batch_compute_graph_soundscape.R

## SOUNDSCAPE CHARACTERIZATION
# References
# Campos‐Cerqueira, M., et al., 2020. How does FSC forest certification affect the acoustically active fauna in Madre de Dios, Peru? Remote Sensing in Ecology and Conservation 6, 274–285. https://doi.org/10.1002/rse2.120
# Furumo, P.R., Aide, T.M., 2019. Using soundscapes to assess biodiversity in Neotropical oil palm landscapes. Landscape Ecology 34, 911–923.
# Campos-Cerqueira, M., Aide, T.M., 2017. Changes in the acoustic structure and composition along a tropical elevational gradient. JEA 1, 1–1. https://doi.org/10.22261/JEA.PNCO7I
source('graph_soundscape_fcns.R')
library(viridis)
library(vegan)

## SET VARIABLES
path_dataset = '/Volumes/lacie_exfat/BST_ejemplo_PPII/audio/' # location of audio dataset
sites = c("C1BO","C2BO","C3GU","C4GU","C5GU","C6CE","V1TO","V2TO","V3HU","V4HU","V5DA","V6DA")


## 1. BATCH READ AUDIO METADATA
path_save_metadata = '/Volumes/lacie_exfat/BST_ejemplo_PPII/metadata/audio_metadata.csv' # Filename of csv that will store the metadata

flist = list.files(path_dataset, recursive = T, pattern = '.WAV', ignore.case = T)
df = metadata_audio(flist, path_dataset, verbose = T, rec_model = 'SM')
## post-process to include factors or sites
aux = strsplit(df$path_audio, split = '/')
aux_df = as.data.frame(do.call(rbind, aux))
head(aux_df)
# set treatment, site and short file name
df['treatment'] = aux_df$V1
df['site'] = aux_df$V2
df['fname_audio'] = aux_df$V3
# Check dataframe manually
head(df)
tail(df)
table(df$site)  # number of recordings per site
# plot sampling
plot_sampling(df, y_axis_factor = df$site, color_factor = df$site, shape_factor = df$treatment, plot_title = 'Example')
# save dataframe to csv
write.table(df, fpath_save, sep=',', col.names = TRUE, row.names = FALSE)


## 2. COMPUTE GRAPH SOUNDSCAPE FOR EACH RECORDING
path_metadata = '/Volumes/lacie_exfat/BST_ejemplo_PPII/metadata/audio_metadata.csv' 
path_save = './dataframes_gs/'

df = read.csv(path_metadata) 
for(site in sites){
    df_site = df[df$site==site,]
    gs = graphical_soundscape(df_site, spec_wl=256, fpeaks_th=0.003, fpeaks_f=0, verbose=T) # inicial 0.002
    fname_save = paste(path_save, site, '.csv', sep='')
    write.csv(gs, file=fname_save, row.names = F)
    }


## 3. PLOT
path_gs = './dataframes_gs/'
path_save_figure = './figures/'

for(site in sites){
    gs = read.csv(paste(path_gs,site,'.csv',sep=''))
    png(paste(path_save_figure,site,'.png',sep=''))
    plot_graphical_soundscape(gs)
    dev.off()
    }