Study of Supply and Demand of Industrial Roundwood...1. Reports on Commercial Timber Resources and...

S T U D Y O F S U P P L Y

A N D D E M A N D O F

I N D U S T R I A L R O U N D W O O D

i n S o u t h A f r i c a

J A N U A R Y 2 0 0 5

Study of Supply and Demand

of Industrial Roundwood in South Africa

Period 2005 to 2034

January 2005

Disclaimer : Although the information is presented in good faith and believed to be correct, the Department of Water Affairs and Forestry makes no representations or warranties as to the completeness or accuracy of the information and makes no commitment to update or correct information. Opinions expressed do not necessarily reflect the views of DWAF.

CONTENTS

1. BACKGROUND AND TERMS OF REFERENCE...................................................................... 1

1.1 Acknowledgements........................................................................................................ 1

2. EXECUTIVE SUMMARY ....................................................................................................... 2

3. THE IMPORTANCE OF COMMERCIAL FORESTRY IN SOUTH AFRICA.................................. 5

4. METHODOLOGY AND CONSTRAINTS IN ASSESSING ROUNDWOOD,

CHIPS AND WASTE SUPPLY ............................................................................................... 6

4.1 Growth of Trees: 2002 to 2005..................................................................................... 7

4.2 Simulated Felling Areas ................................................................................................ 7

4.3 Phasing out of Pine Sawlog Areas .................................................................................. 7

4.4 Environmental Standards Area Allowance ....................................................................... 7

4.5 Areas in Age Classes Older than the Rotation Age .......................................................... 8

4.6 Area Allowance for Delays in Re-establishment .............................................................. 8

4.7 Volume Allowance for Fire and Severe Weather Damage (Appendices H) ......................... 8

4.8 Net Increase/Decrease in Planted Area per Genus: 1991/1992 to 2001/2002(Appendices I) ............................................................................................................... 9

4.9 Mass to Volume Conversion Ratios (Appendix E).............................................................. 9

4.10 Mean Annual Increments at Rotation Age (Appendices F) ................................................. 10

4.11 Wattle Areas ................................................................................................................. 10

4.12 Wattle Jungle Areas (Appendix J).................................................................................... 10

4.13 History of Roundwood Purchases 1991/1992 to 2001/2002 (Appendix K) ....................... 10

5. SUPPLY (OTHER THAN SAWLOGS)..................................................................................... 11

5.1 Growing Stock by Genus and Age.................................................................................. 11

5.2 Yields by Genus and Region........................................................................................... 12

5.3 Projected Yields – 2005 to 2034 .................................................................................... 13

5.4 Resources in Other SADC Countries ............................................................................... 14

5.4.1 Swaziland ......................................................................................................................... 14

5.4.2 Zimbabwe......................................................................................................................... 14

5.4.3 Malawi ............................................................................................................................. 14

5.4.4 Mozambique..................................................................................................................... 15

5.4.5 Angola and Zambia .......................................................................................................... 15

5.4.6 Tanzania .......................................................................................................................... 15

5.5 New Forest Areas .......................................................................................................... 15

5.6 Recommended Action to Expand the Resource................................................................. 18

6. METHODOLOGY AND CONSTRAINTS IN FORECASTING THE DEMAND............................ 18

7. EXPECTED DEMAND OTHER THAN FOR SAWLOGS ........................................................... 19

7.1 2005 Demand for Roundwood Other than Sawlogs ........................................................ 19

7.2 2005 Pulpwood Demand for Waste................................................................................ 20

7.3 Summary of Total Use (including Waste and Sawlogs) ..................................................... 20

STUDY OF SUPPLY AND DEMAND OF INDUSTRIAL ROUNDWOOD IN SOUTH AFRICA iJanuary 2005

7.4 Comment on the Expected Demand ............................................................................... 20

7.4.1 Pulp and Paper ................................................................................................................. 21

7.4.2 Board Mills ....................................................................................................................... 22

7.4.3 Chipping Plants................................................................................................................. 22

7.4.4 Mining Timber................................................................................................................... 23

7.4.5 Log Exports ....................................................................................................................... 23

7.4.6 Poles ................................................................................................................................ 23

7.4.7 Charcoal Timber ............................................................................................................... 24

7.4.8 Summary of Known Adjustments ........................................................................................ 25

8. SUPPLY AND DEMAND PROJECTIONS FOR ROUNDWOOD OTHER THAN SAWLOGS ....... 26

9. TOTAL SUPPLY AND DEMAND OF ALL ROUNDWOOD INCLUDING SAWLOGS................. 27

9.1 Softwood Sawlogs ......................................................................................................... 27

9.2 Eucalypt Sawlogs........................................................................................................... 27

9.3 Supply and Demand including Softwood and Hardwood Sawlogs .................................... 28

9.4 Reconciliation of Past Performance with Forecasts............................................................ 29

9.5 The Changes that have Occurred to Supply the Market.................................................... 30

10. SENSITIVITY ANALYSIS ...................................................................................................... 30

10.1 Demand ....................................................................................................................... 30

10.2 Supply .......................................................................................................................... 31

10.3 Other Factors that could Influence the Forecasts.............................................................. 31

LIST OF TABLES

1. Analysis of Supply and Demand: 2005 – 2034: All Genera including sawlogs prior to anygrowth scenarios....................................................................................................................... 2

2. South Africa’s Timber Usage (tons)............................................................................................. 33. Analysis of Supply and Demand: 2005 – 2034: Pine (excluding sawlogs)................................... 34. Analysis of Supply and Demand: 2005 – 2034: Eucalypts (excluding sawlogs) ........................... 35. Analysis of Supply and Demand: 2005 – 2034: Wattle (excluding sawlogs)................................ 46. Analysis of Commercially Afforested Areas: South Africa, Australia, Chile, New Zealand, Brazil.... 57. Number of People Employed in the South African Timber Industry ............................................... 68. Areas to be Phased Out (ha)...................................................................................................... 79. Net Increase/Decrease in Planted Area per Genus: 1991/1992 to 2001/2002 ........................... 910. Wattle Jungle Areas .................................................................................................................. 1011. Growing Stock by Genus and Age ............................................................................................. 1112. Yields by Genus and Region ...................................................................................................... 1213. Projected Yields – 2005 to 2034 ................................................................................................ 1314. Plantation Areas by Genus – Swaziland ...................................................................................... 1415. Age Area Distribution by Genus – Zimbabwe.............................................................................. 1416. Average Annual New Plantings in South Africa and some Other Southern Hemisphere Countries .. 1517. Summary of Potential Suitable and Available Areas for Afforestation ............................................ 1618. Afforestable Areas in the Previously Independent Homelands....................................................... 1619. 2005 Demand for Roundwood Other than Sawlogs.................................................................... 1920. 2004/5 Pulpwood Demand for Waste........................................................................................ 2021. Summary of Total Use (including waste and sawlogs) 2005......................................................... 2022. Particle Board and MDF Market (Tons) ....................................................................................... 2223. Treated Pole Sales: 1996 – 2003 in ‘000 m³ ............................................................................ 2424. Projected Shortfall – All Genera in tons ...................................................................................... 2625. Projected Shortfall – Eucalypt in tons .......................................................................................... 2626. Projected Shortfall – Pine in tons ................................................................................................ 2627. Projected Shortfall – Wattle in tons ............................................................................................ 2728. Summary of Supply and Demand including Sawlogs in tons ........................................................ 2829. Roundwood Production ex. Planations by Mass ........................................................................... 2930. Scenarios One to Three............................................................................................................. 3131. Allowance for Environmental Compliance .................................................................................. 3132. Scenarios Four to Six ................................................................................................................. 32

ii STUDY OF SUPPLY AND DEMAND OF INDUSTRIAL ROUNDWOOD IN SOUTH AFRICA

January 2005

LIST OF FIGURES

1. Forest Products’ Exports Compared to Other Industries ............................................................... 5

2. 5-Year Averages for Pulpwood Projections: All Regions .............................................................. 8

3. Growing Stock by Genus and Age ............................................................................................. 11

4. Forecast by Genus and Region .................................................................................................. 12

5. Roundwood Production ex. Plantation – Pulpwood (tons) ............................................................. 21

6. Roundwood Production ex. Plantation – Mining Timber (tons) ...................................................... 23

7. Roundwood Production ex. Plantation – Poles (tons) .................................................................... 23

8. Roundwood Production ex. Plantation – Charcoal and Firewood (tons)......................................... 25

APPENDICES

A LOCALITY MAP OF PLANTATIONS AND PROCESSING PLANTS .................................................. 33

B REGIONAL YIELD FORECASTS OF ROUNDWOOD OTHER THAN SAWLOGS IN TONS –2005 TO 2034 ......................................................................................................................... 34

C ESTIMATED DEMAND FOR ROUNDWOOD (OTHER THAN SAWLOGS) CHIPS AND WASTE –2004 TO 2009 ......................................................................................................................... 43

D AREAS BY AGE, GENUS AND REGION ..................................................................................... 50

E CONVERSION RATIOS – TONS/M³ .......................................................................................... 59

F ESTIMATED MAI PER PRODUCT TYPE BY GENUS........................................................................ 60

G AREAS ACCORDING TO THE MAIN PURPOSE FOR WHICH THE TREES ARE GROWN.................. 65

H AREAS DAMAGED BY FIRE AND SEVERE WEATHER CONDITIONS – 1991 TO 2002 .................... 68

I NET INCREASE/DECREASE IN AREA BY GENUS 1991/1992 TO 2001/2002 ............................... 70

J WATTLE JUNGLE AREAS............................................................................................................ 73

K HISTORICAL ANNUAL PURCHASES REPORTED IN THE ANNUAL COMMERCIALTIMBER RESOURCE TABLES......................................................................................................... 74

L ESTIMATE OF CHIP SOURCE..................................................................................................... 75

M FORESTRY OUTPUT AND CONTRIBUTION TO THE ECONOMY – 1979/1980 TO 2002/2003.... 76

N FORECAST OF ROUNDWOOD SUPPLY INCLUDING ADJUSTMENTS.......................................... 77

O SUPPLY AND DEMAND LEVELS EXCLUDING SAWLOGS ADJUSTED BY PUBLISHED/KNOWN INCREASES ONLY ...................................................................................................... 78

P SOFTWOOD SAWLOG SUPPLY AND DEMAND PROJECTION – TABLE 26 .................................. 79

LIST OF REFERENCES

1. Reports on Commercial Timber Resources and Primary Roundwood Processing in South Africa1991 – 2002

2. Forestry Guide Plan for South Africa 1982

3. Strategic Forestry Development Plan 1989

4. Supply and Demand Study of Softwood Sawlog and Sawn Timber 2004 - CA

5. Roundwood Supply and Demand to 2030 – LHA

6. National Forestry Action Plan

7. Lumber Index – Crickmay & Associates (Pty) Ltd.

8. Forestry South Africa – various reports

9. Studies done on Forestry in Australia, Chile and New Zealand – M Smith

10. Reports on Treated Poles – SAWPA

11. SADC Forestry Reports – CA

12. Sundry Sawmilling and Processing reports – CA

STUDY OF SUPPLY AND DEMAND OF INDUSTRIAL ROUNDWOOD IN SOUTH AFRICA iiiJanuary 2005

ABBREVIATIONS

a.s.l. Above sea levelCA Crickmay & Associates (Pty) Ltd.CIT Chipboard Industries (Transkei) (Pty) Ltd.COMPAS Computerised Plantation Analysis SystemCSIR Council for Scientific and Industrial ResearchCTC The Central Timber Co-op Ltd.DBSA Development Bank of South AfricaDWAF Department of Water Affairs and ForestryEIA Environmental Impact AssessmentFES Forestry Economics ServicesFSA Forestry South AfricaFSC Forestry Stewardship CouncilISO International Standards OrganisationLCM Low Cost SawmillsLHA Louis Heyl & AssociatesLPI Lumber Price IndexMAI Mean Annual IncrementMDF Medium Density FibreboardMMRC Mensuration and Modelling Research ConsortiumMTO Mountain to Ocean ForestryNFAP National Forestry Action PlanNCT NCT Forestry Co-operative Ltd.SABS South African Bureau of StandardsSADC Southern African Developing CountriesSAFCOL South African Forestry Company LimitedSALMA South African Lumber Miller’s AssociationSANS South African National StandardsSAWGU South African Wattle Growers UnionSAWPA South African Wood Preservers AssociationTons In the text means metric tonnesTWK Transvaal Wattle Kweekers (Kooperasie) Bpk, since 1999 TWK Landbou Beperk

DEFINITIONS

Mean Annual IncrementThe average annual growth of a given plantation harvested over a full rotation for a given area. In this case, one hectare.Expressed in this report as tons per hectare per annum because the bulk of the harvest is sold in tons rather than in cubicmeters.

HarvestThe total utilisable volume or tonnage removed, i.e. harvested.

Sustainable YieldThe volume or tonnage that can be harvested on an ongoing basis without diminishing the resource.

All RoundwoodRefers to industrial roundwood prior to conversion and includes sawlogs, pulpwood, poles, mining timber, firewood androundwood used for the manufacture of charcoal, etc.

Domestic RoundwoodTimber derived from non commercial plantations which is used for building and fencing poles and for firewood of whichfirewood is the greatest and has been stated to comprise 40% to 50% of all roundwood used. Domestic roundwood is notincluded in this study.

Wattle JungleRefers to self generated uneven aged and unthinned plantations which are frequently harvested for specific roundwood types.

Timber IndustryComprises the growing and conversion of industrial roundwood forest products.

ProjectionsThese are arithmetic projections based on known data.

ForecastsAre projections which have been adjusted to take account of uncertainties.

iv STUDY OF SUPPLY AND DEMAND OF INDUSTRIAL ROUNDWOOD IN SOUTH AFRICA

January 2005

1. BACKGROUND AND TERMS OF REFERENCE

Following a recently published supply and demand study on softwood sawlogs in South Africa, it was consideredthat a similar study for roundwood other than sawlogs should be developed. This study was commissioned by

the Department of Water Affairs and Forestry and has been undertaken by Crickmay & Associates (Pty) Ltd.

It is important to note that this report addresses only the industrial and not the domestic use of timber, e.g. hutpoles, firewood, etc., which has been estimated by the CSIR to be approximately equal to 40% to 50% of allroundwood used.

Furthermore, this report focuses on roundwood other than sawlogs but does incorporate the results of the sawlogstudy in Sections 9 and 10.

The object of the study is to establish the supply and demand on regional and national levels with the followingTerms of Reference:

• Project the demand for industrial roundwood and chips for pulp and board plants, taking into account thedemand for mining timber, treated poles, charcoal and related products.

• Project fibre availability by genus and by region for overall industry planning and marketing.

• Avoid the question of ownership of the resource.

• Provide through quantifying supply and demand a means of communication between the forest industry andthe Government to facilitate development and protection of the industry.

• Facilitate easy updating of supply and demand data and accommodate improved input in the future.

• Provide updated standard norms of conversion of volume to mass.

• Provide generally achieved Mean Annual Increment figures by genus and region.

The window period runs from 2005 to 2034.

The measure used throughout this study is metric tons other than the section dealing specifically with sawlogswhere the measure is cubic meters.

1.1 ACKNOWLEDGEMENTS

This study has been compiled by Crickmay & Associates in a team comprising of D G Crickmay, J Le Brasseur,Prof J A Stubbings and A E Daugherty.

Messrs Edwards and Godsmark of Forestry South Africa have assisted with their comments, as have Dr Diekvan der Zel and many others from growers, timber co-operatives, sawmillers, pulp and paper, particleboard, mining timber manufacturers and pole treaters.

Reference is made to the Forestry Guide Plan for South Africa 1982, the Strategic Forestry Development Planfor South Africa 1989 and the Supply and Demand Study of Softwood Sawlog and Sawn Timber 2004.

Forest Economics Services were most helpful in providing information.

In finalising this report Louis Heyl & Associates’ projections prepared for DWAF were checked against theforecasts and projections contained herein. Our forecast and the end of LHA’s 30-year window period wereremarkably close, although derived from completely different methodology.

Constructive comments submitted by DWAF in an assessment of the draft study have been incorporated inthe final report.

Forestry South Africa have given their formal approval of this report.

STUDY OF SUPPLY AND DEMAND OF INDUSTRIAL ROUNDWOOD IN SOUTH AFRICA 1January 2005

2. EXECUTIVE SUMMARY

2.1 CONCLUSION

This study concludes that the existing plantation resource is insufficient to supply current marketsand the shortage becomes more serious with time. The shortage is alleviated to some extent in theinitial ten years by the accelerated harvesting of over-age Eucalypt plantations. The sustainableannual harvest amounts to 13.5 million tons while the demand is 17.3 million tons (excludingsawlogs). If Pine and Eucalypt sawlogs are included then the annual demand increases to 23.0million tons but the sustainable harvest is 19.8 million tons.

If an allowance is made for growth of 3%, the demand increases to 31.9 million tons resulting ina shortfall of 12.6 million tons at the end of the window period. A further 785,275 hectares ofnew plantings will be required to make up the shortfall.

The shortfall for domestic processing could be alleviated if necessary and profitable to do so, bysubstituting the 5.1 million tons of chips being exported annually for local processing.

2.2 The primary source of information for the study is the latest report on Commercial Timber Resources andPrimary Roundwood Processing in South Africa 2001/2002 (Para 4.0).

2.3 Updated information on roundwood volume : mass ratios for different periods of air drying is provided(Appendix E) as well as Mean Annual Increments generally achieved by genus and region (Appendices F).

2.4 In projecting demand, current usage and known expansion to local downstream processing have beenincluded (Para 7.4) as well as different scenarios of expected real growth and possible interchanging ofroundwood between sectors (Para 10.3).

2.5 In projecting supply and current total plantation area of 1,399,241 ha is used (Table 9, Para 4.8), yieldregulation is based on rotation age/area (Para 4.1) and allowances are made for the following:

• Projections of tree growth from 2002 to base year 2005 (Para 4.1).

• Simulated clearfelling areas (Para 4.2 and 4.5).

• Phasing out of Pine sawlog areas (Para 4.3).

• Area allowance for implementing environmental standards (Para 4.4, Table 31).

• Area allowance for delays in re-establishment (Para 4.6).

• Volume allowance for fire losses (Paras 4.7 and 10.2).

2.6 A summary of the supply and demand over the window period of 2005 to 2034 in five year averages issummarised as follows:

TABLE 1: Analysis of Supply and Demand: 2005 – 2034: All Genera including sawlogs prior to any growth scenarios

FIVE YEAR PERIODTOTAL SUPPLY

(tons)TOTAL

DEMAND (tons)

SURPLUS (+) / SHORTFALL (-)

(tons) (%)

2005 – 2009 20,550,761 23,249,214 -2,698,453 -13.1

2010 – 2014 20,087,199 23,932,910 -3,845,711 -19.1

2015 – 2019 18,609,931 24,650,053 -6,040,122 -32.5

2020 – 2024 19,454,356 25,448,516 -5,994,160 -30.8

2025 – 2029 18,666,332 26,372,899 -7,706,567 -41.3

2030 – 2034 18,134,701 27,501,409 -9,366,708 -51.7

Estimated sustainable supply: 19,250,547 25,192,500 -5,941,953 -23.2

(Table 28)

2 STUDY OF SUPPLY AND DEMAND OF INDUSTRIAL ROUNDWOOD IN SOUTH AFRICA

January 2005

2.7 In 2005, South Africa will use 23.5 millions tons of timber including sawlogs and waste, which is made upas follows (Para 7.3, Table 21 and Appendices C):

TABLE 2: South Africa’s Timber Usage (tons)

2005 ‘000s Tons

Roundwood 17,238

Waste and chips 688

Imports 271

Softwood sawlog 5,070

Eucalypt sawlog 184

TOTAL 23,451

2.8 South Africa has 73,000 ha of Eucalypts in excess of ten years of age. These have been assumed to befelled over the first nine years in this forecast and has contributed to suppressing the shortage prior to 2013(Para 5.1, Table 11).

2.9 The supply and demand by genus from 2005 to 2034 show that supplies of Pine pulpwood are almost inbalance but there is a serious shortage of Eucalypt and Wattle pulpwood (Section 8).

TABLE 3: Analysis of Supply and Demand: 2005 – 2034: Pine (excluding sawlogs)


(tons)TOTAL

DEMAND (tons)


(tons) (%)

2005 – 2009 4,576,051 3,266,000 1,310,051 40%

2010 – 2014 4,225,485 3,242,000 983,485 30%

2015 – 2019 3,116,840 3,242,000 -125,160 -4%

2020 – 2024 3,197,740 3,242,000 -44,260 -1%

2025 – 2029 4,441,426 3,242,000 1,199,426 37%

2030 – 2034 3,372,768 3,242,000 130,768 4%

Estimated sustainable supply: 3,821,700

TABLE 4: Analysis of Supply and Demand: 2005 – 2034: Eucalypt (excluding sawlogs)


(tons)TOTAL

DEMAND (tons)


(tons) (%)

2005 – 2009 9,963,574 12,272,400 -2,308,826 -19%

2010 – 2014 9,376,974 12,340,000 -2,963,026 -24%

2015 – 2019 8,050,747 12,340,000 -4,289,253 -35%

2020 – 2024 8,597,568 12,340,000 -3,742,432 -30%

2025 – 2029 7,143,001 12,340,000 -5,196,999 -42%

2030 – 2034 8,728,321 12,340,000 -3,611,679 -29%



TABLE 5: Analysis of Supply and Demand: 2005 – 2034: Wattle (excluding sawlogs)


(tons)TOTAL

DEMAND (tons)


(tons) (%)

2005 – 2009 1,252,124 1,643,000 -390,876 -24%

2010 – 2014 941,921 1,623,000 -681,079 -42%

2015 – 2019 1,203,738 1,623,000 -419,262 -26%

2020 – 2024 886,027 1,623,000 -736,973 -45%

2025 – 2029 1,147,182 1,623,000 -475,818 -29%

2030 – 2034 840,782 1,623,000 -782,218 -48%


2.10 Plantation expansion rate has slowed dramatically and reasons and suggested corrective actions are givenin Paragraphs 5.5 and 5.6.

2.11 COMMENT AND RECOMMENDATIONS

The forest industry is important:

• Employing 129,160 people directly (516,640 including dependants);

• Contributing R18.7 billion per annum to the GDP;

• Second only to coal in exports;

• Contributing 9.7% to agricultural GDP;

• Is internationally highly accredited environmentally and is therefore a strong candidate for accreditation

of the benefits of carbon sequestration.

If the timber supply is unable to meet demand and South Africa has to resort to cutting productionor importing either roundwood chips or manufactured products, e.g. sawn timber, there will be asubstantial loss of jobs and revenue. On the other hand, if the industry can establish a further785,275 ha it will provide direct employment for 72,300 people and benefit the country to thetune of R10.4 billion.

In compiling this report certain serious problems confronting the timber industry became clear and inour view need to be addressed. These include the following:

• The release of land on this scale will need the help of Government.

• Continue improving vigour and productivity of the trees.

• Continue to improve recoveries of converting roundwood.

• Review the cumbersome and costly systems of processing afforestation licences.

• Improve forest protection to decrease losses from fires, pests, etc.

• Upgrade accuracy of plantation inventory.

To do this there needs to be substantial improvements in the profileand appreciation of the forest industry.


January 2005

3. THE IMPORTANCE OF COMMERCIAL FORESTRY IN SOUTH AFRICA

South Africa used to be a world leader in commercial afforestation with the best technology in propagatingclones and seedlings as well as in silviculture and management of man-made forests. Unfortunately much of

this expertise has been lost to overseas countries, particularly Australia, New Zealand, Brazil and Chile.

Commercial forestry in South Africa has been widely criticised from an environmental and water conservation point ofview. This negative attitude according to Forestry South Africa, who represents many of the stakeholders, is oftenunjustified. It is said to restrict and inhibit development of plantations, despite the fact that compared to the rest of theworld, South Africa has the highest proportion of its plantations environmentally accredited at 81% and thereforeinternationally ranks highly as a candidate for accreditation for the benefits of applying carbon sequestration.However, FSA believe that these efforts have not been generally acknowledged and the forest industry has continuedto be discriminated against and its strategic and commercial value under-rated. Some important facts are as follows:

• Comparison of the total plantation area of 1.40 million hectares in South Africa (which covers only 1.2% of thetotal land area), with other southern hemisphere countries is as follows:

TABLE 6: Analysis of Commercially Afforested Areas: South Africa, Australia, Chile, New Zealand and Brazil

COUNTRY TOTAL AREA

COMMERCIAL FORESTRY AREA (ha) (Exotic only)

Hardwood Softwood Other Total% of totalArea ofCountry

South Africa 122,103,000 699,306 699,934 8,045 1,399 241 1.2%

Australia 768,000,000 675,962 988,223 1,508 1,665,693 0.22%

Chile +/- 95,690,000 340,000 1,500,000 160,000 2,000,000 20.9%

New Zealand 27,053,000 52,000 1,590,000 127,000 1,769,000 6.54%

Brazil N/A 2,300,000 1,500,000 N/A 3,800,000 Not Known

SOURCE: Web sites.Approximate areas only.

• Forestry and forest products contribute 18.7 billion Rand or 1.55% to the overall GDP of South Africa and9.7% to the Agriculture, Fisheries and Forestry GDP.

• Forest products’ ranked second only to coal as exports, the comparison being as follows:


(Appendix N)

Figure 1: Forest Products’ Exports Compared to Other Industries

• The timber industry employs approximately 129,160 people directly as shown below:

TABLE 7

SECTOR NUMBER OF EMPLOYEES

Forestry 67,460

Sawmilling 21,000

Mining Timber 2,200

Pulp and Paper 15,000

Panel/Particleboard 5,400

Treating/Poles 5,800

Charcoal 5,500

Pallet/Cable Drums/Fruit Bins, etc. 1,400

Roof Trusses 2,400

Timber Transport 3,000

TOTAL 129,160

If the number of those employed directly were extended by a factor of four to include their dependants, thenumber of people dependent on the timber industry amounts to 516,640. Most of these people areemployed in the rural areas where gainful employment is most needed. Furthermore, it is estimated thatabout 30% to 40% of the employees are female.

4. METHODOLOGY AND CONSTRAINTS IN ASSESSING ROUNDWOOD, CHIPS AND

WASTE SUPPLY

The primary source of information used to assess potential roundwood supply is the Report on CommercialTimber Resources and Primary Roundwood Products in South Africa 2001/2002, which is the latest such report

available. The integrity of the information depends upon the input from the growers. In this regard the followingcomments apply:

• Professionally managed companies, such as Sappi, Mondi, Safcol, Masonite, Steinhoff, Hans Merensky, NCT andCTC comprise approximately 70% of the forest area and their input is likely to be accurate.

• FES advises that the small grower schemes, such as Khulanathi and Sappi Grow have information submittedby the co-ordinating body and these are included in the resource.

• If there are inaccuracies in the commercial forestry data they are most likely to be found in the independentgrowers, some of whom may slip through the data collection net. However, these are likely to be the smallerrather than medium or larger of the independent growers. It is acknowledged by FES however that if there areerrors they will be as a result of omissions and not overstatements therefore errors are likely to understate ratherthan overstate the resource. FES advise that in applying their checks and balances they are confident that themaximum understatement of the resource is 90,000 ha at the very most, i.e. 6.3% of the total but that it is likely tobe no more than half of that, say 3.5%. Assuming that the extent of the understatement in area would have thesame proportionate affect in yield then at the outside this would account for a relatively small volume of say500,000 tons per annum. This allowance has been included in the supply.

Based on these comments the methodology adopted for assessing and factors affecting the forecast supply aredescribed in the paragraphs that follow.


January 2005

4.1 GROWTH OF TREES: 2002 to 2005

The yield regulation in this study was based on age/area, i.e. effective area divided by rotation age,multiplied by Mean Annual Increment at rotation age.

Data from the Report on Commercial Timber Resources and Primary Roundwood Processing in South Africa2001/2002 was taken and grown to the start year, 2005, merely by simulating felling and replanting areasas they reached rotation age. Wattle data (as of June 2003) was obtained from industry sources and treatedin the same way. Wattle jungle data was acquired from SAWGU and other sources and it is assumed thatonly 50% of the Wattle jungle area will be rehabilitated and no further timber being generated from the other50% for commercial purposes. No attempt was made to smooth the annual harvests.

4.2 SIMULATED FELLING AREAS

In the 30 year window period a similar process of simulated felling and replanting as described in 4.1 abovewas used to obtain the volumes used for the projections. Because of an imbalance in age classes, smoothing ofyields was done over the period 2009 to 2013 for Eucalypt and 2013 to 2022 for Pine. Mean annual yieldswere agreed between the authors and can be checked (Appendices F).

4.3 PHASING OUT OF PINE SAWLOG AREAS

An allowance was made for the phasing out of the Pine sawlog areas listed in Table 8 from Pine sawlogproduction. In this projection the areas were systematically phased out to fit in with the simulated fellingareas and not replanted. The effect on the pulpwood yields from these areas was taken into account for thepurposes of this study.

TABLE 8

REGION AREA TO BE PHASED OUT (ha)

Limpopo 9,000

Zululand 7,000

Southern Cape 35,000

Western Cape 14,345

TOTAL 65,345

SOURCE: DWAF

Only four of the regions are mentioned as these are the major areas of concern. This is independent of anyreductions for environmental reasons as shown in Para 4.4.

4.4 ENVIRONMENTAL STANDARDS AREA ALLOWANCE

An initial environmental standards compliance area allowance of 5% is applied in the first rotation of theshorter rotation areas and in the first half of the longer (Pine sawlog and Pine pulpwood) rotation areas. Afurther 2.5% is deducted from the second rotation for the short rotation areas and in the second half of thelonger rotations. Several growers feel that the allowance is too low, but DWAF believe anything more than2.5% is excessive and this has been accepted with some reservation. The area allowance was applied bynot replanting areas as they were felled in the simulation (Table 31).


4.5 AREAS IN AGE CLASSES OLDER THAN THE ROTATION AGE

Areas in age classes older than the rotation age were treated separately in the simulation and felled overthe following periods:

Pine sawlog 2 periodic blocks = 10 yearsPine pulpwood ½ a rotation = 9 yearsEucalypt pulpwood one rotation = 9 yearsWattle ½ a rotation = 5 years

The sustainable supply of 12.1 million tons indicated in Figure 2 has been based on the yields over the last20 years of the window period. This means that the accumulated over-age timber has not been included inthe sustainable supply, which makes the 12.1 million tons per annum slightly conservative.

4.6 AREA ALLOWANCE FOR DELAYS IN RE-ESTABLISHMENT

Allowances have been made for the delay in replanting of felled areas on the assumption that only 50% ofannual felling is re-established in the year of felling and the other half the year after. This has been done byadjusting annually replanted areas downwards, as follows:

Pine sawlog production Plantable area ÷ 28 years ÷ 2 or 1.8%Pine pulpwood production Plantable area ÷ 18 years ÷ 2 or 2.8%Eucalypt pulpwood production Plantable area ÷ 9 years ÷ 2 or 5.6%Wattle bark and pulpwood production Plantable area ÷ 10 years ÷ 2 or 5.0%

4.7 VOLUME ALLOWANCE FOR FIRE AND SEVERE WEATHER DAMAGE

Fire and weather damage data were collated from the Report on Commercial Timber Resources andPrimary Roundwood Processing in South Africa 1991/1992 – 2001/2002 and final volumes were reducedby the calculated average losses per region (Appendices H). Averages show an annual loss of 1.8% of Pineareas and 1.4% of Hardwood areas. No account has been taken of the apparent recent escalation in theextent of fire damage. While Swaziland plantations have not been included in the growing stock theroundwood yield and lumber sold into South Africa has been included. Recently Swaziland has alsosuffered an increase in the incidence and severity of fires, which has an influence, albeit indirectly, on thesupply into South Africa.


