ecospat: an R package to support spatial analyses and modeling of species niches and distributions

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 2016) 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. This article is protected by copyright. All rights reserved.

[1]  C. Rahbek,et al.  Spatial predictions at the community level: from current approaches to future frameworks , 2017, Biological reviews of the Cambridge Philosophical Society.

[2]  B. Petitpierre,et al.  Realized climatic niches are conserved along maximum temperatures among herpetofaunal invaders , 2017 .

[3]  Lindsay P. Campbell,et al.  NicheA: creating virtual species and ecological niches in multivariate environmental scenarios , 2016 .

[4]  B. Petitpierre,et al.  The mossy north: an inverse latitudinal diversity gradient in European bryophytes , 2016, Scientific Reports.

[5]  Miguel B. Araújo,et al.  sdm: a reproducible and extensible R platform for species distribution modelling , 2016 .

[6]  Diego Nieto-Lugilde,et al.  Modeling Species and Community Responses to Past, Present, and Future Episodes of Climatic and Ecological Change , 2015 .

[7]  A. Guisan,et al.  Predicting richness and composition in mountain insect communities at high resolution: a new test of the SESAM framework , 2015 .

[8]  Antoine Guisan,et al.  Overcoming limitations of modelling rare species by using ensembles of small models , 2015 .

[9]  Rui F. Fernandes,et al.  Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models , 2015 .

[10]  B. Laenen,et al.  What is the potential of spread in invasive bryophytes , 2015 .

[11]  Constantinos Tsirogiannis,et al.  Fast and Exact Algorithms for Computing PhylogeneticBiodiversity Measures , 2015 .

[12]  J. Gareth Polhill,et al.  Habitat networks and food security: promoting species range shift under climate change depends on life history and the dynamics of land use choices , 2015, Landscape Ecology.

[13]  J. Engler,et al.  Niche shift in four non‐native estrildid finches and implications for species distribution models , 2015 .

[14]  A. Guisan,et al.  Areas of high conservation value in Georgia: present and future threats by invasive alien plants , 2015, Biological Invasions.

[15]  Modeling the distribution of Apennine brown bears during hyperphagia to reduce the impact of wild boar hunting , 2015, European Journal of Wildlife Research.

[16]  D. Sax,et al.  Climatic niche shifts between species' native and naturalized ranges raise concern for ecological forecasts during invasions and climate change , 2014 .

[17]  P. De Marco,et al.  Using Ecological Niche Models and Niche Analyses to Understand Speciation Patterns: The Case of Sister Neotropical Orchid Bees , 2014, PloS one.

[18]  B. Lieberman,et al.  Macroevolutionary consequences of profound climate change on niche evolution in marine molluscs over the past three million years , 2014, Proceedings of the Royal Society B: Biological Sciences.

[19]  A. Guisan,et al.  Influence of climate on the presence of colour polymorphism in two montane reptile species , 2014, Biology Letters.

[20]  Sunil Kumar,et al.  Niche dynamics and potential geographic distribution of Didymosphenia geminata (Lyngbye) M. Schmidt, an invasive freshwater diatom in Southern Chile , 2014 .

[21]  R. Bustamante,et al.  Global Invasion of Lantana camara: Has the Climatic Niche Been Conserved across Continents? , 2014, PloS one.

[22]  D. Scaravelli,et al.  What Story Does Geographic Separation of Insular Bats Tell? A Case Study on Sardinian Rhinolophids , 2014, PloS one.

[23]  B. Petitpierre,et al.  Residence time, expansion toward the equator in the invaded range and native range size matter to climatic niche shifts in non‐native species , 2014 .

[24]  D. Richardson,et al.  Relatedness defies biogeography: the tale of two island endemics (Acacia heterophylla and A. koa). , 2014, The New phytologist.

[25]  P. Vittoz,et al.  Plant functional and phylogenetic turnover correlate with climate and land use in the Western Swiss Alps , 2014 .

[26]  Brenna R. Forester,et al.  Integrating environmental, molecular, and morphological data to unravel an ice-age radiation of arctic-alpine Campanula in western North America , 2014, Ecology and evolution.

[27]  R. Bustamante,et al.  Climatic Niche Conservatism and Biogeographical Non-Equilibrium in Eschscholzia californica (Papaveraceae), an Invasive Plant in the Chilean Mediterranean Region , 2014, PloS one.

[28]  J. Drake,et al.  Pattern‐recognition ecological niche models fit to presence‐only and presence–absence data , 2014 .

[29]  N. Zimmermann,et al.  Topo‐climatic microrefugia explain the persistence of a rare endemic plant in the Alps during the last 21 millennia , 2014, Global change biology.

