Effects of spatial scale and choice of statistical model (linear versus tree-based) on determining species-habitat relationships

Canadian Journal of Fisheries and Aquatic Sciences

Volumn 69, Issue 12, 2012, Pages 2095-2111

  Sharma, Sapna ^a,c   Legendre, Pierre ^a   Boisclair, Daniel ^a   Gauthier, Stéphane ^b,d  

^a UNIVERSITÉ DE MONTRÉAL   (Canada)

^b NATIONAL INSTITUTE OF WATER AND ATMOSPHERIC RESEARCH   (New Zealand)

^c YORK UNIVERSITY   (Canada)

^d INSTITUTE OF OCEAN SCIENCES   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EIGENVALUE; GPS; HABITAT QUALITY; HABITAT SELECTION; HABITAT STRUCTURE; HETEROGENEITY; LAKE ECOSYSTEM; POPULATION DENSITY; SPECIES-AREA RELATIONSHIP; UNDERWATER ENVIRONMENT;

CANADA; LAURENTIAN MOUNTAINS; QUEBEC [CANADA];

EID: 84870995971     PISSN: 0706652X     EISSN: 12057533     Source Type: Journal    
DOI: 10.1139/cjfas-2011-0505     Document Type: Article

References (79)

1. Anderson-Sprecher, R. 1994. Model comparisons and R2. Am. Sci. 48: 113-117.
2. Araújo, M.B., and New, M. 2007. Ensemble forecasting of species distributions. Trends Ecol. Evol. 22(1): 42-47. doi:10.1016/ j.tree.2006.09.010. PMID:17011070
3. Bellehumeur, C., and Legendre, P. 1997. Aggregation of sampling units: an analytical solution to predict variance. Geogr. Anal. 29(3): 258-266. doi:10.1111/j.1538-4632.1997.tb00961.x
4. Bellehumeur, C., Legendre, P., and Marcotte, D. 1997. Variance and spatial scales in a tropical rain forest: changing the size of sampling units. Plant Ecol. 130(1): 89-98. doi:10.1023/A: 1009763830908.
5. Blanchet, F.G., Legendre, P., and Borcard, D. 2008. Forward selection of explanatory variables. Ecology, 89(9): 2623-2632. doi: 10.1890/07-0986.1. PMID:18831183
6. Borcard, D., and Legendre, P. 2002. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol. Model. 153(1-2): 51-68. doi:10.1016/S0304-3800(01)00501-4
7. Borcard, D., Legendre, P., Avois-Jacquet, C., and Tuomisto, H. 2004. Dissecting the spatial structure of ecological data at multiple scales. Ecology, 85(7): 1826-1832. doi:10.1890/03-3111
8. Bouchard, J., and Boisclair, D. 2008. The relative importance of local, lateral, and longitudinal variables on the development of habitat quality models for a river. Can. J. Fish. Aquat. Sci. 65(1): 61-73. doi:10.1139/f07-140
9. Boyce, M.S., Vernier, P.R., Nielsen, E., and Schmiegelow, F.K.A. 2002. Evaluating resource selection functions. Ecol. Model. 157(2-3): 281-300. doi:10.1016/S0304-3800(02)00200-4
10. Breiman, L. 1996. Bagging predictors. Mach. Learn. 24(2): 123-140. doi:10.1007/BF00058655.
11. Breiman, L. 2001. Random forests. Mach. Learn. 45(1): 5-32. doi: 10.1023/A:1010933404324
12. Breiman, L., Friedman, J.H., Olshen, R.A., and Stone, C.J. 1984, Classification and regression trees. Wadsworth International Group, Belmont, California.
13. Brind'Amour, A., and Boisclair, D. 2006. Effect of the spatial arrangement of habitat patches on the development of fish habitat models in the littoral zone of a Canadian Shield lake. Can. J. Fish. Aquat. Sci. 63(4): 737-753. doi:10.1139/f05-249
14. Brind'Amour, A., Boisclair, D., Legendre, P., and Borcard, D. 2005. Multiscale spatial distribution of a littoral fish community in relation to environmental variables. Limnol. Oceanogr. 50(2): 465-479. doi:10.4319/lo.2005.50.2.0465
