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1 Guidelines for defining forest resources

1.1 Resources and inventories
1.2 Land area in sustainable forest management
1.3 Forest inventory
1.4 Forest growth and yield
1.5 Diagnostic sampling
1.6 Further reading

1.1 Resources and inventories

1.1.1 Definition and maintenance of forest boundaries
1.1.2 Mapping
1.1.3 Zoning
1.1.4 Remote sensing imagery
1.1.5 Geographic information systems

1.1.1 Definition and maintenance of forest boundaries

Selection of Forest Management Unit Boundaries

Wherever it is practicable to do so, natural geographic features should be selected to define the boundaries of a forest management unit. These include rivers, streams, shorelines, ridges and spurs. Permanent and clearly defined roads, railways and tracks may also be used. On flat country not having clearly recognisable natural features boundaries can be defined using straight lines that have a N-S, E-W orientation to enable them to be shown as true or magnetic coordinates on maps. The number of comers on straight line boundaries should be kept to a minimum.

Demarcation and Maintenance of External Forest Boundaries

External boundaries should be kept clear of bushy vegetation for a width of two metres in order that neighbours may easily recognise a boundary and to allow it to be patrolled. Trees located on a boundary should not be removed. Cost sharing between forest neighbours in the maintenance of common boundaries is desirable. This approach confirms agreement on the line of a common boundary and is cost-efficient.

Boundaries should be defined and marked using beacons which may be durable wooden poles or stone or concrete pillars painted using two contrasting colours, such as broad red and white bands. The tops of poles should be pointed, partly to shed water and also to assist with recognition. Poles should be between 1.5 metres and two metres tall. Although not all pillars need to be labelled, permanent labels should be firmly attached to those that indicate major changes in boundary direction or are triangulation points for surveys, or are "tie-in" points for internal surveys, such as compartment boundaries or various types of reserves. Continuous lines of" live markers are a practical means of spotting a boundary from an aircraft or from a distance. Trees or shrubs used for boundary definition should be fast growing and distinctively different from surrounding forest vegetation. Live markers may also be used on boundary pillars. At the comers of boundary lines direction trenches can be dug and kept clear of vegetation. Direction trenches should be 30 cm × 30 cm (wide × deep), up to 3 metres long, and should be correctly aligned to indicate the direction of the boundary.

Patrolling is essential and should be undertaken often in heavily populated areas or where the risk of boundary transgression is considered to be high. Forest guards should be accountable to a senior officer or director. Aerial inspection and remote sensing imagery can be helpful for checking boundaries but these methods are most useful after boundaries are known on the ground. Notices should be erected on high-use parts of a boundary.

Demarcation and Maintenance of Internal Forest Boundaries

The boundaries of biological, wildlife, watershed, forest community or other reserves should be as clearly defined as are external boundaries. Roads, cut lines, pillars, painted standing trees and poles should be used to define internal boundaries. Internal compartment boundaries should be surveyed and mapped. Notices should be erected showing boundaries of watershed and other reserves where wood harvesting is not allowed.


A compartment is a permanent, geographically recognisable unit of forest land forming the basis for planning, prescription, implementation, monitoring and recording of forest operations. To the extent that it is practicable, areas of forest that are to be managed for different purposes, or have clearly different functions or values, should be placed in separately defined compartments. A compatibility matrix of forest functions that can be used as a guideline for determining compartment functions is shown in Tables 5 (a) and (b).

Practical guidelines for defining forest compartments are:

· Wherever practicable:

· Boundaries should be geographically recognisable, such as rivers, streams, ridges and gullies. Permanent roads and trails may also be used. Boundaries should be recorded on all forest management maps.

· Compartments should as far as possible comprise uniform forest types and be physically recognisable on the ground.

· Numbering should be sequential, usually commencing at a forest headquarters. Compartment numbers should not be changed.

· Compartments should not be so large that sub-division into numerous sub-compartments is required in order to achieve effective implementation of forest operations. Sub-compartmentation should be minimised. Flexibility is required in determining compartment size; a practical size range for many management situations is between 100 ha and 500 ha, depending upon the physical features of the forest and land.

