Novel methods improve prediction of species’ distributions from occurrence data Tập 29 Số 2 - Trang 129-151 - 2006
Jane Elith, Catherine H. Graham, Robert P. Anderson, Miroslav Dudı́k, 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 McC. 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
Prediction of species’ distributions is central to diverse applications in
ecology, evolution and conservation science. There is increasing electronic
access to vast sets of occurrence records in museums and herbaria, yet little
effective guidance on how best to use this information in the context of
numerous approaches for modelling distributions. To meet this need, we compared
16 modelling metho... hiện toàn bộ
Collinearity: a review of methods to deal with it and a simulation study evaluating their performance Tập 36 Số 1 - Trang 27-46 - 2013
Carsten F. Dormann, Jane Elith, Sven Bacher, Carsten M. Buchmann, Gudrun Carl, Gabriel Carré, Jaime Márquez, Bernd Gruber, Bruno Lafourcade, Pedro J. Leitão, Tamara Münkemüller, Colin J. McClean, Patrick E. Osborne, Björn Reineking, Boris Schröder, Andrew K. Skidmore, Damaris Zurell, Sven Lautenbach
Collinearity refers to the non independence of predictor variables, usually in a
regression‐type analysis. It is a common feature of any descriptive ecological
data set and can be a problem for parameter estimation because it inflates the
variance of regression parameters and hence potentially leads to the wrong
identification of relevant predictors in a statistical model. Collinearity is a
severe... hiện toàn bộ
Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation Tập 31 Số 2 - Trang 161-175 - 2008
Steven J. Phillips, Miroslav Dudík
Accurate modeling of geographic distributions of species is crucial to various
applications in ecology and conservation. The best performing techniques often
require some parameter tuning, which may be prohibitively time‐consuming to do
separately for each species, or unreliable for small or biased datasets.
Additionally, even with the abundance of good quality data, users interested in
the applic... hiện toàn bộ
Methods to account for spatial autocorrelation in the analysis of species distributional data: a review Tập 30 Số 5 - Trang 609-628 - 2007
Carsten F. Dormann, Jana McPherson, Miguel B. Araújo, Roger Bivand, Janine Bolliger, Gudrun Carl, R. Davies, Alexandre H. Hirzel, Walter Jetz, W. Daniel Kissling, Ingolf Kühn, Ralf Ohlemüller, Pedro R. Peres‐Neto, Björn Reineking, Boris Schröder, Frank M. Schurr, Robert J. Wilson
Species distributional or trait data based on range map (extent‐of‐occurrence)
or atlas survey data often display spatial autocorrelation, i.e. locations close
to each other exhibit more similar values than those further apart. If this
pattern remains present in the residuals of a statistical model based on such
data, one of the key assumptions of standard statistical analyses, that
residuals are ... hiện toàn bộ
A practical guide to MaxEnt for modeling species' distributions: what it does, and why inputs and settings matter Tập 36 Số 10 - Trang 1058-1069 - 2013
Cory Merow, Matthew J. Smith, John A. Silander
The MaxEnt software package is one of the most popular tools for species
distribution and environmental niche modeling, with over 1000 published
applications since 2006. Its popularity is likely for two reasons: 1) MaxEnt
typically outperforms other methods based on predictive accuracy and 2) the
software is particularly easy to use. MaxEnt users must make a number of
decisions about how they shou... hiện toàn bộ
Selecting thresholds of occurrence in the prediction of species distributions Tập 28 Số 3 - Trang 385-393 - 2005
Canran Liu, Pam Berry, Terence P. Dawson, Richard G. Pearson
Transforming the results of species distribution modelling from probabilities of
or suitabilities for species occurrence to presences/absences needs a specific
threshold. Even though there are many approaches to determining thresholds,
there is no comparative study. In this paper, twelve approaches were compared
using two species in Europe and artificial neural networks, and the modelling
results ... hiện toàn bộ
Opening the black box: an open‐source release of Maxent Tập 40 Số 7 - Trang 887-893 - 2017
Steven J. Phillips, Robert P. Anderson, Miroslav Dudík, Robert E. Schapire, Mary E. Blair
This software note announces a new open‐source release of the Maxent software
for modeling species distributions from occurrence records and environmental
data, and describes a new R package for fitting such models. The new release
(ver. 3.4.0) will be hosted online by the American Museum of Natural History,
along with future versions. It contains small functional changes, most notably
use of a co... hiện toàn bộ
spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models Tập 38 Số 5 - Trang 541-545 - 2015
Matthew Aiello‐Lammens, Robert A. Boria, Aleksandar Radosavljević, Bruno Vilela, Robert P. Anderson
Spatial thinning of species occurrence records can help address problems
associated with spatial sampling biases. Ideally, thinning removes the fewest
records necessary to substantially reduce the effects of sampling bias, while
simultaneously retaining the greatest amount of useful information. Spatial
thinning can be done manually; however, this is prohibitively time consuming for
large datasets... hiện toàn bộ
Where is positional uncertainty a problem for species distribution modelling? Tập 37 Số 2 - Trang 191-203 - 2014
Babak Naimi, Nicholas Hamm, T.A. Groen, Andrew K. Skidmore, Albertus G. Toxopeus
Species data held in museum and herbaria, survey data and opportunistically
observed data are a substantial information resource. A key challenge in using
these data is the uncertainty about where an observation is located. This is
important when the data are used for species distribution modelling (SDM),
because the coordinates are used to extract the environmental variables and
thus, positional ... hiện toàn bộ
ecospat: an R package to support spatial analyses and modeling of species niches and distributions Tập 40 Số 6 - Trang 774-787 - 2017
Valeria Di Cola, Olivier Broennimann, Blaise Petitpierre, Frank T. Breiner, Manuela D’Amen, Christophe F. Randin, Robin Engler, Antoine Guisan, Dorothea Pio, Luigi Maiorano, Loïc Pellissier, Rubén G. Mateo, Wim Hordijk, Nicolas Salamin
The aim of the ecospat package is to make available novel tools and methods to
support spatial analyses and modeling of species niches and distributions in a
coherent workflow. The package is written in the R language (R Development Core
Team) and contains several features, unique in their implementation, that are
complementary to other existing R packages. Pre‐modeling analyses include
species ni... hiện toàn bộ