Shannon M. Barber‐Meyer
- Ecology top 2%
- Wildlife Ecology and Conservation 28
- Rangeland and Wildlife Management 11
- Marine animal studies overview 9
- Ecology and biodiversity studies 5
- Animal Ecology and Behavior Studies 4
- Wildlife-Road Interactions and Conservation 4
- Ecological Modeling top 5%
- Species Distribution and Climate Change 7
- Small Animals top 2%
- Animal Behavior and Welfare Studies 10
- Developmental Biology top 10%
- Co-authors
- L. David MechP. J. WhiteGerald L. KooymanPaul J. PonganisAdam BarlowColby LoucksJohn D. ErbDominic J. Demma
- Journals
- SHILAP Revista de lepidopterología (4 papers)PLoS ONE (1 paper)Clinical Microbiology Reviews (1 paper)
- Partner nations
- United StatesIndiaCanada
In The Last Decade
Shannon M. Barber‐Meyer
47 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 86
- Ecology 877
- Ecological Modeling 121
- Small Animals 153
- Developmental Biology 29
- Nature and Landscape Conservation 127
Countries citing papers authored by Shannon M. Barber‐Meyer
This map shows the geographic impact of Shannon M. Barber‐Meyer'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 Shannon M. Barber‐Meyer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shannon M. Barber‐Meyer more than expected).
Fields of papers citing papers by Shannon M. Barber‐Meyer
This network shows the impact of papers produced by Shannon M. Barber‐Meyer. 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 Shannon M. Barber‐Meyer. The network helps show where Shannon M. Barber‐Meyer may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shannon M. Barber‐Meyer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2023 | 7 | |
| 4 | 2022 | 1 | |
| 5 | 2022 | 2 | |
| 6 | 2022 | 2 | |
| 7 | 2021 | 2 | |
| 8 | 2018 | 17 | |
| 9 | Use of non-invasive genetics to generate core-area population estimates of a threatened predator in the Superior National Forest, USA | 2018 | 3 |
| 10 | 2017 | 1 | |
| 11 | 2016 | 37 | |
| 12 | 2016 | 6 | |
| 13 | Gray Wolf ( Canis lupus ) dyad monthly association rates by demographic group. | 2015 | 16 |
| 14 | 2011 | 141 | |
| 15 | 2010 | 76 | |
| 16 | 2008 | 24 | |
| 17 | 2007 | 35 | |
| 18 | 2007 | 13 | |
| 19 | 1990 | 38 | |
| 20 | 1988 | 55 |
About Shannon M. Barber‐Meyer
Shannon M. Barber‐Meyer is a scholar working on Ecological Modeling, Small Animals and Ecology, having authored 50 papers that have together received 1.1k indexed citations. Recurring topics across this work include Wildlife Ecology and Conservation (28 papers), Rangeland and Wildlife Management (11 papers), Animal Behavior and Welfare Studies (10 papers), Marine animal studies overview (9 papers), Species Distribution and Climate Change (7 papers), Ecology and biodiversity studies (5 papers), Animal Ecology and Behavior Studies (4 papers) and Wildlife-Road Interactions and Conservation (4 papers). The work is most often cited by research in Ecology (877 citations), Ecological Modeling (121 citations) and Small Animals (153 citations). Shannon M. Barber‐Meyer has collaborated with scholars based in United States, India and Canada. Frequent co-authors include L. David Mech, P. J. White, Gerald L. Kooyman, Paul J. Ponganis, Adam Barlow, Colby Loucks, John D. Erb, Dominic J. Demma, Peyton T. Taylor and James K. Roche. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Clinical Microbiology Reviews.
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.