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This is a tutorial containing a full worked example of species distribution modelling using different methods for pseudo-absence generation presented in Iturbide et al., 2015, combining environmental profiling and spatial extent restriction of the background (see Fig. 2 in the cited article). We illustrate the steps followed to produce some of the analyses presented in the article using the R package mopa (MOdelling Pseudo Absences). With mopa, data pre-processing and modeling is easily done in a few command lines.
mopa v0.4.0
mopa v1.0.0
- Data formats and pre-processing
- Pseudo-absence data generation
- Model fitting and prediction
- Further options to assess model performace
- Analysis of SDM projections
###References
Iturbide, M., Bedia, J., Herrera, S., del Hierro, O., Pinto, M., Guti ́errez, J.M., 2015. A framework for species distribution modelling with improved pseudo-absence generation. Ecological Modelling DOI:10.1016/j.ecolmodel.2015.05.018.
Petit, R. J., Csaikl, U. M., Bord ́acs, S., Burg, K., Coart, E., Cottrell,J., van Dam, B., Deans, J. D., Dumolin Lap ́egue, S., Fineschi, S., Finkeldey, R., Gillies, A., Glaz, I., Goicoechea, P. G., Jensen,J. S., Konig, A. O., Lowe, A. J., Madsen, S. F., Mátyás, G., Munro, R. C., Olalde, M., Pemonge, M.H., Popescu, F., Slade, D., Tabbener, H., Taurchini, D., de Vries, S. G. M., Ziegenhagen, B., Kremer, A., 2002b. Chloroplast DNA variation in european white oaks: Phylogeography and patterns of diversity based on data from over 2600 populations. Forest Ecology and Management 156 (1-3), 5-26.
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