Megan Ruffley

693 total citations · 1 hit paper
16 papers, 355 citations indexed

About

Megan Ruffley is a scholar working on Ecological Modeling, Genetics and Nature and Landscape Conservation. According to data from OpenAlex, Megan Ruffley has authored 16 papers receiving a total of 355 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Ecological Modeling, 9 papers in Genetics and 8 papers in Nature and Landscape Conservation. Recurrent topics in Megan Ruffley's work include Species Distribution and Climate Change (9 papers), Ecology and Vegetation Dynamics Studies (8 papers) and Genetic diversity and population structure (7 papers). Megan Ruffley is often cited by papers focused on Species Distribution and Climate Change (9 papers), Ecology and Vegetation Dynamics Studies (8 papers) and Genetic diversity and population structure (7 papers). Megan Ruffley collaborates with scholars based in United States, Spain and United Kingdom. Megan Ruffley's co-authors include David C. Tank, Bryan C. Carstens, Jack Sullivan, Anahí Espíndola, Megan L. Smith, Moisés Expósito‐Alonso, Lauren Gillespie, Patricia L. M. Lang, Lucas Czech and Tom R. Booker and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and PLoS ONE.

In The Last Decade

Megan Ruffley

16 papers receiving 351 citations

Hit Papers

Genetic diversity loss in the Anthropocene 2022 2026 2023 2024 2022 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Megan Ruffley United States 9 177 118 115 97 93 16 355
Alexander T. Xue United States 10 241 1.4× 129 1.1× 115 1.0× 95 1.0× 117 1.3× 12 418
Hernando Rodríguez‐Correa Mexico 10 143 0.8× 95 0.8× 72 0.6× 84 0.9× 97 1.0× 20 320
Nicolás A. Hazzi United States 9 160 0.9× 88 0.7× 57 0.5× 127 1.3× 83 0.9× 21 329
Jorge Montiel United States 1 80 0.5× 102 0.9× 153 1.3× 109 1.1× 99 1.1× 3 318
Odile Maliet France 7 134 0.8× 72 0.6× 104 0.9× 133 1.4× 115 1.2× 10 371
Rob Massatti United States 11 254 1.4× 156 1.3× 171 1.5× 127 1.3× 113 1.2× 22 420
Celestino Flores‐López Mexico 8 109 0.6× 85 0.7× 113 1.0× 68 0.7× 147 1.6× 24 319
Natalia Trujillo‐Arias Argentina 10 137 0.8× 78 0.7× 85 0.7× 121 1.2× 91 1.0× 19 275
Bogdan‐Iuliu Hurdu Romania 10 69 0.4× 129 1.1× 132 1.1× 120 1.2× 118 1.3× 28 412
Frank R. Stokvis Netherlands 8 177 1.0× 88 0.7× 239 2.1× 122 1.3× 46 0.5× 17 367

Countries citing papers authored by Megan Ruffley

Since Specialization
Citations

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

Fields of papers citing papers by Megan Ruffley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megan Ruffley

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

All Works

16 of 16 papers shown
1.
Ruffley, Megan, et al.. (2025). Planting Genomes in the Wild: Arabidopsis from Genetics History to the Ecology and Evolutionary Genomics Era. Annual Review of Plant Biology. 76(1). 605–635. 5 indexed citations
2.
Gillespie, Lauren, Megan Ruffley, & Moisés Expósito‐Alonso. (2024). Deep learning models map rapid plant species changes from citizen science and remote sensing data. Proceedings of the National Academy of Sciences. 121(37). e2318296121–e2318296121. 9 indexed citations
3.
Overcast, Isaac, et al.. (2024). Detecting the ecological footprint of selection. PLoS ONE. 19(6). e0302794–e0302794. 1 indexed citations
4.
Ruffley, Megan, Megan L. Smith, Anahí Espíndola, et al.. (2022). Genomic evidence of an ancient inland temperate rainforest in the Pacific Northwest of North America. Molecular Ecology. 31(10). 2985–3001. 5 indexed citations
5.
Vance, Summer E., et al.. (2022). From coral reefs to Joshua trees: What ecological interactions teach us about the adaptive capacity of biodiversity in the Anthropocene. Philosophical Transactions of the Royal Society B Biological Sciences. 377(1857). 20210389–20210389. 8 indexed citations
6.
Expósito‐Alonso, Moisés, Tom R. Booker, Lucas Czech, et al.. (2022). Genetic diversity loss in the Anthropocene. Science. 377(6613). 1431–1435. 128 indexed citations breakdown →
7.
Overcast, Isaac, Megan Ruffley, James Rosindell, et al.. (2021). A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities. Molecular Ecology Resources. 21(8). 2782–2800. 29 indexed citations
8.
Gillespie, Lauren, Megan Ruffley, & Moisés Expósito‐Alonso. (2021). An Image is Worth a Thousand Species: Scaling high-resolution plant biodiversity prediction to biome-level using citizen science data and remote sensing imagery. Biodiversity Information Science and Standards. 5. 1 indexed citations
9.
Ruffley, Megan, et al.. (2021). Phylogenetic diversity and community assembly in a naturally fragmented system. Ecology and Evolution. 11(24). 18066–18080. 3 indexed citations
10.
Sullivan, Jack, Megan L. Smith, Anahí Espíndola, et al.. (2019). Integrating life history traits into predictive phylogeography. Molecular Ecology. 28(8). 2062–2073. 13 indexed citations
11.
McGill, Brian J., Jonathan M. Chase, Joaquín Hortal, et al.. (2019). Unifying macroecology and macroevolution to answer fundamental questions about biodiversity. Global Ecology and Biogeography. 28(12). 1925–1936. 38 indexed citations
12.
Ruffley, Megan, et al.. (2019). Identifying models of trait‐mediated community assembly using random forests and approximate Bayesian computation. Ecology and Evolution. 9(23). 13218–13230. 14 indexed citations
13.
Ruffley, Megan, Megan L. Smith, Anahí Espíndola, et al.. (2018). Combining allele frequency and tree‐based approaches improves phylogeographic inference from natural history collections. Molecular Ecology. 27(4). 1012–1024. 8 indexed citations
14.
Smith, Megan L., Megan Ruffley, A. M. Rankin, et al.. (2018). Testing for the presence of cryptic diversity in tail-dropper slugs (Prophysaon) using molecular data. Biological Journal of the Linnean Society. 124(3). 518–532. 8 indexed citations
15.
Smith, Megan L., Megan Ruffley, Anahí Espíndola, et al.. (2017). Demographic model selection using random forests and the site frequency spectrum. Molecular Ecology. 26(17). 4562–4573. 38 indexed citations
16.
Espíndola, Anahí, Megan Ruffley, Megan L. Smith, et al.. (2016). Identifying cryptic diversity with predictive phylogeography. Proceedings of the Royal Society B Biological Sciences. 283(1841). 20161529–20161529. 47 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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