Spatial prediction of species distribution: An interface between ecological theory and statistical modelling

Ecological Modelling

Volumn 157, Issue 2-3, 2002, Pages 101-118

  Austin, M P ^a  

^a CSIRO   (Australia)

Author keywords

Canonical correspondence analysis; CCA; Continuum; GAM; Generalised additive models; Generalised linear models; GLM; Niche; Ordination; Regression; Spatial prediction; Species models; Species response curves; Vegetation models

Indexed keywords

CORRESPONDENCE ANALYSIS; ECOLOGICAL MODELING; ECOLOGICAL THEORY; PREDICTION; SPATIAL DISTRIBUTION; STATISTICAL ANALYSIS;

EID: 0037202447     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3800(02)00205-3     Document Type: Article

References (111)

1. Aspinall, R., Veitch, N., 1993. Habitat mapping from satellite imagery and wildlife survey data using a Bayesian modelling procedure in a GIS. P E & R S 59, 537-543.
2. Augustin, N., Mugglestone, M., Buckland, S., 1996. An autologistic model for spatial distribution of wildlife. J. Appl. Ecol. 33, 339-347.
3. Austin, M.P., 1971. Role of regression analysis in plant ecology. Proc. Ecol. Soc. Aust. 6, 63-75.
4. Austin, M.P., 1979. Current approaches to the non-linearity problems in vegetation analysis. In: Patil, G.P., Rosenzweig, M.L. (Eds.), Contemporary Quantitative Ecology and Related Ecometrics. International Co-operative Publishing House, Fairland, MD, pp. 197-210.
5. Austin, M.P., 1980. Searching for a model for use in vegetation analysis. Vegetatio. 42, 11-21.
6. Austin, M.P., 1985. Continuum concept, ordination methods and niche theory. Ann. Rev. Ecol. Syst. 16, 39-61.
7. Austin, M.P., 1987. Models for the analysis of species response to environmental gradients. Vegetatio 69, 35-45.
8. Austin, M.P., 1990. Community theory and competition in vegetation. In: Grace, J.B., Tilman, D. (Eds.), Perspectives on Plant Competition. Academic Press, California, pp. 215-238.
9. Austin, M.P., 1991. Vegetation: Data Collection and Analysis. In: C.R. Margules, M.P. Austin (Eds.) Nature Conservation: Cost-Effective Biological Surveys and Data Analysis, Proceedings of CONCOM Workshop, pp. 37-41.
10. 2 levels. Aust. J. Botany 40, 615-630.
11. Austin, M.P., 1998. An ecological perspective on bidiversity investigations: Examples from Australian eucalypt forests. Ann. Mo. Bot Gard. 85, 2-17.
12. Austin, M.P., 1999a. A silent clash of paradigms: Some inconsistencies in communily ecology. Oikos 86, 170-178.
13. Austin, M.P., 1999b. The potential contribution of vegetation ecology to biodiversity research. Ecography 22, 465-484.
14. Austin, M.P., 2002. Case studies of the use of environmental gradients in vegetation and fauna modelling: Theory and practice in Australia and New Zealand. In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M., Wall, B. (Eds.), Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Covelo, CA, pp. 73-82.
15. Austin, M.P., Cunningham, R.B., 1981. Observational analysis of environmental gradients. Proc. Ecol. Soc. Aust. 11, 109-119.
16. Austin, M.P., Heyligers, P.C., 1989. Vegetation survey design for conservation: gradsect sampling of forests in Northeastern New South Wales. Biol. Conserv. 50, 13-32.
17. Austin, M.P., Gaywood, M.J., 1994. Current problems of environmental gradients and species response curves in relation to continuum theory. J. Veg. Sci. 5, 473-482.
18. Austin, M.P., Nicholls, A.O., 1997. To fix or not to fix the species limits, that is the ecological question: Response to Jari Oksanen. J. Veg. Sci. 8, 743-748.
19. Austin, M.P., Smith, T.M., 1989. A new model for the continuum concept. Vegetatio 83, 35-47.
