Dean F. Meason

819 total citations
42 papers, 586 citations indexed

About

Dean F. Meason is a scholar working on Global and Planetary Change, Nature and Landscape Conservation and Soil Science. According to data from OpenAlex, Dean F. Meason has authored 42 papers receiving a total of 586 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Global and Planetary Change, 19 papers in Nature and Landscape Conservation and 11 papers in Soil Science. Recurrent topics in Dean F. Meason's work include Forest ecology and management (18 papers), Plant Water Relations and Carbon Dynamics (14 papers) and Soil Carbon and Nitrogen Dynamics (9 papers). Dean F. Meason is often cited by papers focused on Forest ecology and management (18 papers), Plant Water Relations and Carbon Dynamics (14 papers) and Soil Carbon and Nitrogen Dynamics (9 papers). Dean F. Meason collaborates with scholars based in New Zealand, United States and Australia. Dean F. Meason's co-authors include Travis Idol, Serajis Salekin, Justin Morgenroth, Euan G. Mason, Jianming Xue, Peter W. Clinton, W. L. Mason, Paul G. Scowcroft, James B. Friday and Jean‐Christophe Domec and has published in prestigious journals such as Journal of Experimental Botany, Journal of Hydrology and Soil Science Society of America Journal.

In The Last Decade

Dean F. Meason

41 papers receiving 571 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dean F. Meason New Zealand 15 242 217 165 137 77 42 586
Viliam Pichler Slovakia 16 238 1.0× 179 0.8× 155 0.9× 111 0.8× 104 1.4× 47 672
Partap K. Khanna Australia 10 220 0.9× 250 1.2× 113 0.7× 249 1.8× 77 1.0× 10 636
Kevin Black Ireland 15 342 1.4× 204 0.9× 263 1.6× 131 1.0× 79 1.0× 41 742
Gregorio Ángeles–Pérez Mexico 13 295 1.2× 401 1.8× 112 0.7× 94 0.7× 145 1.9× 100 714
Yanting Hu China 16 358 1.5× 172 0.8× 174 1.1× 250 1.8× 122 1.6× 37 705
Seyed Mohsen Hosseini Iran 17 253 1.0× 228 1.1× 178 1.1× 152 1.1× 74 1.0× 62 761
Marco Bascietto Italy 11 263 1.1× 182 0.8× 155 0.9× 129 0.9× 56 0.7× 23 540
Christine Fischer Germany 10 236 1.0× 241 1.1× 179 1.1× 286 2.1× 39 0.5× 14 697
Guangyi Zhou China 11 188 0.8× 125 0.6× 90 0.5× 119 0.9× 33 0.4× 38 435
Sylvia Mota de Oliveira Netherlands 14 173 0.7× 143 0.7× 208 1.3× 70 0.5× 68 0.9× 33 833

Countries citing papers authored by Dean F. Meason

Since Specialization
Citations

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

Fields of papers citing papers by Dean F. Meason

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dean F. Meason. 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 Dean F. Meason. The network helps show where Dean F. Meason may publish in the future.

Co-authorship network of co-authors of Dean F. Meason

This figure shows the co-authorship network connecting the top 25 collaborators of Dean F. Meason. A scholar is included among the top collaborators of Dean F. Meason 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 Dean F. Meason. Dean F. Meason 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.
Villamor, Grace B., et al.. (2025). Trees and water: A survey of the perception and decisions of landowners in New Zealand. People and Nature. 7(4). 828–846. 2 indexed citations
2.
Salekin, Serajis, et al.. (2025). A comparative study of four deep learning algorithms for predicting tree stem radius measured by dendrometer: A case study. Ecological Informatics. 86. 103014–103014. 3 indexed citations
3.
4.
Meason, Dean F., et al.. (2024). Time stability of soil volumetric water content and its optimal sampling design in contrasting forest catchments. Journal of Hydrology. 636. 131344–131344. 1 indexed citations
5.
Salekin, Serajis, Yvette L. Dickinson, Mark Bloomberg, & Dean F. Meason. (2024). Carbon sequestration potential of plantation forests in New Zealand - no single tree species is universally best. Carbon Balance and Management. 19(1). 11–11. 2 indexed citations
6.
Salekin, Serajis, et al.. (2023). Uncertainty in primary and secondary topographic attributes caused by digital elevation model spatial resolution. CATENA. 231. 107320–107320. 7 indexed citations
7.
White, Donald, Daniel S. Mendham, Francisco Balocchi, et al.. (2022). Is the reputation of Eucalyptus plantations for using more water than Pinus plantations justified?. Hydrology and earth system sciences. 26(20). 5357–5371. 14 indexed citations
8.
Xue, Jianming, Dean F. Meason, Jaroslav Klápště, et al.. (2022). Genetic Variation in Drought-Tolerance Traits and Their Relationships to Growth in Pinus radiata D. Don Under Water Stress. Frontiers in Plant Science. 12. 766803–766803. 11 indexed citations
9.
Andreadis, Konstantinos M., et al.. (2022). Evaluation of Multiscale SMAP Soil Moisture Products in Forested Environments. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 6 indexed citations
10.
Salekin, Serajis, Mark Bloomberg, Justin Morgenroth, Dean F. Meason, & Euan G. Mason. (2021). Within-site drivers for soil nutrient variability in plantation forests: A case study from dry sub-humid New Zealand. CATENA. 200. 105149–105149. 12 indexed citations
11.
Xue, Jianming, Dean F. Meason, Jaroslav Klápště, et al.. (2021). Data for Genetic Variation in Drought-Tolerance Traits and Their Relationships to Growth in Pinus radiata D. Don Under Water Stress. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
12.
Klápště, Jaroslav, et al.. (2020). Genotype-by-environment interaction in coast redwood outside natural distribution - search for environmental cues. BMC Genetics. 21(1). 15–15. 8 indexed citations
13.
Kusbach, Antonín, Jan Šebesta, Dean F. Meason, et al.. (2020). Site-specific approach to growth assessment and cultivation of teak (Tectona grandis) in Nicaraguan dry tropics. Forest Ecology and Management. 480. 118658–118658. 3 indexed citations
14.
Meason, Dean F., Amanda Matson, Brenda R. Baillie, et al.. (2020). Forest Flows-Real Time Monitoring of Water Quantity and Quality Spatio-Temporal Dynamics in Planted Forests. 4626–4629. 3 indexed citations
15.
Nanayakkara, Bernadette, Alan Dickson, & Dean F. Meason. (2019). Xylogenesis of Pinus radiata D. Don growing in New Zealand. Annals of Forest Science. 76(3). 15 indexed citations
16.
Gallart, Marta, Karen L. Adair, Jonathan Love, et al.. (2018). Genotypic variation in Pinus radiata responses to nitrogen source are related to changes in the root microbiome. FEMS Microbiology Ecology. 94(6). 8 indexed citations
17.
Gallart, Marta, Karen L. Adair, Jonathan Love, et al.. (2017). Host Genotype and Nitrogen Form Shape the Root Microbiome of Pinus radiata. Microbial Ecology. 75(2). 419–433. 36 indexed citations
18.
19.
Dickson, Alan, et al.. (2016). Fluorescence imaging of cambial zones to study wood formation in Pinus radiata D. Don.. Trees. 31(2). 479–490. 26 indexed citations
20.
Idol, Travis, Patrick J. Baker, & Dean F. Meason. (2007). Indicators of forest ecosystem productivity and nutrient status across precipitation and temperature gradients in Hawaii. Journal of Tropical Ecology. 23(6). 693–704. 19 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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