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

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1007/s10764-023-00398-z. This is version 1 of this Preprint.

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Authors

Odd Thomas Jacobson , Brendan Barrett, Margaret Crofoot, Susan Perry, Kosmas Hench, Genevieve Finerty

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.

DOI

https://doi.org/10.32942/X2XG63

Subjects

Behavior and Ethology, Other Ecology and Evolutionary Biology

Keywords

capuchin, movement, spatial ecology, autocorrelated kernel density, handheld GPS

Dates

Published: 2023-05-04 09:24

License

No Creative Commons license

Additional Metadata

Language:
English

Conflict of interest statement:
The authors declare no financial or non-financial conflicts of interest.

Data and Code Availability Statement:
The datasets generated and/or analyzed during the current study are available in a public anonymized github repository found here: https://anonymous.4open.science/r/CH1_Sampling-CEB3/README.md. We will deposit them in Zenodo or Movebank in a DOIed repository upon acceptance.