January 2005

Figure 2:

The percentages referred to are the reduction in potential production per annum of Pine or Hardwoodsrespectively. No allowance has been made for salvage.

The scenario explained in Para 10.2 shows an increase in allowance for fire damage based on recent losses.

Snow damage experienced about every ten years in KwaZulu-Natal has recently been extensive in the Wattleplantations with mature damaged plantations having to be felled prematurely and immature plantationshaving to be abandoned and re-established. No allowance has been made for these potential losses.

4.8 NET INCREASE/DECREASE IN PLANTED AREA PER GENUS: 1991/1992 to 2001/2002 (Appendices I)

In order to generate the data for this, Appendix I was used. All losses and gains for each genus werecalculated (i.e. conversions from Pine to Eucalyptus, Eucalyptus to Wattle, Wattle to Agriculture, etc., and areasafforested in each case). The trend of the gains of planted areas for each genus (Pine, Eucalyptus andWattle) is distinctly downward as indicated in Table 9 below.

TABLE 9:

GENUSAVERAGE ANNUAL CHANGE IN AREA (ha) TOTAL AREA IN 2001

(Wattle 2003) (ha)1992 – 2001 1997 – 2001

Pine 1,596 -885 699,934

Wattle 501 459 128,049

Wattle Jungle - - 47,100

Eucalypt 4,024 1,198 524,158

TOTAL 6,121 772 1,399,241

SOURCE: Report on Commercial Timber Resources and Primary Roundwood Processing in South Africa: 2001/2002.NOTE: Negative values are reductions.

In the case of Wattle there has been an increase in planting in the last five years but there seems to be aslow down in the rate of new plantings in the last year and this may have been as a result of the recentdecrease in the price of Wattle pulpwood.

Eucalypts showed a considerable increase from 1992 to 1996 but this dropped dramatically between1997 and 2001 largely as a result of decline in demand for mining timber.

Pine shows a steady decrease between 1991 and 2001 and the trend has now become negative as a resultof conversions to Eucalypt pulpwood plantations.

As the trends are downward and areas for all genera have or will shortly become negative (except possiblyfor Wattle where the volumes in general are small), no allowance is made for any gains in afforested areain the simulated window period. Instead the present situation is regarded as static as far as the areas pergenus are concerned.

4.9 MASS TO VOLUME CONVERSION RATIOS

Roundwood, other than sawlogs, traditionally has been purchased in tons, but the working plan dataparticularly for Pine are expressed in cubic meters, making the volume to mass ratio critical in calculatingthe forecast yields.

The extent of air drying, i.e. the time between felling and the time of timber being purchased has changedin the case of Eucalypts from six weeks to an average of three weeks and the volume/mass ratio haschanged accordingly. The volume/mass ratios used in this study that could be adopted for the sake ofconsistency are given in Appendix E.

Normally pulpwood is estimated and sold in tons (metric tonnes), therefore, all estimates in this report arequoted in tons, unless otherwise stated.


4.10 MEAN ANNUAL INCREMENTS AT ROTATION AGE (Appendices F)

Mean annual increment figures used are estimates only, based as realistically as possible on the opinionsand experience of those involved in compiling this study.

4.11 WATTLE AREAS

Wattle areas and ages, except for Wattle jungle estimates (Para 4.12 below), were obtained from industrysources, then compared with the figures in the Report on Commercial Timber Resources and PrimaryRoundwood Products in South Africa 2001/2002. These former estimates were found to be some 16%higher and are preferred because the recent usage indicates that the resource is likely to be greater thanthat contained in the Commercial Timber Resources and Primary Roundwood Processing in South Africa2001/2002.

4.12 WATTLE JUNGLE AREAS (Appendix J)

Areas of Wattle jungle indicated by timber co-operatives as additional to those listed in Commercial TimberResources and Primary Roundwood Processing in South Africa 2001/2002 have been included. It isbelieved that these jungle areas exist but that they are not reported because they are not formalplantations.

It is estimated that 47,100 ha exist as jungle with yields of 3 tons/ha/annum during the first 10 years of thewindow period. Thereafter the area is expected to be reduced by approximately half but managed ascommercial plantations, albeit less intensively, with increased yields to 5 tons/ ha/annum as shown inTable 10.

TABLE 10: Analysis of Wattle Jungle Areas

REGION

FIRST ROTATION(10 yrs)

FOLLOWING TWO ROTATIONS(20 yrs)

Period(years)

Area(hectares)

MAI(tons per hectare

per year)

Yield perAnnum

(tons)

Period(years)

Area(hectares)


per year)

Yield perAnnum

(tons)

Mpumalanga South 10 23,100 3.0 69,300 20 12,800 5.0 64,000

Northern KwaZulu-Natal 10 6,000 3.0 18,000 20 3,300 5.0 16,500

Eastern Cape 10 18,000 3.0 54,000 20 10,000 5.0 50,000

Initial Total Area/Yield: 47,100 141,300 26,100 130,500

NOTE: Areas and MAI’s were estimated.

A yield of 5 tons/ha/annum was determined in consultation with the co-operatives and it may be conservative,but we are in favour of being conservative as it is not a standard crop and is sensitive to poor management.

4.13 HISTORY OF ROUNDWOOD PURCHASES 1991/1992 to 2001/2002

The history of roundwood purchases as obtained from the Report on Commercial Timber Resources andPrimary Roundwood Processing in South Africa 1991/1992 – 2001/2002 is reproduced in Appendix K andshows total annual pulpwood purchases reported by processors to have been 10 million tons. But, theannual pulpwood production in the report as being supplied by the growers over the same period was 8.7million tons per annum as reported by Forestry South Africa (Table 29). This significant differenceillustrates the problems with accuracy being experienced with the Commercial Timber Resources andPrimary Roundwood Processing annual figures supplied by the growers.

These figures provided by growers have been ignored for the purposes of this study. The consumption asreported by the processors is considerably more accurate and is used throughout this study and shown inAppendix K.


January 2005

5. SUPPLY (OTHER THAN SAWLOGS)

5.1 GROWING STOCK BY GENUS AND AGE

The 1,399,240 ha of commercial plantations are accounted for as follows:

TABLE 11: Areas Used in the Study in Hectares by Genus and Age Class in Five Year Age Groupings on 01/06/2002*: All Regions

AGE IN YEARS PINE E.GRANDISOTHER

EUCALYPTUSSPECIES

WATTLE*As on

30/06/2003TOTAL

Temporarily Unplanted 45,253 10,209 6,908 10,078 72,449

0 – 4 151,568 119,421 108,916 55,242 435,147

5 – 9 160,254 118,814 86,587 52,464 418,118

10 – 14 142,153 34,973 21,435 9,182 207,743

15 – 19 86,931 8,363 2,165 1,083 98,542

20 – 24 55,050 1,407 600 - 57,056

25 – 29 34,042 897 285 - 35,225

30 + 24,683 1,517 1,661 - 27,861

Wattle Jungle - - - 47,100 47,100

TOTALS 699,935 295,600 228,557 175,149 1,399,241

SOURCE: Report on Commercial Timber Resources and Primary Roundwood Processing in South Africa: 2001/2002.Areas Excluded: Jungle (except the Wattle Jungle areas which were estimated), and Pine grown for “Other Products” inthe Southern and Western Cape Regions.Wattle regions were based on Extract Factory or Collection Depot location.* Wattle as on 30/06/2003.

COMMENTS

• Wattle has been over-felled and can sustain only 1,045,300 tons on average per year (Table 5). Of this

approximately 140,000 tons per annum are derived from jungle plantations.

• Pine sawlogs have been and continue to be over-felled as evidenced by the decline in average age from

14.7 years to 11.3 years between 1983 and 2003. To sustain the current market for sawn timber

(including peeler logs) 5,250,000 m³ of sawlogs are required per annum, but the industry can only

sustain 4,040,000m³ per annum. This has been dealt with in detail in the Supply and Demand Study of


Figure 3

Softwood Sawlog and Sawn Timber 2004 (which can be obtained from DWAF). Sections 9 and 10

summarise the overall supply and demand including sawlogs.

• The felling cycle for Eucalypts is between six and ten years and on average current plantations can

sustain only 8.6 million tons per annum. However, because there are approximately 73,000 ha of

Eucalypts in excess of ten years of age the harvest will amount to 9.96 million tons in the 2005 to 2009

period and 9.38 million tons during the 2010 to 2014 five year period before the harvest declines to the

sustainable yield of 8.6 million tons per annum (Tables 4 and 25, Figure 4).

5.2 YIELDS BY GENUS AND REGION

Table 12 and Figure 4 cover the full window period of 2005 to 2034 and include over-age timber.Therefore, in our opinion it is a slight over estimate, but nevertheless is used in the projections.

TABLE 12: Analysis of Forecast by Genus and Region: Window Period Average:

REGION

FORECAST IN TONS

GENUSTOTAL

Pine Eucalypt Wattle

Limpopo 46,600 517,000 - 563,600

Mpumalanga North 684,600 1,373,000 - 2,057,600

Mpumalanga South CD (Combined) 1,330,900 2,174,400 194,700 3,700,000

Zululand Combined 278,200 2,442,000 284,300 3,004,500

KwaZulu-Natal Midlands 703,600 1,180,600 485,700 2,369,900

Southern KwaZulu-Natal 397,500 776,000 29,500 1,203,000

Eastern Cape 302,800 165,900 50,900 519,600

Southern Cape 66,400 10,000 - 76,400

Western Cape 13,300 2,500 - 15,800

TOTAL 3,823,900 8,641,400 1,045,100 13,510,400

Reductions have been applied to allow for losses as a result of fire and severe weather.Mpumalanga South/Central Districts (Combined) includes both Regions’ data, Zululand and Northern KwaZulu-Natal Regions.Adjustments made to make provision for differences as a result of rounding.


January 2005

Figure 4

5.3 PROJECTED YIELDS – 2005 TO 2034

TABLE 13: Projected Yields of Roundwood other than Sawlogs in Tons: All Regions: 2005–2034


YEA

R

TO

NS

%Red

uct

ion

for

Fir

es

an

dO

ther

Fact

ors

:Soft

wood

%Red

uct

ion

for

Fir

es

an

dO

ther

Fact

ors

:H

ard

wood

s

TO

NS

Pin

e(1

.00)

E.g

ran

dis

(1.3

7)

Oth

er

Eu

caly

pts

(1.1

6)

Watt

le(1

.138)

Watt

leJu

ng

le(1

.138)

Watt

leTota

lTota

lH

ard

wood

s

Tota

lFore

cast

(Rou

nd

ed

to100)

20

05

–0

63

,75

5,7

78

5,6

28

,43

75

,33

3,3

50

1,1

07

,46

01

41

,30

01

,24

8,7

60

12,2

10,5

47

1.8

%1.4

%15,7

24,0

00

20

06

–0

74

,22

7,8

29

5,4

97

,20

85

,06

1,9

33

1,1

33

,52

71

41

,30

01

,27

4,8

27

11,8

33,9

67

1.8

%1.4

%15,8

15,8

00

20

07

–0

84

,67

4,1

29

5,4

25

,28

54

,56

4,6

59

1,2

54

,48

61

41

,30

01

,39

5,7

86

11,3

85,7

31

1.8

%1.4

%15,8

11,7

00

20

08

–0

95

,03

4,6

68

5,5

15

,62

94

,73

6,1

74

1,1

74

,63

21

41

,30

01

,31

5,9

32

11,5

67,7

35

1.8

%1.4

%16,3

44,8

00

20

09

–1

05

,63

0,9

98

4,8

54

,59

33

,90

7,9

57

97

2,9

10

14

1,3

00

1,1

14

,21

09,8

76,7

60

1.8

%1.4

%15,2

62,5

00

An

nu

alA

vera

ge:

2005–2009

4,6

64,6

80

5,3

84,2

30

4,7

20,8

15

1,1

28,6

03

141,3

00

1,2

69,9

03

11,3

74,9

48

1.8

%1.4

%15,7

91,8

00

20

10

–1

15

,89

8,1

72

4,8

38

,40

03

,90

3,4

43

96

2,5

03

14

1,3

00

1,1

03

,80

39,8

45,6

45

1.8

%1.4

%15,4

93,9

00

20

11

–1

24

,17

9,9

50

4,8

28

,10

73

,90

5,7

12

85

5,5

61

14

1,3

00

99

6,8

61

9,7

30,6

79

1.8

%1.4

%13,6

95,0

00

20

12

–1

34

,06

8,7

61

4,8

21

,46

53

,90

4,1

16

85

8,6

01

14

1,3

00

99

9,9

01

9,7

25,4

82

1.8

%1.4

%13,5

80,8

00

20

13

–1

44

,16

8,1

57

4,8

33

,15

73

,91

6,6

36

80

9,1

69

14

1,3

00

95

0,4

69

9,7

00,2

62

1.8

%1.4

%13,6

53,4

00

20

14

–1

53

,22

1,5

79

6,3

15

,09

16

,28

4,4

51

58

4,1

42

14

1,3

00

72

5,4

42

13,3

24,9

84

1.8

%1.4

%16,2

98,8

00

An

nu

alA

vera

ge:

2010–2014

4,3

07,3

24

5,1

27,2

44

4,3

82,8

72

813,9

95

141,3

00

955,2

95

10,4

65,4

10

1.8

%1.4

%14,5

44,4

00

20

15

–1

63

,43

5,6

25

4,5

84

,74

94

,45

2,9

27

1,2

30

,10

11

30

,50

01

,36

0,6

01

10,3

98,2

77

1.8

%1.4

%13,6

23,0

00

20

16

–1

73

,05

1,9

29

4,5

06

,12

93

,95

2,5

43

1,0

55

,02

41

30

,50

01

,18

5,5

24

9,6

44,1

96

1.8

%1.4

%12,5

03,1

00

20

17

–1

83

,09

9,7

79

4,6

34

,20

54

,14

4,1

80

1,1

75

,98

41

30

,50

01

,30

6,4

84

10,0

84,8

69

1.8

%1.4

%12,9

84,6

00

20

18

–1

93

,10

7,9

61

3,9

79

,03

03

,29

2,5

22

1,0

96

,13

01

30

,50

01

,22

6,6

30

8,4

98,1

82

1.8

%1.4

%11,4

28,1

00

20

19

–2

03

,19

0,7

43

3,9

84

,53

83

,29

4,4

65

89

4,4

07

13

0,5

00

1,0

24

,90

78,3

03,9

10

1.8

%1.4

%11,3

17,8

00

An

nu

alA

vera

ge:

2015–2019

3,1

77,2

07

4,3

37,7

30

3,8

27,3

27

1,0

90,3

29

130,5

00

1,2

20,8

29

9,3

85,8

87

1.8

%1.4

%12,3

71,3

00

20

20

–2

13

,28

5,9

86

3,9

99

,73

33

,29

3,4

36

90

5,1

43

13

0,5

00

1,0

35

,64

38,3

28,8

13

1.8

%1.4

%11,4

35,8

00

20

21

–2

23

,01

8,9

41

4,3

16

,80

13

,57

8,4

79

79

8,2

01

13

0,5

00

92

8,7

01

8,8

23,9

81

1.8

%1.4

%11,6

62,0

00

20

22

–2

33

,08

4,9

07

4,3

21

,63

93

,57

7,8

60

80

1,2

42

13

0,5

00

93

1,7

42

8,8

31,2

41

1.8

%1.4

%11,7

33,9

00

20

23

–2

43

,22

9,9

57

6,0

16

,79

35

,99

5,1

39

75

1,8

10

13

0,5

00

88

2,3

10

12,8

94,2

41

1.8

%1.4

%15,8

82,3

00

20

24

–2

53

,67

8,5

78

4,3

33

,82

44

,16

4,5

10

58

4,1

42

13

0,5

00

71

4,6

42

9,2

12,9

77

1.8

%1.4

%12,6

92,7

00

An

nu

alA

vera

ge:

2020–2024

3,2

59,6

74

4,5

97,7

58

4,1

21,8

85

768,1

08

130,5

00

898,6

08

9,6

18,2

51

1.8

%1.4

%12,6

81,3

00

20

25

–2

64

,19

4,6

31

4,2

47

,17

13

,66

5,1

14

1,1

72

,74

21

30

,50

01

,30

3,2

42

9,2

15,5

27

1.8

%1.4

%13,2

01,4

00

20

26

–2

74

,56

1,7

85

4,3

84

,36

43

,83

6,8

77

99

7,6

65

13

0,5

00

1,1

28

,16

59,3

49,4

06

1.8

%1.4

%13,6

93,6

00

20

27

–2

85

,06

7,2

46

3,6

89

,90

43

,00

7,1

23

1,1

18

,62

51

30

,50

01

,24

9,1

25

7,9

46,1

52

1.8

%1.4

%12,8

05,9

00

20

28

–2

94

,94

4,6

24

3,6

87

,41

83

,00

6,6

34

1,0

38

,77

11

30

,50

01

,16

9,2

71

7,8

63,3

22

1.8

%1.4

%12,6

03,9

00

20

29

–3

03

,86

8,9

52

3,6

89

,36

53

,00

8,1

45

83

7,0

48

13

0,5

00

96

7,5

48

7,6

65,0

58

1.8

%1.4

%11,3

53,2

00

An

nu

alA

vera

ge:

2025–2029

4,5

27,4

47

3,9

39,6

44

3,3

04,7

79

1,0

32,9

70

130,5

00

1,1

63,4

70

8,4

07,8

93

1.8

%1.4

%12,7

31,6

00

20

30

–3

14

,09

3,7

89

4,3

31

,08

63

,61

4,6

19

84

7,7

84

13

0,5

00

97

8,2

84

8,9

23,9

89

1.8

%1.4

%12,8

15,1

00

20

31

–3

24

,01

3,7

34

4,3

25

,87

03

,57

8,2

18

74

0,8

42

13

0,5

00

87

1,3

42

8,7

75,4

30

1.8

%1.4

%12,5

90,0

00

20

32

–3

33

,08

5,2

37

6,0

41

,36

65

,99

6,0

65

74

3,8

83

13

0,5

00

87

4,3

83

12,9

11,8

13

1.8

%1.4

%15,7

57,7

00

20

33

–3

43

,02

5,4

52

4,3

12

,15

74

,16

6,9

46

69

4,4

50

13

0,5

00

82

4,9

50

9,3

04,0

54

1.8

%1.4

%12,1

41,8

00

20

34

–3

52

,97

2,2

47

4,2

25

,45

23

,66

9,4

83

58

4,1

42

13

0,5

00

71

4,6

42

8,6

09,5

78

1.8

%1.4

%11,4

04,8

00

An

nu

alA

vera

ge:

2030–2034

3,4

38,0

92

4,6

47,1

86

4,2

05,0

66

72

2,2

20

130,5

00

85

2,7

20

9,7

04,9

73

1.8

%1.4

%12,9

41,9

00

An

nu

alA

vera

ge:

2005–2034

3,8

95,7

37

4,6

72,2

99

4,0

93,7

91

92

6,0

38

134,1

00

1,0

60

,138

9,8

26,2

27

1.8

%1.4

%13,5

10,4

00

5.4 RESOURCES IN OTHER SADC COUNTRIES

Because Swaziland and Zimbabwe already contribute towards meeting some of the demand for forestproducts in South Africa and the fact that there are additional areas suitable for new afforestation in theneighbouring SADC countries, notably Mozambique, it is logical that this overview be provided. Notincluded, but should perhaps be noted is that the Republic of Congo has some 50,000 ha of commercialEucalypts at Pointe Noire, which will generate about one million tons per annum.

5.4.1 Swaziland

Usutu Pulp Company Ltd., owned by Sappi; Piggs Peak plantation and sawmill owned by Mondi;independently owned Swaziland Plantations (Pty) Ltd.; and Shiselweni Plantations owned by TWKLandbou Beperk comprise with a few minor exceptions all the commercial forests which areestimated to total 132,400 ha as shown below.

TABLE 14

AREA (ha)

Pine 86,000

Eucalypt Sawlog 12,400

Eucalypt 9,000

Wattle Jungle 25,000

TOTAL 132,400

Usutu processes all their Pine pulp in their Usutu mill and the roundwood yield has thereforebeen ignored in this study. Peak Timbers is in the process of converting the Pine plantations toEucalypt sawlogs and have already converted 12,400 ha to Eucalypt with only 6,700 ha of Pineremaining. The changeover should be complete by 2011.

Swaziland could be an option for obtaining further suitable land to expand the plantation resource.Rainfall and soils in the Northern, Western parts and sections of Central Swaziland are highly suitablefor commercial afforestation. With an unemployment rate of over 70% the people of Swazilandcould be receptive to a planting programme of some size.

5.4.2 Zimbabwe

The Zimbabwean plantations account for only 3% of the land area and the growing stock issummarised as follows, which includes plantations expropriated for resettlement and/or destroyedby invaders in 2003/2004.

TABLE 15: Age Area Distribution Excluding Sawlogs

YEARS 1 – 5 6 – 10 11 – 15 16 – 20 21 – 25 25> UNKNOWN TOTAL

Pine (ha) 13,852 16,756 14,331 12,229 6,294 7,264 179 70,905

Eucalyptus (ha) 11,716 7,033 2,346 304 137 985 3,957 26,478

Wattle (ha) 5,857 3,191 790 0 0 0 10 9,848

Total Plantation (ha) 31,425 26,980 17,467 12,533 6,431 8,249 4,146 107,231

The annual exports into South Africa are approximately 85,000 m³ of softwood sawn timber,9,000 m³ of Eucalypt sawn timber and 12,000 tons of charcoal from Wattle with a roundwoodequivalent of 56,000 tons.

5.4.3 Malawi

Malawi has approximately 45,000 ha of mature Pine on the Viphya Flats on their Northernborder with Tanzania, apart from some smaller plantations in the Central and Southern parts.However, distances preclude this from being a viable source of supply to South Africa at present.


January 2005

5.4.4 Mozambique

It is estimated that there are at least a further 80,000 ha of vacant but suitable forestry landaccessible to South Africa via the Beira Corridor. The Mozambique Government are keen to havecommercial plantations established and this could become a meaningful ancillary resource ofpulpwood. However, there is a possibility of a chipping plant being installed in Maputo whichwould need to draw its supplies initially from South Africa.

5.4.5 Angola and Zambia

Although distance may preclude the economics of growing timber for South Africa, both of thesecountries have large areas of good forest land that could be used to grow timber should SouthAfrica ever become a viable option for them.

Zambia is a landlocked country with a very high cost of transport which would probably alsoprohibit the growing of pulpwood for South Africa.

5.4.6 Tanzania

Rainfall and soils along the East Coast of Tanzania both North and South of Dar-es-Salaam are goodand suitable for growing of Eucalypt clones. The heart of the Eastern timber growing region is Segerasituated approximately 150 kilometres inland from the Tanga harbour (which lies approximatelymidway between Dar-es-Salaam and Mombassa). Other areas with high forestry potential lie in thehighlands in the West near Njombe. Major plantations are those of the Tanganyika Wattle CompanyLtd. (Tanwat) with some 14,000 ha under Wattle (63%), Pine (31%) and Eucalypt (6%) and the SoaHills Pine plantations +/- 5,000 ha of the Southern Highlands Pulp Milling Company. Possible chippersites are Tanga which is a naturally deep water harbour or Dar-es-Salaam. These harbours are alsowell situated to export to India or to Richards Bay in South Africa.

5.5 NEW FOREST AREAS

If the plantation area in South Africa were to be expanded to meet the demand, between 700,000 and900,000 ha of additional plantation area would be required to fulfil that need. If the shortfall were to beestablished over ten years this would require an annual planting rate, which is possible if compared tothose being achieved by competitor countries.

TABLE 16

COUNTRY AVERAGE ANNUAL NEW PLANTINGS (ha) PERIOD

Australia 82,684 1999 – 2003

Chile 100,000 1990 – 1999

New Zealand 62,480 1995 – 1999

South Africa 6,121 1992 – 2001

South Africa 772 1997 – 2001

SOURCE: Web Pages

The question that arises is whether South Africa has sufficient available land and in this regard work donein the past is relevant.

In 1989 the Directorate of National Forest Planning produced a strategic forestry development plan whichfollowed the initial plan done in 1982. These reports were funded by DWAF but the source of the informationwas the CSIR.

The strategic forestry plan was developed after very thorough research and investigation into the timberneeds in the years that were to follow. It was evident even in 1989 that the South African forestry resource


would need to be expanded substantially. The committee also researched all the potential forestry sites anda summary of its conclusions is quoted as follows:

TABLE 17: Summary of Potential Suitable and Available Areas for Afforestation

The committee summarised its findings as to afforestation in the various priority areas, excluding the nationalstates, as per the table below:

REGION

AREA (ha)

GOOD LAND MARGINAL LAND

TOTALReadilyAvailable

RestrictedAvailability

ReadilyAvailable

RestrictedAvailability

1 Venda 0 1,500 0 0 1,500

2 Letaba 0 14,800 0 0 14,800

4 Pilgrims Rest 10,100 0 3,500 0 13,600

5 Treur River 1,700 0 0 0 1,700

6 Mariti River 4,700 0 400 0 5,100

7 Long Tom Pass 4,000 1,000 1,000 700 6,700

8 Rhenosterhoek 300 200 0 0 500

9 Eastern Transvaal State Forests 1,800 400 500 200 2,900

10 Crocodile River 39,200 37,000 7,000 36,000 119,200

11 Komati River 43,600 20,000 11,800 10,000 85,400

12 Usuthu River 86,000 16,500 0 0 102,500

13 Middelsburg – Belfast 0 0 40,000 20,000 60,000

14 Wakkerstroom 72,000 0 15,000 0 87,000

15 Vaal 0 72,400 0 0 72,400

18 Northern KwaZulu-Natal 81,800 0 64,500 0 146,300

19 Remainder of KwaZulu-Natal 155,000 0 84,700 0 239,700

20 Griqualand East 50,000 0 20,000 0 70,000

23 Eastern Cape Coast 18,000 7,100 20,000 26,600 71,700

24 Eastern Cape Mountains 30,000 9,000 20,000 16,500 75,500

25 Elliott Maclear 87,000 0 49,000 0 136,000

26 Tsitskama 26,700 0 59,000 0 85,700

27 Southern Cape 40,000 0 3,800 0 43,800

28 Western Cape 22,600 10,000 4,400 10,000 47,000

TOTAL 774,500 189,900 404,600 120,000 1,489,000

NOTE:

This was based on CSIR studies commissioned by the Dept. of Forestry and fully supported by scientific reports and a

series of 1 : 250 000 map overlays. However, DWAF today contend that this report was flawed.

In addition to the 774,500 ha of good, readily available land, the plan indicated a further 432,100 ha of good land

from the former homelands was suitable as shown below:

TABLE 18

NATIONAL STATEAREA (ha)

TOTAL (ha)Good Land Marginal Land

Venda 29,300 18,500 47,800

Lebowa 37,400 4,100 41,500

Swazi 75,000 0 75,000

KwaZulu 178,000 272,200 450,200

Transkei 100,000 0 100,000

Ciskei 12,400 15,200 27,600

TOTAL 432,100 310,000 742,100

SOURCE: Strategic Forestry Development Plan for South Africa 1989


January 2005

The Development Plan states that if the areas classified as ‘Good Land’ in Tables 17 and 18 are included thetotal area potentially available amounted to 1,206,600 ha, representing an annual rate of afforestation of48,264 ha over a period of 25 years.

While the experts involved in drafting the Strategic Plan may have been optimistic regarding the availablearea their views speak for themselves and show clearly how far the legislation and restraints on afforestationhave moved to contain the expansion of commercial plantations. In view of the decline in the sustainable yieldFSA maintain that it would be wise for all stakeholders to review the restraints and ensure that whateverconstraints are in place are absolutely necessary and furthermore that the cumbersome and costly proceduresfor obtaining additional afforestation licences are reduced to bare essentials and vested interests eliminated.FSA maintain that the requirements for acquiring a licence to plant trees are so cumbersome and costly andtake so long to process, that growers are discouraged from attempting to acquire licences for new plantings.

South Africa generally is a dry country and there is little doubt that the conservation of water is paramount.Plantation owners have however recognised and addressed this where today no less than 81% of theplantations have been accredited with international environmental and conservation standards (FSC andISO) which is something that no other country has achieved.

The area required for new afforestation is substantial and the following comments address the needs andpracticalities of accomplishing this:

• The shortage of softwood sawlogs from South African plantations is serious. To sustain the existing

markets for sawn timber 5.25 million m³ of sawlogs per annum will be required, but the plantations can

only sustain 3.81 million m³ per annum. However, there is likely to be a surplus of Pine pulpwood and it is

assumed that small log milling will use 500,000 tons per annum of small logs ex. pulp by 2007.

• Exports of sawn timber and downstream products amounted to +/- 35% in 2001. Due largely to the

value of the Rand at R 5.8/USD in December 2004, exports had fallen to an estimated 12% (Source:

Lumber Index). However the building sector is more active than ever before and due to a shortage of

sawlogs, South Africa is likely to have to resort to importing, rather than exporting sawn timber.

• Sawlog harvesting increased as a result of sales of sawn timber in South Africa unexpectedly doubling

(from 1.2 million m³ in 1994 to 2.5 million in 2004) and at the same time export of sawlogs commenced

for the first time. As a result the sawlog plantations have been over-felled and ages have fallen from an

average of 14.14 years to the current 11.25 years, i.e. rotation age has fallen from approx. 30 years to

less than 23 years.

• Profits from timber growing are not good and a Real Rate of Return of 5% to 6% is normal (FES and CA).

This is no great incentive to investors in addition to which plantation owners in South Africa have to

contend with a number of issues that are not conducive to investment, namely:

~ Extensive land claims;

~ Municipal rates being applied to plantation owners;

~ South Africa is the only country in the world where growers are required to pay tax on the estimatedeffect that trees have on stream flow reduction – this being to the exclusion of all other crops, suchas sugar, etc.;

~ Black Economic Empowerment (BEE) while welcomed by the industry at large, does place pressureon investors, which is a challenge that investors in other countries do not have;

~ There are no tax incentives for establishing plantations such as there are in countries like Chile;

~ The administration and the laws for acquiring a licence to plant trees have become so cumbersomeand expensive that frequently plantation owners consider it impossible and not worth attempting;

~ Minimum wages;

~ High cost of imported capital equipment;

~ The incidence of fire is very high and there is no assistance in the form of subsidies for fireprotection as there is in some other countries, such as the Southern States in the USA;

~ The cost of plantation insurance is becoming prohibitive.


5.6 RECOMMENDED ACTION TO EXPAND THE RESOURCE

The following comments merely recommend broadly what needs to be done. How it is to be accomplishedhas not been dealt with as that would call for a high level action plan which is beyond the Terms ofReference of this study and would best be developed by a partnership headed by Forestry South Africa andthe Government, with involvement from other stakeholders. It must be pointed out that the NationalForestry Action Plan of 1997 is still valid. By 2004 DWAF has not produced another NFAP nor has it carriedout expected investigations and commissioned tasks as set out in the NFAP of 1997. DWAF neverthelesssupports the goal, “To put into place those measures which promote the development of an industrialforest sector so that it contributes fully to the future economic and social well-being of South Africa, withinthe parameters of acceptable social and environmental impacts.”

