Erratum: Testing the accuracy of new methods for reconstructing historical structure of forest landscapes using GLO survey data (Ecological Monographs (2011) 81:1 (63-88) DOI: 10.1890/10-0256.1);Testing the accuracy of new methods for reconstructing historical structure of forest landscapes using GLO survey data

Ecological Monographs

Volumn 81, Issue 1, 2011, Pages 63-88

  Williams, Mark A ^a   Baker, William L ^a  

^a UNIVERSITY OF WYOMING   (United States)

Author keywords

Accuracy; Estimation bias; General Land Office; Historical range of variability; Landscape; Pinus ponderosa; Plotless density estimator; Ponderosa pine; Public Land Survey System; Reconstruction.

Indexed keywords

ACCURACY ASSESSMENT; BASAL AREA; CALIBRATION; CONIFEROUS TREE; ESTIMATION METHOD; FIELD SURVEY; GEOGRAPHICAL DISTRIBUTION; MODEL VALIDATION; RECONSTRUCTION; RESTORATION ECOLOGY; TREE RING;

PINUS PONDEROSA;

EID: 79955445791     PISSN: 00129615     EISSN: 15577015     Source Type: Journal    
DOI: 10.1002/ecm.1251     Document Type: Erratum

References (85)

1. Anderson, R. C., and M. R. Anderson. 1975. The presettlement vegetation of Williamson County, Illinois. Castanea 40:345-363.
2. Anderson, R. C., S. L. Jones, and R. Swigart. 2006. Modifying distance methods to improve estimates of historical tree density from General Land Office survey notes. Journal of the Torrey Botanical Society 133:449-459. (Pubitemid 46071828)
3. Arundel, T. R. 2000. Using general land office survey records to determine pre-settlement forest conditions in north-central Arizona, 1878-1879. Thesis. Northern Arizona University, Flagstaff, Arizona, USA.
4. Baker, W. L., T. T. Veblen, and R. L. Sherriff. 2007. Fire, fuels and restoration of ponderosa pine-Douglas fir forests in the Rocky Mountains, USA. Journal of Biogeography 34:251-269. (Pubitemid 46143982)
5. Batcheler, C. L., and D. G. Craib. 1985. A variable area plot method of assessment of forest condition and trend. New Zealand Journal of Ecology 8:83-95. (Pubitemid 17248971)
6. Bonham, D. 1989. Measurements for terrestrial vegetation, John Wiley and Sons, New York, New York, USA.
7. Bouldin, J. 2008. Some problems and solutions in density estimation from bearing tree data: a review and synthesis. Journal of Biogeography 35:2000-2011.
8. Bourdo, E. A., Jr. 1956. A review of the general land office survey and of its use in quantitative studies of former forests. Ecology 37:754-768.
9. Brock, D. A. 1977. Comparison of community similarity indexes. Journal Water Pollution Control Federation 49: 2488-2494. (Pubitemid 8242506)
10. Cochran, W. G. 1977. Sampling techniques. John Wiley and Sons, New York, New York, USA.
11. Cottam, G. 1947. A point method for making rapid surveys of woodlands. Bulletin of the Ecological Society ofAmerica 28:60.
12. Cottam, G. 1949. The phytosociology of an oak woods in southwestern Wisconsin. Ecology 30:271-287.
13. Cottam, G., and J. T. Curtis. 1949. A method for making rapid surveys of woodlands by means of pairs of randomly selected trees. Ecology 30:101-104.
14. Cottam, G., and J. T. Curtis. 1955. Correction for various exclusion angles in the random pairs method. Ecology 36: 767.
15. Cottam, G., and J. T. Curtis. 1956. The use of distance measures in phytosociological sampling. Ecology 37:451-460.
16. Cottam, G., J. T. Curtis, and B. W. Hale. 1953. Some sampling characteristics of a population of randomly dispersed individuals. Ecology 34:741-757.
17. Covington, W. W., and M. M. Moore. 1994. Southwestern ponderosa forest structure: changes since Euro-American settlement. Journal of Forestry 92:39-47.
18. Curtis, J. T., and R. P. McIntosh. 1950. The interrelations of certain analytic and synthetic phytosociological characters. Ecology 31:434-455.
19. Curtis, R. O., and D. D. Marshall. 2000. Why quadratic mean diameter? Western Journal of Applied Forestry 15:137-139.
