David L.R. Affleck

2.0k total citations · 1 hit paper
51 papers, 1.4k citations indexed

About

David L.R. Affleck is a scholar working on Nature and Landscape Conservation, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, David L.R. Affleck has authored 51 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Nature and Landscape Conservation, 35 papers in Global and Planetary Change and 22 papers in Environmental Engineering. Recurrent topics in David L.R. Affleck's work include Forest ecology and management (29 papers), Remote Sensing and LiDAR Applications (20 papers) and Plant Water Relations and Carbon Dynamics (18 papers). David L.R. Affleck is often cited by papers focused on Forest ecology and management (29 papers), Remote Sensing and LiDAR Applications (20 papers) and Plant Water Relations and Carbon Dynamics (18 papers). David L.R. Affleck collaborates with scholars based in United States, Australia and Netherlands. David L.R. Affleck's co-authors include Marco A. Contreras, Woodam Chung, Zachary A. Holden, Marco Maneta, Alan Swanson, W. Matt Jolly, Jared W. Oyler, Russell A. Parsons, Hailemariam Temesgen and Charles H. Luce and has published in prestigious journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.

In The Last Decade

David L.R. Affleck

49 papers receiving 1.4k citations

Hit Papers

Decreasing fire season precipitation increased recent wes... 2018 2026 2020 2023 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David L.R. Affleck United States 18 951 745 349 348 190 51 1.4k
Markku Larjavaara Finland 19 797 0.8× 657 0.9× 228 0.7× 227 0.7× 200 1.1× 46 1.4k
Vincent Kint Belgium 22 856 0.9× 1.0k 1.4× 316 0.9× 270 0.8× 351 1.8× 46 1.6k
Don C. Bragg United States 15 869 0.9× 753 1.0× 159 0.5× 381 1.1× 297 1.6× 102 1.4k
Carlos A. González-Benecke United States 20 703 0.7× 716 1.0× 402 1.2× 210 0.6× 163 0.9× 60 1.2k
Andrés Bravo‐Oviedo Spain 28 1.2k 1.3× 1.4k 1.9× 357 1.0× 190 0.5× 283 1.5× 54 1.9k
Guy R. Larocque Canada 24 876 0.9× 910 1.2× 184 0.5× 252 0.7× 169 0.9× 82 1.5k
Frédéric Raulier Canada 25 1.6k 1.6× 1.3k 1.7× 371 1.1× 371 1.1× 548 2.9× 64 2.0k
Robinson Negrón‐Juárez United States 25 1.0k 1.1× 694 0.9× 239 0.7× 416 1.2× 289 1.5× 57 1.6k
Hannu Salminen Finland 19 1.0k 1.1× 793 1.1× 203 0.6× 233 0.7× 290 1.5× 56 1.4k
Ricardo Ruíz‐Peinado Spain 24 1.4k 1.4× 1.5k 2.0× 398 1.1× 242 0.7× 305 1.6× 58 2.1k

Countries citing papers authored by David L.R. Affleck

Since Specialization
Citations

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

Fields of papers citing papers by David L.R. Affleck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David L.R. Affleck. 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 David L.R. Affleck. The network helps show where David L.R. Affleck may publish in the future.

