Matthew D. Cameron

510 total citations
32 papers, 327 citations indexed

About

Matthew D. Cameron is a scholar working on Ecology, Ecological Modeling and General Health Professions. According to data from OpenAlex, Matthew D. Cameron has authored 32 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Ecology, 6 papers in Ecological Modeling and 5 papers in General Health Professions. Recurrent topics in Matthew D. Cameron's work include Wildlife Ecology and Conservation (22 papers), Rangeland and Wildlife Management (10 papers) and Marine animal studies overview (6 papers). Matthew D. Cameron is often cited by papers focused on Wildlife Ecology and Conservation (22 papers), Rangeland and Wildlife Management (10 papers) and Marine animal studies overview (6 papers). Matthew D. Cameron collaborates with scholars based in United States, Australia and Germany. Matthew D. Cameron's co-authors include Kyle Joly, Mathew S. Sorum, Eliezer Gurarie, Knut Kielland, Greg A. Breed, David D. Gustine, Grant V. Hilderbrand, Mark Hebblewhite, Bayarbaatar Buuveibaatar and Kirk A. Olson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Global Change Biology.

In The Last Decade

Matthew D. Cameron

28 papers receiving 322 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matthew D. Cameron United States 9 256 63 50 47 41 32 327
Mathew S. Sorum United States 9 235 0.9× 37 0.6× 47 0.9× 35 0.7× 20 0.5× 20 277
Larissa T. Beumer Denmark 14 214 0.8× 39 0.6× 54 1.1× 69 1.5× 47 1.1× 24 318
Bridget L. Borg United States 10 285 1.1× 34 0.5× 41 0.8× 42 0.9× 18 0.4× 14 332
Natalia Sokolova Russia 10 203 0.8× 60 1.0× 67 1.3× 26 0.6× 63 1.5× 40 326
Troy Hegel Canada 12 289 1.1× 41 0.7× 63 1.3× 22 0.5× 29 0.7× 23 346
Eirin Bjørkvoll Norway 7 233 0.9× 70 1.1× 47 0.9× 49 1.0× 37 0.9× 9 319
Robert D. Otto Canada 9 290 1.1× 93 1.5× 48 1.0× 22 0.5× 25 0.6× 14 349
Allicia Kelly Canada 10 227 0.9× 55 0.9× 55 1.1× 21 0.4× 40 1.0× 20 299
Maël Le Corre Canada 10 178 0.7× 43 0.7× 44 0.9× 26 0.6× 25 0.6× 16 255
Nandintsetseg Dejid Germany 7 254 1.0× 35 0.6× 40 0.8× 24 0.5× 8 0.2× 16 329

Countries citing papers authored by Matthew D. Cameron

Since Specialization
Citations

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

Fields of papers citing papers by Matthew D. Cameron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew D. Cameron. 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 Matthew D. Cameron. The network helps show where Matthew D. Cameron may publish in the future.

