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 modelli...... 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 ...... 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 th...... 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 residu...... 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 ...... 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...... 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 ...... 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, pos...... 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 sp...... hiện toàn bộ