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Simapse – simulation maps for ecological niche modelling
Author(s) -
Tarroso Pedro,
Carvalho Sílvia B.,
Brito José Carlos
Publication year - 2012
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/j.2041-210x.2012.00210.x
Subject(s) - python (programming language) , environmental niche modelling , computer science , artificial neural network , niche , machine learning , ecological niche , sampling (signal processing) , artificial intelligence , predictive power , data mining , ecology , biology , philosophy , filter (signal processing) , epistemology , habitat , computer vision , operating system
Summary 1. Artificial neural networks (ANNs) are known for their powerful predictive power in the analysis of both linear and nonlinear relationships. They have been successfully applied to several fields including ecological modelling and predictive species’ distributions. 2. Here we present Simapse – Simulation Maps for Ecological Niche Modelling, a free and open‐source application written in Python and available to the most common platforms. It uses ANNs with back‐propagation to build spatially explicit distribution models from species data (presence/absence, presence‐only and abundance). 3. The main features include the automatic production of replicates with different sub‐sampling methods and total control of ANN structure and learning parameters. 4. Simapse uses common text formats as main input and output and provides assessment of variable importance and behaviour and measurement of model fitness.