Paper Silva et al Paru forest manegement
Description
Raw data in spreadsheets collected during a study in the Paru State Forest, northeastern Amazon, Brazil. They are organized in a spreadsheet and were used to perform statistical analyses and obtain the results presented in an article in the journal Data in Brief.
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Camera traps For data collection, VIKERI camera traps (https://vikeri.tech/) were utilized. These were installed approximately 30 cm above ground level and oriented perpendicular to the ground, ensuring a minimum distance of 1 km between each sampling point. A total of 18 camera traps were deployed at 12 distinct points (Figure 1). The employment of camera traps in wildlife monitoring is acknowledged as a reliable and minimally invasive approach, significantly reducing the effort required for wildlife research (Chiarello 2007; Silveira et al. 2003). Photo trapping was executed in three distinct stages. The first stage, from November 2, 2021, to December 6, 2021, involved installing five traps at various points. The second stage spanned from December 6, 2021, to March 9, 2022, when the traps remained at the same points. The final stage, from March 11, 2022, to July 31, 2022, saw the addition of eight cameras at new points within the FMU IX area. During sampling 18 cameras deployed, two encountered technical issues. This resulted in a total sampling effort of 1,401 cameras/day, yielding 3,442 images and approximately 1,147 videos. Of these, 2,652 were animal records, predominantly mammals with 1,857 image captures and birds with 795 captures. There were also 237 blank photos (triggered without capturing an image), 174 images of small mammals or passerine birds, 327 images depicting researchers in the facilities and during equipment collection, and 41 images affected by technical failures. Handling of records through trap cameras Wild.ID (https://wildlifeinsights.org/WMS/#/shareData) was employed to screen and identify images captured by the camera traps. This software is adept at managing and processing large volumes of data and possesses the capability to export data for sharing with other users on the same platform. However, as it is designed to process only images, the videos recorded by the traps were manually screened and identified. Statistical analyses The Rarefaction Accumulation Curve was utilized for mammals and birds to assess the completeness of the sampling process (Oksane et al. 2022. An Analysis of Variance (ANOVA) was conducted to examine differences in the diversity of mammals and birds across various selective cutting environments. Subsequently, a nonmetric Multidimensional Scaling Analysis (nMDS) was performed, employing the abundance matrix of the studied groups (using two dimensions and Bray-Curtis dissimilarity) to determine species behavior in different forest management environments. All statistical analyses were executed using R (R DEVELOPMENT CORE TEAM 2014).