.. _example_applications_plot_species_distribution_modeling.py: ============================= Species distribution modeling ============================= Modeling species' geographic distributions is an important problem in conservation biology. In this example we model the geographic distribution of two south american mammals given past observations and 14 environmental variables. Since we have only positive examples (there are no unsuccessful observations), we cast this problem as a density estimation problem and use the `OneClassSVM` provided by the package `sklearn.svm` as our modeling tool. The dataset is provided by Phillips et. al. (2006). If available, the example uses `basemap `_ to plot the coast lines and national boundaries of South America. The two species are: - `"Bradypus variegatus" `_ , the Brown-throated Sloth. - `"Microryzomys minutus" `_ , also known as the Forest Small Rice Rat, a rodent that lives in Peru, Colombia, Ecuador, Peru, and Venezuela. References ---------- * `"Maximum entropy modeling of species geographic distributions" `_ S. J. Phillips, R. P. Anderson, R. E. Schapire - Ecological Modelling, 190:231-259, 2006. .. image:: images/plot_species_distribution_modeling_001.png :align: center **Script output**:: ________________________________________________________________________________ Modeling distribution of species 'bradypus variegatus' - fit OneClassSVM ... done. - plot coastlines from coverage - predict species distribution Area under the ROC curve : 0.865253 ________________________________________________________________________________ Modeling distribution of species 'microryzomys minutus' - fit OneClassSVM ... done. - plot coastlines from coverage - predict species distribution Area under the ROC curve : 0.993919 time elapsed: 6.80s **Python source code:** :download:`plot_species_distribution_modeling.py ` .. literalinclude:: plot_species_distribution_modeling.py :lines: 38- **Total running time of the example:** 6.88 seconds ( 0 minutes 6.88 seconds)