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4. Data for the Cost-Benefit Analysis

4.1 General data

Discount rate (r):

The discount rate used in the analysis was set at 10%, reflecting the approximate real interest rate in Sarawak during the study period (Sander, 2000a).

Conversion factor:

A conversion factor is used to adjust financial costs and benefits to reflect economic values. In order to simplify the calculation of shadow prices, a standard conversion factor of 1.2 (i.e., an increase of 20%) was applied to traded financial prices.

Net production area (NPA):

Forest zoning has been used to classify the FSPA area with regard to defined ecological, social, and managerial criteria. One main objective of the zoning is to calculate the net production area where timber production is permitted. The NPA is derived by reducing the gross area of the FSPA by areas reserved for non-timber purposes: protection, community use, permanent infrastructure, rivers, and river buffers (Kleine, 2000).

The financial analysis was carried out for two theoretic blocks with a net production area of 100 ha, representing the average block size within the FSPA.

Net operable area (NOA):

The determination of the net production area (above) is based on topographic maps. Experience with RIL in the FSPA has demonstrated that due to small-scale terrain features like rock outcrops or steep slopes occurring scattered in the area, some sections of the block cannot be harvested. This results in a reduction of the net production area. The remaining net area where trees can be harvested is defined as net operable area (Kleine, 2000).

Under CL this reduction amounts to about 10% of the net production area. Studies in the FSPA have shown that this reduction averages 30% for the RIL system. Hence, regarding the first harvesting operation (1-year calculation period) the net operable area amounts to 90 ha for CL and 70 ha for RIL. The NOA for RIL, however, represents a lowest possible bound and it may be increased through more experience in suitable skidtrail alignment and tree marking procedures.

The net operable area is further reduced after the first harvesting operations by highly compacted skidtrails and log landings.

In the FSPA, Richter (2000) calculated mean losses of production area caused by skidtrail construction in conventionally logged blocks. As a mean for 36 sub-blocks he estimated a loss of 12% in the area of forest due to skidtrails. Butaud (1998) gives estimates of 17% for CL blocks in the MFMA. The average of the two figures, 14.5%, was applied for the CBA computation. The log landing construction leads to a soil compaction of 0.3% of the NOA.

Therefore, the NOA for the second harvesting operation (40-year calculation period) under CL is reduced by 13 ha due to soil compaction. This results in a NOA of 77 ha.

For the RIL blocks, an average skidtrail density of 66 m/ha NOA and an average skidtrail width of 6 m was calculated. Thus, about 4% of the area is subject to compaction. The construction of log landings adds another 0.1%. In comparison with figures given by other authors (e.g., 9%, Pinard et al., 2000) this value seems to be quite low. But, provided that the RIL guidelines are met, the predominantly difficult terrain conditions in the FSPA do not permit higher skidtrail densities.

In applying the above data, the NOA for the second harvesting operation (40-year calculation period) under RIL is reduced by 3 ha, resulting in a NOA of 67 ha.

Rotation period:

Based on first results of DIPSIM simulations (Forest Officer Rani, personal communication) the rotation period for CL and RIL was set at 40 years (i.e., a 40-year calculation period).

Damage to the residual stand:

The results of the damage assessment demonstrated that the percentage of severely damaged trees was reduced from 54% under CL to 28% under RIL (Table 4). The average percentage of damaged trees in the three diameter classes was used for the growth simulation.

 

Table 4. Percentage of trees severely damaged by felling and skidding operations nine months after logging under Conventional Logging and Reduced-Impact Logging, by diameter class for both commercial and non-commercial species.

Conventional Logging

Reduced-Impact Logging

Coupe / Block

Percentage of damaged trees in diameter class [cm dbh]

Coupe / Block

Percentage of damaged trees in diameter class [cm dbh]

10-20

20-40

> 40

Total

10-20

20-40

> 40

Total

[No.]

[%]

[No.]

[%]

8A / 1

53

67

57

57

8A / 3

20

23

14

19

7A / 6

58

55

52

55

8A / 4

26

30

20

26

7A / 24

59

65

64

61

8A / 21

26

26

24

26

7A / 25

41

41

29

38

8A / 22

46

53

29

45

7A / 29

50

61

71

56

8A / 25

39

36

29

36

7A / 51

59

61

66

60

8A / 26

16

21

11

17

Mean

53

58

56

54

 

Mean

29

32

21

28

 

Quality factor (QF):

The use of RIL techniques reduces the damage to the residual stand and therefore leads to an increased quality of the future harvestable stand.