Table 5 (a): Key For A Compatibility Matrix Of Forest Functions That May Be Used As A Guideline For Compartment Formation


Not Compatible

To Be Defined In Each Case

On All Slope Gradients

<50% Slope

<30% Slope




Key to abbreviations used in the matrix:

CLR = Customary land Rights
IPT = Industrial Tree Plantation
GSS = Reduced Impact ground Skidding
LDCCS = Long Distance Cable Crane System
NFM = Natural Forest Management
NWFP = Non-wood Forest Products

Compartment Records

Compartment records may either be constructed and maintained manually in a register, or on a personal computer using database software. Each record should have four main components, as follows:

· A summary of site conditions (soils, slopes, rainfall),

· Pre-harvest inventory data (species, tree numbers and volumes expressed by stem diameter classes),

· Dates and details of harvesting and silvicultural operations (selective harvesting, shelterwood cutting, thinning, climber cutting, enrichment planting, release weeding),

· Post-harvest inventory data (poles, saplings, seedlings, nucleus trees).

An example of a manually maintained compartment history record is shown in Table 6. The design should be modified to meet the requirements of local situations. One form should be prepared for each sub-compartment. The example shows how operations may be recorded. Each record should be accompanied by a compartment map; the scale can vary depending upon local conditions but suitable scales are between 1:5,000 and 1:10,000.

1.1.2 Mapping

Map Interpretation

Maps fulfil a wide range of functions in forest management depending on the type, the amount of detail of features represented and their scale. Map interpretation is the art of extracting from a map all of the information it contains for management purposes so that a "picture" can be drawn in the planner's or manager's mind of the shapes and slopes of the ground, the pattern of streams and rivers, the vegetation cover, and the location and nature of man-made features.

Map reading is best learnt by experience, in a forest or outdoors by comparing the detail of map symbols with the actual area of country they represent. Once an appreciation of a map and its symbols has been built up by comparison with a known landscape, this knowledge can be used to gain an understanding of an unknown area from a map. For example, by comparing the spacing of contour lines in a known locality with those in an unknown area, the relative steepness and alignment of slopes may be determined.

Table 5 (b): Compatibility Matrix of Forest Functions

Table 6: A Manually Maintained Compartment History Record

Forest Name:




Site Summary:

· Rainfall:
· Soils:
· Topography.

Pre-harvest Inventory Data:
· Forest Type:
· Inventory Date


Harvestable Trees (per ha)

Nucleus Trees (per ha)

Over 60 cm

Under 59 cm








Species A

Species B

Species C

Harvesting And Silvicultural Operations:

Completion Date

Area (ha)


e.g. 25 April 1993


selective harvesting; 7 sp/ha cut; skidder; x production = 45 m3/ha

e.g. 31 Sept. 1993


post-harvest assessment;

e.g. 20 May 1994


diagnostic sampling; 5%; leading trees -26; leading desirables - 87.

e.g. 28 July 1994


release weeding (cleaning);

e.g. 25 Feb. 1995


enrichment planting; 5 m strips; 150 sp/ha (species to be recorded)

Post-harvest Assessments:





Seed Trees

Damaged Trees






Stages in the Review of Maps for Practical Forest Management

There are two stages in the review of maps for forest management.

· Stage One: To identify and acquire published base maps of a forest area to be managed showing physical features, including settlements, villages, roads and other infrastructure, rivers and coastlines, contours, geology, soils, land uses, forests and agricultural vegetation type boundaries. Reports or notes which might accompany the maps should also be acquired. In many countries, the national series of topographic maps combine some of these features at scales of 1:50,000, (2 cm = 1 km), or 1:25,000 (4 cm = 1 km). Maps produced by triangulation control surveys at a scale of 1:100,000 may also be available.

· Stage Two: To review the maps that have been collected. The questions to be answered could include:

· Is the map coverage, map scales and physical detail on maps adequate for planning, zoning or operational purposes, such as recognition of forest boundaries, definition of major physical features (rivers, ridges) and definition of contours? Are they up-to-date?

