskov method
equivalency
	avoid data aggregation
stationarity
	standard time-series approaches
	preference for relative over absolute quantities
	sub-setting or optimal partitioning
	time-varying metrics
reliability
	comparative approach
	null models
	analytical expressions