Considering this aspect, a Quality Factor (QF) was introduced. Under CL a QF of 50% was defined; thus 50% of the volume increment is allocated to trees that are defective or damaged. A QF of 65% was set for the management option RIL. In the absence of sound scientific data, these values represent professional estimates.

Utilisation Factor (UF):

The increase of resource utilisation through the application of RIL techniques has been highlighted in a number of recent studies (e.g., Gerwing et al., 1996, Barreto et al., 1998, Sist & Bertault, 1998). According to these studies the major reasons for timber wastage are: (1) logs are felled but not found by the tractor operator; (2) poor felling and bucking techniques; and (3) logs extracted but left behind at the landing. Gerwing et al. (1996) demonstrated that owing to (1) and (2), 27% of the typically extracted volume in Amazonia is wasted under CL, a loss that was reduced to 6% under RIL.

In the FSPA, felling and log extraction are carried out simultaneously, so waste due to overlooked logs was not of great importance. However, timber wasted as a result of poor felling and trimming techniques was considered in the analysis. Therefore the Utilisation Factor (UF) was defined.

Under RIL an UF of 80% was calculated. For CL no data on UF was available. Nevertheless, according to estimates by FDS staff (Forest Officer Jonathan, personal communication) the UF under CL amounts to 75%. In comparison with other studies this difference between RIL and CL appears quite low. Holmes et al. (1999) for example found that RIL techniques reduced the volume of wasted timber by 68% in relation to CL. In the FSPA, however, a high percentage of timber is wasted following the extraction of the logs to the first log landing site.

Log waste (LW):

Under CL the volume of timber wasted due to logs left on the log landing or due to second trimmings amounts to 20% of the total extracted volume. In a planned harvesting operation this kind of timber wastage was eliminated. Thus the LW under RIL was set at 0%.

Extracted volume in the first harvesting operation (1-year period):

According to company records the volume extracted between 1994 and 1999 averaged 44.5 m/ha in conventional logging. This value was used to calculate timber revenues and royalty cost.

However, this information considerably underestimates the actual harvesting volume. Richter (2000) calculated the extracted net volume based on an inventory carried out in the FSPA. This inventory covers 10 CL blocks that were harvested between 1991 and 1996. A comparison of these data with official company figures indicates that on average an additional 20 m/ha (45% of the recorded figure) were extracted for internal uses, e.g., for the construction of bridges, culverts and camp buildings. Thus, the overall harvesting volume under CL totals 64.5 m/ha. Since this figure appears more realistic compared to the official records it was applied for the growth simulation.

The average harvesting volume for the 17 RIL blocks (FSPA and MFMA) amounts to 27.8 m/ha.

Extractable volume in the second harvesting operation (40-year period):

The potential harvesting volume in the second harvesting operation, 40 years after the first cut, was estimated by simulating growth and mortality with DIPSIM (Table 5). The basic parameters used for the DIPSIM calculation are summarised in Appendix 1.

 

Table 5. Gross volume per hectare 40 years after the first harvesting operation; results of a growth simulation with the Dipterocarp Forest Growth Simulation Model, DIPSIM (Ong & Kleine 1995). Results are for 21 harvesting units.

Species group

Gross volume [m/ha]

Conventional Logging

Reduced-Impact Logging

Diameter class [cm dbh]

Diameter class [cm dbh]

10-20

20-45

45-60

> 60

Total

10-20

20-45

45-60

> 60

Total

Com. dipterocarps

2.1

16.2

14.0

28.3

60.5

3.0

21.3

15.5

78.3

118.1

Prot. dipterocarps

0.0

0.3

0.6

1.4

2.3

0.0

0.2

1.0

4.2

5.4

Com. non-dipterocarps

10.8

38.6

15.6

13.1

78.1

14.2

53.4

22.7

29.7

120.0

Non-com. non-dipterocarps

7.6

24.8

11.5

7.2

51.1

9.5

32.6

15.5

10.8

68.4

Prot. non-dipterocarps

0.1

1.6

0.5

2.0

4.2

0.1

1.7

1.1

2.6

5.5

Total non-com. species

7.7

26.7

12.6

10.6

57.6

9.6

34.5

17.6

17.6

79.3

Total com. species

12.9

54.8

29.5

41.4

138.6

17.2

74.7

38.1

108.1

238.1

Harvestable volumea

   

