Evaluating alternative data sets for ecological niche models of birds in the Andes

Ecography

Volumn 27, Issue 3, 2004, Pages 350-360

  Parra, Juan L ^a   Graham, Catherine C ^a   Freile, Juan F ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Fund Numashir Conservacion E   (Ecuador)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATE; CONSERVATION; ECOLOGY; NICHE; REMOTE SENSING; SPATIAL DISTRIBUTION;

ANDES; ECUADOR; SOUTH AMERICA;

AVES; GRALLARIA;

EID: 3042679179     PISSN: 09067590     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0906-7590.2004.03822.x     Document Type: Article

References (52)

1. Anderson, R. P., Gomez-Laverde, M. and Peterson, A. T. 2002. Geographical distributions of spiny pocket mice in South America: insights from predictive models. - Glob. Ecol. Biogeogr. 11: 131-141.
2. Anderson, R. P., Lew, D. and Peterson, A. T. 2003. Evaluating predictive models of species distributions: criteria for selecting optimal models. - Ecol. Modell. 162: 211-232.
3. Asrar, G. et al. 1984. Estimating absorbed photosynthetic radiation and leaf area index from spectral reflectance in wheat. - Agr. J. 76: 300-306.
4. Asner, G. P 2001. Cloud cover observation of the Brazilian Amazon. - Int. J. Remote Sens. 22: 3855-3862.
5. Berry, P. M. et al. 2002. Modelling potential impacts of climate change on the bioclimatic envelope of species in Britain and Ireland. - Glob. Ecol. Biogeogr. 11: 453-462.
6. Busby, J. R. 1991. BIOCLIM - A bioclimate analysis and prediction system. - In: Margules, C. R. and Austin, M. P. (eds), Nature conservation: cost effective biological surveys and data analysis. CSIRO. pp. 64-68.
7. Carpenter, G., Gillison, A. N. and Winter, J. 1993. DOMAIN: a flexible modeling procedure for mapping potential distributions of plants and animals. - Biodiv. Conserv. 2: 667-680.
8. Chong, D. L. S., Mougin, E. and Gastellu-Etchegorry, J. P. 1993. Relating the global vegetation index to net primary productivity and actual evapotranspiration over Africa. - Int. J. Remote Sens. 14: 1517-1546.
9. Faith, D. P. et al. 2001. The Biorap biodiversity assessment and planning study for Papua New Guinea. - Pacific Conserv. Biol. 4: 279-288.
10. Farber, O. and Kadmon, R. 2003. Assessment of alternative approaches for bioclimatic modeling with special emphasis on the Mahalanobis distance. - Ecol. Modell. 160: 115-130.
11. Fielding, A. H. 2002. What are the appropiate characteristics of an accuracy measure? - In: Scott, J. M. et al. (eds). Predicting species occurrences: issues of accuracy and scale. Island Press, pp. 271-279.
12. Fielding, A. H. and Bell, J. F. 1997. A review for the assessment of prediction errors in conservation presence/absence models. - Environ. Conserv. 24: 38-49.
13. Fjeldså, J. et al. 1997. Are biodiversity "hotspots" correlated with current ecoclimatic stability? A pilot study using the NOAA-AVHRR remote sensing data. - Biodiv. Conserv. 6: 401-422.
14. Freile, J. F. 2000. Patrones de distribución y sus implicaciones en la conservación de los géneros Grallaria y Grallaricula (Aves: Formicariidae) en Ecuador. PhD thesis, Dept of Biology, Pontificia Univ. Católica del Ecuador, Quito, Ecuador.
15. Fuentes, M. V., Malone, J. B. and Mas-coma, S. 2001. Validation of a mapping and prediction model for human fasciolosis transmission in Andean very high altitude endemic areas using remote sensing data. - Acta Tropica 79: 87-95.
16. Godown, M. E. and Peterson, A. T. 2000. Preliminary distributional analysis of US endangered bird species. - Biodiv. Conserv. 9: 1313-1322.
17. Green, R. H. 1979. Sampling design and statistical methods for environmental biologists. - Wiley.
18. Guisan, A. and Zimmermann, N. E. 2000. Predictive habitat distribution models in ecology. - Ecol. Modell. 135: 147-186.
19. Henricksen, B. L. and Durkin, J. W. 1986. Growing period and drought early warming in Africa using satellite data. - Int. J. Remote Sens. 7: 1583-1608.
20. Holben, B. N. 1986. Characteristics of maximum-value composite images from temporal AVHRR data. - Int. J. Remote Sens. 7: 1417-1434.
21. Holt, R. T. 2003. On the evolutionary ecology of species' ranges. - Evol. Ecol. Res. 5: 159-178.
22. Houlder, D. et al. 2000. ANUCLIM user's guide. Centre for Resource and Environmental Studies (CRES). - Australian National Univ., Canberra, Australia.
23. Huete, A. R. 1989. Soil influences in remotely sensed vegetation-canopy spectra. - In: Asrar, G. (ed.), Theory and applications of optical remote sensing. Wiley. pp. 107-141.
24. Hugall, A. et al. 2002. Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875). - Proc. Natl. Acad. Sci. USA 99: 6112-6117.
