Comparison of predictor sets for species richness and the number of rare species of butterflies and birds

Journal of Biogeography

Volumn 34, Issue 1, 2007, Pages 90-101

  Thomson, James R ^a   Fleishman, Erica ^b,d   Mac Nally, Ralph ^a   Dobkin, David S ^c  

^a MONASH UNIVERSITY   (Australia)

^b STANFORD UNIVERSITY   (United States)

^c High Desert Ecological Research Institute   (United States)

^d NATIONAL CENTER FOR ECOLOGICAL ANALYSIS AND SYNTHESIS   (United States)

Author keywords

Bayesian model averaging; Biodiversity surrogates; Great Basin; Indicator species; Predictive modelling; Rarity; Remote sensing; Topoclimate; Vegetation composition; Vegetation structure

Indexed keywords

BIRD; BUTTERFLY; COMMUNITY COMPOSITION; COMPARATIVE STUDY; GIS; NUMERICAL MODEL; PREDICTION; RARE SPECIES; SATELLITE DATA; SATELLITE IMAGERY; SPECIES RICHNESS; VEGETATION STRUCTURE;

BASIN AND RANGE PROVINCE; GREAT BASIN; NEVADA; NORTH AMERICA; SHOSHONE MOUNTAINS; TOIYABE RANGE; TOQUIMA RANGE; UNITED STATES;

AVES; PAPILIONOIDEA;

EID: 33845612826     PISSN: 03050270     EISSN: 13652699     Source Type: Journal    
DOI: 10.1111/j.1365-2699.2006.01576.x     Document Type: Article

References (80)