15.6

41.4

57.0

   

22.7

108.1

130.7

Total

20.6

81.5

42.1

52.0

196.3

26.8

109.2

55.8

125.6

317.4

Explanation:
Com. = Commercial
Prot. = Protected
a Commercial non-dipterocarps with dbh 45-60 cm + commercial dipterocarps and commercial non-dipterocarps with dbh > 60 cm.
Basic parameters used for the DIPSIM calculation are summarised in Appendix 1.

 

The simulation for the CL and RIL systems indicated that in 40 years the timber volume available for extraction would be 57 m/ha and 131 m/ha respectively. The results consider the logging damage as well as the Utilisation Factor (UF). But the model does not take into account either the quality factor (QF) or the log waste (LW). To include these factors in the analysis, QF and LW were multiplied with the results of the DIPSIM simulation. After reduction for poor-quality timber and log waste, the net harvestable volume would be 23 m/ha in CL and 85 m/ha in RIL.

The calculation of the Annual Allowable Cut (AAC) was carried out by FDS/FOMISS staff. Based on the results of the DIPSIM simulations (Forest Officer Rani, personal communication) a maximum harvesting volume of 40 m/ha was defined for a cutting cycle length of 40 years. Hence the overall harvestable volume would amount to 23 m/ha under CL and to 40 m/ha under RIL.

Table 6 summarises the assumptions made for the input data that were taken into account for the financial and economic analysis.

 

Table 6. General data and assumptions for the analysis.

No.

General data used for the analysis

Unit

Calculation period

1 year

40 years

CL

RIL

CL

RIL

1

Discount rate

[%]

10

10

2

Conversion factor

1.2

1.2

3

Net production area (NPA)

[ha]

100

100

100

100

4

Area compacted by harvesting operation

[ha]

13

3

5

Net operable area (NOA)

[ha]

90

70

77

67

6

Calculation period; cutting cycle

[y]

1

1

40

40

7

Damage to residual trees in:

 

   

7.1

Diameter class 10-20 cm

[%]

   

53

29

7.2

Diameter class 20-40 cm

[%]

   

58

32

7.3

Diameter class > 40 cm

[%]

   

50

21

8

Quality Factor (QF)

[%]

50

65

9

Utilisation Factor (UF)

[%]

75

80

10

Log waste (LW)

[%]

20

0

11

Results from the DIPSIM simulation:

harvestable volume

[m/ha]

57

131

12

Maximum extractable volume after 40 years

[m/ha]

23

85

13

Total extracted volume per hectare in the net operable area

[m/ha]

44.5

(64.5)

27.8

23

40


Explanation:

CL = Conventional Logging system.
RIL = Reduced-Impact Logging system.
No. 7 = Reduction factor with regard to defective or damaged trees.
No. 8 = Percentage of the wood volume extracted as commercial timber and measured in the stand in relation to the gross volume of the standing tree.
No. 11 = Dipterocarp Forest Growth Simulation Model; simulation results consider no. 7 & 9, but not no. 8 & 10.
No. 12 = DIPSIM results * QF * (1.0 LW)
No. 13 = CL: 44.5 m/ha: the official harvesting intensity was used to calculate timber revenues and royalty cost; in brackets: 64.5 m/ha: the estimated actual volume harvested was used for the DIPSIM calculation.
RIL 40-year period: Considering a growth rate of 1 m/ha/y a maximum harvesting volume of 40 m/ha was defined.

 

4.2 Cost centers for the financial analysis

Two cost centers were considered for the computation of the financial analysis:

4.2.1 Harvesting operations

Only those aspects of the harvesting operation that are influenced by the introduction of RIL techniques were taken into account in the analysis:

Table 7 lists the costs for the individual harvesting components. They include the following elements (for details refer to Appendices 2 to 5): (1) staff; (2) transport; (3) equipment and office supplies; and (4) capital cost (skidding only).

The total costs add up to RM 28/m under CL and RM 43/m under RIL.