Co-authorship network of co-authors of Matthew D. Cameron

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew D. Cameron. A scholar is included among the top collaborators of Matthew D. Cameron 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 Matthew D. Cameron. Matthew D. Cameron 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.
Bolst, David, Matthew D. Cameron, Stéphanie Corde, et al.. (2025). Comparison of Deep Learning Models for fast and accurate dose map prediction in Microbeam Radiation Therapy. Physica Medica. 136. 105012–105012.
2.
Engels, E., Helen B. Forrester, Verdiana Trappetti, et al.. (2025). Is Ultrahigh Dose Rate Critical for the Effectiveness of Microbeam Radiation Therapy in a Broad-Beam Combined Treatment?. Advances in Radiation Oncology. 11(2). 101949–101949.
3.
Cameron, Matthew D., E. Engels, Cristian Fernández-Palomo, et al.. (2025). Treatment planning for in vivo multi-fraction, multi-port, multi-modal Synchrotron Radiotherapy. Physica Medica. 136. 105029–105029. 1 indexed citations
4.
Joly, Kyle, et al.. (2025). Barrier impermeability is associated with migratory ungulate survival rates. Scientific Reports. 16(1). 152–152.
5.
Joly, Kyle, et al.. (2025). Behavioral responses of migratory caribou to semi-permeable roads in Arctic Alaska. Scientific Reports. 15(1). 24712–24712. 1 indexed citations
6.
Joly, Kyle, Matthew D. Cameron, & Robert G. White. (2024). Behavioral adaptation to seasonal resource scarcity by Caribou (Rangifer tarandus) and its role in partial migration. Journal of Mammalogy. 106(1). 96–104. 3 indexed citations
7.
Engels, E., Sarah Vogel, Dave Potter, et al.. (2024). Microbeam Radiation Therapy Bio-Dosimetry Enhanced by Novel Radiosensitiser Combinations in the Treatment of Brain Cancer. Cancers. 16(24). 4231–4231.
8.
Gurarie, Eliezer, et al.. (2024). Evidence for an Adaptive, Large‐Scale Range Shift in a Long‐Distance Terrestrial Migrant. Global Change Biology. 30(11). e17589–e17589. 5 indexed citations
9.
Cameron, Matthew D., Kyle Joly, Jan Adamczewski, et al.. (2023). Continental synchrony and local responses: Climatic effects on spatiotemporal patterns of calving in a social ungulate. Ecosphere. 14(1). 8 indexed citations
10.
Sorum, Mathew S., Matthew D. Cameron, George K. Sage, et al.. (2023). Pronounced brown bear aggregation along anadromous streams in interior Alaska. Wildlife Biology. 2023(3). 4 indexed citations
11.
Cameron, Matthew D., Stéphanie Corde, E. Engels, et al.. (2023). Accurate and Fast Deep Learning Dose Prediction for a Preclinical Microbeam Radiation Therapy Study Using Low-Statistics Monte Carlo Simulations. Cancers. 15(7). 2137–2137. 5 indexed citations
12.
Schmidt, Joshua H., et al.. (2022). Bayesian spatial modeling of moose count data: increasing estimator efficiency and exploring ecological hypotheses. Journal of Wildlife Management. 86(5). 2 indexed citations
13.
Cameron, Matthew D., et al.. (2021). Mechanistic movement models identify continuously updated autumn migration cues in Arctic caribou. Movement Ecology. 9(1). 54–54. 7 indexed citations
14.
Joly, Kyle, et al.. (2021). Seasonal patterns of spatial fidelity and temporal consistency in the distribution and movements of a migratory ungulate. Ecology and Evolution. 11(12). 8183–8200. 24 indexed citations
15.
Cameron, Matthew D., et al.. (2021). Simulation modeling accounts for uncertainty while quantifying ecological effects of development alternatives. Ecosphere. 12(5). 3 indexed citations
16.
Cameron, Matthew D., Grant V. Hilderbrand, Kyle Joly, et al.. (2020). Body size plasticity in North American black and brown bears. Ecosphere. 11(8). 7 indexed citations
17.
Joly, Kyle, Eliezer Gurarie, Mathew S. Sorum, et al.. (2019). Longest terrestrial migrations and movements around the world. Scientific Reports. 9(1). 15333–15333. 102 indexed citations
18.
Sorum, Mathew S., et al.. (2019). Den‐site characteristics and selection by brown bears (Ursus arctos) in the central Brooks Range of Alaska. Ecosphere. 10(8). 14 indexed citations
19.
Hilderbrand, Grant V., David D. Gustine, Buck A. Mangipane, et al.. (2018). Plasticity in physiological condition of female brown bears across diverse ecosystems. Polar Biology. 41(4). 773–780. 13 indexed citations
20.
Joly, Kyle, Mathew S. Sorum, & Matthew D. Cameron. (2018). Denning Ecology of Wolves in East-Central Alaska, 1993–2017. ARCTIC. 71(4). 444–455. 6 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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