Jarad Niemi
- Molecular Biology
- Plant Science
- Ecology, Evolution, Behavior and Systematics top 10%
- Ecology
- Environmental Engineering top 10%
- Co-authors
- Lisa A. SchulteMatthew J. HelmersCheemeng TanLingchong YouMatthew E. O’NealJohn TyndallMike WestMichael J Simmons
- Topics
- Chromosomal and Genetic Variations (5 papers)Data-Driven Disease Surveillance (4 papers)CRISPR and Genetic Engineering (3 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Statistical AssociationPLoS ONE
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Jarad Niemi
40 papers receiving 808 citations
Hit Papers
Peers
Comparison fields: 5 of 112
- Molecular Biology 232
- Plant Science 166
- Ecology, Evolution, Behavior and Systematics 101
- Ecology 99
- Environmental Engineering 90
Countries citing papers authored by Jarad Niemi
This map shows the geographic impact of Jarad Niemi'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 Jarad Niemi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jarad Niemi more than expected).
Fields of papers citing papers by Jarad Niemi
This network shows the impact of papers produced by Jarad Niemi. 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 Jarad Niemi. The network helps show where Jarad Niemi may publish in the future.
Co-authorship network of co-authors of Jarad Niemi
This figure shows the co-authorship network connecting the top 25 collaborators of Jarad Niemi. A scholar is included among the top collaborators of Jarad Niemi 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 Jarad Niemi. Jarad Niemi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 4 | |
| 5 | 5 | |
| 6 | 14 | |
| 7 | 2 | |
| 8 | 1 | |
| 9 | Prairie strips improve biodiversity and the delivery of multiple ecosystem services from corn–soybean croplandsbreakdown → | 253 |
| 10 | 25 | |
| 11 | 7 | |
| 12 | 3 | |
| 13 | 20 | |
| 14 | 35 | |
| 15 | 3 | |
| 16 | 10 | |
| 17 | 75 | |
| 18 | 0 | |
| 19 | 30 | |
| 20 | 23 |
About Jarad Niemi
Jarad Niemi is a scholar working on Statistics and Probability, Modeling and Simulation and Soil Science, having authored 43 papers that have together received 839 indexed citations. Recurring topics across this work include Chromosomal and Genetic Variations (5 papers), Data-Driven Disease Surveillance (4 papers) and CRISPR and Genetic Engineering (3 papers). The work is most often cited by research in Biophysics (65 citations), Soil Science (64 citations) and Agronomy and Crop Science (67 citations). Jarad Niemi has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Lisa A. Schulte, Matthew J. Helmers, Cheemeng Tan, Lingchong You, Matthew E. O’Neal, John Tyndall, Mike West, Michael J Simmons, David James and Mark D. Tomer. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Statistical Association and PLoS ONE.
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.