[30]  Michael R Kearney,et al.  Realized niche shift during a global biological invasion , 2014, Proceedings of the National Academy of Sciences.

[31]  B. Petitpierre,et al.  Contrasting spatio‐temporal climatic niche dynamics during the eastern and western invasions of spotted knapweed in North America , 2014 .

[32]  J. Engler,et al.  Mapping Species Distributions with MAXENT Using a Geographically Biased Sample of Presence Data: A Performance Assessment of Methods for Correcting Sampling Bias , 2014, PloS one.

[33]  Dorothea V. Pio,et al.  Climate change effects on animal and plant phylogenetic diversity in southern Africa , 2014 .

[34]  B. Enquist,et al.  The n‐dimensional hypervolume , 2014 .

[35]  S. Veloz,et al.  NICHE AND RANGE SIZE PATTERNS SUGGEST THAT SPECIATION BEGINS IN SMALL, ECOLOGICALLY DIVERGED POPULATIONS IN NORTH AMERICAN MONKEYFLOWERS (MIMULUS SPP.) , 2014, Evolution; international journal of organic evolution.

[36]  M. Ritchie,et al.  Evidence for shared broad-scale climatic niches of diploid and polyploid plants. , 2014, Ecology letters.

[37]  Antoine Guisan,et al.  Unifying niche shift studies: insights from biological invasions. , 2014, Trends in ecology & evolution.

[38]  Anna F. Cord,et al.  Remote sensing data can improve predictions of species richness by stacked species distribution models: a case study for Mexican pines , 2014 .

[39]  Martin J. P. Sullivan,et al.  Testing multiple pathways for impacts of the non‐native Black‐headed Weaver Ploceus melanocephalus on native birds in Iberia in the early phase of invasion , 2014 .

[40]  S. Suárez‐Seoane,et al.  Scaling of species distribution models across spatial resolutions and extents along a biogeographic gradient. The case of the Iberian mole Talpa occidentalis , 2014 .

[41]  Deborah A. Jenkins,et al.  Genetic diversity in caribou linked to past and future climate change , 2014 .

[42]  M. Vences,et al.  New insights on phylogeography and distribution of painted frogs (Discoglossus) in northern Africa and the Iberian Peninsula , 2014 .

[43]  J. Calabrese,et al.  Stacking species distribution models and adjusting bias by linking them to macroecological models , 2014 .

[44]  Patterns of niche conservatism among non-native birds in Europe are dependent on introduction history and selection of variables , 2014, Biological Invasions.

[45]  P. Peres‐Neto,et al.  Shifts in Climate Foster Exceptional Opportunities for Species Radiation: The Case of South African Geraniums , 2013, PloS one.

[46]  D. Harris,et al.  Cryptic Speciation Patterns in Iranian Rock Lizards Uncovered by Integrative Taxonomy , 2013, PloS one.

[47]  P. Vittoz,et al.  Phylogenetic plant community structure along elevation is lineage specific , 2013, Ecology and evolution.

[48]  J. Engler,et al.  Confronting expert-based and modelled distributions for species with uncertain conservation status: A case study from the corncrake (Crex crex) , 2013 .

[49]  Brendan A. Wintle,et al.  Predicting species distributions for conservation decisions , 2013, Ecology letters.

[50]  J. Engler,et al.  The role of climate for the range limits of parapatric European land salamanders , 2013 .

[51]  Karel Mokany,et al.  Appropriateness of full‐, partial‐ and no‐dispersal scenarios in climate change impact modelling , 2013 .

[52]  J. Alexander.  Evolution under changing climates: climatic niche stasis despite rapid evolution in a non-native plant , 2013, Proceedings of the Royal Society B: Biological Sciences.

[53]  J. Engler,et al.  Rapid lizard radiation lacking niche conservatism: ecological diversification within a complex landscape , 2013 .

[54]  Niklaus E. Zimmermann,et al.  A greener Greenland? Climatic potential and long-term constraints on future expansions of trees and shrubs , 2013, Philosophical Transactions of the Royal Society B: Biological Sciences.

[55]  E. Matthysen,et al.  Niche conservatism in non‐native birds in Europe: niche unfilling rather than niche expansion , 2013 .

[56]  Luigi Maiorano,et al.  The Use of Climatic Niches in Screening Procedures for Introduced Species to Evaluate Risk of Spread: A Case with the American Eastern Grey Squirrel , 2013, PloS one.

[57]  Antoine Guisan,et al.  Improving the prediction of plant species distribution and community composition by adding edaphic to topo-climatic variables , 2013 .

