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Model Implementation and Evaluation

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Modeling Forest Trees and Stands

Abstract

Computer programs that implement growth and prediction functions, jointly with algorithms for the simulation of silvicultural treatments and user-friendly interfaces, are commonly known as forest simulators. This chapter starts with an example of input/output functions that are typically used in implementation of forest stand simulators. The value of visual, as well as numeric, output is discussed. The second major part of the chapter deals with model evaluation, which may be divided into two categories: qualitative and quantitative (commonly designated model verification and validation, respectively). The logic of the model structure should be evaluated, along with the reasonableness of the predictions. Statistical procedures that are commonly applied to evaluate model bias and precision, modeling efficiency, and tendencies in model error are presented. The chapter continues with a discussion of evaluating models with independent sample data and concludes with remarks on applying growth and yield models.

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Notes

  1. 1.

    The USDA Forest Service stand visualization system (SVS) can be accessed at <www.fs.fed.us/pnw/svs/>

References

  • Bennett FA, Clutter JL (1968) Multiple-product yield estimates for unthinned slash pine plantations – pulpwood, sawtimber, gum. USDA Forest Service, Asheville, Research Paper SE-35

    Google Scholar 

  • Botkin DB (1993) Forest dynamics: an ecological model. Oxford University Press, New York

    Google Scholar 

  • Buchman RG, Shifley SR (1983) Guide to evaluating forest growth projection systems. J For 81:232–234, 254

    Google Scholar 

  • Burkhart HE (1971) Slash pine yield estimates based on diameter distribution: an evaluation. For Sci 17:452–453

    Google Scholar 

  • Burkhart HE (1992) Scientific visualization for the study and use of forest stand simulators. Landsc Urb Plan 21:317–318

    Article  Google Scholar 

  • Burkhart HE, Strub MR (1974) A model for simulation of planted loblolly pine stands. In: Fries J (ed) Growth models for tree and stand simulation. Royal College of Forestry, Stockholm, pp 128–135, Research Notes 30

    Google Scholar 

  • Burkhart HE, Parker RC, Strub MR, Oderwald RG (1972) Yields of old-field loblolly pine plantations. Virginia Polytechnic Institute and State University, Blacksburg, Pub. FWS-3-72

    Google Scholar 

  • Cieszewski CJ, Strub M (2007) Parameter estimation of base-age invariant site index models: which data structure to use? A discussion. For Sci 53:552–555

    Google Scholar 

  • Crow TR (1986) Comparing the performance of two northern hardwood growth projection systems. North J Appl For 3:28–32

    Google Scholar 

  • Daniels RF, Burkhart HE (1975) Simulation of individual tree growth and stand development in managed loblolly pine plantations. Virginia Polytechnic Institute and State University, Blacksburg, Pub. FWS-5-75

    Google Scholar 

  • Daniels RF, Burkhart HE, Strub MR (1979) Yield estimates for loblolly pine plantations. J For 77:581–583, 586

    Google Scholar 

  • Davison AC, Hinkley DV (1997) Bootstrap methods and their application. Cambridge University Press, New York

    Google Scholar 

  • Gauch HG Jr, Hwang JTG, Fick GW (2003) Model evaluation by comparison of model-based predictions and measured values. Agron J 95:1442–1446

    Article  Google Scholar 

  • Gertner G (1987) Approximating precision in simulation projections: an efficient alternative to Monte Carlo methods. For Sci 33:230–239

    Google Scholar 

  • Gertner GZ (1988) Alternative methods for improving variance approximation of single tree growth and yield projections. In: Ek AR, Shifley SR, Burk TE (eds) Forest growth modelling and prediction. USDA Forest Service, St. Paul, pp 739–746, General Technical Report NC- 120

    Google Scholar 

  • Huang S, Yang Y, Wang Y (2003) A critical look at procedures for validating growth and yield models. In: Amaro A, Reed D, Soares P (eds) Modelling forest systems. CAB International, Wallingford, pp 271–293

    Google Scholar 

  • Janssen PHM, Heuberger PSC (1995) Calibration of process-oriented models. Ecol Mod 83:55–66

    Article  Google Scholar 

  • Knoebel BR, Burkhart HE, Beck DE (1986) A growth and yield model for thinned stands of yellow-poplar. For Sci Monogr 27:62

    Google Scholar 

  • Kobayashi K, Salam MU (2000) Comparing simulated and measured values using mean squared deviation and its components. Agron J 92:345–352

    Google Scholar 

  • Kozak A, Kozak R (2003) Does cross validation provide additional information in the evaluation of regression models? Can J For Res 33:976–987

    Article  Google Scholar 

  • Leary RA (1988) Some factors that will affect the next generation of forest growth models. In: Ek AR, Shifley SR, Burk TE (eds) Forest growth modelling and prediction. USDA Forest Service, St. Paul, pp 22–32, General Technical Report NC-120

