GRASP: Generalized regression analysis and spatial prediction

Ecological Modelling

Volumn 157, Issue 2-3, 2002, Pages 189-207

  Lehmann, Anthony ^b   Overton, Jacob McC ^a   Leathwick, John R ^a  

^a LANDCARE RESEARCH   (New Zealand)

^b Centre Suisse de Cartographie de la Faune   (Switzerland)

Author keywords

Biodiversity; Ferns; Generalized additive models; Geographic information systems; New Zealand; Spatial prediction; Sustainable management

Indexed keywords

ECOLOGICAL MODELING; PREDICTION; REGRESSION ANALYSIS; SPATIAL DISTRIBUTION;

CYATHEA; FILICOPHYTA;

EID: 0037202453     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3800(02)00195-3     Document Type: Article

References (53)

1. Allen, R.B., 1992. RECCE an Inventory Method for Describing New Zealand Vegetation. Forest Research Institute, Christchurch, p. 25.
2. Austin, M.P., 1999a. The potential contribution of vegetation ecology to biodiversity research. Ecography 22, 465-484.
3. Austin, M.P., 1999b. A silent clash of paradigms: Some inconsistencies in community ecology. Oikos 86, 170-178.
4. Austin, M.P., 2002. Spatial prediction of species distribution: An interface between ecological theory and statistical modeling. Ecol. Model. 157 (2-3), 101-118.
5. Austin, M.P., Graywood, M.J., 1994. Current problems of environmental gradients and species response curves in relation to continuum theory. J. Veg. Sci. 5, 473-482.
6. Austin, M.P., Meyers, J.A., 1996. Current approaches to modeling the environmental niche of eucalypts: Implication for management of forest biodiversity. Forest Ecol. Manage. 85, 95-106.
7. Austin, M.P., Smith, T.M., 1989. A new model for the continuum concept. Vegetation 83, 35-47.
8. Bio, A.M.F., 2000. Does Vegetation Suit our Models? Data and Model Assumptions and the Assessment of Species Distribution in Space. Ph.D. thesis, Utrecht University.
9. Bio, A.M.F., Alkemade, R., Barendregt, A., 1998. Determining alternative models for vegetation response analysis: A non parametric approach. J. Veg. Sci. 9, 5-16.
10. Breiman, L.J., Freidman, J., Olshen, R., Stone, C., 1984. Classification and Regression Trees. Wadsworth, Belmont, CA.
11. Brosse, S., Lek, S., 2000. Modelling roach (Rutilus rutilus) microhabitat using linear and nonlinear techniques. Freshwater Biol. 44, 441-452.
12. Cawsey, E.M., Austin, M.P., Baker, B.L., 2002. Regional vegetation mapping in Australia: A case study in the practical use of statistical modeling. Biodivers. Conserv. 11, 2239-2274.
13. Chambers, J.M., Hastie, T.J., 1993. Statistical Models. Chapman & Hall, London, p. 608.
14. Draper, N.R., Smith, H., 1981. Applied Regression Analysis. Wiley, New York, p. 709.
15. Ferrier, S. Drielsma, M., Manion, G., Watson, G. 2002b. Extended Statistical Approaches to Modeling Spatial Pattern in Biodiversity: The North-east New South Wales Experience. II. Community-level Modeling, 11, 2309-2338.
16. Ferrier, S., Watson, G., Pearce, J. Drielsma, M., 2002b. Extended Statistical Approaches to Modeling Spatial Pattern in Biodiversity: The North-east New South Wales Experience. I. Species-level Modeling, 11, 2275-2307.
17. Fielding, A.H., Bell, J.F., 1997. A review of methods for the assessment of prediction errors in conservation presence/ absence models. Environ. Conserv. 24, 38-49.
18. Franklin, J., 1995. Predictive vegetation mapping: Geographical modeling of biospatial patterns in relation to environmental gradients. Prog. Phys. Geogr. 19, 474-499.
19. Franklin, J., 1998. Predicting the distribution of shrub species in southern California from climate and terrain-derived variables. J. Veg. Sci. 9, 733-748.
20. Guisan, A., Theurillat, J.-P., 2000. Equilibrium modeling of alpine plant distribution and climate change: How far can we go? Phytocoenologia 30, 353-384.
21. Guisan, A., Zimmermann, N.E., 2000. Predictive habitat distribution models in ecology. Ecol. Model. 135, 147-186.
22. Guisan, A., Theurillat, J.-P., Kienast, F., 1998. Predicting the potential distribution of plant species in an alpine environment. J. Veg. Sci. 9, 65-74.
23. Hastie, T.J., Tibshirani, R.J., 1990. Generalized Additive Models. Chapman & Hall, London, p. 335.
24. Hirzel, A.H., Hausser, J., Perrin, N., 2002. Ecological-niche factor analysis: How to compute habitat-suitability maps without absence data? Ecology, in press.
25. Hosmer, D.W.J., Lemeshow, S., 1989. Assessing the fit of the model. In: Applied Logistic Regression. Wiley, New York.
