H. Lisle Gibbs

8.8k total citations · 1 hit paper
171 papers, 6.8k citations indexed

About

H. Lisle Gibbs is a scholar working on Genetics, Ecology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, H. Lisle Gibbs has authored 171 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 110 papers in Genetics, 75 papers in Ecology and 60 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in H. Lisle Gibbs's work include Genetic diversity and population structure (77 papers), Amphibian and Reptile Biology (52 papers) and Avian ecology and behavior (48 papers). H. Lisle Gibbs is often cited by papers focused on Genetic diversity and population structure (77 papers), Amphibian and Reptile Biology (52 papers) and Avian ecology and behavior (48 papers). H. Lisle Gibbs collaborates with scholars based in United States, Canada and Brazil. H. Lisle Gibbs's co-authors include Keith A. Hobson, Peter R. Grant, Patrick J. Weatherhead, Peter T. Boag, Juan J. Calvete, Líbia Sanz, Spencer G. Sealy, Stephen P. Mackessy, Mark L. Gloutney and Michael G. Sovic and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

H. Lisle Gibbs

166 papers receiving 6.3k citations

Hit Papers

Genomic signals of selection predict climate-driven popul... 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H. Lisle Gibbs United States 44 3.5k 3.3k 2.5k 1.4k 930 171 6.8k
Roger S. Thorpe United Kingdom 45 3.4k 1.0× 1.6k 0.5× 1.7k 0.7× 2.6k 1.8× 835 0.9× 137 5.9k
Carles Vilà Spain 48 4.9k 1.4× 3.4k 1.0× 909 0.4× 699 0.5× 504 0.5× 125 7.3k
DeeAnn M. Reeder United States 29 1.9k 0.6× 3.4k 1.0× 3.9k 1.6× 587 0.4× 407 0.4× 63 7.4k
Steven M. Goodman United States 45 2.0k 0.6× 3.4k 1.0× 4.3k 1.7× 2.0k 1.4× 1.2k 1.3× 385 9.7k
Kelly R. Zamudio United States 56 2.9k 0.8× 2.8k 0.8× 3.0k 1.2× 4.9k 3.4× 2.1k 2.3× 187 9.3k
Alan R. Lemmon United States 52 4.7k 1.4× 1.7k 0.5× 3.9k 1.6× 1.9k 1.3× 1.4k 1.5× 155 10.0k
Uwe Fritz Germany 39 2.1k 0.6× 1.6k 0.5× 726 0.3× 2.4k 1.7× 2.8k 3.0× 197 5.0k
David S. Woodruff United States 38 2.1k 0.6× 2.4k 0.7× 1.2k 0.5× 724 0.5× 612 0.7× 95 5.0k
Frank T. Burbrink United States 47 4.0k 1.2× 2.0k 0.6× 2.5k 1.0× 4.8k 3.3× 2.0k 2.2× 128 8.5k
Emily Moriarty Lemmon United States 50 4.2k 1.2× 1.7k 0.5× 3.7k 1.5× 1.9k 1.3× 1.4k 1.5× 156 9.2k

Countries citing papers authored by H. Lisle Gibbs

Since Specialization
Citations

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

Fields of papers citing papers by H. Lisle Gibbs

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H. Lisle Gibbs. 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 H. Lisle Gibbs. The network helps show where H. Lisle Gibbs may publish in the future.