· Which new maps are required for forest zoning (protection, production and other broad zones), for forest stratification and inventory, roading, for forest protection, community development and other purposes which might be related to specific forest management objectives? What map scales should be used?

· Where and through whom can relevant new maps showing the detail required for management purposes be prepared or acquired? What are the priorities in map preparation?

· How long will acquisition of new maps take? What are the requirements and estimated cost?

Primary Map Types and Scales for Planned Forest Management

Detailed mapping requirements for planned forest management will depend upon the goal and objectives for each forest management unit, determined through the review outlined in the previous section. As a general guide, the primary map types to be purchased, or drawn if they do not exist, for planning sustainable management for wood production should include the following:

· Essential Maps:

· Topographic map, showing primary geographic features, including contours; 1:50,000 or 1:25,000.

· Land use planning map, showing the forest management unit together with settlement, agriculture and other land uses; 1:50,000 or 1:25,000.

· Forest zoning map, showing zones for watershed protection, wood production, specific non-wood products, biological diversity conservation, recreation (or amenity) and any other primary forest zones; 1: 50,000 or 1:25,000.

· This map should be drawn as a part of the planning process, especially to determine the net productive area for wood production.

· Strategic planning forest harvesting map (felling blocks or felling series/compartments/roading); 1:50,000 or 1:10,000.

· Tactical planning forest harvesting map (felling blocks/topography); 1:10,000, 1:5,000 or 1:2,000.

· This map should be drawn as a part of the planning process.

· Reconnaissance forest map of merchantable tree species above a minimum dbh, e.g. > 50cm dbh, based on a low intensity forest reconnaissance; 1:50,000 or 1:100,000.

· This map, or maps, should be drawn progressively as a management plan is implemented.

· Forest inventory map (for continuous forest inventory), showing sampling strata/blocks and PSP positions; 1:50,000 or 1:25,000. This map should be drawn as a part of the planning process.

· Tree position/tree species/topographic maps, overlaid with road map, compiled through 100% pre-harvest inventory of each compartment; 1:10,000 or less. This is a series of maps that should be drawn regularly for compartments as a management plan is implemented.

· Desirable Maps:

· Cadastral map, showing legal ownership of land; 1:50,000.
· Geology map; 1:100,000, or less.
· Soils map; 1:50,000, or less.
· Contour map; 1:5,000 or 1:10,000.

These need not be the only map types for forest management and it is important that a forest manager should ask questions about mapping needs for each specific management situation. The following are examples:

· What other map types are needed that will assist a forest manager in implementing planned management objectives?

· Is a rainfall map necessary? Why?

· Would maps showing the location or distribution of specific, uncommon or endangered plants or animals be helpful? What scale should such maps be?

· Will maps showing the location of villages, areas where traditional food crops, medicinal plants or other products are gathered be managerially helpful? What is the most appropriate scale?

· Will maps showing localities having scenic, recreational or ecotourism value be helpful? Why?

1.1.3 Zoning

A mapping technique that provides a practical basis for planning the sustainable management of tropical forests where wood production and other values are present is forest zoning. Forest zoning is applied where multiple-uses occur and involves identification of the predominant values for specific areas of forest land that are to be managed in respect of management objectives that are related to those values. For example, steep slopes where serious soil erosion may occur if a part of a forest is roaded and logged could be placed into a watershed protection zone. Again, forest that is an important habitat for endangered plants or animals may be described as a biological reserve zone. Where significant environmental or social constraints are not identified an area of forest can be zoned for wood production.

Zoning is a critically important step in defining and locating the "net productive area" for wood production for a forest management unit. The wood production zone is determined by deducting the area of land which is "unproductive" from the total area of a forest management unit. "Unproductive" land does not, or will not, contribute to wood production; it includes agricultural land, roads, rivers and lakes, industrial areas, settlements and land that has been zoned for watershed and biological diversity conservation and for the conservation of forest used by indigenous people. The wood production zone forms the area basis for the determination of the Annual Allowable Cut, explained further in Part II, 3.6.

