Effects of sampling regime on the mean and variance of home range size estimates

Abstract

Summary 1.Although the home range is a fundamental ecological concept, there is considerable debate over how it is best measured. There is a substantial literature concerning the precision and accuracy of all commonly used home range estimation methods; however, there has been considerably less work concerning how estimates vary with sampling regime, and how this affects statistical inferences. 2. We propose a new procedure, based on a variance components analysis using generalized mixed effects models to examine how estimates vary with sampling regime. 3. To demonstrate the method we analyse data from one study of 32 individually marked roe deer and another study of 21 individually marked kestrels. We subsampled these data to simulate increasingly less intense sampling regimes, and compared the performance of two kernel density estimation (KDE) methods, of the minimum convex polygon (MCP) and of the bivariate ellipse methods. 4. Variation between individuals and study areas contributed most to the total variance in home range size. Contrary to recent concerns over reliability, both KDE methods were remarkably efficient, robust and unbiased: 10 fixes per month, if collected over a standardized number of days, were sufficient for accurate estimates of home range size. However, the commonly used 95% isopleth should be avoided; we recommend using isopleths between 90 and 50%. 5. Using the same number of fixes does not guarantee unbiased home range estimates: statistical inferences differ with the number of days sampled, even if using KDE methods. 6. The MCP method was highly inefficient and results were subject to considerable and unpredictable biases. The bivariate ellipse was not the most reliable method at low sample sizes. 7. We conclude that effort should be directed at marking more individuals monitored over long periods at the expense of the sampling rate per individual. Statistical results are reliable only if the whole sampling regime is standardized. We derive practical guidelines for field studies and data analysis.

Modelling ranging behaviour of female orang-utans: a case study in Tuanan, Central Kalimantan, Indonesia

“…The MCP method geometrically defines the home range as the convex hull around a set of point locations. However, using the MCP method for home range modelling has been criticised (Nilsen et al 2008, Börger et al 2006. First and foremost it has the undesirable property that biases increase as sample sizes increase (Burgman 2003).…”

“…However, animals are unlikely to use all parts of their home range with the same intensity and thus important information on differential space use within the range is lost (Katajisto & Moilanen 2006). Despite these limitations and a range of alternatives, the MCP method is still widely used (Börger et al 2006), although few studies report primate ranging based solely on MCP estimates (but see Kaplin 2001, Savini et al 2008. Most include other home range estimators besides MCP (e.g.…”

“…1). The various constraints of the MCP method have led researchers to advise against its use as a home range size estimator (Börger et al 2006, Nilsen et al 2008). …”

“…Over time the focus has shifted from studying temporal fluctuations in abundance to more spatially explicit approaches of individual movements (Patterson et al 2008). A central question when analysing animal movements is how the observed patterns of animal distribution are determined by the interactions between individuals and their environment (Börger 2006). A useful approach is to understand the dynamics of animal movements in relation to social and ecological factors (Benson et al 2006, Robbins & McNeilage 2003, Harvey et al 2008.…”

“…Although the home range is a common concept in analysing animal space use, there is considerable debate in the scientific literature on how it should be measured (Börger 2006). Several methods to estimate home range size exist and their number is still increasing (Horne & Garton 2006a).…”