Maya Guéguen

22 papers receiving 1.0k citations

Maya Guéguen's Hit Papers

Uncertainty in ensembles of global biodiversity scenarios 2019 · 336 citations
3360+2+4Years since publication100200300

Peers

Maya Guéguen
Comparison fields: 5 of 79
  • Ecological Modeling 544
  • Nature and Landscape Conservation 404
  • Ecology 459
  • Ecology, Evolution, Behavior and Systematics 273
  • Global and Planetary Change 212
Replace Guilherme de Oliveira with:
Guilherme de Oliveira Brazil
Mindy M. Syfert United Kingdom
Vera Zizka Germany
María Ariza Norway
Josué A. R. Azevedo Brazil
Severin D. H. Irl Germany
Andrew J. Suggitt United Kingdom
Buntarou Kusumoto Japan
Alex Gilman United States
Niklas Wengström Sweden
Maya Guéguen relative to Guilherme de Oliveira Brazil Guilherme de Oliveira's profile →
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Citations per year

Countries citing papers authored by Maya Guéguen

Since Specialization
Citations

This map shows the geographic impact of Maya Guéguen'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 Maya Guéguen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya Guéguen more than expected).

Fields of papers citing papers by Maya Guéguen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maya Guéguen. 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 Maya Guéguen. The network helps show where Maya Guéguen may publish in the future.

Co-authors

The 25 scholars most cited alongside Maya Guéguen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Maya Guéguen Line = papers co-authored together Maya Guéguen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Uncertainty in ensembles of global biodiversity scenarios
Hit paper breakdown →
2019336
2 202096
3 202183
4 201758
5 201453
6 201950
7 202049
8 202244
9 201642
10 201935
11 201731
12 202127
13 202022
14 201721
15 201919
16 202117
17 201816
18 202111
19 20235
20 20224

About Maya Guéguen

Maya Guéguen is a scholar working on Ecological Modeling, Nature and Landscape Conservation, Ecology, Ecology, Evolution, Behavior and Systematics and Genetics, having authored 24 papers that have together received 1.0k indexed citations. Recurring topics across this work include Species Distribution and Climate Change (19 papers), Ecology and Vegetation Dynamics Studies (13 papers), Plant and animal studies (7 papers), Forest Insect Ecology and Management (3 papers), Wildlife Ecology and Conservation (3 papers), Avian ecology and behavior (2 papers), Lepidoptera: Biology and Taxonomy (2 papers) and Plant Water Relations and Carbon Dynamics (2 papers). The work is most often cited by research in Ecological Modeling (544 citations), Nature and Landscape Conservation (404 citations), Ecology (459 citations), Ecology, Evolution, Behavior and Systematics (273 citations) and Global and Planetary Change (212 citations). Maya Guéguen has collaborated with scholars based in France, Switzerland and Italy. Frequent co-authors include Wilfried Thuiller, Julien Renaud, Niklaus E. Zimmermann, Dirk Nikolaus Karger, Sébastien Lavergne, Nicolas Loiseau, Matthias Grenié, Mattia Menchetti, Gerard Talavera and Brian Maitner. Their work appears in journals such as Diversity and Distributions, Current Biology, Nature Communications, Ecography and Journal of Biogeography.

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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