DOI: 10.5061/dryad.p2ngf1vzw
title: Extending species-area relationships into the realm of ecoacoustics: The soundscape-area relationship

description: The rise in species richness with area is one of the few ironclad
 ecological relationships. Yet, little is known about the spatial scaling
 of alternative dimensions of diversity. Here, we provide empirical
 evidence for a relationship between the richness of acoustic traits
 emanating from a landscape, or soundscape richness, and island area, which
 we term the SoundScape-Area Relationship (SSAR). We show a positive
 relationship between the gamma soundscape richness and island area. This
 relationship breaks down at the smallest spatial scales, indicating a
 small-island effect. Moreover, we demonstrate a positive spatial scaling
 of the plot-scale alpha soundscape richness, but not the beta soundscape
 turnover, suggesting disproportionate effects combined with acoustic niche
 partitioning as an underlying mechanism. We conclude that the general
 scaling of biodiversity can be extended into the realm of ecoacoustics,
 implying soundscape metrics are sensitive to fundamental ecological
 patterns and useful in disentangling their complex mechanistic drivers.
description: <strong>Raw acoustic
 data:<br><br></strong>Acoustic data were collected at
 the Balbina Hydroelectric Reservoir in Brazilian Amazonia. We used a
 standardized spatial sampling design, scaling the number of plots per
 island with island size. Long-duration acoustic surveys were conducted at
 Balbina between July-December 2015, sampling 74 forest islands (Bueno et al. 2020). The number of sampling plots per island ranged from 1-7 and increased with island size. At each plot, a passive acoustic sensor was deployed on a tree trunk at 1.5 m height with the microphone pointing downward. Each sensor consisted of an LG smartphone in a waterproof case linked to an omnidirectional microphone, set to record 1 in every 5 min at a sampling rate of 44.1 kHz for 4-10 days using the ARBIMON Touch application ( arbimon.rfcx.org). Due to poor recording quality, and to retain proportional sampling, some sites were excluded from the study, retaining 69 sampling plots (1-4 plots per island) on 49 islands (0.45 - 668.03 ha).  Due to the size of the raw sound file dataset, recordings could not be uploaded onto Dryad. The recordings are stored on an external repository specialized in large ecoacoustic datasets and can be accessed here: https://arbimon.org/p/balbina/insights.  <strong>Soundscape richness data:</strong> To quantify the diversity of acoustic traits emanating from the landscape, we followed the analytical pipeline outlined in Luypaert et al. (2022) to calculate the <em>soundscape richness</em> index. This acoustic index was previously shown to correlate positively with soniferous species richness at Balbina (Luypaert et al. 2022). To capture ecological patterns without identifying species, the pipeline quantifies the richness of Operational Sound Units (OSUs), a unit of measurement that groups sounds by their shared spectro-temporal coordinates in the 24-hour acoustic space in which species produce sound.  To ensure consistency in temporal sampling efforts, we designated a 5-day period for sampling across all study plots. Using a sampling rate of 44,100 Hz and a window length of 256 frames, we calculated the Acoustic Cover (CVR) spectral index for each 1-minute sound file at each plot. To do this, we used the 'ss_index_calc' function from the 'soundscapeR' R-package, which is under development on GitHub. The CVR index consists of a series of values, each corresponding to a specific frequency bin within a 1-minute spectrogram. Each bin's CVR value represents the percentage of cells surpassing a 3-dB threshold, ranging from 0 to 1 (Fig. 1 in Luypaert et al. 2022). We merged these CVR-index files for each plot chronologically, resulting in a frequency-by-time dataframe that contains the CVR-index values. By employing the ‘<em>IsoData’</em> binarization algorithm, we converted raw CVR-index values into a binary variable. Doing so, we determined whether OSUs were detected within each 24-hour sample of the soundscape (Fig. 2 in Luypaert et al. 2022). Subsequently, an incidence matrix was constructed for each plot, providing information on the detection or non-detection of OSUs in each 24-hour soundscape sample throughout the 5-day acoustic survey. These incidence matrices serve as the foundation for all subsequent computations related to soundscape richness. The resulting incidence matrices are stored in the repository under <em>".