Gradient modeling of conifer species using random forests

Landscape Ecology

Volumn 24, Issue 5, 2009, Pages 673-683

  Evans, Jeffrey S ^a   Cushman, Samuel A ^b  

^a THE NATURE CONSERVANCY   (United States)

^b ROCKY MOUNTAIN RESEARCH STATION   (United States)

Author keywords

CART; Gradient; Predictive modeling; Random forests

Indexed keywords

BOOTSTRAPPING; COMMUNITY COMPOSITION; CONIFEROUS FOREST; DOWNSCALING; ECOLOGICAL MODELING; GRADIENT ANALYSIS; LANDSCAPE ECOLOGY; PATCHINESS; PIXEL; VEGETATION CLASSIFICATION; VEGETATION MAPPING; VEGETATION STRUCTURE;

IDAHO; NORTH AMERICA; UNITED STATES;

CONIFEROPHYTA;

EID: 67349136470     PISSN: 09212973     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10980-009-9341-0     Document Type: Article

References (46)

1. MP Austin 2002 Spatial prediction of species distribution: an interface between ecological theory and statistical modelling Ecol Model 157 101 118
2. L Breiman 1996 Bagging predictors Mach Learn 24 2 123 140
3. L Brieman 2001 Statistical modeling: the two cultures Stat Sci 16 3 199 231 10.1214/ss/1009213726
4. L Breiman 2001 Random forests Mach Learn 45 5 32 10.1023/A:1010933404324
5. PS Chavez 1988 An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data Remote Sens Environ 24 459 479 10.1016/0034-4257(88)90019-3
6. Chawla NV, Lazarevic A, Hall LO, Bowyer KW (2003) SMOTEboost: improving prediction of the minority class in boosting. In: 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, pp 107-119
7. Chen C, Liaw A, Breiman L (2004) Using random forest to learn imbalanced data. http://oz.berkeley.edu/users/chenchao/666.pdf
8. NL Crookston AO Finley 2008 yaImpute: an R package for kNN imputation J Stat Softw 23 1 16
9. JT Curtis RP McIntosh 1951 An upland forest continuum in the prairie-forest border region of Wisconsin Ecol Monogr 32 476 496
10. Cushman SA, McKenzie D, Peterson DL, Littell J, McKelvey KS (2007) Research agenda for integrated landscape modelling. USDA Forest Service General Technical Report RMRS-GTR-194
11. DR Cutler TC Edwards Jr KH Beard A Cutler KT Hess J Gibson J Lawler 2007 Random forests for classification in ecology Ecology 88 2783 2792 10.1890/07-0539.1
12. G Déath KE Fabricius 2000 Classification and regression trees: a powerful yet simple technique for ecological data analysis Ecology 81 3178 3192
13. ER DeLong DM DeLong DL Clarke-Pearson 1988 Comparing the area under tow or more correlated receiver operating characteristics curves: a nonparametric approach Biometrics 59 837 845 10.2307/2531595
14. Evans IS (1972) General geomorphometry, derivatives of altitude, and descriptive statistics. In: Chorley RJ (ed) Spatial analysis in geomorphology. Harper & Row, New York, pp 17-90
15. Forman RTT (1995) Land mosaics: the ecology of landscapes and regions. Cambridge University Press, Cambridge
16. Forman RTT, Godron M (1986) Landscape ecology. John Wiley & Sons, New York
17. EA Freeman G Moisen 2008 Presence absence: an R package for presence absence analysis J Stat Softw 23 11 31
18. Fu P, Rich PM (1999) Design and implementation of the solar analyst: an ArcView extension for modeling solar radiation at landscape scales. Proceedings of the 19th Annual ESRI User Conference, San Diego, USA, http://www.esri.com/ library/userconf/proc99/proceed/papers/pap867/p867.htm
19. HA Gleason 1926 The individualistic concept of the plant association Bull Torrey Bot Club 53 7 26 10.2307/2479933
20. A Guisan NE Zimmermann 2000 Predictive habitat distribution model in ecology Ecol Model 135 147 186 10.1016/S0304-3800(00)00354-9
21. Hastie T, Tibshirani R, Friedman JH (2001) The elements of statistical learning. Springer, New York
22. GE Hutchinson 1957 Concluding remarks Cold Spring Harb Symp Quant Biol 22 415 427
23. Liaw A, Wiener M (2002) Classification and regression by random forest. R news: the newsletter of the R project ( http://cran.r-project.org/doc/Rnews/ ) 2(3):18-22