26. Hutchinson, M.F., Gessler, P.E., 1994. Splines - More than just a smooth interpolator. Geoderma 62, 45-67.
27. Iverson, L.R., Prasad, A., 1998. Estimating regional plant biodiversity with GIS modeling. Divers. Distrib. 4, 49-61.
28. Leathwick, J.R., 1998. Are New Zealand's Nothofagus species in equilibrium with their environment. J. Veg. Sci. 9, 719-732.
29. Leathwick, J.R., 2001. New Zealand's potential forest pattern as predicted from current species-environment relationships. New Zealand J. Botany 39, 447-464.
30. Leathwick, J.R., Austin, M.P., 2001. Competitive interactions between tree species in New Zealand's old growth indigenous forests. Ecology 82, 2560-2573.
31. Leathwick, J.R., Stephens, R.T.T., 1998. Climate Surfaces for New Zealand. Contract Report LC9798/126, Landcare Research, Hamilton.
32. Leathwick, J.R., Whitehead, D., 2001. Soil and atmospheric water deficits, and the distributions of New Zealand's indigenous tree species. Funct. Ecol. 15, 233-242.
33. 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.
34. Leathwick, J.R., 2002. Incorporating the effects of inter-specific competition when modeling species distributions at landscape scales. Biodivers. Conserv., in press.
35. Leathwick, J.R., Whitehead, D., McLeod, M., 1996. Predicting changes in the composition of New Zealand's indigenous forests in response to global warning: A modeling approach. Environ. Software 11, 81-90.
36. Lehmann, A., 1998. GIS modeling of submerged macrophyte distribution using generalized additive models. Plant Ecol. 139, 113-124.
37. Lehmann, A., Jaquet, J.-M., Lachavanne, J.-B., 1997. A GIS approach of aquatic plant spatial heterogeneity in relation to sediment and depth gradient, Lake Geneva, Switzerland. Aquat. Bot. 347-361.
38. Lehmann, A., Overton, J.McC., Leathwick, J.R., 1999. GRASP: Generalized Regression Analysis and Spatial Predictions, User's Manual. Landcare Research, Hamilton, New Zealand.
39. Lehmann, A., Leathwick, J.R., Overton, J.McC., 2002. Assessing New Zealand fern diversity from spatial predictions of species assemblages. Biodivers. Conserv. 11, 2217-2238.
40. McCullagh, P., Nelder, J.A., 1997. Generalized linear models. Monographs on Statistics and Applied Probability. Chapman & Hall, London, p. 511.
41. McKenzie, N.J., Ryan, P.J., 1999. Spatial prediction of soil properties using environmental correlation. Geoderma 89, 67-94.
42. Narumalani, S., Jensen, J.R., Althausen, J.D., Burkhalter, S.G., Mackey, H., 1997. Aquatic macrophyte modeling using GIS and logistic multiple regression. Photogramm. Eng. Remote Sens. 63, 41-49.
43. Newsome, P.F.J., 1992. New Zealand Resource Inventory. ARC/INFO data manual, DSIR.
44. Overton, J.McC., Leathwick, J.R., Lehmann, A., 2000. Predict first, classify later - A new paradigm of spatial classification for environmental management: A revolution in the mapping of vegetation, soil, land cover, and other environmental information. In: Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Banff, Alta., Canada.
45. Overton, J.McC., Leathwick, J.R., Stephens, R.T.T., Lehmann, A., 2002. Information pyramids for informed ecosystem management. Biodivers. Conserv. 11, 2093-2116.
46. Peters, D., Thackway, R., 1998. A New Biogeographic Regionalisation for Tasmania. Tasmanian Parks and Wildlife Service GIS Section.
47. Ray, N., Lehmann, A., Joly, P., 2002. Modelling spatial distribution of amphibian populations: A GIS approach based on habitat matrix permeability. Biodivers. Conserv. 11, 2243-2265.
48. Wiser, S.K., Bellingham, P.J., Burrows, L.E., 2001. Managing biodiversity information: Development of New Zealand's National Vegetation Survey databank. New Zealand J. Ecol. 25, 1-17.
49. Wolgemuth, T., 1998. Modelling floristic richness on a regional scale: A case study in Switzerland. Biodivers. Conserv. 7, 159-177.
50. Wood, S.N., 2000. Modelling and smoothing parameter estimation with multiple quadratic penalties. J. R. Stat. Soc. 62, 413-428.
51. Yee, T.W., Mitchell, N.D., 1991. Generalized additive models in plant ecology. J. Veg. Sci. 2, 587-602.
52. Yee, T.W., Mackenzie, M., 2002. Vector generalized additive models plant ecology. Ecol. Model. 157 (2-3), 141-156.
53. Zaniewski, A.E., Lehmann, A., Overton, J.McC., 2002. Predicting species distribution using presence-only data: A case study of native New Zealand ferns. Ecol. Model. 157 (2-3), 259-278.