20. Austin, M.P., Nicholls, A.O., Doherty, M.D., Meyers, J.A., 1994. Determining species response functions to an environmental gradient by means of a β-function. J. Veg. Sci. 5, 215-228.
21. Austin, M.P., Meyers, J.A., Belbin, I., Doherty, M.D., 1995. Modelling of landscape patterns and processes using biological data. Subproject 5: Simulated Data Case Study. Consultancy report for ERIN, CSIRO Wildlife and Ecology, Canberra.
22. Austin, M.P., Pausas, J.G., Nicholls, A.O., 1996. Patterns of tree species richness in relation to environment in southeastern New South Wales, Australia. Aust. J. Ecol. 21, 154-164.
23. Bayliss, G.T.S., 1980. Mycorrhias and the spread of beech. New Zealand J. Ecol. 3, 151-153.
24. Begon, M., Harper, J.L., Townsend, C.R., 1990. Ecology, Individuals, Populations and Communities, Second Ed.. Blackwell Scientific Publications, Boston, p. 945.
25. Birks, H.J.B., Frey, D.G., Deevey, E.S., 1998. Review #1 numerical tools in palaeolimnology-progress, potentialities, and problems. J. Palaeolimnol. 20, 307-332.
26. Birks, H.J.B., Austin, H.A., 1992. An Annotated Bibliography of Canonical Correspondence Analysis and Related Constrained Ordination Methods 1986-1991. Botanical Institute, University of Bergen, Bergen, Norway.
27. Bio, A.M.F., Alkemade, R., Barendgret, A., 1998. Determining alternative models for vegetation response analysis: A non-parametric approach. J. Veg. Sci. 9, 5-16.
28. Boyce, M.S., Vernier, P.R., Nielsen, S.E., Schmiegelow, F.K.A., 2002. Evaluating resource selection functions. Ecol. Model. 157 (2-3), 279-298.
29. Box, G.E.P., 1966. Use and abuse of regression. Technometrics 8, 625-629.
30. Braun-Blanquet, J., 1964. Pflanzensoziologie, Third Ed.. Springer, Wien.
31. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J., 1984. Classification and Regression Trees. Wadsworth International Group, Belmont, CA, USA, p. 358.
32. Brunet, J., von Oheimb, G., Diekmann, M., 2000. Factors influencing vegetation gradients across ancient-recent woodland borderlines in southern Sweden. J. Veg. Sci. 11, 515-524.
33. Brzeziecki, B., 1987. Analysis of vegetation-environment relationships using a simultaneous equations model. Vegetatio 71, 175-184.
34. Cawsey, E.M., Austin, M.P., Baker, B.L., 2002. Regional vegetation mapping in Australia: a case study in the practical use of statistical modelling, Biodivers. Conserv., in press.
35. Cornell, H.V., Karlson, R.H., 1997. Local and regional processes as controls of species richness. In: Tilman, D., Kareiva, P. (Eds.), Spatial Ecology: The Role of Space in Population Dynamics and Interspecific Interactions. Princeton University Press, Princeton, pp. 250-268.
36. Cornell, H.V., Lawton, J.H., 1992. Species interactions, local and regional processes, and limits to the richness of ecological communities: A theoretical perspective. J. Anim. Ecol. 61, 1-12.
37. Currie, D.J., 1991. Energy and large-scale patterns of animal-and plant-species richness. Am. Naturalist 137, 27-49.
38. Elith, J., Burgman, M.A., 2002. Habitat models for PVA. In: Brigham, C.A., Schwanz, M.W. (Eds.), Population Viability in Plants. Springer.
39. Ejrnaes, R., 2000. Can we trust gradients extracted by detrended correspondence analysis. J. Veg. Sci. 11, 565-572.
40. Ejrnaes, R., Bruun, H.H., 2000. Gradient analysis of dry grassland vegetation in Denmark. J. Veg. Sci. 11, 573-584.
41. Faith, D.P., Minchin, P.R., Belbin, I., 1987. Compositional dissimilarity as a robust measure of ecological distance. Vegetatio 69, 57-68.
42. Fewster, R.M., Buckland, S.T., Siriwardena, G.M., Baillie, S.R., Wilson, J.D., 2000. Analysis of population trends for farmland birds using generalized additive models. Ecology 81, 1970-1984.
