scholarly journals ENMTML: An R package for a straightforward construction of complex ecological niche models

2020 ◽  
Vol 125 ◽  
pp. 104615 ◽  
Author(s):  
André Felipe Alves de Andrade ◽  
Santiago José Elías Velazco ◽  
Paulo De Marco Júnior
Keyword(s):  
Ecological Niche ◽  
R Package ◽  
Ecological Niche Models ◽  
Niche Models

scholarly journals Local Segregation of Realised Niches in Lizards

2020 ◽  
Vol 9 (12) ◽  
pp. 764
Author(s):  
Neftalí Sillero ◽  
Elena Argaña ◽  
Cátia Matos ◽  
Marc Franch ◽  
Antigoni Kaliontzopoulou ◽  
...  
Keyword(s):  
Environmental Variables ◽  
Ecological Niche ◽  
Species Coexistence ◽  
Niche Overlap ◽  
R Package ◽  
Abundant Species ◽  
Ecological Niche Models ◽  
Changes Over Time ◽  
Local Segregation ◽  
Niche Models

Species can occupy different realised niches when sharing the space with other congeneric species or when living in allopatry. Ecological niche models are powerful tools to analyse species niches and their changes over time and space. Analysing how species’ realised niches shift is paramount in ecology. Here, we examine the ecological realised niche of three species of wall lizards in six study areas: three areas where each species occurs alone; and three areas where they occur together in pairs. We compared the species’ realised niches and how they vary depending on species’ coexistence, by quantifying niche overlap between pairs of species or populations with the R package ecospat. For this, we considered three environmental variables (temperature, humidity, and wind speed) recorded at each lizard re-sighting location. Realised niches were very similar when comparing syntopic species occurring in the same study area. However, realised niches differed when comparing conspecific populations across areas. In each of the three areas of syntopy, the less abundant species shift its realised niche. Our study demonstrates that sympatry may shift species’ realised niche.

scholarly journals kuenm: an R package for detailed development of ecological niche models using Maxent

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6281 ◽  
Author(s):  
Marlon E. Cobos ◽  
A. Townsend Peterson ◽  
Narayani Barve ◽  
Luis Osorio-Olvera
Keyword(s):  
Model Calibration ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
Statistical Significance ◽  
R Package ◽  
Model Complexity ◽  
Ecological Niche Models ◽  
Detailed Model ◽  
Analytical Tools ◽  
Niche Models

Background Ecological niche modeling is a set of analytical tools with applications in diverse disciplines, yet creating these models rigorously is now a challenging task. The calibration phase of these models is critical, but despite recent attempts at providing tools for performing this step, adequate detail is still missing. Here, we present the kuenm R package, a new set of tools for performing detailed development of ecological niche models using the platform Maxent in a reproducible way. Results This package takes advantage of the versatility of R and Maxent to enable detailed model calibration and selection, final model creation and evaluation, and extrapolation risk analysis. Best parameters for modeling are selected considering (1) statistical significance, (2) predictive power, and (3) model complexity. For final models, we enable multiple parameter sets and model transfers, making processing simpler. Users can also evaluate extrapolation risk in model transfers via mobility-oriented parity (MOP) metric. Discussion Use of this package allows robust processes of model calibration, facilitating creation of final models based on model significance, performance, and simplicity. Model transfers to multiple scenarios, also facilitated in this package, significantly reduce time invested in performing these tasks. Finally, efficient assessments of strict-extrapolation risks in model transfers via the MOP and MESS metrics help to prevent overinterpretation in model outcomes.

scholarly journals Biomod2EZ - An R script suite for visualizing projected niche model ensembles and reporting statistical results

2017 ◽  
Author(s):  
Paul R. Sesink Clee ◽  
Stephen Woloszynek ◽  
Mary Katherine Gonder
Keyword(s):  
Graphical User Interface ◽  
Ecological Niche ◽  
Ecological Niche Modeling ◽  
R Package ◽  
Ecological Niche Models ◽  
Report Generation ◽  
Modeling Techniques ◽  
Model Ensembles ◽  
Statistical Results ◽  
Niche Models

AbstractBiomod2EZ is a suite of R scripts to use in conjunction with the Biomod2 R package by Thuiller et al. (2016) that is used to create ensemble ecological niche models using up to 11 different modeling techniques. Biomod2EZ adds to the functionality of Biomod2 (Thuiller et al. 2016) by incorporating a report generation feature, detailed script annotation, and sample dataset/tutorial to ease the transition from ecological niche modeling using a Graphical User Interface to the coding environment of the R framework (R Development Core Team, 2016).

scholarly journals spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models

Ecography ◽  
2015 ◽  
Vol 38 (5) ◽  
pp. 541-545 ◽  
Author(s):  
Matthew E. Aiello-Lammens ◽  
Robert A. Boria ◽  
Aleksandar Radosavljevic ◽  
Bruno Vilela ◽  
Robert P. Anderson
Keyword(s):  
Ecological Niche ◽  
R Package ◽  
Ecological Niche Models ◽  
Species Occurrence ◽  
Niche Models ◽  
Occurrence Records

The status of the anomalepidid snake Liotyphlops albirostris and the revalidation of three taxa based on morphology and ecological niche models

2021 ◽  
Vol 304 (10) ◽  
pp. 2264-2278
Author(s):  
Camilo A. Linares‐Vargas ◽  
Wilmar Bolívar‐García ◽  
Alexandra Herrera‐Martínez ◽  
Daniel Osorio‐Domínguez ◽  
Oscar E. Ospina ◽  
...  
Keyword(s):  
Ecological Niche ◽  
Ecological Niche Models ◽  
The Status ◽  
Niche Models

Evaluating alternative data sets for ecological niche models of birds in the Andes

Ecography ◽  
2004 ◽  
Vol 27 (3) ◽  
pp. 350-360 ◽  
Author(s):  
Juan L. Parra ◽  
Catherine C. Graham ◽  
Juan F. Freile
Keyword(s):  
Ecological Niche ◽  
Data Sets ◽  
Ecological Niche Models ◽  
The Andes ◽  
Niche Models
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