M
Miguel Nakamura
Researcher at Centro de Investigación en Matemáticas
Publications - 33
Citations - 12210
Miguel Nakamura is an academic researcher from Centro de Investigación en Matemáticas. The author has contributed to research in topics: Population & Biology. The author has an hindex of 12, co-authored 27 publications receiving 10589 citations. Previous affiliations of Miguel Nakamura include Consejo Nacional de Ciencia y Tecnología.
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Journal ArticleDOI
Novel methods improve prediction of species' distributions from occurrence data
Jane Elith,Catherine H. Graham,Robert P. Anderson,Miroslav Dudík,Simon Ferrier,Antoine Guisan,Robert J. Hijmans,Falk Huettmann,John R. Leathwick,Anthony Lehmann,Jin Li,Lúcia G. Lohmann,Bette A. Loiselle,Glenn Manion,Craig Moritz,Miguel Nakamura,Yoshinori Nakazawa,Jacob C. M. Mc Overton,A. Townsend Peterson,Steven J. Phillips,Karen Richardson,Ricardo Scachetti-Pereira,Robert E. Schapire,Jorge Soberón,Stephen E. Williams,Mary S. Wisz,Niklaus E. Zimmermann +26 more
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Journal ArticleDOI
Predicting species distributions from small numbers of occurrence records: A test case using cryptic geckos in Madagascar
TL;DR: A novel jackknife validation approach is developed and tested to assess the ability to predict species occurrence when fewer than 25 occurrence records are available and the minimum sample sizes required to yield useful predictions remain difficult to determine.
Journal ArticleDOI
Niches and distributional areas: Concepts, methods, and assumptions
Jorge Soberón,Miguel Nakamura +1 more
TL;DR: It is argued that conceptual clarity is enhanced by adopting restricted definitions of “niche” that enable operational definitions of basic concepts like fundamental, potential, and realized niches and potential and actual distributional areas to be applied to the question of niche conservatism.
BookDOI
Ecological Niches and Geographic Distributions (MPB-49)
A. Townsend Peterson,Jorge Soberón,Richard G. Pearson,Robert P. Anderson,Enrique Martínez-Meyer,Miguel Nakamura +5 more
Journal ArticleDOI
Gauss-Markov measure field models for low-level vision
TL;DR: A class of models derived from classical discrete Markov random fields that may be used for the solution of ill-posed problems in image processing and in computational vision are presented, leading to reconstruction algorithms that are flexible, computationally efficient, and biologically plausible.