15. Buhlmann, P. 2004. Bagging, boosting and ensemble methods. In Handbook of computational statistics: concepts and methods. Edited by J. Gentle, W. Hardle, and Y. Mori. Springer, New York. pp. 877-907.
16. Cooper, S.D., Diehl, S., Kratz, K., and Sarnelle, O. 1998. Implications of scale for patterns and processes in stream ecology. Aust. J. Ecol. 23(1): 27-40. doi:10.1111/j.1442-9993.1998.tb00703.x
17. Cushman, S.A., and Huettmann, F. 2010. Spatial complexity, informatics and wildlife conservation. Springer, Tokyo.
18. Cutler, D.R., Edwards, T.C., Jr, Beard, K.H., Cutler, A., Hess, K.T., Gibson, J., and Lawler, J.J. 2007. Random forests for classification in ecology. Ecology, 88(11): 2783-2792. doi:10.1890/07-0539.1. PMID:18051647
19. De'ath, G. 2002. Multivariate regression trees: a new technique for modeling species-environment relationships. Ecology, 83: 1105-1117.
20. De'ath, G. 2007. Boosted trees for ecological modelling and prediction. Ecology, 88(1): 243-251. doi:10.1890/0012-9658(2007)88 [243:BTFEMA]2.0.CO;2. PMID:17489472.
21. De'ath, G., and Fabricius, K.E. 2000. Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology, 81(11): 3178-3192. doi:10.1890/0012-9658(2000)081 [3178:CARTAP]2.0.CO;2.
22. Dray, S., Legendre, P., and Peres-Neto, P. 2006. Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM). Ecol. Model. 196(3-4): 483-493. doi:10.1016/j.ecolmodel.2006.02.015
23. Drew, C.A., Wiersma, Y.F., and Huetmann, F. 2011. Predictive species and habitat modelling in landscape ecology: concepts and applications. Springer, New York.
24. Dungan, J.L., Perry, J.N., Dale, M.R.T., Legendre, P., Citron-Pousty, S., Fortin, M.-J., Jakomulska, A., Miriti, M., and Rosenberg, M.S. 2002. A balanced view of scale in spatial statistical analysis. Ecography, 25(5): 626-640. doi:10.1034/j.1600-0587.2002.250510.x
25. Elith, J., and Leathwick, J. 2009. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 40(1): 677-697. doi:10.1146/annurev.ecolsys. 110308.120159
26. Elith, J., Graham, C.H., Anderson, R.P., Dudik, M., Ferrier, S., Guisan, A., Hijmans, R.J., Huettmann, F., Leathwick, J.R., Lehmann, A., Li, J., Lohmann, L., Loiselle, B.A., Manion, G., Moritz, C., Nakamura, M., Nakazawa, Y., Overton, J.M., Peterson, A.T., Phillips, S., Richardson, K., Schachetti Pereira, R., Schapire, R.E., Soberón, J., Williams, S.E., Wisz, M., and Zimmermann, N.E. 2006. Novel methods improve predictions of species' distributions from occurrence data. Ecography, 29: 129-151. doi:10.1111/ j.2006.0906-7590.04596.x
27. Elith, J., Leathwick, J.R., and Hastie, T. 2008. A working guide to boosted regression trees. J. Anim. Ecol. 77(4): 802-813. doi: 10.1111/j.1365-2656.2008.01390.x. PMID:18397250
28. Ellis, N., Smith, S., and Pitcher, C. 2012. Gradient forests: calculating importance gradients on physical predictors. Ecology, 93(1): 156-168. doi:10.1890/11-0252.1. PMID:22486096
29. Evans, J.S., Murphy, M.A., Holden, Z.A., and Cushman, S.A. 2011. Modelling species distribution and change using random forest. In Predictive species and habitat modeling in landscape ecology. Edited by C.A. Drew, Y.F. Wiersma, and F. Huettmann. Springer, New York. pp. 139-159.
30. Ferrier, S., Manion, G., Elith, J., and Richardson, K. 2007. Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment. Divers. Distrib. 13(3): 252-264. doi:10.1111/j.1472-4642.2007.00341.x
31. Fortin, M.-J., and Dale, M.R.T. 2005. Spatial analysis: a guide for ecologists. Cambridge University Press, Cambridge.