20. Dahdouh-Guebas, F., and K. Koedam. 2006. Empirical estimate of the reliability of the use of the point-centered quarter method (PCQM): solutions to ambiguous field situations and description of the PCQM protocol. Forest Ecology and Management 228:1-18. (Pubitemid 43728577)
21. Delcourt, H. R., and P. A. Delcourt. 1996. Presettlement landscape heterogeneity: evaluating grain of resolution using General Land Office survey data. Landscape Ecology 11: 363-381.
22. Delincé, J. 1986. Robust density estimation through distance measurements. Ecology 67:1576-1581.
23. Engeman, R. M., R. T. Sugihaara, L. F. Pank, and W. E. Dusenberry. 1994. A comparison of plotless density estimators using Monte Carlo simulation. Ecology 75:1769-1779. (Pubitemid 2134550)
24. Franklin, D. A. 1967. Basal area as determined by the pointcentred quarter method. New Zealand Journal of Botany 5: 168-169.
25. Fraser, A. R. 1977. Triangle-based probability polygons for forest sampling. Forest Science 23:111-121.
26. Fulé, P. Z., W. W. Covington, and M. M. Moore. 1997. Determining reference conditions for ecosystem management of southwestern ponderosa pine forests. Ecological Applications 7:895-908.
27. Fulé, P. Z., W. W. Covington, M. M. Moore, T. A. Heinlein, and A. E. M. Waltz. 2002. Natural variability in forests of the Grand Canyon, USA. Journal of Biogeography 29:31-47. (Pubitemid 34172039)
28. Galatowitsch, S. M. 1990. Using the original land survey notes to reconstruct presettlement landscapes in the American West. Great Basin Naturalist 50:181-191.
29. Grimm, E. C. 1984. Fire and other factors controlling the Big Woods vegetation of Minnesota in the mid-nineteenth century. Ecological Monographs 54:291-311.
30. Habeck, J. R. 1994. Using General Land Office records to assess forest succession in ponderosa pine/Douglas-fir forests in western Montana. Northwest Science 68:69-78. (Pubitemid 2115150)
31. Hann, W. J., J. L. Jones, M. G. Karl, P. F. Hessburg, R. E. Keane, D. G. Long, J. P. Menakis, C. H. McNicoll, S. G. Leonard, R. A. Gravenmier, and B. G. Smith. 1997. Landscape dynamics of the Basin. Pages 336-1055 in T. M. Quigley and S. J. Arbelbide, editors. An assessment of ecosystem components in the Interior Columbia Basin including portions of the Klamath and Great Basins. Volume 2. General Technical Report PNW-GTR-405. U.S. Forest Service, Pacific Northwest Research Station, Portland, Oregon, USA.
32. He, H. S., D. C. Dey, X. Fan, M. B. Hooten, J. M. Kabrick, C. K. Wikle, and Z. Fan. 2006. Mapping pre-European settlement vegetation at fine resolutions using a hierarchical Bayesian model and GIS. Plant Ecology 191:85-94. (Pubitemid 46897530)
33. He, H. S., D. J. Mladenoff, T. A. Sickley, and G. G. Gutenspergen. 2000. GIS interpolation of witness tree records (1839-1866) for northern Wisconsin at multiple scales. Journal of Biogeography 27:1031-1042. (Pubitemid 32122482)
34. Hessburg, P. H., R. B. Salter, and K. M. James. 2007. Reexamining fire severity relations in pre-management era mixed conifer forests: inference from landscape patterns of forest structure. Landscape Ecology 22:5-24. (Pubitemid 350060726)
35. Heyerdahl, E. K., L. B. Brubaker, and J. K. Agee. 2001. Spatial controls of historical fire regimes: a multi-scale example from the interior west, USA. Ecology 82:660-678. (Pubitemid 32175314)
36. Heyerdahl, E. K., D. McKenzie, L. D. Daniels, A. E. Hessl, J. S. Littell, and N. J. Mantua. 2008. Climate drivers of regionally synchronous fires in the inland Northwest (1651-1900). International Journal of Wildland Fire 17:40-49. (Pubitemid 351278370)
37. Horvitz, D. G., and D. J. Thompson. 1952. A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association 47:663-685.
38. Kleinn, C., and F. Vilčko. 2006. Design-unbiased estimation for point-to-tree distance sampling. Canadian Journal of Forest Research 36:1407-1414. (Pubitemid 44368755)
39. Kline, V. M., and G. Cottam. 1979. Vegetation response to climate and fire in the Driftless Area of Wisconsin. Ecology 60:861-868.