The process of identifying and describing forest zones is primarily a field activity which should be undertaken with the benefit of good on-the-ground knowledge, gained through observations in a forest by planning foresters, rangers and specialists. All compartments should be examined and the forest values on each compartment considered.

Each specific area of forest that is a separate zone should be placed in a separate sub-compartment, or a compartment if the zone occupies a whole compartment. Value judgements that are formed in the field and will form the basis of forest zones should be supported by inventory data. Forest zoning may be assisted through the use of a GIS that enables computer generated maps of zones to be drawn. A simple forest zoning scheme is shown Figure 9.

Common descriptions of the primary forest zones are set out below. Each may be sub-divided, depending upon local needs, into more specific zones:

Figure 9: Example of a Forest Zoning Map

· Wood Production Zone - where wood production is not bound by other forest values.

· Watershed Zone - where soil conservation and watershed values are dominant.

· Wildlife Conservation Zone - where forest forms an important habitat for specific animals.

· Biological Diversity Conservation Zone - where forest is ecologically important because it contains unusual and possibly endangered plants and/or animals.

· Amenity (or Scenic) Zone - where forest has landscape values in relation to highways, railways or towns where the forest is frequently viewed by people.

· Local Community Zone - where areas of forest are predominantly of value to the physical and spiritual well-being of local forest dependent communities. It can include burial grounds.

· Recreation Zone - where forest is used for public recreation, such as picnic, camping and trekking areas.

· Scientific Studies Zone - where forest is used, or might be used, for specific forest research studies. It may be linked to wildlife, biological diversity and watershed conservation zones.

Important questions that should be asked when undertaking zoning should include the following:

· What are the primary values, or characteristics, of each specific area of forest? Can the values identified be clearly described and can they form the basis of a zone?

· Can value judgements on possible zones be supported by good quality inventory and other technical data? What new data is necessary and how can it best be acquired?

1.1.4 Remote sensing imagery

The Practical Value of Aerial Photography

Aerial photographs are helpful for identification of geographic features and for orientation in the field. They are a practical tool for mapping rivers, ridges, coastlines, swamps and other geographic features. Where vegetation patterns are distinct, aerial photographs are valuable for recognising and interpreting forest types for zoning and stratification at an early stage in inventory planning. Aerial photographs are also useful for locating permanent sample plot positions, for reading, silviculture, forest protection, community settlement planning and for ecological research..

Commonly used and practical scales for black and white aerial photography are 1:20,000 and 1:25,000. Colour or black and white photography taken for specific purposes where greater detail is needed over limited areas is often at a lower scale such as 1:15,000 or 1:10,000.

Questions which should be asked by forest planners and managers when the practical uses of aerial photographs are being considered can include:

· Are recent aerial photographs (black & white, or colour) of a forest management unit available which can be used for detailed forest type mapping?

· Is the quality adequate for the purposes for which photography is being considered (e.g. clarity, cloud cover)?

· Is the coverage complete, or at least adequate, for the areas of a forest where planning interest is to be focused?

· Is the scale suitable for field interpretation for zoning, for recognition and definition of forest types and for other planning needs?

· Is specialist expertise and/or training needed in order that aerial photography can be used in the field effectively? What additional expertise and training might be required?

Satellite Imagery for Forest Management Mapping

Where photographic coverage is limited, or is difficult to obtain because of persistent cloud cover, satellite imagery is more useful than aerial photography for mapping. Good quality, up-to-date imagery and computer mapping systems can strengthen mapping quality and coverage. A mosaic mapping approach is often followed, where cloud-free sections of a series of satellite images are digitised to form a map base. Once formed, maps should be field checked and amended where required to ensure that they are both accurate and precise. Map formation using satellite imagery is a technically skilled task that should be carried out by a trained.