[58]  E. Conti,et al.  Divergent and narrower climatic niches characterize polyploid species of European primroses in Primula sect. Aleuritia , 2013 .

[59]  N. Alvarez,et al.  Phylogenetic alpha and beta diversities of butterfly communities correlate with climate in the western Swiss Alps , 2013 .

[60]  N. Salamin,et al.  Turnover of plant lineages shapes herbivore phylogenetic beta diversity along ecological gradients. , 2013, Ecology letters.

[61]  Antoine Guisan,et al.  Building the niche through time: using 13,000 years of data to predict the effects of climate change on three tree species in Europe , 2013 .

[62]  L. Maiorano,et al.  Modeling the potential distribution for a range-expanding species: Wolf recolonization of the Alpine range , 2013 .

[63]  W. D. Kissling,et al.  The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling , 2012, Biological reviews of the Cambridge Philosophical Society.

[64]  Antoine Guisan,et al.  The accuracy of plant assemblage prediction from species distribution models varies along environmental gradients , 2013 .

[65]  Alycia L. Stigall,et al.  An horizon scan of biogeography. , 2013, Frontiers of biogeography.

[66]  S. Lavorel,et al.  Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology , 2012 .

[67]  S. R. Baral,et al.  Using Morphological, Molecular and Climatic Data to Delimitate Yews along the Hindu Kush-Himalaya and Adjacent Regions , 2012, PloS one.

[68]  Antoine Guisan,et al.  The MIGCLIM R package - seamless integration of dispersal constraints into projections of species distribution models , 2012 .

[69]  A. Skidmore,et al.  Corresponding Mitochondrial DNA and Niche Divergence for Crested Newt Candidate Species , 2012, PloS one.

[70]  C. Plutzar,et al.  Extinction debt of high-mountain plants under twenty-first-century climate change , 2012 .

[71]  W. Monahan,et al.  Niche Tracking and Rapid Establishment of Distributional Equilibrium in the House Sparrow Show Potential Responsiveness of Species to Climate Change , 2012, PloS one.

[72]  M. Salman,et al.  Association of environmental traits with the geographic ranges of ticks (Acari: Ixodidae) of medical and veterinary importance in the western Palearctic. A digital data set , 2012, Experimental and Applied Acarology.

[73]  Wilfried Thuiller,et al.  Accounting for dispersal and biotic interactions to disentangle the drivers of species distributions and their abundances. , 2012, Ecology letters.

[74]  A. Estrada-Peña,et al.  Occurrence Patterns of Afrotropical Ticks (Acari: Ixodidae) in the Climate Space Are Not Correlated with Their Taxonomic Relationships , 2012, PloS one.

[75]  M. Fortin,et al.  Measuring ecological niche overlap from occurrence and spatial environmental data , 2012 .

[76]  Terry Walshe,et al.  Designing occupancy surveys and interpreting non‐detection when observations are imperfect , 2012 .

[77]  Antoine Guisan,et al.  Climatic Niche Shifts Are Rare Among Terrestrial Plant Invaders , 2012, Science.

[78]  Á. Felicísimo,et al.  Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns? , 2012, PloS one.

[79]  A. Rebelo,et al.  Spatial Predictions of Phylogenetic Diversity in Conservation Decision Making , 2011, Conservation biology : the journal of the Society for Conservation Biology.

[80]  Robert P. Anderson,et al.  Ecological Niches and Geographic Distributions , 2011 .

[81]  A. Guisan,et al.  Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches , 2011 .

[82]  Jorge Soberón.  Mapping Species Distributions: Spatial Inference and Prediction (Book-Review) , 2011 .

[83]  Antoine Guisan,et al.  SESAM – a new framework integrating macroecological and species distribution models for predicting spatio‐temporal patterns of species assemblages , 2011 .

[84]  Janet Franklin,et al.  Geospatial tools address emerging issues in spatial ecology: a review and commentary on the Special Issue , 2011, Int. J. Geogr. Inf. Sci..

[85]  Hélène Morlon,et al.  Spatial patterns of phylogenetic diversity , 2011, Ecology letters.

[86]  Sergei Petrovskii,et al.  Spatial ecology across scales , 2011, Biology Letters.

[87]  A. Peterson,et al.  Conclusions about Niche Expansion in Introduced Impatiens walleriana Populations Depend on Method of Analysis , 2010, PloS one.

[88]  Steven J. Phillips,et al.  The art of modelling range‐shifting species , 2010 .

[89]  Antoine Guisan,et al.  Species distribution models reveal apparent competitive and facilitative effects of a dominant species on the distribution of tundra plants , 2010 .

