Abstract
In the whole-stand approach, quantities such as volume, basal area and/or number of trees per unit area are forecast. The input or predictor variables for whole-stand models are typically age, site index, and stand density. Approaches for ensuring analytic compatibility and numeric consistency between growth and yield estimates are discussed, and a detailed example of specifying and fitting an interdependent system of growth and yield equations in which all relationships are assumed to hold simultaneously is given. Mixed-effects techniques for growth and yield predictions are briefly described. The state space approach to stand modeling, in which the state of a stand at any given time is assumed to be the necessary and sufficient information need to determine its future behavior, is described in detail.
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References
Avery TE, Burkhart HE (2002) Forest measurements, 5th edn. McGraw-Hill, New York, NY
Beekhuis J (1966) Prediction of yield and increment in Pinus radiata stands in New Zealand. New Zealand Forest Service, Wellington, Forest Research Institute Technical Paper 49
Borders BE (1989) Systems of equations in forest stand modeling. For Sci 35:548–556
Borders BE, Bailey RL (1986) A compatible system of growth and yield equations for slash pine fitted with restricted three-stage least squares. For Sci 32:185–201
Bruce D (1977) Yield differences between research plots and managed forests. J For 75:14–17
Buckman RE (1962) Growth and yield of red pine in Minnesota. USDA Forest Service, Washington, DC, Technical Bulletin 1272
Buckman RE, Bishaw B, Hanson TJ, Benford FA (2006) Growth and yield of red pine in the Lake States. USDA Forest Service, Washington, DC, General Technical Report NC-271
Burkhart HE (1986) Fitting analytically related models to forestry data. In: Proceedings invited papers, XIIIth international biometric conference, Seattle, WA, 15pp
Burkhart HE, Sprinz PT (1984) Compatible cubic volume and basal area projection equations for thinned old-field loblolly pine plantations. For Sci 30:86–93
Chapman DG (1961) Statistical problems in dynamics of exploited fisheries populations. In: Proceedings of 4th Berkeley Symposium Mathematical Statistics and Probability. University of California Press, Berkeley, pp 153–168
Clutter JL (1963) Compatible growth and yield models for loblolly pine. For Sci 9:354–371
Coble DW (2009) A new whole-stand model for unmanaged loblolly and slash pine plantations in east Texas. South J Appl For 33:69–76
Curtis RO (1967) A method of estimation of gross yield of Douglas-fir. For Sci Monograph 13:1–24
Curtis RO (1972) Yield tables past and present. J For 70:28–32
Curtis RO, Clendenen GW, DeMars DJ (1981) A new stand simulator for coast Douglas-fir: DFSIM user’s guide. USDA Forest Service, Washington, DC, General Technical Report PNW-128
Furnival GM, Wilson RW Jr (1971) Systems of equations for predicting forest growth and yield. In: Patil GP, Pielou EC, Waters WE (eds) Statistical ecology, vol 3. Pennsylvania State University Press, University Park, pp 43–55
García 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
García O (1988) Growth modelling – a (re)view. N Z J For 33(3):14–17
García O (1994) The state-space approach in growth modelling. Can J For Res 24:1894–1903
García O (2011) A parsimonious dynamic stand model for interior spruce in British Columbia. For Sci 57:265–280
García O, Ruiz F (2003) A growth model for eucalypt in Galicia. Spain For Ecol Manage 173:49–62
García O, Burkhart HE, Amateis RL (2011) A biologically-consistent stand growth model for loblolly pine in the Piedmont physiographic region. USA For Ecol Manage 262:2035–2041
Gregoire TG (1987) Generalized error structure for forestry yield models. For Sci 33:423–444
Gregoire TG, Schabenberger O, Barrett JP (1995) Linear modelling of irregularly spaced, unbalanced, longitudinal data from permanent-plot measurements. Can J For Res 25:137–156
Hall DB, Clutter M (2004) Multivariate multilevel nonlinear mixed effects models for timber yield predictions. Biometrics 60:16–24
Huuskonen S, Miina J (2007) Stand-level growth models for young Scots pine stands in Finland. For Ecol Manage 241:49–61
MacKinney AL, Chaiken LE (1939) Volume, yield, and growth of loblolly pine in the mid-Atlantic coastal region. USDA Forest Service, Washington, DC, Technical Note 33
MacKinney AL, Schumacher FX, Chaiken LF (1937) Construction of yield tables for nonnormal loblolly pine stands. J Agric Res 54:531–545
Murphy PA (1983) A nonlinear timber yield equation system for loblolly pine. For Sci 29:582–591
Murphy PA, Beltz RC (1981) Growth and yield of shortleaf pine in the West Gulf region. USDA Forest Service, Washington, DC, Research Paper SO-169
Murphy PA, Sternitzke HS (1979) Growth and yield estimation for loblolly pine in the West Gulf. USDA Forest Service, Washington, DC, Research Paper SO-154
Murphy PA, Lawson ER, Lynch TB (1992) Basal area and volume development of natural even-aged shortleaf pine stands in the Ouachita Mountains. South J Appl For 16:30–34
Nord-Larsen T, Johannsen VK (2007) A state-space approach to stand growth modelling of European beech. Ann For Sci 64:365–374
Ochi N, Cao QV (2003) A comparison of compatible and annual growth models. For Sci 49:285–290
Pienaar LV, Harrison WM (1989) Simultaneous growth and yield prediction equations for Pinus elliottii plantations in Zululand. South African For J 149:48–53
Pienaar LV, Shiver BD (1986) Basal area prediction and projection equations for pine plantations. For Sci 32:626–633
Pienaar LV, Turnbull KJ (1973) The Chapman-Richards generalization of von Bertalanffy’s growth model for basal area growth and yield in even-aged stands. For Sci 19:2–22
Reed DD, Jones EA, Bottenfield TR, Trettin CC (1986) Compatible cubic volume and basal area equations for red pine plantations. Can J For Res 16:416–419
Richards FJ (1959) A flexible growth function for empirical use. J Exp Bot 10:290–300
Sadiq RA (1983) Estimation of stand basal area growth and yield with a reverse logistic function. Can J For Res 13:289–297
Schultz EB, Iles JC, Matney TG, Ezell AW, Meadows JS, Leininger TD, Booth WC, Jeffreys JP (2010) Stand-level growth and yield component models for red oak-sweetgum forests on mid-south minor stream bottoms. South J Appl For 34:161–175
Schumacher FX (1939) A new growth curve and its application to timber-yield studies. J For 37:819–820
Sullivan AD, Clutter JL (1972) A simultaneous growth and yield model for loblolly pine. For Sci 18:76–86
Sullivan AD, Reynolds MR (1976) Regression problems from repeated measurements. For Sci 22:382–385
Tang S, Meng CH, Meng F-R, Wang YH (1994) A growth and self-thinning model for pure even-age stands: theory and applications. For Ecol Manage 70:67–73
Van Deusen PC (1988) Simultaneous estimation with a squared error loss function. Can J For Res 18:1093–1096
West PW, Ratkowsky DA, Davis AW (1984) Problems of hypothesis testing of regressions with multiple measurements from individual sampling units. For Ecol Manage 7:207–224
Zhang Y, Borders BE (2001) An iterative state-space growth and yield modeling approach for unthinned loblolly pine plantations. For Ecol Manage 146:89–98
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Burkhart, H.E., Tomé, M. (2012). Whole-Stand Models for Even-Aged Stands. In: Modeling Forest Trees and Stands. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3170-9_11
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DOI: https://doi.org/10.1007/978-90-481-3170-9_11
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