Global Positioning System Technology in Planned Forest Management

The Global Positioning System, or GPS, is a system of satellites orbiting the Earth which transmit precise time and geographic position information. Positions are updated continuously thus enabling speed and bearings to be computed with considerable accuracy, usually less than 30 meters in both latitude and longitude. Position information can be obtained quickly using a range of small, hand-held GPS receivers that can be operated anywhere on Earth, day or night, under any weather conditions. A limitation however is that GPS technology cannot be easily used beneath a forest canopy; "open- to-the-sky" conditions are necessary for the reception of satellite signals.

Although GPS technology cannot be used easily to determine geographic positions within a natural forest it still has several other useful management applications. Some of these are:

· For navigation along rivers, roads and tracks.

· For finding specific positions on a forest edge, such as PSP or research plot track entrances and forest landings.

· For monitoring the location and length of forest roads and tracks.

· In conjunction with formal boundary surveys, GPS data can be used for computer map generation. It is helpful for mapping recently built logging roads and tracks.

· GPS data can be included into GIS updates for the creation of new GIS data layers. In turn, these can be used for the creation of new maps. Positional accuracy is critical in providing optimal use of GPS collected data for integration into a GIS.

Several different commercially available GPS receivers can be purchased and their use is explained in manufacturer's handbooks.

1.1.5 Geographic information systems

The Role of Geographic Information Systems in Planned Forest Management

The term Geographic Information System, or GIS, is applied to the computerised storage, processing and retrieval of geographically referenced spatial data, such as various types of maps, and the corresponding statistical and other attribute information. The capability of combining different maps, known as "overlaying", is one of the most important GIS functions. Three-dimensional images can be generated from contours.

The greatest value of GIS in natural forest management is for modelling alternative technical options as an aid in decision-making. Modelling is a tool for analysis of trends and for identification of the factors affecting them, or for showing the possible consequences of planning decisions that affect forest resource use and management. Training of operational and planning foresters in the use of GIS is necessary in order to gain maximum value from this powerful planning tool.

Three examples of GIS capabilities having practical value in tropical forest management are:

· Integrating maps made at different scales, different projections, or different legends.

· Overlaying different map types for parts of a forest to make a new map by combining features of several separate maps. For example, a forest type map could be overlaid onto soil and rainfall maps.

· Generating three-dimensional (oblique) images of the positions of trees to be harvested, overlaid onto a landform map to assist with logging road location and design.

1.2 Land area in sustainable forest management

1.2.1 Practical methods for measurement of area from maps

A knowledge of area is a fundamentally important aspect of in the management of all tropical forests. Reliable area data are required for:

· Showing the size of a forest management unit, or any part of it.

· Expressing the area of forest types, scrubland, unproductive land, conservation and community development land, water surfaces and other land use categories.

· Deriving the annual allowable cut for the production zone, or net productive area, of a forest.

· Effective planning of forest protection, watershed conservation, silvicultural tending, rural community development and all aspects of sustainable forest management.

1.2.1 Practical methods for measurement of area from maps

The use of a planimeter and the dot-grid are two practical methods for office and field measurement of area from maps. Worked examples of their use are shown in Annex 2. Areas can also be derived by computer using a GIS.

Case Study 1: PT. Sumalindo Lestari Jaya: Batu Putih, East Kalimantan, Indonesia.

Mapping and remote sensing imagery used for map preparation, is firmly recognised by PT. Sumalindo Lestari Jaya as being fundamentally important for planned forest management. Some parts of the concession have an aerial photographic coverage but a high frequency of cloudy days and smoke during the dry season are prominent technical difficulties in not being able to acquire photographs more easily.

