DOI: 10.5061/dryad.0000000bs
title: The effectiveness of Marine Protected Areas on the spatiotemporal patterns of reef fish in the Southwest Atlantic

description: This study explored spatiotemporal patterns influencing reef fish richness
 and abundance in two coastal islands within Marine Protected Areas (MPAs)
 in southeastern Brazil. Data were collected using a Remotely Operated
 Vehicle (ROV) during the 2022 seasonal cycle, with samples taken day and
 night. A total of 16,661 individuals from 81 species was recorded. The
 results showed that fish abundance was higher during the day, in winter,
 and in areas with high temperatures. At night, in autumn, behavioral
 changes were observed in schooling species. Seasonal variations, including
 temperature changes and the oceanographic characteristics of the study
 area, influenced fish abundance and species composition, favoring tropical
 and subtropical species. Depth affected the islands differently: higher
 abundance was observed in deeper waters at Anchieta Island State Park,
 while shallower waters at Mar Virado Island showed greater abundance due
 to habitat complexity. Diurnal variation in richness was significant at
 Mar Virado Island, likely due to increased nocturnal predation. For
 fishing-targeted species, the islands showed significant effects on
 species composition and abundance, highlighting the importance of
 protected areas. The study offers key insights into reef fish dynamics,
 emphasizing the role of spatiotemporal variables in shaping communities
 and supporting conservation strategies in MPAs.
description: The dataset was collected in the field during the development of
 this work, through visual census conducted by a remotely operated vehicle
 (ROV). The data were processed using the R platform.
description: # The effectiveness of Marine Protected Areas on the spatiotemporal
 patterns of reef fish in the Southwest Atlantic
 [https://doi.org/10.5061/dryad.0000000bs](https://doi.org/10.5061/dryad.0000000bs) ### Data Table **1 - data.xlsx **– the complete Excel spreadsheet containing the raw data. To run the data in R Studio, use exactly the data from the ' data' spreadsheet, starting with the "dada" tab and then the "importance" tab. **Tab: dada - Dataset for abundance and richness analyses.** The columns that will be used for the analyses are: **Columns A, B, C, and D:** Categorical variables: "CS", "DP", "LOC" and "POI" **Columns E and F:** Abiotic variables: "TEMP" and "DEPT" **Columns G and H:** Response variables: "NAB" and "RIC" **Columns I to CK:** Numerical abundances of the species **Legend:** **CS** = season (4 levels: WIN: winter, SUM: summer, AUT: autumn and SPR: spring) **DP** = diurnal period (2 levels: DIA: day and NOI: night) **LOC** = locality (2 levels: IMV: Ilha do Mar Virado and PEIA: Parque Estadual Ilha Anchieta) **POI** = Sampling point (4 points (1,2,3 and 4) on each locality) **TEMP** = Temperature (ºC) **DEPT** = Depth (meters) **NAB** = Numerical abundance **RIC** = Richness **Tab: importance - Dataset for behavior and composition analysis. The data in this tab are binary, as the objective is to determine which species are of interest for fishing, which are threatened, and whether they form schools or not. The species are the same as those present in the "data" tab.** The columns that will be used for the analyses are: **Columns A, B, C, and D:** Categorical variables: “COD”, " Fishing", "Threatened" and " Schooling" **Legend:** **COD:** Code with the species names **Fishing:** target fishing species **Threatened:** threatened species **Schooling:** schooling species ### Scripts R **2- abundance.R** – contains the script for the statistical analysis of the abundance data **3- supplementary material** - run after abundance.R **4- behavior.R** – contains the script for the statistical analysis of the abundance data, segmented by the species behavior of forming or not forming schools. **5- composition.R** – contains the script for the statistical analysis of the species composition data **6- richness.R** – contains the script for the statistical analysis of the species richness data