Journal ArticleDOI
Spatial bias in the GBIF database and its effect on modeling species' geographic distributions
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TLDR
A subsampling routine is used as an exemplar taxon to provide evidence that range model quality is decreasing due to the spatial clustering of distributional records in GBIF and shows that data with less spatial bias produce better predictive models even though they are based on less input data.About:
This article is published in Ecological Informatics.The article was published on 2014-01-01. It has received 424 citations till now.read more
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sampbias, a method for quantifying geographic sampling biases in species distribution data
Alexander Zizka,Alexander Zizka,Alexandre Antonelli,Alexandre Antonelli,Daniele Silvestro,Daniele Silvestro +5 more
TL;DR: Sampbias is implemented as a well-documented, open-access and user-friendly R package that it is hoped will become a standard tool for anyone working with species occurrences in ecology, evolution, conservation and related fields.
Journal ArticleDOI
Effects of occurrence record number, environmental variable number, and spatial scales on MaxEnt distribution modelling for invasive plants
TL;DR: In this article, the authors used the area under the curve (AUC) of the receiver operator characteristics as an indicator of MaxEnt performance, and evaluated the effects of the number of occurrence records, number of environmental variables, and spatial scales on MaxEnt distribution modelling of invasive plants.
Journal ArticleDOI
Optimizing biodiversity informatics to improve information flow, data quality, and utility for science and society
Robert P. Anderson,Miguel B. Araújo,Antoine Guisan,Jorge M. Lobo,Enrique Martínez-Meyer,A. Townsend Peterson,Jorge Soberón +6 more
TL;DR: In this paper, the authors discuss relevant issues from the perspective of modeling species distributions, currently the most common use of Primary Biodiversity Data, and highlight issues regarding data quality and representativeness, and improving feedback mechanisms.
Journal ArticleDOI
Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate-driven range shift in a butterfly.
TL;DR: It is argued that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate, including factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches.
Journal ArticleDOI
Slimy invasion: Climatic niche and current and future biogeography of Arion slug invaders
TL;DR: In this paper, the authors focus on three Arion slug species recently introduced to North America and Australia with potentially significant impact, Ater, A. rufus and A. vulgaris, and combine interception records, molecular analyses, and species distribution modeling to assess their introduction history and to predict which regions are at highest risk of future invasions.
References
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Journal ArticleDOI
Maximum entropy modeling of species geographic distributions
TL;DR: In this paper, the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data was introduced, which is a general-purpose machine learning method with a simple and precise mathematical formulation.
Journal ArticleDOI
Novel methods improve prediction of species' distributions from occurrence data
Jane Elith,Catherine H. Graham,Robert P. Anderson,Miroslav Dudík,Simon Ferrier,Antoine Guisan,Robert J. Hijmans,Falk Huettmann,John R. Leathwick,Anthony Lehmann,Jin Li,Lúcia G. Lohmann,Bette A. Loiselle,Glenn Manion,Craig Moritz,Miguel Nakamura,Yoshinori Nakazawa,Jacob C. M. Mc Overton,A. Townsend Peterson,Steven J. Phillips,Karen Richardson,Ricardo Scachetti-Pereira,Robert E. Schapire,Jorge Soberón,Stephen E. Williams,Mary S. Wisz,Niklaus E. Zimmermann +26 more
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Journal ArticleDOI
Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation
TL;DR: This paper presents a tuning method that uses presence-only data for parameter tuning, and introduces several concepts that improve the predictive accuracy and running time of Maxent and describes a new logistic output format that gives an estimate of probability of presence.
Journal ArticleDOI
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time
Jane Elith,John R. Leathwick +1 more
TL;DR: Species distribution models (SDMs) as mentioned in this paper are numerical tools that combine observations of species occurrence or abundance with environmental estimates, and are used to gain ecological and evolutionary insights and to predict distributions across landscapes, sometimes requiring extrapolation in space and time.
Journal ArticleDOI
AUC: a misleading measure of the performance of predictive distribution models
TL;DR: The area under the receiver operating characteristic (ROC) curve, known as the AUC, is currently considered to be the standard method to assess the accuracy of predictive distribution models as discussed by the authors.
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