David W. MacFarlane

1.8k total citations
67 papers, 1.3k citations indexed

About

David W. MacFarlane is a scholar working on Nature and Landscape Conservation, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, David W. MacFarlane has authored 67 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Nature and Landscape Conservation, 42 papers in Global and Planetary Change and 24 papers in Environmental Engineering. Recurrent topics in David W. MacFarlane's work include Forest ecology and management (44 papers), Plant Water Relations and Carbon Dynamics (27 papers) and Remote Sensing and LiDAR Applications (22 papers). David W. MacFarlane is often cited by papers focused on Forest ecology and management (44 papers), Plant Water Relations and Carbon Dynamics (27 papers) and Remote Sensing and LiDAR Applications (22 papers). David W. MacFarlane collaborates with scholars based in United States, Brazil and United Kingdom. David W. MacFarlane's co-authors include Edwin J. Green, Brian Kane, Aaron R. Weiskittel, Harry T. Valentine, Harold E. Burkhart, Andrew O. Finley, Grant M. Domke, Richard K. Kobe, Christopher W. Woodall and Zhonglei Wang and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

David W. MacFarlane

65 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David W. MacFarlane United States 21 736 642 401 249 197 67 1.3k
José Javier Corral‐Rivas Mexico 22 864 1.2× 672 1.0× 431 1.1× 393 1.6× 88 0.4× 137 1.5k
Paula Soares Portugal 19 1.1k 1.4× 679 1.1× 668 1.7× 251 1.0× 203 1.0× 42 1.4k
Sebastian Hein Germany 22 808 1.1× 451 0.7× 201 0.5× 208 0.8× 240 1.2× 49 1.4k
Hugues Claessens Belgium 17 533 0.7× 490 0.8× 415 1.0× 512 2.1× 202 1.0× 98 1.3k
Mariola Sánchez‐González Spain 20 628 0.9× 511 0.8× 180 0.4× 122 0.5× 119 0.6× 55 991
David Auty United States 23 1.1k 1.6× 608 0.9× 693 1.7× 363 1.5× 321 1.6× 60 1.9k
John Turner Australia 23 1.1k 1.5× 729 1.1× 173 0.4× 439 1.8× 153 0.8× 75 1.8k
Marcos Barrio-Anta Spain 26 1.2k 1.7× 797 1.2× 599 1.5× 136 0.5× 95 0.5× 64 1.6k
Carlos Pedro Boëchat Soares Brazil 19 733 1.0× 347 0.5× 373 0.9× 237 1.0× 48 0.2× 111 1.2k
Fernando Castedo‐Dorado Spain 28 1.5k 2.0× 1.1k 1.7× 871 2.2× 222 0.9× 127 0.6× 74 1.9k

Countries citing papers authored by David W. MacFarlane

Since Specialization
Citations

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

Fields of papers citing papers by David W. MacFarlane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David W. MacFarlane. 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 W. MacFarlane. The network helps show where David W. MacFarlane may publish in the future.

Co-authorship network of co-authors of David W. MacFarlane

This figure shows the co-authorship network connecting the top 25 collaborators of David W. MacFarlane. A scholar is included among the top collaborators of David W. MacFarlane 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 W. MacFarlane. David W. MacFarlane 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.
MacFarlane, David W., et al.. (2025). A new approach for quantification of total above-ground heartwood and sapwood volume of trees. Trees. 39(1). 1 indexed citations
2.
3.
MacFarlane, David W., et al.. (2025). Controls on deforestation in the Brazilian Amazon: Explaining past success actions, new challenges and recommendations. Acta Amazonica. 55. 1 indexed citations
4.
MacFarlane, David W., et al.. (2025). rTwig: An R package to correct overestimated small branches and twigs in quantitative structure models of trees. Science of Remote Sensing. 12. 100284–100284.
5.
Verbeeck, Hans, Louise Terryn, Matheus Boni Vicari, et al.. (2024). The impact of leaf-wood separation algorithms on aboveground biomass estimation from terrestrial laser scanning. Remote Sensing of Environment. 318. 114581–114581. 6 indexed citations
6.
7.
MacFarlane, David W., et al.. (2024). Reducing tree volume overestimation in quantitative structure models using modeled branch topology and direct twig measurements. Forestry An International Journal of Forest Research. 98(3). 394–409. 4 indexed citations
8.
9.
10.
Stovall, Atticus, et al.. (2023). Comparing mobile and terrestrial laser scanning for measuring and modelling tree stem taper. Forestry An International Journal of Forest Research. 96(5). 705–717. 10 indexed citations
11.
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
12.
Finley, Andrew O., et al.. (2021). Over half of western United States' most abundant tree species in decline. Nature Communications. 12(1). 451–451. 53 indexed citations
13.
MacFarlane, David W., et al.. (2018). Trans‐species predictors of tree leaf mass. Ecological Applications. 29(1). e01817–e01817. 7 indexed citations
14.
McCann, Robert S., Joseph P. Messina, David W. MacFarlane, et al.. (2017). Explaining variation in adult Anopheles indoor resting abundance: the relative effects of larval habitat proximity and insecticide-treated bed net use. Malaria Journal. 16(1). 288–288. 13 indexed citations
15.
McCann, Robert S., Joseph P. Messina, David W. MacFarlane, et al.. (2014). Modeling larval malaria vector habitat locations using landscape features and cumulative precipitation measures. International Journal of Health Geographics. 13(1). 17–17. 27 indexed citations
16.
MacFarlane, David W., et al.. (2012). Comparing a new model-based method to fixed-area sampling for estimating the abundance of standing dead trees. Forestry An International Journal of Forest Research. 86(2). 231–239. 4 indexed citations
17.
18.
Finley, Andrew O., Sudipto Banerjee, & David W. MacFarlane. (2011). A Hierarchical Model for Quantifying Forest Variables Over Large Heterogeneous Landscapes With Uncertain Forest Areas. Journal of the American Statistical Association. 106(493). 31–48. 36 indexed citations
19.
MacFarlane, David W., et al.. (2000). Bayesian synthesis for quantifying uncertainty in predictions from process models. Tree Physiology. 20(5-6). 415–419. 18 indexed citations
20.
Stone, Peter, et al.. (1996). Pregnancy-associated arterio-venous malformations of the uterus. Journal of Obstetrics and Gynaecology. 16(2). 91–93. 2 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by José Javier Corral‐Rivas Breakdown of academic impact, for papers by Paula Soares Breakdown of academic impact, for papers by Sebastian Hein Breakdown of academic impact, for papers by Hugues Claessens Breakdown of academic impact, for papers by Mariola Sánchez‐González Breakdown of academic impact, for papers by David Auty Breakdown of academic impact, for papers by John Turner Breakdown of academic impact, for papers by Marcos Barrio-Anta Breakdown of academic impact, for papers by Carlos Pedro Boëchat Soares Breakdown of academic impact, for papers by Fernando Castedo‐Dorado
Rankless by CCL
2026