17th Global Online Seminar in Biodiversity Informatics
The MigClim R Package: Seamless Integration of Dispersal Constraints into Projections of Species Distribution Models
This seminar will present "MigClim," an R package developed to integrate dispersal constraints into projections from ecological niche models (also known as species distribution models). The presentation will include an overview of the tool and its main options, examples of applications, and a hands-on example of how to use MigClim in R. MigClim can be downloaded from CRAN at "cran.r-project.org/web/packages/MigClim
", or by typing "install.packages("MigClim", dependencies=T)" directly in the R console.
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Two publications are provided to give an introduction to MigClim:
Engler R., Hordijk W. and Guisan A, 2012. The MIGCLIM R package – seamless integration of dispersal constraints into projections of species distribution models. Ecography, 35, 872-878.
Engler R. and Guisan A., 2009. MIGCLIM: Predicting plant distribution and dispersal in a changing climate. Diversity and Distributions, 15, 590-601.
They can be downloaded from https://www.dropbox.com/s/6trrjlpe0mjj7o7/17_Engler.zip?dl=0
After obtaining a MSc degree with emphasis on plant ecology and geographic information systems, Robin joined the Spatial Ecology Lab at the University of Lausanne in 2005, where he obtained a Ph.D. in 2009 under the supervision of Antoine Guisan. His Ph.D. focused on ecological niche modelling, and in particular on using models to help detect rare species in the field, predictions of potential distributions of plants under climate change, and integration of dispersal constraints into ecological niche models. These explorations eventually led to the development of MigClim. In parallel to his thesis and in the years thereafter, Robin worked as scientific collaborator specialized in GIS for the Seismic Atlas of the Swiss Molasse Basin, a collaboration between the Swiss Geophysical Commission, the University of Lausanne, and the Swiss federal office of topography. In early 2014, he joined the Swiss Institute of Bioinformatics to work on spatial epidemiology risk modeling.