40. Knox, S. C. 2005. Multi-scale spatial heterogeneity in historical fire regimes of ponderosa pine and Douglas-fir forests in Arizona, USA. Thesis. Colorado State University, Fort Collins, Colorado, USA
41. Kronenfeld, B. J., and Y.-C. Wang. 2007. Accounting for surveyor inconsistency and bias in estimation of tree density from presettlement land survey records. Canadian Journal of Forest Research 37:2365-2379. (Pubitemid 351195050)
42. Leahy, M. J., and K. S. Pregitzer. 2003. A comparison of presettlement and present-day forests in northeastern lower Michigan. American Midland Naturalist 149:71-89. (Pubitemid 36093470)
43. Leitner, L. A., C. P. Dunn, G. R. Guntenspergen, F. Stearns, and D. M. Sharpe. 1991. Effects of site, landscape features, and fire regime on vegetational patterns in presettlement southern Wisconsin. Landscape Ecology 5:203-217.
44. Liermann, M., A. Steel, M. Rosing, and P. Guttorp. 2004. Random denominators and the analysis of ratio data. Environmental and Ecological Statistics 11:55-71. (Pubitemid 38329636)
45. Lindsey, A. A., J. D. Barton, Jr., and S. R. Miles. 1958. Field efficiencies of forest sampling methods. Ecology 39:428-444.
46. Manies, K. L., and D. J. Mladenoff. 2000. Testing methods to produce landscape-scale presettlement vegetation maps from the U.S. public land survey records. Landscape Ecology 15: 741-754. (Pubitemid 32044942)
47. Mark, A. F., and A. E. Esler. 1970. An assessment of the pointcentred quarter method of plotless sampling in some New Zealand forests. Proceedings of the New Zealand Ecological Society 17:106-110.
48. Mast, J. N., P. Z. Fulé, M. M. Moore, W. W. Covington, and A. E. M. Waltz. 1999. Restoration of presettlement age structure of an Arizona ponderosa pine forest. Ecological Applications 9:228-239. (Pubitemid 29114415)
49. Menzel, J. P. 1996. Historical changes in forest structure in the ponderosa pine type,Walnut Canyon Area, northern Arizona. Thesis.NorthernArizona University, Flagstaff,Arizona,USA.
50. Mercier, F., and O. Baujard. 1997. Voronoi diagrams to model forest dynamics in French Guiana. Pages 161-171 in Proceedings of the Second International Conference on GeoComputation. University of Otago, Dunedin, New Zealand.
51. Moore, M. M., W. W. Covington, and P. Fulé. 1999. Reference conditions and ecological restoration: a southwestern ponderosa pine perspective. Ecological Applications 9:1266-1277. (Pubitemid 29536902)
52. Moore, M. M., D. W. Huffman, P. Z. Fulé, W. W. Covington, and J. E. Crouse. 2004. Comparison of historical and contemporary forest structure and composition on permanent plots in southwestern ponderosa pine forests. Forest Science 50:162-176. (Pubitemid 38708757)
53. Moore, P. G. 1954. Spacing in plant populations. Ecology 35: 222-227.
54. Morisita, M. 1957. A new method for the estimation of density by spacing method applicable to nonrandomly distributed populations. Physiology and Ecology 7:134-144.
55. Morrow, R. J. 1986. Age structure and spatial pattern of oldgrowth ponderosa pine in Pringle Falls Experimental Forest, central Oregon. Thesis. Oregon State University, Corvallis, Oregon, USA.
56. Nelson, J. C. 1997. Presettlement vegetation patterns along the 5th Principal Meridian, Missouri Territory, 1815. American Midland Naturalist 137:79-94. (Pubitemid 27103383)
57. Nielson, R. M., R. T. Sugihara, T. J. Boardman, and R. M. Engeman. 2004. Optimization of ordered distance sampling. Environmetrics 15:119-128. (Pubitemid 38362338)
58. Okabe, A., B. Boots, K. Sugihara, and S. N. Chiu. 2000. Concepts and applications of Voronoi diagrams. Second edition. John Wiley and Sons, Chichester, West Sussex, UK.
59. Payandeh, B., and A. R. Ek. 1986. Distance methods and density estimators. Canadian Journal of Forest Research 16: 918-924.
60. Peet, R. K. 1981. Forest vegetation of the Colorado Front Range: patterns of species diversity. Vegetatio 37:65-78.