1. Anderson, S.H. & Shugart, H.H. (1974) Habitat selection of breeding birds in an east Tennessee deciduous forest. Ecology, 55, 828-837.
2. Betrus, C.J. (2002) Refining the umbrella index complex: an application to bird and butterfly communities in montane canyons in the Great Basin. M.S. Thesis, Miami University, Oxford, OH.
3. Bibby, C.J., Burgess, N.D., Hill, D.A. & Mustoe, S. (2000) Bird census techniques. Academic Press, London.
4. Brown, J.H. (1984) On the relationship between abundance and distribution of species. The American Naturalist, 124, 255-279.
5. Buckland, S.T., Anderson, D.R., Burnham, K.P., Laake, J.L., Borchers, D.L. & Thomas, L. (2001) Introduction to distance sampling: estimating abundance of biological populations. Oxford University Press, New York.
6. Burgman, M.A., Lindenmayer, D.B. & Elith, J. (2005) Managing landscapes for conservation under uncertainty. Ecology, 86, 2007-2017.
7. Burnham, K.P. & Anderson, D.R. (2004) Multimodel inference: understanding AIC and BIC in model selection. Sociological Methods and Research, 33, 261-304.
8. Chaplin, S.J., Gerrard, R.A., Watson, H.M., Master, L.L. & Flack, S.R. (2000) The geography of imperilment: targeting conservation toward critical biodiversity areas. Precious heritage: the status of biodiversity in the United States (ed. by B.A. Stein, L.S. Kutner and J.S. Adams), pp. 159-199. Oxford University Press, Oxford.
9. Dobkin, D.S. & Rich, A.C. (1998) Comparison of line-transect, spot-map, and point-count surveys for birds in riparian areas of the Great Basin. Journal of Field Ornithology, 69, 430-443.
10. Dobkin, D.S. & Wilcox, B.A. (1986) Analysis of natural forest fragments: riparian birds in the Toiyabe Mountains, Nevada. Wildlife 2000: modelling habitat relationships of terrestrial vertebrates (ed. by J. Verner, M.L. Morrison and C.J. Ralph), pp. 293-299. University of Wisconsin Press, Madison, WI.
11. Efron, B. & Tibshirani, R.J. (1993) An introduction to the bootstrap. Chapman and Hall, London.
12. Efron, B. & Tibshirani, R.J. (1997) Improvements on cross-validation: the 632+ bootstrap method. Journal of the American Statistical Association, 92, 548-560.
13. Faith, D.P., Nix, H.A., Margules, C.R., Hutchinson, M.F., Walker, P.A., West, J., Stein, J., Kesteven, J.L., Allison, A. & Natera, G. (2001) The BioRap biodiversity assessment and planning study for Papua New Guinea. Pacific Conservation Biology, 6, 279-288.
14. Fleishman, E., Austin, G.T. & Murphy, D.D. (1997) Natural history and biogeography of the butterflies of the Toiyabe Range, Nevada (Lepidoptera: Hesperioidea and Papilionoidea). Holarctic Lepidoptera, 4, 1-18.
15. Fleishman, E., Fay, J.P. and Murphy, D.D. (2000) Upsides and downsides: contrasting topographic gradients in species richness and associated scenarios for climate change. Journal of Biogeography, 27, 1209-1219.
16. Fleishman, E., Mac Nally, R., Fay, J.P. & Murphy, D.D. (2001) Modeling and predicting species occurrence using broad-scale environmental variables: an example with butterflies of the Great Basin. Conservation Biology, 15, 1674-1685.
17. Fleishman, E., Betrus, C.J., Blair, R.B., Mac Nally, R. & Murphy, D.D. (2002) Nestedness analysis and conservation planning: the importance of place, environment, and life history across taxonomic groups. Oecologia, 133, 78-89.
18. Fleishman, E., Thomson, J.R., Mac Nally, R., Murphy, D.D. & Fay, J.P. (2005) Predicting species richness of multiple taxonomic groups using indicator species and genetic algorithms. Conservation Biology, 19, 1125-1137.
19. Fleishman, E., Noss, R.F. & Noon, B.R. (2006) Utility and limitations of species richness metrics for conservation planning. Ecological Indicators, 6, 543-553.
20. Freitag, S., van Jaarsveld, A.S. & Biggs, H.C. (1997) Ranking priority biodiversity areas: an iterative conservation value-based approach. Biological Conservation, 82, 263-272.
21. Friedman, J.H. (1991) Multivariate adaptive regression splines (with discussion). Annals of Statistics, 19, 1-141.
22. Furnival, G.M. & Wilson, R.W. (1974) Regression by leaps and bounds. Technometrics, 16, 499.
23. Gaston, K.J. (1994) Rarity. Chapman and Hall, London.
24. Guisan, A. & Thuiller, W. (2005) Predicting species distributions: offering more than simple habitat models. Ecology Letters, 8, 993-1009.
25. Gustafsson, L. (2000) Red-listed species and indicators: vascular plants in woodland key habitats and surrounding production forests in Sweden. Biological Conservation, 92, 35-43.
26. Hastie, T., Tibshirani, R., Leisch, F., Hornik, K. & Ripley, B.D. (2005) mda: mixture and flexible discriminant analysis, R package version 0.2-27. Available from http://www.r-project.org (accessed August 2005).
27. Hawkins, B.A., Field, R., Cornell, H.V., Currie, D.J., Guégan, J.-F., Kaufman, D.M., Kerr, J.T., Mittelbach, G.G., Oberdorff, T., O'Brien, E.M., Porter, E.E. & Turner, J.R.G. (2003) Energy, water, and broad-scale geographic patterns of species richness. Ecology, 84, 3105-3117.
