DOI: 10.5061/dryad.0rxwdbsdd
title: Data from: Optimizing passive acoustic monitoring (PAM) for Biodiversity Studies: using species-area relationship (SAR) to predict species richness

description: Passive acoustic monitoring (PAM) using autonomous recording units (ARUs)
 has become a key tool in long-term, low-cost ecological studies. However,
 one of the main challenges lies in storing and analyzing the large volume
 of data it generates, which requires significant processing effort and
 species annotation. In this context, it is crucial to establish a sampling
 and acoustic data analysis protocol that maximizes the efficiency of
 ecological information retrieval. This study proposes the application of
 the species-area relationship (SAR) mathematical model to optimize the use
 of ARUs and reduce the effort required for acoustic data analysis, aiming
 to predict the number of detected species in three Neotropical ecoregions:
 Amazonia, Caatinga, and Campos y Malezales. Our results suggest that
 increasing the number of ARUs (12 in this study) while reducing the
 post-recording listening effort (12 minutes per ARU) enhances sampling
 efficiency, allowing for a more accurate representation of biodiversity in
 the study sites. The SAR model was first applied to estimate both alpha
 and beta diversity in relation to sampling effort. In addition, beta
 diversity increased by 20% between ARUs spaced 500–1000 m apart in Campos
 y Malezales, while in Amazonia and Caatinga, where distances between
 recorders were shorter (200–250 m), the increase was much smaller (0.8 –
 5%). This highlights the importance of spatial configuration among
 recorders when interpreting species turnover patterns. Our findings
 support the design of sampling strategies adapted to different ecological
 contexts and levels of sampling effort. These insights provide a solid
 foundation for improving the management and optimization of biodiversity
 monitoring protocols in Neotropical environments. Similarly, they may be
 applied in other ecoregions using PAM, contributing to the development of
 more efficient methodologies for large-scale assessment of biological
 communities.
description: # Data from: Optimizing passive acoustic monitoring (PAM) for Biodiversity
 Studies: using species-area relationship (SAR) to predict species richness
 Dataset DOI: [10.5061/dryad.0rxwdbsdd](10.5061/dryad.0rxwdbsdd) ##
 Description of the data and file structure This dataset compiles avian
 occurrence records obtained through passive acoustic monitoring within the
 Campos and Malezales ecoregion of Argentina. The analysis is based on
 1,152 one-minute audio recordings collected using autonomous recording
 units (ARUs). Each audio file was manually inspected to identify all
 vocally detected species. These data form part of a standardized series of
 acoustic matrices for Neotropical biomes, ensuring compatibility and
 comparability across studies. Their principal value lies in providing
 organized and reusable information on avian richness and occurrence at a
 per-minute recording scale. This granularity facilitates subsequent
 analyses on diversity, acoustic patterns, and the optimization of passive
 acoustic monitoring (PAM) protocols in Neotropical landscapes through the
 application of species accumulation curves (SARs).  **Data set
 description** This dataset compiles bird occurrence data obtained from the
 manual inspection of 1,152 one-minute audio recordings collected in the
 Southern Cone Mesopotamian Savanna (Campos y Malezales ecoregion,
 Argentina). Species presence was annotated through direct listening of
 each file. The dataset is provided as a comma-separated values (CSV) file,
 consistent with the structure used in Rosa et al. (2024). In this series,
 the dataset corresponds to reference number #10
 (data_10_Campos_y_Malezales.csv). The table includes a first column
 “Species” listing all identified species, and the subsequent columns, each
 representing an individual one-minute recording. The species detections
 are encoded as 1 (present) or 0 (absent). These data complement similar
 surveys from Amazonia and Caatinga published by Rosa et al. (2024),
 allowing comparative analyses of acoustic biodiversity patterns across
 Neotropical biomes. ## Access information Other publicly accessible
 locations of the data: * n/a Data was derived from the following sources:
 *
 [https://zenodo.org/records/10556620](https://zenodo.org/records/10556620)