Evaluating forest growth models

Ecological Modelling

Volumn 98, Issue 1, 1997, Pages 1-12

  Vanclay, J K ^a   Skovsgaard, J P ^b  

^a CENTER FOR INTERNATIONAL FORESTRY RESEARCH   (Indonesia)

^b DANISH FOREST LANDSCAPE RES INST   (Denmark)

Author keywords

Forest growth modelling; Model evaluation; Testing; Validation; Verification

Indexed keywords

EID: 0030988826     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3800(96)01932-1     Document Type: Article

References (68)

1. Bates, D.M. and Watts, D.G., 1988. Nonlinear Regression Analysis and its Applications. Wiley, New York, xiv + 365 pp.
2. Belcher, D.W., Holdaway, M.R. and Brand, G.J., 1982. A description of STEMS: the stand and tree evaluation and modelling system. USDA For. Serv. Gen. Tech. Rep., NC-79, 18 pp.
3. Biggs, A.G. and Cawthorns, A.R., 1962, quoted in: P.W. House and J. McLeod (Editors), Large-Scale Models for Policy Evaluation. Wiley, New York, p. 73.
4. Botkin, D.B., 1993. Forest Dynamics: An Ecological Model. Oxford University Press, Oxford, xv + 309 pp.
5. Botkin, D.B., Janak, J.F. and Wallis, J., 1972. Some ecological consequences of a computer model of forest growth. J. Ecology, 60: 849-872.
6. Brand, G.J. and Holdaway, M.R., 1983. Users need performance information to evaluate models. J. For., 81: 235-237, 254.
7. Brand, G.J. and Holdaway, M.R., 1989. Assessing the accuracy of TWIGS and STEMS85 volume predictions: a new approach. Northern J. Appl. For., 6: 109-114.
8. Brewer, G.D., 1973. Politicians, Bureaucrats and the Consultant. Basic Books, New York.
9. Burk, T.E., 1986. Growth and yield model validation: Have you ever met one that you liked? In: A. Allen and T.C. Cooney (Editors), Data Management Issues in Forestry. Forests Resources Systems Institute, Florence, AL, pp. 35-39.
10. Burk, T.E., 1990. Prediction error evaluation: preliminary results. In: L.C. Wensel and G.S. Biging (Editors), Forest Simulation Systems: Proc. IUFRO Conf., 2-5 Nov. 1988. University of California, Division of Agriculture and National Research, Bulletin, 1927, pp. 81-88.
11. D'Agostino, R.B. and Stephens, M.A. (Editors), 1986. Goodness-of-fit Techniques. Marcel Dekker, New York, xviii + 560 pp.
12. Dent, J.B. and Blackie, M.J., 1979. Systems Simulation in Agriculture. Applied Science, London.
13. Draper, N.R. and Smith, H., 1981. Applied Regression Analysis. Wiley, New York, 709 pp.
14. Efron, B. and Gong, G., 1983. A leisurely look at the bootstrap, the jackknife and cross-validation. Am. Stat., 37: 36-48.
15. Furnival, G.M. and Wilson, R.W., 1971. Systems of equations for predicting forest growth and yield. In: G.P. Patil, E.C. Pielou and W.E. Walters (Editors), Statistical Ecology, Vol. 3. Pennsylvania State University Press, pp. 43-57.
16. Gallant, R.A., 1987. Nonlinear Statistical Models. Wiley, New York, xii + 610 pp.
17. Garcia, O., 1984. New class of growth models for even-aged stands: Pinus radiata in Golden Downs Forest. N.Z. J. For. Sci., 14: 65-88.
18. Gertner, G., 1987. Approximating precision in simulation projections: an efficient alternative to Monte Carlo methods. For. Sci., 33: 230-239.
19. Gertner, G.Z., Cao, X. and Zhu, H. 1995. A quality assessment of a Weibull based growth projection system. For. Ecol. Manage., 71: 235-250.
20. Gilchrist, W., 1984. Statistical Modelling. Wiley, Chichester, xv + 339 pp.
