Towards an integrated computational tool for spatial analysis in macroecology and biogeography

Because most macroecological and biodiversity data are spatially autocorrelated, special tools for describing spatial structures and dealing with hypothesis testing are usually required. Unfortunately, most of these methods have not been available in a single statistical package. Consequently, using these tools is still a challenge for most ecologists and biogeographers. In this paper, we present sam (Spatial Analysis in Macroecology), a new, easy-to-use, freeware package for spatial analysis in macroecology and biogeography. Through an intuitive, fully graphical interface, this package allows the user to describe spatial patterns in variables and provides an explicit spatial framework for standard techniques of regression and correlation. Moran's I autocorrelation coefficient can be calculated based on a range of matrices describing spatial relationships, for original variables as well as for residuals of regression models, which can also include filtering components (obtained by standard trend surface analysis or by principal coordinates of neighbour matrices). sam also offers tools for correcting the number of degrees of freedom when calculating the significance of correlation coefficients. Explicit spatial modelling using several forms of autoregression and generalized least-squares models are also available. We believe this new tool will provide researchers with the basic statistical tools to resolve autocorrelation problems and, simultaneously, to explore spatial components in macroecological and biogeographical data. Although the program was designed primarily for the applications in macroecology and biogeography, most of sam's statistical tools will be useful for all kinds of surface pattern spatial analysis. The program is freely available at http://www.ecoevol.ufg.br/sam (permanent URL at http://purl.oclc.org/sam/).

[1]  M. Fortin,et al.  Spatial pattern and ecological analysis , 1989, Vegetatio.

[2]  José Alexandre Felizola Diniz-Filho,et al.  PRODUCTIVITY AND HISTORY AS PREDICTORS OF THE LATITUDINAL DIVERSITY GRADIENT OF TERRESTRIAL BIRDS , 2003 .

[3]  T. Simons,et al.  Spatial autocorrelation and autoregressive models in ecology , 2002 .

[4]  C. Rahbek,et al.  Geographic Range Size and Determinants of Avian Species Richness , 2002, Science.

[5]  Michael Tiefelsdorf,et al.  Modelling Spatial Processes , 2000 .

[6]  D Hémon,et al.  Assessing the significance of the correlation between two spatial processes. , 1989, Biometrics.

[7]  R. Haining.  Spatial Data Analysis in the Social and Environmental Sciences , 1990 .

[8]  Luc Anselin,et al.  Under the hood , 2002 .

[9]  R. Reyment,et al.  Statistics and Data Analysis in Geology. , 1988 .

[10]  M.-J. Fortin,et al.  Issues related to the detection of boundaries , 2000, Landscape Ecology.

[11]  K. Gaston,et al.  Species‐energy relationships at the macroecological scale: a review of the mechanisms , 2005, Biological reviews of the Cambridge Philosophical Society.

[12]  C. Rahbek.  The role of spatial scale and the perception of large‐scale species‐richness patterns , 2004 .

[13]  Jessica Gurevitch,et al.  Integrating the Statistical Analysis of Spatial Data in Ecology , 2022 .

[14]  J. Diniz‐Filho,et al.  Water links the historical and contemporary components of the Australian bird diversity gradient , 2005 .

[15]  M. Fortin,et al.  Delineation of Ecological Boundaries: Comparison of Approaches and Significance Tests , 1995 .

[16]  Noel A Cressie,et al.  Statistics for Spatial Data. , 1992 .

[17]  WILLIAM F. FAGAN,et al.  Integrating Edge Detection and Dynamic Modeling in Quantitative Analyses of Ecological Boundaries , 2003 .

[18]  Noel A. C. Cressie,et al.  Statistics for Spatial Data: Cressie/Statistics , 1993 .

[19]  R. Hilborn,et al.  The Ecological Detective: Confronting Models with Data , 1997 .

[20]  Mark Rounsevell,et al.  Spatial autocorrelation as a tool for identifying the geographical patterns of aphid annual abundance , 2005 .

[21]  David J. Mulla,et al.  Geostatistical Tools for Modeling and Interpreting Ecological Spatial Dependence , 1992 .

[22]  Marie-Josée Fortin,et al.  Edge detection algorithms for two-dimensional ecological data , 1993 .

[23]  Hanna Tuomisto,et al.  DISSECTING THE SPATIAL STRUCTURE OF ECOLOGICAL DATA AT MULTIPLE SCALES , 2004 .

