The ‘StatAnalysis.zip’ contains the data and model files. We used it for the four analyses below.

First, we estimated population densities, the mean body mass and camera-trap capture rates of five main bushmeat targets in a rainforest of southeast Cameroon: Peters’s duikers (Cephalophus callipygus), bay duikers (C. dorsalis), blue duikers (Philantomba monticola), brush-tailed porcupines (Atherurus africanus) and Emin’s pouched rats (Cricetomys emini). Second, on the basis of the density and body mass estimates, we estimated bushmeat biomass—the total biomass of the five bushmeat species—and its spatial variation. Third, we calculated six bushmeat indicators based on the capture rate estimates. Lastly, we examined the correlation between bushmeat biomass and the indicators.

The ZIP file consists of 16 R script files, three CSV files (in the ‘data’ subfolder) and 135 stan files (in the ‘stan’ subfolders). It also has two empty folders, ‘figure’ and ‘res’, where the figures and R objects of model results will be stored following the analyses. Please see the document ‘README.txt’ before performing the analysis. This text file gives the ZIP file structure and brief descriptions of the files.

The two data files—‘DetectionData.csv’ and ‘StayTimeData.csv’—were created based on a camera trap study conducted from September 2018 to February 2019. The ‘BodyMassData.csv’ contains the body mass data of the hunted animals in the study area.

We estimated population density and its spatial variation using the REST model (Nakashima et al. 2018, 2020). The REST model was implemented in a Bayesian framework using Stan. We also used Stan to estimate the mean body mass and camera-trap capture rates from the ‘BodyMassData.csv’ and the 'DetectionData.csv', respectively. Finally, bushmeat biomass and bushmeat indicators were calculated using the MCMC samples from the WAIC-based optimal models of the density, body mass and capture rate estimation.

1. Keep the current folder structure. Don't move any files for proper analysis.

2. Please proceed with the analyses in the order of the R script file numbers.

3. In each subfolder of the ‘figure’ and ‘res’ folders, there is a ‘dummy.txt’ file. It is to preserve the folder structure. You may remove these text files after unzipping.