21. Goulding, C.J., 1979. Validation of growth models used in forest management. N.Z. J. For., 24: 108-124.
22. Gregoire, T.G. and Reynolds, M.R., 1988. Accuracy testing and estimation alternatives. For. Sci., 34: 302-320.
23. Gregoire, T.G., Schabenberger, O. and Barrett, J.P., 1995. Linear modelling of irregularly spaced, unbalanced, longitudinal data from permanent-plot measurements. Can. J. For. Res., 25: 137-156.
24. Hamilton, D.A., 1990. Extending the range of applicability of an individual tree model. Can. J. For. Res., 20: 1212-1218.
25. Hann, D.W., 1980. Development and evaluation of an even- and uneven-aged ponderosa pine/Arizone fescue stand simulator. USDA For. Serv. Res. Pap., INT-267, 95 pp.
26. Hirsch, R.P., 1991. Validation samples. Biometrics, 47: 1193-1194.
27. Holdaway, M.R. and Brand, G.J., 1983. An evaluation of the STEMS tree growth projection system. USDA For. Serv. Res. Pap., NC-234, 20 pp.
28. Holdaway, M.R. and Brand, G.J., 1986. An evaluation of Lake States STEMS85. USDA For. Serv. Res. Pap., NC-269, 10 pp.
29. Jørgensen, S.E., 1986. Fundamentals of Ecological Modelling. Elsevier, Amsterdam, 389 pp.
30. Keuzenkamp, H.A. and McAleer, M., 1995. Simplicity, scientific inference and econometric modelling. Econ. J., 105: 1-21.
31. Kincaid, H., 1996. Philosophical Foundations of the Social Sciences: Analyzing Controversies in Social Research. Cambridge, New York.
32. Leary, R.A., 1970. Systems identification principles in studies of forest dynamics. USDA For. Serv. Res. Pap., NC-45, 38 pp.
33. Leary, R.A., 1979. Design. In: A generalized forest growth projection system applied to the lake states region. USDA For. Serv. Gen. Tech. Rep., NC-49: 5-15.
34. Leary, R.A., 1988. Some factors that will affect the next generation of forest growth models. In: A.R. Ek, S.R. Shifley and T.E. Burk (Editors), Forest Growth Modeling and Prediction. Proc. IUFRO Conf., 24-28 Aug. 1987, Minneapolis, MN. USDA For. Serv., Gen. Tech. Rep., NC-120: 22-32.
35. Leary, R.A., 1997. Testing models of red pine plantation dynamics using a modified Bakuzis matrix of stand properties. Ecol. Model., 98: 35-46.
36. Liu, J. and Ashton, P.S., 1995. Individual-based simulation models for forest succession and management. For. Ecol. Manage., 73: 157-175.
37. Majone, G., 1977. Pitfalls of analysis and analysis of pitfalls. Urban Ana., 4: 235.
38. Mayer, D.G. and Butler, D.G., 1993. Statistical validation. Ecol. Model., 68: 21-32.
39. Mayer, D.G., Stuart, M.A. and Swain, A.J., 1994. Regression of real world data on model output: an appropriate overall test of validity. Agric. Syst., 45: 93-104.
40. Meadows, D.H. and Robinson, J.M., 1985. The Electronic Oracle: Computer Models and Social Decisions. Wiley, Chichester, xv + 445 pp.
41. Moir, W.H. and Mowrer, H.T., 1995. Unsustainability. For. Ecol. Manage., 73: 239-248.
42. Monserud, R.A., 1989. Optimizing single-tree simulators. In: H.E. Burkhart, M. Rauscher and K. Johann (Editors), Artificial intelligence and growth models for forest management decisions. Proceedings IUFRO meeting, Vienna, 18-22 Sept 1989. VPI and SU, Blacksburg VA, FWS-1-89, pp. 308-321.
43. Mowrer, H.T., 1991. Estimating components of propagated variance in growth simulation model projections. Can. J. For. Res., 21: 379-386.
