Dean W. Coble

1.7k total citations
70 papers, 1.1k citations indexed

About

Dean W. Coble is a scholar working on Nature and Landscape Conservation, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Dean W. Coble has authored 70 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Nature and Landscape Conservation, 26 papers in Global and Planetary Change and 17 papers in Environmental Engineering. Recurrent topics in Dean W. Coble's work include Forest ecology and management (32 papers), Remote Sensing and LiDAR Applications (17 papers) and Forest Management and Policy (17 papers). Dean W. Coble is often cited by papers focused on Forest ecology and management (32 papers), Remote Sensing and LiDAR Applications (17 papers) and Forest Management and Policy (17 papers). Dean W. Coble collaborates with scholars based in United States, United Kingdom and South Korea. Dean W. Coble's co-authors include Penelope Latham, Hans R. Zuuring, Gregory P. Van Stavern, Bliss E. O’Bryhim, Nathan H. Kung, Rajendra S. Apte, Chengjie Xiong, Kelsey S. Milner, Young‐Jin Lee and John C. Morris and has published in prestigious journals such as Brain, Neurology and Bioresource Technology.

In The Last Decade

Dean W. Coble

69 papers receiving 1.1k citations

Peers

Dean W. Coble
David Maxwell United Kingdom
George W. Brown United States
James C. White United States
Keith R. Edwards United States
Caroline Sullivan United States
James M. Long United States
Steven G. Nelson United States
Dean W. Coble
Citations per year, relative to Dean W. Coble Dean W. Coble (= 1×) peers Shi-Dong Chen

Countries citing papers authored by Dean W. Coble

Since Specialization
Citations

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

Fields of papers citing papers by Dean W. Coble

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dean W. Coble

This figure shows the co-authorship network connecting the top 25 collaborators of Dean W. Coble. A scholar is included among the top collaborators of Dean W. Coble 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 W. Coble. Dean W. Coble 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.
Weng, Yuhui, et al.. (2024). Evaluating Stand Density Measures for Regulating Mid-Rotation Loblolly Pine Plantation Density in the Western Gulf, USA. Sustainability. 16(21). 9452–9452. 1 indexed citations
2.
Weng, Yuhui, et al.. (2024). Gains from one-time mid-rotation thinning on loblolly pine plantations in the Western Gulf region. New Forests. 56(1). 1 indexed citations
3.
Thibodeaux, Suzanne R., Dean W. Coble, Magali J. Fontaine, et al.. (2023). Assessing deviations for HPCs obtained during COVID‐19 (ADHOC): Evaluating impact of the COVID‐19 pandemic on cellular therapy products and processes, the BEST collaborative study. Transfusion. 63(4). 782–790. 1 indexed citations
4.
Bollinger, Rebecca M., Matthew J. Gabel, Dean W. Coble, et al.. (2023). Retention of Study Partners in Longitudinal Studies of Alzheimer Disease. Journal of Alzheimer s Disease. 94(1). 189–199. 2 indexed citations
5.
Long, Justin M., Dean W. Coble, Chengjie Xiong, et al.. (2022). Preclinical Alzheimer’s disease biomarkers accurately predict cognitive and neuropathological outcomes. Brain. 145(12). 4506–4518. 23 indexed citations
6.
Farrish, Kenneth W., et al.. (2021). Potential of several native and introduced warm season grasses as components of Silvopastures in the Southeastern United States. Agroforestry Systems. 95(8). 1735–1744. 2 indexed citations
7.
Patel, Tirth K., Xuefeng Gao, Baogang Xu, et al.. (2019). Dural lymphatics regulate clearance of extracellular tau from the CNS. Molecular Neurodegeneration. 14(1). 11–11. 156 indexed citations
8.
Snider, B. Joy, Dean W. Coble, Chengjie Xiong, et al.. (2018). Effect of apolipoprotein E4 on clinical, neuroimaging, and biomarker measures in noncarrier participants in the Dominantly Inherited Alzheimer Network. Neurobiology of Aging. 75. 42–50. 32 indexed citations
9.
Stavern, Gregory Van, Rajendra S. Apte, Nathan H. Kung, Bliss E. O’Bryhim, & Dean W. Coble. (2018). Optical Coherence Tomography Angiography in pre-clinical Alzheimer’s disease (S16.001). Neurology. 90(15_supplement). 1 indexed citations
10.
O’Bryhim, Bliss E., Rajendra S. Apte, Nathan H. Kung, Dean W. Coble, & Gregory P. Van Stavern. (2018). Association of Preclinical Alzheimer Disease With Optical Coherence Tomographic Angiography Findings. JAMA Ophthalmology. 136(11). 1242–1242. 180 indexed citations
11.
Coble, Dean W., John Paul McTague, & Yuhui Weng. (2017). A WHOLE-STAND GROWTH AND YIELD MODEL FOR INTENSIVELY AND EXTENSIVELY MANAGED LOBLOLLY PINE PLANTATIONS IN EAST TEXAS PRIOR TO FIRST THIN. Index of Texas Archaeology Open Access Grey Literature from the Lone Star State. 3 indexed citations
12.
Kulhavy, David, et al.. (2017). Service Learning for the Port Jefferson History and Nature Center: Senior Capstone Forestry Course. 9(2). 67–79. 6 indexed citations
13.
Coble, Dean W., et al.. (2015). Loblolly Pine Growth Patterns on Reclaimed Mineland: Allometry, Biomass, and Volume. Forests. 6(10). 3547–3581. 7 indexed citations
14.
Hung, I‐Kuai, et al.. (2008). A Standardized, Cost-Effective, and Repeatable Remote Sensing Methodology to Quantify Forested Resources in Texas. Southern Journal of Applied Forestry. 32(1). 12–20. 2 indexed citations
15.
Bataineh, Mohammad, et al.. (2007). Plant Communities Associated with Pinus Ponderosa Forests in the Sky Islands of the Davis Mountains, Texas1. The Journal of the Torrey Botanical Society. 134(4). 468–478. 10 indexed citations
16.
Lee, Young‐Jin & Dean W. Coble. (2002). Modeling Survival for Unthinned Slash Pine Plantations in East Texas Under the Influence of Non-Planted Tree Basal Area and Incidence of Fusiform Rust. Index of Texas Archaeology Open Access Grey Literature from the Lone Star State. 54(4). 325–338. 4 indexed citations
17.
Lee, Young‐Jin & Dean W. Coble. (2002). A survival model for unthinned loblolly pine plantations that incorporates non-planted tree competition, site quality, and incidence of fusiform rust. Bioresource Technology. 85(3). 301–308. 6 indexed citations
18.
Coble, Dean W. & Harry V. Wiant. (2000). Centroid Method: Comparison of Simple and Complex Proxy Tree Taper Functions. Forest Science. 46(4). 473–477. 2 indexed citations
19.
Coble, Dean W.. (1997). Trends in above and below-ground production of trees and non-tree vegetation on contrasting aspects in western Montana. The Mathematics Enthusiast. 3 indexed citations
20.
Coble, Dean W., et al.. (1991). Height growth of young Pacific silver fir and noble fir established on clearcuts in the Pacific silver fir zone of western Washington. Canadian Journal of Forest Research. 21(8). 1213–1221. 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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