~/Data/RData/inc_mat.rds"</em>. All code to perform soundscape richness computations can be found in RNotebook 2: <em>"2_Soundscape_metrics.Rmd".</em> <strong><em>Predictor variables - island isolation:</em></strong> As islands at Balbina may contain non-forest patches lacking an arborescent cover, we focused on soundscapes produced by forest-dwelling species. Thus, island size was calculated as the total forest area per island, omitting areas of non-forest vegetation or bare soil. We downloaded a classified image from MapBiomas (30m resolution; Souza et al. 2020) and calculated the amount of ‘<em>dense forest’ </em>per island (pixel value 3), as other pixel values contained either heavily degraded or non-forest cover types (Bueno et al. 2020). Many different definitions for island isolation exist, and the most appropriate metric likely varies between ecosystems, island type (<em>i.e.</em> oceanic vs land-bridge), taxonomic groups, and more (Itescu et al. 2020). To assess whether different metrics influence the perceived impact of isolation on the soundscape richness, we calculated three metrics: (i) distance to nearest mainland (DNM); (ii) distance to nearest island (DNI); and (iii) proportion of water (PW) within a buffer around the island perimeter. The optimal scale-of-effect for the <em>’proportion of water in surrounding matrix</em>’ isolation variable (see Jackson & Fahrig 2015) was determined by trialing 40 different buffer sizes (50-2000m at 50m intervals), choosing the spatial scale at which isolation attained the strongest relationship with soundscape richness. The required GIS files to calculate the isolation variables can be found under <em>".~/Data/QGIS_data". </em>The code to extract isolation variables and determine the scale-of-effect is found in RNotebook 1: <em>"1_Metadata_preparation.Rmd"</em> and RNotebook 5: "<em>5_Isolation_scale_of_effect.Rmd".</em> <strong>Subsequent analyses:</strong> All other required files are produced by following the RNotebook files provided in this repository in sequence from RNotebook 1 - 10.   <strong>Note for downloading the dataset:</strong> Some users may experience difficulties downloading or unzipping the data in this repository. If you are experiencing issues with the data download, be patient and only click the download button once to avoid overwhelming the Dryad download prompt. This dataset contains many thousands of files, corresponding to the individual CVR-index value files for each 1-minute file in the study, which can lead to longer download times. If you experience difficulties unzipping the downloaded data file, particularly on Mac computers, consider using the following data unpacking software: https://theunarchiver.com. If you still experience issues after following these steps, you can reach out at thomas.luypaert@nmbu.no.  
description: # Extending species-area relationships into the realm of ecoacoustics: The
 soundscape-area relationship
 [https://doi.org/10.5061/dryad.p2ngf1vzw](https://doi.org/10.5061/dryad.p2ngf1vzw) The data and code presented in this repository supports the analysis in *Luypaert et al. (2024): Extending species-area relationships to the realm of acoustics - the soundscape-area relationship.* The repository contains all required data and R scripts to calculate the soundscape richness acoustic index (alpha, beta and gamma), and assess the spatial variation of this index in relation to island size and isolation at the Balbina Hydroelectric Reservoir in Brazilian Amazonia.  **Usage note**: Download the '*Luypaert_et_al_2024_RNotebooks.zip'*  file from this repository and unzip it in the desired location. If you are only interested in inspecting the code and outputs without running it, just inspect the '.html' files in sequential order from 1 to 10. If you want to try running the code, simply start with RNotebook 1 (*1_Metadata_preparation.Rmd)* and follow the order of the listed RNotebooks (1 to 10) to create all plots and models presented in the main text and supplementary materials of Luypaert et al. (2024). All RNotebooks are self-contained and automatically locate the required data objects and scripts for analysis.  **Note on downloading the data**: Some users may experience difficulties downloading or unzipping the data in this repository. If you are experiencing issues with the data download, be patient and only click the download button once to avoid overwhelming the Dryad download prompt. This dataset contains many thousands of files, corresponding to the individual CVR-index value files for each 1-minute file in the study, which can lead to longer download times. If you experience difficulties unzipping the downloaded data file, particularly on Mac computers, consider using the following data unpacking [software](https://theunarchiver.com). If you still experience issues after following these steps, you can reach out at [thomas.luypaert@nmbu.no](thomas.luypaert@nmbu.no). ## Description of the data and file structure ### 1. File structure Below, we describe the file structure for 'Luypaert_et_al_2024_RNotebooks.zip', available for download from this repository. Filenames are listed in italic, whereas directory names are listed in bold. The nested hierarchy is represented by the order of  bullet points. Where too many files are present in a directory, the content is briefly described.  **Luypaert_et_al_2024_RNotebooks.zip** * *"1_Metadata_preparation.Rmd"* * *"1_Metadata_preparation.html"* * *"2_Soundscape_metrics.Rmd"* * *"2_Soundscape_metrics.html"* * *"3_Map.Rmd"* * *"3_Map.html"* * *"4_Small_island_effect.Rmd"* * *"4_Small_island_effect.html"* * *"5_Isolation_scale_of_effect.Rmd"* * *"5_Isolation_scale_of_effect.html"* * *"6_Data_exploration.Rmd"* * *"6_Data_exploration.html"* * *"7_Modelling_effect_of_area_and_isolation.Rmd"* * *"7_Modelling_effect_of_area_and_isolation.html"* * *"8_Decomposing_SSARs_with_rarefaction.Rmd"* * *"8_Decomposing_SSARs_with_rarefaction.html"* * *"9_Rarefaction_sensitivity_analysis.Rmd"* * *"9_Rarefaction_sensitivity_analysis.html"* * *"10_SAC_analysis.Rmd"* * *"10_SAC_analysis.html"* * **Data** * **Index_files** * 69 directories (in per plot) containing 1,440 CVR index files (*'.csv'* *format*) * **Metadata** * *"metadata_sites.csv"* * *"metadata_clean.csv"* * *"metadata_isolation.csv"* * **QGIS_data** * **Shapefiles** * *"amazonia.shp"* * *"Balbina_all_islands_without_mainland.shp"* * *"Balbina_islands_without_study_island_or_mainland.shp"* * *"Balbina_mainland_without_islands.shp"* * *"Balbina_study_island_sampling_points.shp"* * *"Balbina_study_islands.shp"* * *"islands_archipelago.shp"* * *"reservoir_balbina.shp"* * **Total_buffer_area** * 40 '.csv' files for isolation variables (PW; 50 - 2000m buffers) * **Clipped_buffer_area** * 40 '.csv' files for isolation variables without focal island (PW; 50 - 2000m buffers) * **Functions** * A selection of additional functions that are sourced in the RMarkdown documents listed above.  * **RData** * *"balbina_soundscapes.rds"* * *"sample_list.rds"* * *"inc_mat_island.rds"* * *"inc_mat.rds"* * *"unrarefied_gamma_soundrich.rds"* * *"rarefaction_cmin.rds"* * *"rarefaction_cmax.rds"* * *"rarefaction_cmin_total.rds"* * *"rarefaction_cmax_total.rds"* ### 2. File descriptions #### 2.1. Scripts To perform the analysis yourself, the only files that need  to be opened are those ending in '.Rmd', representing the RNotebooks containing the code for different steps in the analytical pipeline. Note that these have also been knitted into readable '.html' documents for easier inspection. The following scripts are included in the repository: * `1_Metadata_preparation.Rmd` Used to prepare all metadata for subquent analyses, including the area and isolation predictor variables.  * `2_Soundscape_metrics.Rmd` Used to calculate the '*soundscape richness'* acoustic index and incidence matrices used in downstream analysis. * `3_Map.Rmd` Used to create Figure 1, containing a map of the study area and sampling plots.  * `4_Small_island_effect.Rmd` Used to test for the presence of a small island effect.  * `5_Isolation_scale_of_effect.Rmd` Used to assess at which spatial scale (50-2000m) isolation measured as the proportion of water in the surrounding buffer best describes the variation in the unrarefied gamma soundscape richness.  * `6_Data_exploration.Rmd` Used to assess variables distributions and correlations, and explore the influence of island size and isolation on the unrarefied gamma soundscape richness using partial regression plots and conditioning plots.  * `7_Modelling_effect_of_area_and_isolation.Rmd` Used to model the effect of island size and isolation on the unrarefied gamma soundscape richness.  * `8_Decomposing_SSARs_with_rarefaction.Rmd` Used to calculate the rarefied gamma,  alpha, and beta soundscape metrics and assess how they're influenced by island size.  * `9_Rarefaction_sensitivity_analysis.Rmd` Used to assess the sensitivity of SSAR model parameter estimates to the width of rarefaction confidence intervals.  * `10_SAC_analysis.Rmd` Used to check for the presence of spatial autocorrelation in the data.  #### 2.2. Data overview and relationships In addition to the RNotebooks, the repository also contains a number of data objects that are called in the RNotebooks, or created by the RNotebooks. In theory, you do not need to access these files separately, as they are automatically detected and used by the scripts presented above.  * **Index_files**: This directory contains 69 subdirectories - one for each plot in the study. Each subdirectory contains 1,440 '.csv' files holding the CVR index values for each 1-minute sound file that was recorded at that location. These CVR index files are used in RNotebook 2 *'2_Soundscape_metrics.Rmd'* to calculate the unrarefied soundscape richness and OSU-by-sample incidence matrices used in downstream analyses.  * **Metadata:** * `metadata_sites.csv` A '.csv' file containing some important metadata of the sampling campaign, including the geographic coordinates of sampling plots, first day of recording per plot, number of recording days per plot, island size and island/plot names. This data object is used in RNotebook 1 *'1_Metadata_preparation.Rmd'* . * `metadata_clean.csv` A '.csv' file created in RNotebook 1 *'1_Metadata_preparation.Rmd'* . Contains metadata for the study sites used in Luypaert et al. (2024).  * `metadata_isolation.csv` A '.csv' file created in RNotebook 1 *'1_Metadata_preparation.Rmd'* . Contains metadata for the different isolation metrics used in downstream analyses for each of the 40 buffer distances around each island.  * **RData:** * `balbina_soundscapes.rds` A list of soundscape objects created in RNotebook 2 *'2_Soundscape_metrics.Rmd'.*  * `sample_list.rds` A list of soundscape objects separated by sampling day created in RNotebook 2 *'2_Soundscape_metrics.Rmd'.*  * `inc_mat_island.rds` An island-wide OSU-by-sample incidence matrix, created in RNotebook 2 *'2_Soundscape_metrics.Rmd'.* * `inc_mat.rds` A plot-scale OSU-by-sample incidence matrix, created in RNotebook 2 *'2_Soundscape_metrics.Rmd'.* * `unrarefied_gamma_soundrich.rds` A dataframe containing information on the unrarefied gamma soundscape richness, as well as associated metadata. Created in RNotebook 2 *'2_Soundscape_metrics.Rmd'.* * `rarefaction_cmin.rds` A list of rarefaction data for the gamma, alpha and beta soundscape richness for 24 study islands. A coverage-based rarefaction approach to Cmin was used. Data object created in RNotebook 8 *'8_Decomposing_SSARs_with_rarefaction.Rmd'.*  * `rarefaction_cmax.rds` A list of rarefaction data for the gamma, alpha and beta soundscape richness for 24 study islands. A coverage-based rarefaction approach to Cmax was used. Data object created in RNotebook 8 *'8_Decomposing_SSARs_with_rarefaction.Rmd'.*  * `rarefaction_cmin_total.rds` A data frame containing aggregatred rarefaction data for *'rarefaction_cmin.rds'*. Data object created in RNotebook 8 *'8_Decomposing_SSARs_with_rarefaction.Rmd'.*  * `rarefaction_cmax_total.rds` A data frame containing aggregatred rarefaction data for *'rarefaction_cmax.rds'*. Data object created in RNotebook 8 *'8_Decomposing_SSARs_with_rarefaction.Rmd'.*  * **QGIS_data** * **Shapefiles**: a directory 8 containing useful shapefiles of islands, mainland, reservoir outline, plots locations, and more. Used in RNotebook 3 *'3_Map.Rmd'* for creating Figure 1, showing a map of the study area. Also used in RNotebook 1 '*1_Metadata_preparation.Rmd'*  to calculate isolation variable metadata.  * **Total_buffer_area**: a directory containing 40 '.csv' files containing information on the proportion of land in a range of buffer sizes (40 - 2000 m at 50m increments) for each study island. This information was derived in QGIS and is processed in RNotebook 1 '*1_Metadata_preparation.Rmd'* .  * **Clipped_buffer_area**: a directory containing 40 '.csv' files containing information on the proportion of land in a range of buffer sizes (40 - 2000 m at 50m increments) for each study island. This information was derived in QGIS and is processed in RNotebook 1 '*1_Metadata_preparation.Rmd'* .  * **Functions:** This directory contains some functions that are called in the RNotebook, but do not make part of the core scripts.  ### 2.3. Detailed file descriptions ##### A. CVR-index '.csv' files ***(Data/Index\_files)*** **filename**: varied (CVR-index file '.csv' files for each island / sampling plot / sound file combination). Format = G._ISLANDNAME_DATE_TIME * **content**: The values of CVR-index values calculated for each sound file. Each '.csv' file contains 128 values (columns), or one per frequency bin (172 Hz width). The unusual file format (value by columns instead of rows) is the result of how indices are calculated and is required for downstream analysis. - **columns**: * column 1 (Index): No information - ignore. * columns 2-129: CVR-index values (proportion of cells in noise-reduced frequency bin with value &gt; 3dB) for each frequency bin (0-172 Hz, 173-344 Hz, etc...) ##### B. Metadata files *(Data/Metadata)* **filename**: metadata_sites.csv * **content**: This metadata file contains the information for all the locations at which acoustic data was collected at the Balbina Hydroelectric Reservoir. For more information on how this data was collected, see [Bueno et al. 2020](https://nsojournals.onlinelibrary.wiley.com/doi/full/10.1111/ecog.04568). - **columns**: * island_name: The name of the island on which acoustic sensors were placed. For more information, see Bueno et al. 2020 (see above). * site: The name of the sampling point at which acoustic data was collected. For more information, see Bueno et al. 2020 (see above). * latitude: The latitude of the sampling point, in decimal degrees. * longitude: The longitude of the sampling point, in decimal degrees. * area: The size of the island, in hectares. * ndays: The number of full days during which the soundscape was recorded. * first_day: The date of the first recording day of the soundscape at each sampling point (YYYY-MM-DD). * **rows**: Each row represents a sampling point at which soundscape data was collected, as described in Bueno et al. 2020 (see above). **filename**: metadata_clean.csv * **content**: This metadata file contains information for the locations used in this study. - **columns**: * island_name: The name of the island on which acoustic sensors were placed. For more information, see Bueno et al. 2020 (see above). * site: The name of the sampling point at which acoustic data was collected. For more information, see Bueno et al. 2020 (see above). * latitude: The latitude of the sampling point, in decimal degrees. * longitude: The longitude of the sampling point, in decimal degrees. * area: The size of the island, in hectares. * ndays: The number of full days during which the soundscape was recorded. * first_day: The date of the first recording day of the soundscape at each sampling point (YYYY-MM-DD). * nplots: The total number of sampling plots at which acoustic data was collected on each island, after removal of corrupted sites. * **rows**: Each row represents a sampling point at which soundscape data was collected, as described in Bueno et al. 2020 (see above). **filename**: metadata_isolation.csv * **content**: This metadata file contains information for the locations used in this study. - **columns**: * island_name: The name of the island on which acoustic sensors were placed. For more information, see Bueno et al. 2020 (see above). * site: The name of the sampling point at which acoustic data was collected. For more information, see Bueno et al. 2020 (see above). * latitude: The latitude of the sampling point, in decimal degrees. * longitude: The longitude of the sampling point, in decimal degrees. * area: The size of the island, in hectares. * ndays: The number of full days during which the soundscape was recorded. * first_day: The date of the