28. Hodkinson, I.D. & Jackson, J.K. (2005) Terrestrial and aquatic invertebrates as bioindicators for environmental monitoring, with particular reference to mountain ecosystems. Environmental Management, 25, 649-666.
29. Hoeting, J.A., Madigan, D., Raftery, A.E. & Volinsky, C.T. (1999) Bayesian model averaging: a tutorial. Statistical Science, 14, 382-417.
30. Hoving, C.L., Harrison, D.J., Krohn, W.B., Joseph, R.A. & O'Brien, M. (2005) Broad-scale predictors of Canada lynx occurrence in eastern North America. Journal of Wildlife Management, 69, 739-751.
31. Janzen, D.H., Ataroff, M., Farinas, M., Reyes, S., Rincón, N., Soler, A., Soriano, P. & Vera, M. (1976) Changes in the arthropod community along an elevational transect in the Venezuelan Andes. Biotropica, 8, 193-203.
32. Jetz, W. & Rahbek, C. (2002) Geographic range size and determinants of avian species richness. Science, 297, 1548-1551.
33. Landres, P.B., Verner, J. & Thomas, J.W. (1988) Ecological uses of vertebrate indicator species: a critique. Conservation Biology, 2, 316-328.
34. Lawler, J.J., White, D., Sifneos, J.C. & Master, L.L. (2003) Rare species and the use of indicator groups for conservation planning. Conservation Biology, 16, 936-947.
35. Leathwick, J.R., Rowe, D., Richardson, J., Elith, J. & Hastie, T. (2005) Using multivariate adaptive regression splines to predict the distributions of New Zealand's freshwater diadromous fish. Freshwater Biology, 50, 2034-2052.
36. Lee, P.-Y. & Rotenberry, J.T. (2005) Relationships between bird species and tree species assemblages in forested habitats of eastern North America. Journal of Biogeography, 32, 1139-1150.
37. Link, W.A. & Sauer, J.R. (1998) Estimating population change from count data: application to the North American Breeding Bird Survey. Ecological Applications, 8, 258-268.
38. Mac Nally, R. & Fleishman, E. (2004) A successful predictive model of species richness based on indicator species. Conservation Biology, 18, 646-654.
39. Mac Nally, R., Bennett, A.F. & Horrocks, G. (2000) Forecasting the impacts of habitat fragmentation. Evaluation of species-specific predictions of the impact of habitat fragmentation on birds in the box-ironbark forests of central Victoria, Australia. Biological Conservation, 95, 7-29.
40. Mac Nally, R., Fleishman, E., Fay, J.P. & Murphy, D.D. (2003) Modelling butterfly species richness using mesoscale environmental variables: model construction and validation for mountain ranges in the great basin of western North America. Biological Conservation, 110, 21-31.
41. Mac Nally, R., Fleishman, E., Bulluck, L. & Betrus, C. (2004) Comparative influence of spatial scale on beta diversity within regional assemblages of birds and butterflies. Journal of Biogeography, 31, 917-929.
42. MacArthur, R.W., Recher, H. & Cody, M.L. (1966) On the relation between habitat selection and species diversity. The American Naturalist, 100, 319-332.
43. MacKenzie, D.I., Nichols, J.D., Royle, J.A., Pollock, K.H., Bailey, L.L. & Hines, J.E. (2006) Occupancy estimation and modeling: inferring patterns and dynamics of species occurrence. Elsevier, Burlington, MA.
44. McCullagh, P. & Nelder, J.A. (1989) Generalized linear models, 2nd edn. Chapman and Hall, London.
45. Moore, J.L., Balmford, A., Brooks, T., Burgess, N., Hansen, L.A., Rahbek, C. & Williams, P.H. (2003) Performance of sub-Saharan vertebrates as indicator groups for identifying priority areas for conservation. Conservation Biology, 17, 207-218.
46. Myers, N., Mittermeier, R.A., Mittermeier, C.G., da Fonesca, G.A.B. & Kent, J. (2000) Biodiversity hotspots for conservation priorities. Nature, 403, 853-858.
47. Noon, B.R. (1981) Techniques for sampling avian habitats. The use of multivariate statistics in studies of wildlife habitat (ed. by D.E. Capen), USDA Forest Service General Technical Report RM-89, pp. 42-52. Rocky Mountain Forest and Range Experimental Station, Fort Collins, CO.
48. Noss, R.N. & Cooperrider, A.Y. (2004) Saving nature's legacy. Island Press, Washington DC.
49. Orme, C.D.L., Davies, R.G., Burgess, M., Eigenbrod, F., Pickup, N., Olson, V.A., Webster, A.J., Ding, T., Rasmussen, P.C., Ridgely, R.S., Stattersfield, A.J., Bennett, P.M., Blackburn, T.M., Gaston, K.J. & Owens, I.P.F. (2005) Global hotspots of species richness are not congruent with endemism or threat. Nature, 436, 1016-1019.
50. Patterson, B.D. & Atmar, W. (1986) Nested subsets and the structure of insular mammalian faunas and archipelagos. Biological Journal of the Linnean Society, 28, 65-82.
51. Pearson, D.L. (1994) Selecting indicator taxa for the quantitative assessment of biodiversity. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences, 345, 75-79.
52. Pickett, S.T.A., Cadenasso, M.L., Grove, J.M., Nilon, C.H., Pouyat, R.V., Zipperer, W.C. & Costanza, R. (2001) Urban ecological systems: linking terrestrial ecological, physical, and socioeconomic components of metropolitan areas. Annual Review of Ecology and Systematics, 32, 127-157.