32. Friedman, J.H. 2001. Greedy function approximation: a gradient boosting machine. Ann. Stat. 29(5): 1189-1232. doi:10.1214/aos/ 1013203451
33. Graf, R.F., Bollmann, K., Suter, W., and Bugmann, H. 2005. The importance of spatial scale in habitat models: capercaillie in the Swiss Alps. Landsc. Ecol. 20(6): 703-717. doi:10.1007/s10980-005-0063-7
34. Guisan, A., and Zimmermann, N.E. 2000. Predictive habitat distribution models in ecology. Ecol. Model. 135(2-3): 147-186. doi: 10.1016/S0304-3800(00)00354-9
35. Guisan, A., Graham, C.H., Elith, J., and Huettmann, F. 2007a. Sensitivity of predictive species distribution models to change in grain size. Divers. Distrib. 13(3): 332-340. doi:10.1111/j.1472-4642. 2007.00342.x
36. Guisan, A., Zimmermann, N.E., Elith, J., Graham, C.H., Phillips, S., and Peterson, A.T. 2007b. What matters for predicting the occurrences of trees: techniques, data, or species' characteristics? Ecol. Monogr. 77(4): 615-630. doi:10.1890/06-1060.1
37. Hardy, S.M., Lindgren, M., Konakanchi, H., and Huettmann, F. 2011. Predicting the distribution and ecological niche of unexploited snow crab (Chionoecetes opilio) populations in Alaskan waters: a first open-access ensemble model. Integr. Comp. Biol. 51(4): 608-622. doi:10.1093/icb/icr102. PMID:21873643
38. Huettmann, F., and Diamond, A.W. 2006. Large-scale effects on the spatial distribution of seabird in the Northwest Atlantic. Landsc. Ecol. 21(7): 1089-1108. doi:10.1007/s10980-006-7246-8
39. Keast, A., Harker, J., and Turnbull, D. 1978. Nearshore fish habitat utilization and species associations in Lake Opinicon (Ontario, Canada). Environ. Biol. Fishes, 3(2): 173-184. doi:10.1007/ BF00691941
40. Kitchell, J.F., Johnson, M.G., Minns, C.K., Loftus, K.H., Greig, L., and Olver, C.M. 1977. Percid habitat: the river analogy. J. Fish. Res. Board Can. 34(10): 1936-1940. doi:10.1139/f77-259
41. Knudby, A., Brenning, A., and LeDrew, E. 2010. New approaches to modelling fish-habitat relationships. Ecol. Model. 221(3): 503-511. doi:10.1016/j.ecolmodel.2009.11.008
42. Lawler, J.J., White, D., Neilson, R.P., and Blaustein, A.R. 2006. Predicting climate-induced range shifts: model differences and model reliability. Glob. Change Biol. 12(8): 1568-1584. doi: 10.1111/j.1365-2486.2006.01191.x
43. Leathwick, J.R., Rowe, D., Richardson, J., Elith, J., and Hastie, T. 2005. Using multivariate adaptive regression splines to predict the distributions of New Zealand's freshwater diadromous fish. Freshw. Biol. 50(12): 2034-2052. doi:10.1111/j.1365-2427.2005. 01448.x
44. Legendre, P., and Gallagher, E. 2001. Ecologically meaningful transformations for ordination of species data. Oecologia (Berl.), 129(2): 271-280. doi:10.1007/s004420100716
45. Legendre, P., and Legendre, L. 1998. Numerical ecology. Elsevier Science B.V., Amsterdam.
46. Legendre, P., Dale, M.R.T., Fortin, M.-J., Gurevitch, J., Hohn, M., and Myers, D. 2002. The consequences of spatial structure for the design and analysis of ecological field surveys. Ecography, 25(5): 601-615. doi:10.1034/j.1600-0587.2002.250508.x
47. Lele, S.R., and Keim, J.L. 2006. Weighted distributions and estimation of resource selection probability functions. Ecology, 87(12): 3021-3028. doi:10.1890/0012-9658(2006)87[3021:WDAEOR]2.0. CO;2. PMID:17249227
48. Leroux, S.J., Schmiegelow, F.K.A., Cumming, S.G., Lessard, R.B., and Nagy, J. 2007. Accounting for system dynamics in reserve design. Ecol. Appl. 17(7): 1954-1966. doi:10.1890/06-1115.1. PMID:17974334
