Fluxograma para artigo cientifico

Preciso de um organograma para artigo científico que considere o seguinte texto: Data compilation:  Data was obtained from published literature including 83 papers, since 1986 to December 2022. The initial date was established because it was the year of publication of CONAMA Resolution No. 001/1986, which provides for criteria and guidelines for environmental impact assessment. This resolution established that all projects with the potential to cause any type of impact on the environment must conduct studies that must be submitted and evaluated by the competent environmental agency. We searched for potential studies in the following sources: (i) online academic databases (e.g., ISI Web of Knowledge, Google Scholar, Scielo, Scopus, JStore) (ii) digital libraries of state and federal Brazilian universities, (iii) references cited in literature. The searches were based on the species listed in the Brazilian List of Reptiles and Amphibians of the Brazilian Society of Herpetology (Segalla et al., 2021; Guedes et al, 2023). More recent articles, of species described in the last year and not listed in the cited lists, were included through individual analysis. Those individuals from rescue and environmental monitoring data that integrate the type-series were also considered. For those species not listed in the mentioned lists, we used the Species New to Science Scientific Disclosure Blog (https://novataxa.blogspot.com), which is constantly updated with the discovery of new species.
Those studies that contained any mention of projects and/or activity resulting from an environmental impact study (e.g., uhe, pch, fauna rescue, fauna monitoring) or even mention of the contracting company were considered, and the following information was transcribed to a database: taxonomic group (amphibians, reptiles), year of description), project development (e.g., Mining, road, hydroelectric and transmission line), and scientific journal.

Site description:  We selected studies that were published in Brazil, in any region and biome of the country. We restricted our focus to species described in Brazil due to a better understanding of environmental legislation and the need for environmental studies in the scope of environmental licensing. In addition, the fauna monitoring and rescue data in the description of species seems to be more common in Brazil, where several projects are licensed every year. 

Research Methods: We included in this database, studies that reported describing new reptiles and amphibians species (taxon), year, project development and the enterprise name. Lack of information were filled with NA. However, some studies that did not provide a substantial detailed information were excluded at early stages of the database. We also included information from the geographical location (when provided, we tabulated latitude, longitude, locality, municipality and state).

Taxonomic data: We used animal taxonomic information for amphibians according to Frost (2023) and for the reptile’s species Uetz et al. (2023). We added one column with the current scientific name based on previous authors where this association was possible (e.g., Changes on generic attribution, species group name synonymy, species identified as sp. Or spp. Were sometimes identifiable by geography). In addition, we recorded the basic publishing information of each study (author, title, year, journal, volume, number of issues, pages, place of publication, DOI to the document and others relevant information) in the supplementary material.

Data analyses
The descriptive analyses represented in graphs and tables, we sought to evaluate whether the number of descriptions increased over the years, through a Spearman correlation analysis (Zar, 1999). The analysis procedures were performed in Rstudio software version 4.2.3 (Rstudio, 2023).
To observe the spatial distribution of information and determine which Brazilian biome had the highest number of described species in recent years, we plotted the data on a map with divisions of Brazil according to the Brazilian Institute of Geography and Statistics - ibge (ibge, 2019). In order to observe the regions where more species were described and, consequently, more representative, heat maps were made using a shapefile (.shp) file using the Qgis software version 3.20 (Qgis, 2021). The heat map uses a so-called kernel density technique to estimate the density of occurrences in different regions of space. When viewing a heat map, regions with a higher concentration of occurrence are represented by more intense nuclei, while areas with lower density are represented by lighter nuclei. This allows you to quickly identify locations of high activity or concentration, as well as locations with less occurrence