Plant Systematics, Conservation Biology, and Ethnobotany


Iván Jiménez and Oyomoare Osazuwa-Peters

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Iván Jiménez and Oyomoare Osazuwa-Peters

Associate Scientist Center for Conservation and Sustainable Development

Performance of rarefaction as an approach to account for botanical collection effort in estimates of broad-scale patterns of plant species richness. Jiménez is an Associate Scientist in MBG’s Center for Conservation and Sustainable Development. He is an ecologist with particular expertise in statistics, who regularly runs a three-day workshop in which students from local institutions are trained to use the statistical software package R. Understanding patterns of spatial variation in the number of species co-occurring within broad geographic areas is a major issue in ecology and biogeography, having practical implications for the identification of priority areas for the conservation of biodiversity. These patterns are relatively well documented for some groups (e.g., birds, mammals), but poorly described for Neotropical plants due to extremely uneven spatial distribution of botanical collection effort. Previous efforts to describe broad-scale spatial patterns of plant richness across the Neotropics have accounted for spatial variation in botanical collection effort using an approach called “rarefaction” (Jiménez et al. 2009). Rarefaction is unlikely to account for all error due to spatial variation in collection effort, but is thought to provide reasonable results (Engemann et al. 2015). Moreover, different types of rarefaction have been developed in attempts to provide better estimates of species richness (Chiarucci, et al. 2009; Bacaro et al. 2012). Nonetheless, little is known about the performance of these various types of rarefaction in the context of estimating broad-scale spatial patterns of plant richness using herbarium specimen records. This project will use data on the vascular plant flora of Nicaragua, stored in the Tropicos® database, to examine the performance of various types of rarefaction to estimate spatial patterns of Neotropical plant richness. The participating student(s) will use the R environment ( to 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 computer language and statistics is required.

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