24. AD Manning DB Lindenmayer HA Nix 2004 Continua and umwelt: novel perspectives on viewing landscapes Oikos 104 621 628 10.1111/j.0030-1299.2004. 12813.x
25. B McCune D Keon 2002 Equations for potential annual direct incident radiation and heat load index J Veg Sci 13 603 606 10.1658/1100-9233(2002) 013[0603:EFPADI]2.0.CO;2
26. McGarigal K, Cushman SA (2005) The gradient concept of landscape structure. In: Wiens J, Moss M (eds) Issues and perspectives in landscape ecology. Cambridge University Press, Cambridge, pp 112-119
27. K McGarigal S Tagil SA Cushman 2009 Surface metrics: an alternative to patch metrics for the quantification of landscape structure Landscape Ecol 24 433 450
28. S McIntyre GW Barrett 1992 Habitat variegation, an alternative to fragmentation Conserv Biol 6 146 147 10.1046/j.1523-1739.1992.610146.x
29. Moore ID, Gessler PE, Nielsen GA, Petersen GA (1993) Terrain attributes: estimation methods and scale effects. In: Jakeman AJ, Beck MB, McAleer M (eds) Modeling change in environmental systems. Wiley, London, pp 189-214
30. Morrison D (2002) Multivariate statistical methods. McGraw-Hill series in probability and statistics, 4th edn. McGraw-Hill, New York
31. Murphy MA, Evans JS, Storfer AS (2009) Quantifying Bufo boreas connectivity in Yellowstone National Park with landscape genetics. Ecology (in press)
32. R Nemani L Pierce S Running L Brand 1993 Forest ecosystem processes at the watershed scale; sensitivity to remotely-sensed leaf-area index estimates Int J Remote Sens 14 2519 2534 10.1080/01431169308904290
33. Y-S Park T-S Chon 2006 Biologically inspired machine learning implemented to ecological informatics Ecol Inform 203 1 7
34. SJ Phillips RP Anderson RE Schapire 2006 Maximum entropy modeling of species geographic distributions Ecol Model 190 231 259 10.1016/j.ecolmodel. 2005.03.026
35. AM Prasad LR Iverson A Liaw 2006 Random forests for modeling the distribution of tree abundances Ecosystems (NY, Print) 9 181 199 10.1007/s10021-005-0054-1
36. R Development Core Team (2007) R: a language and environment for statistical computing. R foundation for statistical computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org
37. B Rabus M Eineder A Roth R Bamler 2003 The shuttle radar topography mission-a new class of digital elevation models acquired by spaceborne radar Photogramm Eng Remote Sens 57 241 262 10.1016/S0924-2716(02)00124-7
38. GE Rehfeldt NL Crookston MV Warwell JS Evans 2006 Empirical analyses of plant-climate relationships for the western United States Int J Plant Sci 167 6 1123 1150 10.1086/507711
39. Roberts DW, Cooper SV (1989) Concepts and techniques of vegetation mapping, land classifications based on vegetation: applications for resource management. GTR-INT-257, USDA Forest Service Intermountain Research Station, Ogden, UT, pp 90-96
40. R Schapire 1990 Strength of weak learnability J Mach Learn 5 197 227
41. AR Stage 1976 An expression of the effects of aspect, slope, and habitat type on tree growth For Sci 22 3 457 460
42. DRB Stockwell DP Peters 1999 The GARP modeling system: problems and solutions to automated spatial prediction Int J Geogr Inf Syst 13 143 158 10.1080/136588199241391
43. Svetnik V, Liaw A, Tong C, Wang T (2004) Application of Breiman's random forest to modeling structure-activity relationships of pharmaceutical molecules. In: Roli F, Kittler J, Windeatt T (eds) Lecture notes in computer science, vol 3077. Springer, Berlin, pp 334-343
44. DG Tarboton 1997 A new method for the determination of flow directions and contributing areas in grid digital elevation models Water Resour Res 33 2 309 319 10.1029/96WR03137
45. Turner MG, Gardner RH, O'Neill RV (2001) Landscape ecology in theory and practice. Springer-Verlag, New York
46. RH Whittaker 1967 Gradient analysis of vegetation Biol Rev Camb Philos Soc 42 207 264 10.1111/j.1469-185X.1967.tb01419.x