R. Tucker Gilman

874 total citations
34 papers, 556 citations indexed

About

R. Tucker Gilman is a scholar working on Ecology, Evolution, Behavior and Systematics, Genetics and Ecology. According to data from OpenAlex, R. Tucker Gilman has authored 34 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Ecology, Evolution, Behavior and Systematics, 12 papers in Genetics and 10 papers in Ecology. Recurrent topics in R. Tucker Gilman's work include Plant and animal studies (14 papers), Animal Behavior and Reproduction (10 papers) and Animal Vocal Communication and Behavior (7 papers). R. Tucker Gilman is often cited by papers focused on Plant and animal studies (14 papers), Animal Behavior and Reproduction (10 papers) and Animal Vocal Communication and Behavior (7 papers). R. Tucker Gilman collaborates with scholars based in United Kingdom, United States and Japan. R. Tucker Gilman's co-authors include Jocelyn E. Behm, Nicholas S. Fabina, Karen C. Abbott, Janette W. Boughman, Dwueng-Chwuan Jhwueng, Scott L. Nuismer, Nicole E. Rafferty, Leah J. Williams, Robin Abell and Christopher E. Williams and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and Scientific Reports.

In The Last Decade

R. Tucker Gilman

33 papers receiving 538 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
R. Tucker Gilman United Kingdom 13 237 179 162 122 67 34 556
Vincent A. Formica United States 12 395 1.7× 179 1.0× 199 1.2× 41 0.3× 76 1.1× 27 538
Raphaël Royauté United States 14 570 2.4× 213 1.2× 244 1.5× 88 0.7× 33 0.5× 23 776
Irja I. Ratikainen Norway 15 383 1.6× 239 1.3× 341 2.1× 159 1.3× 86 1.3× 25 758
T. A. Waite United States 12 269 1.1× 127 0.7× 203 1.3× 58 0.5× 51 0.8× 19 616
Etienne Sirot France 16 517 2.2× 193 1.1× 309 1.9× 80 0.7× 124 1.9× 25 807
Nikki Tagg Belgium 17 251 1.1× 99 0.6× 280 1.7× 147 1.2× 22 0.3× 45 661
Bram Kuijper United Kingdom 19 588 2.5× 371 2.1× 239 1.5× 59 0.5× 111 1.7× 36 1.0k
Rose Thorogood United Kingdom 17 600 2.5× 111 0.6× 485 3.0× 79 0.6× 90 1.3× 59 910
Jason Gilchrist United Kingdom 18 596 2.5× 266 1.5× 409 2.5× 73 0.6× 91 1.4× 26 947
Paulo Enrique Cardoso Peixoto Brazil 15 439 1.9× 244 1.4× 128 0.8× 111 0.9× 62 0.9× 46 571

Countries citing papers authored by R. Tucker Gilman

Since Specialization
Citations

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

Fields of papers citing papers by R. Tucker Gilman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by R. Tucker Gilman. 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 R. Tucker Gilman. The network helps show where R. Tucker Gilman may publish in the future.