To this end, in consultation with FSA, the following recommendations are made:

• Continue to implement all aspects of improving the vigour and productivity of new plantings.

• Review and substantially streamline the process of afforestation licensing.

• Review and substantially reduce all extraneous rates and levies.

• Improve the accuracy of the supply and demand base information.

• Reduce the incidence and extent of fire damage.

• Seek ways of making additional land available for forestry.

• DWAF forestry should, in accordance with the NFAP actively contribute to, facilitate and promote this

flourishing wealth-creating industry.

• Global warming presents a very real threat to the forests and there is a need to increase diligence in

monitoring the extent and severity of the effects.

• Cognisance should be taken of the opportunities to benefit from accreditation arising from carbon

sequestration.

• Update this forecast annually to monitor progress in order to assist the industry in its planning.

“Above all, there needs to be a substantial improvement in the profile and appreciation of theforest industry”. Comment by Brian Aitkin, former Chairman of Forestry South Africa.

6. METHODOLOGY AND CONSTRAINTS IN FORECASTING THE DEMAND

Pulp, paper, particleboard and mining timber production are very competitive activities and information is notfreely shared by all particularly with regard to future planning.

The purpose of this study is to assist and promote the interests of the stakeholders and every effort has been madetherefore to avoid interfering with the confidentiality or competitiveness of the players. At the same timeinformation is provided which is useful to all stakeholders for forward planning. Timber users are comfortablewith disclosing current usage but are generally not keen to disclose their plans for the future. Only known andpublished expansion or changes (e.g. from one genus to another) have been used for the period 2005 to 2009.

Because of the competition for the resource the question of what each company owns has been avoided and focushas been on the overall regional resource areas and yields.

The information contained in the Commercial Forestry Resource annual report is invaluable as it is the only basedata available. However, there are areas of concern, particularly the reporting of sales by growers. There arealso inaccuracies in the plantation growing stock and those are probably due to lack of submission of annualreturns by very small growers.


January 2005

7. EXPECTED DEMAND OTHER THAN FOR SAWLOGS

7.1 2005 DEMAND FOR ROUNDWOOD OTHER THAN SAWLOGS (‘000 tons – rounded to the closest 1,000 tons)

TABLE 19

SOFT-WOOD

Logs

SUBTOTAL

Wattle

HARDWOODSUB

TOTALTOTALHard

GumE.grandis

PULP AND PAPER

Sappi Enstra

Ngodwana

Mandini

Saiccor

Mondi Richards Bay

Merebank

Piet Retief

-

1,000

800

-

431

485

-

-

1,000

800

-

431

485

-

-

-

-

190

-

-

-

280

250

220

200

1,421

-

-

-

700

-

1,950

1,050

-

70

280

950

220

2,340

2,471

-

70

280

1,950

1,020

2,340

2,902

485

70

Sub Total 2,716 2,716 190 2,371 3,770 6,331 9,047

BOARD MILLS

Masonite

Sonae White River

Panbult

George

PG Bison Piet Retief

Pietermaritzburg

Stellenbosch

Boksburg

ChipboardIndustries near Langeni

-

13

43

8

100

37

18

-

66

-

13

43

8

100

37

18

-

66

-

-

-

-

-

-

-

-

-

-

-

65

-

-

10

10

-

-

200

80

-

-

-

54

-

60

-

200

80

65

-

-

64

10

60

-

200

93

108

8

100

101

28

60

66

Sub Total 285 285 - 85 394 479 764

CHIPPING PLANTS

CTC Richards Bay

Silvacel

Shincel

NCT Durban

-

-

-

-

-

-

-

-

700

324

100

-

527

871

60

-

1,173

720

460

350

2,400

1,915

620

350

2,400

1,915

620

350

Sub Total - - 1,124 1,458 2,703 5,285 5,285

MINING TIMBEREXPORTS

-

-

-

-

-

-

200

-

579

-

779

-

779

-

Sub Total - - - 200 579 779 779

OTHER

Poles 70% Recovery

Charcoal Timber

316

-

316

-

-

400

-

472

446

-

446

872

762

872

TOTAL CONSUMED IN RSA 3,317 3,317 1,714 4,586 7,892 14,192 17,509

LESS

Swaziland

Zimbabwe

Namibia

25

-

-

25

-

-

10

56

-

-

-

80

100

-

-

110

56

80

135

56

80

TOTAL DEMAND FOR RSA 3,292 3,292 1,648 4,506 7,792 13,946 17,238

Waste excluded 688

NOTES:

1. Export of Eucalypt and Pine roundwood terminated.2. Merebank intake reduced from 617,000 to 485,000 tons Pine.3. Mondi Richards Bay intake increased by 600,000 tons Eucalypt.4. SAICCOR increased by 200,000 tons Eucalypt.5. PG Bison Piet Retief convert to Pine.6. NCT Durban up to full production.7. Mining Timber reduced by 50,000 tons per annum.


7.2 2005 PULPWOOD DEMAND FOR WASTE (‘000 tons – rounded to the closest 1,000 tons)

TABLE 20

SOFTWOODChips + Waste

HARDWOODWaste

TOTAL

PULP AND PAPER

Sappi Enstra

Ngodwana

Mandini

Saiccor

Mondi Richards Bay

Merebank

Piet Retief

-

122

102

-

-

-

-

-

-

-

-

-

-

-

-

122

102

-

-

-

-

Sub Total 224 - 224

BOARD MILLS

Masonite

Sonae White River

Panbult

George

PG Bison Piet Retief

Pietermaritzburg

Stellenbosch

Boksburg

Chipboard Industries

Langeni

-

17

43

29

51

6

25

5

-

47

-

37

-

5

30

27

-

60

44

-

-

54

43

34

81

33

25

65

44

47

Sub Total 223 203 426

SILICON SMELTERSHEATLOG

2710

GRAND TOTAL 447 203 688

NOTE:

While the overall volume of Gum is accurate the split between Hard Gum and Grandis is interpolated and is not accurate.

For ease of access these tables have been repeated in Appendix C, which also includes projections to 2009.

7.3 SUMMARY OF TOTAL USE (including waste and sawlogs) – ‘000s tons

TABLE 21

2005 ‘000s TONS (REFERENCES)

Roundwood 17,238 (Appendix C)

Waste and chips 688 (Table 20)

Imports 271 (Table 19)

Softwood sawlog 5,070 (Softwood Sawlog report)

Eucalypt sawlog 184 (Para 9.2)

23,451

7.4 COMMENT ON THE EXPECTED DEMAND

Forecasting the future is hazardous under any circumstances and is made even more difficult by predictingexport markets where exchange rates and interest factors play such a major role. Forecasting becomeseven more complex when sensitivities of competition between the role players who compete for theresource are taken into account. In order to avoid conflict between competitors, the demand in this exercisehas been based simply on current usage and the projections have been estimated on a globular rather than a


January 2005

company or even sector basis (Appendix C). The volumes have been obtained with the consent of therelevant companies and where this was not the case the volumes have been estimated by the authors.

The supply and demand situation for roundwood other than sawlogs is summarised as follows.

South Africa is currently (2004) using approximately 17.1 million tons per annum, excluding 0.7

million tons that come from waste. The sustainable harvest in South Africa is 12.1 million tons per

annum but with accelerated felling of over-age timber the supply will increase annually to 15.8

million tons for the first five years and 14.5 million tons for the second five year period 2010 to 2014.

Thereafter the harvest declines to 12.4 million tons per annum for the next five years and 12.7 million

tons per annum for the fourth five year period, i.e. 2020 to 2024 (Table 24). It is clear therefore that

there is insufficient resource to sustain the current processing. While 5.1 million tons are being

exported in chip form, depending upon the economics and profitability of making chips compared to

that of manufacturing pulp and paper it would seem likely that some, if not all, of the chip supply

instead of being exported will be turned to servicing the local downstream plants – pulpmills.

In view of the shortage of sawlogs to produce sawn timber and the projected surplus of 1.3 million

tons of Pine pulp in the first ten years it is very likely that sawmills will specialise in small wood

milling and will draw off up to 0.5 million tons of pulpwood per annum to be utilised as sawlogs.

Comments on the usage of timber by sector are given in the following sub paragraphs of this section.

7.4.1 Pulp and Paper

The use of pulpwood roundwood has increased over the past eleven years by 5.29% per year, asfollows:

Worldwide pulp and paper mills tend to expand every seven to ten years with significant volumeincreases to offset high capital expenditure and improve economies of scale, rather than at aneven or slow rate of increase.

The pulp and paper mills may also change the mix of product. This may well occur in the case ofNgodwana which it is rumoured is to change from using largely softwood to hardwood andincrease capacity.


Figure 5

(Table 29)

NCT have signed an agreement with Södra Cell, a subsidiary of Södra, a large Swedish forestryco-operative to investigate the feasibility of building a pulp mill at Richards Bay. The purpose ofthe mill, which is to be known as Pulp United (Pty) Ltd. with an expected output of 300,000 tonsper annum will be to process some of the Eucalyptus pulpwood of the NCT members, i.e.400,000 to 500,000 tons of roundwood per annum. The pulp mill is expected to come onstream in 2007.

Mondi are increasing their Richards Bay plant capacity by 600,000 tons of Eucalypts which isexpected to come into effect in 2005.

SAICCOR have embarked on a R330 million capital expansion, which is expected to increasetheir roundwood intake by 200,000 tons per annum by 2005.

A new particleboard plant is expected to be installed near Mthatha with a capacity of 100,000tons per annum of which 40,000 tons will be chips and the balance softwood logs.

7.4.2 Board Mills

While interest rates remain low and building activity remains strong the market for particleboardand hardboard exceeds the capacity to supply. The board mills have also been successful inreducing the intake of roundwood compared to waste to 36% in favour of waste. Theirperformance is summarised below:

TABLE 22: Particle Board and MDF Market (tons)

2002 2003 2004 2005 Est.

PARTICLE BOARD

Domestic Sales 540,000 546,000 562,000 590,000

Imports by Third Parties 5,000 8,000 15,000 15,000

Exports 20,000 18,000 18,000 15,000

TOTAL PARTICLE BOARD 565,000 572,000 595,000 620,000

MDF

Domestic Production 96,000 98,000 103,000 110,000

Imports by Third Parties – thicknesses >9mm 2,000 5,000 10,000 10,000

Imports by Third Parties – thicknesses <9mm 8,000 8,500 10,000 11,000

Exports 5,000 4,000 4,000 4,000

TOTAL MDF 111,000 115,500 127,000 135,000

NOTES

Domestic Particle Board producers consist of PG Bison, Sonae and CITDomestic MDF producers consist of PG Bison and SonaeImports of both Particle Board and MDF by Sonae and PG Bison to supplement peak period capacityshortfalls are included in domestic sales.

7.4.3 Chipping Plants

Chipping plants are running at capacity with the NCT Durban Wood Chips plant expected toachieve 120,000 tons in 2004 compared to the full capacity of 350,000 tons per annum, whichis expected to be achieved in 2005. No allowance for growth other than Durban ChippingCompany has been made. No allowance has been made for the planned chipping plant inMaputo nor the chipping plant at Richards Bay for which an Environmental Impact Assessmenthas been completed.


January 2005

7.4.4 Mining Timber

Mining timber demand has declined from 2,399,914 tons in 1979/ 1980 to the current 559,345tons per annum at the rate of 6.3% per annum over the past eleven years. It is likely that thisdecline will continue for the foreseeable future. Demand therefore has been reduced by 50,000tons per annum to 600,000 tons by 2009, which has been retained for the rest of the study period.

7.4.5 Log Exports

Log exports in 2004 were made up of 260,000 tons of Pine sawlogs and 300,000 tons of Eucalyptpulpwood (total 560,000 tons). This is likely to terminate altogether over the next year, dependingupon the value of the Rand, therefore has not been included in the study.

7.4.6 Poles

The current levels of poles purchased for treating is 762,000 m³ per annum. Although SAWPAbelieve that this will increase at the rate of 1.7% per annum this has not been done in order not toconfuse the growth scenarios of zero, two, three and four percent overall rates of growth shownin Tables 30 and 32.


Figure 6

(Table 29)

Figure 7

(Table 29)

The historical demand for poles has been as follows:

TABLE 23

TYPE

1996 1997 1998 1999 2000 2001 2002 2003Ave-rage

Pin

e

Gu

m

Pin

e

Gu

m

Pin

e

Gu

m

Pin

e

Gu

m

Pin

e

Gu

m

Pin

e

Gu

m

Pin

e

Gu

m

Pin

e

Gu

m

Pin

e

Gu

m

Transmission

Telephone

Other

74

23

124

50

24

181

69

21

124

50

30

188

69

20

122

53

33

168

72

22

132

56

36

208

66

18

122

60

31

170

68

13

108

78

20

221

76

15

121

87

22

224

71

19

131

81

16

215

71

19

123

64

27

197

TOTAL 221 255 214 268 211 254 226 300 206 261 189 319 212 333 221 312 213 288

NOTE

In order to establish the roundwood intake a recovery factor of 70% has been used and the volumesconverted to tons for this study.

SOURCE: SAWPA

For the purpose of the demand projections given later in this report, the cubic metres have beenconverted to tons.

7.4.7 Charcoal Timber

It is difficult to establish how much the charcoal demand has grown because many of the operatorsare small and their production may not have been recorded. It is thought, however, in terms ofroundwood intake, that approximately 540,000 tons per annum are being used which yield 90,000tons of charcoal (Louis Heyl & Associates’ estimate is almost double this based on a conversion ratioof 10 : 1 compared to 6 : 1 used in this study).

The greatest single user is Silicon Smelters in Polokwane, who account for almost 20% of the totalproduction with some of the charcoal being sourced from Zimbabwe.

The new Carbotek plant based at Estcourt in KwaZulu-Natal is currently using 50,000 tons ofE.macarthurii per annum at present but would like to quadruple this production.

The proportion of charcoal exported, either in briquette or in lump form, is affected by theexchange rate but on average accounts for 20% to 40% of the total annual production.

The trend of consumption of roundwood for charcoal manufacture has been negative at the rateof 2.4% per annum. However, for future projections the annual consumption has been assumedto be constant.

An unknown but substantial proportion of the intake is derived from unregistered plantationswhich accounts for some of the differences. It should be noted however, that an allowance hasbeen made for 500,000 tons additional supply of roundwood as a result of a possible underrecording of 3.5% of productive area (Para 4.0).

LHA have undertaken an extensive study into the charcoal industry and their estimate ofconsumption is approximately twice that of ours at 1 million tons per annum.


January 2005

7.4.8 Summary of Known Adjustments

• Merebank will scale-down to 485,000 tons in 2005.

• NCT chipping plant in Durban will scale-up to 350,000 tons (capacity 420,000 tons) in 2005.

• P G Bison at Piet Retief is likely to phase out of Eucalypts into Pine and increase capacity.

• Mondi at Richards Bay expect to commission their expansion of at least 600,000 tons of

Eucalypt in 2005.

• SAICCOR expansion of 200,000 tons is expected to be commissioned in 2005.

• Supplies from Swaziland could change from 25,000 tons of Pine pulp logs and 20,000 tons of

Eucalypts.

• Swaziland Peak Timbers will phase over to Eucalypts.

• It is very likely that a further chipboard plant will be installed near Mthatha which will use

100,000 tons of Pine with 40% chips.

• The chipping plant in Durban, known as NCT Durban Wood Chips has been commissioned.

• NCT’s partnership with Södra in a pulpmill at Richards Bay known as Pulp United (Pty) Ltd is

due to commence in 2007 and will have an intake of 450,000 tons of Eucalypt per annum.

• No account has been taken of the new chipping plant at Richards Bay for which an

Environmental Impact Assessment has already been done.

• Nor has account been taken of the possibility of a chipping plant being installed at Maputo

which would draw supplies from South Africa initially.


Figure 8

(Table 29)

8. SUPPLY AND DEMAND PROJECTIONS FOR ROUNDWOOD OTHER THAN SAWLOGS

The projected supply of timber both in log form as well as in the form of chips and waste is reasonablypredictable despite some inaccuracies in the base data. The prediction of demand however is considerably

more complex. The known and expected increases in capacity are dealt with in Para 7.4.

In this section all commodities have been projected forward based on the assumption that there will be noincrease in capacity other than those that have already been pointed out or are known (Section 7).

This projection shows that there will be a shortfall of:

TABLE 24 – All Genera


(tons)TOTAL DEMAND

(tons)SHORTFALL

(%)

2005 – 2009 15,791,800 17,181,400 8.1

2010 – 2014 14,544,400 17,205,000 15.5

2015 – 2019 12,371,300 17,205,000 28.1

2020 – 2024 12,681,300 17,205,000 26.3

2025 – 2029 12,731,600 17,205,000 26.0

2030 – 2034 12,941,900 17,205,000 24.8

The most serious shortage occurs in the Eucalypt as follows:

TABLE 25 – Eucalypt


(tons)TOTAL DEMAND

(tons)SHORTFALL

(%)

2005 – 2009 9,963,574 12,272,400 18.8

2010 – 2014 9,376,974 12,340,000 24.0

2015 – 2019 8,050,747 12,340,000 34.8

2020 – 2024 8,597,568 12,340,000 30.3

2025 – 2029 7,143,001 12,340,000 42.1

2030 – 2034 8,728,321 12,340,000 29.3

Pine supply looks more encouraging as follows:

TABLE 26 – Pine


(tons)TOTAL DEMAND

(tons)

SURPLUS(+)/SHORTFALL

(%)

2005 – 2009 4,576,051 3,266,000 +40.1

2010 – 2014 4,225,485 3,242,000 +30.3

2015 – 2019 3,116,840 3,242,000 3.9

2020 – 2024 3,197,740 3,242,000 1.4

2025 – 2029 4,441,426 3,242,000 +37.0

2030 – 2034 3,372,768 3,242,000 +4.0


January 2005

The Wattle shortage is as follows:

TABLE 27 – Wattle


(tons)TOTAL DEMAND

(tons)SHORTFALL

(%)

2005 – 2009 1,252,124 1,643,000 23.8

2010 – 2014 941,921 1,623,000 42.0

2015 – 2019 1,203,738 1,623,000 25.8

2020 – 2024 886,027 1,623,000 45.4

2025 – 2029 1,147,182 1,623,000 29.3

2030 – 2034 840,782 1,623,000 48.2

If the chip exports of 5.1 million tons were to be used internally in part or in total, it would go a long way to closingthe gap between overall supply and demand.

For detail see Appendix O.

9. TOTAL SUPPLY AND DEMAND OF ALL ROUNDWOOD INCLUDING SAWLOGS

In order to complete this study the sawlogs, which have been excluded to this point, have been introduced andinformation has been drawn from the Supply and Demand Study of Softwood Sawlog and Sawn Timber in South

Africa.

9.1 SOFTWOOD SAWLOGS

Softwood sawn timber will be in such short supply that sawmillers are likely to adapt their sawmills to cutsmallwood. This inevitably will mean that millers will have to pay more for small logs in order to attract logsaway from pulp. As indicated elsewhere, sawmillers could initially draw off 500,000 tons of smallwoodfrom pulpwood.

9.2 EUCALYPT SAWLOGS

Commercial hardwood sawmilling is confined to Eucalyptus comprising mainly “Saligna” (E.grandis) whichhas not been subject to a specific supply and demand study. The reasons for this are that sawmilling “Saligna”is highly technical and capital intensive requiring high quality salwogs all of which contribute to making the“Saligna” lumber barely competitive with the imports of Meranti, its main competitor. Furthermore withincreased demand for short rotation E.grandis by pulpmills, the reduced production of longer rotation“Saligna” sawlogs will not allow for sawmilling of “Saligna” to expand to any great extent. The growth into“Saligna” sawmilling is therefore likely to be very modest.

“Saligna” sawlog consumption at 184,000 tons per annum has been included in the overall demandforecast.


9.3 The summary of supply and demand including softwood and hardwood sawlogs, is as follows:

TABLE 28

YEARTOTALSUPPLY(tons)

TOTALDEMAND

(tons)

ANNUALBALANCE

(tons)

ANNUALBALANCE

(%)

PINE SAWLOGDEMAND ALREADY

INCLUDED IN TOTALDEMAND (tons)

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

2015

2016

2017

2018

2019

2020

2021

2022

2023

2024

2025

2026

2027

2028

2029

2030

2031

2032

2033

2034

19,753,709

19,981,706

20,459,587

21,673,849

20,884,952

21,284,030

19,579,406

19,004,142

19,097,739

21,470,676

19,203,591

17,633,077

19,183,352

18,297,543

18,732,094

19,133,006

17,158,739

17,911,727

23,181,363

19,886,946

19,787,942

20,416,349

18,606,470

17,974,879

16,546,018

18,007,890

17,782,877

20,950,496

17,334,595

16,597,648

23,016,840

23,121,388

23,049,048

23,571,894

23,486,899

23,639,372

23,795,995

23,955,729

24,119,612

24,153,840

24,323,947

24,497,165

24,674,532

24,857,085

24,897,537

25,085,277

25,278,202

25,475,277

25,677,537

25,726,287

25,934,771

26,148,441

26,367,298

26,592,378

26,821,606

27,058,096

27,299,771

27,547,670

27,800,755

27,800,755

-3,263,132

-3,139,682

-2,589,461

-1,898,044

-2,601,947

-2,355,342

-4,216,589

-4,951,587

-5,021,873

-2,683,164

-5,120,356

-6,864,088

-5,491,180

-6,559,542

-6,165,443

-5,952,271

-8,119,463

-7,563,549

-2,496,174

-5,839,341

-6,146,829

-5,732,093

-7,760,828

-8,617,498

-10,275,588

-9,050,206

-9,516,895

-6,597,175

-10,466,161

-11,203,107

-14.18

-13.58

-11.23

-8.05

-11.08

-9.96

-17.72

-20.67

-20.82

-11.11

-21.05

-28.02

-22.25

-26.39

-24.76

-23.73

-32.12

-29.69

-9.72

-22.70

-23.70

-21.92

-29.43

-32.41

-38.31

-33.45

-34.86

-23.95

-37.65

-40.30

5,594,840

5,749,388

5,907,048

6,069,894

6,097,899

6,250,372

6,406,995

6,566,729

6,730,612

6,764,840

6,934,947

7,108,165

7,285,532

7,468,085

7,508,537

7,696,277

7,889,202

8,086,277

8,288,537

8,337,287

8,545,771

8,759,441

8,978,298

9,203,378

9,432,606

9,669,096

9,910,771

10,158,670

10,411,755

10,411,755

AVERAGE 19,250,547 25,192,500 -5,941,954 -23.16 7,807,434

NOTES:

a) Waste, chips and imports have not been included in Table 28 because the logs from which they were derived have

been included.

b) In order to test the forecast against historical supply, Table 29 is relevant, as 21.7 million tons were used and the

projection estimates with new capacity will rise to 23.0 million tons.

c) The sawlog forecast in Table 26 of the Supply and Demand Study of Softwood Sawlog and Sawn Timber in South

Africa (Appendix P) has been adjusted downwards by removing the 2.5% growth and converting it to tons.


January 2005

9.4 RECONCILIATION OF PAST PERFORMANCE WITH FORECASTS

Table 29 tracks the consumption of all roundwood including sawlogs and is expressed in tons.

TABLE 29


PRO

DU

CT

YEA

R

1992/

93

1993/

94

1994/

95

1995/

96

1996/

97

1997/

98

1998/

99

1999/

00

2000/

01

2001/

02

2002/

03

2003/

04

m3/T

on

s

SAW

LOGS

&VE

NEER

LOGS

Tons

PULP

WOO

DTo

ns

MIN

ING

TIM

BER

Tons

POLE

STo

ns

MAT

CHW

OOD

Tons

CHAR

COAL

&FI

REW

OOD

Tons

OTHE

RTo

ns

4,57

7,77

0

6,99

9,38

2

1,77

9,63

9

217,

108

9,83

8

247,

119

65,0

21

4,37

7,96

9

8,45

3,08

7

1,55

4,56

5

242,

918

13,9

37

191,

607

100,

092

5,43

1,97

3

7,45

7,87

3

1,46

6,09

5

423,

924

19,1

42

137,

696

101,

857

6,06

0,28

2

7,08

8,64

5

1,75

1,30

8

493,

670

21,1

59

344,

427

315,

309

6,45

2,32

9

7,16

4,10

7

1,66

0,22

5

533,

555

18,3

68

335,

647

307,

374

4,65

0,76

9

6,72

7,38

2

1,30

8,54

0

358,

897

31,4

08

348,

348

265,

793

4,93

1,62

9

6,94

8,67

4

1,16

2,61

1

345,

933

12,6

61

333,

120

267,

126

4,73

3,55

6

8,77

3,33

7

498,

762

484,

067

n/a

135,

179

114,

439

4,81

8,78

3

8,85

5,51

2

332,

983

370,

679 -

188,

950

89,8

30

4,68

4,02

8

8,68

4,07

3

496,

423

402,

952

n/a

185,

528

87,7

89

5,57

0,04

7

10,0

93,1

63

559,

345

331,

856

n/a

173,

921

103,

942

5,25

0,00

0

14,8

00,0

00

829,

000

762,

000

n/a

29,0

00 -

TOTA

LTo

ns1

3,8

95

,877

14,9

34,1

75

15,0

38,5

61

16,0

74,8

00

16,4

71,6

05

13,6

91,1

37

14,0

01,7

54

14

,73

9,3

41

14

,65

6,7

37

14

,54

0,7

93

16

,83

2,2

74

21

,67

0,0

00

Sourc

e:

Fore

stry

South

Afr

ica

9.5 THE CHANGES THAT HAVE OCCURRED TO SUPPLY THE MARKET

• The average age of Pine sawlogs has declined from 14.14 years in 1983 to 11.25 years in 2003, which

illustrates how over-felling has dug into the reserves. The over-felling continues today.

• It is accepted that the registered Wattle plantations can only supply at best 1.0 million tons per annum,

but at the peak demand 1.6 million tons were used. Wattle jungles in the Eastern Cape as well as

KwaZulu-Natal and Swaziland were exploited to make up the deficit but that volume is not sustainable.

• Pulpwood production remained relatively static from 1992 until 1999 as can be seen in Table 29. As

Eucalypts account for approximately two thirds of the pulpwood consumed and the demand for mining

timber (almost entirely made up of Eucalypts) declined from 1.8 million tons to 0.56 million tons, a

surplus of Eucalypts arose. As a result the average age of Eucalypts rose from 5.57 years to 6.09 years

from 1991/1992 to 2001/2002. It is this build up that eases the shortage in the first seven to ten years

of the study period.

As a result of the above, the plantations have been able to meet the increase in demand to 23.2 million tonsper annum. However, the surplus Eucalypt yield and Wattle jungle area have been so diminished, as well asthe clearfelling age of Pine for sawlogs having been reduced to a minimum, that the plantations will be ableto sustain only 19.8 million tons per annum (Appendix O).

10. SENSITIVITY ANALYSES

This section endeavours to provide allowances for some of the imponderables in the form of different scenariosthereby converting the ‘forecasts’ produced in this report to this point, into ‘projections’.

10.1 DEMAND

The real growth in the RSA has been approximately 2% p.a. Confidence however is growing and couldexceed this and we have therefore used the levels used by Louis Heyl & Associates as follows:

2% Conservative3% Average4% Optimistic

There is likely to be considerable interchanging of roundwood between the sectors, some of the moreimportant being:

• The export of 5.1 million tons of chips is likely to be substantially reduced or terminated altogether in

favour of supplying the local pulpmills.

• Up to 500,000 tons of Pine pulpwood is likely to be sawn into lumber to supply the local market.

• Board products are likely to draw pulpwood and chips away from pulpmills, but will also increase their

efforts to use waste wood.

In view of the introduction of growth the shortages are projected to rise from 3.3 million tons per annum or14.2% (Table 30) to about 11.2 million tons or 40.3%.


January 2005

TABLE 30

SCENARIO 1 SCENARIO 2 SCENARIO 3

AnnualAverage

Tota

lSup

ply

(tons

)

Tota

lDem

and

(tons

)2%

p.a.

-con

serv

ativ

e

Annu

alBa

lanc

e(to

ns)

Annu

alBa

lanc

e(%

)

Tota

lDem

and

(tons

)3%

p.a.

-ave

rage

Annu

alBa

lanc

e(to

ns)

Annu

alBa

lanc

e(%

)

Tota

lDem

and

(tons

)4%

p.a.

-opt

imist

ic

Annu

alBa

lanc

e(to

ns)

Annu

alBa

lanc

e(%

)

2005 - 2009

2010 - 2014

2015 - 2019

2020 - 2024

2025 - 2029

2030 - 2034

21,071,111

20,550,899

18,999,286

19,984,481

19,384,983

18,781,930

24,188,482

26,423,866

27,215,651

28,097,218

29,117,811

30,363,778

-3,117,371

-5,872,967

-8,216,364

-8,112,737

-9,732,828

-11,581,849

-12.89

-22.23

-30.19

-28.87

-33.43

-38.14

24,665,091

27,744,802

28,576,168

29,501,805

30,573,418

31,881,671

-3,593,980

-7,193,902

-9,576,881

-9,517,324

-11,188,435

-13,099,741

-14.57

-25.93

-33.51

-32.26

-36.60

-41.09

25,146,350

29,118,044

29,990,559

30,962,011

32,086,664

33,459,670

-4,075,239

-8,567,145

-10,991,272

-10,977,530

-12,701,681

-14,677,740

-16.21

-29.42

-36.65

-35.45

-39.59

-43.87

Equivalent AreaRequired (hectares) 721,835 816,437 914,786

NOTE: Mean Annual Increment used of 16.045 tons/ha/annum shown in Appendix F to determine area.

10.2 SUPPLY

Modifications to the Pulpwood Study to produce scenarios four, five and six (Table 32) are as follows:

• Allowance for improved yields as a result of genetic and silvicultural advancement in the future:

Pine 3%Eucalypts 6%Wattle 6%

• Modifications in the provision for fire and weather losses in para 4.8 to allow for the increased fire

damage recorded over the recent past. New percentages applied:

Pine 2.6% p.a. (was 1.8% p.a.)Hardwoods 1.9% p.a. (was 1.4% p.a.)

• Adjustment to the allowance for environmental compliance:

TABLE 31

PREVIOUS ALLOWANCES NEW ALLOWANCES

First Rotation/15 year period

Second Rotation/15 year period

First Rotation/15 year period

Second Rotation/15 year period

5% 5% 5% 2.5%

• 500,000 tons have been included per annum to account for the possible 3.5% not recorded in the

Commercial Timber Resources and Primary Roundwood Processing in South Africa annual report (Para 4).

10.3 OTHER FACTORS THAT COULD INFLUENCE THE FORECASTS

• The exchange rate which will depress exports and encourage imports of finished products as well as

roundwood and chips.

• The effect that a recession in any of the major countries would have on global markets.

• The effect that accelerated global warming could have on plantations.

• The effect that serious outbreaks of insect pests or disease would have on the plantations.

• The effect that improved technology could have on conserving the resource.

• The effect of substitution and particularly replacement of timber with steel in construction.


It makes good sense to expand the plantations by 785,275 ha at least, which would increase the numbersemployed by 72,300 thereby benefiting 289,200 people. This would also increase the country’s earningsby about R10.4 billion.

TABLE 32

SCENARIO 4 SCENARIO 5 SCENARIO 6

AnnualAverage

Tota

lSup

ply

(tons

)

Tota

lDem

and

(tons

)2%

p.a.

-con

serv

ativ

e

Annu

alBa

lanc

e(to

ns)

Annu

alBa

lanc

e(%

)

Tota

lDem

and

(tons

)3%

p.a.