Co-authorship network of co-authors of David L.R. Affleck

This figure shows the co-authorship network connecting the top 25 collaborators of David L.R. Affleck. A scholar is included among the top collaborators of David L.R. Affleck 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 David L.R. Affleck. David L.R. Affleck 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.
Affleck, David L.R., et al.. (2025). Recognizing van Deusen’s mixed estimator for annual forest inventory as a linear mixed model. Canadian Journal of Forest Research. 55. 1–10.
3.
Kreider, Mark R., David L.R. Affleck, Philip E. Higuera, et al.. (2023). Mesic mixed-conifer forests are resilient to both historical high-severity fire and contemporary reburns in the US Northern Rocky Mountains. Forest Ecology and Management. 545. 121283–121283. 7 indexed citations
4.
MacFarlane, David W., Philip J. Radtke, Aaron R. Weiskittel, et al.. (2022). Testing a generalized leaf mass estimation method for diverse tree species and climates of the continental United States. Ecological Applications. 32(7). e2646–e2646. 2 indexed citations
5.
Hogland, John, et al.. (2019). Using Forest Inventory Data with Landsat 8 Imagery to Map Longleaf Pine Forest Characteristics in Georgia, USA. Remote Sensing. 11(15). 1803–1803. 11 indexed citations
6.
Affleck, David L.R., et al.. (2019). Tree spatial patterns modulate peak snow accumulation and snow disappearance. Forest Ecology and Management. 441. 9–19. 20 indexed citations
7.
Madani, Nima, John S. Kimball, Ashley P. Ballantyne, et al.. (2018). Future global productivity will be affected by plant trait response to climate. Scientific Reports. 8(1). 2870–2870. 109 indexed citations
8.
Keane, Robert E., et al.. (2018). Growth Response of Whitebark Pine (Pinus albicaulis Engelm) Regeneration to Thinning and Prescribed Burn Treatments. Forests. 9(6). 311–311. 13 indexed citations
9.
Madani, Nima, et al.. (2016). Remote Sensing Derived Fire Frequency, Soil Moisture and Ecosystem Productivity Explain Regional Movements in Emu over Australia. PLoS ONE. 11(1). e0147285–e0147285. 4 indexed citations
10.
Affleck, David L.R. & Ulises Diéguez‐Aranda. (2016). Additive Nonlinear Biomass Equations: A Likelihood-Based Approach. Forest Science. 62(2). 129–140. 41 indexed citations
11.
Affleck, David L.R., et al.. (2015). Conifer crown profile models from terrestrial laser scanning. Silva Fennica. 49(1). 23 indexed citations
12.
Temesgen, Hailemariam, David L.R. Affleck, Krishna Prasad Poudel, Andrew N. Gray, & John Sessions. (2015). A review of the challenges and opportunities in estimating above ground forest biomass using tree-level models. Scandinavian Journal of Forest Research. 1–10. 126 indexed citations
13.
Affleck, David L.R., et al.. (2015). Shelter provided by wood, facilitation, and density-dependent herbivory influence Great Basin bristlecone pine seedling survival. Forest Ecology and Management. 342. 76–83. 15 indexed citations
14.
Affleck, David L.R., et al.. (2014). Branch aggregation and crown allometry condition the precision of randomized branch sampling estimators of conifer crown mass. Canadian Journal of Forest Research. 44(5). 499–508. 4 indexed citations
15.
Nelson, Cara R., et al.. (2011). Assessing the performance of sampling designs for measuring the abundance of understory plants. Ecological Applications. 21(2). 452–464. 22 indexed citations
16.
Affleck, David L.R.. (2010). On the efficiency of line intersect distance sampling. Canadian Journal of Forest Research. 40(6). 1086–1094. 8 indexed citations
17.
Valentine, Harry T., David L.R. Affleck, & Timothy G. Grégoire. (2009). Systematic sampling of discrete and continuous populations: sample selection and the choice of estimator. Canadian Journal of Forest Research. 39(6). 1061–1068. 13 indexed citations
18.
Affleck, David L.R.. (2009). A comparative study of spatial analysis methods for forestry Nelder experiments. Open Collections. 5 indexed citations
19.
Valentine, Harry T., Mark J. Ducey, Jeffrey H. Gove, Adrian Lanz, & David L.R. Affleck. (2006). Corrections for Cluster-Plot Slop. Forest Science. 52(1). 55–66. 3 indexed citations
20.
Affleck, David L.R., Timothy G. Grégoire, & Harry T. Valentine. (2005). Design unbiased estimation in line intersect sampling using segmented transects. Environmental and Ecological Statistics. 12(2). 139–154. 21 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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