Mao-Ning Tuanmu

Dr. Mao-Ning Tuanmu

Biodiversity Research Center, Academia Sinica, 128 Academia Rd., Sec. 2, Nankang Dist., Taipei City 115, Taiwan
orcid

Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

View All Publications
31 March 2017 in Science
Verified
Journal Article
Closed access
GPGretta T. Pecl
Gretta T. Pecl
MAMiguel B. Araújo
Miguel B. Araújo
JBJohann D. Bell
Johann D. Bell
JBJulia Blanchard
Julia Blanchard
TBTimothy C. Bonebrake
Timothy C. Bonebrake
SWStephen E. Williams
Stephen E. Williams
Consequences of shifting species distributions: Climate change is causing geographical redistribution of plant and animal species globally. These distributional shifts are leading to new ecosystems and ecological communities, changes that will affect human society. Pecl et al. review these current and future impacts and assess their implications for sustainable development goals. Science , this issue p. eaai9214

20 March 2018 in Scientific Data
Verified
Journal Article
Open access
PDF file
GAGIUSEPPE AMATULLI
GIUSEPPE AMATULLI
SDSami Domisch
Sami Domisch
MTMao-Ning Tuanmu
Mao-Ning Tuanmu
BPBenoit Parmentier
Benoit Parmentier
ARAjay Ranipeta
Ajay Ranipeta
WJWalter Jetz
Walter Jetz
Topographic variation underpins a myriad of patterns and processes in hydrology, climatology, geography and ecology and is key to understanding the variation of life on the planet. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale research applications, however to date, such datasets are unavailable. Here we used the digital elevation model products of global 250 m GMTED2010 and near-global 90 m SRTM4.1dev to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile/tangential curvature, first/second order partial derivative, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches. While a cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at Data Citation 1 and for download and visualization at http://www.earthenv.org/topography.

2 September 2015 in Nature
Verified
Journal Article
Closed access
PDF file
TCT. W. Crowther
T. W. Crowther
HGH. B. Glick
H. B. Glick
KCK. R. Covey
K. R. Covey
CBC. Bettigole
C. Bettigole
Daniel S. MaynardDaniel S. Maynard
Daniel S. Maynard
MBM. A. Bradford
M. A. Bradford

24 April 2014 in Global Ecology and Biogeography
Verified
Journal Article
Closed access
PDF file
MTMao-Ning Tuanmu
Mao-Ning Tuanmu
WJWalter Jetz
Walter Jetz


30 November 2017 in Biological Invasions
Verified
Journal Article
Closed access
PDF file
BBBethany A. Bradley
Bethany A. Bradley
CCCaroline A. Curtis
Caroline A. Curtis
EFEmily J. Fusco
Emily J. Fusco
JAJohn T. Abatzoglou
John T. Abatzoglou
JBJennifer K. Balch
Jennifer K. Balch
MTMao-Ning Tuanmu
Mao-Ning Tuanmu