first recording day of the soundscape at each sampling point (YYYY-MM-DD). * nplots: The total number of sampling plots at which acoustic data was collected on each island, after removal of corrupted sites. * mrb_dist: The buffer distance used (meters) around each island edge to calculate the PW (proportion of water in buffer) isolation variable. * proportion_water: The PW (proportion of water in buffer around each island) isolation variable. * DNI: The 'distance to nearest island' isolation variable, capturing the edge-to-edge distance (meters) from a focal island to the nearest other island. * DMI: The 'distance to nearest mainland' isolation variable, capturing the edge-to-edge distance (meters) from a focal island to the nearest edge of the mainland * **rows**: Each row represents a sampling point at which soundscape data was collected, as described in Bueno et al. 2020 (see above). ##### C. RData files *(Data/RData)* **filename**: balbina_soundscapes.rds * **content**: For each plot on each island in the study, this RData file contains a an S4-object (soundscape object) with the information used to calculate the soundscape richness values. For a detailed overview of the structure of a soundscape object, consult [this](https://thomasluypaert.github.io/soundscapeR_vignette) link. Within the soundscape object, calculations are performed on the '*aggregated_df*' dataframe, which contains information on how many days OSUs were detected for each time (columns - HH:MM:SS) and frequency bin (rows - upper limit as rownames). **filename**: inc_mat.rds * **content**: For each plot on each island in the study, this RData file contains an incidence matrix with detection/non-detection data of Operational Sound Units (OSUs - rows) for each sampling day (columns). **filename**: inc_mat_island.rds * **content**: For each island in the study, this RData file contains an incidence matrix with detection/non-detection data of Operational Sound Units (OSUs - rows) for each sampling day and each plot on that island (columns). **filename**: rarefaction_cmax.rds * **content**: For each large island in the study (area &gt; 9.4 ha), this RData file contains a list with the outputs of the rarefaction procedure of `iNEXT.beta3D` to *Cmax*, including gamma, alpha, and beta values, as well as several dissimilarity measures. For an overview of the outputs of iNEXT.beta3D, consult [this](https://github.com/KaiHsiangHu/iNEXT.beta3D) link.  **filename**: rarefaction_cmin.rds * **content**: For each large island in the study (area &gt; 9.4 ha), this RData file contains a list with the outputs of the rarefaction procedure of `iNEXT.beta3D` to *Cmin*, including gamma, alpha, and beta values, as well as several dissimilarity measures. For an overview of the outputs of `iNEXT.beta3D`, consult [this](https://github.com/KaiHsiangHu/iNEXT.beta3D) link. **filename**: rarefaction_cmax_total.rds * **content**: This RData file contains a data frame with the combined output of rarefaction to *Cmax* using `iNEXT.beta3D` for the gamma (24 islands or rows), alpha (24 islands or rows) and beta (13 islands islands or rows) soundscape richness. - **columns**: * island_name: The name of the island for which rarefaction results are presented. * Order.q: The order of diversity (based on Hill numbers). Here, q=0 means the soundscape richness is presented. * SC: The sample coverage to which the rarefaction was performed (here *Cmax*). * Size: The sampling effort (number of sampling days) corresponding to the sample coverage used for rarefaction. * value: The soundscape richness value at *Cmax* (in percentage of total discoverable OSUs). * Method: Whether the rarefied values represent the observed values at the sampling effort, or were rarefied/extrapolated. * s.e.: The standard error around rarefaction estimates. * LCL: The lower 95% confidence interval. * UCL: The upper 95% confidence interval. * Diversity: The diversity type used by `iNEXT.beta3D` (here TD refers to 'Taxonomic Diversity' - even though we are working with soundscape values). Consult [https://github.com/KaiHsiangHu/iNEXT.beta3D](https://github.com/KaiHsiangHu/iNEXT.beta3D) for more information. * type: The type of biodiversity that is provided for each row (one of 'gamma', 'alpha' or 'beta). * area: The size of the island for which