44. Mowrer, H.T. and Frayer, W.E., 1986. Variance propagation in growth and yield projections. Can. J. For. Res., 16: 1196-1200.
45. Oderwald, R.G. and Hans, R.P., 1993. Corroborating models with model properties. For. Ecol. Manage., 62: 271-283.
46. Oreskes, N., Shrader-Frechette, K. and Belitz, K., 1994. Verification, validation and confirmation of numerical models in the earth sciences. Science, 263: 641-645.
47. Power, M., 1993. The predictive validation of ecological and environmental models. Ecol. Model., 68: 33-50.
48. Quade, E.S. and Boucher, W.I. (Editors), 1968. Systems Analysis and Policy Planning. Elsevier, New York.
49. Ratkowsky, D.A., 1983. Nonlinear Regression Modeling. Marcel Dekker, New York, viii + 276 pp.
50. Ratkowsky, D.A., 1990. Handbook of Nonlinear Regression Models. Marcel Dekker, New York, ix + 241 pp.
51. Reynolds, M.R., 1984. Estimating the error in model predictions. For. Sci., 30: 454-469.
52. Reynolds, M.R. and Chung, J., 1986. Regression methodology for estimating model prediction error. Can. J. For. Res., 16: 931-938.
53. Reynolds, M.R., Burk, T.E. and Huang, W., 1988. Goodness-of-fit tests and model selection procedures for diameter distribution models. For. Sci., 34: 373-399.
54. Seber, G.A.F. and Wild, C.J., 1989. Nonlinear Regression. Wiley, New York, xx + 768 pp.
55. Shifley, S.R., 1987. A generalized system of models forecasting Central States growth. USDA For. Serv. Res. Pap., NC-279, 10 pp.
56. Sievänen, R. and Burk, T.E., 1993. Adjusting a process-based growth model for varying site conditions through parameter estimation. Can. J. For. Res., 23: 1837-1851.
57. Snee, R.D., 1977. Validation of regression models: methods and examples. Technometrics, 19: 415-428.
58. Soares, P., Tomé, M., Skovsgaard, J.P. and Vanclay, J.K., 1995. Validating growth models for forest management using continuous forest inventory data. For. Ecol. Manage., 71: 251-266.
59. Spilsbury, M.J., 1991. Computer modelling of mixed age, polyspecific broadleaf woodland in the United Kingdom. D. Phil. Thesis, University of Oxford, 215 pp.
60. Tarp-Johansen, M.J., Skovsgaard, J.P., Madsen, S.F., Johannsen, V.K. and Skovgaard, I., 1997. Compatible stem taper and stem volume functions for oak in Denmark. Ann. Sci. For., 54: in press.
61. Vanclay, J.K., 1994. Modelling Forest Growth and Yield: Applications to Mixed Tropical Forests. CAB International, Wallingford, UK, xvii + 312 pp.
62. Vanclay, J.K., 1996. Lessons from the Queensland rainforests: steps towards sustainability. J. Sustainable For., 3(2/3): 1-27.
63. Van Henten, E.J. and Van Straten, G., 1991. Sensitivity analysis of a dynamic growth model of lettuce. J. Agric. Eng. Res., 59: 19-31.
64. Weisberg, S., 1985. Applied Linear Regression, 2nd edn. Wiley, New York, xiv + 324 pp.
65. West, P.W., 1981. Simulation of diameter growth and mortality in regrowth eucalypt forest of southern Tasmania. For. Sci., 27: 603-616.
66. West, P.W., 1995. Application of regression analysis to inventory data with measurements on successive occasions. For. Ecol. Manage., 71: 227-234.
67. Ziman, J., 1978. Reliable Knowledge: An Exploration of the Grounds for Belief in Science. Cambridge University Press, Cambridge, 197 pp.
68. Zhang, L., Moore, J.A. and Newberr, J.D., 1993. Disaggregating stand volume growth to individual trees. For. Sci., 39: 295-308.