Flávia Pinto

797 total citations
8 papers, 428 citations indexed

About

Flávia Pinto is a scholar working on Nature and Landscape Conservation, Ecology and Global and Planetary Change. According to data from OpenAlex, Flávia Pinto has authored 8 papers receiving a total of 428 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Nature and Landscape Conservation, 4 papers in Ecology and 3 papers in Global and Planetary Change. Recurrent topics in Flávia Pinto's work include Ecology and Vegetation Dynamics Studies (4 papers), Species Distribution and Climate Change (2 papers) and Conservation, Biodiversity, and Resource Management (2 papers). Flávia Pinto is often cited by papers focused on Ecology and Vegetation Dynamics Studies (4 papers), Species Distribution and Climate Change (2 papers) and Conservation, Biodiversity, and Resource Management (2 papers). Flávia Pinto collaborates with scholars based in Brazil and United States. Flávia Pinto's co-authors include Eric A. Davidson, Carlos Augusto Klink, Rafael S. Oliveira, Luciano Mendes Bezerra, Adriana Gonçalves Moreira, Daniel C. Nepstad, Reinaldo Imbrózio Barbosa, Philip M. Fearnside, Laerte Guimarães Ferreira and Leandro Baumgarten and has published in prestigious journals such as Expert Systems with Applications, Remote Sensing and Functional Ecology.

In The Last Decade

Flávia Pinto

8 papers receiving 413 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Flávia Pinto Brazil	5	215	121	102	97	86	8	428
Khishigbayar Jamiyansharav United States	6	257 1.2×	82 0.7×	85 0.8×	112 1.2×	61 0.7×	7	431
Changming Zhao China	13	223 1.0×	126 1.0×	179 1.8×	135 1.4×	117 1.4×	32	485
Carla Nogueira Portugal	10	228 1.1×	106 0.9×	187 1.8×	142 1.5×	119 1.4×	17	435
Meta Francis Justine China	12	126 0.6×	186 1.5×	113 1.1×	102 1.1×	53 0.6×	17	388
Patrick Mordelet France	11	261 1.2×	161 1.3×	205 2.0×	108 1.1×	87 1.0×	17	488
C. Rebella Argentina	5	203 0.9×	105 0.9×	46 0.5×	183 1.9×	106 1.2×	12	451
Marcus Guderle Germany	9	162 0.8×	60 0.5×	128 1.3×	80 0.8×	50 0.6×	10	302
G. M. Bettiol Brazil	9	108 0.5×	92 0.8×	68 0.7×	120 1.2×	65 0.8×	25	371
S. R. Murphy Australia	17	91 0.4×	166 1.4×	73 0.7×	117 1.2×	67 0.8×	38	642
Monika Rawat India	11	144 0.7×	85 0.7×	173 1.7×	65 0.7×	67 0.8×	24	312

Countries citing papers authored by Flávia Pinto

Since Specialization

Citations

This map shows the geographic impact of Flávia Pinto's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Flávia Pinto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Flávia Pinto more than expected).

Fields of papers citing papers by Flávia Pinto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Flávia Pinto. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Flávia Pinto. The network helps show where Flávia Pinto may publish in the future.

Co-authorship network of co-authors of Flávia Pinto

This figure shows the co-authorship network connecting the top 25 collaborators of Flávia Pinto. A scholar is included among the top collaborators of Flávia Pinto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Flávia Pinto. Flávia Pinto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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8 of 8 papers shown

Leandro‐Silva, Victor, et al.. (2022). Using consensus mapping methods as an efficient way of depicting avian distributions in the Caatinga Dry Forest, a poorly known Neotropical biome. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 30(3). 204–215. 1 indexed citations

Naka, Luciano N., et al.. (2020). Climate as a major driver of avian diversity in riparian Amazonian habitats along an environmental gradient. Journal of Biogeography. 47(11). 2328–2340. 9 indexed citations

Ferreira, Laerte Guimarães, et al.. (2019). Correction: Pereira, O.; et al. Assessing Pasture Degradation in the Brazilian Cerrado Based on the Analysis of MODIS NDVI Time-Series. Remote Sensing 2018, 10(11) 1761. Remote Sensing. 11(21). 2491–2491. 1 indexed citations

Ferreira, Laerte Guimarães, et al.. (2018). Assessing Pasture Degradation in the Brazilian Cerrado Based on the Analysis of MODIS NDVI Time-Series. Remote Sensing. 10(11). 1761–1761. 75 indexed citations

Siqueira, Marinez Ferreira de, et al.. (2015). Applying data mining techniques for spatial distribution analysis of plant species co-occurrences. Expert Systems with Applications. 43. 250–260. 9 indexed citations

Barbosa, Reinaldo Imbrózio, et al.. (2007). The Lavrados of Roraima: Biodiversity and Conservation of Brazil's Amazonian Savannas. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 78 indexed citations

Oliveira, Rafael S., Luciano Mendes Bezerra, Eric A. Davidson, et al.. (2005). Deep root function in soil water dynamics in cerrado savannas of central Brazil. Functional Ecology. 19(4). 574–581. 253 indexed citations

Laurance, William F., Rita C. G. Mesquita, Regina C. C. Luizão, & Flávia Pinto. (2004). The Biological Dynamics of Forest Fragments Project: 25 Years of Research in the Brazilian Amazon. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 20(14). 2175–82. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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