TITLE:
Sample Size Affect Ethnobotanical Index Values: Bootstrap as a Remedial Approach
AUTHORS:
Gbemavo Dossou Sèblodo Judes Charlemagne, Cachon Fresnel Boris, Lokonon Bruno
KEYWORDS:
Quantitative Ethnobotany, Re-Sampling, Inference
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.12 No.11,
November
7,
2022
ABSTRACT: Ethnobotanical indices are widely used to quantify
cultural importance of plants in social studies. This study aims to show users of ethnobotanical indices the effect of
sample variation and what methodological approach can be used to circumvent the
problems related to sample variation. The methods used are to write an algorithm and used
to simulate different sample sizes from which four ethnobotanic indices
selected for the present study were estimated. Results showed the instability of the ethnobotanical indices under
variations in the size of informants. It proposes bootstrapping as a
statistical aid tool to remove the sample
size effect in quantitative ethnobotany. For the indices used in the present
study 1000 re-samplings eliminated the effect of sample size on the value of
the indices. Researchers will have to take this new approach into account in
order to calculate more precise ethnobotanical indices in order to better
appreciate the cultural importance of plants.