Marie‐Laure Navas
- Nature and Landscape Conservation top 0.5%
- Ecology and Vegetation Dynamics Studies 7
- Ecological Modeling top 0.5%
- Species Distribution and Climate Change 4
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- Plant and animal studies 9
- Global and Planetary Change top 2%
- Plant Water Relations and Carbon Dynamics 4
- Conservation, Biodiversity, and Resource Management 1
- Ecology top 1%
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- Horticultural and Viticultural Research 3
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- Irrigation Practices and Water Management 1
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- Fermentation and Sensory Analysis 1
Marie‐Laure Navas
11 papers receiving 3.8k citations
Hit Papers
Peers
Comparison fields: 5 of 94
- Nature and Landscape Conservation 2.5k
- Ecological Modeling 732
- Ecology, Evolution, Behavior and Systematics 1.5k
- Global and Planetary Change 1.1k
- Ecology 1.2k
Countries citing papers authored by Marie‐Laure Navas
This map shows the geographic impact of Marie‐Laure Navas'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 Marie‐Laure Navas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marie‐Laure Navas more than expected).
Fields of papers citing papers by Marie‐Laure Navas
This network shows the impact of papers produced by Marie‐Laure Navas. 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 Marie‐Laure Navas. The network helps show where Marie‐Laure Navas may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Marie‐Laure Navas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2021 | 9 | |
| 4 | 2019 | 27 | |
| 5 | 2017 | 78 | |
| 6 | 2016 | 20 | |
| 7 | 2013 | 120 | |
| 8 | 2009 | 100 | |
| 9 | Let the concept of trait be functional!breakdown → | 2007 | 3396 |
| 10 | 2007 | 17 | |
| 11 | 2007 | 59 | |
| 12 | 1991 | 7 | |
| 13 | 1990 | 23 |
About Marie‐Laure Navas
Marie‐Laure Navas is a scholar working on Ecological Modeling, Nature and Landscape Conservation, Ecology, Evolution, Behavior and Systematics, Global and Planetary Change and Plant Science, having authored 13 papers that have together received 3.9k indexed citations. Recurring topics across this work include Plant and animal studies (9 papers), Ecology and Vegetation Dynamics Studies (7 papers), Species Distribution and Climate Change (4 papers), Plant Water Relations and Carbon Dynamics (4 papers), Horticultural and Viticultural Research (3 papers), Irrigation Practices and Water Management (1 paper), Fermentation and Sensory Analysis (1 paper) and Conservation, Biodiversity, and Resource Management (1 paper). The work is most often cited by research in Nature and Landscape Conservation (2.5k citations), Ecological Modeling (732 citations), Ecology, Evolution, Behavior and Systematics (1.5k citations), Global and Planetary Change (1.1k citations) and Ecology (1.2k citations). Marie‐Laure Navas has collaborated with scholars based in France, Germany and Argentina. Frequent co-authors include Éric Garnier, Elena Kazakou, Cyrille Violle, Denis Vile, Claire Fortunel, Irène Hummel, Catherine Roumet, Laurent Granjon, Jens Kattge and Karim Barkaoui. Their work appears in journals such as Functional Ecology, New Phytologist, Ecology and Evolution, Weed Research and Journal of Ecology.
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.