Co-authorship network of co-authors of H. Lisle Gibbs

This figure shows the co-authorship network connecting the top 25 collaborators of H. Lisle Gibbs. A scholar is included among the top collaborators of H. Lisle Gibbs 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 H. Lisle Gibbs. H. Lisle Gibbs 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.
Hogan, Michael, Matthew L. Holding, Gunnar S. Nystrom, et al.. (2024). The genetic regulatory architecture and epigenomic basis for age-related changes in rattlesnake venom. Proceedings of the National Academy of Sciences. 121(16). e2313440121–e2313440121. 12 indexed citations
2.
Titus, Benjamin M., H. Lisle Gibbs, Nuno Simões, & Marymegan Daly. (2024). Topology Testing and Demographic Modeling Illuminate a Novel Speciation Pathway in the Greater Caribbean Sea Following the Formation of the Isthmus of Panama. Systematic Biology. 73(5). 758–768.
4.
Anderson, Eric C., Christen M. Bossu, Teia M. Schweizer, et al.. (2023). Low‐coverage whole genome sequencing for highly accurate population assignment: Mapping migratory connectivity in the American Redstart (Setophaga ruticilla). Molecular Ecology. 32(20). 5528–5540. 9 indexed citations
5.
6.
Sousa, Leijiane F., Matthew L. Holding, Marisa Maria Teixeira da Rocha, et al.. (2021). Individual Variability in Bothrops atrox Snakes Collected from Different Habitats in the Brazilian Amazon: New Findings on Venom Composition and Functionality. Toxins. 13(11). 814–814. 15 indexed citations
7.
Wieringa, Jamin G., Bryan C. Carstens, & H. Lisle Gibbs. (2021). Predicting migration routes for three species of migratory bats using species distribution models. PeerJ. 9. e11177–e11177. 21 indexed citations
8.
Viala, Vincent Louis, Pedro G. Nachtigall, Michael Broe, et al.. (2021). Tracking the recruitment and evolution of snake toxins using the evolutionary context provided by the Bothrops jararaca genome. Proceedings of the National Academy of Sciences. 118(20). 36 indexed citations
9.
10.
Wieringa, Jamin G., Juliet Nagel, David M. Nelson, Bryan C. Carstens, & H. Lisle Gibbs. (2020). Using trace elements to identify the geographic origin of migratory bats. PeerJ. 8. e10082–e10082. 9 indexed citations
11.
Bay, Rachael A., Ryan J. Harrigan, Vinh Le Underwood, et al.. (2018). Genomic signals of selection predict climate-driven population declines in a migratory bird. Science. 359(6371). 83–86. 338 indexed citations breakdown →
12.
Sovic, Michael G., Bryan C. Carstens, & H. Lisle Gibbs. (2016). Genetic diversity in migratory bats: Results from RADseq data for three tree bat species at an Ohio windfarm. PeerJ. 4. e1647–e1647. 30 indexed citations
13.
Gibbs, H. Lisle, et al.. (2010). Similarity of contemporary and historical gene flow among highly fragmented populations of an endangered rattlesnake. Molecular Ecology. 19(24). 5345–5358. 114 indexed citations
14.
Gibbs, H. Lisle, et al.. (2009). Efficacy of Land‐Cover Models in Predicting Isolation of Marbled Salamander Populations in a Fragmented Landscape. Conservation Biology. 23(5). 1232–1241. 43 indexed citations
15.
Tieleman, B. Irene, Maaike A. Versteegh, Anthony C Fries, et al.. (2009). Genetic modulation of energy metabolism in birds through mitochondrial function. Proceedings of the Royal Society B Biological Sciences. 276(1662). 1685–1693. 55 indexed citations
16.
Francisco, Mercival R., H. Lisle Gibbs, Mauro Galetti, Vitor de Oliveira Lunardi, & Pedro Manoel Galetti. (2007). Genetic structure in a tropical lek‐breeding bird, the blue manakin (Chiroxiphia caudata) in the Brazilian Atlantic Forest. Molecular Ecology. 16(23). 4908–4918. 45 indexed citations
17.
18.
Gibbs, H. Lisle, Michael D. Sorenson, Karen Marchetti, et al.. (2000). Genetic evidence for female host-specific races of the common cuckoo. Nature. 407(6801). 183–186. 207 indexed citations
20.
Gibbs, H. Lisle, et al.. (1974). Initial-stage sulfuric acid leaching kinetics of chalcopyrite using radiochemical techniques. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 31(5). 816–816. 13 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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