-ave

rage

Annu

alBa

lanc

e(to

ns)

Annu

alBa

lanc

e(%

)

Tota

lDem

and

(tons

)4%

p.a.

-opt

imist

ic

Annu

alBa

lanc

e(to

ns)

Annu

alBa

lanc

e(%

)

2005 - 2009

2010 - 2014

2015 - 2019

2020 - 2024

2025 - 2029

2030 - 2034

21,571,111

21,050,899

19,499,286

20,484,481

19,884,983

19,281,930

24,188,482

26,423,866

27,215,651

28,097,218

29,117,811

30,363,778

-2,617,371

-5,372,967

-7,716,364

-7,612,737

-9,232,828

-11,081,849

-10.82

-20.33

-28.35

-27.09

-31.71

-36.50

24,665,091

27,744,802

28,576,168

29,501,805

30,573,418

31,881,671

-3,093,980

-6,693,902

-9,076,881

-9,017,324

-10,688,435

-12,599,741

-12.54

-24.13

-31.76

-30.57

-34.96

-39.52

25,146,350

29,118,044

29,990,559

30,962,011

32,086,664

33,459,670

-3,575,239

-8,067,145

-10,491,272

-10,477,530

-12,201,681

-14,177,740

-14.22

-27.70

-34.98

-33.84

-38.03

-42.37

Equivalent AreaRequired (hectares) 690,673 785,275 883,623

NOTE: The percentage allowance for the growth scenarios commences only in 2008, i.e. after the major expansion.

We are of the opinion that of all these scenarios, Scenario 5 would be the most realistic one to use. The totalshortage would rise from 3,093,980 tons per annum in 2005 – 2009 (12.5% shortage) to 12,599,741tons per annum or a 39.52% shortage at the end of the window period (2034).


January 2005


Appendix A


January 2005

FO

REC

AST

OF

RO

UN

DW

OO

DO

TH

ER

TH

AN

SA

WLO

GS

INTO

NS:

LIM

PO

PO

:2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

53

,94

73

54

,51

33

71

,37

2-

--

72

5,8

86

1.8

%2

.5%

76

0,5

00

20

06

-07

64

,17

43

27

,29

22

69

,51

3-

--

59

6,8

05

1.8

%2

.5%

64

4,8

00

20

07

-08

56

,11

83

49

,07

72

48

,36

1-

--

59

7,4

38

1.8

%2

.5%

63

7,5

00

20

08

-09

93

,04

93

58

,90

92

71

,13

2-

--

63

0,0

41

1.8

%2

.5%

70

5,5

00

20

09

-10

82

,70

23

20

,93

02

24

,65

9-

--

54

5,5

88

1.8

%2

.5%

61

3,0

00

An

nu

alA

vera

ge:

2005

-2009

69,9

98

342,1

44

277,0

07

--

-619,1

52

1.8

%2.5

%672,3

00

20

10

-11

54

,56

23

14

,02

12

24

,65

9-

--

53

8,6

79

1.8

%2

.5%

57

8,7

00

20

11

-12

52

,48

93

08

,70

62

24

,65

9-

--

53

3,3

65

1.8

%2

.5%

57

1,4

00

20

12

-13

53

,79

63

06

,65

12

24

,65

9-

--

53

1,3

09

1.8

%2

.5%

57

0,7

00

20

13

-14

63

,25

83

11

,22

22

24

,65

9-

--

53

5,8

81

1.8

%2

.5%

58

4,5

00

20

14

-15

58

,24

13

76

,14

04

44

,43

2-

--

82

0,5

72

1.8

%2

.5%

85

7,0

00

An

nu

alA

vera

ge:

2010

-2014

56,4

69

323,3

48

268,6

13

--

-591,9

61

1.8

%2.5

%632,5

00

20

15

-16

36

,26

32

35

,84

92

26

,88

7-

--

46

2,7

36

1.8

%2

.5%

48

6,7

00

20

16

-17

32

,77

52

58

,43

32

05

,73

5-

--

46

4,1

68

1.8

%2

.5%

48

4,6

00

20

17

-18

32

,89

02

84

,99

62

28

,50

6-

--

51

3,5

02

1.8

%2

.5%

53

2,8

00

20

18

-19

34

,29

12

49

,15

41

82

,03

3-

--

43

1,1

87

1.8

%2

.5%

45

4,0

00

20

19

-20

39

,03

32

51

,85

31

82

,03

3-

--

43

3,8

86

1.8

%2

.5%

46

1,3

00

An

nu

alA

vera

ge:

2015

-2019

35,0

51

256,0

57

205,0

39

--

-461,0

96

1.8

%2.5

%483,9

00

20

20

-21

25

,99

32

64

,63

11

82

,03

3-

--

44

6,6

64

1.8

%2

.5%

46

0,9

00

20

21

-22

30

,71

72

76

,18

51

98

,39

1-

--

47

4,5

76

1.8

%2

.5%

49

2,8

00

20

22

-23

28

,29

92

75

,96

71

98

,39

1-

--

47

4,3

58

1.8

%2

.5%

49

0,2

00

20

23

-24

51

,42

33

71

,62

44

28

,07

4-

--

79

9,6

98

1.8

%2

.5%

83

0,0

00

20

24

-25

37

,94

12

54

,51

22

10

,52

8-

--

46

5,0

41

1.8

%2

.5%

49

0,6

00

An

nu

alA

vera

ge:

2020

-2024

34,8

74

288,5

84

243,4

83

--

-532,0

67

1.8

%2.5

%552,9

00

20

25

-26

23

,77

72

65

,95

41

89

,37

7-

--

45

5,3

31

1.8

%2

.5%

46

7,2

00

20

26

-27

46

,57

32

95

,92

12

12

,14

8-

--

50

8,0

69

1.8

%2

.5%

54

1,0

00

20

27

-28

28

,08

02

47

,11

51

65

,67

4-

--

41

2,7

89

1.8

%2

.5%

42

9,9

00

20

28

-29

21

,52

02

52

,59

51

65

,67

4-

--

41

8,2

69

1.8

%2

.5%

42

8,8

00

20

29

-30

51

,96

12

47

,34

91

65

,67

4-

--

41

3,0

23

1.8

%2

.5%

45

3,6

00

An

nu

alA

vera

ge:

2025

-2029

34,3

82

261,7

87

179,7

09

--

-441,4

96

1.8

%2.5

%464,1

00

20

30

-31

42

,72

52

84

,68

51

98

,39

1-

--

48

3,0

76

1.8

%2

.5%

51

2,8

00

20

31

-32

90

,77

92

84

,09

51

98

,39

1-

--

48

2,4

86

1.8

%2

.5%

55

9,4

00

20

32

-33

52

,17

63

85

,93

74

28

,07

4-

--

81

4,0

11

1.8

%2

.5%

84

4,7

00

20

33

-34

40

,02

22

42

,50

02

10

,52

8-

--

45

3,0

28

1.8

%2

.5%

48

0,9

00

20

34

-35

45

,08

42

56

,11

71

89

,37

7-

--

44

5,4

94

1.8

%2

.5%

47

8,5

00

An

nu

alA

vera

ge:

2030

-2034

54,1

57

290,6

67

244,9

52

--

-535,6

19

1.8

%2.5

%575,3

00

An

nu

alA

vera

ge:

2005

-2034

47,4

89

293,7

65

236,4

67

--

-530,2

32

1.8

%2.5

%563,5

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 1


FO

REC

AST

OF

RO

UN

DW

OO

DO

TH

ER

TH

AN

SA

WLO

GS

INTO

NS:

MPU

MA

LAN

GA

NO

RTH

:2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

79

1,7

21

1,3

57

,25

03

98

,39

9-

--

1,7

55

,64

90

.9%

2.3

%2

,50

0,8

00

20

06

-07

74

8,8

82

1,1

90

,07

16

23

,99

9-

--

1,8

14

,06

90

.9%

2.3

%2

,51

5,5

00

20

07

-08

80

3,0

00

1,1

90

,05

06

12

,03

0-

--

1,8

02

,08

00

.9%

2.3

%2

,55

7,4

00

20

08

-09

86

1,2

08

1,2

63

,20

43

73

,67

1-

--

1,6

36

,87

50

.9%

2.3

%2

,45

3,6

00

20

09

-10

75

0,6

98

1,2

24

,63

62

57

,28

5-

--

1,4

81

,92

10

.9%

2.3

%2

,19

2,6

00

An

nu

alA

vera

ge:

2005

-2009

791,1

02

1,2

45,0

42

453,0

77

--

-1,6

98,1

19

0.9

%2.3

%2,4

44,0

00

20

10

-11

84

8,3

31

1,2

16

,59

92

57

,28

5-

--

1,4

73

,88

40

.9%

2.3

%2

,28

1,5

00

20

11

-12

71

7,2

78

1,2

12

,93

22

57

,28

5-

--

1,4

70

,21

70

.9%

2.3

%2

,14

8,1

00

20

12

-13

88

6,8

65

1,2

08

,79

02

57

,28

5-

--

1,4

66

,07

50

.9%

2.3

%2

,31

2,1

00

20

13

-14

77

1,9

90

1,2

15

,18

82

57

,28

5-

--

1,4

72

,47

20

.9%

2.3

%2

,20

4,5

00

20

14

-15

55

9,8

17

1,3

39

,26

13

38

,15

6-

--

1,6

77

,41

70

.9%

2.3

%2

,19

4,5

00

An

nu

alA

vera

ge:

2010

-2014

756,8

56

1,2

38,5

54

273,4

59

--

-1,5

12,0

13

0.9

%2.3

%2,2

28,1

00

20

15

-16

57

0,9

83

91

3,5

83

56

5,9

94

--

-1

,47

9,5

77

0.9

%2

.3%

2,0

12

,20

0

20

16

-17

53

7,7

50

90

4,8

03

55

4,0

25

--

-1

,45

8,8

28

0.9

%2

.3%

1,9

59

,00

0

20

17

-18

54

7,1

14

99

7,7

82

31

5,6

66

--

-1

,31

3,4

48

0.9

%2

.3%

1,8

26

,20

0

20

18

-19

55

0,4

56

96

1,2

38

19

9,2

80

--

-1

,16

0,5

18

0.9

%2

.3%

1,6

80

,00

0

20

19

-20

56

6,8

20

96

3,6

08

19

9,2

80

--

-1

,16

2,8

88

0.9

%2

.3%

1,6

98

,50

0

An

nu

alA

vera

ge:

2015

-2019

554,6

25

948,2

03

366,8

49

--

-1,3

15,0

52

0.9

%2.3

%1,8

35,2

00

20

20

-21

59

3,8

77

96

5,2

62

19

9,2

80

--

-1

,16

4,5

42

0.9

%2

.3%

1,7

26

,90

0

20

21

-22

54

5,5

74

1,0

38

,81

92

21

,76

2-

--

1,2

60

,58

10

.9%

2.3

%1

,77

3,0

00

20

22

-23

58

7,2

22

1,0

43

,13

92

21

,76

2-

--

1,2

64

,90

10

.9%

2.3

%1

,81

8,5

00

20

23

-24

80

7,8

01

1,2

72

,47

53

15

,67

4-

--

1,5

88

,15

00

.9%

2.3

%2

,35

3,1

00

20

24

-25

70

3,2

34

86

9,6

48

54

3,5

12

--

-1

,41

3,1

60

0.9

%2

.3%

2,0

78

,40

0

An

nu

alA

vera

ge:

2020

-2024

647,5

42

1,0

37,8

69

300,3

98

--

-1,3

38,2

67

0.9

%2.3

%1,9

50,0

00

20

25

-26

72

2,0

60

86

5,1

40

53

1,5

44

--

-1

,39

6,6

83

0.9

%2

.3%

2,0

80

,90

0

20

26

-27

75

2,8

82

96

3,0

23

29

3,1

84

--

-1

,25

6,2

08

0.9

%2

.3%

1,9

74

,10

0

20

27

-28

67

5,6

60

90

4,8

70

17

6,7

98

--

-1

,08

1,6

68

0.9

%2

.3%

1,7

27

,00

0

20

28

-29

81

0,9

43

89

8,2

66

17

6,7

98

--

-1

,07

5,0

65

0.9

%2

.3%

1,8

54

,60

0

20

29

-30

68

5,3

06

90

5,4

70

17

6,7

98

--

-1

,08

2,2

69

0.9

%2

.3%

1,7

37

,10

0

An

nu

alA

vera

ge:

2025

-2029

729,3

70

907,3

54

271,0

25

--

-1,1

78,3

78

0.9

%2.3

%1,8

74,7

00

20

30

-31

89

8,3

01

1,0

44

,75

72

21

,76

2-

--

1,2

66

,51

90

.9%

2.3

%2

,12

8,4

00

20

31

-32

79

1,5

87

1,0

40

,55

02

21

,76

2-

--

1,2

62

,31

20

.9%

2.3

%2

,01

8,5

00

20

32

-33

56

4,7

13

1,2

83

,55

53

15

,67

4-

--

1,5

99

,22

90

.9%

2.3

%2

,12

2,9

00

20

33

-34

56

1,3

42

86

1,1

02

54

3,5

12

--

-1

,40

4,6

15

0.9

%2

.3%

1,9

29

,40

0

20

34

-35

53

7,4

55

85

4,0

47

53

1,5

44

--

-1

,38

5,5

90

0.9

%2

.3%

1,8

87

,10

0

An

nu

alA

vera

ge:

2030

-2034

670,6

80

1,0

16,8

02

366,8

51

--

-1,3

83,6

53

0.9

%2.3

%2,0

17,3

00

An

nu

alA

vera

ge:

2005

-2034

691,6

96

1,0

65,6

37

338,6

10

--

-1,4

04,2

47

0.9

%2.3

%2,0

58,2

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 2


January 2005

FO

REC

AST

OF

RO

UN

DW

OO

DO

TH

ER

TH

AN

SA

WLO

GS

INTO

NS:

MPU

MA

LAN

GA

SO

UTH

/CEN

TRA

LD

ISTRIC

TS(C

OM

BIN

ED

):2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

1,0

95

,28

35

50

,16

72

,04

9,2

99

12

4,5

77

69

,30

01

93

,87

72

,79

3,3

43

1.1

%1

.0%

3,8

49

,40

0

20

06

-07

1,4

57

,29

45

64

,35

01

,97

9,7

47

13

8,8

05

69

,30

02

08

,10

52

,75

2,2

03

1.1

%1

.0%

4,1

66

,80

0

20

07

-08

1,4

22

,10

55

38

,47

72

,03

0,1

82

17

1,7

08

69

,30

02

41

,00

82

,80

9,6

67

1.1

%1

.0%

4,1

88

,90

0

20

08

-09

1,5

28

,44

24

22

,23

22

,08

6,4

99

19

2,6

47

69

,30

02

61

,94

72

,77

0,6

78

1.1

%1

.0%

4,2

55

,50

0

20

09

-10

1,7

67

,47

73

86

,86

21

,83

3,6

79

12

9,5

89

69

,30

01

98

,88

92

,41

9,4

29

1.1

%1

.0%

4,1

44

,20

0

An

nu

alA

vera

ge:

2005

-2009

1,4

54,1

20

492,4

18

1,9

95,8

81

151,4

65

69,3

00

220,7

65

2,7

09,0

64

1.1

%1.0

%4,1

21,0

00

20

10

-11

2,0

37

,57

53

86

,41

41

,83

3,6

79

15

5,1

39

69

,30

02

24

,43

92

,44

4,5

32

1.1

%1

.0%

4,4

36

,20

0

20

11

-12

1,5

48

,28

73

85

,99

41

,83

3,6

79

12

9,0

26

69

,30

01

98

,32

62

,41

7,9

99

1.1

%1

.0%

3,9

25

,90

0

20

12

-13

1,6

25

,11

73

85

,90

41

,83

3,6

79

13

9,4

55

69

,30

02

08

,75

52

,42

8,3

38

1.1

%1

.0%

4,0

12

,20

0

20

13

-14

1,5

42

,46

03

86

,31

31

,83

3,6

79

12

3,2

86

69

,30

01

92

,58

62

,41

2,5

78

1.1

%1

.0%

3,9

14

,80

0

20

14

-15

1,1

50

,10

86

34

,02

02

,40

3,2

37

74

,61

96

9,3

00

14

3,9

19

3,1

81

,17

61

.1%

1.0

%4

,28

7,7

00

An

nu

alA

vera

ge:

2010

-2014

1,5

80,7

10

435,7

29

1,9

47,5

90

124,3

05

69,3

00

193,6

05

2,5

76,9

24

1.1

%1.0

%4,1

15,4

00

20

15

-16

1,1

89

,17

95

11

,85

41

,68

6,5

60

14

2,3

73

64

,00

02

06

,37

32

,40

4,7

87

1.1

%1

.0%

3,5

57

,60

0

20

16

-17

1,1

54

,37

54

86

,30

11

,73

6,9

94

12

6,1

88

64

,00

01

90

,18

82

,41

3,4

83

1.1

%1

.0%

3,5

31

,80

0

20

17

-18

1,1

55

,00

73

69

,99

81

,79

3,3

11

15

9,0

91

64

,00

02

23

,09

12

,38

6,4

00

1.1

%1

.0%

3,5

05

,60

0

20

18

-19

1,1

56

,52

83

34

,69

61

,54

0,4

91

18

0,0

30

64

,00

02

44

,03

02

,11

9,2

17

1.1

%1

.0%

3,2

42

,50

0

20

19

-20

1,1

73

,40

93

35

,09

41

,54

0,4

91

11

6,9

72

64

,00

01

80

,97

22

,05

6,5

56

1.1

%1

.0%

3,1

97

,20

0

An

nu

alA

vera

ge:

2015

-2019

1,1

65,7

00

407,5

89

1,6

59,5

69

144,9

31

64,0

00

208,9

31

2,2

76,0

89

1.1

%1.0

%3,4

06,9

00

20

20

-21

1,1

68

,45

63

35

,01

81

,54

0,4

91

14

7,0

29

64

,00

02

11

,02

92

,08

6,5

38

1.1

%1

.0%

3,2

22

,00

0

20

21

-22

1,1

31

,56

93

65

,16

71

,66

4,8

40

12

0,9

17

64

,00

01

84

,91

72

,21

4,9

23

1.1

%1

.0%

3,3

12

,60

0

20

22

-23

1,1

32

,65

33

65

,29

31

,66

4,8

40

13

1,3

46

64

,00

01

95

,34

62

,22

5,4

78

1.1

%1

.0%

3,3

24

,10

0

20

23

-24

86

5,9

61

60

5,4

27

2,2

78

,88

81

15

,17

76

4,0

00

17

9,1

77

3,0

63

,49

21

.1%

1.0

%3

,89

0,1

00

20

24

-25

1,2

98

,69

04

83

,05

31

,56

2,2

11

74

,61

96

4,0

00

13

8,6

19

2,1

83

,88

21

.1%

1.0

%3

,44

7,2

00

An

nu

alA

vera

ge:

2020

-2024

1,1

19,4

66

430,7

91

1,7

42,2

54

117,8

17

64,0

00

181,8

17

2,3

54,8

63

1.1

%1.0

%3,4

39,2

00

20

25

-26

1,2

70

,41

84

57

,43

71

,61

2,6

45

13

4,2

63

64

,00

01

98

,26

32

,26

8,3

46

1.1

%1

.0%

3,5

02

,80

0

20

26

-27

1,3

95

,47

43

41

,68

71

,66

8,9

62

11

8,0

78

64

,00

01

82

,07

82

,19

2,7

28

1.1

%1

.0%

3,5

51

,70

0

20

27

-28

1,6

07

,79

73

05

,17

81

,41

6,1

42

15

0,9

82

64

,00

02

14

,98

21

,93

6,3

02

1.1

%1

.0%

3,5

07

,80

0

20

28

-29

1,8

20

,39

13

04

,80

11

,41

6,1

42

17

1,9

20

64

,00

02

35

,92

01

,95

6,8

63

1.1

%1

.0%

3,7

38

,50

0

20

29

-30

1,4

31

,47

83

04

,99

81

,41

6,1

42

10

8,8

62

64

,00

01

72

,86

21

,89

4,0

02

1.1

%1

.0%

3,2

91

,50

0

An

nu

alA

vera

ge:

2025

-2029

1,5

05,1

11

342,8

20

1,5

06,0

07

136,8

21

64,0

00

200,8

21

2,0

49,6

48

1.1

%1.0

%3,5

18,5

00

20

30

-31

1,5

55

,20

53

64

,90

31

,66

4,8

40

13

8,9

20

64

,00

02

02

,92

02

,23

2,6

63

1.1

%1

.0%

3,7

49

,20

0

20

31

-32

1,4

43

,64

23

64

,80

61

,66

4,8

40

11

2,8

07

64

,00

01

76

,80

72

,20

6,4

54

1.1

%1

.0%

3,6

12

,90

0

20

32

-33

1,0

86

,20

16

04

,93

82

,27

8,8

88

12

3,2

36

64

,00

01

87

,23

63

,07

1,0

62

1.1

%1

.0%

4,1

15

,40

0

20

33

-34

1,1

09

,70

24

83

,08

11

,56

2,2

11

10

7,0

67

64

,00

01

71

,06

72

,21

6,3

59

1.1

%1

.0%

3,2

92

,40

0

20

34

-35

1,0

99

,10

54

57

,70

91

,61

2,6

45

74

,61

96

4,0

00

13

8,6

19

2,2

08

,97

31

.1%

1.0

%3

,27

4,6

00

An

nu

alA

vera

ge:

2030

-2034

1,2

58,7

71

455,0

88

1,7

56,6

85

111,3

30

64,0

00

175,3

30

2,3

87,1

02

1.1

%1.0

%3,6

08,9

00

An

nu

alA

vera

ge:

2005

-2034

1,3

47,3

13

427,4

06

1,7

67,9

98

131,1

12

65,7

67

196,8

78

2,3

92,2

82

1.1

%1.0

%3,7

01,6

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 3


FO

REC

AST

OF

RO

UN

DW

OO

DO

TH

ER

TH

AN

SA

WLO

GS

INTO

NS:

ZU

LULA

ND

(CO

MBIN

ED

):2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

43

4,4

78

1,8

53

,18

01

,11

1,6

08

30

6,1

48

18

,00

03

24

,14

83

,28

8,9

36

4.8

%1

.4%

3,6

58

,00

0

20

06

-07

36

2,5

56

1,8

16

,11

29

87

,60

42

98

,10

61

8,0

00

31

6,1

06

3,1

19

,82

24

.8%

1.4

%3

,42

2,7

00

20

07

-08

35

5,8

75

1,8

31

,24

78

07

,00

73

68

,86

21

8,0

00

38

6,8

62

3,0

25

,11

64

.8%

1.4

%3

,32

2,9

00

20

08

-09

36

3,3

44

2,0

81

,08

09

65

,90

53

44

,73

51

8,0

00

36

2,7

35

3,4

09

,72

04

.8%

1.4

%3

,70

9,4

00

20

09

-10

30

4,6

56

1,6

01

,90

87

57

,93

33

02

,43

61

8,0

00

32

0,4

36

2,6

80

,27

84

.8%

1.4

%2

,93

4,0

00

An

nu

alA

vera

ge:

2005

-2009

364,1

82

1,8

36,7

05

926,0

11

324,0

57

18,0

00

342,0

57

3,1

04,7

74

4.8

%1

.4%

3,4

09,4

00

20

10

-11

38

7,8

14

1,6

01

,83

87

57

,93

32

83

,10

01

8,0

00

30

1,1

00

2,6

60

,87

24

.8%

1.4

%2

,99

4,0

00

20

11

-12

41

9,4

30

1,6

01

,52

57

57

,93

32

68

,09

81

8,0

00

28

6,0

98

2,6

45

,55

74

.8%

1.4

%3

,00

9,0

00

20

12

-13

31

5,0

79

1,6

01

,21

47

57

,93

32

45

,05

41

8,0

00

26

3,0

54

2,6

22

,20

24

.8%

1.4

%2

,88

6,6

00

20

13

-14

30

0,0

17

1,6

01

,06

17

57

,93

32

87

,97

21

8,0

00

30

5,9

72

2,6

64

,96

64

.8%

1.4

%2

,91

4,5

00

20

14

-15

21

3,6

37

2,3

37

,52

21

,56

1,3

10

15

3,4

97

18

,00

01

71

,49

74

,07

0,3

29

4.8

%1

.4%

4,2

18

,60

0

An

nu

alA

vera

ge:

2010

-2014

327,1

96

1,7

48,6

32

918,6

09

247,5

44

18,0

00

265,5

44

2,9

32,7

85

4.8

%1

.4%

3,2

04,5

00

20

15

-16

24

7,6

80

1,5

82

,30

09

04

,48

53

24

,00

11

6,5

00

34

0,5

01

2,8

27

,28

64

.8%

1.4

%3

,02

4,8

00

20

16

-17

20

7,2

43

1,5

97

,68

57

23

,88

82

75

,61

31

6,5

00

29

2,1

13

2,6

13

,68

64

.8%

1.4

%2

,77

5,6

00

20

17

-18

21

2,7

51

1,8

48

,14

88

82

,78

63

46

,36

81

6,5

00

36

2,8

68

3,0

93

,80

24

.8%

1.4

%3

,25

4,4

00

20

18

-19

21

1,4

85

1,3

70

,51

96

74

,81

53

22

,24

21

6,5

00

33

8,7

42

2,3

84

,07

54

.8%

1.4

%2

,55

3,1

00

20

19

-20

20

4,4

88

1,3

70

,48

06

74

,81

52

79

,94

31

6,5

00

29

6,4

43

2,3

41

,73

84

.8%

1.4

%2

,50

4,7

00

An

nu

alA

vera

ge:

2015

-2019

216,7

29

1,5

53,8

26

772,1

58

309,6

33

16,5

00

326,1

33

2,6

52,1

17

4.8

%1

.4%

2,8

22,5

00

20

20

-21

22

0,6

01

1,3

70

,56

56

74

,81

52

66

,31

81

6,5

00

28

2,8

18

2,3

28

,19

84

.8%

1.4

%2

,50

6,7

00

20

21

-22

21

3,3

69

1,4

85

,93

67

35

,24

72

51

,31

61

6,5

00

26

7,8

16

2,4

88

,99

84

.8%

1.4

%2

,65

8,4

00

20

22

-23

20

2,0

57

1,4

86

,10

57

35

,24

72

28

,27

21

6,5

00

24

4,7

72

2,4

66

,12

34

.8%

1.4

%2

,62

5,1

00

20

23

-24

44

3,6

57

2,2

23

,92

41

,50

0,8

78

27

1,1

89

16

,50

02

87

,68

94

,01

2,4

91

4.8

%1

.4%

4,3

80

,50

0

20

24

-25

29

9,1

77

1,4

69

,22

88

44

,05

41

53

,49

71

6,5

00

16

9,9

97

2,4

83

,27

94

.8%

1.4

%2

,73

4,4

00

An

nu

alA

vera

ge:

2020

-2024

275,7

72

1,6

07,1

52

898,0

48

234,1

18

16,5

00

250,6

18

2,7

55,8

18

4.8

%1

.4%

2,9

81,0

00

20

25

-26

31

4,9

42

1,4

84

,19

16

63

,45

73

07

,21

91

6,5

00

32

3,7

19

2,4

71

,36

64

.8%

1.4

%2

,73

7,7

00

20

26

-27

33

4,8

80

1,7

34

,76

38

22

,35

42

58

,83

01

6,5

00

27

5,3

30

2,8

32

,44

74

.8%

1.4

%3

,11

2,8

00

20

27

-28

27

5,5

13

1,2

55

,60

06

14

,38

33

29

,58

61

6,5

00

34

6,0

86

2,2

16

,06

94

.8%

1.4

%2

,44

8,3

00

20

28

-29

32

5,4

87

1,2

55

,17

66

14

,38

33

05

,45

91

6,5

00

32

1,9

59

2,1

91

,51

84

.8%

1.4

%2

,47

1,7

00

20

29

-30

39

0,6

55

1,2

54

,98

86

14

,38

32

63

,16

11

6,5

00

27

9,6

61

2,1

49

,03

14

.8%

1.4

%2

,49

1,8

00

An

nu

alA

vera

ge:

2025

-2029

328,2

95

1,3

96,9

44

665,7

92

292,8

51

16,5

00

309,3

51

2,3

72,0

86

4.8

%1

.4%

2,6

52,5

00

20

30

-31

32

1,0

87

1,4

86

,56

97

35

,24

72

49

,53

51

6,5

00

26

6,0

35

2,4

87

,85

14

.8%

1.4

%2

,75

9,8

00

20

31

-32

28

7,1

76

1,4

86

,60

57

35

,24

72

34

,53

31

6,5

00

25

1,0

33

2,4

72

,88

54

.8%

1.4

%2

,71

2,7

00

20

32

-33

20

2,3

51

2,2

24

,27

41

,50

0,8

78

21

1,4

90

16

,50

02

27

,99

03

,95

3,1

42

4.8

%1

.4%

4,0

92

,30

0

20

33

-34

20

3,4

79

1,4

69

,12

78

44

,05

42

54

,40

71

6,5

00

27

0,9

07

2,5

84

,08

84

.8%

1.4

%2

,74

2,8

00

20

34

-35

20

5,6

52

1,4

83

,85

26

63

,45

71

53

,49

71

6,5

00

16

9,9

97

2,3

17

,30

64

.8%

1.4

%2

,48

1,7

00

An

nu

alA

vera

ge:

2030

-2034

243,9

49

1,6

30,0

86

895,7

76

220,6

93

16,5

00

237,1

93

2,7

63,0

54

4.8

%1

.4%

2,9

57,9

00

An

nu

alA

vera

ge:

2005

-2034

292,6

87

1,6

28,8

91

846,0

66

271,4

83

17,0

00

288,4

83

2,7

63,4

39

4.8

%1

.4%

3,0

04,6

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 4


January 2005

FO

REC

AST

OF

RO

UN

DW

OO

DO

TH

ER

TH

AN

SA

WLO

GS

INTO

NS:

KZ

NM

IDLA

ND

S:

2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

63

0,4

98

79

2,2

74

82

2,0

66

64

2,2

02

-6

42

,20

22

,25

6,5

43

1.5

%1

.5%

2,8

43

,40

0

20

06

-07

74

0,1

08

84

5,6

47

68

1,0

66

65

9,6

31

-6

59

,63

12

,18

6,3

44

1.5

%1

.5%

2,8

82

,20

0

20

07

-08

1,0

50

,09

18

36

,27

15

28

,02

46

72

,18

7-

67

2,1

87

2,0

36

,48

11

.5%

1.5

%3

,04

0,0

00

20

08

-09

1,2

11

,55

57

76

,55

25

20

,03

95

85

,95

1-

58

5,9

51

1,8

82

,54

21

.5%

1.5

%3

,04

7,5

00

20

09

-10

1,2

97

,79

77

05

,17

74

77

,86

85

14

,41

9-

51

4,4

19

1,6

97

,46

31

.5%

1.5

%2

,95

0,2

00

An

nu

alA

vera

ge:

