Niall Hanan

Niall Hanan

orcid

Research Focus & Metrics

Academic Career Length

36Years (1991-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 2005 in Nature
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Journal Article
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MSMahesh Sankaran
Mahesh Sankaran
NHNiall Hanan
Niall Hanan
RSRobert Scholes
Robert Scholes
JRJayashree Ratnam
Jayashree Ratnam
DADavid Augustine
David Augustine
NZNick Zambatis
Nick Zambatis

31 January 2014 in Science
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Journal Article
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CLCaroline E. R. Lehmann
Caroline E. R. Lehmann
TAT. Michael Anderson
T. Michael Anderson
MSMahesh Sankaran
Mahesh Sankaran
SHSteven I. Higgins
Steven I. Higgins
SASally Archibald
Sally Archibald
WBWilliam J. Bond
William J. Bond
Surveying Savannas: Savannas are structurally similar across the three major continents where they occur, leading to the assumption that the factors controlling vegetation structure and function are broadly similar, too. Lehmann et al. (p. 548 ) report the results of an extensive analysis of ground-based tree abundance in savannas, sampled at more than 2000 sites in Africa, Australia, and South America. All savannas, independent of region, shared a common functional property in the way that moisture and fire regulated tree abundance. However, despite qualitative similarity in the moisture–fire–tree-biomass relationships among continents, key quantitative differences exist among the three regions, presumably as a result of unique evolutionary histories and climatic domains.

19 April 2004 in Ecology Letters
Verified
Journal Article
Closed access
MSMahesh Sankaran
Mahesh Sankaran
JRJayashree Ratnam
Jayashree Ratnam
NHNiall Hanan
Niall Hanan

14 September 2007 in Global Ecology and Biogeography
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Journal Article
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MSMahesh Sankaran
Mahesh Sankaran
JRJayashree Ratnam
Jayashree Ratnam
NHNiall Hanan
Niall Hanan

15 May 2018 in Scientific Data
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Journal Article
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CRC. Wade Ross
C. Wade Ross
LPLara Prihodko
Lara Prihodko
JAJulius Anchang
Julius Anchang
SKSanath Kumar
Sanath Kumar
WJWenjie Ji
Wenjie Ji
NHNiall Hanan
Niall Hanan
Hydrologic soil groups (HSGs) are a fundamental component of the USDA curve-number (CN) method for estimation of rainfall runoff; yet these data are not readily available in a format or spatial-resolution suitable for regional- and global-scale modeling applications. We developed a globally consistent, gridded dataset defining HSGs from soil texture, bedrock depth, and groundwater. The resulting data product—HYSOGs250m—represents runoff potential at 250 m spatial resolution. Our analysis indicates that the global distribution of soil is dominated by moderately high runoff potential, followed by moderately low, high, and low runoff potential. Low runoff potential, sandy soils are found primarily in parts of the Sahara and Arabian Deserts. High runoff potential soils occur predominantly within tropical and sub-tropical regions. No clear pattern could be discerned for moderately low runoff potential soils, as they occur in arid and humid environments and at both high and low elevations. Potential applications of this data include CN-based runoff modeling, flood risk assessment, and as a covariate for biogeographical analysis of vegetation distributions.

1 August 2009 in Journal of Hydrology
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Journal Article
Closed access
TLThierry Lebel
Thierry Lebel
BCBernard Cappelaere
Bernard Cappelaere
SGSylvie Galle
Sylvie Galle
NHNiall Hanan
Niall Hanan
LKLaurent Kergoat
Laurent Kergoat
LSL. Séguis
L. Séguis