Chris Toney

676 total citations
20 papers, 465 citations indexed

About

Chris Toney is a scholar working on Global and Planetary Change, Nature and Landscape Conservation and Ecology. According to data from OpenAlex, Chris Toney has authored 20 papers receiving a total of 465 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Global and Planetary Change, 12 papers in Nature and Landscape Conservation and 10 papers in Ecology. Recurrent topics in Chris Toney's work include Fire effects on ecosystems (11 papers), Forest ecology and management (10 papers) and Species Distribution and Climate Change (6 papers). Chris Toney is often cited by papers focused on Fire effects on ecosystems (11 papers), Forest ecology and management (10 papers) and Species Distribution and Climate Change (6 papers). Chris Toney collaborates with scholars based in United States, Mexico and China. Chris Toney's co-authors include Karen Schleeweis, Todd A. Schroeder, Gretchen G. Moisen, Ellen E. Freeman, Chengquan Huang, Brian F. Walters, Christopher W. Woodall, Andrew J. Shirk, Kristen M. Waring and Sonja N. Oswalt and has published in prestigious journals such as Remote Sensing of Environment, Global Change Biology and Ecological Applications.

In The Last Decade

Chris Toney

20 papers receiving 438 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chris Toney United States 11 281 233 165 146 107 20 465
Michele Torresani Italy 14 226 0.8× 394 1.7× 172 1.0× 158 1.1× 214 2.0× 28 577
Lan Qie United Kingdom 7 197 0.7× 151 0.6× 275 1.7× 98 0.7× 70 0.7× 13 436
David C. Marvin United States 13 242 0.9× 230 1.0× 184 1.1× 113 0.8× 103 1.0× 13 491
Stephen R. Hardwick United Kingdom 4 283 1.0× 233 1.0× 184 1.1× 87 0.6× 120 1.1× 5 565
Yamina Micaela Rosas Argentina 13 198 0.7× 186 0.8× 152 0.9× 65 0.4× 71 0.7× 33 409
Chuping Wu China 9 249 0.9× 293 1.3× 323 2.0× 208 1.4× 59 0.6× 44 627
Robert Nuske Germany 8 170 0.6× 131 0.6× 210 1.3× 144 1.0× 45 0.4× 8 431
Klaus Ecker Switzerland 12 130 0.5× 264 1.1× 139 0.8× 130 0.9× 96 0.9× 26 413
Scott Pokswinski United States 15 416 1.5× 256 1.1× 306 1.9× 164 1.1× 44 0.4× 32 552
K. Gunia Finland 6 442 1.6× 161 0.7× 302 1.8× 121 0.8× 47 0.4× 7 660

Countries citing papers authored by Chris Toney

Since Specialization
Citations

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

Fields of papers citing papers by Chris Toney

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chris Toney. 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 Chris Toney. The network helps show where Chris Toney may publish in the future.

Co-authorship network of co-authors of Chris Toney

This figure shows the co-authorship network connecting the top 25 collaborators of Chris Toney. A scholar is included among the top collaborators of Chris Toney 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 Chris Toney. Chris Toney 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.
Frescino, Tracey S., et al.. (2023). ‘FIESTA': a forest inventory estimation and analysis R package. Ecography. 2023(7). 2 indexed citations
2.
Hansen, Andrew J., et al.. (2021). Is whitebark pine less sensitive to climate warming when climate tolerances of juveniles are considered?. Forest Ecology and Management. 493. 119221–119221. 4 indexed citations
3.
Schleeweis, Karen, Gretchen G. Moisen, Todd A. Schroeder, et al.. (2020). US National Maps Attributing Forest Change: 1986–2010. Forests. 11(6). 653–653. 34 indexed citations
4.
Shirk, Andrew J., Samuel A. Cushman, Kristen M. Waring, et al.. (2018). Southwestern white pine (Pinus strobiformis) species distribution models project a large range shift and contraction due to regional climatic changes. Forest Ecology and Management. 411. 176–186. 73 indexed citations
5.
Schroeder, Todd A., Karen Schleeweis, Gretchen G. Moisen, et al.. (2017). Testing a Landsat-based approach for mapping disturbance causality in U.S. forests. Remote Sensing of Environment. 195. 230–243. 57 indexed citations
6.
Moisen, Gretchen G., Mary C. Meyer, Todd A. Schroeder, et al.. (2016). Shape selection in Landsat time series: a tool for monitoring forest dynamics. Global Change Biology. 22(10). 3518–3528. 45 indexed citations
7.
Riemann, Rachel, Greg C. Liknes, Jarlath O’Neil‐Dunne, Chris Toney, & Tonya W. Lister. (2016). Comparative assessment of methods for estimating tree canopy cover across a rural-to-urban gradient in the mid-Atlantic region of the USA. Environmental Monitoring and Assessment. 188(5). 297–297. 14 indexed citations
8.
Keane, Robert E., et al.. (2015). Assessing three fuel classification systems and their maps using Forest Inventory and Analysis (FIA) surface fuel measurements. 73. 128–140. 1 indexed citations
9.
Nelson, Mark D., et al.. (2013). Changes in forest habitat classes under alternative climate and land-use change scenarios in the northeast and midwest, USA. BearWorks (Missouri State University). 5(2). 135–150. 3 indexed citations
10.
Woodall, Christopher W., Brian F. Walters, Sonja N. Oswalt, et al.. (2013). Biomass and carbon attributes of downed woody materials in forests of the United States. Forest Ecology and Management. 305. 48–59. 58 indexed citations
11.
Keane, Robert E., et al.. (2013). Evaluating the performance and mapping of three fuel classification systems using Forest Inventory and Analysis surface fuel measurements. Forest Ecology and Management. 305. 248–263. 29 indexed citations
12.
Toney, Chris, et al.. (2012). Development and applications of the LANDFIRE forest structure layers. 305–309. 2 indexed citations
13.
Nelson, Mark D., et al.. (2012). Relating FIA data to habitat classifications via tree-based models of canopy cover. 254–259. 2 indexed citations
14.
Toney, Chris, et al.. (2012). Assessing alternative measures of tree canopy cover: Photo-interpreted NAIP and ground-based estimates. 157. 209–215. 7 indexed citations
15.
Li, Ainong, Chengquan Huang, Guoqing Sun, et al.. (2011). Modeling the height of young forests regenerating from recent disturbances in Mississippi using Landsat and ICESat data. Remote Sensing of Environment. 115(8). 1837–1849. 38 indexed citations
16.
Cole, Kenneth L., Kirsten E. Ironside, Jon Eischeid, et al.. (2010). Past and ongoing shifts in Joshua tree distribution support future modeled range contraction. Ecological Applications. 21(1). 137–149. 54 indexed citations
17.
Cole, Kenneth D., Kirsten E. Ironside, Jon Eischeid, et al.. (2010). Past and ongoing shifts in Joshua tree support future modeled range contraction. Ecological Applications. 4258415954–4258415954. 1 indexed citations
18.
Toney, Chris & Matthew C. Reeves. (2009). Equations to Convert Compacted Crown Ratio to Uncompacted Crown Ratio for Trees in the Interior West. Western Journal of Applied Forestry. 24(2). 76–82. 17 indexed citations
19.
Toney, Chris, John D. Shaw, & Mark D. Nelson. (2009). A stem-map model for predicting tree canopy cover of Forest Inventory and Analysis (FIA) plots. 56. 21 indexed citations
20.
Toney, Chris, et al.. (2007). Use of FIA plot data in the LANDFIRE project. 77. 3 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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