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 niche quantifications and comparisons between distinct ranges or time periods, measures of phylogenetic diversity, and other data exploration functionalities (e.g. extrapolation detection, ExDet). Core modeling brings together the new approach of ensemble of small models (ESM) and various implementations of the spatially‐explicit modeling of species assemblages (SESAM) framework. Post‐modeling analyses include evaluation of species predictions based on presence‐only data (Boyce index) and of community predictions, phylogenetic diversity and environmentally‐constrained species co‐occurrences analyses. The ecospat package also provides some functions to supplement the ‘biomod2’ package (e.g. data preparation, permutation tests and cross‐validation of model predictive power). With this novel package, we intend to stimulate the use of comprehensive approaches in spatial modelling of species and community distributions.

Aim  The presence‐only data stored in natural history collections is the most important source of information available regarding the distribution of organisms. These data and profile techniques can be used to generate species distribution models (SDMs), but pseudo‐absences must be generated to use group discriminative techniques. In this study, we evaluated whether the SDMs generated with pseudo‐absences are reliable and also if there are differences in the results obtained with profile and group discriminative techniques.Location  Ecuador, South America.Methods  The SDMs were generated with a training data set for each of the five species of Anthurium and six different methods: two profile techniques (BIOCLIM and Gower’s distance index), three group discriminative techniques [logistic multiple regression (LMR), multivariate adaptative regression splines (MARS) and Maxent] and a mixed modelling approach genetic algorithm for rule‐set production (GARP), which employs a combination of profile and group discriminative techniques and generates its own pseudo‐absences. For LMR, MARS and Maxent, three types of absences were generated: (1) random pseudo‐absences in equal number to presences and excluding a buffer area around presences (except for Maxent, which assumes that this background sample includes presences), (2) a large number (10,000) of random pseudo‐absences, also excluding a buffer area around each presence and (3) ‘target‐group absences’ (TGA), consisting of sites where other species of the group have been collected by the specialist, but not the species being modelled. To compare the predictive performance of the SDMs, the area under the curve statistic was calculated using an independent testing data set for each species.Results  MARS, Maxent and LMR produce better results than the profile techniques. The models created with TGA are generally more accurate than those generated with pseudo‐absences.Main conclusions  The advantages and disadvantages of different options for using pseudo‐absences and TGA with profile and group discriminative modelling techniques are explained and recommendations are made for the future.

RESUMENEn los últimos años se ha generalizado una nueva herramienta que permite analizar objetivamente los patrones espaciales de presencia de organismos: los modelos de distribución de especies. Estos modelos se basan en procedimientos estadísticos y cartográficos que partiendo de datos reales de presencia permiten inferir zonas potencialmente idóneas en función de sus características ambientales. Los datos de colecciones de historia natural pueden ser utilizados para este fin adquiriendo así una nueva utilidad. Los modelos han evolucionado desde su aplicación a especies aisladas hasta análisis de cientos o miles de taxones para combinarlos en el análisis de la biodiversidad y riqueza específica. En este trabajo se hace una revisión sobre la variedad de métodos utilizables, sus potencialidades e inconvenientes y los factores limitantes que influyen en la interpretación de lo que los modelos de distribución significan.Palabras clave: modelización ecológica, modelos de distribución de especies, revisión. ABSTRACTIn the last years a new tool has become widely used in ecological studies: species distribution models. These models analyze the spatial patterns of presence of organisms objectively, by means of statistical and cartographic procedures based on real data. They infer the presence of potentially suitable areas according to their environmental characteristics. Data stored in natural history collections can be used for this purpose, which gives new opportunities to use to these types of data. The models have evolved from the analysis of single species to the study of hundreds or thousands of taxa which are combined for the assessment of biodiversity and species richness. In this paper we review the variety of methods used, their potential and weaknesses, and the limiting factors that influence the interpretation of species distribution models. Key words: ecological modeling, revision, species distribution models. INTRODUCCIÓNLa generalización de los Sistemas de Información Geográfica y el desarrollo de técnicas estadísticas aplicadas ha permitido en los últimos años la expansión de herramientas para el análisis de los patrones espaciales de presencia y ausencia de especies: los modelos de distribución de especies (Franklin 1995, Guisan & Zimmermann 2000, Rushton et al. 2004, Foody 2008, Swenson 2008. Los modelos de distribución de especies están en pleno desarrollo y expansión con nuevos métodos y estrategias para el tratamiento e interpretación (Wilson et al. 2005, Elith et al. 2006, Ferrier & Guisan 2006, Mateo 2008. Como consecuencia, se han acumulado abundantes artículos con contribuciones metodológicas y teóricas significativas para la modelización de la distribución de especies.Este trabajo sintetiza la información disponible en la actualidad de una forma ordenada. Para ello se ha partido de las principales revisiones publicadas hasta la fecha (