2005

-2009

986,0

10

791,1

84

605,8

12

614,8

78

-614,8

78

2,0

11,8

75

1.5

%1.5

%2,9

52,6

60

20

10

-11

1,1

63

,53

67

04

,71

54

77

,86

84

92

,55

0-

49

2,5

50

1,6

75

,13

31

.5%

1.5

%2

,79

5,9

00

20

11

-12

69

5,2

40

70

4,3

45

47

7,8

68

43

9,8

51

-4

39

,85

11

,62

2,0

63

1.5

%1

.5%

2,2

82

,30

0

20

12

-13

50

6,8

46

70

4,1

93

47

7,8

68

45

0,9

19

-4

50

,91

91

,63

2,9

79

1.5

%1

.5%

2,1

07

,50

0

20

13

-14

66

5,6

73

70

4,6

13

47

7,8

68

37

6,0

83

-3

76

,08

31

,55

8,5

63

1.5

%1

.5%

2,1

90

,70

0

20

14

-15

50

5,1

59

92

1,2

64

85

0,3

26

32

4,7

87

-3

24

,78

72

,09

6,3

78

1.5

%1

.5%

2,5

62

,20

0

An

nu

alA

vera

ge:

2010

-2014

707,2

91

747,8

26

552,3

59

416,8

38

-416,8

38

1,7

17,0

23

1.5

%1.5

%2,3

87,7

20

20

15

-16

50

6,2

29

71

5,3

38

60

6,5

88

73

1,7

99

-7

31

,79

92

,05

3,7

24

1.5

%1

.5%

2,5

21

,20

0

20

16

-17

50

5,4

90

70

6,0

28

45

3,5

47

61

9,0

69

-6

19

,06

91

,77

8,6

44

1.5

%1

.5%

2,2

49

,60

0

20

17

-18

51

5,4

30

64

6,9

65

44

5,5

61

63

1,6

24

-6

31

,62

41

,72

4,1

50

1.5

%1

.5%

2,2

05

,70

0

20

18

-19

51

6,7

58

57

5,4

59

40

3,3

90

54

5,3

89

-5

45

,38

91

,52

4,2

38

1.5

%1

.5%

2,0

10

,20

0

20

19

-20

51

4,3

13

57

5,3

05

40

3,3

90

47

3,8

56

-4

73

,85

61

,45

2,5

51

1.5

%1

.5%

1,9

37

,20

0

An

nu

alA

vera

ge:

2015

-2019

511,6

44

643,8

19

462,4

95

600,3

47

-600,3

47

1,7

06,6

61

1.5

%1.5

%2,1

84,7

80

20

20

-21

51

4,0

20

57

5,7

81

40

3,3

90

46

1,9

12

-4

61

,91

21

,44

1,0

83

1.5

%1

.5%

1,9

25

,60

0

20

21

-22

50

2,9

31

62

3,2

16

43

8,8

79

40

9,2

13

-4

09

,21

31

,47

1,3

07

1.5

%1

.5%

1,9

44

,40

0

20

22

-23

50

4,0

10

62

3,4

48

43

8,8

79

42

0,2

81

-4

20

,28

11

,48

2,6

08

1.5

%1

.5%

1,9

56

,60

0

20

23

-24

55

7,6

55

87

4,7

87

81

4,8

38

34

5,4

44

-3

45

,44

42

,03

5,0

69

1.5

%1

.5%

2,5

53

,50

0

20

24

-25

67

3,4

21

66

9,1

54

57

1,0

99

32

4,7

87

-3

24

,78

71

,56

5,0

41

1.5

%1

.5%

2,2

04

,70

0

An

nu

alA

vera

ge:

2020

-2024

550,4

07

673,2

77

533,4

17

392,3

27

-392,3

27

1,5

99,0

22

1.5

%1.5

%2,1

16,9

60

20

25

-26

99

5,4

16

65

9,5

84

41

8,0

58

70

1,1

60

-7

01

,16

01

,77

8,8

03

1.5

%1

.5%

2,7

32

,40

0

20

26

-27

1,1

63

,12

36

00

,64

34

10

,07

35

88

,43

1-

58

8,4

31

1,5

99

,14

61

.5%

1.5

%2

,72

0,7

00

20

27

-28

1,2

43

,54

55

27

,80

53

67

,90

26

00

,98

6-

60

0,9

86

1,4

96

,69

31

.5%

1.5

%2

,69

9,0

00

20

28

-29

1,1

09

,68

65

27

,71

03

67

,90

25

14

,75

0-

51

4,7

50

1,4

10

,36

21

.5%

1.5

%2

,48

2,1

00

20

29

-30

65

0,2

03

52

7,8

53

36

7,9

02

44

3,2

18

-4

43

,21

81

,33

8,9

72

1.5

%1

.5%

1,9

59

,20

0

An

nu

alA

vera

ge:

2025

-2029

1,0

32,3

95

568,7

19

386,3

67

569,7

09

-569,7

09

1,5

24,7

95

1.5

%1.5

%2,5

18,6

80

20

30

-31

46

3,5

45

62

3,3

22

43

8,8

79

43

1,2

74

-4

31

,27

41

,49

3,4

74

1.5

%1

.5%

1,9

27

,40

0

20

31

-32

62

1,0

46

62

2,9

40

43

8,8

79

37

8,5

74

-3

78

,57

41

,44

0,3

93

1.5

%1

.5%

2,0

30

,30

0

20

32

-33

48

3,3

55

87

4,7

13

81

4,8

38

38

9,6

43

-3

89

,64

32

,07

9,1

93

1.5

%1

.5%

2,5

23

,80

0

20

33

-34

47

8,2

41

66

8,8

47

57

1,0

99

31

4,8

06

-3

14

,80

61

,55

4,7

52

1.5

%1

.5%

2,0

02

,30

0

20

34

-35

47

3,8

03

65

9,5

60

41

8,0

58

32

4,7

87

-3

24

,78

71

,40

2,4

05

1.5

%1

.5%

1,8

47

,90

0

An

nu

alA

vera

ge:

2030

-2034

503,9

98

689,8

76

536,3

50

367,8

17

-367,8

17

1,5

94,0

44

1.5

%1.5

%2,0

66,3

40

-

An

nu

alA

vera

ge:

2005

-2034

715,2

91

685,7

84

512,8

00

493,6

53

-493,6

53

1,6

92,2

37

1.5

%1.5

%2,3

71,2

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 5


FO

REC

AST

OF

RO

UN

DW

OO

DO

TH

ER

TH

AN

SA

WLO

GS

INTO

NS:

SO

UTH

ERN

KZ

N:

2005

-2034

Year

Ton

s%

Redu

ctio

nfo

rFi

res

and

Oth

erFa

ctor

s:So

ftw

ood

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

Ton

s

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

35

0,6

75

60

8,3

26

44

6,8

49

34

,53

3-

34

,53

31

,08

9,7

07

2.7

%0

.9%

1,4

21

,50

0

20

06

-07

47

0,1

27

62

8,7

13

43

5,8

16

36

,98

5-

36

,98

51

,10

1,5

13

2.7

%0

.9%

1,5

49

,40

0

20

07

-08

50

1,2

46

57

7,4

34

23

3,9

14

41

,73

0-

41

,73

08

53

,07

82

.7%

0.9

%1

,33

3,4

00

20

08

-09

45

0,8

42

50

6,8

24

38

6,0

41

51

,29

9-

51

,29

99

44

,16

42

.7%

0.9

%1

,37

4,7

00

20

09

-10

82

4,2

35

52

5,0

98

26

1,3

08

26

,46

6-

26

,46

68

12

,87

22

.7%

0.9

%1

,60

7,8

00

An

nu

alA

vera

ge:

2005

-2009

519,4

25

569,2

79

352,7

86

38,2

03

-38,2

03

960,2

67

2.7

%0.9

%1,4

57,4

00

20

10

-11

60

0,7

46

52

4,9

48

26

1,3

08

31

,71

4-

31

,71

48

17

,96

92

.7%

0.9

%1

,39

5,4

00

20

11

-12

38

6,3

23

52

4,8

19

26

1,3

08

18

,58

5-

18

,58

58

04

,71

22

.7%

0.9

%1

,17

3,6

00

20

12

-13

26

9,4

25

52

4,9

56

26

1,3

08

23

,17

2-

23

,17

28

09

,43

52

.7%

0.9

%1

,06

4,6

00

20

13

-14

43

7,7

69

52

5,0

09

26

1,3

08

21

,82

8-

21

,82

88

08

,14

42

.7%

0.9

%1

,22

7,1

00

20

14

-15

33

9,1

18

53

6,7

54

62

0,2

44

31

,23

9-

31

,23

91

,18

8,2

38

2.7

%0

.9%

1,5

07

,90

0

An

nu

alA

vera

ge:

2010

-2014

406,6

76

527,2

97

333,0

95

25,3

08

-25,3

08

885,7

00

2.7

%0.9

%1,2

73,7

00

20

15

-16

33

3,6

58

51

4,1

04

39

9,6

94

31

,92

9-

31

,92

99

45

,72

62

.7%

0.9

%1

,26

2,2

00

20

16

-17

33

1,5

30

46

3,5

74

19

7,7

92

34

,15

5-

34

,15

56

95

,52

12

.7%

0.9

%1

,01

2,1

00

20

17

-18

33

2,0

34

39

2,7

74

34

9,9

19

38

,90

0-

38

,90

07

81

,59

32

.7%

0.9

%1

,09

7,9

00

20

18

-19

33

3,1

42

41

1,0

80

22

5,1

85

48

,47

0-

48

,47

06

84

,73

52

.7%

0.9

%1

,00

3,0

00

20

19

-20

34

5,7

44

41

1,3

58

22

5,1

85

23

,63

7-

23

,63

76

60

,18

02

.7%

0.9

%9

90

,90

0

An

nu

alA

vera

ge:

2015

-2019

335,2

22

438,5

78

279,5

55

35,4

18

-35,4

18

753,5

51

2.7

%0.9

%1,0

73,2

00

20

20

-21

33

1,2

68

41

1,1

32

22

5,1

85

29

,88

4-

29

,88

46

66

,20

12

.7%

0.9

%9

82

,80

0

20

21

-22

32

2,3

60

44

3,4

24

24

7,0

45

16

,75

6-

16

,75

67

07

,22

52

.7%

0.9

%1

,01

4,8

00

20

22

-23

32

4,2

94

44

3,5

32

24

7,0

45

21

,34

3-

21

,34

37

11

,92

02

.7%

0.9

%1

,02

1,3

00

20

23

-24

30

9,5

41

50

4,9

70

59

8,3

85

19

,99

9-

19

,99

91

,12

3,3

53

2.7

%0

.9%

1,4

14

,80

0

20

24

-25

43

6,5

09

48

2,6

26

37

7,8

34

31

,23

9-

31

,23

98

91

,69

92

.7%

0.9

%1

,30

8,7

00

An

nu

alA

vera

ge:

2020

-2024

344,7

94

457,1

37

339,0

99

23,8

44

-23,8

44

820,0

80

2.7

%0.9

%1,1

48,5

00

20

25

-26

46

8,0

23

43

1,7

97

17

5,9

33

30

,10

0-

30

,10

06

37

,83

02

.7%

0.9

%1

,08

7,7

00

20

26

-27

40

3,5

86

36

1,0

44

32

8,0

59

32

,32

6-

32

,32

67

21

,42

92

.7%

0.9

%1

,10

7,9

00

20

27

-28

79

2,9

78

37

9,1

51

20

3,3

26

37

,07

1-

37

,07

16

19

,54

82

.7%

0.9

%1

,38

5,8

00

20

28

-29

55

9,0

29

37

8,9

82

20

3,3

26

46

,64

1-

46

,64

16

28

,94

92

.7%

0.9

%1

,16

7,4

00

20

29

-30

36

7,1

16

37

8,9

55

20

3,3

26

21

,80

8-

21

,80

86

04

,08

82

.7%

0.9

%9

56

,10

0

An

nu

alA

vera

ge:

2025

-2029

518,1

47

385,9

86

222,7

94

33,5

89

-33,5

89

642,3

69

2.7

%0.9

%1,1

41,0

00

20

30

-31

24

1,8

44

44

3,1

88

24

7,0

45

28

,05

5-

28

,05

57

18

,28

82

.7%

0.9

%9

47

,40

0

20

31

-32

42

0,7

65

44

3,3

22

24

7,0

45

14

,92

7-

14

,92

77

05

,29

42

.7%

0.9

%1

,10

8,6

00

20

32

-33

34

1,0

58

50

4,5

78

59

8,3

85

19

,51

4-

19

,51

41

,12

2,4

77

2.7

%0

.9%

1,4

44

,60

0

20

33

-34

33

2,4

18

48

2,3

00

37

7,8

34

18

,17

0-

18

,17

08

78

,30

42

.7%

0.9

%1

,19

4,1

00

20

34

-35

31

7,8

46

43

1,3

44

17

5,9

33

31

,23

9-

31

,23

96

38

,51

62

.7%

0.9

%9

42

,30

0

An

nu

alA

vera

ge:

2030

-2034

330,7

86

460,9

46

329,2

48

22,3

81

-22,3

81

812,5

76

2.7

%0.9

%1,1

27,4

00

An

nu

alA

vera

ge:

2005

-2034

409,1

75

473,2

04

309,4

29

29,7

90

-29,7

90

812,4

24

2.7

%0.9

%1,2

03,5

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 6


January 2005

Fore

cast

of

Rou

nd

wood

oth

er

than

Saw

log

sin

Ton

s:East

ern

Cap

e:

2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)W

attle

Tota

lTo

talH

ardw

oods

Tota

lFor

ecas

t(R

ound

edto

100)

20

05

-06

27

7,9

40

11

2,4

66

82

,94

4-

54

,00

05

4,0

00

24

9,4

10

2.3

%0

.8%

51

8,9

00

20

06

-07

27

2,2

22

12

4,7

61

73

,62

0-

54

,00

05

4,0

00

25

2,3

82

2.3

%0

.8%

51

6,3

00

20

07

-08

35

5,1

95

10

2,4

69

92

,19

2-

54

,00

05

4,0

00

24

8,6

61

2.3

%0

.8%

59

3,6

00

20

08

-09

39

7,6

44

10

6,5

67

12

0,2

96

-5

4,0

00

54,0

00

28

0,8

62

2.3

%0

.8%

66

7,0

00

20

09

-10

46

3,6

83

89

,62

08

0,3

97

-5

4,0

00

54,0

00

22

4,0

17

2.3

%0

.8%

67

5,2

00

An

nu

alA

vera

ge:

2005

-2009

353,3

37

107,1

77

89,8

90

-54,0

00

54,0

00

251,0

66

2.3

%0.8

%594,2

00

20

10

-11

54

9,3

66

89

,50

28

0,3

97

-5

4,0

00

54,0

00

22

3,8

99

2.3

%0

.8%

75

8,8

00

20

11

-12

26

7,0

52

89

,42

28

0,3

97

-5

4,0

00

54,0

00

22

3,8

19

2.3

%0

.8%

48

2,9

00

20

12

-13

29

9,8

12

89

,39

58

0,3

97

-5

4,0

00

54,0

00

22

3,7

92

2.3

%0

.8%

51

4,9

00

20

13

-14

30

0,8

09

89

,38

88

0,3

97

-5

4,0

00

54,0

00

22

3,7

86

2.3

%0

.8%

51

5,8

00

20

14

-15

29

1,6

95

17

0,0

02

60

,33

5-

54

,00

05

4,0

00

28

4,3

38

2.3

%0

.8%

56

7,0

00

An

nu

alA

vera

ge:

2010

-2014

341,7

47

105,5

42

76,3

85

-54,0

00

54,0

00

235,9

27

2.3

%0.8

%567,9

00

20

15

-16

38

7,4

74

11

1,5

05

53

,20

1-

50

,00

05

0,0

00

21

4,7

06

2.3

%0

.8%

59

1,5

00

20

16

-17

21

6,7

55

89

,08

97

1,7

73

-5

0,0

00

50,0

00

21

0,8

62

2.3

%0

.8%

42

0,9

00

20

17

-18

23

7,7

05

93

,32

59

9,8

77

-5

0,0

00

50,0

00

24

3,2

01

2.3

%0

.8%

47

3,4

00

20

18

-19

25

5,8

65

76

,65

05

9,9

78

-5

0,0

00

50,0

00

18

6,6

28

2.3

%0

.8%

43

5,1

00

20

19

-20

27

8,7

04

76

,52

25

9,9

78

-5

0,0

00

50,0

00

18

6,5

01

2.3

%0

.8%

45

7,3

00

An

nu

alA

vera

ge:

2015

-2019

275,3

01

89,4

18

68,9

61

-50,0

00

50,0

00

208,3

80

2.3

%0.8

%475,6

00

20

20

-21

31

4,2

89

77

,11

15

9,9

78

-5

0,0

00

50,0

00

18

7,0

89

2.3

%0

.8%

49

2,6

00

20

21

-22

21

1,0

61

83

,73

66

4,7

26

-5

0,0

00

50,0

00

19

8,4

63

2.3

%0

.8%

40

3,0

00

20

22

-23

23

9,6

30

83

,83

86

4,7

26

-5

0,0

00

50,0

00

19

8,5

64

2.3

%0

.8%

43

1,0

00

20

23

-24

15

3,0

98

16

3,4

97

55

,58

7-

50

,00

05

0,0

00

26

9,0

84

2.3

%0

.8%

41

6,4

00

20

24

-25

18

1,0

55

10

5,3

86

48

,45

3-

50

,00

05

0,0

00

20

3,8

40

2.3

%0

.8%

37

9,0

00

An

nu

alA

vera

ge:

2020

-2024

219,8

27

102,7

14

58,6

94

-50,0

00

50,0

00

211,4

08

2.3

%0.8

%424,4

00

20

25

-26

35

0,3

00

82

,85

06

7,0

25

-5

0,0

00

50,0

00

19

9,8

75

2.3

%0

.8%

54

0,5

00

20

26

-27

41

8,8

86

87

,06

59

5,1

28

-5

0,0

00

50,0

00

23

2,1

93

2.3

%0

.8%

63

9,5

00

20

27

-28

38

5,2

01

69

,95

15

5,2

30

-5

0,0

00

50,0

00

17

5,1

81

2.3

%0

.8%

55

0,1

00

20

28

-29

26

6,4

74

69

,56

95

5,2

30

-5

0,0

00

50,0

00

17

4,7

99

2.3

%0

.8%

43

3,7

00

20

29

-30

26

1,8

54

69

,51

95

5,2

30

-5

0,0

00

50,0

00

17

4,7

49

2.3

%0

.8%

42

9,1

00

An

nu

alA

vera

ge:

2025

-2029

336,5

43

75,7

91

65,5

69

-50,0

00

50,0

00

191,3

60

2.3

%0.8

%518,6

00

20

30

-31

46

2,2

48

83

,34

36

4,7

26

-5

0,0

00

50,0

00

19

8,0

70

2.3

%0

.8%

64

8,0

00

20

31

-32

32

5,9

68

83

,23

46

4,7

26

-5

0,0

00

50,0

00

19

7,9

60

2.3

%0

.8%

51

4,8

00

20

32

-33

32

1,5

22

16

3,2

83

55

,58

7-

50

,00

05

0,0

00

26

8,8

70

2.3

%0

.8%

58

0,8

00

20

33

-34

28

0,0

34

10

4,9

83

48

,45

3-

50

,00

05

0,0

00

20

3,4

36

2.3

%0

.8%

47

5,3

00

20

34

-35

28

8,4

35

82

,60

76

7,0

25

-5

0,0

00

50,0

00

19

9,6

32

2.3

%0

.8%

47

9,8

00

An

nu

alA

vera

ge:

2030

-2034

335,6

41

103,4

90

60,1

03

-50,0

00

50,0

00

213,5

93

2.3

%0.8

%539,7

00

An

nu

alA

vera

ge:

2005

-2034

310,3

99

97,3

55

69,9

34

-51,3

33

51,3

33

218,6

22

2.3

%0.8

%520,1

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 7


Fore

cast

of

Rou

nd

wood

oth

er

than

Saw

log

sin

Ton

s:Sou

thern

Cap

e:

2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

82

,02

51

32

46

,46

3-

--

46

,59

51

.9%

1.2

%1

26

,50

0

20

06

-07

88

,34

21

32

7,2

30

--

-7

,36

21

.9%

1.2

%9

3,9

00

20

07

-08

11

2,3

34

13

29

,54

5-

--

9,6

77

1.9

%1

.2%

11

9,8

00

20

08

-09

10

5,8

24

13

29

,24

8-

--

9,3

80

1.9

%1

.2%

11

3,1

00

20

09

-10

11

2,1

78

21

61

1,3

11

--

-1

1,5

27

1.9

%1

.2%

12

1,5

00

An

nu

alA

vera

ge:

2005

-2009

100,1

40

149

16,7

59

--

-16,9

08

1.9

%1.2

%115,0

00

20

10

-11

19

9,0

93

21

66

,91

2-

--

7,1

28

1.9

%1

.2%

20

2,4

00

20

11

-12

74

,92

42

16

9,1

74

--

-9

,39

01

.9%

1.2

%8

2,8

00

20

12

-13

96

,19

62

16

7,5

83

--

-7

,79

91

.9%

1.2

%1

02

,10

0

20

13

-14

72

,02

82

16

19

,76

2-

--

19

,97

81

.9%

1.2

%9

0,4

00

20

14

-15

87

,92

64

64

,77

5-

--

4,8

21

1.9

%1

.2%

91

,00

0

An

nu

alA

vera

ge:

2010

-2014

106,0

33

182

9,6

41

--

-9,8

23

1.9

%1.2

%113,7

00

20

15

-16

13

1,6

22

13

27

,29

6-

--

7,4

28

1.9

%1

.2%

13

6,5

00

20

16

-17

55

,45

61

32

6,5

68

--

-6

,70

01

.9%

1.2

%6

1,0

00

20

17

-18

60

,69

81

32

25

,79

2-

--

25

,92

31

.9%

1.2

%8

5,2

00

20

18

-19

43

,92

32

16

5,0

49

--

-5

,26

51

.9%

1.2

%4

8,3

00

20

19

-20

57

,64

62

16

6,9

88

--

-7

,20

41

.9%

1.2

%6

3,7

00

An

nu

alA

vera

ge:

2015

-2019

69,8

69

166

10,3

39

--

-10,5

04

1.9

%1.2

%78,9

00

20

20

-21

99

,17

11

32

5,8

75

--

-6

,00

71

.9%

1.2

%1

03

,20

0

20

21

-22

53

,89

02

16

5,2

95

--

-5

,51

11

.9%

1.2

%5

8,3

00

20

22

-23

60

,10

02

16

4,6

83

--

-4

,89

91

.9%

1.2

%6

3,8

00

20

23

-24

33

,22

25

02

,27

9-

--

2,3

30

1.9

%1

.2%

34

,90

0

20

24

-25

39

,30

51

32

4,6

00

--

-4

,73

21

.9%

1.2

%4

3,2

00

An

nu

alA

vera

ge:

2020

-2024

57,1

37

149

4,5

46

--

-4,6

96

1.9

%1.2

%60,7

00

20

25

-26

39

,23

21

32

4,8

62

--

-4

,99

31

.9%

1.2

%4

3,4

00

20

26

-27

41

,83

71

32

4,7

49

--

-4

,88

11

.9%

1.2

%4

5,9

00

20

27

-28

56

,42

72

16

5,3

79

--

-5

,59

51

.9%

1.2

%6

0,9

00

20

28

-29

29

,26

12

16

4,8

79

--

-5

,09

61

.9%

1.2

%3

3,7

00

20

29

-30

27

,84

81

32

6,4

03

--

-6

,53

51

.9%

1.2

%3

3,8

00

An

nu

alA

vera

ge:

2025

-2029

38,9

21

166

5,2

54

--

-5,4

20

1.9

%1.2

%43,5

00

20

30

-31

92

,58

52

16

40

,49

2-

--

40

,70

81

.9%

1.2

%1

31

,10

0

20

31

-32

29

,22

72

16

5,0

36

--

-5

,25

21

.9%

1.2

%3

3,9

00

20

32

-33

30

,71

85

03

,17

1-

--

3,2

21

1.9

%1

.2%

33

,30

0

20

33

-34

17

,33

51

32

7,0

26

--

-7

,15

81

.9%

1.2

%2

4,1

00

20

34

-35

4,1

24

13

29

,11

5-

--

9,2

46

1.9

%1

.2%

13

,20

0

An

nu

alA

vera

ge:

2030

-2034

34,7

98

149

12,9

68

--

-13,1

17

1.9

%1.2

%47,1

00

An

nu

alA

vera

ge:

2005

-2034

67,8

17

160

9,9

18

--

-10,0

78

1.9

%1.2

%76,5

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 8


January 2005

FO

REC

AST

OF

RO

UN

DW

OO

DO

TH

ER

TH

AN

SA

WLO

GS

INTO

NS:

WESTERN

CA

PE:

2005

-2034

YEA

R

TO

NS

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Soft

woo

d

%Re

duct

ion

for

Fire

san

dO

ther

Fact

ors:

Har

dwoo

ds

TO

NS

Pine

(1.0

0)E.

gran

dis

(1.3

7)O

ther

Euca

lypt

s(1

.16)

Wat

tle(1

.138

)W

attle

Jung

le(1

.138

)To

talW

attle

Tota

lHar

dwoo

dsTo

talF

orec

ast

(Rou

nded

to10

0)

20

05

-06

39

,21

31

29

4,3

48

--

-4

,47

74

.0%

5.3

%4

1,9

00

20

06

-07

24

,12

41

29

3,3

38

--

-3

,46

74

.0%

5.3

%2

6,4

00

20

07

-08

18

,16

51

29

3,4

04

--

-3

,53

34

.0%

5.3

%2

0,8

00

20

08

-09

22

,75

91

29

3,3

45

--

-3

,47

44

.0%

5.3

%2

5,1

00

20

09

-10

27

,57

31

46

3,5

19

--

-3

,66

54

.0%

5.3

%2

9,9

00

An

nu

alA

vera

ge:

2005

-2009

26,3

67

132

3,5

91

--

-3,7

23

4.0

%5.3

%28,8

00

20

10

-11

57

,14

81

46

3,4

04

--

-3

,55

04

.0%

5.3

%5

8,2

00

20

11

-12

18

,92

71

46

3,4

10

--

-3

,55

64

.0%

5.3

%2

1,5

00

20

12

-13

15

,62

51

46

3,4

05

--

-3

,55

14

.0%

5.3

%1

8,4

00

20

13

-14

14

,15

31

46

3,7

47

--

-3

,89

34

.0%

5.3

%1

7,3

00

20

14

-15

15

,87

98

01

,63

6-

--

1,7

16

4.0

%5

.3%

16

,90

0

An

nu

alA

vera

ge:

2010

-2014

24,3

46

133

3,1

20

--

-3,2

53

4.0

%5.3

%26,5

00

20

15

-16

32

,53

58

42

,22

2-

--

2,3

07

4.0

%5

.3%

33

,40

0

20

16

-17

10

,55

68

42

,22

0-

--

2,3

04

4.0

%5

.3%

12

,30

0

20

17

-18

6,1

49

84

2,7

63

--

-2

,84

84

.0%

5.3

%8

,60

0

20

18

-19

5,5

13

17

2,3

02

--

-2

,31

84

.0%

5.3

%7

,50

0

20

19

-20

10

,58

71

01

2,3

05

--

-2

,40

74

.0%

5.3

%1

2,4

00

An

nu

alA

vera

ge:

2015

-2019

13,0

68

74

2,3

63

--

-2,4

37

4.0

%5.3

%14,8

00

20

20

-21

18

,31

11

01

2,3

89

--

-2

,49

14

.0%

5.3

%1

9,9

00

20

21

-22

7,4

69

10

12

,29

6-

--

2,3

97

4.0

%5

.3%

9,4

00

20

22

-23

6,6

43

10

12

,28

8-

--

2,3

90

4.0

%5

.3%

8,6

00

20

23

-24

7,5

99

38

53

7-

--

57

44

.0%

5.3

%7

,80

0

20

24

-25

9,2

46

84

2,2

19

--

-2

,30

44

.0%

5.3

%1

1,1

00

An

nu

alA

vera

ge:

2020

-2024

9,8

54

85

1,9

46

--

-2,0

31

4.0

%5.3

%11,4

00

20

25

-26

10

,46

38

42

,21

5-

--

2,3

00

4.0

%5

.3%

12

,20

0

20

26

-27

4,5

44

84

2,2

20

--

-2

,30

44

.0%

5.3

%6

,50

0

20

27

-28

2,0

47

17

2,2

89

--

-2

,30

64

.0%

5.3

%4

,10

0

20

28

-29

1,8

32

10

12

,30

0-

--

2,4

01

4.0

%5

.3%

4,0

00

20

29

-30

2,5

30

10

12

,28

7-

--

2,3

88

4.0

%5

.3%

4,7

00

An

nu

alA

vera

ge:

2025

-2029

4,2

83

78

2,2

62

--

-2,3

40

4.0

%5.3

%6,3

00

20

30

-31

16

,24

81

01

3,2

39

--

-3

,34

04

.0%

5.3

%1

8,8

00

20

31

-32

3,5

45

10

12

,29

3-

--

2,3

95

4.0

%5

.3%

5,7

00

20

32

-33

3,1

43

38

57

1-

--

60

84

.0%

5.3

%3

,60

0

20

33

-34

2,8

78

84

2,2

28

--

-2

,31

34

.0%

5.3

%5

,00

0

20

34

-35

74

58

42

,33

1-

--

2,4

15

4.0

%5

.3%

3,0

00

An

nu

alA

vera

ge:

2030

-2034

5,3

12

82

2,1

32

--

-2,2

14

4.0

%5.3

%7,2

00

An

nu

alA

vera

ge:

2005

-2034

13,8

72

97

2,5

69

--

-2,6

66

4.0

%5.3

%15,8

00

Logs

incl

uded

are

those

of

pulp

wood

dim

ensi

ons

only

from

each

tim

ber

type

and

there

fore

incl

udes

by-

pro

duct

sfr

om

the

saw

log

pro

duct

ion

opera

tions.

30%

of

Cla

ssa

logs

from

Pin

esa

wtim

ber

com

part

ments

(thin

nin

gs

and

clearf

elli

ngs)

were

ass

um

ed

tobe

pulp

wood.

Pulp

wood

conve

rsio

nra

tios,

m³

toto

ns,

are

giv

en

inbra

ckets

.W

attle

regio

ns

were

base

don

Ext

ract

Fact

ory

or

Colle

ctio

nD

epotlo

cation.

Wattle

Jungle

fore

cast

sare

base

don:

Mpum

ala

nga

South

:2

3,1

00

ha

@3

tons/

ha/a

nnum

,N

ort

hern

KZN

ata

l:6

,00

0ha

@3

tons/

ha/a

nnum

and

East

ern

Cape:

18,0

00

ha

@3

tons/

ha/a

nnum

for

one

rota

tion

and

10,0

00

ha

@5

tons/

ha/a

nnum

there

aft

er.

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

incl

udes

both

Regio

ns’

data

,Zulu

land

(Com

bin

ed)

incl

udes

Maputa

land,Zulu

land

and

Nort

hern

Kw

aZulu

-Nata

lRegio

ns.

Som

esm

ooth

ing

was

applie

dto

Pin

eand

Euca

lyptcl

earf

elli

ng

are

as

inord

er

toeve

noutyi

eld

sre

alis

tica

lly.