Training costs include expenditures for the training of tree fellers and machine operators as well as costs linked with the monitoring of harvesting operations. For the 1-year calculation period these cost centers amounted to RM 6.6/m under the RIL system. Costs related to training and damage assessment inventories were considered as introductory costs. This is why these cost centers were not taken into account for the 40-year calculation period, resulting in a reduction of the overall RIL costs to RM 37/m.

All costs calculated for the first harvesting operation (1-year calculation period) were based on actual production. Advanced practical experience with RIL techniques probably will probably lead to an increase in production. Consequently, this point was considered during the sensitivity analysis.

 

Table 7. Estimated costs of training, harvest planning, harvesting, and post-harvesting operations in Conventional Logging and Reduced-Impact Logging.

No.

Operation / cost centre

Unit

Calculation period

1 year

40 years

CL

RIL

CL

RIL

1

Training

[RM/m]

0.00

6.06

0.00

0.00

2

Harvest planning

2.1

Skidtrail alignment

[RM/m]

0.00

1.87

0.00

1.87

2.2

Mapping of skidtrails

[RM/m]

0.00

0.06

0.00

0.06

2.3

Marking of harvestable trees

[RM/m]

0.50

2.15

0.50

2.15

2.4

Data analysis, digitising

[RM/m]

0.00

0.22

0.00

0.22

2.5

Review of Forest Harvesting Map

[RM/m]

0.00

0.08

0.00

0.08

 

Subtotal

[RM/m]

0.50

4.39

0.50

4.39

3

Harvesting operation

3.1

Skidtrail preparation

         

3.2

Log landing preparation

         

3.3

Tree felling

         

3.4

Winching & Skidding

         
 

Subtotal 3.1-3.4

[RM/m]

27.44

31.70

27.44

31.70

3.5

Cross drains & sediment traps

[RM/m]

0.00

0.00

0.00

0.00

3.6

Treatment of compacted areas

[RM/m]

0.00

0.00

0.00

0.00

 

Subtotal

[RM/m]

27.44

31.70

27.44

31.70

4

Post-harvesting operation

4.1

Damage assessment

[RM/m]

0.00

0.56

0.00

0.00

4.2

RIL compliance assessment

[RM/m]

0.00

0.58

0.00

0.58

 

Subtotal

[RM/m]

0.00

1.13

0.00

0.58

 

Total

[RM/m]

27.94

43.28

27.94

36.67


Explanation:

CL = Conventional Logging.
RIL = Reduced-Impact Logging.
No. 1 = For the second harvest it was assumed that the training costs will not incur (introductory costs).
No. 3.6 = Not actually carried out.
No. 4.1 = Only realised for the first harvest (introductory costs).
NOTE: = Costs include staff, transport, equipment/office supplies, and capital costs (skidding only). Costs reflect actual costs; no discounting has been applied. For further details refer to Appendices 2-5.

 

4.2.2 Royalties

Table 8 shows the royalty rates by species groups (FDS, 1998). Actually, a royalty rebate of 80% is given for domestically processed logs. The average royalty cost per m, weighted by species share, is RM 37/m. The total costs of royalty payments under the two management options were calculated by multiplying the weighted average royalty rate per m with the total extraction volume.

 

Table 8. Royalty rates per m by species groups.

Species group

Share of growing stock

Royalty rate

Export quotas under

Export

Domestic

CL

RIL

[%]

[RM/m]

[%]

Meranti

57

90

18

40

40

Kapur/Keruing

22

63

13

40

40

Selangan Batu

5

36

7

40

40

MLH

16

27

5

40

40

Weighted mean

 

71

14

   
Source: Forest Department Sarawak (1998)

Explanation:

CL = Conventional Logging system
RIL = Reduced-Impact Logging
MLH = Mixed Light Hardwoods

 

4.3 Revenues for the financial analysis

Two types of revenues were considered for the computation of the financial analysis:

4.3.1 Timber

Timber price:

The timber prices given by Sander (2000b) were used for the calculation of timber revenues.

Export quota:

For calculating timber revenues under CL and RIL, an export quota of 40% was used. A price difference of 17.5% between domestic prices and international export prices was applied (Sander, 2000a).

Certification premium:

A 10% certification premium was added to the timber prices for RIL.

Timber value:

With regard to the assumptions made under the three points above, the total timber value was determined by multiplying the average price per m timber with the total harvesting volume as calculated in Section 4.1.