43. Fitzgerald, R.W., Lees, B.G., 1992. The application of neural networks to the floristic classification of remote sensing and GIS data in complex terrain. In: Proceedings of the 17th Congress of the International Society for Photogrammetry and Remote Sensing, Washington, USA.
44. Franklin, J., 1995. Predictive vegetation mapping: Geographic modelling of biospatial patterns in relation to environmental gradients. Prog. Phys. Geogr. 19, 474-499.
45. Franklin, J., 1998. Predicting the distribution of shrub species in southern California from climate and terrain-derived variables. J. Veg. Sci. 9, 733-748.
46. Franklin, J., McCullough, P., Gray, C., 2000. Terrain variables used for predictive mapping of vegetation communities in southern California. In: Wilson, J.P., Gallant, J.C. (Eds.), Terrain Analysis: Principles and Applications. Wiley.
47. Franklin, J., Keeler-Wolf, T., Thomas, K.A., Shaari, D.A., Stine, P.A., Michaelsen, J., Miller, J., 2002. Stratified sampling for field survey of environmental gradients in the Mojave desert ecoregion. In: Millington, A., Walsh, S., Osbome, P. (Eds.), GTS and Remote-Sensing Applications in Biogeography and Ecology. Kluwer Academic Publishers.
48. Gauch, H.G., Whittaker, R.H., 1972. Coenocline simulation. Ecology 53, 446-451.
49. Giller, J., 1984. Community Structure and the Niche. Chapman & Hall, London, p. 176.
50. Gleason, H.A., 1926. The individualistic concept of the plant association. Bull. Torrey Botanical Club 53, 7-26.
51. Grime, J.P., 1979. Plant Strategies and Vegetation Processes. Wiley, New York.
52. Guisan, A., 2002. Semi-quantitative response models for predicting the spatial distribution of plant species. In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M., Wall, B. (Eds.), Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Covelo, CA, pp. 315-326.
53. Guisan, A., Harrell, R.E., 2000. Ordinal response regression models in ecology. J. Veg. Sci. 11, 617-626.
54. Guisan, A., Theurillat, J.-P., 2000. Equilibrium modelling of alpine plant distribution: How far can we go. Phytocoenologia 30, 353-384.
55. Guisan, A., Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecol. Model. 135, 147-186.
56. Guisan, A., Weiss, S.B., Weiss, A.D., 1999. GLM versus CCA spatial modelling of plant species distribution. Plant Ecol. 143, 107-122.
57. Gumpertz, M.L., Graham, J.M., Ristaino, J.B., 1997. Autologistic model of spatial pattern of phytophthora epidemic in Bell Pepper: effects of soil variables on disease presence. J. Agric. Biol. Environ. Stat. 2, 131-156.
58. Hastie, T., Tibshirani, R., 1990. Generalised Additive Models. Chapman & Hall, London.
59. Heegaard, E., 2001. Environmental relationships of perichaetial and sporophyte production in Andreaea spp. in Western Norway. J. Bryol. 23, 97-108.
60. Huston, M.A., 1994. Biological Diversity: The Coexistence of Species on Changing Landscapes. Cambridge University Press, Cambridge.
61. Iverson, L.R., Pasad, A.M., 1998. Predicting abundance of 80 tree species following climate change in the eastern United States. Ecol. Monogr. 68, 465-485.
62. Keddy, P.A., 1982. Population ecology on an environmental gradient: Cattle edentula on a sand dune. Oecologia 52, 348-355.
63. Keddy, P.A., 1989. Competition. Chapman & Hall, London.
64. Krebs, C.J., 1994. Ecology: The Experimental Analysis of the Distribution of Distribution and Abundance, Fourth Ed.. Harper & Row, New York.
65. Leathwick, J.R., 1995. Climatic relationships of some New Zealand forest tree species. J. Veg. Sci. 6, 237-248.
66. Leathwick, J.R., 1998. Are New Zealand's Nothofagus species in equilibrium with their environment. J. Veg. Sci. 9, 719-732.