Appendix B 9


Appendix C 1

2004 ROUNDWOOD DEMAND OTHER THAN FOR SAWLOGS (‘000 tons - rounded to the closest 1,000 tons)

SOFTWOOD SUBTOTAL

WattleHARDWOOD SUB

TOTALTOTAL

Logs Hard Gum E.grandis

PULP AND PAPER

Sappi Enstra - - - 280 - 280 280

Ngodwana 1,700 1,700 - 50 200 250 1,950

Mandini 800 800 - 220 - 220 1,020

Saiccor - - 190 200 1,750 2,140 2,140

Mondi Richards Bay 431 431 - 1,221 650 1,871 2,302

Merebank 617 617 - - - - 617

Piet Retief - - - - 70 70 70

Sub Total 3,548 3,548 190 1,971 2,670 4,831 8,379

BOARD MILLS

Masonite - - - - 200 200 200

Sonae White River 13 13 - - 80 80 93

Panbult 43 43 - 65 - 65 108

George 8 8 - 332 - 332 340

PG Bison Piet Retief - - - 40 40 80 80

Pietermaritzburg 37 37 - 10 54 64 101

Stellenbosch 18 18 - 10 - 10 28

Boksburg - - - - 60 60 60

Chipboard Industries near Langeni 66 66 - - - - 66

Sub Total 185 185 - 457 434 891 1,076

CHIPPING PLANTS

CTC Richards Bay - - 700 527 1,173 2,400 2,400

Silvacel - - 324 871 720 1,915 1,915

Shincell - - 100 60 460 620 620

NCT Durban - - - - 120 120 120

Sub Total - - 1,124 1,458 2,473 5,055 5,055

MINING TIMBER - - - 200 629 829 829

EXPORTS 260 260 - - 300 300 560

Sub Total 260 260 - 200 929 1,129 1,389

OTHER

POLES 70% Recovery 316 316 - - 446 446 762

CHARCOAL TIMBER - - 369 60 - 429 429


Less

Swaziland 25 25 10 - 100 110 135

Zimbabwe - - 56 - - 56 56

Namibia - - - 80 - 80 80


Waste excluded 688

NOTES: The market as it is estimated to be at present.


January 2005

Appendix C 2

DEMAND FOR WASTE (‘000 tons - rounded to the closest 1,000 tons)

2004 ONWARDS

SOFTWOOD HARDWOODTOTAL

Chips + Waste Waste

PULP AND PAPER

Sappi Enstra - - -

Ngodwana 122 - 122

Mandini 102 - 102

Saiccor - - -

Mondi Richards Bay - - -

Merebank - - -

Piet Retief - - -

Sub Total 224 - 224

BOARD MILLS

Masonite - - -

Sonae White River 17 37 54

Panbult 43 - 43

George 29 5 34

PG Bison Piet Retief 51 30 81

Pietermaritzburg 6 27 33

Stellenbosch 25 - 25

Boksburg 5 60 65

Chipboard Industry - 44 44

Langeni 47 - 47

Sub Total 223 203 426

SILICON SMELTERS - - 27

HEATLOG - - 10

GRAND TOTAL 447 203 688

NOTE: While the overall volume of Gum is accurate the split between Hard Gum and Grandis is interpoloated and is not accurate.


Appendix C 3


SOFTWOOD SUBTOTAL

WattleHARDWOOD SUB

TOTALTOTAL


PULP AND PAPER

Sappi Enstra - - - 280 - 280 280

Ngodwana 1,000 1,000 - 250 700 950 1,950

Mandini 800 800 - 220 - 220 1,020

Saiccor - - 190 200 1,950 2,340 2,340

Mondi Richards Bay 431 431 - 1,421 1,050 2,471 2,902

Merebank 485 485 - - - - 485

Piet Retief - - - - 70 70 70

Sub Total 2,716 2,716 190 2,371 3,770 6,331 9,047

BOARD MILLS

Masonite - - - - 200 200 200


Panbult 43 43 - 65 - 65 108

George 8 8 - - - - 8

PG Bison Piet Retief 100 100 - - - - 100


Stellenbosch 18 18 - 10 - 10 28

Boksburg - - - - 60 60 60


Sub Total 285 285 - 85 394 479 764

CHIPPING PLANTS

CTC Richards Bay - - 700 527 1,173 2,400 2,400

Silvacel - - 324 871 720 1,915 1,915

Shincell - - 100 60 460 620 620

NCT Durban - - - - 350 350 350

Sub Total - - 1,124 1,458 2,703 5,285 5,285

MINING TIMBER - - - 200 579 779 779

EXPORTS - - - - - - -

Sub Total - - - 200 579 779 779

OTHER

POLES 70% Recovery 316 316 - - 446 446 762

CHARCOAL TIMBER - - 400 472 - 872 872


Less

Swaziland 25 25 10 - 100 110 135

Zimbabwe - - 56 - - 56 56

Namibia - - - 80 - 80 80


Waste excluded 688

NOTES:

1. Export of Eucalypt and Pine roundwood terminated.

2. Merebank intake reduced from 617,000 to 485,000 tons Pine.

3. Mondi Richards Bay intake increased by 600,000 tons Eucalypt.

4. SAICCOR increased by 200,000 tons Eucalypt.

5. PG Bison Piet Retief convert to Pine.

6. NCT Durban up to full production.

7. Mining Timber reduced by 50,000 tons per annum.


January 2005

Appendix C 4


SOFTWOOD SUBTOTAL

WattleHARDWOOD SUB

TOTALTOTAL


PULP AND PAPER

Sappi Enstra - 280 280 280

Ngodwana 1,000 1,000 250 700 950 1,950

Mandini 800 800 220 220 1,020

Saiccor - 190 200 1,950 2,340 2,340

Mondi Richards Bay 431 431 1,421 1,050 2,471 2,902

Merebank 485 485 - 485

Piet Retief - 70 70 70

Sub Total 2,716 2,716 190 2,371 3,770 6,331 9,047

BOARD MILLS

Masonite - 200 200 200

Sonae White River 13 13 80 80 93

Panbult 43 43 65 65 108

George 8 8 - 8

PG Bison Piet Retief 100 100 - 100

Pietermaritzburg 37 37 10 54 64 101

Stellenbosch 18 18 10 10 28

Boksburg - 60 60 60

Chipboard Industries near Langeni 66 66 - 66

Sub Total 285 285 - 85 394 479 764

CHIPPING PLANTS

CTC Richards Bay - 700 527 1,173 2,400 2,400

Silvacel - 324 871 720 1,915 1,915

Shincell - 100 60 460 620 620

NCT Durban 350 350 350

Sub Total - - 1,124 1,458 2,703 5,285 5,285

MINING TIMBER - - - 200 529 729 729

EXPORTS - - - - - - -

Sub Total - - - 200 529 729 729

OTHER

POLES 70% Recovery 316 316 - - 446 446 762

CHARCOAL TIMBER - - 400 472 - 872 872


Less

Swaziland 25 25 10 - 100 110 135

Zimbabwe - - 56 - - 56 56

Namibia - - - 80 - 80 80


Waste excluded 688

NOTES:1. Mining Timber reduced by 50,000 tons per annum.


Appendix C 5


SOFTWOOD SUBTOTAL

WattleHARDWOOD SUB

TOTALTOTAL


PULP AND PAPER

Sappi Enstra - - - 280 - 280 280

Ngodwana 1,000 1,000 - 250 700 950 1,950

Mandini 800 800 - 220 - 220 1,020

Saiccor - - 190 200 1,950 2,340 2,340


Merebank 485 485 - - - - 485

Piet Retief - - - - 70 70 70

Sub Total 2,716 2,716 190 2,371 3,770 6,331 9,047

BOARD MILLS

Masonite - - - - 200 200 200


Panbult 43 43 - 65 - 65 108

George 8 8 - - - - 8

PG Bison Piet Retief 20 20 - 40 40 80 100


Stellenbosch 18 18 - 10 10 28

Boksburg - - - - 60 60 60


Umtata 50 50 - - - - 50

Sub Total 255 255 - 125 434 559 814

CHIPPING PLANTS

CTC Richards Bay - - 700 527 1,173 2,400 2,400

Silvacel - - 324 871 720 1,915 1,915

Shincell - - 100 60 460 620 620

NCT Durban - - 120 120 120

Sub Total - - 1,124 1,458 2,473 5,055 5,055

MINING TIMBER - - - 200 479 679 679

EXPORTS - - - - - -

Sub Total - - - 200 479 679 679

OTHER

POLES 70% Recovery 316 316 - - 446 446 762

CHARCOAL TIMBER - - 400 472 - 872 872


Less

Swaziland 25 25 10 - 100 110 135

Zimbabwe - - 56 - - 56 56

Namibia - - - 80 - 80 80


Waste excluded 688

NOTES:CHANGES FROM 20061. New Particle Board plant at Umtata 50,000 tons.2. PG Bison Piet Retief convert to Pine.3. Mining Timber reduced by 50,000 tons per annum.


January 2005

Appendix C 6


SOFTWOOD SUBTOTAL

WattleHARDWOOD SUB

TOTALTOTAL


PULP AND PAPER

Sappi Enstra - - - 280 - 280 280

Ngodwana 1,000 1,000 - 250 700 950 1,950

Mandini 800 800 - 220 - 220 1,020

Saiccor - 190 200 1,950 2,340 2,340


Merebank 485 485 - - - - 485

Piet Retief - - - - 70 70 70

NCT Richards Bay - - - - 200 200 200

Sub Total 2,716 2,716 190 2,371 3,970 6,531 9,247

BOARD MILLS

Masonite - - - - 200 200 200


Panbult 43 43 - 65 - 65 108

George 8 8 - - - - 8



Stellenbosch 18 18 - 10 - 10 28

Boksburg - - - - 60 60 60


Umtata 50 50 - - - - 50

Sub Total 235 235 - 125 434 559 794

CHIPPING PLANTS

CTC Richards Bay - - 700 527 1,173 2,400 2,400

Silvacel - - 324 871 720 1,915 1,915

Shincell - - 100 60 460 620 620

NCT Durban - - - - 350 350 350

Sub Total - - 1,124 1,458 2,703 5,285 5,285

MINING TIMBER - - - 200 429 629 629

EXPORTS - - - - - - -

Sub Total - - - 200 429 629 629

OTHER

POLES 70% Recovery 316 316 - - 446 446 762

CHARCOAL TIMBER - - 400 472 - 872 872


Less

Swaziland 25 25 10 - 100 110 135

Zimbabwe - - 56 - - 56 56

Namibia - - - 80 - 80 80


Waste excluded 688

NOTES:CHANGES FROM 20071. First phase of production NCT/Sodra pulpmill - international pulp company.2. Mining Timber reduced by 50,000 tons per annum.


Appendix C 7


SOFTWOOD SUBTOTAL

WattleHARDWOOD SUB

TOTALTOTAL


PULP AND PAPER

Sappi Enstra - - - 280 - 280 280

Ngodwana 1,000 1,000 - 250 700 950 1,950

Mandini 800 800 - 220 - 220 1,020

Saiccor - - 190 200 1,950 2,340 2,340


Merebank 485 485 - - - - 485

Piet Retief - - - - 70 70 70

NCT Richards Bay - - - - 450 450 450

Sub Total 2,716 2,716 190 2,371 4,220 6,781 9,497

BOARD MILLS

Masonite - - - - 200 200 200


Panbult 43 43 - 65 - 65 108

George 8 8 - - - - 8



Stellenbosch 18 18 - 10 - 10 28

Boksburg - - - - 60 60 60


Umtata 50 50 - - - - 50

Sub Total 235 235 - 125 434 559 794

CHIPPING PLANTS

CTC Richards Bay - - 700 527 1,173 2,400 2,400

Silvacel - - 324 871 720 1,915 1,915

Shincell - - 100 60 460 620 620

NCT Durban - - - - 120 120 120

Sub Total - - 1,124 1,458 2,473 5,055 5,055

MINING TIMBER - - - 200 400 600 600

EXPORTS - - - - - - -

Sub Total - - - 200 400 600 600

OTHER

POLES 70% Recovery 316 316 - - 446 446 762

CHARCOAL TIMBER - - 375 393 - 768 768


Less

Swaziland 25 25 10 - 100 110 135

Zimbabwe - - 56 - - 56 56

Namibia - - - 80 - 80 80


Waste excluded 688

NOTES:CHANGES FROM 20081. NCT/Sodra pulpmill up to full production.2. Mining Timber reduced to the expected sustainable level of 600,000 tons.


January 2005

Appendix D 1

AREAS USED IN THE STUDY IN HECTARES BY GENUS AND AGE CLASS IN FIVE YEAR AGE GROUPINGS ON 01/06/2002*:

LIMPOPO REGION

Age in Years Pine E.grandisOther Eucalyptus

SpeciesWattle * As on30/06/2003

TOTAL

Temporarily Unplanted 680 777 227 - 1,684

0 - 4 5,785 7,978 6,133 - 19,897

5 - 9 7,771 9,071 7,208 - 24,050

10 - 14 3,914 3,286 2,070 - 9,270

15 - 19 3,557 832 249 - 4,638

20 - 24 2,487 404 247 - 3,138

25 - 29 1,272 170 51 - 1,494

30 + 1,642 18 32 - 1,693

Wattle Jungle - - - - -

TOTALS 27,108 22,537 16,219 - 65,863

SOURCE: Report on Commercial Timber Resources and Primary Roundwood Processing in South Africa 2001/2002.

Areas Excluded: Jungle (except the Wattle Jungle areas which were estimated), and Pine grown for “Other Products” in the Southern and Western Cape Regions.

Wattle regions were based on Extract Factory or Collection Depot location.

* Wattle as on 30/06/2003.


Appendix D 2


MPUMALANGA NORTH REGION



TOTAL

Temporarily Unplanted 4,664 2,533 505 - 7,702

0 - 4 32,006 18,932 9,494 - 60,432

5 - 9 41,337 21,993 5,199 - 68,530

10 - 14 30,598 10,446 1,890 - 42,935

15 - 19 27,164 4,106 168 - 31,437

20 - 24 17,221 448 87 - 17,756

25 - 29 10,216 359 32 - 10,607

30 + 3,162 269 178 - 3,609


TOTALS 166,368 59,086 17,553 - 243,007




* Wattle as on 30/06/2003.


January 2005

Appendix D 3


MPUMALANGA SOUTH/CENTRAL DISTRICTS REGION



TOTAL

Temporarily Unplanted 8,612 1,001 4,331 1,525 15,469

0 - 4 42,606 15,504 44,464 8,242 110,817

5 - 9 37,769 11,728 30,914 6,108 86,519

10 - 14 28,693 1,561 11,141 1,782 43,177

15 - 19 20,803 216 876 399 22,294

20 - 24 13,399 7 140 - 13,545

25 - 29 5,741 - 47 - 5,788

30 + 924 13 5 - 943

Wattle Jungle - - - 23,100 23,100

TOTALS 158,547 30,030 91,917 41,156 321,650




* Wattle as on 30/06/2003.


Appendix D 4


MAPUTALAND/ZULULAND/NORTHERN KWAZULU-NATAL REGION



TOTAL

Temporarily Unplanted 4,475 2,642 607 3,724 11,449

0 - 4 8,145 41,499 23,853 17,362 90,859

5 - 9 11,598 41,364 22,364 15,088 90,413

10 - 14 12,525 6,904 1,518 2,762 23,709

15 - 19 8,353 951 7 129 9,439

20 - 24 1,891 25 - - 1,916

25 - 29 1,707 6 6 - 1,719

30 + 1,351 563 38 - 1,952

Wattle Jungle - - - 6,000 6,000

TOTALS 50,045 93,953 48,393 45,065 237,456




* Wattle as on 30/06/2003.


January 2005

Appendix D 5


KWAZULU-NATAL MIDLANDS REGION



TOTAL

Temporarily Unplanted 2,027 1,492 733 4,553 8,805

0 - 4 15,094 18,736 14,524 27,949 76,303

5 - 9 13,660 17,110 10,943 29,565 71,278

10 - 14 20,121 4,503 2,765 4,157 31,546

15 - 19 8,076 1,753 356 541 10,726

20 - 24 3,820 295 15 - 4,130

25 - 29 893 213 3 - 1,109

30 + 584 187 21 - 791


TOTALS 64,274 44,289 29,360 66,765 204,688




* Wattle as on 30/06/2003.


Appendix D 6


SOUTHERN KWAZULU-NATAL REGION



TOTAL

Temporarily Unplanted 1,798 894 397 276 3,364

0 - 4 12,765 11,392 8,853 1,689 34,699

5 - 9 12,029 13,187 9,045 1,703 35,964

10 - 14 13,145 7,572 823 481 22,021

15 - 19 4,951 363 18 14 5,346

20 - 24 2,370 212 2 - 2,584

25 - 29 2,433 82 2 - 2,517

30 + 851 416 91 - 1,358


TOTALS 50,342 34,118 19,231 4,163 107,853




* Wattle as on 30/06/2003.


January 2005

Appendix D 7


EASTERN CAPE REGION



TOTAL

Temporarily Unplanted 14,571 865 108 - 15,544

0 - 4 23,354 5,379 1,586 - 30,319

5 - 9 23,278 4,360 867 - 28,505

10 - 14 22,364 696 1,088 - 24,148

15 - 19 7,216 143 270 - 7,629

20 - 24 7,218 16 30 - 7,264

25 - 29 5,481 54 11 - 5,546

30 + 5,260 44 217 - 5,521

Wattle Jungle - - - 18,000 18,000

TOTALS 108,740 11,558 4,177 18,000 142,476




* Wattle as on 30/06/2003.


Appendix D 8


SOUTHERN CAPE REGION



TOTAL

Temporarily Unplanted 7,024 5 - - 7,029

0 - 4 10,066 - 9 - 10,074

5 - 9 9,637 - 29 - 9,666

10 - 14 8,191 - 140 - 8,330

15 - 19 5,319 - 214 - 5,533

20 - 24 5,108 - 71 - 5,180

25 - 29 5,368 12 134 - 5,513

30 + 8,137 2 927 - 9,066


TOTALS 58,849 19 1,523 - 60,392




* Wattle as on 30/06/2003.


January 2005

Appendix D 9


WESTERN CAPE REGION



TOTAL

Temporarily Unplanted 1,403 - - - 1,403

0 - 4 1,748 1 - - 1,749

5 - 9 3,176 - 18 - 3,193

10 - 14 2,602 4 - - 2,606

15 - 19 1,493 - 8 - 1,500

20 - 24 1,534 - 8 - 1,542

25 - 29 932 - - - 932

30 + 2,772 5 151 - 2,928


TOTALS 15,660 10 184 - 15,854




* Wattle as on 30/06/2003.


Appendix E 1

VOLUME : MASS AND MASS : VOLUME CONVERSION RATIOS

Industrial Roundwood TypeRatios Used in this Study Historically Accepted Ratios

m³ per ton tons per m³ Notes m³ per ton tons per m³ Notes

Softwood: Sawlogs 0.94 1.06 0.94 1.06

Pulpwood 1.00 1.00 1.00 1.00

Poles@ 1.00 1.00 1.00 1.00

Other Products@ 1.00 1.00 1.00 1.00

E.grandis: Sawlogs 0.94 1.06 3 weeks air dry 0.94 1.06 6 weeks air dry

Pulpwood 1.37 0.73 3 weeks air dry 1.47 0.68 6 weeks air dry

Mining Timber@ 1.37 0.73 3 weeks air dry 1.47 0.68 6 weeks air dry

Poles@ 1.37 0.73 3 weeks air dry 1.47 0.68 6 weeks air dry

Other Products@ 1.37 0.73 3 weeks air dry 1.47 0.68 6 weeks air dry

Other Eucalypts: Sawlogs 0.78 1.28 3 weeks air dry 0.78 1.28 6 weeks air dry

Pulpwood 1.16 0.86 3 weeks air dry 1.25 0.80 6 weeks air dry




Wattle: Pulpwood 1.138 0.879 6 weeks air dry 1.138 0.879 6 weeks air dry




@ assumed for the purposes of this study.


January 2005

Appendix F 1

REGION

SUMMARY OF STUDY DETAILS

Area Excluded:Jungle:

(All Timber Typesexcept Wattle)

Total AreaIncluded in Study

(includingadditional Wattle

Jungle Areas)

Total Area perRegion (includingadditional Wattle

Jungle Areas)

% of the TotalArea Includedin the Study

Limpopo 58 65,864 66,807 98.6%

Mpumalanga North 412 243,007 243,669 99.7%

Central Districts 61 19,310 19,387 99.6%

Mpumalanga South 110 302,340 304,934 99.1%

Totals/Wtd. Averages: Central Districts/ Mpumalanga South 171 321,650 324,321 99.2%

Maputaland - 19,320 19,336 99.9%

Zululand 30 118,054 119,636 98.7%

Northern KwaZulu-Natal 168 99,979 100,458 99.5%

Totals/Wtd. Averages: Maputaland/Zululand/ NorthernKwaZulu-Natal 198 237,353 239,430 99.1%

KwaZulu-Natal Midlands 66 204,790 205,910 99.5%

Southern KwaZulu-Natal 35 107,855 108,143 99.7%

Eastern Cape 449 142,477 143,434 99.3%

Southern Cape 77 60,392 63,802 94.7%

Western Cape 619 15,854 18,543 85.5%

Total and weighted averages 2,086 1,399,242 1,414,059 99.0%

NOTES:

Source(Unless otherwise stated): Report on Commercial Timber Resourcesand Primary Roundwood Processing in South Africa: 2001/2002.

Areas in shaded columns were excluded.

N/A: Not Applicable

Wattle areas (except jungle areas) were obtained from industry sourcesand inserted on a pro rata basis based on Commercial Timber Resourceareas.

The Wattle jungle area of 47,100 hectares is an estimate and was notobtained from the Report on Commercial Timber Resources and PrimaryRoundwood Processing in South Africa: 2001/2002.

Mean annual increment figures for Pine sawlog and Eucalyptus sawlogareas were calculated using the pulpwood conversion ratios as theproduct to be removed from the yields will be pulpwood and not sawlogs.

SUMMARY: ALL AREAS EXCEPT SAWLOG AND WATTLE JUNGLE AREAS:

Timber Type: Softwood E.grandisOther

EucalyptsWattle

%: 25.8% 32.6% 26.6% 15.0%

Area: (ha) 220,379 279,096 227,489 128,049

MAI:(t/ha/yr) 14.612 17.966 19.568 8.066

MAI:(m³/ha/yr) 14.612 24.614 22.698 9.179

Total Area: 855,013 Total MAI: t/ha/yr 16.045

Total MAI: m³/ha/yr 19.215


REG

ION

AREA

SM

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AN

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BY

PRO

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on

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Reso

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es

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ing

inSouth

Afr

ica:

20

01

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02

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Are

as

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aded

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were

exc

luded.

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are

as

(exc

eptju

ngle

are

as)

were

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ined

from

indust

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ined

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the

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on

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ialTim

ber

Reso

urc

es

and

Pri

mary

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ood

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cess

ing

inSouth

Afr

ica:

2001/2

00

2.

Mean

annualin

crem

entfigure

sfo

rPin

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gand

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lyptu

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as

were

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ng

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as

the

pro

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om

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³/ha/y

r)1

4.6

12

14

.79

0

Appendix F 2


January 2005

REG

ION

AREA

SM

AIs

AN

DRO

TA

TIO

NA

GES

USED

INTH

ESTU

DY

BY

PRO

DU

CT

TYPE

E.G

RA

ND

IS

Saw

log

Pu

lpw

ood

Min

ing

Tim

ber

Pole

sO

ther

Pu

rpose

s

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

hect

ares

tons

year

she

ctar

esto

nsye

ars

hect

ares

tons

year

she

ctar

esto

nsye

ars

hect

ares

tons

year

s

Lim

popo

7,7

22

25

.52

52

,97

31

9.4

97

,70

31

9.4

93

,20

81

9.4

99

31

19

.49

Mpum

ala

nga

Nort

h8

,26

92

5.5

25

20

,86

82

1.8

92

9,0

84

21

.89

81

12

1.8

91

31

21

.89

Centr

alD

istr

icts

-8

.02

51

,23

29

.49

-9

.49

-9

.49

-9

.49

Mpum

ala

nga

South

11

41

3.5

25

24

,77

21

5.9

93

,79

61

5.9

91

15

15

.99

81

5.9

9

Tota

ls/W

td.A

vera

ges:

Central

Dis

tric

ts/M

pum

ala

nga

South

11

41

3.5

25

26

,00

41

5.6

93

,79

61

5.9

91

15

15

.99

81

5.9

9

Maputa

land

--

25

8,4

21

12

.99

-1

2.9

9-

12

.99

71

2.9

9

Zulu

land

48

02

1.9

25

64

,13

92

1.0

9-

21

.09

-2

1.0

95

21

.09

Nort

hern

Kw

aZulu

-Nata

l11

13.5

25

20,0

92

15.9

9716

15.9

96

915.9

94

315.9

9

Tota

ls/W

td.A

vera

ges:

Maputa

land/Z

ulu

land/

Northern

Kw

aZulu

-Nata

l

49

12

1.7

25

92

,65

21

9.2

97

16

15

.99

69

15

.99

55

16

.01

0

Kw

aZulu

-Nata

lM

idla

nds

105

14.3

25

43,2

98

16.9

9286

16.9

9640

16.9

91

16.9

9

South

ern

Kw

aZulu

-Nata

l7

51

2.5

25

33

,27

11

4.8

91

38

14

.89

64

71

4.8

97

14

.89

East

ern

Cape

48

.02

59

31

9.4

91

88

9.4

91

0,3

87

9.4

91

49

9.4

9

South

ern

Cape

-2

51

49

.49

59

.49

-9

.49

-9

.49

West

ern

Cape

-2

5-

9.4

9-

9.4

95

9.4

95

9.4

9

Tota

land

weig

hte

dave

rages

16

,78

02

5.2

22

0,0

11

17

.84

1,9

16

20

.61

5,8

82

12

.71

,28

71

8.2

m³/

ha/y

r:2

3.6

65

(X0

.94

)2

4.4

42

(X1

.37

)2

8.2

57

(X1

.37

)1

7.3

52

(X1

.37

)2

4.9

71

(X1

.37

)

NO

TES:

Sourc

e(U

nle

ssoth

erw

ise

state

d):

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

20

01

/20

02

.

Are

as

insh

aded

colu

mns

were

exc

luded.

N/A

:N

otA

pplic

able

Wattle

are

as

(exc

eptju

ngle

are

as)

were

obta

ined

from

indust

ryso

urc

es

and

inse

rted

on

apro

rata

basi

sbase

don

Com

merc

ialTim

ber

Reso

urc

eare

as.

The

Wattle

jungle

are

aof4

7,1

00

hect

are

sis

an

est

imate

and

was

notobta

ined

from

the

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

2001/2

00

2.

Mean

annualin

crem

entfigure

sfo

rPin

esa

wlo

gand

Euca

lyptu

ssa

wlo

gare

as

were

calc

ula

ted

usi

ng

the

pulp

wood

conve

rsio

nra

tios

as

the

pro

duct

tobe

rem

ove

dfr

om

the

yield

sw

illbe

pulp

wood

and

notsa

wlo

gs

SU

MM

ARY:

E.G

RA

ND

IS:

SU

MM

ARY:

EU

CA

LYPTU

SSA

WLO

GA

REA

S:

Su

bd

ivis

ion

:A

llTim

ber

Su

bd

ivis

ion

:E.g

ran

dis

E.d

iv.

Tota

l

%1

00

%%

Are

a:

(ha)

29

5,8

76

Are

a:

(ha)

16

,78

09

07

17

,68

7

MA

I:(t/h

a/y

r)1

8.3

75

MA

I:(t/h

a/y

r)2

5.2

12

.92

4.5

5

MA

I:(m

³/ha/y

r)2

4.5

60

MA

I:(m

³/ha/y

r)2

3.6

65

10

.06

2

Appendix F 3


REG

ION

AREA

SM

AIs

AN

DRO

TA

TIO

NA

GES

USED

INTH

ESTU

DY

BY

PRO

DU

CT

TYPE

OTH

ER

EU

CA

LYPTU

SSPEC

IES

Saw

log

***

E.d

ivers

icolo

rSaw

log

Pu

lpw

ood

Min

ing

Tim

ber

Pole

sO

ther

Pu

rpose

s

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

hect

ares

tons

year

she

ctar

esto

nsye

ars

hect

ares

tons

year

she

ctar

esto

nsye

ars

hect

ares

tons

year

she

ctar

esto

nsye

ars

Lim

popo

17

--

--

-1

0,2

87

15

.79

3,4

91

15

.79

1,9

38

15

.79

48

61

5.7

9

Mpum

ala

nga

Nort

h2

79

--

--

-1

5,0

77

20

.19

1,8

30

20

.19

30

62

0.1

91

21

20

.19

Centr

alD

istr

icts

--

--

--

1,0

63

8.3

99

99

8.3

9-

8.3

9-

8.3

9

Mpum

ala

nga

South

21

7-

--

--

87

,01

92

1.2

91

,63

42

1.2

9-

21

.29

1,1

15

21

.29

Tota

ls/W

td.A

vera

ges:

CentralD

istr

icts

/M

pum

ala

nga

South

21

7-

--

--

88

,08

22

1.1

92

,63

31

6.3

9-

0.0

91

,11

52

1.2

9

Maputa

land

--

--

--

62

28

.39

-8

.39

-8

.39

38

.39

Zulu

land

--

--

--

26

,52

32

1.0

9-

21

.09

-2

1.0

9-

21

.09

Nort

hern

Kw

aZulu

-Nata

l-

--

--

-2

0,9

54

17

.89

67

17

.89

24

01

7.8

9-

17

.89

Tota

ls/W

td.A

vera

ges

:M

aputa

land/Z

ulu

land/

Norther

nKw

aZulu

-Nata

l

--

--

--

48

,09

91

9.5

96

71

7.8

92

40

17

.89

38

.39

Kw

aZulu

-Nata

lM

idla

nds

19

0-

--

--

28

,97

61

8.9

92

89

18

.99

51

8.9

9-

18

.99

South

ern

Kw

aZulu

-Nata

l8

7-

--

--

18

,94

41

7.7

96

01

7.7

91

56

17

.79

-1

7.7

9

East

ern

Cape

70

--

--

-1

,46

91

7.7

93

01

7.7

92

,61

81

7.7

91

65

17

.79

South

ern

Cape

--

-8

79

12

.92

56

39

17

.79

-1

7.7

9-

17

.79

51

7.7

9

West

ern

Cape

--

-2

81

2.9

25

51

5.9

9-

15

.99

24

15

.99

32

91

5.9

9

Tota

land

weig

hte

dave

rages

86

00

.09

07

12

.92

11

,57

81

9.7

8,4

00

17

.05

,28

71

7.1

2,2

24

18

.9

m³/

ha/y

r:0

.00

0(X

0.9

4)

10

.06

2(X

0.7

8)

22

.89

7(X

1.1

6)

19

.70

6(X

1.1

6)

19

.83

6(X

1.1

6)

21

.91

3(X

1.1

6)

NO

TES:

Sourc

e(U

nle

ssoth

erw

ise

state

d):

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

20

01

/20

02

.

Are

as

insh

aded

colu

mns

were

exc

luded.

N/A

:N

otA

pplic

able

Wattle

are

as

(exc

eptju

ngle

are

as)

were

obta

ined

from

indust

ryso

urc

es

and

inse

rted

on

apro

rata

basi

sbase

don

Com

merc

ialTim

ber

Reso

urc

eare

as.

The

Wattle

jungle

are

aof4

7,1

00

hect

are

sis

an

est

imate

and

was

notobta

ined

from

the

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

2001/2

00

2.