25. Hurlbert, A. H. and Haskell, J. P. 2003. The effect of energy and seasonally on avian species richness and community composition. - Am. Nat. 161: 83-97.
26. Hutchinson, M. F. 1991. Climatic analyses in data sparse regions. - In: Muchow, R. C. and Bellamy, J. A. (eds), Climatic risk in crop production. CAB, pp. 55-71.
27. Hutchinson, M. F. 1995. Interpolating mean rainfall using thin plate smoothing splines. - Int. J. GIS 9: 305-403.
28. Hutchinson, M. F. 1998. Interpolation of rainfall data with thin plate smoothing splines: 11 analysis of topographic dependence. - J. Geogr. Inf. Dec. Anal. 2: 168-185.
29. Hutchinson, M. F. 2000. Anusplin, ver. 4.1. User guide. - Centre for Resource and Environmental Studies, The Australian National Univ., Canberra, Australia.
30. Ichii, K., Kawabata, A. and Yamaguchi, Y. 2002. Global correlation analysis for NDVI and climatic variables and NDVI trends: 1982-1990. - Int. J. Remote Sens. 23: 3873-3878.
31. Joseph, L. and Stockwell, D. 2002. Climatic modeling of the distribution of some Pyrrhura parakeets of Northwestern South America with notes on their systematics and special reference to Pyrrhura caeruleiceps Todd, 1947. - Ornitol. Neotrop. 13: 1-8.
32. Krabbe, N. et al. 1998. An Atlas of avian diversity in the Ecuadorian Andes. - Centre for Research on Cultural and Biological Diversity of Andean Rainforests (DIVA). DIVA Tech. Rep. no. 4. Quito, Ecuador.
33. Landis, J. R. and Koch, G. C. 1977. The measurement of observer agreement for categorical data. - Biometrics 33: 159-174.
34. Lillesand, T. M. and Kiefer, R. W. 2000. Remote sensing and image interpretation. 4th edn. - Wiley.
35. Loiselle, B. A. et al. 2003. Avoiding pitfalls of using species distribution models in conservation planning. - Conserv. Biol. 17: 1591-1600.
36. Manel, S., Williams, H. C. and Ormerod, S. J. 2001. Evaluating presence-absence models in ecology: the need to account for prevalence. - J. Appl. Ecol. 38: 921-931.
37. New, M., Hulme, M. and Jones, P. 1999. Representing twentieth-century space-time climate variability. Part I: development of a 961-90 mean monthly terrestrial climatology. - J. Climate 12: 829-856.
38. Nix, H. A. 1986. A biogeographic analysis of Australian elapid snakes. - In: Anon. (ed.). Atlas of Australian elapid snakes. Bureau Flora Fauna, Canberra, Australia, pp. 4-15.
39. O'Connor, R. J. 2002, The conceptual basis of species distribution modeling: time for a paradigm shift? - In: Scott, J. M. et al. (eds). Predicting species occurences: issues of accuracy and scale. Island Press, pp. 25-33.
40. Oindo, B. O. 2002. Predicting mammal species richness and abundance usine multitemporal NDVI. - Photo. Engin. Rem. Sens. 68: 623-629.
41. Peterson, A. T. 2001. Predicting species geographic distributions based on ecological niche modeling. - Condor 103: 599-605.
42. Peterson, A. T., Stockwell, D. R. B. and Kluza, D. A. 2002. Distributional prediction based on ecological niche modeling of primary occurrence data. - In: Scott, J. M. et al. (eds). Predicting species occurences: issues of accuracy and scale. Island Press, pp. 617-623.
43. Peterson, A. T. and Robins, C. R. 2003. Using ecological niche modeling to predict barred owl invasions with implications for spotted owl conservation. - Conserv. Biol. 17: 1161-1165.
44. Renjifo, L. M. et al. 1997. Patterns of species composition and endemism in the northern Neotropics: a case for conservation of montane avifaunas. - Ornit. Monographs 48: 577-594.
45. Richard, Y. and Poccard, I. 1998. A statistical study of NDVI sensitivity to seasonal and interannual variations in Southern Africa. - Int. J. Remote Sens. 19: 2907-2920.
46. Ridgely, R. S. and Tudor, G. 1994. The birds of South America. vol. I: the oscine passerines. - Univ. of Texas Press.
47. Sánchez-Cordero, V. and Martinez-Meyer, E. 2000. Museum specimen data predict crop damage by tropical rodents. - Proc. Natl. Acad. USA 97: 7074-7077.
48. Stockwell, D. R. B. and Noble, I. R. 1991. Induction of sets of rules from animal distribution data: a robust and informative method of data analysis. Math. Comp. Sim. 32: 249-254.
49. Sierra, R. 1999. Propuesta preliminar de un sistema de clasificación de vegetación para el Ecuador continental. - Proyecto Inefan/Gef-Birf y EcoCiencia. Quito. Ecuador
50. Sierra, R., Campos, F. and Chamberlin, J. 2002. Assessing biodiversity conservation priorities: ecosystem risk and representativeness in continental Ecuador. - Landsc. Urban Plann. 59: 95-110.
51. Zar, J. H. 1996. Biostatistical analysis. 3rd ed. - Prentice Hall.
52. Zinner, D., Peláez, F. and Tokler, F. 2002. Distribution and habitat of grivet monkeys (Cercopithecus aethiops aethiops) in eastern and central Eritrea. - Afr. J. Ecol. 40: 151-158.