Satellite imagery is proving to be more useful than aerial photography because of good quality up-to-date imagery and availability of data processing systems. Satellite imagery can be delivered within a few days of ordering. A mosaic mapping approach is followed, where cloud free sections of a series of satellite images are digitised to form the map base. Extensive use is made of computer technology for map formation and it comprises the basis of the company's geographic information system. Twenty five different overlays are produced from digitisation of remote sensing imagery. Once formed, all maps are field checked and amended where required to ensure they are both accurate and precise. Computer-generated oblique topographic images upon which the positions of trees that can be selectively-harvested (over 60 cm diam, location determined from cruising) can be superimposed are a part of the GIS system. Oblique images greatly help logging planning, including making considerable savings in road construction and for minimising adverse environmental impacts associated with roading and logging

Planimeter Measurement of Area

A planimeter is an instrument for accurate measurement of irregularly shaped map areas. Older types have a fixed or adjustable pole, a tracer arm and a recording meter showing readings read on a vernier scale at the beginning and end of each measurement. Recently developed planimeters are electronic and show area data automatically for each measurement. Some digitise the measured area which can be transferred to a computer. Map readings are scaled up according to the map scale, as follows:

MA = PU* Ms2 * 0.00001


MA = mapped area in square metres
Pu = planimeter reading (number of units),
Ms = map scale.

Dot Grid Area Measurement

A dot-grid is a simple and easily used technique for measuring map areas quickly, either in an office or a forest. The transparent dot-grid sheet is placed on an irregularly shaped part of a map, such as a forest type, and the number of dots which occur within the area to be measured are counted. The map scale must be known. There are two procedures for converting an average dot count to area, as follows:

· Where a square grid has been printed on a map

Derive the area of each grid-square from the scale of the map. The area, in hectares, of a dot-grid count on a map is calculated as follows:

MA= (D/dc)* G


MA = mapped area in hectares
D = the average number of dots counted on the map,
dc = number of dots per cm2 on the dot grid
G = grid-square area (hectares).

· Where there is no grid-square on a map:

Derive the area of each square centimetre on the dot-grid, in square metres or hectares, according to the map scale as follows:

In square metres; Dcm = Ms2/1000 and in ha; Dha = Ms2/10000000


Dcm = area in square metres
Dha = dot-grid area (square metres or hectares respectively);
Ms = map scale

The area of a dot-grid count of an irregular area on a map, in square metres or hectares, is calculated using the following formula:

MA = (D/dc)* Dg


MA = map area in square metres, or hectares,
Dg = dot-grid area (square metres or hectares).
D and dc = Idem as before

The main limitation of the dot grid method is the error of the area estimates. It is desirable to take three or more dot counts of each map area being measured and the area is calculated from the average of the number of dots counted on each.

1.3 Forest inventory

1.3.1 Forest resources inventories for sustainable forest management
1.3.2 Types of forest inventories
1.3.3 Inventory objectives
1.3.4 A format for a harvesting and forest management planning inventory
1.3.5 Preharvest inventory (cruising)
1.3.6 Check cruising

1.3.1 Forest resources inventories for sustainable forest management

A wood resources inventory is always required to determine wood volumes, species, log qualities and utilization prospects for forest resources planning and for advertising reliable minimum estimates of volume for public bidding for concessions or licenses. Depending upon objectives, existing forest uses, forest composition and distribution, inventories may also be required for non-wood resources.

There are two levels of inventory:

· Planning inventories for the whole or a substantial part of a forest management unit, for example, an inventory of wood or of specific non-wood resources.

· Operational inventories at the level of the compartment, for example, pre-harvest inventories and diagnostic sampling.

The design and conduct of a wood resources inventory for a tropical forest is a detailed task and should always involve the knowledge and experience of inventory specialists. It is beyond the scope of these Guidelines to describe the detail of a wood resources inventory but some guidance is provided in Part II, 1.4 - Forest Growth and Yields. For specific guidance readers are referred to FAO Forestry Papers No. 27, Manual of Forest Inventory with Special Reference to Mixed Tropical Forests (1992) and No. 22/1, Forest Volume Estimation and Yield Prediction; Volume 1 - Volume Estimation (1980).

1.3.2 Types of forest inventories

Eight prominent types of forest inventory, each having their own objectives, are:

· Harvesting

· Pre-concession (for bidding)
· Logging planning
· Management planning.