[24]  Daniel Wartenberg,et al.  Canonical Trend Surface Analysis: A Method for Describing Geographic Patterns , 1985 .

[25]  Helmut Hillebrand,et al.  Body size determines the strength of the latitudinal diversity gradient , 2001 .

[26]  Richard Field,et al.  Predictions and tests of climate‐based hypotheses of broad‐scale variation in taxonomic richness , 2004 .

[27]  N. Nagelkerke,et al.  A note on a general definition of the coefficient of determination , 1991 .

[28]  M. Fortin,et al.  Spatial Analysis: A Guide for Ecologists 1st edition , 2005 .

[29]  Pedro R. Peres-Neto,et al.  Patterns in the co-occurrence of fish species in streams: the role of site suitability, morphology and phylogeny versus species interactions , 2004, Oecologia.

[30]  David L. Fox,et al.  Ecological biogeography of North American mammals: species density and ecological structure in relation to environmental gradients , 2000 .

[31]  J. Diniz‐Filho,et al.  Spatial autocorrelation and red herrings in geographical ecology , 2003 .

[32]  Jessica Gurevitch,et al.  Ecography 25: 601 -- 615, 2002 , 2022 .

[33]  T. Boulinier,et al.  Ecological Biogeography of Southern Ocean Islands: The Importance of Considering Spatial Issues , 2001, The American Naturalist.

[34]  M. Graham.  CONFRONTING MULTICOLLINEARITY IN ECOLOGICAL MULTIPLE REGRESSION , 2003 .

[35]  P. Clifford,et al.  Modifying the t test for assessing the correlation between two spatial processes , 1993 .

[36]  L. Anselin.  Spatial Econometrics: Methods and Models , 1988 .

[37]  R. Sokal,et al.  Spatial autocorrelation in biology: 1. Methodology , 1978 .

[38]  Jerald B. Johnson,et al.  Model selection in ecology and evolution. , 2004, Trends in ecology & evolution.

[39]  Pierre Legendre,et al.  All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices , 2002 .

[40]  B. Manly.  Randomization, Bootstrap and Monte Carlo Methods in Biology , 2018 .

[41]  M. Tiefelsdorf.  Modelling spatial processes : the identification and analysis of spatial relationships in regression residuals by means of Moran's I : with 32 figures and 8 talbes , 1999 .

[42]  Lawrence B. Slobodkin,et al.  A Critique for Ecology , 1991 .

[43]  Robert R. Sokal,et al.  Local spatial autocorrelation in biological variables , 1998 .

[44]  M. Cardillo,et al.  Body size and latitudinal gradients in regional diversity of New World birds , 2002 .

[45]  José Alexandre Felizola Diniz-Filho,et al.  The mid-domain effect cannot explain the diversity gradient of Nearctic birds , 2002 .

[46]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[47]  M. Wall.  A close look at the spatial structure implied by the CAR and SAR models , 2004 .

[48]  M. Tognelli,et al.  Analysis of determinants of mammalian species richness in South America using spatial autoregressive models , 2004 .

[49]  Mike Rees,et al.  5. Statistics for Spatial Data , 1993 .

[50]  Lisa M. Ganio,et al.  A geostatistical approach for describing spatial pattern in stream networks , 2005 .

[51]  R. Whittaker,et al.  Scale and species richness: towards a general, hierarchical theory of species diversity , 2001 .

[52]  José Alexandre Felizola Diniz-Filho,et al.  Macroecological explanations for differences in species richness gradients: a canonical analysis of South American birds , 2004 .

[53]  P. Legendre.  Spatial Autocorrelation: Trouble or New Paradigm? , 1993 .

[54]  Sw. Banerjee,et al.  Hierarchical Modeling and Analysis for Spatial Data , 2003 .

[55]  Robert Haining,et al.  Spatial data analysis , 2003 .

[56]  Robert R. Sokal,et al.  Spatial autocorrelation in biology: 2. Some biological implications and four applications of evolutionary and ecological interest , 1978 .

[57]  José Alexandre Felizola Diniz-Filho,et al.  Modelling geographical patterns in species richness using eigenvector-based spatial filters , 2005 .

[58]  S. Dark,et al.  The biogeography of invasive alien plants in California: an application of GIS and spatial regression analysis , 2004 .

[59]  Ole R. Vetaas,et al.  Pteridophyte richness, climate and topography in the Iberian Peninsula: comparing spatial and nonspatial models of richness patterns , 2005 .