Eliminating autocorrelation reduces biological relevance of home range estimates

摘要: 1. Destructive subsampling or restrictive sampling are often standard procedures to obtain independence of spatial observations in home range analyses. We examined whether estimators based upon kernel densities require serial observations, by using a Monte Carlo simulation, antler flies and snapping turtles as models. 2. Home size, time partitioning total straight line distances travelled were tested determine if improved performance estimation parameters. 3. The accuracy precision estimates from the simulated data set at shorter intervals despite increase autocorrelation among observations. 4. Subsampling did not reduce locational flies, distance better represented autocorrelated observations. 5. found that do when estimating range, we recommend researchers maximize number constant their estimates.