Mean

annualin

crem

entfigure

sfo

rPin

esa

wlo

gand

Euca

lyptu

ssa

wlo

gare

as

were

calc

ula

ted

usi

ng

the

pulp

wood

conve

rsio

nra

tios

as

the

pro

duct

tobe

rem

ove

dfr

om

the

yield

sw

illbe

pulp

wood

and

notsa

wlo

gs

SU

MM

ARY:

EU

CA

LYPTU

SA

REA

S:

INC

LUD

ING

SA

WLO

GS:

SU

MM

ARY:

EU

CA

LYPTU

SA

REA

S:

EXC

LUD

ING

SA

WLO

GS:

Su

bd

ivis

ion

:E.g

ran

dis

Oth

er

Eu

caly

pts

Tota

lSu

bd

ivis

ion

:E.g

ran

dis

Oth

er

Eu

caly

pts

Tota

l

%5

6.4

%4

3.6

%1

00

%%

55

.1%

44

.9%

10

0%

Are

a:

(ha)

29

5,8

76

22

8,3

96

52

4,2

72

Are

a:

(ha)

27

9,0

96

22

7,4

89

50

6,5

85

MA

I:(t/h

a/y

r)1

8.3

75

19

.54

11

8.8

83

MA

I:(t/h

a/y

r)1

7.9

66

19

.56

81

8.6

85

MA

I:(m

³/ha/y

r)2

4.5

60

22

.64

82

3.7

27

MA

I:(m

³/ha/y

r)2

4.6

12

2.6

98

23

.75

4

Saw

logs*

**exc

luded

from

sum

mary

.

Appendix F 4


January 2005

REG

ION

AREA

SM

AIs

AN

DRO

TA

TIO

NA

GES

USED

INTH

ESTU

DY

BY

PRO

DU

CT

TYPE

WA

TTLE

Pu

lpw

ood

Min

ing

Tim

ber

Pole

sO

ther

Pu

rpose

s

Jun

gle

(Are

as

Est

imate

d.N

ot

from

Rep

ort

on

Com

merc

ialTim

ber

Reso

urc

es

an

dPri

mary

Rou

nd

wood

Pro

cess

ing

inSou

thA

fric

a:

2001/2

002.)

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

Area

Aver

age

Mea

nAn

nual

Incr

emen

tat

Clea

rfel

ling

Age

(Ton

s/ha

/yea

r)

Rota

tion

Appl

ied

hect

ares

tons

year

she

ctar

esto

nsye

ars

hect

ares

tons

year

she

ctar

esto

nsye

ars

hect

ares

tons

year

s

Lim

popo

-6

.01

0-

6.0

10

-6

.01

0-

6.0

10

-1

0

Mpum

ala

nga

Nort

h-

6.0

10

-6

.01

0-

6.0

10

-6

.01

0-

10

Centr

alD

istr

icts

-6

.01

0-

6.0

10

-6

.01

0-

6.0

10

-1

0

Mpum

ala

nga

South

17

,41

58

.11

05

40

8.1

10

-8

.11

01

01

8.1

10

23

,10

03

.01

0

Tota

ls/W

td.

Ave

rages:

Centr

alD

istr

icts

/M

pum

ala

nga

South

17

,41

58

.11

05

40

8.1

10

-0

.01

01

01

8.1

10

23

,10

03

.01

0

Maputa

land

-N

/A1

0-

N/A

10

-N

/A1

0-

N/A

10

10

Zulu

land

4,1

95

7.4

10

-7

.41

01

36

7.4

10

-7

.41

01

0

Nort

hern

Kw

aZulu

-Nata

l33,5

96

7.7

10

387

7.7

10

339

7.7

10

413

7.7

10

6,0

00

3.0

10

Tota

ls/W

td.A

vera

ges:

Maputa

land/Z

ulu

land/

Nort

hern

Kw

aZulu

-Nata

l

37

,79

17

.71

03

87

7.7

10

47

57

.61

04

13

7.7

10

6,0

00

3.0

10

Kw

aZulu

-Nata

lM

idla

nds

62,9

91

8.3

10

159

8.3

10

3,5

36

8.3

10

78

8.3

10

10

South

ern

Kw

aZulu

-Nata

l4

,10

77

.91

04

97

.91

0-

7.9

10

77

.91

01

0

East

ern

Cape

-5

.01

0-

5.0

10

-5

.01

0-

5.0

10

18

,00

03

.01

0

South

ern

Cape

-N

/A1

0-

N/A

10

-N

/A1

0-

N/A

10

10

West

ern

Cape

-N

/A1

0-

N/A

10

-N

/A1

0-

N/A

10

10

Tota

land

weig

hte

dave

rages

12

2,3

04

8.1

1,1

35

8.0

4,0

11

8.2

59

97

.84

7,1

00

3.0

m³/

ha/y

r:9

.17

5(X

1.1

38

)9

.08

5(X

1.1

38

)9

.35

3(X

1.1

38

)8

.93

1(X

1.1

38

)3

.41

4(X

1.1

38

)

NO

TES:

Sourc

e(U

nle

ssoth

erw

ise

state

d):

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

20

01

/20

02

.

Are

as

insh

aded

colu

mns

were

exc

luded.

N/A

:N

otA

pplic

able

Wattle

are

as

(exc

eptju

ngle

are

as)

were

obta

ined

from

indust

ryso

urc

es

and

inse

rted

on

apro

rata

basi

sbase

don

Com

merc

ialTim

ber

Reso

urc

eare

as.

The

Wattle

jungle

are

aof4

7,1

00

hect

are

sis

an

est

imate

and

was

notobta

ined

from

the

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

2001/2

00

2.

Mean

annualin

crem

entfigure

sfo

rPin

esa

wlo

gand

Euca

lyptu

ssa

wlo

gare

as

were

calc

ula

ted

usi

ng

the

pulp

wood

conve

rsio

nra

tios

as

the

pro

duct

tobe

rem

ove

dfr

om

the

yield

sw

illbe

pulp

wood

and

notsa

wlo

gs.

SU

MM

ARY:

WA

TTLE

S:

Su

bd

ivis

ion

:Exc

l.Ju

ng

leIn

cl.Ju

ng

le

%7

3%

10

0%

Are

a:

(ha)

12

8,0

49

17

5,1

49

MA

I:(t/h

a/y

r)8

.06

66

.70

3

MA

I:(m

³/ha/y

r)9

.17

97

.62

8

Appendix F 5


REG

ION

SU

MM

ARY

OF

AREA

SIN

HEC

TA

RES

Tota

ls:

Soft

woo

dTo

tals

:E.

gran

dis

Tota

ls:

Oth

erEu

caly

ptus

Spec

ies

Tota

ls:

Wat

tle

Tota

ls:

Oth

erH

ardw

ood

Spec

ies

Regi

onTo

tals

Estim

ated

Wat

tleJu

ngle

Area

s

Regi

onTo

tals

with

Wat

tleJu

ngle

Area

sAd

ded

Jung

leAr

eas

Soft

woo

d

Jung

leAr

eas

E.gr

andi

s

Jung

leAr

eas

Oth

erEu

caly

ptus

Spec

ies

Ori

gina

lJu

ngle

Area

sW

attle

Area

sEx

clud

edSo

ftw

ood

Area

sEx

clud

edO

ther

Har

dwoo

dSp

ecie

s

Tota

lof

Area

sEx

clud

ed

Area

sU

sed

inSt

udy

Lim

popo

27

,16

62

2,5

37

16

,21

9-

88

56

6,8

07

-6

6,8

07

58

--

--

88

59

43

65

,86

4

Mpum

ala

nga

Nort

h1

66

,64

359

,16

31

7,6

13

-2

50

24

3,6

69

-2

43

,66

92

75

78

59

--

25

06

62

24

3,0

07

Centr

alD

istr

icts

16

,07

71

,23

22

,06

2-

16

19

,38

7-

19

,38

7-

-6

1-

-1

67

71

9,3

10

Mpum

ala

nga

South

14

2,5

04

28

,80

58

9,9

85

18

,05

62

,48

42

81

,83

42

3,1

00

30

4,9

34

34

67

0-

-2

,48

42

,59

43

02

,34

0

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

15

8,5

81

30

,03

79

2,0

47

18

,05

62

,50

03

01

,22

12

3,1

00

32

4,3

21

34

61

31

--

2,5

00

2,6

71

32

1,6

50

Maputa

land

10

,26

78

,42

86

25

-1

61

9,3

36

-1

9,3

36

--

--

-1

61

61

9,3

20

Zulu

land

22

,60

664

,62

42

6,5

23

4,3

31

1,5

52

11

9,6

36

-1

19

,63

6-

30

--

-1

,55

21

,58

21

18

,05

4

Nort

hern

Kw

azu

lu-N

ata

l1

7,2

21

20

,93

12

1,2

61

34

,73

53

10

94

,45

86

,00

01

00

,45

82

74

11

00

--

31

04

78

99

,98

0

Maputa

land/Z

ulu

land/

Northern

Kw

aZulu

-Nata

l(C

om

bin

ed)

50

,09

493

,98

34

8,4

09

39

,06

61

,87

82

33

,43

06

,00

02

39

,43

02

77

11

00

--

1,8

78

2,0

76

23

7,3

54

Kw

aZulu

-Nata

lM

idla

nds

64

,30

144

,33

02

9,4

60

66

,76

41

,05

52

05

,91

0-

20

5,9

10

50

11

5-

-1

,05

51

,12

12

04

,79

0

South

ern

Kw

aZulu

-Nata

l5

0,3

42

34

,13

81

9,2

47

4,1

63

25

31

08

,14

3-

10

8,1

43

-2

01

5-

-2

53

28

81

07

,85

5

East

ern

Cape

10

8,9

15

11

,65

94

,35

2-

50

81

25

,43

41

8,0

00

14

3,4

34

17

41

00

17

5-

-5

08

95

71

42

,47

7

South

ern

Cape

61

,30

81

91

,52

3-

95

26

3,8

02

-6

3,8

02

77

--

-2

,38

19

52

3,4

10

60

,39

2

West

ern

Cape

17

,86

71

03

86

-2

80

18

,54

3-

18

,54

34

18

-2

01

-1

,79

02

80

2,6

89

15

,85

4

Tota

l705,2

17

295,8

76

229,2

56

128,0

49

8,5

61

1,3

66,9

59

47,1

00

1,4

14,0

59

1,1

13

276

697

-4,1

71

8,5

61

14,8

17

1,3

99,2

42

Perc

enta

ges:

49

.9%

20

.9%

16

.2%

9.1

%0

.6%

96

.7%

3.3

%1

00

.0%

0.1

%0

.0%

0.0

%0

.0%

0.3

%0

.6%

1.0

%9

9.0

%

Perc

enta

ge

ofEuca

lypts

Com

bin

ed:

38

.4%

NO

TES:

SO

URC

E:

(unle

ssoth

erw

ise

state

d):

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica

20

01

/20

02

.

Are

as

insh

aded

colu

mns

were

exc

luded.

Wattle

are

as

(exc

eptju

ngle

are

as)

were

obta

ined

from

indust

ryso

urc

es

and

inse

rted

on

apro

rata

basi

sbase

don

Com

merc

ialTim

ber

Reso

urc

eare

as.

Wattle

jungle

are

as

were

est

imate

dand

the

are

as

added

toth

egra

nd

tota

l.

Appendix G 1


January 2005

REG

ION

AREA

AC

CO

RD

ING

TO

TH

EM

AIN

PU

RPO

SE

FO

RW

HIC

HTREES

ARE

GRO

WN

SA

WTIM

BER

PU

LPW

OO

D

Saw

logs

:So

ftw

ood

Saw

logs

:E.

gran

dis

Saw

logs

:O

ther

Euca

lypt

usSp

ecie

s

Saw

logs

:W

attle

Saw

logs

:O

ther

Har

dwoo

dSp

ecie

s

Tota

ls:

Saw

logs

Pulp

woo

d:So

ftw

ood

Pulp

woo

d:E.

gran

dis

Pulp

woo

d:O

ther

Euca

lypt

usSp

ecie

s

Pulp

woo

d:W

attle

Pulp

woo

d:O

ther

Har

dwoo

dSp

ecie

s

Tota

ls:

Pulp

woo

d

Lim

popo

26

,17

97

,72

21

7-

10

93

4,0

27

95

22

,97

31

0,2

87

-4

14

,21

6

Mpum

ala

nga

Nort

h1

35

,89

98

,26

92

79

-5

14

4,4

52

30

,74

42

0,8

68

15

,07

7-

13

66

6,8

25

Centr

alD

istr

icts

3,4

23

--

--

3,4

23

12

,64

91

,23

21

,06

3-

16

14

,96

0

Mpum

ala

nga

South

67

,38

61

14

21

7-

26

7,7

19

75

,11

82

4,7

72

87

,01

91

7,4

15

2,0

20

20

6,3

44

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

70

,80

91

14

21

7-

27

1,1

42

87

,76

72

6,0

04

88

,08

21

7,4

15

2,0

36

22

1,3

04

Maputa

land

5,7

71

--

--

5,7

71

4,4

96

8,4

21

62

2-

-1

3,5

39

Zulu

land

13

,82

84

80

--

-1

4,3

08

8,7

78

64

,13

92

6,5

23

4,1

95

34

10

3,6

69

Nort

hern

Kw

azu

lu-N

ata

l1

0,7

42

11

--

-1

0,7

53

6,4

79

20

,09

22

0,9

54

33

,59

62

36

81

,35

7

Maputa

land/Z

ulu

land/N

ort

hern

Kw

aZulu

-Nata

l(C

om

bin

ed)

30,3

41

491

--

-30,8

32

19,7

53

92,6

52

48,0

99

37,7

91

270

198,5

65

Kw

aZulu

-Nata

lM

idla

nds

22

,00

01

05

19

0-

16

52

2,4

60

42

,15

04

3,2

98

28

,97

66

2,9

91

73

31

78

,14

8

South

ern

Kw

aZulu

-Nata

l2

5,7

63

75

87

-1

17

26

,04

22

4,5

76

33

,27

11

8,9

44

4,1

07

12

68

1,0

24

East

ern

Cape

95

,53

94

70

-1

35

95

,74

89

,85

39

31

1,4

69

-9

12

,26

2

South

ern

Cape

58

,65

2-

87

9-

51

36

0,0

44

31

46

39

-2

66

82

West

ern

Cape

15

,48

5-

28

-2

15

,51

52

-5

-1

07

11

4

Tota

l480,6

67

16,7

80

1,7

67

-1,0

48

500,2

62

215,8

00

220,0

11

211,5

78

122,3

04

3,4

47

773,1

40

Perc

enta

ges:

96

.1%

3.4

%0

.4%

0.0

%0

.2%

10

0.0

%2

7.9

%2

8.5

%2

7.4

%1

5.8

%0

.4%

10

0.0

%

Perc

enta

ge

ofEuca

lypts

Com

bin

ed:

3.7

%

NO

TES:

SO

URC

E:

(unle

ssoth

erw

ise

state

d):

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica

20

01

/20

02

.

Are

as

insh

aded

colu

mns

were

exc

luded.

Wattle

are

as

(exc

eptju

ngle

are

as)

were

obta

ined

from

indust

ryso

urc

es

and

inse

rted

on

apro

rata

basi

sbase

don

Com

merc

ialTim

ber

Reso

urc

eare

as.

Wattle

Jungle

are

as

were

est

imate

dand

the

are

as

added

toth

egra

nd

tota

l.

Appendix G 2


REG

ION

AREA

AC

CO

RD

ING

TO

TH

EM

AIN

PU

RPO

SE

FO

RW

HIC

HTREES

ARE

GRO

WN

PO

LES

AN

DD

RO

PPERS

MIN

ING

TIM

BER

OTH

ER

PRO

DU

CTS

Pole

san

dD

ropp

ers:

Soft

woo

d

Pole

san

dD

ropp

ers:

E.gr

andi

s

Pole

san

dD

ropp

ers:

Oth

erEu

caly

ptus

Spec

ies

Pole

san

dD

ropp

ers:

Wat

tle

Pole

san

dD

ropp

ers:

Oth

erH

ardw

ood

Spec

ies

Tota

ls:

Pole

san

dD

ropp

ers

Min

ing

Tim

ber:

Soft

woo

d

Min

ing

Tim

ber:

E.gr

andi

s

Min

ing

Tim

ber:

Oth

erEu

caly

ptus

Spec

ies

Min

ing

Tim

ber:

Wat

tle

Min

ing

Tim

ber:

Oth

erH

ardw

ood

Spec

ies

Tota

ls:

Min

ing

Tim

ber

Oth

erPr

oduc

ts:

Soft

woo

d

Oth

erPr

oduc

ts:

E.gr

andi

s

Oth

erPr

oduc

ts:

Oth

erEu

caly

ptus

Spec

ies

Oth

erPr

oduc

ts:

Wat

tle

Lim

popo

35

3,2

08

1,9

38

--

5,1

81

-7

,70

33

,49

1-

11

1,1

95

-9

31

48

6-

Mpum

ala

nga

Nort

h-

81

13

06

--

1,1

17

-2

9,0

84

1,8

30

-5

03

0,9

64

-1

31

12

1-

Centr

alD

istr

icts

--

--

--

--

99

9-

-9

99

5-

--

Mpum

ala

nga

South

-1

15

--

-1

15

-3

,79

61

,63

45

40

41

36

,38

3-

81

,11

51

01

Mpum

ala

nga

South

/Centr

alD

istr

icts

(Com

bin

ed)

-1

15

--

-1

15

-3

,79

62

,63

35

40

41

37

,38

25

81

,11

51

01

Maputa

land

--

--

44

--

--

--

-7

3-

Zulu

land

--

-1

36

-1

36

--

--

--

-5

--

Nort

hern

Kw

azu

lu-N

ata

l-

69

24

03

39

-6

48

-7

16

67

38

74

31

,21

3-

43

-4

13

Maputa

land/Z

ulu

land/N

ort

hern

Kw

aZulu

-Nata

l(C

om

bin

ed)

-6

92

40

47

54

78

8-

71

66

73

87

43

1,2

13

-5

53

41

3

Kw

aZulu

-Nata

lM

idla

nds

14

66

40

53

,53

6-

4,3

27

-2

86

28

91

59

57

79

15

1-

78

South

ern

Kw

aZulu

-Nata

l-

64

71

56

--

80

3-

13

86

04

98

25

53

7-

7

East

ern

Cape

3,5

11

10

,38

72

,61

8-

20

16

,53

6-

18

83

0-

72

25

12

14

91

65

-

South

ern

Cape

27

2-

--

-2

72

-5

--

-5

2,3

81

-5

-

West

ern

Cape

59

05

24

-1

65

78

4-

--

--

-1

,79

05

32

9-

Tota

l4,5

54

15,8

82

5,2

87

4,0

11

189

29,9

23

-41,9

16

8,4

00

1,1

35

579

52,0

30

4,1

96

1,2

87

2,2

24

599

Perc

enta

ges:

15

.2%

53

.1%

17

.7%

13

.4%

0.6

%1

00

.0%

0.0

%8

0.6

%1

6.1

%2

.2%

1.1

%1

00

.0%

36

.2%

11

.1%

19

.2%

5.2

%

Perc

enta

ge

ofEuca

lypts

Com

bin

ed:

70

.7%

NO

TES:

SO

URC

E:

(unle

ssoth

erw

ise

state

d):

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica

20

01

/20

02

.

Are

as

insh

aded

colu

mns

were

exc

luded.

Wattle

are

as

(exc

eptju

ngle

are

as)

were

obta

ined

from

indust

ryso

urc

es

and

inse

rted

on

apro

rata

basi

sbase

don

Com

merc

ialTim

ber

Reso

urc

eare

as.

Wattle

Jungle

are

as

were

est

imate

dand

the

are

as

added

toth

egra

nd

tota

l.

Appendix G 3


January 2005

AREA

SD

AM

AG

ED

AS

ARESU

LTO

FFIR

EA

ND

SEV

ERE

WEA

TH

ER

CO

ND

ITIO

NS:

SO

FTW

OO

D:

1991

-2002

YEA

R

Lim

pop

oM

pu

mala

ng

aN

ort

h

Mp

um

ala

ng

aSou

thC

en

tral

Dis

tric

ts(C

om

bin

ed

)

Map

uta

lan

dZ

ulu

lan

dN

ort

hern

Kw

aZ

ulu

-Nata

l(C

om

bin

ed

)

Kw

aZ

ulu

-Nata

lM

idla

nd

sSou

thern

Kw

aZ

ulu

-Nata

lEast

ern

Cap

eSou

thern

Cap

eW

est

ern

Cap

eA

llA

reas

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

1991/9

22

79

23

77

80

3,4

13

1,0

41

47

66

94

40

21

,57

12

82

40

53

10

23

42

10

48

03

32

00

35

,68

45

,36

6

1992/9

37

21

,39

77

28

1,1

77

88

27

86

3,7

68

1,3

84

78

51

,08

42

95

81

76

87

25

29

21

22

81

52

7,5

90

6,8

44

1993/9

43

33

61

88

82

44

76

65

29

2,5

45

1,0

66

49

79

25

2,9

15

35

26

,40

41

11

27

19

49

48

14

,12

43

,65

5

1994/9

51

,96

82

78

5,7

84

-1

,41

85

04

2,8

29

1,0

51

55

86

00

3,2

41

28

23

,60

01

06

50

01

92

08

49

20

,10

62

,88

9

1995/9

65

02

18

27

11

45

20

42

01

,79

17

43

72

74

52

1,9

87

31

09

14

63

58

81

35

19

6-

7,0

44

2,3

55

1996/9

72

52

32

21

94

02

1,1

79

1,4

31

54

25

52

50

09

99

34

48

18

40

3,4

23

19

99

-8

,07

12

,64

5

1997/9

81

54

35

39

58

56

41

10

2,1

41

70

11

57

84

59

33

68

5-

32

7-

22

72

45

,10

99

19

1998/9

94

9-

73

13

46

86

46

61

,24

53

24

20

61

27

41

92

36

96

01

74

4,1

26

-2

,57

92

51

1,0

01

1,3

86

1999/0

02

21

-1

01

55

51

11

51

,17

5-

55

74

59

21

96

3,5

98

-2

,17

7-

1,7

17

-1

0,6

49

27

0

2000/0

12

7-

34

31

63

4,5

32

71

,47

5-

46

93

39

78

3,0

18

-3

13

-1

,64

5-

12

,21

91

81

2001/0

22

-5

78

17

92

,45

74

71

1,2

88

-4

28

19

34

41

5,9

19

41

16

-7

28

61

1,8

60

68

0

Avera

ge

per

Year

262

230

993

482

1,2

53

451

1,8

53

565

592

364

1,0

96

263

2,4

40

67

1,1

24

32

703

19

10,3

14

2,4

72

Tota

lA

rea

of

Reg

ion

27,1

66

27,1

66

166,6

43

166.6

43

158,5

81

158,5

81

50,0

95

50,0

95

64,3

01

64,3

01

50,3

42

50,3

42

108,9

14

108,9

14

61,3

07

61,3

07

17,8

68

17,8

68

705,2

17

705,2

17

%1.0

%0.8

%0.6

%0.3

%0.8

%0.3

%3.7

%1.1

%0.9

%0.6

%2.2

%0.5

%2.2

%0.1

%1.8

%0.1

%3.9

%0.1

%1.5

%0.4

%

Com

bin

ed

Ave

rages:

1.8

%0

.9%

1.1

%4

.8%

1.5

%2

.7%

2.3

%1

.9%

4.0

%1

.8%

SO

URC

E:

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

19

91

/19

92

-2

00

1/2

00

2.

Ove

rall

est

imate

s(H

ard

wood

and

Softw

ood)fo

r2

00

2/2

00

3are

35

,00

0ha.

Appendix H 1


AREA

SD

AM

AG

ED

AS

ARESU

LTO

FFIR

EA

ND

SEV

ERE

WEA

TH

ER

CO

ND

ITIO

NS:

HA

RD

WO

OD

:1991

-2002

YEA

R

Lim

pop

oM

pu

mala

ng

aN

ort

h

Mp

um

ala

ng

aSou

thC

en

tral

Dis

tric

ts(C

om

bin

ed

)

Map

uta

lan

dZ

ulu

lan

dN

ort

hern

Kw

aZ

ulu

-Nata

l(C

om

bin

ed

)

Kw

aZ

ulu

-Nata

lM

idla

nd

sSou

thern

Kw

aZ

ulu

-Nata

lEast

ern

Cap

eSou

thern

Cap

eW

est

ern

Cap

eA

llA

reas

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

age

dby

Fire

(ha)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

Area

Dam

aged

byFi

re(h

a)

Area

dam

aged

asa

resu

ltof

Seve

reW

eath

erCo

nditi

ons

(ha)

1991/9

22

39

1,6

04

1,4

74

2,9

37

63

29

18

2,1

48

87

48

80

66

83

98

68

7-

-1

2-

2-

5,7

85

7,6

88

1992/9

32

65

,20

48

25

60

37

97

1,5

57

3,0

84

1,7

86

1,3

88

3,1

43

14

81

,34

26

2-

3-

1-

6,3

34

13

,63

5

1993/9

43

07

1,1

23

1,6

75

40

96

40

1,3

51

2,0

14

51

68

94

78

72

59

86

81

11

--

-5

,79

15

,05

5

1994/9

51

31

83

81

,76

14

15

1,3

63

1,0

29

1,9

06

40

56

80

1,7

21

15

81

93

19

11

3-

--

6,0

31

4,6

02

1995/9

62

19

11

54

21

18

1,1

45

48

71

,77

12

99

77

71

,17

51

96

55

16

0-

--

--

4,6

89

2,1

49

1996/9

74

47

44

68

18

93

67

08

63

92

69

3,4

77

91

11

17

25

14

9-

--

--

5,8

30

2,0

05

1997/9

83

61

09

97

56

45

12

21

,76

51

51

22

73

49

8-

12

3-

1-

17

5-

3,1

67

42

1

1998/9

91

46

20

73

44

24

41

93

05

2,9

65

19

71

,03

49

00

32

52

02

00

-2

1-

--

5,4

54

1,6

53

1999/0

05

7-

6,9

08

12

52

14

13

1,0

14

64

73

91

10

51

11

57

41

45

10

10

-9

,57

23

38

2000/0

17

43

02

27

-1

,20

91

13

1,8

19

69

68

22

73

70

10

44

59

51

-2

06

35

,04

73

51

2001/0

24

21

10

33

0-

51

03

88

2,3

87

96

31

85

42

98

23

79

-2

24

--

-4

,86

75

50

Avera

ge

per

Year

155

847

1,3

21

414

774

636

1,9

56

430

1,0

09

866

262

301

148

129

136

05,6

88

3,4

95

Tota

lA

rea

ofRegio

n39,6

73

39,6

73

77,0

78

77,0

78

143,5

53

143,5

53

176,3

26

176,3

26

123,4

21

123,4

21

64,9

49

64,9

49

18,0

17

18,0

17

2,4

94

2,4

94

675

675

646,1

86

646,1

86

%0.4

%2.1

%1.7

%0.5

%0.5

%0.4

%1.1

%0.2

%0.8

%0.7

%0.4

%0.5

%0.8

%0.0

%1.2

%0.0

%5.3

%0.0

%0.9

%0.5

%

Com

bin

ed

Ave

rages:

2.5

%2

.3%

1.0

%1

.4%

1.5

%0

.9%

0.8

%1

.2%

5.3

%1

.4%

SO

URC

E:

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

19

91

/19

92

-2

00

1/2

00

2.

Ove

rall

est

imate

s(H

ard

wood

and

Softw

ood)fo

r2

00

2/2

00

3are

35

,00

0ha.

Appendix H 2


January 2005

Appendix I 1

NET INCREASE/DECREASE IN AREA:

SOFTWOODS: 1991 - 2001

YEARNet increase/decrease in Area:

Softwoods

1991/92 16,331

1992/93 8,310

1993/94 8,722

1994/95 3,145

1995/96 717

1996/97 -510

1997/98 -523

1998/99 -1,443

1999/00 475

2000/01 -3,142

2001/02 208

10 yr. Av.: 1992 - 2001 1,596

5 yr. Av.: 1997 - 2001 -885

SOURCE: Report on Commercial Timber Resources and PrimaryRoundwood Processing in South Africa: 1991/1992 - 2001/2002.

* The net increase is the area afforested in a given year less the areaconverted therefrom to another Genus or to non-forestry activities.


Appendix I 2


EUCALYPTS: 1991 - 2001


Eucalypts

1991/92 8,666

1992/93 3,898

1993/94 6,488

1994/95 7,016

1995/96 8,442

1996/97 8,403

1997/98 4,562

1998/99 -32

1999/00 -1,463

2000/01 1,228

2001/02 1,695

10 yr. Av.: 1992 - 2001 4,024

5 yr. Av.: 1997 - 2001 1,198




January 2005

Appendix I 3


WATTLES: 1991 - 2001


Wattles

1991/92 1,498

1992/93 1,003

1993/94 1,533

1994/95 95

1995/96 295

1996/97 -206

1997/98 -1,193

1998/99 325

1999/00 850

2000/01 1,557

2001/02 754

10 yr. Av.: 1992 - 2001 501

5 yr. Av.: 1997 - 2001 459




Appendix J

ANALYSIS OF WATTLE JUNGLE AREAS

REGION

FIRST ROTATION (10 Yrs) FOLLOWING TWO ROTATIONS (20 yrs)

Period(years)

Area(hectares)


per year)

Yield perAnnum(Tons)

Period(years)

Area(hectares)


per year)

Yield perAnnum(Tons)

Mpumalanga South 10 23,100 3.0 69,300 20 12,800 5.0 64,000

Northern KwaZulu-Natal 10 6,000 3.0 18,000 20 3,300 5.0 16,500

Eastern Cape 10 18,000 3.0 54,000 20 10,000 5.0 50,000

TOTALS: (Area/Yield) 47,100 141,300 26,100 130,500

NOTE: Areas and MAI’s were estimated.


