# Glossary

**Accuracy ellipses** are generated round locations from bearing data by some packages (eg LOCATE II).
**Arithmetic mean** is the mean x and y coordinates for a set of locations.
**Autocorrelation analysis** estimates the degree of spatio-temporal dependence of locations.
**ASCII** is American Standard Code, used to turn bytes into text characters.

Bivariate ellipses are based on location distributions along a major and a minor axis.

Boundary strips round locations in polygons have a width of half the tracking resolution.

Byte arrays are Ranges storage format for raster maps; each byte codes for 1 raster.

Centroid distance is from a location to all the locations in a cluster.

Cluster analysis joins locations in groups based on the distances between them.

Core denotes one or more high areas of high location density in a range.

CSV files are composed of Comma Separated Values (other separators are Break/Space and Tab).

Density matrix values are estimated at intersections of an arbitrary grid for contouring.

Dispersal detection provides an objective estimate of when animals leave an area.

Dispersion (in contour analyses) the peak density value (at the range centre location) divided by the standard deviation of the density value across all the locations.

Edge denotes an outline estimated round locations as a polygon or by contouring.

Ellipses include circles.

Ellipse asymmetry is the ratio of the standard deviations along the major and minor axes.

EMF Enhanced Meta File, windows vector graphics file format.

Focal site denotes an attraction point in a range, such as a den or nest.

Grid cells are as wide as the location resolution.

Grid edges are the eastmost, westmost, northmost and southmost coordinates in sets of locations.

Gridascii files are used by ArcView for transferring raster map data.

Habitat points are x,y coordinates associated with habitat codes for different trees, etc.

Habitat shapes are formed from a clockwise set of x,y values with the same start and end point.

Harmonic mean analyses are based on the inverse reciprocal mean of distances.

hRef the reference smoothing parameter in kernel analyses ( SD / sixth root N )

Incremental analysis estimates the change in range area as successive locations are added.

Isolines of equal location density are created during contour analysis and converted to polygons.

Jacob's index has values between -1 and +1 to indicate attraction versus avoidance.

Kernel analyses are based on estimating location density as functions of distance.

Kurtosis indicates spread in the density distribution during harmonic mean & kernel contouring.

Location denotes x,y coordinates of a location, often with associated qualifying variables.

Location centring is computed during harmonic mean contouring to remove location resolution effects.

Location resolution is the smallest distance that can be recorded between adjacent locations.

Location Qualifying Variables (LQVs) are time, activity, habitat, values associated with x,y coordinates.

Nearest neighbour locations are those closest to a single site or location in a cluster.

Neighbour Linkage

Objective Cores

OREP Objective Restrictive Edge Polygons – and check for any choices or outputs that need defining

Outlier locations are those beyond the main distribution of locations.

Overlap matrices are formed as % overlaps of range A on B and B on A.

Partial area is the summed area of clusters divided by a single area encompassing all clusters.

Polygons are formed by joining edge lines round a set of locations.

Range variables are 7 values that code ID, age, sex, month, year and focal site coordinates.

Raster maps are composed of equal-size rectangles with different habitat codes.

Schoener's index increases from 0 with decreasing spatio-temporal dependence between locations (= mean squared distances between locations / mean squared distance from each location to the arithmetic activity centre).

Skew in the location density distribution is estimated during harmonic mean & kernel contouring ( the Euclidean distance between the arithmetic mean centre and the location with the peak density value, divided by the standard deviation of the density value across all the locations).

Simpson's index increases from 1 with increasing diversity between clusters.

Smoothing factor modulates the density function in kernel analyses to improve fit of contours.

Spread of a range is the grand mean of distances between all the locations.

Tracking resolution is the smallest distance that can be recorded between adjacent locations.

Utilisation plots are of range area against increase in location density until all are included.

Vector maps are composed of lines and closed shapes defined by a sequence of x,y coordinates.

Width of a range is the maximum diagonal dimension of a polygon enclosing all the locations.

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