Analysis of biomass accumulation and stem size distributions over long periods in managed stands of Pinus sylvestris in Finland using the 3-PG model.

We tested the performance of a process-based model (PBM) in relation to long-term mensuration data from two sites in Finland where the stands were up to 90 years old and had been thinned at approximately 5-year intervals over the last 50 years. The PBM used was based on the 3-PG (Physiological Principles to Predict Growth) model developed by Landsberg and Waring (1997), with modifications in the biomass allocation routine, for which we used data and calculations by Vanninen (2003) to estimate the allocation coefficients and turnover rates. Site fertility was estimated in terms of known site-type characteristics. The model was evaluated in terms of stand development and its ability to simulate responses to thinning; stem numbers after thinning were specified at the dates when the thinning took place. Stand development in terms of basal area, volume and mean diameter at breast height, closely followed the measured characteristics of all stands. Foliage mass predictions were close to estimates obtained by an empirical method. The analysis shows that, under normal thinning regimes, a range of different thinning intensities can be adequately described using a simple multiplicative model relating the proportion of volume and foliage mass removed to the corresponding proportion of stem numbers. This model, together with stem allometry data, described the "growth" in mean diameter after thinning, which simply reflected the removal of the smaller trees. These results indicate that, with a single set of parameter values, 3-PG can provide good descriptions of the growth patterns of trees-in this case Pinus sylvestris L.-over long periods, including growth after repeated thinning. One of the outputs from the 3-PG model is mean stem diameter (B): we show that it is feasible to estimate stem size distributions, which changed considerably over the life of these stands, from B using the Weibull function. This shows that, given information about the Weibull parameters for particular species and cultural systems, it should be possible to use stem numbers and the B obtained from the 3-PG model to produce information about stem size distributions from simulated data.

[1]  A. Lehtonen Estimating foliage biomass in Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) plots. , 2005, Tree physiology.

[2]  A. Mäkelä,et al.  Effects of tree size and position on pipe model ratios in Scots pine , 2005 .

[3]  Petteri Vanninen,et al.  Carbon budget for Scots pine trees: effects of size, competition and site fertility on growth allocation and production. , 2005, Tree physiology.

[4]  Frank Berninger,et al.  Carbon balance of different aged Scots pine forests in Southern Finland , 2004 .

[5]  J. Moncrieff,et al.  Top-down models and flux measurements are complementary methods of estimating carbon sequestration by forests: illustrations using the 3-PG model. , 2004 .

[6]  Joe Landsberg,et al.  Modelling forest ecosystems: state of the art, challenges, and future directions , 2003 .

[7]  N. Coops,et al.  Performance of the forest productivity model 3-PG applied to a wide range of forest types , 2003 .

[8]  S. Kellomäki,et al.  Below- and above-ground biomass, production and nitrogen use in Scots pine stands in eastern Finland , 2002 .

[9]  P. Sands,et al.  Parameterisation of 3-PG for plantation grown Eucalyptus globulus , 2002 .

[10]  Nicholas C. Coops,et al.  Assessing forest productivity at local scales across a native eucalypt forest using a process model, 3PG-SPATIAL , 2001 .

[11]  P. Stenberg,et al.  Shoot structure and photosynthetic efficiency along the light gradient in a Scots pine canopy. , 2001, Tree physiology.

[12]  Kurt H. Johnsen,et al.  Applying 3-PG, a Simple Process-Based Model Designed to Produce Practical Results, to Data from Loblolly Pine Experiments , 2001, Forestry sciences.

[13]  N. Coops,et al.  Assessing forest growth across southwestern Oregon under a range of current and future global change scenarios using a process model, 3‐PG , 2001 .

[14]  Nicholas C. Coops,et al.  Estimates of New Zealand forest and scrub biomass from the 3-PG model , 2000 .

[15]  Alan R. Ek,et al.  Process-based models for forest ecosystem management: current state of the art and challenges for practical implementation. , 2000, Tree physiology.

[16]  Richard H. Waring,et al.  A process model analysis of environmental limitations on the growth of Sitka spruce plantations in Great Britain , 2000 .

[17]  Harry T. Valentine,et al.  Estimation of the net primary productivity of even-aged stands with a carbon-allocation model , 1999 .

[18]  William E. Winner,et al.  Foliage physiology and biochemistry in response to light gradients in conifers with varying shade tolerance , 1999, Oecologia.

[19]  Nicholas C. Coops,et al.  Assessing forest productivity in Australia and New Zealand using a physiologically-based model driven with averaged monthly weather data and satellite-derived estimates of canopy photosynthetic capacity , 1998 .

[20]  D. M. Nanang Suitability of the Normal, Log-normal and Weibull distributions for fitting diameter distributions of neem plantations in Northern Ghana , 1998 .

[21]  H. Gholz Applications of Physiological Ecology to Forest Management , 1997 .

[22]  R. Waring,et al.  A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning , 1997 .

[23]  R. K. Dixon,et al.  Process modeling of forest growth responses to environmental stress , 1991 .

[24]  Peter Pfeifer,et al.  A Method for Estimation of Fractal Dimension of Tree Crowns , 1991, Forest Science.

[25]  D. N. Geary,et al.  Characterizing diameter distributions by the use of the Weibull distribution , 1985 .

[26]  P. G. Jarvis,et al.  Canopy Structure and Leaf Area Index in a Mature Scots Pine Forest , 1982 .

[27]  A. Cajander,et al.  Forest types and their significance. , 1949 .