January 2005

HIS

TO

RY

OF

AN

NU

AL

PU

RC

HA

SES

OF

PU

LPW

OO

DA

ND

RELA

TED

PRO

DU

CTS

INTO

NS:

1991/0

2-

2001/0

2

YEAR

Soft

woo

dPu

lp(1

.0)

Euca

lypt

usgr

andi

sPu

lp(1

.47)

Oth

erEu

caly

ptus

Spec

ies

Pulp

(1.2

5)

Wat

tlePu

lp(1

.19)

Oth

erH

ardw

ood

Spec

ies:

Pulp

(1.2

5)

Pole

s:So

ftw

ood

(1.0

)

Pole

s:E.

gran

dis

(1.4

7)

Pole

s:O

ther

Euca

lypt

usSp

ecie

s(1

.25)

Pole

s:W

attle

(1.1

9)(1

.138

sinc

e20

00/2

001)

Pole

s:O

ther

Har

dwoo

dSp

ecie

s(1

.25)

Min

ing

Tim

ber:

E.gr

andi

s(1

.47)

Min

ing

Tim

ber:

Oth

erEu

caly

ptus

Spec

ies

(1.2

5)

Min

ing

Tim

ber:

Wat

tle(1

.19)

(1.1

38si

nce

2000

/200

1)

Min

ing

Tim

ber:

Oth

erH

ardw

ood

Spec

ies

(1.2

5)

Char

coal

:So

ftw

ood

(1.0

)

Char

coal

:E.

gran

dis

(1.4

7)

Char

coal

:O

ther

Euca

lypt

usSp

ecie

s(1

.25)

Char

coal

:W

attle

(1.1

9)(1

.138

sinc

e20

00/2

001)

Char

coal

:O

ther

Har

dwoo

dSp

ecie

s(1

.25)

TOTA

L

19

91

/92

3,4

72,6

95

1,7

74,2

84

1,1

35,3

13

1,0

27

,25

14

3,7

60

14

4,1

65

76

,81

51

3,5

23

--

1,2

71

,16

6188,9

31

81,6

37

--

-22,0

00

229,1

06

-9,4

80,6

46

19

92

/93

3,4

64,5

75

2,2

30,8

77

710,5

51

61

5,6

77

25

,69

61

46

,36

96

9,5

48

10

,82

2-

-9

71

,75

990,9

67

54,0

79

--

-4,4

25

134,3

87

-8,5

29,7

32

19

93

/94

3,0

99,5

21

3,6

58,4

68

503,0

06

72

5,5

17

21

,62

79

3,3

75

78

,18

71

3,2

98

5,0

42

-8

24

,70

6299,0

38

71,3

45

-1,0

00

-13,2

42

55,8

67

-9,4

63,2

39

19

94

/95

3,2

12,0

17

3,4

01,0

71

687,3

14

59

1,2

80

1,2

17

94

,81

17

7,3

65

20

,25

45

,04

2-

69

5,4

15

294,1

59

27,5

15

-1,0

00

-7,5

00

107,3

49

16,0

73

9,2

39,3

83

19

95

/96

3,2

16,5

17

3,7

02,9

66

760,2

54

68

1,4

27

76

91

07

,24

08

9,0

99

13

,67

53

,78

2-

50

4,6

22

184,3

30

5,9

70

-1,0

00

-7,5

00

78,0

33

34,9

80

9,3

92,1

64

19

96

/97

3,0

05,6

78

3,6

91,3

83

773,1

76

62

5,6

32

1,6

20

11

6,1

49

90

,88

31

2,9

70

1,8

24

-4

33

,24

0190,8

57

7,4

80

-1,1

13

-7,4

85

97,9

76

-9,0

57,4

66

19

97

/98

3,4

20,6

17

3,8

47,1

36

2,0

24,0

00

1,5

95

,27

71

,29

21

04

,63

34

0,6

30

17

,03

53

,78

2-

45

5,0

94

184,2

80

--

-11,8

00

-265,6

90

-11,9

71,2

66

19

98

/99

3,3

09,7

04

3,5

60,6

76

1,6

84,6

43

1,3

34

,28

81

,42

41

14

,95

72

8,1

54

17

,60

2-

-2

17

,78

3302,2

70

--

--

-250,1

72

-10,8

21,6

73

19

99

/00

2,9

42,0

97

3,7

31,2

57

1,5

83,1

02

1,0

33

,92

06

44

,61

41

07

,59

51

03

,34

61

6,8

38

-2

,92

73

75

,80

1164,4

99

--

--

21,6

59

186,8

78

-10,9

14,5

33

20

00

/01

3,3

13,2

55

3,6

93,9

87

1,4

46,9

76

75

9,8

00

-1

01

,80

11

47

,97

61

,03

2-

-5

14

,11

034,3

28

--

-25,6

30

-201,4

36

-10,2

40,3

31

20

01

/02

3,1

78,3

48

3,3

82,4

08

2,1

22,2

39

1,3

03

,40

5-

11

2,0

79

13

2,0

18

44

,11

8-

-3

83

,91

4-

-455

-25,6

30

41,2

78

157,6

57

-10,8

83,5

50

Ave

rage

per

Year:

3,2

39,5

48

3,3

34,0

47

1,2

20,9

61

93

5,7

70

67

,45

61

13

,01

68

4,9

11

16

,47

01

,77

02

66

60

4,3

28

175,7

87

22,5

48

41

374

5,7

33

11,3

72

160,4

14

4,6

41

9,9

99,4

53

*Fig

ure

sin

bra

ckets

are

conve

rsio

nra

tios

-m

³to

tons.

SO

URC

E:

Report

on

Com

merc

ialTim

ber

Reso

urc

es

and

Pri

mary

Roundw

ood

Pro

cess

ing

inSouth

Afr

ica:

19

91

/19

92

-2

00

1/2

00

2.

This

info

rmation

was

ext

ract

ed

from

the

AnnualReport

son

Com

merc

ialTim

ber

Reso

urc

es

butth

evo

lum

es

report

ed

are

too

low

com

pare

dto

the

independently

gath

ere

din

form

ation

and

has

there

fore

notbeen

use

d.

Data

incl

uded

inth

eta

ble

on

the

rightis

for

info

rmation

only

.It

isgiv

en

into

ns

as

all

yield

sin

this

study

are

quote

din

tons.

HIS

TO

RY

OF

AN

NU

AL

PU

RC

HA

SES:

SA

WTIM

BER

AN

DV

EN

EER

PRO

DU

CTS

INTO

NS

1991/0

2-

2001/0

2

YEAR

Soft

woo

dSa

wtim

ber

and

Vene

er(t

ons)

(1:0

.94)

E.gr

andi

san

dO

ther

Euca

lypt

usSp

ecie

sSa

wtim

ber

and

Vene

er(t

ons)

(1:0

.94,

1:0.

78)

Oth

erH

ardw

ood

Spec

ies

Saw

timbe

ran

dVe

neer

(ton

s)(1

:0.7

8)TO

TAL

(ton

s)

19

91

/92

3,5

69,6

02

704,8

10

15

,99

04

,29

0,4

02

19

92

/93

3,4

89,2

31

311,2

75

10

,24

63

,81

0,7

52

19

93

/94

2,9

94,1

26

329,1

70

12

,23

73

,33

5,5

32

19

94

/95

3,2

86,9

73

326,0

30

11

,96

53

,62

4,9

69

19

95

/96

3,0

63,5

11

299,2

49

10

,56

33

,37

3,3

22

19

96

/97

3,1

86,0

62

319,7

85

11

,81

93

,51

7,6

66

19

97

/98

3,1

11,2

11

233,7

89

15

,95

63

,36

0,9

56

19

98

/99

3,2

60,3

27

284,7

31

10

,21

43

,55

5,2

72

19

99

/00

3,2

77,3

77

256,4

31

6,9

51

3,5

40

,75

9

20

00

/01

3,3

64,0

52

254,2

45

10

,28

83

,62

8,5

85

20

01

/02

3,6

65,4

90

230,6

58

17

,76

23

,91

3,9

10

Ave

rage

per

Year:

3,2

97,0

87

322,7

43

12

,18

13

,63

2,0

12

Appendix K


Appendix L

ESTIMATE OF CHIP SOURCE

SawmillChip Volume

Recovered PerAnnum (m³)

Piet Retief Mandini SonaePG Bison

PMBMagnaboard George Stellenbosch Ngodwana

SiliconSmelters

Bracken Timbers 11,770 11,770

Cape Sawmills 25,032 25,032

Densa 9,264 9,264

e’Mpuluzi 17,318 17,318

Graskop 18,000 18,000

Great Brak 5,356 5,356

KLF Blyde 7,663 7,663

KLF Timbadola 5,140 5,140

Kusel 7,692 7,692

Langeni 41,024 41,024

Lomati 50,000 50,000

Madiba Mills 2,074 2,074

Malenge 43,521 43,521

Mogoboya -

MTO George 23,181 23,181

Newington Timber Co. 7,362 7,362

Nicholson & Mullin 12,702 12,702

Pine Valley 5,083 5,083

R F Gevers 9,548 9,548

Rance Timber 6,444 6,444

Seven Oaks 5,647 5,647

Singisi 26,820 26,820

Stevens Lumber Mill 22,255 22,255

Swaziland -

TTC Sabie 23,249 23,249

Weza 12,519 12,519

White River 6,834 6,834

York Lumber 4,789 4,789

Yorkcor Golden Rhino 9,779 9,779

Yorkcor Roburnia 6,784 6,784

TOTAL 426,851 51,473 102,321 17,318 5,647 47,468 28,538 25,032 121,658 27,395


January 2005

TA

BLE

24A

:C

ON

TRIB

UTIO

NO

FFO

RESTRY

&FO

REST

PRO

DU

CTS

IND

USTRY

TO

G.D

.P.(E

xpre

ssed

InRealte

rms)

C.P

.I

EXPRESSED

IN2002/0

3V

ALU

ES

8.4

9.6

11.1

12.6

14.0

16.0

18.8

22.2

25.3

28.7

33.0

37.7

43.7

YEA

R

1979

/80

1980

/81

1981

/82

1982

/83

1983

/84

1984

/85

1985

/86

1986

/87

1987

/88

1988

/89

1989

/90

1990

/91

1991

/92

RA

ND

MIL

LIO

N

Tota

lR.S

.A.

G.D

.P.

60

95

48

63

88

44

63

32

25

64

22

70

66

39

07

67

08

56

64

39

10

63

90

09

65

19

88

68

64

81

69

59

82

69

21

51

59

71

19

Agri

culture

,Fore

stry

&Fis

heri

es

G.D

.P.

44

03

64

13

23

46

10

83

56

83

33

25

03

93

75

36

63

83

94

14

41

68

04

08

29

41

26

13

44

40

29

71

2

Manufa

cturi

ng

G.D

.P.

13

24

76

14

56

56

15

48

56

15

31

19

16

26

43

15

31

13

14

86

76

14

96

94

15

84

55

17

32

40

17

64

21

17

44

93

15

05

35

Fore

stry

G.D

.P.

1,9

60

.72

,25

2.2

2,0

28

.82

,25

9.4

2,2

04

.32

,26

3.1

2,3

75

.52

,60

5.1

2,6

72

.72

,90

1.4

2,7

23

.32

,41

9.3

2,4

52

.0

Fore

stPro

duct

sG

.D.P

.8

,29

9.9

9,8

97

.18

,90

6.3

9,1

55

.68

,99

2.8

10

,42

6.3

10

,95

4.3

12

,99

8.3

13

,29

3.5

16

,28

4.3

16

,14

8.8

14

,40

9.7

12

,94

8.7

Fore

stry

as

%to

Agri

cultura

lG

.D.P

.4

.5%

5.5

%4

.4%

6.3

%6

.6%

5.7

%6

.5%

6.6

%6

.4%

7.1

%6

.6%

7.0

%8

.3%

Fore

stPro

duct

sas

%to

Manufa

cturing

G.D

.P.

6.3

%6.8

%5.8

%6.0

%5.5

%6.8

%7.4

%8.7

%8.4

%9.4

%9.2

%8.3

%8.6

%

Fore

stPro

duct

sas

%to

Tota

lG

.D.P

.1

.4%

1.5

%1

.4%

1.4

%1

.4%

1.6

%1

.7%

2.0

%2

.0%

2.4

%2

.3%

2.1

%2

.2%

TA

BLE

24B:

CO

NTRIB

UTIO

NO

FFO

RESTRY

&FO

REST

PRO

DU

CTS

IND

USTRY

TO

G.D

.P.(E

xpre

ssed

inre

alte

rms)

C.P

.I

EXPRESSED

IN2002/0

3V

ALU

ES

48.5

52.8

58.1

62.0

67.5

71.9

77.8

80.3

85.8

90.6

100.0

Ch

an

ge

on

pre

v.

year

Gro

wth

per

an

nu

m

YEA

R

1992

/93

1993

/94

1994

/95

1995

/96

1996

/97

1997

/98

1998

/99

1999

/00

2000

/01

2001

/02

2002

/03

RA

ND

MIL

LIO

N

Tota

lR.S

.A.

G.D

.P.

87

86

23

91

31

04

94

33

72

99

67

05

10

15

89

51

02

77

15

10

29

26

71

10

64

20

11

46

21

01

23

71

92

12

09

49

9-2

.2%

3.0

%

Agri

culture

,Fore

stry

&Fis

heri

es

G.D

.P.

33

57

53

83

56

33

24

83

82

60

37

24

43

37

79

32

12

93

24

53

36

28

44

64

66

41

93

5-9

.8%

-0.2

%

Manufa

cturi

ng

G.D

.P.

17

03

96

17

43

71

18

27

54

18

40

73

18

45

99

17

94

39

17

48

28

18

70

46

19

38

59

21

86

47

20

82

67

-4.7

%2

.0%

Fore

stry

G.D

.P.

2,1

01

.12

,01

4.0

2,7

71

.12

,89

9.8

2,5

86

.62

,95

9.4

2,9

15

.63

,20

5.6

3,1

61

.23

,60

5.1

4,0

79

.91

3.2

%3

.2%

Fore

stPro

duct

sG

.D.P

.1

0,4

95

.91

1,8

41

.51

2,8

72

.31

4,5

13

.31

3,5

44

.71

4,0

33

.51

5,1

84

.21

6,0

12

.11

3,8

30

.41

5,2

39

.41

4,5

90

.7-4

.3%

2.5

%

Fore

stry

as

%to

Agri

cultura

lG

.D.P

.6

.3%

5.3

%8

.3%

7.6

%6

.9%

8.8

%9

.1%

9.9

%8

.7%

7.8

%9

.7%

25

.4%

3.5

%

Fore

stPro

duct

sas

%to

Manufa

cturing

G.D

.P.

6.2

%6.8

%7.0

%7.9

%7.3

%7.8

%8.7

%8.6

%7.1

%7.0

%7.0

%0.5

%0.5

%

Fore

stPro

duct

sas

%to

Tota

lG

.D.P

.1

.2%

1.3

%1

.4%

1.5

%1

.3%

1.4

%1

.5%

1.4

%1

.2%

1.2

%1

.2%

-2.1

%-0

.5%

SO

URC

E:

FO

RESTRY

SO

UTH

AFRIC

A

Appendix M


Appendix N

FORECAST OF ROUNDWOOD OTHER THAN SAWLOGS IN TONS: ALL REGIONS: 2005 - 2034: INCLUDING ADJUSTMENTS

YEAR

TONS %Reductionfor Fires

and OtherFactors:

Softwood

%Reductionfor Fires

and OtherFactors:

Hardwoods

TONS

Pine (1.00)E. grandis

(1.37)

OtherEucalypts

(1.16)

Wattle(1.138)

WattleJungle(1.138)

Wattle TotalTotal

Hardwoods

Total Forecast(Rounded to

100)

2005-06 3,868,452 5,966,143 5,653,351 1,173,908 141,300 1,315,208 12,934,701 2.6% 1.9% 16,453,400

2006-07 4,354,663 5,827,040 5,365,649 1,201,538 141,300 1,342,838 12,535,527 2.6% 1.9% 16,535,200

2007-08 4,814,353 5,750,802 4,838,539 1,329,756 141,300 1,471,056 12,060,397 2.6% 1.9% 16,516,800

2008-09 5,185,708 5,846,566 5,020,344 1,245,110 141,300 1,386,410 12,253,321 2.6% 1.9% 17,067,600

2009-10 5,799,928 5,145,868 4,142,435 1,031,285 141,300 1,172,585 10,460,887 2.6% 1.9% 15,907,500

Annual Average:2005–2009

4,804,621 5,707,284 5,004,063 1,196,319 141,300 1,337,619 12,048,967 2.6% 1.9% 16,496,100

2010-11 6,075,117 5,128,704 4,137,650 1,020,253 141,300 1,161,553 10,427,906 2.6% 1.9% 16,143,100

2011-12 4,305,349 5,117,793 4,140,054 906,894 141,300 1,048,194 10,306,042 2.6% 1.9% 14,300,500

2012-13 4,190,824 5,110,753 4,138,362 910,117 141,300 1,051,417 10,300,533 2.6% 1.9% 14,183,500

2013-14 4,293,201 5,123,146 4,151,634 857,719 141,300 999,019 10,273,799 2.6% 1.9% 14,257,000

2014-15 3,318,227 6,693,996 6,661,518 619,191 141,300 760,491 14,116,005 2.6% 1.9% 17,076,300


4,436,544 5,434,878 4,645,844 862,835 141,300 1,004,135 11,084,857 2.6% 1.9% 15,192,100

2015-16 3,538,693 4,859,834 4,720,103 1,303,907 138,330 1,442,237 11,022,173 2.6% 1.9% 14,256,400

2016-17 3,143,487 4,776,497 4,189,695 1,118,326 138,330 1,256,656 10,222,848 2.6% 1.9% 13,087,600

2017-18 3,192,772 4,912,258 4,392,831 1,246,543 138,330 1,384,873 10,689,961 2.6% 1.9% 13,593,800

2018-19 3,201,200 4,217,772 3,490,074 1,161,898 138,330 1,300,228 9,008,073 2.6% 1.9% 11,952,300

2019-20 3,286,466 4,223,610 3,492,133 948,072 138,330 1,086,402 8,802,145 2.6% 1.9% 11,833,300

Annual Average:2015–2019 3,272,524 4,597,994 4,056,967 1,155,749 138,330 1,294,079 9,949,040 2.6% 1.9% 12,944,700

2020-21 3,384,565 4,239,717 3,491,043 959,452 138,330 1,097,782 8,828,541 2.6% 1.9% 11,954,700

2021-22 3,109,509 4,575,809 3,793,188 846,094 138,330 984,424 9,353,420 2.6% 1.9% 12,201,800

2022-23 3,177,454 4,580,937 3,792,532 849,316 138,330 987,646 9,361,115 2.6% 1.9% 12,275,500

2023-24 3,326,856 6,547,934 6,507,396 796,918 138,330 935,248 13,990,579 2.6% 1.9% 16,961,700

2024-25 3,788,935 4,764,333 4,565,974 619,191 138,330 757,521 10,087,828 2.6% 1.9% 13,583,600


3,357,464 4,941,746 4,430,026 814,194 138,330 952,524 10,324,2972.6% 1.9% 13,395,500

2025-26 4,320,470 4,672,480 4,036,451 1,273,507 138,330 1,411,837 10,120,769 2.6% 1.9% 14,133,500

2026-27 4,698,638 4,817,899 4,218,520 1,087,925 138,330 1,226,255 10,262,674 2.6% 1.9% 14,640,800

2027-28 5,219,264 4,081,772 3,338,980 1,216,143 138,330 1,354,473 8,775,225 2.6% 1.9% 13,688,800

2028-29 5,108,975 4,080,113 3,339,016 1,131,497 138,330 1,269,827 8,688,956 2.6% 1.9% 13,496,800

2029-30 4,001,033 4,082,178 3,340,063 917,672 138,330 1,056,002 8,478,242 2.6% 1.9% 12,211,400


4,669,676 4,346,889 3,654,606 1,125,349 138,330 1,263,679 9,265,173 2.6% 1.9% 13,634,300

2030-31 4,232,615 4,592,308 3,831,497 929,052 138,330 1,067,382 9,491,186 2.6% 1.9% 13,430,400

2031-32 4,150,158 4,586,779 3,792,911 815,693 138,330 954,023 9,333,713 2.6% 1.9% 13,195,700

2032-33 3,193,807 6,576,463 6,509,257 818,916 138,330 957,246 14,042,965 2.6% 1.9% 16,883,500

2033-34 3,142,500 4,743,436 4,568,393 766,518 138,330 904,848 10,216,677 2.6% 1.9% 13,080,600

2034-35 3,087,700 4,651,487 4,041,082 619,191 138,330 757,521 9,450,090 2.6% 1.9% 12,275,300


3,561,356 5,030,094 4,548,628 789,874 138,330 928,204 10,506,926 2.6% 1.9% 13,773,100


4,017,031 5,009,814 4,390,022 990,720 139,320 1,130,040 10,529,877 2.6% 1.9% 14,239,300

Logs included are are those of pulpwood dimensions only from each timber type and therefore includes by-products from the sawlog productionoperations.

30% of Class a logs from Pine sawtimber compartments (thinnings and clearfellings) were assumed to be pulpwood.


Wattle Jungle forecasts are based on: Mpumalanga South: 23,100 ha @ 3 tons/ha/annum, Northern KZNatal: 6,000 ha @ 3 tons/ha/annum andEastern Cape: 18,000 ha @ 3 tons/ha/annum for one rotation and 10,000 ha @ 5 tons/ha/annum thereafter.

Mpumalanga South/Central Districts (Combined) includes both Regions’ data, Zululand (Combined) includes Maputaland, Zululand and NorthernKwaZulu-Natal Regions.

Some smoothing was applied to Pine and Eucalypt clearfelling areas in order to even out yields realistically.

Allowance of 6% Pine and Eucalypt increase in MAI.

Increase in fire damage.

Reduction from 5% to 2.5% of area to be removed for environmental reasons (DWAF).


January 2005

CU

RREN

TSU

PPLY

AN

DD

EM

AN

DLE

VELS

AD

JUSTED

BY

PU

BLI

SH

ED

/KN

OW

NIN

CREA

SES

ON

LY

An

aly

sis

of

Su

pp

lyan

dD

em

an

dfo

rRou

nd

wood

oth

er

than

Saw

log

sin

‘000

Ton

s:2005

-2034

YEA

RSU

PPLY

DEM

AN

DO

VERSU

PPLY

(+)

/U

ND

ERSU

PPLY

(-)

%SH

ORTA

GE

Pine

Euca

lypt

Wat

tleTo

tal

Pine

Euca

lypt

Wat

tleTo

tal

Pine

Euca

lypt

Wat

tleTo

tal

Cum

ulat

ive

20

05

3,6

84

10

,80

81

,23

11

5,7

24

3,2

92

12

,29

81

,64

81

7,2

38

39

2-1

,49

0-4

17

-1,5

14

-1,5

14

8.7

8

20

06

4,1

47

10

,41

11

,25

71

5,8

16

3,2

92

12

,24

81

,64

81

7,1

88

85

5-1

,83

7-3

91

-1,3

72

-2,8

86

7.9

8

20

07

4,5

85

9,8

50

1,3

76

15

,81

23

,26

21

2,0

48

1,6

48

16

,95

81

,32

3-2

,19

8-2

72

-1,1

46

-4,0

33

6.7

6

20

08

4,9

39

10

,10

81

,29

81

6,3

45

3,2

42

12

,42

81

,64

81

7,3

18

1,6

97

-2,3

20

-35

0-9

73

-5,0

06

5.6

2

20

09

5,5

24

8,6

40

1,0

99

15

,26

23

,24

21

2,3

40

1,6

23

17

,20

52

,28

2-3

,70

0-5

24

-1,9

43

-6,9

48

11

.29

5yr

Avg

2005-2

009

4,5

76

9,9

64

1,2

52

15,7

92

3,2

66

12,2

72

1,6

43

17,1

81

1,3

10

-2,3

09

-391

-1,3

90

-4,0

77

8.0

9

20

10

5,7

86

8,6

19

1,0

88

15

,49

43

,24

21

2,3

40

1,6

23

17

,20

52

,54

4-3

,72

1-5

35

-1,7

11

-8,6

59

9.9

5

20

11

4,1

01

8,6

12

98

31

3,6

95

3,2

42

12

,34

01

,62

31

7,2

05

85

9-3

,72

8-6

40

-3,5

10

-12

,16

92

0.4

0

20

12

3,9

91

8,6

03

98

61

3,5

81

3,2

42

12

,34

01

,62

31

7,2

05

74

9-3

,73

7-6

37

-3,6

24

-15

,79

42

1.0

6

20

13

4,0

89

8,6

27

93

71

3,6

53

3,2

42

12

,34

01

,62

31

7,2

05

84

7-3

,71

3-6

86

-3,5

52

-19

,34

52

0.6

4

20

14

3,1

60

12

,42

37

15

16

,29

93

,24

21

2,3

40

1,6

23

17

,20

5-8

28

3-9

08

-90

6-2

0,2

51

5.2

7

5yr

Avg

2010-2

014

4,2

25

9,3

77

942

14,5

44

3,2

42

12,3

40

1,6

23

17,2

05

983

-2,9

63

-681

-2,6

61

-15,2

44

15.4

6

20

15

3,3

70

8,9

11

1,3

42

13

,62

33

,24

21

2,3

40

1,6

23

17

,20

51

28

-3,4

29

-28

1-3

,58

2-2

3,8

33

20

.82

20

16

2,9

94

8,3

40

1,1

69

12

,50

33

,24

21

2,3

40

1,6

23

17

,20

5-2

48

-4,0

00

-45

4-4

,70

2-2

8,5

35

27

.33

20

17

3,0

41

8,6

55

1,2

88

12

,98

53

,24

21

2,3

40

1,6

23

17

,20

5-2

01

-3,6

85

-33

5-4

,22

0-3

2,7

56

24

.53

20

18

3,0

49

7,1

70

1,2

09

11

,42

83

,24

21

2,3

40

1,6

23

17

,20

5-1

93

-5,1

70

-41

4-5

,77

7-3

8,5

33

33

.58

20

19

3,1

30

7,1

77

1,0

11

11

,31

83

,24

21

2,3

40

1,6

23

17

,20

5-1

12

-5,1

63

-61

2-5

,88

7-4

4,4

20

34

.22

5yr

Avg

2015-2

019

3,1

17

8,0

51

1,2

04

12,3

71

3,2

42

12,3

40

1,6

23

17,2

05

-125

-4,2

89

-419

-4,8

34

-33,6

15

28.0

9

20

20

3,2

24

7,1

91

1,0

21

11

,43

63

,24

21

2,3

40

1,6

23

17

,20

5-1

8-5

,14

9-6

02

-5,7

69

-50

,18

93

3.5

3

20

21

2,9

62

7,7

85

91

61

1,6

62

3,2

42

12

,34

01

,62

31

7,2

05

-28

0-4

,55

5-7

07

-5,5

43

-55

,73

23

2.2

2

20

22

3,0

26

7,7

89

91

91

1,7

34

3,2

42

12

,34

01

,62

31

7,2

05

-21

6-4

,55

1-7

04

-5,4

71

-61

,20

33

1.8

0

20

23

3,1

69

11

,84

48

70

15

,88

23

,24

21

2,3

40

1,6

23

17

,20

5-7

3-4

96

-75

3-1

,32

3-6

2,5

26

7.6

9

20

24

3,6

09

8,3

79

70

51

2,6

93

3,2

42

12

,34

01

,62

31

7,2

05

36

7-3

,96

1-9

18

-4,5

12

-67

,03

82

6.2

3

5yr

Avg

2020-2

024

3,1

98

8,5

98

886

12,6

81

3,2

42

12,3

40

1,6

23

17,2

05

-44

-3,7

42

-737

-4,5

24

-59,3

38

26.2

9

20

25

4,1

15

7,8

02

1,2

85

13

,20

13

,24

21

2,3

40

1,6

23

17

,20

58

73

-4,5

38

-33

8-4

,00

4-7

1,0

42

23

.27

20

26

4,4

75

8,1

06

1,1

12

13

,69

43

,24

21

2,3

40

1,6

23

17

,20

51

,23

3-4

,23

4-5

11

-3,5

11

-74

,55

32

0.4

1

20

27

4,9

71

6,6

03

1,2

32

12

,80

63

,24

21

2,3

40

1,6

23

17

,20

51

,72

9-5

,73

7-3

91

-4,3

99

-78

,95

22

5.5

7

20

28

4,8

51

6,6

00

1,1

53

12

,60

43

,24

21

2,3

40

1,6

23

17

,20

51

,60

9-5

,74

0-4

70

-4,6

01

-83

,55

32

6.7

4

20

29

3,7

95

6,6

04

95

41

1,3

53

3,2

42

12

,34

01

,62

31

7,2

05

55

3-5

,73

6-6

69

-5,8

52

-89

,40

53

4.0

1

5yr

Avg

2025-2

029

4,4

41

7,1

43

1,1

47

12,7

32

3,2

42

12,3

40

1,6

23

17,2

05

1,1

99

-5,1

97

-476

-4,4

73

-79,5

01

26.0

0

20

30

4,0

16

7,8

34

96

51

2,8

15

3,2

42

12

,34

01

,62

31

7,2

05

77

4-4

,50

6-6

58

-4,3

90

-93

,79

52

5.5

2

20

31

3,9

37

7,7

93

85

91

2,5

90

3,2

42

12

,34

01

,62

31

7,2

05

69

5-4

,54

7-7

64

-4,6

15

-98

,41

02

6.8

2

20

32

3,0

27

11

,86

98

62

15

,75

83

,24

21

2,3

40

1,6

23

17

,20

5-2

15

-47

1-7

61

-1,4

47

-99

,85

78

.41

20

33

2,9

68

8,3

60

81

31

2,1

42

3,2

42

12

,34

01

,62

31

7,2

05

-27

4-3

,98

0-8

10

-5,0

63

-10

4,9

20

29

.43

20

34

2,9

16

7,7

84

70

51

1,4

05

3,2

42

12

,34

01

,62

31

7,2

05

-32

6-4

,55

6-9

18

-5,8

00

-11

0,7

21

33

.71

5yr

Avg

2030-2

034

3,3

73

8,7

28

841

12,9

42

3,2

42

12,3

40

1,6

23

17,2

05

131

-3,6

12

-782

-4,2

63

-101,5

41

24.7

8

Fig

ure

sin

clude

allo

wance

sfo

rFir

eand

Weath

er

dam

age.

Appendix O


Appendix P

TABLE 26: SUPPLY AND DEMAND OF SAWLOGS (PRIOR TO ADJUSTMENTS)

Year Demand Supply Annual ShortagePercentageShortage

AccumalitiveShortage

(Paragraph 3.6) (Paragraph 5.9)

(m³) (m³) (m³) (%) (m³)

2004 1 5,250,000 3,811,950 1,438,050 27% 1,438,050

2005 2 5,394,000 3,614,950 1,779,050 33% 3,217,100

2006 3 5,543,000 3,743,000 1,800,000 32% 5,017,100

2007 4 5,695,000 4,196,100 1,498,900 26% 6,516,000

2008 5 5,852,000 4,836,350 1,015,650 17% 7,531,650

2009 6 5,879,000 5,112,150 766,850 13% 8,298,500

2010 7 6,026,000 5,269,750 756,250 13% 9,054,750

2011 8 6,177,000 5,358,400 818,600 13% 9,873,350

2012 9 6,331,000 4,925,000 1,406,000 22% 11,279,350

2013 10 6,489,000 4,944,700 1,544,300 24% 12,823,650

2014 11 6,522,000 4,688,600 1,833,400 28% 14,657,050

2015 12 6,686,000 5,072,750 1,613,250 24% 16,270,300

2016 13 6,853,000 4,649,200 2,203,800 32% 18,474,100

2017 14 7,024,000 5,653,900 1,370,100 20% 19,844,200

2018 15 7,200,000 6,284,300 915,700 13% 20,759,900

2019 16 7,239,000 6,796,500 442,500 6% 21,202,400

2020 17 7,420,000 7,062,450 357,550 5% 21,559,950

2021 18 7,606,000 4,993,950 2,612,050 34% 24,172,000

2022 19 7,796,000 5,634,200 2,161,800 28% 26,333,800

2023 20 7,991,000 6,688,150 1,302,850 16% 27,636,650

2024 21 8,038,000 6,589,650 1,448,350 18% 29,085,000

2025 22 8,239,000 6,018,350 2,220,650 27% 31,305,650

2026 23 8,445,000 6,146,400 2,298,600 27% 33,604,250

2027 24 8,656,000 5,279,600 3,376,400 39% 36,980,650

2028 25 8,873,000 4,875,750 3,997,250 45% 40,977,900

2029 26 9,094,000 4,708,300 4,385,700 48% 45,363,600

2030 27 9,322,000 4,708,300 4,613,700 49% 49,977,300

2031 28 9,555,000 4,708,300 4,846,700 51% 54,824,000

2032 29 9,794,000 4,708,300 5,085,700 52% 59,909,700

2033 30 10,038,000 4,708,300 5,329,700 53% 65,239,400

SOURCE: Supply and Demand Study of Softwood Sawlog and Sawn Timber in South Africa by Crickmay & Associates (2004)

Study of Supply and Demand of Industrial Roundwood...1. Reports on Commercial Timber Resources and...

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Transcript of Study of Supply and Demand of Industrial Roundwood...1. Reports on Commercial Timber Resources and...