The Importance of Representative Sampling for Home Range Estimation in Field Primatology

Abstract

Understanding the amount of space required by animals to fulfill their biological needs is essential for comprehending their behavior, their ecological role within their community, and for effective conservation planning and resource management. Habituated primates are often studied using handheld GPS data, which provides detailed movement information that can link patterns of ranging and space-use to the behavioral decisions that generate these patterns. However, this data may not accurately represent an animal's total movements, posing challenges when the desired inference is at the home range scale. To address this, we used a rich 13-year dataset from 11 groups of white-faced capuchins (Cebus imitator) to examine the impact of sampling elements, such as sample size and regularity, on home range estimation accuracy. We found that accurate home range estimation is feasible with relatively small sample sizes and irregular sampling, as long as the data are collected over extended time periods. Concentrated sampling can lead to bias and overconfidence due to uncaptured variations in space-use and underlying movement behaviors. Therefore, it is crucial to develop sampling protocols that provide adequate temporal coverage and consider the movement behaviors of the study species.

Consistency in Verreaux's sifaka home range and core area size despite seasonal variation in resource availability as assessed by Enhanced Vegetation Index (EVI)

“…Our findings suggest that sampling design has a major impact on Verreaux's sifaka home range estimates and it may account for differences reported, even for the same population (e.g., Norscia et al, 2006;Rudolph et al, 2019). For example, home range estimates that rely on a minimum number of locations and ignore the span of time over which these locations were collected may be inadequate to accurately estimate home range area, as recently found for capuchins (Jacobson et al, 2023). Asymptote analyses using accumulation curves suggest that location data collected over a small temporal portion of a season is not likely to be representative of a seasonal or yearly home range; these snapshots may under-represent the total amount of space used by sifaka groups.…”

“…We found that the addition of temporal requirements (data collected over 4 months with at least 1 month from each season) to a minimum number of locations (n = 175) was essential for reaching asymptote yearly home range values. Jacobson et al (2023) also caution against concentrated sampling to avoid bias in home range estimation., Additionally, sample size of seasons/years accounted for large differences in the precision of group home range estimates; when data were collected over just 1-2 seasons (or years), group home range estimates had much larger confidence intervals.…”