Comparison of resolution of methods used in mapping biodiversity patterns from point-occurrence data

Ecological Indicators

Volumn 3, Issue 3, 2003, Pages 213-221

  Stockwell, David ^a   Peterson, A Townsend ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF KANSAS   (United States)

Author keywords

Accuracy; Bias; Biodiversity; Birds; Map; Mexico; Prediction; Scale; Species composition; Species richness

Indexed keywords

DATA REDUCTION; GEOGRAPHIC INFORMATION SYSTEMS; VEGETATION;

SPECIES COMPOSITION;

BIODIVERSITY;

AVIFAUNA; BIODIVERSITY; PREDICTION; SPECIES OCCURRENCE; SPECIES RICHNESS;

MEXICO;

AVES;

EID: 0141958573     PISSN: 1470160X     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1470-160X(03)00045-1     Document Type: Article

References (30)

1. Alberch, P., 1993. Museums, collections and biodiversity inventories. Trends Ecol. Evol. 8 (10), 372-374.
2. Aspinall, R., Matthews, K., 1994. Climate change impact on distribution and abundance of wildlife species: an analytical approach using GIS. Environ. Pollut. 86, 217-223.
3. Austin, M.P., Nicholls, A.O., Margules, C.R., 1990. Measurement of the realized qualitative niche: environmental niches of five eucalyptus species. Ecol. Monogr. 60 (2), 161-177.
4. Colwell, R.K., Coddington, J.A., 1994. Estimating terrestrial biodiversity through extrapolation. Phil. Trans. Roy. Soc. London B 335, 101-118.
5. Escalante-Pliego, P., Navarro-Siguenza, A.G., Peterson, A.T., 1993. A geographic, historical, and ecological analysis of avian diversity in Mexico. In: Ramamoorthy, T.P., Bye, R., Lot, A., Fa. J. (Eds.), The Biological Diversity of Mexico, Part 1. Pac. Coast Avif. 29, 1-202.
6. Ferrier, S., Watson, G., 1996. An evaluation of the effectiveness of environmental surrogates and modelling techniques in predicting the distribution of biological diversity. Consultancy report to NSW National Parks and Wildlife Service. June 1996.
7. Franklin, J.F., 1993. Preserving biodiversity: species, ecosystems, or landscapes? (in forum: preserving biodiversity). Ecol. Appl. 3, 202-205.
8. Gaston, K.J., Blackburn, T.M., 1995. Mapping biodiversity using surrogates for species richness: macro-scales and New World birds. Proc. Roy. Soc. London B 262, 335-341.
9. Keitt, T.H., Urban, D.L., Milne, B.T., 1997. Detecting critical scales in fragmented landscapes. Conserv. Ecol. (online) 1 (1), 4. Available from the Internet. URL: http://www.consecol.org/vol1/iss1/art4.
10. Lande, R., 1996. Statistics and partitioning of species diversity, and similarity among multiple communities. Oikos 76, 5-13 (Copenhagen).
11. Miller, R.I. (Ed.), 1994. Mapping the Diversity of Nature. Chapman amp; Hall, London, 218 pp.
12. Nix, H.A., 1986. A biogeographic analysis of Australian elapid snakes. In: Longmore, R. (Ed.), Atlas of Elapid Snakes of Australia. Australian Flora and Fauna Series Number 7. Australian Government Publishing Service. Canberra, pp. 4-15.
13. Peterson, A.T., Cohoon, K.P., 1999. Sensitivity of distributional prediction algorithms to geographic data completeness. Ecol. Model. 117, 159-164.
14. Peterson, A.T., Slade, N.A., 1998. Extrapolating inventory results into biodiversity estimates and the importance of stoping rules. Diversity Distributions 4, 95-105.
15. Peterson, A.T., Watson, D.M., 1998. Problems with areal definitions of endemism: the effects of spatial scaling. Diversity Distributions 4, 189-194.
16. Peterson, A.T., Navarro-Siguenza, A.G., Benitez-Diez, H., 1998. The need for continued collecting a geographic analysis of Mexican bird specimens. IBIS 140, 288-294.
17. Ponder, W.F., 1992. Bias and biodiversity. Aust. Zool. 28, 47-51.
18. Scott, J.M., Jennings, M., Wright, R.G., Csuti, B., 1996a. Landscape approaches to mapping biodiversity. BioScience 46, 77-78.
19. Scott, J.M., Tear, T.H., Davis, F.W. (Eds.), 1996b. Gap Analysis: A landscape approach to biodiversity planning. American Society for Photogrammetry and Remote Sensing, Bethesda, Maryland. ISBN-1-57083-03603.
20. Soberon, J., Llorente, J., 1993. The use of species accumulation functions for the prediction of species richness. Conserv. Biol. 7 (3), 480-488.
21. Stockwell, D.R.B., 1999. Genetic Algorithms II. In: Fielding. A.M. (Ed.), Machine Learning Methods for Ecological Applications, Kluwer Academic Publishers, Boston, pp. 123-144.
22. Stockwell, D.R.B., Noble, I.R., 1992. Induction of sets of rules from animal distribution data: a robust and informative method of analysis. Math. Comput. Simul. 33, 385-390.
23. Stockwell, D.R.B., Peters, D.P., 1993. ERINYES. 18:8. Newsletter of the Environmental Information Resources Network.
24. Stockwell, D.R.B., Peters, D.P., 1999. The CARP modeling system: problems and solutions to automated spatial prediction. Int. J. Geogr. Inform. Syst. 13 (2), 143-158.
25. Stockwell, D.R.B., Peterson, A.T., 2001. Controlling bias during predictive modeling with museum data. In: Scott J.M., Heglund P.J., Morrison M., Raphael M., Haufler J., Wall B., Samson F. (Eds.), Predicting Species Occurrences: Issues of Scale and Accuracy. Island Press, Covelo, CA.
26. Stockwell, D.R.B., Townsend Peterson, A.T., 2002. Effects of sample size on accuracy of species distribution models. Ecol. Model. 148, 1-13.
27. Stoms, D.M., 1994. Scale dependence of species richness maps. Professional Geogr. 46, 346-358.
28. Stoms, D.M., Estes, J.E., 1993. A remote sensing research agenda for mapping and monitoring biodiversity, Int. J. Remote Sens. 1839-1860.
29. Walker, P.A., Cocks, K.D., 1991. Global Ecol. Biogeogr. Lett. 1, 108-118.
30. Wilson, E.O., 1988. Biodiversity. National Academy Press, Washington. DC.