67. Leathwick, J.R., 2002. Intra-generic competition among Nothofagus in New Zealand's old-growth forests. Biodivers. Conserv., in press.
68. Leathwick, J.R., Austin, M., 2001. Competitive interactions between tree species in New Zealand old-growth indigenous forests. Ecology 82, 2560-2573.
69. Leathwick, J.R., Mitchell, N.D., 1992. Forest pattern, climate and vulcanism in central North Island, New Zealand. J. Veg. Sci. 3, 603-616.
70. Leathwick, J.R., Whitehead, D., McLeod, M., 1996. Predicting changes in the composition of New Zealand's indigenous forests in response to global warming: A modelling approach. Environ. Software 11, 81-90.
71. Leathwick, J.R., Burns, B.R., Clarkson, B.D., 1998. Environmental correlates of tree alpha-diversity in New Zealand primary forests. Ecography 21, 235-246.
72. Leps, J., Michalek, J., Rauch, O., Uhlik, P., 2000. Early succession on plots with the upper soil horizon removed. J. Veg. Sci. 11, 259-264.
73. McCullagh, P., Nelder, J.A., 1989. Generalized Linear Models, Second Ed.. Chapman & Hall, London.
74. Malanson, G.P., Westman, W.E., Van, Y.-L., 1992. Realized versus fundamental niche functions in a model of chaparral response to climatic change. Ecol. Model. 64, 261-277.
75. Margules, C.R., Nicholls, A.O., Austin, M.P., 1987. Diversity of Eucalyptus species predicted by a multi variables environmental gradient. Oecologia 71, 229-232.
76. McGlone, M.S., Mildenhall, D.C., Pole, M.S., 1996. History and palaeoecology of New Zealand Nolkofagus forests. In: Veblin, T.T., Hill, R.S., Read, J. (Eds.), The Ecology and Biogeagraphy of Nothofagus Forests. Yale University Press, New Haven, pp. 83-130.
77. Meentemeyer, R.K., Moody, A., Franklin, J., 2001. Landscape-scale patterns of shrub-species abundance in California chaparral: The role of topographically mediated resource gradients. Plant Ecol. 156, 19-41.
78. Minchin, P.R., 1987. Simulation of multidimensional community patterns: Towards a comprehensive model. Vegetatio 71, 145-156.
79. Minchin, P.R., 1989. Montane vegetation of the Mt. Field Massif, Tasmania: A test of some hypotheses about properties of community patterns. Vegetatio 83, 97-110.
80. Mueller-Dombois, D., Ellenberg, H., 1974. Aims and Methods of Vegetation Ecology. Wiley, New York, p. 547.
81. Naeem, S., Hakansson, K., Lawton, J.H., Crawley, M.J., Thompson, L.J., 1996. Biodiversity and plant productivity in a model assemblage of plant species. Oikos 76, 259-264.
82. Naeem, S., Thompson, L.J., Lawler, S.P., Lawton, J.H., Woodfin, R.M., 1994. Declining biodiversity can alter the performance of ecosystems. Nature 368, 734-737.
83. O'Connor, R.J., 2001. The conceptual basis of species distribution modelling; time for paradigm shift. In: Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M., Wall, B. (Eds.), Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Covelo, CA, pp. 25-33.
84. O'Connor, R.J., Jones, M.T., White, D., Hunsaker, C., Loveland, T., Jones, B., Preston, E., 1996. Spatial partitioning of the environmental correlates of avian biodiversity in the lower United States. Biodivers. Lett. 3, 97-110.
85. Oksanen, J., 1997. Why the beta-function cannot be used to estimate skewness of species responses. J. Veg. Sci. 8, 147-152.
86. Oksanen, J., Minchin, P.R., 2002. Continuum theory revisited: what shape are species responses along ecological gradients? Ecol. Model. 157 (213), 119-129.
87. Palmer, M.W., 1993. Putting things in even better order: The advantages of canonical correspondence analysis. Ecology 74, 2215-2230.
88. Partel, M., Zobel, M., Zobel, K., van der Maarel, E., 1996. The species pool and its relation to species richness: Evidence from Estonian plant communities. Oikos 75, 111-117.