    Google Scholar 

  • Leary RA (1997) Testing models of unthinned red pine plantation dynamics using a modified Bakuzis matrix of stand properties. Ecol Mod 98:35–46

    Article  Google Scholar 

  • Liu CM, Leuschner WA, Burkhart HE (1989) A production function analysis of loblolly pine yield equations. For Sci 35:775–788

    Google Scholar 

  • Mayer DG, Butler DG (1993) Statistical validation. Ecol Mod 68:21–32

    Article  Google Scholar 

  • McCarter JB, Wilson JS, Baker PJ, Moffett JL, Oliver CD (1998) Landscape management through integration of existing tools and emerging technologies. J For 96(6):17–23

    Google Scholar 

  • McGaughey RJ (1998) Techniques for visualizing the appearance of forestry operations. J For 96(6):9–14

    Google Scholar 

  • Moeur M, Ek AR (1981) Plot, stand, and cover-type aggregation effects on projections with an individual tree based stand growth model. Can J For Res 11:309–315

    Article  Google Scholar 

  • Myers RH (1990) Classical and modern regression with applications, 2nd edn. Duxbury, Pacific Grove

    Google Scholar 

  • Oderwald RG, Hans RP (1993) Corroborating models with model properties. For Ecol Manag 62:271–283

    Article  Google Scholar 

  • Oreskes N, Shrader-Frechette K, Belitz K (1994) Verification, validation, and confirmation of numerical models in the earth sciences. Science 263:641–646

    Article  PubMed  CAS  Google Scholar 

  • Power M (1993) The predictive validation of ecological and environmental models. Ecol Mod 68:33–50

    Article  Google Scholar 

  • Rauscher HM, Young MJ, Webb CD, Robison DJ (2000) Testing the accuracy of growth and yield models for southern hardwood forests. South J Appl For 24:176–185

    Google Scholar 

  • Reckhow KH, Chapra SC (1983) Confirmation of water quality models. Ecol Mod 20:113–133

    Article  Google Scholar 

  • Rykiel EJ Jr (1996) Testing ecological models: the meaning of validation. Ecol Mod 90:229–244

    Article  Google Scholar 

  • Smith JL, Burkhart HE (1984) A simulation study assessing the effect of sampling for predictor variable values on estimates of yield. Can J For Res 14:326–330

    Article  Google Scholar 

  • Snee RD (1977) Validation of regression models: methods and examples. Technometrics 19:415–428

    Article  Google Scholar 

  • Soares P, Tomé M, Skovsgaard JP, Vanclay JK (1995) Evaluating a growth model for forest management using continuous forest inventory data. For Ecol Manag 71:251–265

    Article  Google Scholar 

  • Stage AR (2003) How forest models are connected to reality: evaluation criteria for their use in decision support. Can J For Res 33:410–421

    Article  Google Scholar 

  • Sterba H, Monserud RA (1997) Applicability of the forest stand growth simulator PROGNAUS for the Austrian part of the Bohemian Massif. Ecol Mod 98:23–34

    Article  Google Scholar 

  • Stoltman AM, Radeloff VC, Mladenoff DJ (2004) Forest visualization for management and planning in Wisconsin. J For 102(4):7–13

    Google Scholar 

  • Tomé M, Soares P (1999) A comparative evaluation of three growth models for eucalypt plantation management in coastal Portugal. In: Amaro A, Tomé M (eds) Empirical and process-based models for forest tree and stand growth simulation. Edições Salamandra/Novas Tecnologias, Lisboa, pp 517–533

    Google Scholar 

  • Van Horn RL (1971) Validation of simulation models. Manag Sci 17:247–258

    Article  Google Scholar 

  • Vanclay JK, Skovsgaard JP (1997) Evaluating forest growth models. Ecol Mod 98:1–12

    Article  Google Scholar 

  • Wang X, Song B, Chen J, Crow TR, LaCroix JJ (2006) Challenges in visualizing forests and landscapes. J For 104:316–319

    Google Scholar 

  • Yang Y, Monserud RA, Huang S (2004) An evaluation of diagnostic tests and their roles in validating forest biometric models. Can J For Res 34:619–629

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Forestry, Virginia Tech, Cheatham Hall 319, Blacksburg, VA, 24061, USA

    Harold E. Burkhart

  2. Instituto Superior de Agronomia DRAT, Universidade Técnica de Lisboa, Tapada da Ajuda, Lisboa, Portugal

    Margarida Tomé

Authors
  1. Harold E. Burkhart
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  2. Margarida Tomé
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© 2012 Springer Science+Business Media Dordrecht

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Burkhart, H.E., Tomé, M. (2012). Model Implementation and Evaluation. In: Modeling Forest Trees and Stands. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3170-9_18

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