Cost cover accounting:

In order to calculate the estimated contribution that timber harvesting would make toward covering forest management costs, all forest operation costs, other than those costs related directly to harvesting operations and royalties, were subtracted from the timber value determined as described above.

Sander (2000a) calculated a BCR of 1.21 for Conventional Logging operations in the FSPA (60 year period). Thus the profit ratio (= cost/revenues) from timber harvesting amounts to 17% (= 1-1/1.21) and the forest operation costs to 83% respectively. This calculation takes account of all forest operation costs. For the actual analysis it was determined that 70% of the total timber revenues under CL (= RM 221/m) are spent on forest operations, excluding costs for harvesting operations and timber royalties and other license fees.

Furthermore, it was assumed, that general operation costs of the two management options are equal. Thus an amount of RM 221/m was subtracted from the weighted timber price, resulting in an estimated profit (before tax) of RM 95/m and RM 126/m under CL and RIL respectively.

Table 9 gives an overview of the data used for timber revenue calculation.

 

Table 9. Data used for the calculation of timber revenues for the management options Conventional Logging (CL) and Reduced-Impact Logging (RIL)

Species group

Share on growing stock

Price

Export quotas under

Weighted price under

Export

Domestic

CL

RIL

CL

RILa

[%]

[RM/m]

[%]

[RM/m]

Meranti

57

366.0

302.0

40

40

187.0

205.0

Kapur/Keruing

22

390.0

322.0

40

40

77.0

84.0

Selangan Batu

5

433.0

357.0

40

40

19.0

21.0

MLH

16

221.0

182.0

40

40

32.0

35.0

Weighted price per m

351.4

289.9

   

314.5

346.0

Timber value after deduction of costsb

     

94.4

125.8


Explanation:

MLH = Mixed Light Hardwoods
a Including a certification premium of 10%.
b Profit ratio: 30% = Assuming a deduction of costs of 70% of the weighted timber price under CL:
Total financial benefit per m under CL = 314.5 (314.5 * 0.70) = 94.4
Total financial benefit per m under RIL = 346.0 (314.5 * 0.70) = 125.8

 

4.3.2 Carbon trading

Carbon sequestration through forestry is a function of biomass accumulation and storage. Hence, any management option changing the biomass of a forest stand affects the ecosystems capacity to store or sequester carbon (Moura Costa, 1996). The application of RIL techniques reduces the rate of release of carbon (carbon conservation) relative to a Conventional Logging system.

A study on the quantification of the amount of carbon that could be traded as Certified Tradable Offsets (CTO) in the FSPA is not yet available. Considerable uncertainty surrounds the market price and the potential cash flow from CTOs. Therefore, the benefits from carbon trading were not included in the financial analysis but were considered as a component of the sensitivity analysis (Section 5.4).

4.4 Cost centers for the economic analysis

Only the costs of the harvesting operation were taken into account for the economic analysis.

4.4.1 Harvesting operations

The economic analysis considers the same components of the harvesting operation as the financial analysis. The percentage of costs of tradable goods relative to the total harvesting costs was estimated for the individual sub-centers of the two management options:

Training: 0%
Harvest planning: 2%
Harvesting operation: 70%
Post-harvest operations: 2%

These tradable cost components were multiplied with the standard conversion factor of 1.2 in order to estimate the economic values of the harvesting operations.

4.5 Revenues for the economic analysis

The following aspects were considered for the economic analysis:

4.5.1 Timber

For the economic analysis of timber revenues it was assumed that export prices reflect real scarcity values. Consequently, the economic value of timber revenues was calculated by multiplying the extraction volume with the average export price, weighted with their species share. This results in average timber prices of RM 351/m for CL and RM 387/m for RIL, including a 10% certification premium. After deduction of the overall forest operation costs as described under Section 4.3.1, the economic values of timber revenues were RM 105 and RM 167 per m under CL and RIL respectively.

4.5.2 Carbon stocks

Carbon stocks for non-production areas (primary forest) and net operable areas under CL and RIL were estimated by applying the data on gross volume obtained from the DIPSIM simulations.

