Related references
Note: Only part of the references are listed.Species distribution modelling is needed to support ecological impact assessments
David J. Baker et al.
JOURNAL OF APPLIED ECOLOGY (2021)
Effect of climate change on the potential distribution of the common cutworm (Spodoptera litura) in South Korea
Jae-Min Jung et al.
ENTOMOLOGICAL RESEARCH (2019)
Prediction of global geographic distribution of Metcalfa pruinosa using CLIMEX
Dae-hyeon Byeon et al.
ENTOMOLOGICAL RESEARCH (2018)
Present and future Koppen-Geiger climate classification maps at 1-km resolution
Hylke E. Beck et al.
SCIENTIFIC DATA (2018)
Review of CLIMEX and MaxEnt for studying species distribution in South Korea
Dae-hyeon Byeon et al.
JOURNAL OF ASIA-PACIFIC BIODIVERSITY (2018)
A quantitative synthesis of the importance of variables used in MaxEnt species distribution models
Johanna Bradie et al.
JOURNAL OF BIOGEOGRAPHY (2017)
WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas
Stephen E. Fick et al.
INTERNATIONAL JOURNAL OF CLIMATOLOGY (2017)
On the selection of thresholds for predicting species occurrence with presence-only data
Canran Liu et al.
ECOLOGY AND EVOLUTION (2016)
How important are choice of model selection method and spatial autocorrelation of presence data. for distribution modelling by MaxEnt?
Rune Halvorsen et al.
ECOLOGICAL MODELLING (2016)
A comparison of absolute performance of different correlative and mechanistic species distribution models in an independent area
Farzin Shabani et al.
ECOLOGY AND EVOLUTION (2016)
BIOCLIM: the first species distribution modelling package, its early applications and relevance to most current MAXENT studies
Trevor H. Booth et al.
DIVERSITY AND DISTRIBUTIONS (2014)
Making better MAXENT models of species distributions: complexity, overfitting and evaluation
Aleksandar Radosavljevic et al.
JOURNAL OF BIOGEOGRAPHY (2014)
ENMeval: An R package for conducting spatially independent evaluations and estimating optimal model complexity for MAXENT ecological niche models
Robert Muscarella et al.
METHODS IN ECOLOGY AND EVOLUTION (2014)
SDMtoolbox: a python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses
Jason L. Brown
METHODS IN ECOLOGY AND EVOLUTION (2014)
The importance of correcting for sampling bias in MaxEnt species distribution models
Stephanie Kramer-Schadt et al.
DIVERSITY AND DISTRIBUTIONS (2013)
The Effects of Sampling Bias and Model Complexity on the Predictive Performance of MaxEnt Species Distribution Models
Mindy M. Syfert et al.
PLOS ONE (2013)
A statistical explanation of MaxEnt for ecologists
Jane Elith et al.
DIVERSITY AND DISTRIBUTIONS (2011)
Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria
Dan L. Warren et al.
ECOLOGICAL APPLICATIONS (2011)
Pest risk analysis of Metcalfa pruinosa in Austria
Gudrun Strauss
JOURNAL OF PEST SCIENCE (2010)
Predicting invasions in Australia by a Neotropical shrub under climate change: the challenge of novel climates and parameter estimation
Rieks D. van Klinken et al.
GLOBAL ECOLOGY AND BIOGEOGRAPHY (2009)
Share Paper
