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ENMTML: An R package for a straightforward construction of complex ecological niche models
Ecological niche models (ENMs) is a popular method in ecology, mostly due to its broad applicability and the fact that required data is simple and easily accessible from digital databases. Nevertheless, there is an underlying methodological complexity, often overlooked by many scientists that rely o...
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Published in: | Environmental modelling & software : with environment data news 2020-03, Vol.125, p.104615, Article 104615 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Ecological niche models (ENMs) is a popular method in ecology, mostly due to its broad applicability and the fact that required data is simple and easily accessible from digital databases. Nevertheless, there is an underlying methodological complexity, often overlooked by many scientists that rely on ENMs to achieve other objectives. We present here the package ENMTML, an Open Source R package. The main purpose of this package is to assemble all this methodological complexity spread over several papers and bring it into the spotlight in a simple way for people not used to the details of ENMs. The package contains several alternatives to different methodological steps, e.g., pseudo-absence allocation and accessible area delimitation, formulated within a single function, to make it accessible for people not used to the programming environment.
•We present ENMTML, an open source R package to fit ecological niche models (ENMs).•The package covers a wide variety of methodological aspects gathered from several studies.•Complex methodological features, which were not readily available in R, are now easily accessible to users.•We condense all this complexity in a single function to make it easier for users to follow a workflow.•We demonstrate an example of fitting models for four species with complex methodological choices and its interactions. |
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ISSN: | 1364-8152 1873-6726 |
DOI: | 10.1016/j.envsoft.2019.104615 |