Spatial autocorrelation and the selection of simultaneous autoregressive models

Global Ecology and Biogeography

Volumn 17, Issue 1, 2008, Pages 59-71

  Kissling, W Daniel ^a,c   Carl, Gudrun ^b,c  

^a JOHANNES GUTENBERG UNIVERSITY   (Germany)

^b HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH UFZ   (Germany)

^c Virtual Institute Macroecology   (Germany)

Author keywords

Autoregressive process; Biogeography; Macroecology; Model selection; Neighbourhood structure; Spatial model; Spatial statistics; Spatial weights; Species richness

Indexed keywords

AUTOCORRELATION; BIOGEOGRAPHY; DATA SET; LEAST SQUARES METHOD; MACROECOLOGY; SPATIAL DISTRIBUTION; SPECIES RICHNESS;

EID: 36749077029     PISSN: 1466822X     EISSN: 14668238     Source Type: Journal    
DOI: 10.1111/j.1466-8238.2007.00334.x     Document Type: Article

References (41)

1. Anselin, L. (1988) Spatial econometrics: Methods and models. Kluwer Academic Publishers, Dordrecht.
2. Anselin, L. (2002) Under the hood. Issues in the specification and interpretation of spatial regression models. Agricultural Economics, 27, 247-267.
3. Anselin, L. (2003) Spatial externalities, spatial multipliers, and spatial econometrics. International Regional Science Review, 26, 153-166.
4. Anselin, L. & Bera, A.K. (1998) Spatial dependence in linear regression models with an introduction to spatial econometrics. Handbook of applied economic statistics (ed. by A. Ullah and D.E.A. Giles), pp. 237-289. Marcel Dekker, New York.
5. Araújo, M.B., Pearson, R.G., Thuiller, W. & Erhard, M. (2005a) Validation of species-climate impact models under climate change. Global Change Biology, 11, 1504-1513.
6. Araújo, M.B., Whittaker, R.J., Ladle, R.J. & Erhard, M. (2005b) Reducing uncertainty in projections of extinction risk from climate change. Global Ecology and Biogeography, 14, 529-538.
7. Besag, J. (1974) Spatial interaction and the statistical analysis of lattice systems. Journal of the Royal Statistical Society, Series B, 36, 192-236.
8. Bivand, R. (20W6) Spdep: Spatial dependence: weighting schemes, statistics and models. R package version 0.3-31. Available online at http://cran.r-project.org/src/contrib/Descriptions/spdep.html
9. Bjørnstad, O.N. (2005) ncf: Spatial nonparametric covariance functions. R package version 1.0-8. Available online at http://onb.ent.psu.edu/onb1/
10. Burnham, K.P. & Anderson, D.R. (1998) Model selection and multimodel inference: A practical information-theoretic approach. Springer, New York.
11. Cliff, A.D. & Ord, J.K. (1981) Spatial processes - models and applications. Pion Ltd., London.
12. Cressie, N.A.C. (1993) Statistics for spatial data. Wiley Series in Probability and Mathematical Statistics. Wiley, New York.
13. Dark, S.J. (2004) The biogeography of invasive alien plants in California: An application of GIS and spatial regression analysis. Diversity and Distributions, 10, 1-9.
14. Diniz-Filho, J.A.F. & Bini, L.M. (2005) Modelling geographical patterns in species richness using eigenvector-based spatial filters. Global Ecology and Biogeography, 14, 177-185.
15. Diniz-Filho, J.A.F., Bini, L.M. & Hawkins, B.A. (2003) Spatial autocorrelation and red herrings in geographical ecology. Global Ecology and Biogeography, 12, 53-64.
16. Dormann, C.F. (2007) Effects of incorporating spatial autocorrelation into the analysis of species distribution data. Global Ecology and Biogeography, 16, 129-138.
17. Elith, J., Graham, C.H., Anderson, R.P., Dudík, M., Ferrier, S., Guisan, A., Hijmans, R.J., Huettmann, F., Leathwick, J.R., Lehmann, A., Li, J., Lohmann, L.G., Loiselle, B.A., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, J.McC., Peterson, A.T., Phillips, S.J., Richardson, K.S., Scachetti-Pereira, R., Schapire, R.E., Soberón, J., Williams, S., Wisz, M.S. & Zimmermann, N.E. (2006) Novel methods improve prediction of species' distributions from occurrence data. Ecography, 29, 129-151.