49. MacRae, P.S.D., and Jackson, D.A. 2001. The influence of smallmouth bass (Micropterus dolomieu) predation and habitat complexity on the structure of littoral zone fish assemblages. Can. J. Fish. Aquat. Sci. 58: 342-351. doi:10.1139/f00-247
50. Manly, B.F.J., McDonald, T.L., Thomas, D.L., and Erickson, W.P. 2002. Resource selection by animals: statistical design and analysis for field studies. 2nd ed. Springer-Verlag. New York.
51. Mayo, J.S., and Jackson, D.A. 2006. Quantifying littoral vertical habitat structure and fish community associations using underwater visual census. Environ. Biol. Fishes, 75(4): 395-407. doi: 10.1007/s10641-005-5150-8
52. McMahon, T.E., Terrell, J.W., and Nelson, P.C. 1984. Habitat suitability information: walleye. US Fish and Wildlife Service, FWS/ OBS-82/10.56.
53. Meador, M.R., and Goldstein, R.M. 2003. Assessing water quality at large geographic scales: relations among land use, water physicochemistry, riparian condition, and fish community structure. Environ. Manage. 31(4): 504-517. doi:10.1007/s00267-002-2805-5. PMID:12677296
54. Mills, E.L., Leach, J.H., Carlton, J.T., and Secor, C.L. 1993. Exotic species in the Great Lakes: A history of biotic crises and anthropogenic introductions. J. Great Lakes Res. 19(1): 1-54. doi: 10.1016/S0380-1330(93)71197-1
55. Ohtani, K. 2000. Bootstrapping R2 and adjusted R2 in regression analysis. Econ. Model. 17(4): 473-483. doi:10.1016/S0264-9993(99)00034-6
56. Oppel, S., and Huettmann, F. 2010. Using a Random Forest model and public data to predict the distribution of prey for marine wildlife management. In Spatial information management in animal science. Edited by S. Cushman and F. Huettmann. Springer, Tokyo, Japan. pp. 151-163.
57. Peres-Neto, P.R., and Legendre, P. 2010. Estimating and controlling for spatial structure in the study of ecological communities. Glob. Ecol. Biogeogr. 19(2): 174-184. doi:10.1111/j.1466-8238.2009. 00506.x
58. Peres-Neto, P.R., Legendre, P., Dray, S., and Borcard, D. 2006. Variance partitioning of species data matrices: estimation and comparison of fractions. Ecology, 87(10): 2614-2625. doi: 10.1890/0012-9658(2006)87[2614:VPOSDM]2.0.CO;2. PMID: 17089669
59. Peters, J., Baets, B., Verhoest, N., Samson, R., Degroeve, S., Becker, P., and Huybrechts, W. 2007. Random forests as a tool for ecohydrological distribution modelling. Ecol. Model. 207(2-4): 304-318. doi:10.1016/j.ecolmodel.2007.05.011
60. Phillips, S.J., and Dudik, M. 2008. Modelling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography, 31(2): 161-175. doi:10.1111/j.0906-7590.2008. 5203.x
61. Phillips, S.J., Anderson, R.P., and Schapire, R.E. 2006. Maximum entropy modelling of species and geographic distributions. Ecol. Model. 190(3-4): 231-259. doi:10.1016/j.ecolmodel.2005.03.026
62. Plante, M., Lowell, K., Potvin, F., Boots, B., and Fortin, M.J. 2004. Studying deer habitat on Anticosti Island, Quebec: relating animal occurrences and forest map information. Ecol. Model. 174(4): 387-399. doi:10.1016/j.ecolmodel.2003.09.035
63. Prasad, A.M., Iverson, L.R., and Liaw, A. 2006. Newer classification and regression tree techniques: Bagging and random forests for ecological prediction. Ecosystems (N.Y.), 9(2): 181-199. doi: 10.1007/s10021-005-0054-1
