Erin E. Peterson

4.3k total citations
68 papers, 3.1k citations indexed

About

Erin E. Peterson is a scholar working on Nature and Landscape Conservation, Ecology and Water Science and Technology. According to data from OpenAlex, Erin E. Peterson has authored 68 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Nature and Landscape Conservation, 29 papers in Ecology and 25 papers in Water Science and Technology. Recurrent topics in Erin E. Peterson's work include Fish Ecology and Management Studies (26 papers), Hydrology and Watershed Management Studies (20 papers) and Soil and Water Nutrient Dynamics (14 papers). Erin E. Peterson is often cited by papers focused on Fish Ecology and Management Studies (26 papers), Hydrology and Watershed Management Studies (20 papers) and Soil and Water Nutrient Dynamics (14 papers). Erin E. Peterson collaborates with scholars based in Australia, United States and France. Erin E. Peterson's co-authors include Jay M. Ver Hoef, David M. Theobald, Daniel J. Isaak, David E. Nagel, Dona L. Horan, Charles H. Luce, Gwynne L. Chandler, Sharon Parkes, Seth J. Wenger and Marie‐Josée Fortin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of the American Statistical Association.

In The Last Decade

Erin E. Peterson

65 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Erin E. Peterson Australia 26 1.6k 1.5k 1.3k 559 521 68 3.1k
Anthony R. Olsen United States 27 1.2k 0.8× 1.7k 1.1× 670 0.5× 413 0.7× 782 1.5× 84 3.9k
Matthew R. Hipsey Australia 35 660 0.4× 1.1k 0.7× 1.6k 1.2× 648 1.2× 930 1.8× 150 3.9k
W. Scott Overton United States 20 924 0.6× 1.2k 0.8× 285 0.2× 271 0.5× 524 1.0× 48 2.8k
Li Wen Australia 27 489 0.3× 1.2k 0.8× 639 0.5× 204 0.4× 994 1.9× 144 2.3k
Juan Pablo Guerschman Australia 32 505 0.3× 1.7k 1.1× 628 0.5× 946 1.7× 2.0k 3.8× 65 3.7k
Giuseppe Amatulli United States 20 487 0.3× 648 0.4× 337 0.3× 255 0.5× 940 1.8× 37 2.2k
Richard Aspinall United States 26 703 0.4× 1.2k 0.7× 224 0.2× 371 0.7× 943 1.8× 61 2.7k
Terry L. Sohl United States 28 367 0.2× 1.2k 0.8× 376 0.3× 424 0.8× 1.9k 3.6× 61 2.8k
Randolph H. Wynne United States 34 2.1k 1.3× 2.6k 1.7× 259 0.2× 3.0k 5.4× 1.8k 3.4× 125 6.0k
Milan Kilibarda Serbia 16 492 0.3× 835 0.5× 519 0.4× 1.3k 2.3× 1.3k 2.5× 32 4.0k

Countries citing papers authored by Erin E. Peterson

Since Specialization
Citations

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

Fields of papers citing papers by Erin E. Peterson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Erin E. Peterson. 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 Erin E. Peterson. The network helps show where Erin E. Peterson may publish in the future.

Co-authorship network of co-authors of Erin E. Peterson

This figure shows the co-authorship network connecting the top 25 collaborators of Erin E. Peterson. A scholar is included among the top collaborators of Erin E. Peterson 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 Erin E. Peterson. Erin E. Peterson 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.
Steel, E. Ashley, Oliver Stoner, S. Simon, et al.. (2025). Global wood fuel production estimates and implications. Nature Communications. 16(1). 6227–6227.
2.
3.
Peterson, Erin E., et al.. (2024). SSN2: The next generation of spatial stream networkmodeling in R. The Journal of Open Source Software. 9(99). 6389–6389. 5 indexed citations
4.
Santos–Fernández, Edgar, Jay M. Ver Hoef, Erin E. Peterson, et al.. (2024). Unsupervised Anomaly Detection in Spatio‐Temporal Stream Network Sensor Data. Water Resources Research. 60(11). 3 indexed citations
5.
Santos–Fernández, Edgar, et al.. (2023). Increasing Trust in New Data Sources: Crowdsourcing Image Classification for Ecology. International Statistical Review. 92(1). 43–61. 2 indexed citations
6.
Liquet, Benoît, Kerrie Mengersen, Erin E. Peterson, et al.. (2023). Understanding links between water-quality variables and nitrate concentration in freshwater streams using high frequency sensor data. PLoS ONE. 18(6). e0287640–e0287640. 8 indexed citations
7.
Santos–Fernández, Edgar, Jay M. Ver Hoef, James McGree, et al.. (2023). SSNbayes: An R Package for Bayesian Spatio-Temporal Modelling on Stream Networks. The R Journal. 15(3). 26–58. 3 indexed citations
8.
Hoef, Jay M. Ver, et al.. (2023). Indexing and partitioning the spatial linear model for large data sets. PLoS ONE. 18(11). e0291906–e0291906. 2 indexed citations
9.
Liquet, Benoît, Jeremy B. Jones, Kerrie Mengersen, et al.. (2021). Reconstructing Missing and Anomalous Data Collected from High-Frequency In-Situ Sensors in Fresh Waters. International Journal of Environmental Research and Public Health. 18(23). 12803–12803. 6 indexed citations
10.
Vercelloni, Julie, Benoît Liquet, Emma Kennedy, et al.. (2020). Forecasting intensifying disturbance effects on coral reefs. Global Change Biology. 26(5). 2785–2797. 50 indexed citations
11.
Leigh, Catherine, Rob J. Hyndman, Sevvandi Kandanaarachchi, et al.. (2019). A framework for automated anomaly detection in high frequency water-quality data from in situ sensors. The Science of The Total Environment. 664. 885–898. 83 indexed citations
12.
Leigh, Catherine, Sevvandi Kandanaarachchi, James McGree, et al.. (2019). Predicting sediment and nutrient concentrations from high-frequency water-quality data. PLoS ONE. 14(8). e0215503–e0215503. 36 indexed citations
13.
Vercelloni, Julie, Samuel Clifford, M. Julian Caley, et al.. (2018). Using virtual reality to estimate aesthetic values of coral reefs. Royal Society Open Science. 5(4). 172226–172226. 17 indexed citations
14.
15.
Sheldon, Fran, et al.. (2012). Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score. Ecological Applications. 22(8). 2188–2203. 79 indexed citations
16.
Ruesch, Aaron S., Christian E. Torgersen, Joshua J. Lawler, et al.. (2012). Projected Climate‐Induced Habitat Loss for Salmonids in the John Day River Network, Oregon, U.S.A.. Conservation Biology. 26(5). 873–882. 77 indexed citations
17.
Isaak, Daniel J., Charles H. Luce, Bruce E. Rieman, et al.. (2010). Effects of climate change and wildfire on stream temperatures and salmonid thermal habitat in a mountain river network. Ecological Applications. 20(5). 1350–1371. 333 indexed citations
18.
Peterson, Erin E. & Jay M. Ver Hoef. (2010). A mixed‐model moving‐average approach to geostatistical modeling in stream networks. Ecology. 91(3). 644–651. 124 indexed citations
19.
Kuhnert, Petra, et al.. (2007). Review of existing approaches used to develop integrated report card frameworks (IRCF) and their relevance to catchments draining to the Great Barrier Reef. QUT ePrints (Queensland University of Technology). 2 indexed citations
20.
Peterson, Erin E., et al.. (2006). Patterns of Spatial Autocorrelation in Stream Water Chemistry. Environmental Monitoring and Assessment. 121(1-3). 571–596. 68 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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