53. Pollard, E. & Yates, T.J. (1993) Monitoring butterflies for ecology and conservation. Chapman and Hall, London.
54. Pressey, R.L., Hager, T.C., Ryan, K.M., Schwarz, J., Wall, S., Ferrier, S. & Creaser, P.M. (2000) Using abiotic data for conservation assessments over extensive regions: quantitative methods applied across New South Wales, Australia. Biological Conservation, 96, 55-82.
55. Pullin, A.S. (ed.) (1995) Ecology and conservation of butterflies. Chapman and Hall, London.
56. R Development Core Team (2005) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna [available from http://www.r-project.org (accessed August 2005)].
57. Raftery, A.E. (1995) Bayesian model selection in social research (with discussion). Sociological Methodology 1995 (ed. by P.V. Marsden), pp. 111-196. Blackwell, Cambridge, MA.
58. Raftery, A.E. & Zheng, Y.Y. (2003) Discussion: performance of Bayesian model averaging. Journal of the American Statistical Association, 98, 931-938.
59. Raftery, A.E., Madigan, D. & Hoeting, J.A. (1997) Bayesian model averaging for linear regression models. Journal of the American Statistical Association, 92, 179-191.
60. Raftery, A.E., Hoeting, J.A., Volinsky, C.T. & Painter, I. (2005) BMA: Bayesian model averaging, R package version 3.0. http://www.r-project.org, http://www.research.att.com/~volinsky/bma.html.
61. Robinson, S.K. & Holmes, R.T. (1984) Effects of plant species and foliage structure on the foraging behavior of forest birds. Auk, 101, 672-684.
62. Roughgarden, J., Running, S.W. & Matson, P.A. (1991) What does remote sensing do for ecology? Ecology, 76, 1918-1922.
63. Rouse, J.W., Haas, R.H., Schell, J.A. & Deering, D.W. (1973) Monitoring vegetation systems in the Great Plains with ERTS. Proceedings of the third ERTS symposium, pp. 309-317. National Aeronautics and Space Administration, Greenbelt, MD.
64. Scott, J.A. (1986) The butterflies of North America. Stanford University Press, Stanford, CA.
65. Scott, C.T. (1998) Sampling methods for estimating change in forest resources. Ecological Applications, 8, 228-233.
66. Scott, J.M., Csuti, B., Jacobi, J.D. & Estes, J.E. (1987) Species richness. BioScience, 37, 782-788.
67. Scott, J.M., Heglund, P.J., Morrison, M., Raphael, M., Haufler, J. & Wall, B. (eds.) (2002) Predicting species occurrences: issues of scale and accuracy. Island Press, Covello, CA.
68. Siegel, R.B., Desante, D.F. & Nott, M.P. (2001) Using point counts to establish conservation priorities: how many visits are optimal? Journal of Field Ornithology, 72, 228-235.
69. Stein, B.A., Kutner, L.S. & Adams, J.S. (eds) (2000) Precious heritage: the status of biodiversity in the United States. Oxford University Press, New York.
70. Stohlgren, T.J., Guenther, D.A., Evangelista, P.H. & Alley, N. (2005) Patterns of plant species richness, rarity, endemism, and uniqueness in an arid landscape. Ecological Applications, 15, 715-725.
71. Thomson, J.R., Fleishman, E., Mac Nally, R. & Dobkin, D.S. (2005) Influence of the temporal resolution of data on the success of indicator species models of species richness across multiple taxonomic groups. Biological Conservation, 124, 503-518.
72. Turner, W., Sterling, E.J. & Janetos, A.C. (2001) Contributions of remote sensing to biodiversity conservation: a NASA approach. Conservation Biology, 15, 832-834.
73. Viallefont, V., Raftery, A.E. & Richardson, S. (2001) Variable selection and Bayesian model averaging in case-control studies. Statistics in Medicine, 20, 3215-3230.
74. Weiss, S.B., Murphy, D.D. & White, R.R. (1988) Sun, slope, and butterflies: topographic determinants of habitat quality for Euphydryas editha. Ecology, 69, 1486-1496.
75. Wiens, J.A. & Rotenberry, J.T. (1981) Habitat associations and community structure of birds in shrubsteppe environments. Ecological Monographs, 51, 21-41.
76. Wintle, B.A., McCarthy, M.A., Volinsky, C.T. & Kavanagh, R.P. (2003) The use of Bayesian model averaging to better represent uncertainty in ecological models. Conservation Biology, 17, 1579-1590.
77. Wintle, B.A., Elith, J. & Potts, J.M. (2005) Fauna habitat modelling and mapping: a review and case study in the Lower Hunter Central Coast region of NSW. Australian Journal of Ecology, 30, 719-738.
78. Wright, D.H., Patterson, B.D., Mikkelson, G.M., Cutler, A. & Atmar, W. (1998) A comparative analysis of nested subset patterns of species composition. Oecologia, 113, 1-20.
79. Yeoman, F. & Mac Nally, R. (2005) The avifaunas of fragmented, periurban, coastal woodlands in south-eastern Australia. Landscape and Urban Planning, 72, 297-312.
80. Zabel, C.J., Dunk, J.R., Stauffer, H.B., Roberts, L.M., Mulder, B.S. & Wright, A. (2003) Northern spotted owl habitat models for research and management application in California (USA). Ecological Applications, 13, 1027-1040.