How sustainable are the different logging scenarios?
unlogged forests before each logging event. Species composition remains rather stable. The logged volumes per cut still show some fluctuations.
• Comparing the four investigated scenarios with respect to the modification they cause in
forest structure, the low impact logging with a logging cycle of 60 years produces the smallest modifications. The highest yields are obtained for the logging scenarios with a
cycle of 60 years irrespective of the used logging method.
4.1.2. How sustainable are the different logging scenarios?
• One concern of sustainable forest management is the sustainability of timber yields.
Therefore management strategies have to be assessed for the continuity and level of yields produced over a long time period. A second concern of sustainable forest
management is the preservation of the forest ecology and its protective functions such as protection of soil and water.
• In the following the authors want to analyze the simulation results for different logging
scenarios in a more aggregated manner to assess certain criteria for sustainable forest management. Again, we investigate both logging methods conventional and low impact
logging, but enlarge the number of analyzed cutting cycles. We investigated logging cycles ranging from 20 to 100 years. As each simulation includes stochastic mortality
events we repeat the simulation of each scenario five times and average the results.
• For the comparison of the different logging scenarios in relation to their sustainability, the
authors use four indicators: total logged volume, logged volume per cut, species composition, and opening of the forest canopy. The first two indicators refer more to the
economic interest of obtaining a continuous good harvest from the forest over a long period. Both indicators are relevant for management decisions. The other two indicators
are concerned with the ecological state of the forest. The degree of the opening of the stand is used as indicator for the risk of erosion.
• For a comprehensive assessment of the sustainability of logging scenarios, further
indicators would have to be considered such as the compaction of the soil and changes in the nutrient balance. Such effects are currently not incorporated in the model.
Nevertheless, the four indicators used give first indications of the sustainability of the different logging scenarios.
• Fig. 6, shows the total logged volume per year and hectare obtained by simulating
different logging cycles over 400 years. With conventional logging, a cutting cycle of 60 years shows the highest logged volumes with 3.5 m
3
ha year 1400 m
3
ha in 400 years. The cycles of 40 and 80 years produce an intermediate wood output. A cutting cycle of 20
years has the lowest wood output 2.4 m
3
ha year. This indicates that short cycles overuse the forest. For reduced impact logging we get significant higher yields for short
logging cycles 20 and 40 years, P0.001, t test.
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Fig. 6. Results for the simulation of different logging scenarios. Average annual logged volume obtained in 400 years for different cutting cycles and logging methods. Total logged volume is defined as the
accumulated logged volume harvested in 400 years and the harvestable volume at the end of this period. To calculate merchantable wood volume we have to multiply the total logged volume by 0.4
Table 6. Each value is an average of five simulations.
• This logged volume is higher than for conventional logging due to the reduced damage of
the reduced impact logging. The highest logged volumes will be obtained for a logging cycle around 50 years. These cycles produce a wood harvest of nearly 3.75 m
3
ha year. For longer cycles 60 years the yields are nearly identical for both logging methods.
• To calculate the merchantable yields from the simulated logged volumes, the total logged
volume must be multiplied by 0.4. This estimated reduction factor reflects a that only 80 Dipterocarp species group 1 2 are merchantable, b felling and skidding during
harvest, and c that the upper parts of the stems belonging to the crown are left behind in the forest logged volume is stem volume to top of tree, including bark.
• The reduction factor is assumed to be constant over time as a matter of simplification. As
shown in the following, logging causes a shift in the mean species group composition. •
This shift might also influence the fraction of merchantable tree species in species group 1 and 2, an effect which is neglected here.
• Table 6 summarizes the respective results of merchantable yields for the different logging
scenarios shown in Fig. 6. Table 6. Estimated average annual merchantable yields obtained in 400 years for the different
logging cenarios based on a reduction factor of 0.4 and the simulation results displayed in Fig. 6
• Fig. 7 shows logged volume for each cut, which gives information about the yield
continuity. The cycle of 20 years produces the highest fluctuations. For both logging methods, the predefined cycle was often not applicable as the actual standing number of
harvestable trees in the forest was often too low below the minimum of 5 trees. This situation occurs more often in case of conventional logging, but it also occurs for low
impact logging.
• Longer logging cycles 40 years and more do not show such events. Reliable continuous
logged volumes per cut are achieved for cycles of 80 and 100 years only. In these cases,
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the forest has enough time to regenerate to a similar structure before each new logging operation. Thus the logged volumes are stable.
Fig. 7. Simulation results for different logging scenarios. Logged volume obtained per cut over time for different cutting cycles and logging methods. The average annual logged volume over a period of 400
years are shown in Fig. 6.
• The fluctuations of logged volume per cut for logging cycles between 40 and 60 years lead
to the conclusion that the forest has a different structure before every logging and is not fully regenerated.
• From the changes in species composition the authors obtain more details of the impact of
logging scenarios on the ecology of the forest. •
Fig. 8 shows the development of most important tree species groups groups 1, 2, 3. There is a clear trend. Very short logging cycles and conventional logging methods
promote the growth of Macaranga and other pioneers group 3. Accordingly, the volume of Dipterocarp species group 1 2 is reduced. This is the reason for the lower yields of
these logging scenarios.
• Conventional logging always changes the species composition in a forest compared to the
structure of a mature forest. Low impact logging combined with cycles of 60 or more years provide a mean species composition which is nearly the same as in a mature forest.
Nevertheless, small changes in species group composition might be an indicator for considerable changes in single-species composition. It is also possible to get some hints
about the erosion risk connected with the different logging scenarios.
• Erosion processes are not included in the model, but depend on coverage of the ground
with vegetation, on slope, on soil compaction, and logging track alignment. Assuming the same slope and the same soil compaction, we can use the mean ground coverage in the
different logging scenarios as an indicator for erosion risk. Ground coverage can be estimated by means of an opening index, which quantities the fraction of a forest area in
which only small trees is standing no trees above 36 m height.
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Fig. 8. Results for the simulation of different logging scenarios. Mean species group proportions for different utting cycles, logging methods and a mature forest. The proportions are
calculated as the share of the species groups in the stem volume of the whole forest. Each value represents a mean value over 400 years for five simulation runs.
• Fig. 9 shows the opening index for different logging methods and cutting cycles. Logging
scenarios with short cycles increase the gap fraction, and thus raise the risk that erosion damages the soil. The erosion risk is much higher for conventional logging methods,
though the impact of logging operations on soil is not included in the model.
• Logging scenarios with long cycles show a lower opening index 0.55, but still a higher
value than for an undisturbed forest about 0.3. If we would include soil compaction caused by heavy machines into the model, the difference of the erosion risk between
conventional logging and low impact logging would increase.
Fig. 9. Simulation results for different logging scenarios. Degree of canopy opening for different cutting cycles and logging methods. The opening index is defined as the fraction of the
stand area ithout big trees no trees higher than 36 m. The opening of the canopy can be used as an indicator for the risk of soil erosion. Each value is an average of five simulations
over 400 years.
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