· Management

· Growth studies
· Biodiversity surveys
· Social surveys.
· Post-harvest
· Diagnostic sampling

1.3.3 Inventory objectives

The main elements of a forest inventory depend very much upon the specific objectives of management. Objectives must be quite clear irrespective of whether an inventory is proposed for an existing forest management unit or for a new concession in order that results obtained from it will be supportive of those objectives. This point cannot be overemphasised. Three specific guidelines should be considered when determining inventory objectives:

· Objectives need to be determined jointly by the people who will use the results, including forest managers, planners and decision-makers, as well as by inventory specialists. Inventory objectives should not be determined by inventory specialists alone.

· Not all inventory objectives have the same level of importance.

Some have higher priority than others and it is the objectives having highest priority that should determine the inventory design and the presentation of results.

· Inventory objectives should consider the physical effort that will be required to conduct an inventory, the organisation, estimated costs and time, the existing knowledge of resources, the availability of specific aspects of inventory technologies and institutional capability. All have a direct bearing upon the implementation of an inventory. An overriding consideration is that an inventory must be practicable and achievable.

1.3.4 A format for a harvesting and forest management planning inventory

The following general format provides a basis for designing a forest inventory for the first time in a tropical forest where sustainable wood harvesting is proposed. It can be adapted for pre-concession harvesting and for management planning. Each inventory is unique and needs to be thoughtfully designed in order to provide information that will satisfy specific management objectives; there is no single inventory format that should be used.

Purpose of an Inventory

· Definition of inventory objectives in collaboration with the potential users of inventory results.
· Priorities for the objectives.
· Specialist needs for non-wood resources.

General Information

· Define the authority that will be responsible for planning and undertaking an inventory and indicate any other agencies that will cooperate with it.

· Assemble, existing and available information and data on the area to be studied based on earlier surveys, reports, maps and remote sensing imagery, as follows:

- a general forest description,
- variability of the parameters to be measured,
- topography, accessibility and transport facilities.

· Resources, including funding, personnel and physical support that will be available.

· Detailed inventory specifications;

- exact limits and area of the inventory,
- divisions that will be made within an inventory area,
- character of the resources information that is required,
-presentation of the inventory information,
- the level of precision, or reliability, that is required.

Inventory Design

· An outline of the inventory design,

· A general description of the various activities that will be undertaken, as follows:

- aerial surveys, interpretation of remote sensing imagery,
- mapping and area estimation procedures,
- sampling methodology to be applied,
- relationships that will be used for expressing estimated quantitative resources data, for example, volume tables.

Measurement Procedures

· A description of the design that will be used, covering both field and analytical activities. In particular, the area, shape, number and distribution of sampling units should be stated to meet specified levels of precision of the results.

· Procedures for interpretation of remote sensing imagery:

- detailed instructions on the use of techniques and procedures,
- staffing requirements and descriptions of duties,
- instruments that will be used.

· Field organization, as follows:

- field crew requirements, organization and duties descriptions,
- transportation arrangements,
- camping guidelines or instructions,
- definition of arrangements for logistical support.

· Field procedures, as follows:

- location of sampling units,

- establishment of sampling units,

- measurements on sampling units,

- instruments that will be used and instructions for their use,

- measurements of tree stems (for wood inventories) or of parts of trees such as foliage, bark or fruit (for non-wood forest products inventories),

- other measurements or assessments, such as insect damage, tree mortality, soil conditions or seed production,

- the design of forms and how observations will be recorded.

Data Compilation Procedures

· Detailed instructions on data processing from both remote sensing imagery interpretation and from field sampling, as follows:

- mathematical formulae that should be applied for computing means and sampling errors,

- the relationships that should be used for converting imagery or forest measurements into desired expressions of quantity, for example, individual tree volume tables.

· Calculation and data compilation methods that should be used, as follows:

- descriptions of procedures to be followed, for example, specific computer software and programs,

- detailed descriptions of all phases of data processing, including data transcription from field forms (or from field computers), verification, data computation, preparation of summaries and database management.


· Report outline,
· An estimate of the time required for reporting,
· Responsibilities for report preparation,
· Printing method,
· Number of copies that are expected to be required,
· Report distribution.