Co-authorship network of co-authors of R. Tucker Gilman

This figure shows the co-authorship network connecting the top 25 collaborators of R. Tucker Gilman. A scholar is included among the top collaborators of R. Tucker Gilman 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 R. Tucker Gilman. R. Tucker Gilman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gilman, R. Tucker, et al.. (2025). Does Zipf’s law of abbreviation shape birdsong?. PLoS Computational Biology. 21(8). e1013228–e1013228. 1 indexed citations
2.
Gilman, R. Tucker, Mark Muldoon, Spyridon Megremis, et al.. (2024). Lysogeny destabilizes computationally simulated microbiomes. Ecology Letters. 27(6). e14464–e14464. 2 indexed citations
3.
Soma, Masayo, et al.. (2023). Inheritance of temporal song features in Java sparrows. Animal Behaviour. 206. 61–74. 3 indexed citations
4.
Müller, Werner, et al.. (2022). Genetic diversity of honeybee colonies predicts gut bacterial diversity of individual colony members. Environmental Microbiology. 24(12). 5643–5653. 6 indexed citations
5.
Soma, Masayo, et al.. (2021). Like Father Like Son: Cultural and Genetic Contributions to Song Inheritance in an Estrildid Finch. Frontiers in Psychology. 12. 7 indexed citations
6.
Gilman, R. Tucker, et al.. (2020). Modelling interventions to control COVID-19 outbreaks in a refugee camp. BMJ Global Health. 5(12). e003727–e003727. 22 indexed citations
7.
Gilman, R. Tucker, et al.. (2020). Young, formidable men show greater sensitivity to facial cues of dominance. Evolution and Human Behavior. 42(1). 43–50. 12 indexed citations
8.
Gilman, R. Tucker, et al.. (2020). Preregistered Report: The Effects of Marking Methodology on Mate Choice in Drosophila melanogaster. SHILAP Revista de lepidopterología. 7(4). 492–504. 1 indexed citations
9.
Gilman, R. Tucker, et al.. (2019). Left-handedness is associated with greater fighting success in humans. Scientific Reports. 9(1). 15402–15402. 31 indexed citations
10.
Smolla, Marco, et al.. (2019). Reproductive skew affects social information use. Royal Society Open Science. 6(7). 182084–182084. 5 indexed citations
11.
Gilman, R. Tucker, et al.. (2019). Light intensity affects leaf morphology in a wild population of Adenostyles alliariae (Asteraceae). SHILAP Revista de lepidopterología. 8. 35–45. 4 indexed citations
12.
Naseeb, Samina, et al.. (2018). Targeted metagenomics approach to capture the biodiversity of Saccharomyces genus in wild environments. Environmental Microbiology Reports. 11(2). 206–214. 21 indexed citations
13.
Gilman, R. Tucker & Genevieve M. Kozak. (2015). Learning to speciate: The biased learning of mate preferences promotes adaptive radiation. Evolution. 69(11). 3004–3012. 11 indexed citations
14.
Gilman, R. Tucker, Scott L. Nuismer, & Dwueng-Chwuan Jhwueng. (2012). Coevolution in multidimensional trait space favours escape from parasites and pathogens. Nature. 483(7389). 328–330. 55 indexed citations
15.
Gilman, R. Tucker, Nicholas S. Fabina, Karen C. Abbott, & Nicole E. Rafferty. (2011). Evolution of plant–pollinator mutualisms in response to climate change. Evolutionary Applications. 5(1). 2–16. 50 indexed citations
16.
Gilman, R. Tucker, et al.. (2011). SEXUAL DIMORPHISM AND SPECIATION ON TWO ECOLOGICAL COINS: PATTERNS FROM NATURE AND THEORETICAL PREDICTIONS. Evolution. 65(9). 2553–2571. 59 indexed citations
17.
Gilman, R. Tucker & Jocelyn E. Behm. (2011). HYBRIDIZATION, SPECIES COLLAPSE, AND SPECIES REEMERGENCE AFTER DISTURBANCE TO PREMATING MECHANISMS OF REPRODUCTIVE ISOLATION. Evolution. 65(9). 2592–2605. 80 indexed citations
18.
Gilman, R. Tucker, et al.. (2010). Effects of Maternal Status on the Movement and Mortality of Sterilized Female White‐Tailed Deer. Journal of Wildlife Management. 74(7). 1484–1491. 10 indexed citations
19.
Fabina, Nicholas S., Karen C. Abbott, & R. Tucker Gilman. (2009). Sensitivity of plant–pollinator–herbivore communities to changes in phenology. Ecological Modelling. 221(3). 453–458. 32 indexed citations
20.
Gilman, R. Tucker, Robin Abell, & Christopher E. Williams. (2004). How can conservation biology inform the practice of Integrated River Basin Management?. International Journal of River Basin Management. 2(2). 135–148. 30 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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