Plant Systematics, Conservation Biology, and Ethnobotany

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Iván Jiménez, Ph.D.

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Iván Jiménez, Ph.D.

Associate Scientist
Center for Conservation and Sustainable Development

Research Interests
• Species concepts and delimitations
• Spatial patterns of species diversity and distributions
• Ecological computer modeling

Species delimitation based on phenotypic data: how many specimens should be measured?. Jiménez is an Associate Scientist in the Center for Conservation and Sustainable Development. His research program seeks to determine the factors that determine the abundance and distribution of species at various spatial scales.The discovery and description of species is a major goal of systematic biology. Accordingly, much effort has been devoted to develop methods for species delimitation based on genomic data. In contrast, there has been relatively little development of quantitative methods for species delimitation based on phenotypic data, even though phenotypic data are just as important as genomic data for species delimitation, most species have been discovered based on phenotypic distinctiveness, and phenotypic data are often the only available data to delimit fossil species. This contrast is illustrated by the existence of general sampling rules for methods based on genomic data, but not for methods based on phenotypic data. In this REU project one or two students will develop sampling rules, in terms of the number of specimens (individuals) measured, for the application of normal mixture models to species delimitation based on phenotypic data (Cadena et al. 2018). This project may be run as a collaboration between two REU students, but it may also be carried out by a single REU student. The student(s) participating in this project will use the R environment  to perform computer simulations, manipulate data and perform statistical analyses. No previous experience with statistics or the R environment is needed; but if the student is not familiar with the R language or basic statistics, strong disposition to learn a computer language and statistics is required.

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