89. Pausas, J.G., 1994. Species richness patterns in the understory of Pyrenean Pinus sylvestris forests. J. Veg. Sci. 5, 517-524.
90. Pausas, J.G., Austin, M.P., 2001. Patterns of plant species richness in relation to different environments: an appraisal. J. Veg. Sci. 12, 153-166.
91. Pereira, J.M.C., Itami, R.M., 1991. GIS-based habitat modeling using logistic multiple regression: A study of the MT. Graham Red Squirrel. PERS 57, 1475-1486.
92. Pulliam, H.R., 1988. Sources, sinks, and population regulation. Am. Nat. 132, 652-661.
93. Ricklefs, R.B., Schluter, D. (Eds.), Species Diversity in Ecological Communities: Historical and Geographical Perspectives. University Chicago Press, Chicago 1993.
94. Rosenzweig, M.L., 1995. Species Diversity in Space and Time. Cambridge University Press, Cambridge, UK.
95. Scott, J.M., Heglund, P.J., Samson, F., Haufler, J., Morrison, M., Raphael, M., Wall, B., 2002. Predicting Species Occurrences: Issues of Accuracy and Scale. Island Press, Covelo, CA, pp. 868.
96. Sokal, R.R., Rohlf, F.J., 1981. Biometry The Principles and Practice of Statistics in Biological Research, Second Ed.. W.H. Freeman, San Francisco.
97. Ter Braak, C.J.F., 1985. Correspondence analysis of incidence and abundance data: properties in terms of a unimodal response model. Biometrics 41, 859-873.
98. Ter Braak, C.J.F., 1986. Canonical correspondence analysis: A new eigenvector technique for multivariate direct gradient analysis. Ecology 67, 1167-1179.
99. Ter Braak, C.J.F., 1987. The analysis of vegetation-environment relationships by canonical correspondence analysis. Vegetatio 69, 69-77.
100. Ter Braak, C.J.F., Juggins, S., 1993. Weighted averaging partial least squares regression (WA-PLS): An improved method for reconstructing environmental variables from species assemblages. Hydrobiologia 269/270, 485-502.
101. Ter Braak, C.J.F., Verdonschot, P.F.M., 1995. Canonical correspondence analysis and related multivariate methods in aquatic ecology. Aquat. Sci. 57, 253-287.
102. Ter Braak, C.J.F., Juggins, S., Birks, H.J.B., van der Voel, H., 1993. Weighted averaging partial least squares regression (WA-PLS); Definition and comparison with other methods for species-environment calibration. In: Patil, G.P., Rao, C.R. (Eds.), Multivariate Environmental Statistics, North-Holland Series in Statistics and Probability, vol. 6, pp. 525-560.
103. Tilman, D., Wedin, D., Knops, J., 1996. Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature 379, 718-720.
104. Tilman, D., Knops, J., Wedin, D., Reich, P., Ritchie, M., Siemann, E., 1997. The influence of functional diversity and composition on ecosystem processes. Science 277, 1300-1302.
105. Vayssieres, M.P., Plant, R.E., Allen-Diaz, B.H., 2000. Classification trees: an alternative non-parametric approach for predicting species distributions. J. Veg. Sci. 11, 679-694.
106. Watkinson, A.R., 1985. On the abundance of species along an environmental gradient. J. Ecol. 73, 569-578.
107. Watkinson, A.R., Sutherland, W.J., 1995. Sources, sinks and pseudo-sinks. J. Anim. Ecol. 64, 126-130.
108. Weir, I.S., Pettit, A.N., 2000. Binary probability maps using a hidden conditional autoregressive Gaussian process with an application to Finnish common toad data. Appl. Stat. 49, 473-484.
109. Westhoff, V., van der Maarel, E., 1978. The braun-blanquet approach. In: Whittaker, R.H. (Ed.), Classification of Plant Communities, Second Ed.. Junk, The Hague, pp. 287-399.
110. Wu, H., Huffer, F.W., 1997. Modelling the distribution the distribution of plant species using the autologistic regression model. Environ. Ecol. Stat. 4, 49-64.
111. Yce, T.W., Mitchell, N.D., 1991. Generalized additive models in plant ecology. J. Veg. Sci. 2, 587-602.