61. Picard, N., A. M. Kouyaté, and H. Dessard. 2005. Tree density estimations using a distance method in Mali savanna. Forest Science 51:7-18. (Pubitemid 40473887)
62. Pielou, E. C. 1959. The use of point-to-plant distances in the study of the pattern of plant populations. Journal of Ecology 47:607-613.
63. Pollard, J. H. 1971. On distance estimators of density in randomly distributed forests. Biometrics 27:991-1002.
64. Prayag, V. R., and S. R. Deshmukh. 2000. Testing randomness of spatial pattern using Eberhardt's index. Environmetrics 11:571-582.
65. Radeloff, V. C., D. J. Mladenoff, H. S. He, and M. S. Boyce. 1999. Forest landscape change in the northwestern Wisconsin Pine Barrens from pre-European settlement to the present. Canadian Journal of Forest Research 29:1649-1659. (Pubitemid 30118843)
66. Sánchez-Meador, A. J. 2006. Modeling spatial and temporal changes of ponderosa pine forests in northern Arizona since Euro-American settlement. Dissertation. Northern Arizona University, Flagstaff, Arizona, USA.
67. Schulte, L. A., and D. J. Mladenoff. 2001. The original US public land survey records. Journal of Forestry 99:5-10.
68. Schulte, L. A., D. J. Mladenoff, and E. V. Nordheim. 2002. Quantitative classification of a historic northern Wisconsin (U.S.A.) landscape: mapping forests at regional scales. Canadian Journal of Forest Research 32:1616-1638. (Pubitemid 35409226)
69. Shanks, R. E. 1953. Forest composition and species association in the beech-maple forest region of western Ohio. Ecology 34: 456-466.
70. Shanks, R. E. 1954. Plotless sampling trials in Appalachian forest types. Ecology 35:237-244.
71. Steinke, I., and K. J. Hennenberg. 2006. On the power of plotless density estimators for statistical comparisons of plant populations. Canadian Journal of Botany 84:421-432. (Pubitemid 44426675)
72. Stewart, L. O. 1935. Public land surveys: history, instructions, methods. Collegiate Press, Ames, Iowa, USA.
73. Trifkovic, S., T. Tsurumi, and H. Yamamoto. 2005. An Unbiased Prodan estimator-stand density estimations applying the n-tree distance sampling. Nihon Shinrin Gakkai Taikai Koen Yoshishu (CD) 116:PC028.
74. Veblen, T. T., T. Kitzberger, and J. Donnegan. 2000. Climatic and human influences on fire regimes in ponderosa pine forests in the Colorado Front Range. Ecological Applications 10:1178-1195. (Pubitemid 32145289)
75. Walther, B. A., and J. L. Moore. 2005. The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28:815-829. (Pubitemid 41754474)
76. Wang, Y-.C., and C. P. S. Larsen. 2006. Do coarse resolution U.S. presettlement land survey records adequately represent the spatial pattern of individual tree species? Landscape Ecology 21:1003-1017. (Pubitemid 44505333)
77. Ward, D. 1991. Triangular tessellation: a new approach to forest inventory. Forest Ecology and Management 44:285-290.
78. Warde, W., and J. W. Petranka. 1981. A correction factor table for missing point-center quarter data. Ecology 62:491-494.
79. Welsh, A. H., A. T. Peterson, and S. A. Altmann. 1988. The fallacy of averages. American Naturalist 132:277-288.
80. White, A. S. 1976. Evaluating land survey notes to determine the pre-settlement structure of the Lubrecht Forest, Montana. Thesis. University of Montana, Missoula, Montana, USA.
81. White, C. A. 1983. A history of the rectangular survey system. USDI Bureau of Land Management, Superintendent of Documents, Washington, D.C., USA.
82. White, N. A., R. M. Engeman, R. T. Sugihara, and H. W. Krupa. 2008. A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets. BMC Ecology 8:6.
83. Whittaker, R. H. 1952. A study of summer foliage insect communities in the Great Smokey Mountains. Ecological Monographs 22:2-44.
84. Williams, M. A., and W. L. Baker. 2010. Bias and error in using survey records for ponderosa pine landscape restoration. Journal of Biogeography 37:707-721.
85. Wuenscher, J. E., and A. J. Valiunas. 1967. Presettlement forest composition of the river hills region of Missouri. American Midland Naturalist 78:487-495.