64. Pratt, T.C., and Fox, M.G. 2001. Biotic influences on habitat selection by young-of-year walleye (Stizostedion vitreum) in the demersal stage. Can. J. Fish. Aquat. Sci. 58(6): 1058-1069. doi:10.1139/ f01-054
65. R Development Core Team. 2010. R: a language and environment for statistical computing [online]. R Foundation for Statistical Computing, Vienna, Austria. Available from http://www.R-project.org.
66. Rao, C.R. 1995. A review of canonical coordinates and an alternative to correspondence analysis using hellinger distance. Qüestiió, 19: 23-63.
67. Ripley, B. 2007. Rpart package [online]. R Development Core Team. Available from http://cran.r-project.org/web/packages/rpart/ index.html.
68. Robinson, B.W., Wilson, D.S., Margosian, A.S., and Lotito, P.T. 1993. Ecological and morphological differentiation of pumpkinseed sunfish in lakes without bluegill sunfish. Evol. Ecol. 7(5): 451-464. doi:10.1007/BF01237641
69. Rossi, J.P., and Nuutinen, V. 2004. The effect of sampling unit size on the perception of the spatial pattern of earthworm (Lumbricus terrestris L.) middens. Appl. Soil Ecol. 27(2): 189-196. doi: 10.1016/j.apsoil.2004.03.001
70. Roth, B.M., Kaplan, I.C., Sass, G.G., Johnson, P.T., Marburg, A.E., Yannarell, A.C., Havlicek, T.D., Willis, T.V., Turner, M.G., and Carpenter, S.R. 2007. Linking terrestrial and aquatic ecosystems: The role of woody habitat in lake food webs. Ecol. Model. 203(3-4): 439-452. doi:10.1016/j.ecolmodel.2006.12.005
71. Sass, G.G., Kitchell, J.F., Carpenter, S.R., Hrabik, T.R., Marburg, A.E., and Turner, M.G. 2006. Fish community and food web responses to a whole-lake removal of coarse woody habitat. Fisheries (Bethesda, Md.), 31(7): 321-330. doi:10.1577/1548-8446(2006)31[321:FCAFWR]2.0.CO;2
72. Schaffers, A.P., Raemakers, I.P., Sy'kora, K.V., and ter Braak, C.J.F. 2008. Arthropod assemblages are best predicted by plant species composition. Ecology, 89(3): 782-794. doi:10.1890/07-0361.1. PMID:18459341
73. Scott, W.B., and Crossman, E.J. 1973. Freshwater fishes of Canada. Galt House Publications Limited, Oakville, Ont.
74. Segal, M.R., and Xiao, Y. 2011. Multivariate random forests. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 1(1): 80-87. doi:10.1002/widm.12
75. Sharma, S., and Jackson, D.A. 2007. Fish assemblages and environmental conditions in the lower reaches of northeastern Lake Erie tributaries. J. Great Lakes Res. 33(1): 15-27. doi:10.3394/0380-1330(2007)33[15:FAAECI]2.0.CO;2
76. Sharma, S., and Jackson, D.A. 2008. Predicting smallmouth bass (Micropterus dolomieu) occurrence across North America under climate change: a comparison of statistical approaches. Can. J. Fish. Aquat. Sci. 65(3): 471-481. doi:10.1139/f07-178
77. Sharma, S., Walker, S.C., and Jackson, D.A. 2008. Empirical modelling of lake water-temperature relationships: a comparison of approaches. Freshw. Biol. 53(5): 897-911. doi:10.1111/j.1365-2427.2008.01943.x
78. Storch, D., Konvicka, M., Benes, J., Martinkova, J., and Gaston, K.J. 2003. Distribution patterns in butterflies and birds of the Czech Republic: separating effects of habitat and geographical position. J. Biogeogr. 30(8): 1195-1205. doi:10.1046/j.1365-2699.2003.00917.x
79. Thompson, A.R., Petty, J.T., and Grossman, G.D. 2001. Multi-scale effects of resource patchiness on foraging behaviour and habitat use by longnose dace, Rhinichthys cataractae. Freshw. Biol. 46(2): 145-160. doi:10.1046/j.1365-2427.2001.00654.x