Michael N. Weiss

1.2k total citations
39 papers, 708 citations indexed

About

Michael N. Weiss is a scholar working on Ecology, Evolution, Behavior and Systematics, Ecology and Developmental Biology. According to data from OpenAlex, Michael N. Weiss has authored 39 papers receiving a total of 708 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Ecology, Evolution, Behavior and Systematics, 23 papers in Ecology and 16 papers in Developmental Biology. Recurrent topics in Michael N. Weiss's work include Animal Behavior and Reproduction (22 papers), Marine animal studies overview (19 papers) and Animal Vocal Communication and Behavior (16 papers). Michael N. Weiss is often cited by papers focused on Animal Behavior and Reproduction (22 papers), Marine animal studies overview (19 papers) and Animal Vocal Communication and Behavior (16 papers). Michael N. Weiss collaborates with scholars based in United Kingdom, Germany and Canada. Michael N. Weiss's co-authors include Daniel W. Franks, Darren P. Croft, Samuel Ellis, Silke Kipper, Lauren J. N. Brent, Michael A. Cant, Kenneth C. Balcomb, Matthew J. Silk, Constance Scharff and Stuart Nattrass and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and PLoS ONE.

In The Last Decade

Michael N. Weiss

35 papers receiving 697 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael N. Weiss United Kingdom 16 365 283 259 186 103 39 708
Adriana A. Maldonado‐Chaparro Germany 13 427 1.2× 251 0.9× 147 0.6× 242 1.3× 94 0.9× 27 627
Eric M. Patterson United States 13 197 0.5× 433 1.5× 273 1.1× 159 0.9× 100 1.0× 26 649
Laura A. Kelley United Kingdom 15 434 1.2× 236 0.8× 221 0.9× 144 0.8× 122 1.2× 41 816
A. Catherine Markham United States 14 284 0.8× 191 0.7× 179 0.7× 437 2.3× 78 0.8× 26 633
Ipek G. Kulahci United States 13 374 1.0× 104 0.4× 157 0.6× 209 1.1× 119 1.2× 18 770
Tom P. Flower South Africa 14 562 1.5× 401 1.4× 157 0.6× 150 0.8× 152 1.5× 21 757
Tara R. Harris United States 15 373 1.0× 318 1.1× 275 1.1× 433 2.3× 57 0.6× 18 739
Margaret A. Stanton United States 16 291 0.8× 309 1.1× 311 1.2× 512 2.8× 176 1.7× 25 873
Winnie Eckardt United States 13 230 0.6× 157 0.6× 127 0.5× 346 1.9× 50 0.5× 46 505
Tyler R. Bonnell Canada 18 349 1.0× 329 1.2× 174 0.7× 455 2.4× 59 0.6× 58 847

Countries citing papers authored by Michael N. Weiss

Since Specialization
Citations

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

Fields of papers citing papers by Michael N. Weiss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael N. Weiss. 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 Michael N. Weiss. The network helps show where Michael N. Weiss may publish in the future.

Co-authorship network of co-authors of Michael N. Weiss

This figure shows the co-authorship network connecting the top 25 collaborators of Michael N. Weiss. A scholar is included among the top collaborators of Michael N. Weiss 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 Michael N. Weiss. Michael N. Weiss 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.
Darden, Safi K., et al.. (2025). Biomimetic robots reveal flexible adjustment of sexual signalling in a wild invertebrate. Proceedings of the Royal Society B Biological Sciences. 292(2052). 20251570–20251570. 1 indexed citations
2.
Silk, Matthew J., et al.. (2025). An introduction to generative network models and their use in animal sociality research. Animal Behaviour. 230. 123364–123364.
3.
Weiss, Michael N., et al.. (2025). Manufacture and use of allogrooming tools by wild killer whales. Current Biology. 35(12). R599–R600.
4.
Ellis, Samuel, et al.. (2024). The evolution of menopause in toothed whales. Nature. 627(8004). 579–585. 15 indexed citations
5.
6.
Giles, Deborah A., Samuel Ellis, John K. B. Ford, et al.. (2023). Harassment and killing of porpoises (“phocoenacide”) by fish‐eating Southern Resident killer whales (Orcinus orca). Marine Mammal Science. 40(2). 6 indexed citations
7.
Grimes, Charli, Lauren J. N. Brent, Samuel Ellis, et al.. (2023). Postreproductive female killer whales reduce socially inflicted injuries in their male offspring. Current Biology. 33(15). 3250–3256.e4. 4 indexed citations
8.
Gaydos, Joseph K., Judy St. Leger, Stephen Raverty, et al.. (2023). Epidemiology of skin changes in endangered Southern Resident killer whales (Orcinus orca). PLoS ONE. 18(6). e0286551–e0286551. 2 indexed citations
9.
Weiss, Michael N., Samuel Ellis, Daniel W. Franks, et al.. (2023). Costly lifetime maternal investment in killer whales. Current Biology. 33(4). 744–748.e3. 15 indexed citations
10.
Weiss, Michael N., et al.. (2022). Common permutation methods in animal social network analysis do not control for non-independence. Behavioral Ecology and Sociobiology. 76(11). 151–151. 35 indexed citations
11.
Grimes, Charli, Lauren J. N. Brent, Michael N. Weiss, et al.. (2022). The effect of age, sex, and resource abundance on patterns of rake markings in resident killer whales (Orcinus orca). Marine Mammal Science. 38(3). 941–958. 8 indexed citations
12.
Franks, Daniel W., et al.. (2021). Accuracy and power analysis of social networks built from count data. Methods in Ecology and Evolution. 13(1). 157–166. 6 indexed citations
13.
Franks, Daniel W., et al.. (2020). Calculating effect sizes in animal social network analysis. Methods in Ecology and Evolution. 12(1). 33–41. 30 indexed citations
14.
Weiss, Michael N., Daniel W. Franks, Lauren J. N. Brent, et al.. (2020). Common datastream permutations of animal social network data are not appropriate for hypothesis testing using regression models. Methods in Ecology and Evolution. 12(2). 255–265. 57 indexed citations
15.
Brent, Lauren J. N., et al.. (2020). Importance of old bulls: leaders and followers in collective movements of all-male groups in African savannah elephants (Loxodonta africana). Scientific Reports. 10(1). 13996–13996. 39 indexed citations
16.
Langley, Ellis, Jayden O. van Horik, Mark Whiteside, et al.. (2020). Early‐life learning ability predicts adult social structure, with potential implications for fitness outcomes in the wild. Journal of Animal Ecology. 89(6). 1340–1349. 8 indexed citations
17.
Wilhelm, Kerstin, et al.. (2017). Affairs happen—to whom? A study on extrapair paternity in common nightingales. Current Zoology. 63(4). 421–431. 7 indexed citations
18.
Weiss, Michael N., et al.. (2015). Multiple song features are related to paternal effort in common nightingales. BMC Evolutionary Biology. 15(1). 115–115. 19 indexed citations
19.
Petrusková, Tereza, Radka Reifová, Silke Kipper, et al.. (2013). The Causes and Evolutionary Consequences of Mixed Singing in Two Hybridizing Songbird Species (Luscinia spp.). PLoS ONE. 8(4). e60172–e60172. 34 indexed citations
20.
Weiss, Michael N., Sarah M. Kiefer, & Silke Kipper. (2012). Buzzwords in Females’ Ears? The Use of Buzz Songs in the Communication of Nightingales (Luscinia megarhynchos). PLoS ONE. 7(9). e45057–e45057. 27 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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