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A MaxEnt package with introspection for ecological niche modeling.

Project description

The Whole Tale Project

Author: Santiago Nunez-Corrales


intros-MaxEnt is a Python software package that provides an open implementation of the MaxEnt algorithm for ecological niche modeling as described in

Phillips, S. J., Anderson, R. P., & Schapire, R. E. (2006). Maximum entropy modeling of species geographic distributions. Ecological modelling, 190(3-4), 231-259.

Our goal with this package is, scientifically, to help improve the modeling landscape in ecological niche modeling by making explicit the consequences of varying various parameters in MaxEnt based on biologically informed hypotheses.

The packaged provides facilities for the following tasks:

  1. Importing georeferenced data from taxa records for modeling species distribution, as well as environmental variables data for locations compliant with WGS84 latitude-longitude coordinates.

  2. Executing the MaxEnt algorithm with inspection and reparametrization capabilities of models and outcomes.

  3. Analyzing and differentially comparing model outcomes including KML and PNG image generation at various resolutions.

  4. Packaging of model configurations and experiments for extended scientific replication.

This package is also intended to be used in Jupyter Notebooks at The Whole Tale environment as an example of scientific reproducibility. The current software implementation was heavily informed by

Merow, C., Smith, M. J., & Silander, J. A. (2013). A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography, 36(10), 1058-1069.

This code is part of The Whole Tale Summer Internship 2018.

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