[90]  Antoine Guisan,et al.  Overcoming the rare species modelling paradox: a novel hierarchical framework applied to an Iberian endemic plant. , 2010 .

[91]  Jane Elith,et al.  POC plots: calibrating species distribution models with presence-only data. , 2010, Ecology.

[92]  Campbell O. Webb,et al.  Picante: R tools for integrating phylogenies and ecology , 2010, Bioinform..

[93]  K. Medley.  Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models , 2010 .

[94]  Werner Ulrich,et al.  The empirical Bayes approach as a tool to identify non-random species associations , 2010, Oecologia.

[95]  P. Vittoz,et al.  Land use improves spatial predictions of mountain plant abundance but not presence-absence , 2009 .

[96]  D. Nogues‐Bravo,et al.  Predicting the past distribution of species climatic niches. , 2009 .

[97]  M. Araújo,et al.  BIOMOD – a platform for ensemble forecasting of species distributions , 2009 .

[98]  N. Zimmermann,et al.  Predicting future distributions of mountain plants under climate change: does dispersal capacity matter? , 2009 .

[99]  Eduardo Pineda,et al.  Assessing the accuracy of species distribution models to predict amphibian species richness patterns. , 2009, The Journal of animal ecology.

[100]  M. Turelli,et al.  Environmental Niche Equivalency versus Conservatism: Quantitative Approaches to Niche Evolution , 2008, Evolution; international journal of organic evolution.

[101]  A. Peterson,et al.  Effects of sample size on the performance of species distribution models , 2008 .

[102]  Ingolf Kühn,et al.  A comparative test of phylogenetic diversity indices , 2008, Oecologia.

[103]  Antoine Guisan,et al.  Niche dynamics in space and time. , 2008, Trends in ecology & evolution.

[104]  Jorge Soberón.  Grinnellian and Eltonian niches and geographic distributions of species. , 2007, Ecology letters.

[105]  Anne-Béatrice Dufour,et al.  The ade4 Package: Implementing the Duality Diagram for Ecologists , 2007 .

[106]  A. Peterson,et al.  Evidence of climatic niche shift during biological invasion. , 2007, Ecology letters.

[107]  Omri Allouche,et al.  A comparative evaluation of presence‐only methods for modelling species distribution , 2007 .

[108]  Jake F. Weltzin,et al.  The biogeography of prediction error: why does the introduced range of the fire ant over-predict its native range? , 2006 .

[109]  A. Hirzel,et al.  Evaluating the ability of habitat suitability models to predict species presences , 2006 .

[110]  M. Zappa,et al.  Are niche‐based species distribution models transferable in space? , 2006 .

[111]  Robert P. Anderson,et al.  Maximum entropy modeling of species geographic distributions , 2006 .

[112]  R. Macarthur.  The Problem of Pattern and Scale in Ecology: The Robert H. MacArthur Award Lecture , 2005 .

[113]  C. Lortie,et al.  Rethinking plant community theory , 2004 .

[114]  Korbinian Strimmer,et al.  APE: Analyses of Phylogenetics and Evolution in R language , 2004, Bioinform..

[115]  L. Stone,et al.  The checkerboard score and species distributions , 1990, Oecologia.

[116]  W. Thuiller.  BIOMOD – optimizing predictions of species distributions and projecting potential future shifts under global change , 2003 .

[117]  M. Boyce,et al.  Evaluating resource selection functions , 2002 .

[118]  Jennifer L. Dungan,et al.  A balanced view of scale in spatial statistical analysis , 2002 .

[119]  Nicholas J. Gotelli,et al.  SPECIES CO‐OCCURRENCE: A META‐ANALYSIS OF J. M. DIAMOND'S ASSEMBLY RULES MODEL , 2002 .

[120]  C. Lortie,et al.  Positive interactions among alpine plants increase with stress , 2002, Nature.

[121]  A. Hirzel,et al.  Assessing habitat-suitability models with a virtual species , 2001 .

[122]  Donald A. Jackson,et al.  Environmentally constrained null models: site suitability as occupancy criterion , 2001 .

[123]  Frank E. Harrell,et al.  Regression Modeling Strategies: With Applications to Linear Models, Logistic Regression, and Survival Analysis , 2001 .

[124]  Antoine Guisan,et al.  Predictive habitat distribution models in ecology , 2000 .

[125]  N. Gotelli.  Null model analysis of species co-occurrence patterns , 2000 .

[126]  H. Pulliam.  On the relationship between niche and distribution , 2000 .

[127]  S. Levin.  The problem of pattern and scale in ecology , 1992 .

[128]  R. Lewontin,et al.  An Elementary Text on Evolution@@@A Textbook of Evolution. , 1952 .