18. Fadili, M.J. & Bullmore, E.T. (2002) Wavelet-generalized least squares: A new BLU estimator of linear regression models with 1/f errors. NeuroImage, 15, 217-232.
19. Fortin, M.-J. & Dale, M.R.T. (2005) Spatial analysis -a guide for ecologists. Cambridge University Press, Cambridge.
20. Guisan, A., Lehmann, A., Ferrier, S., Austin, M., Overton, J.Mc.C., Aspinall, R. & Hastie, T. (2006) Making better biogeographical predictions of species' distributions. Journal of Applied Ecology, 43, 386-392.
21. Haining, R. (2003) Spatial data analysis: Theory and practice. Cambridge University Press, Cambridge.
22. Hijmans, R.J. & Graham, C.H. (2006) The ability of climate envelope models to predict the effect of climate change on species distributions. Global Change Biology, 12, 2272-2281.
23. Hoeting, J.A., Davis, R.A., Merton, A.A. & Thompson, S.E. (2006) Model selection for geostatistical models. Ecological Applications, 16, 87-98.
24. Jetz, W. & Rahbek, C. (2002) Geographic range size and determinants of avian species richness. Science, 297, 1548-1551.
25. Johnson, J.B. & Omland, K.S. (2004) Model selection in ecology and evolution. Trends in Ecology & Evolution, 19, 101-108.
26. Keitt, T.H., Bjørnstad, O.N., Dixon, P.M. & Citron-Pousty, S. (2002) Accounting for spatial pattern when modelling organism-environment interactions. Ecography, 25, 616-625.
27. Kissling, W.D., Rahbek, C. & Böhning-Gaese, K. (2007) Food plant diversity as broad-scale determinant of avian frugivore richness. Proceedings of the Royal Society B: Biological Sciences, 274, 799-808.
28. Kühn, I. (2007) Incorporating spatial autocorrelation may invert observed patterns. Diversity and Distributions, 13, 66-69.
29. Legendre, P. (1993) Spatial autocorrelation: Trouble or new paradigm? Ecology, 74, 1659-1673.
30. Legendre, P. & Fortin, M.-J. (1989) Spatial pattern and ecological analysis. Vegetatio, 80, 107-138.
31. Legendre, P. & Legendre, L. (1998) Numerical ecology. Elsevier, Amsterdam.
32. Legendre, P., Dale, M.R.T., Fortin, M.-J., Gurevitch, J., Hohn, M. & Myers, D. (2002) The consequences of spatial structure for the design and analysis of ecological field surveys. Ecography, 25, 601-615.
33. Lennon, J.J. (2000) Red-shifts and red herrings in geographical ecology. Ecography, 23, 101-113.
34. Lichstein, J.W., Simons, T.R., Shriner, S.A. & Franzreb, K.E. (2002) Spatial autocorrelation and autoregressive models in ecology. Ecological Monographs, 72, 445-463.
35. Moran, P.A.P. (1950) Notes on continuous stochastic phenomena. Biometrika, 37, 17-23.
36. Overmars, K.P., de Koning, G.H.J. & Veldkamp, A. (2003) Spatial autocorrelation in multi-scale land use models. Ecological Modelling, 164, 257-270.
37. Rangel, T.F.L.V.B., Diniz-Filho, J.A.F. & Bini, L.M. (2006) Towards an integrated computational tool for spatial analysis in macroecology and biogeography. Global Ecology and Biogeography, 15, 321-327.
38. R Development Core Team (2005) R: A language and environment for statistical computing. R foundation for Statistical Computing, Vienna. Available at: http://www.R-project.org
39. Segurado, P. & Araújo, M.B. (2004) An evaluation of methods for modelling species distributions. Journal of Biogeography, 31, 1555-1568.
40. Tiefelsdorf, M., Griffith, D.A. & Boots, B. (1999) A variance-stabilizing coding scheme for spatial link matrices. Environment and Planning A, 31, 165-180.
41. Tognelli, M.F. & Kelt, D.A. (2004) Analysis of determinants of mammalian species richness in South America using spatial autoregressive models. Ecography, 27, 427-436.