rarefaction results are presented, in hectares. **filename**: rarefaction_cmin_total.rds * **content**: This RData file contains a data frame with the combined output of rarefaction to *Cmin* using `iNEXT.beta3D` for the gamma (24 islands or rows), alpha (24 islands or rows) and beta (13 islands islands or rows) soundscape richness. - **columns**: * island_name: The name of the island for which rarefaction results are presented. * Order.q: The order of diversity (based on Hill numbers). Here, q=0 means the soundscape richness is presented. * SC: The sample coverage to which the rarefaction was performed (here *Cmin*). * Size: The sampling effort (number of sampling days) corresponding to the sample coverage used for rarefaction. * value: The soundscape richness value at *Cmin* (in percentage of total discoverable OSUs). * Method: Whether the rarefied values represent the observed values at the sampling effort, or were rarefied/extrapolated. * s.e.: The standard error around rarefaction estimates. * LCL: The lower 95% confidence interval. * UCL: The upper 95% confidence interval. * Diversity: The diversity type used by `iNEXT.beta3D` (here TD refers to 'Taxonomic Diversity' - even though we are working with soundscape values). Consult [https://github.com/KaiHsiangHu/iNEXT.beta3D](https://github.com/KaiHsiangHu/iNEXT.beta3D) for more information. * type: The type of biodiversity that is provided for each row (one of 'gamma', 'alpha' or 'beta). * area: The size of the island for which rarefaction results are presented, in hectares. **filename**: sample_list.rds * **content**: This RData file contains a list of 69 elements, one for each sampling plot in the study. Each list element contains five S4-objects (soundscape objects), or one per sampling day. For a detailed overview of the structure of a soundscape object, consult [https://thomasluypaert.github.io/soundscapeR_vignette](https://thomasluypaert.github.io/soundscapeR_vignette). Within the soundscape object, calculations are performed on the '*aggregated_df*' dataframe, which contains information on how many days OSUs were detected for each time (columns - HH:MM:SS) and frequency bin (rows - upper limit as rownames). **filename**: unrarefied_gamma_soundrich.rds * **content**: This RData file contains a data frame with the unrarefied gamma soundscape richness values for each island in our study (49 island - rows), as well as various types of metadata. - **columns**: * island_name: The name of the island for which rarefaction results are presented. * gamma: the unrarefied gamma soundscape richness value (in percentage of total discoverable OSUs). * latitude: the latitude of the study island in decimal degrees. * longitude: the longitude of the study island in decimal degrees. * area: the size of the island in hectares. * proportion_water: The proportion of water in the surrounding buffer (proportion of total buffer area containing water). * DNI: The distance to nearest island (in meters). * DNM: The distance to nearest mainland (in meters). \ Sharing/Access information -------------------------- CVR index data for each sound file was based on the raw sound files available on ARBIMON: * [https://arbimon.org/p/balbina/insights](https://arbimon.org/p/balbina/insights) ## Code/Software The RNotebooks described above rely on the following R packages to run: * `rstudioapi` : version 0.16.0 * `ggplot2`  : version 3.5.0 * `magrittr` : version 2.0.3 * `dplyr` : version 1.1.4 * `ggpubr` : version 0.6.0 * `sf` : version 1.0-15 * `data.table` : version 1.14.8 * `knitr` : version 1.45 * `kableExtra` : version 1.4.0 * `purrr` : version 1.0.2 * `hilldiv` : version 1.5.1 * `soundscapeR` version 0.1.0 (under development on GitHub:[ github.com/ThomasLuypaert/soundscapeR)](https://github.com/ThomasLuypaert/soundscapeR) * `raster` : version 3.6-26 * `rgeoboundaries` : version 1.3 * `elevatr` : version 0.99.0 * `ggspatial` : version 1.1.9 * `rworldmap` : version 1.3-8 * `sars` : version 1.3.6 * `patchwork` : version 1.2.0 * `olsrr` : version 0.5.3 * `iNEXT.beta.3D` : version 1.0.1 * `ggridges` : version 0.5.4 The relationship between RNotebooks is sequential, going from 1 to 10. The relationship between data files, where they are used, and how they relate to eachother is described in section 2 - File descriptions.