The simplest way of measuring the home range is to construct the smallest possible convex polygon around the data but this tends to overestimate the range. The best known methods for constructing utilization distributions are the so-called bivariate Gaussian or normal distribution kernel density methods. More recently, nonparametric methods such as the Burgman and Fox’s alpha-hull and Getz and Wilmers local convex hull have been used. Software is available for using both parametric and nonparametric kernel methods.The concept of the home range can be traced back to a publication in 1943 by W. H. Burt, who constructed maps delineating the spatial extent or outside boundary of an animal’s movement during the course of its everyday activities.
Associated with the concept of a home range is the concept of a utilization distribution, which takes the form of a two dimensional probability density function that represents the probability of finding an animal in a defined area within its home range. The home range of an individual animal is typically constructed from a set of location points that have been collected over a period of time, identifying the position in space of an individual at many points in time. Such data are now collected automatically using collars placed on individuals that transmit through satellites or using mobile cellphone technology and global positioning systems technology, at regular intervals.
The best known methods for constructing utilization distributions are the so-called bivariate Gaussian or normal distribution kernel density methods. This group of methods is part of a more general group of parametric kernel methods that employ distributions other than the normal distribution as the kernel elements associated with each point in the set of location data.Recently, the kernel approach to constructing utilization distributions was extended to include a number of nonparametric methods such as the Burgman and Fox’s alpha-hull method and Getz and Wilmers local convex hull method.This latter method has now been extended from a purely fixed-point LoCoH method to fixed radius and adaptive point/radius LoCoH methods.
They had fled pogroms in Russia and antisemitism in urban America to live in a rural Jewish community, but still they faced antisemitism from their surrounding neighbors. One woman remembers, “they used to call us dirty Jew.” And another woman remembers a particularly frightening night when an antisemitic neighbor threw a barn party and the drunk and rowdy crowd terrified her parents so much that they couldn’t sleep that night. These incidents ingrained the Jews with a painful feeling of being “lesser” than other Americans. But nothing can compare to the violent night that Gentile leaders in the neighboring community took out their antisemitism and anticommunist fears through brute force against the men of Petaluma.