The current cost of topical forestry carbon offsets ranges from US$2-10 per ton of carbon, averaging about US$8 (Stuart & Moura Costa, 1998). This average was used for the valuation of carbon stocks. The total value of carbon stocks per 100 ha NPA amounts to RM 452,208 and to RM 496,156 under CL and RIL respectively. These values of carbon stocks were translated into flows by calculating annuities, taking into account a discount rate of 10% (Table 10).

 

Table 10. Valuation of carbon stocks for the Conventional Logging (CL) system and the Reduced-Impact Logging (RIL) system.

No.

Parameter

Unit

Harvesting system

CL

RIL

1

Area per block

     

1.1

Non-production area

[ha]

10

30

1.2

Net operable area

[ha]

90

70

2

Carbon stocks per hectare

     

2.1

Non-production area

[t/ha]

166

166

2.1

Net operable area

[t/ha]

144

162

3

Value of carbon stocks

     

3.1

Carbon value

[RM/t]

30.32

30.32

3.2

Non-production area

[RM/ha]

5,032

5,032

3.3

Net operable area

[RM/ha]

4,367

4,927

3.4

Total value per NPA

[RM/100 ha]

452,208

496,156

4

Annuity per block

[RM/100 ha/y]

45,221

49,616


Explanation:

No. 1.1 = Non-production area = Net production area net operable area
No. 2 = Calculated with formula (1), (2) and (3) p. 12/13; data on stand volume was obtained from Dipterocarp Forest Growth Simulation Model (DIPSIM) simulations (see Appendix 6) for 21 harvesting units; values represent the average for a 40-year rotation period.
No. 3.1 = US$8/t carbon (Stuart & Moura Costa, 1998).
No. 4 = At a discount rate of 10%.

 

4.5.3 Non-Timber Forest Products (NTFP)

The economic valuation of Non-Timber Forest Products (NTFPs) for the two harvesting options was based on an approach used by Sander (2000a), which incorporates a legal decision of the High Court of Johor Baru in 1996 (Baru, 2000). The legal ruling determined that a compensation of RM 1236/ha had to be paid to local communities for land lost due to the construction of a reservoir.

In order to account for different economic values of NTFPs under different forest management options, Sander (2000a) applied a percentage-based valuation. In adopting this method the following was defined: (1) non-production areas provide 100% of NTFP value (RM 1236/ha); (2) production forest under CL produces 50% of the NTFP value; and (3) production forest under RIL generates 70% of the value. These data are summarised in Table 11.

By multiplying the respective areas of the two harvesting systems with the above values, the total NTFP value per 100 ha NPA was obtained. Since the CBA deals with flows of resources the hectare-based figures have to be transformed into flows. Annuities were calculated by discounting (Table 11) and then incorporated as annual NTFP values into the CBA.

 

Table 11. Valuation of Non-Timber Forest Products (NTFPs) for the Conventional Logging (CL) system and the Reduced-Impact Logging (RIL) system.

No.

Parameter

Unit

Harvesting system

CL

RIL

1

Area per block

     

1.1

Non-production area

[ha]

10

30

1.2

Net operable area

[ha]

90

70

2

Value of NTFP

     

2.1

Non-production area

[RM/ha]

1,236

1,236

2.2

Net operable area

% of 2.1

50

70

2.3

Net operable area

[RM/ha]

618

865

2.4

Total value per NPA

[RM/100 ha]

67,980

97,643

3

Annuity per block

[RM/100 ha/y]

6,798

9,764

Source: Adopted from Sander (2000a)

Explanation:
No. 1.1 = Non-production area = Net production area net operable area
No. 2.4 = NPA: Net production area
No. 3 = At a discount rate of 10%

 

4.5.4 Soil values

Forest harvesting can influence the functioning of a forest ecosystem and ultimately its economic value. Possible hydrological changes include soil erosion, increased sediment delivery, increased runoff or sub-surface flows, and changes in the water table. These hydrological effects are linked with economic impacts such as loss of productivity to downslope farmers, damage to fisheries, or flood damage to settlements (Chomitz & Kumari, 1998). In order to integrate these negative externalities into the CBA of the two harvesting systems, the relative economic benefits of preventing soil erosion were estimated.

Again, the figures given by Sander (2000a) were used for the economic analysis of harvesting systems. He used a value of RM 104/ha/y for total watershed protection, which was adopted from Kumari's (1995) study in Peninsular Malaysia.

To discriminate the different soil erosion prevention benefits of CL and RIL a percentage-based valuation approach was applied.

