Simulations and analysis

The results of the no-harvest simulation showed that at the beginning the ingrowth of pines decreased slowly while the number of trees of medium size increased due to upgrowth. After four 5-year periods the stand began to close with a high basal area of 37.6 m² ha^-1, a reduced number of pine trees in the 15 cm diameter class and an accumulation of pines in the 60 cm diameter class (Fig 3).

The ingrowth of broadleaved species also declined but at a slower rate, leading to an increased share of broadleaved species in the composition of the stand, with 35.2% of the number of trees and 24.0% of the total basal area after 20 years.

Pines

0 10 20 30 40 50 60

15 20 25 30 35 40 45 50 55 60 Diameter class (cm)

Stems·ha-1

Year 1997 Year 2002 Year 2007 Year 2012 Year 2017

Broadleaved species

0 10 20 30 40 50 60

15 20 25 30 35 40 45 50 55 60 Diameter class (cm)

Stems·ha-1

Year 1997 Year 2002 Year 2007 Year 2012 Year 2017

Fig. 3. Diameter distribution in an unmanaged forest after 20 years.

The simulation for the harvest regime in well-stocked stands covered four 5-year periods.

The average removed volume per period amounted to 37.1 m³ ha^-1 and the productivity is 7.4 m³ ha^-1 yr^-1 (Table 4). A high proportion of the harvested roundwood belonged to the highest diameter classes, so that 35% of the pine timber produced could be classified as grade I, or logs with a thin-end diameter greater than 35 cm.

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Table 4. Average number and volume of harvested trees per ha distributed on diameter classes. Average for a 5-year period in the simulation of harvesting well stocked stands.

After 20 years of selection management, a balanced dbh distribution was obtained (Fig. 4) which was characterised by a basal area before harvest of 20 m² ha^-1, of which 16.6% were broadleaved species, which amounted to 20.7 % of the number of trees.

Pines

Year 1997 Year 2002 Year 2007 Year 2012 Year 2017

Broadleaved species

Year 1997 Year 2002 Year 2007 Year 2012 Year 2017

Fig. 4. Development of diameter distributions after 20 years with a harvest cycle of 5 years in a well-stocked stand.

The third simulation involved moderate harvesting to allow the recovery of an understocked stand (Fig. 5). Only 40% of the annual growth was harvested in this simulation. The result was an increase of the stocking to a basal area of 15 m² ha^-1 or a volume of 114.10 m³ ha^-1. The average growth of the stand was 5.36 m³ ha^-1. Due to the low harvest yield of 2.35 m³ ha^-1, it can be expected that the stand will become fully stocked very soon.

Pines

0 10 20 30 40

15 20 25 30 35 40 45 50 55 60 Diameter class (cm)

Stems·ha-1

Year 1997 Year 2002 Year 2007 Year 2012 Year 2017

Broadleaved species

0 10 20 30 40 50 60

15 20 25 30 35 40 45 50 55 60 Diameter class (cm)

Stems·ha-1

Year 1997 Year 2002 Year 2007 Year 2012 Year 2017

Fig. 5. Development of diameter distributions after 20 years with a harvest cycle of 5 years in an understocked stand.

4. Discussion

The potential to commercially grow mixed broadleaved species and maritime pine stands depends mainly on the conifer ingrowth and upgrowth which greatly affects the attainment of a balanced size distribution and adequate growth rates. This essential condition seems to be difficult to achieve with a very light-demanding species like P. pinaster. However, the type of uneven-aged management presented in this paper has been suggested and applied in similar forest types involving other pine species (Pinus taeda L., Pinus echinata Mill.) and broadleaved species in the South Eastern USA (Baker and Murphy, 1982; Baker, 1989).

4.1. The matrix growth model

The basal area coefficients in the logistic regression for probability of ingrowth have, as expected, positive sign for both broadleaved species and conifers. All coefficients in the equations for probability of ingrowth, except the intercept in the equation for conifers, were significant at least at the 0.01% level as judged by the Wald χ² statistic (Hosmer and Lemeshow, 1989). 72% of the data were successfully identified by the equation for conifers and 63.8% in case of broadleaved species.

For the ingrowth regression, the coefficients for N (the number of trees of the same species) had a positive sign. Also the stand basal area had the expected negative sign in the regressions for pines as well as for the broadleaved species. The coefficients of determination (R²) were quite low in both the pines and in the broadleaved model, implying that a small percentage of the ingrowth was explained by the model. This may be due to the differences in the harvest selections practiced in the various plots, i.e. to the lack of common management guides.

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The independent variables in the equations estimating the transition probabilities were basal area of conifers and broadleaved sp., squared basal area and diameter (Tab. 2). The coefficient of determination showed that the pine model explains about 15% of the variation in the upgrowth process whereas in the broadleaved species model this value decreases to 7%.

These values are quite low, but similar to the results obtained by other authors who also found that the upgrowth of broadleaved species was more difficult to explain (Buongiorno et al., 1995; Volin et al., 1996).

The probability of mortality is affected by the basal area and the tree size represented by the breast height diameter. In the case of conifers these variables were significant at least at the 0.1% level as defined by the Wald χ² statistic and 62.3% of the data were successfully identified by the model. In the case of broadleaved species the coefficients were significant at least at the 0.001% level and 59.4% of the data were successfully identified by the equation.

The mortality of broadleaved species seems to be more difficult to explain. This phenomenon has also been observed in other studies (Volin et al., 1996; Rautiainen, 1999).