Fabrizio Spagnolo
- Ecological Modeling top 1%
- Ecology top 5%
- Nature and Landscape Conservation top 5%
- Ecology, Evolution, Behavior and Systematics top 5%
- Global and Planetary Change top 10%
- Co-authors
- M. Caitlin Fisher‐ReidMatthew E. Aiello‐LammensGena C. SbegliaJohn J. WiensCaitlin J. KaranewskyXia HuaAbigail CahillOmar Warsi
- Topics
- COVID-19 epidemiological studies (2 papers)Species Distribution and Climate Change (2 papers)Antibiotic Resistance in Bacteria (2 papers)
- Journals
- PLoS ONEProceedings of the Royal Society B Biological SciencesAntimicrobial Agents and Chemotherapy
- Partner nations
- United StatesAustralia
In The Last Decade
Fabrizio Spagnolo
7 papers receiving 827 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Ecological Modeling 451
- Ecology 434
- Nature and Landscape Conservation 279
- Ecology, Evolution, Behavior and Systematics 247
- Global and Planetary Change 226
Countries citing papers authored by Fabrizio Spagnolo
This map shows the geographic impact of Fabrizio Spagnolo'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 Fabrizio Spagnolo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabrizio Spagnolo more than expected).
Fields of papers citing papers by Fabrizio Spagnolo
This network shows the impact of papers produced by Fabrizio Spagnolo. 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 Fabrizio Spagnolo. The network helps show where Fabrizio Spagnolo may publish in the future.
Co-authorship network of co-authors of Fabrizio Spagnolo
This figure shows the co-authorship network connecting the top 25 collaborators of Fabrizio Spagnolo. A scholar is included among the top collaborators of Fabrizio Spagnolo 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 Fabrizio Spagnolo. Fabrizio Spagnolo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 20 | |
| 3 | 11 | |
| 4 | 3 | |
| 5 | 28 | |
| 6 | 144 | |
| 7 | How does climate change cause extinction?breakdown → | 647 |
| 8 | 2 |
About Fabrizio Spagnolo
Fabrizio Spagnolo is a scholar working on Ecological Modeling, Modeling and Simulation and Molecular Medicine, having authored 8 papers that have together received 855 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (2 papers), Species Distribution and Climate Change (2 papers) and Antibiotic Resistance in Bacteria (2 papers). The work is most often cited by research in Ecological Modeling (451 citations), Nature and Landscape Conservation (279 citations) and Ecology (434 citations). Fabrizio Spagnolo has collaborated with scholars based in United States and Australia. Frequent co-authors include M. Caitlin Fisher‐Reid, Matthew E. Aiello‐Lammens, Gena C. Sbeglia, John J. Wiens, Caitlin J. Karanewsky, Xia Hua, Abigail Cahill, Omar Warsi, Daniel E. Dykhuizen and John J. Dennehy. Their work appears in journals such as PLoS ONE, Proceedings of the Royal Society B Biological Sciences and Antimicrobial Agents and Chemotherapy.
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.