Glauner (2000) used a management factor, C, which was originally developed by Wischmeier & Smith (1978) for erosion modelling. A value of C = 0.001 is commonly used to represent undisturbed forests. In contrast a value of C = 1.0 is appropriate for barren land with severe erosion present. Conventional logging techniques lead to an increase of C by a factor of 20 relative to undisturbed forests, and within 10 years C returns to the original value (Glauner, 2000). According to Marsh et al. (1996) the application of RIL techniques increases C by a factor of 5 and cuts the time of recovery relative to CL by half (Table 12).

 

Table 12. Soil-erosion management factor (C) by harvesting system and disturbance class.

Harvesting system / disturbance class

C factor

Factor in relation to undisturbed forest

Percentage of maximum soil erosion benefit valuea

Yearb

[%]

[n]

Undisturbed forest

0.001

1

100

1 40

Reduced-Impact Logging

0.005

5

20

1 5

Conventional Logging

0.020

20

5

1 10

Compacted areas

1.000

1000

0

1 40

Source: Modified from Glauner (2000)

Explanation:
a Following Kumari (1995a), the maximum soil erosion prevention benefit was set at 104 RM/ha/y.
b Period of time in which the individual C factor was used for the calculation of the soil erosion benefit. As an example, for CL in years 1 to 10 the percentage of maximum soil erosion benefit value = 5% and in years 11 to 40 the value equals 100%

 

Based on these C-values it was assumed that non-production areas provide 100% of the maximum soil erosion prevention value (RM 104/ha/y), whereas the percentage is reduced to 20% and 5% under CL and RIL respectively. Compacted areas (skidtrails and log landings) were rated with 0%. By multiplying the respective areas of the management options with these values and by taking into account the different time frames for recovery, the total soil erosion prevention benefits per 100 ha NPA were obtained (Table 13).

 

Table 13. Evaluation of benefits with regard to soil erosion prevention under Conventional Logging (CL) and Reduced-Impact Logging (RIL).

No.

Parameter

Unit

Harvesting system

CL

RIL

1

Area per block

1.1

Non-production area

[ha]

10

30

1.2

Total net operable area

[ha]

90

70

1.3

Compacted areas within net operable area

[ha]

13

3

2

Soil erosion prevention value

2.1

Non-production area

[RM/ha/y]

104.2

104.2

2.3

Net operable area

[RM/ha/y]

5.2

20.8

2.4

Compacted area

[RM/ha/y]

0.0

0.0

3

Annuity per block

3.1

Years 1-10 (CL) and years 1-5 (RIL)

[RM/100 ha/y]

1,442

4,526

3.2

Remaining time period

[RM/100 ha/y]

9,034

10,126

Explanation:
No. 1.1 = Non-production area = Net production area net operable area

 

4.5.5 Recreational values

Recreational values are highly localised and scale-dependent. Forests in particular are internally quite heterogeneous. Any forest area is likely to contain many varieties and densities of species, types of terrain and areas that are more or less accessible to markets. This diversity results in different recreational values of forests.

For the CBA it was assumed that the NOA managed under CL does not provide any recreational value. The recreational value of non-production areas was set at RM 19/ha/y (Pearce et al., 1999). In accordance with Sander (2000a) the same recreational value was applied for areas managed under RIL. By multiplying these values with the respective areas the following annual recreational benefits per block (100 ha) were obtained: RM 189.5 for CL and RM 1895.0 for RIL.

4.5.6 Biodiversity values

Estimating the economic value of biodiversity or genetic resources is difficult because species extinction cannot be reversed. It is impossible to predict the preferences of future generations and present benefits are difficult to balance against future costs (McNeely & Vorhies, 2000).

In spite of these problems the valuation of biodiversity was included in the CBA in order to point out the relative differences of the studied harvesting systems. In adopting the values given by Sander (2000a) an annual biodiversity benefit of RM 11.4/ha/y was assumed for non-production forest areas. Furthermore it was hypothesised that under CL only 50% of this biodiversity value is maintained in comparison to 70% under RIL. This difference accounts for the lower intensity of disturbance, protection of fruit trees, and other factors. By multiplying the individual values with the respective areas, the estimated annual economic value of biodiversity per block was derived as RM 625 for CL and RM 898 for RIL.

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