Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Changes in assembly processes in soil bacterial communities following a wildfire disturbance
2013351 citationsSteven K. Schmidt, Mark Williams et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Mark Williams'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 Mark Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Williams more than expected).
This network shows the impact of papers produced by Mark Williams. 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 Mark Williams. The network helps show where Mark Williams may publish in the future.
Co-authorship network of co-authors of Mark Williams
This figure shows the co-authorship network connecting the top 25 collaborators of Mark Williams.
A scholar is included among the top collaborators of Mark Williams 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 Mark Williams. Mark Williams is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Knowles, John F., Peter D. Blanken, & Mark Williams. (2014). Variation in Soil Respiration Across an Alpine Soil Moisture and Vegetation Community Gradient at Niwot Ridge, Colorado. 2014 AGU Fall Meeting. 2014.1 indexed citations
6.
Ray, Chris, et al.. (2013). Connecting Long Term Ecological Research to the Classroom: A Partnership Between ScienceLIVE and Niwot Ridge LTER. AGU Fall Meeting Abstracts. 2013.1 indexed citations
7.
Wilson, Alana, Mark Williams, Adina Racoviteanu, et al.. (2012). Using geochemical and isotopic chemistry to evaluate source water contributions to the hydrology of two high-elevation basins in the Himalayas of Nepal. AGU Fall Meeting Abstracts. 2012.1 indexed citations
8.
Driscoll, Jessica M., T. Meixner, N. P. Molotch, et al.. (2011). Inverse Geochemical Reaction Path Modelling and the Impact of Climate Change on Hydrologic Structure in Snowmelt-Dominated Catchments in the Southwestern USA. AGUFM. 2011.1 indexed citations
9.
Williams, Mark, et al.. (2010). Potential Impacts of Climate Change or U.S. Wastach Range Ski Areas: Projections for Park City Mountain Resort in 2030, 2050, and 2075. 436–443.2 indexed citations
10.
Anderson, Suzanne P., et al.. (2009). Weathering, Water, and Slope Aspect. AGU Fall Meeting Abstracts. 2009.1 indexed citations
11.
Williams, Mark, et al.. (2006). Climate Change in Western Ski Areas: Timing of Wet Avalanches in Aspen Ski Area in the Years 2030 and 2100. 899–906.1 indexed citations
Williams, Mark, David W. Clow, & Tamara Blett. (2004). A Novel Indicator of Ecosystem N Status: DIN to DON Ratio in Riverine Waters. AGUFM. 2004.1 indexed citations
Williams, Mark. (1957). The Wichitas: land of the living prairie. National geographic/The complete National geographic/The National geographic magazine. 111(5). 661–697.1 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.