1.3.5 Preharvest inventory (cruising)


In practical terms, a 100 percent preharvest inventory of commercially harvestable trees in a mixed species tropical forest is best planned within the framework of the strategic harvest plan which, itself, is derived from an approved forest management plan. The role of this harvest plan is explained in Part II, 3 - Management Planning.

A preharvest inventory should be based on a specific prescription set out in an approved management plan and also in the harvest plan. Cruising involves the following specific steps:

· A topographic survey and an inventory of potentially harvestable trees (compulsory and optional under the concession) and of trees that should be excluded from the harvesting for environmental and/or conservation reasons.

· The overall area where harvesting is planned should be defined using compartment maps, on a scale of 1:50,000, or a lesser scale, depending upon the area to be harvested. Where compartments are not clearly defined, one kilometre square blocks (100 ha) are a practical starting point for planning a preharvest inventory.

Case Study 2: The Main Features of the Forest Inventory System in Sabah, Malaysia



1. Design

Type of inventory

Systematic layout.

Sampling size

600 - 700 plots per management unit of 100,000 ha.

Plot size

Combined sample plots with 4 different sizes (0.25, 0.04, 0.0025 ha & soil profile pit).

Sampling error < 5% (95% probability level).

2. Accuracy

3. Field work

Field crew

6 persons (1 forest ranger, 2 foresters, 3 labourers).


10 - 13 plots per crew per month.

4. Data processing


FoxPro (databank system)


User-friendly, menu driven for data entry, editing

checking, processing and printing of results

5. Costs

US$2.40/ha (based on a forest area of 100,000 ha).

(Source: Kleine & Heuveldop, Forest Ecology & Management, Vol. 61, 1993.)

· The inventory should be designed and implemented in adjoining, parallel strips, 20 to 70 metres wide, through the forest where harvesting is proposed. The width of the strips will depend on factors such as slope or gradient which determine the ease or difficulty of working through a forest.

· The orientation and length of inventory strips and their relationship to forest type boundaries, roads and tracks should be determined in the office by planning foresters and the inventory team leader. It is desirable that inventory strips be aligned on the inventory planning map to cross ridges, hills and other topographic features but should also be based upon their personal knowledge of the forest. A strategic harvest planning map and aerial photographs, if available, should be used for inventory planning.

Cruising Team

The cruising team, four to six people in number, should comprise a team leader, tree cruisers (measurers), tree identifiers and field survey workers. If the cruising team is in the field for several days, it should also include porters and cooks.

Good Cruising Practice

Essential aspects of good cruising practice are:

· A clearly defined and accurately located access track should be cut that will form the centreline of each inventory strip.

· The traverse distance of each cruise strip should be measured continuously by tape from the strip origin as the cruising team works along it. Marker lines should be cut through undergrowth on the edges of strips, the outer line of one strip marking the inner edge of the next, parallel strip. Strip widths should be regularly checked by tape, at least every 100 metres of traverse distance.

· Topographic contours, tree positions and tree numbers are mapped by sketching on pages of graph paper as the cruise proceeds along the length of a cruise strip. Each graph paper record of the inventory should be associated by appropriate numbering with the tally sheets. Both form a permanent record of the inventory.

· Sketch mapping of tree positions and topography on graph paper is a practical procedure and allows tree positions, contours and streams to be digitised for recording in a GIS. In association with remote sensing imagery, sketch mapping helps in the preparation of detailed topographic maps of specific areas to be harvested in the near future. An example of a tree distribution and topography map compiled from field sketch mapping and tree cruising of Dipterocarp forest in East Kalimantan, Indonesia is shown in Figure 10. The scale is 1:1,000 and the width of each cruising band is 20 metres. Tree positions are marked as triangles and are numbered, corresponding to numbers in the cruising book. Species codes are entered into each "tree triangle."

· The location and density of climbing plants, including rattan, which might need to be cut in a pre-felling treatment, should be noted by the cruising crew.

· Only commercial species and tree sizes (heights and minimum stem diameters) should be measured in a pre-harvest inventory.

· Tree measurement data should be tallied on booking sheets as the cruise proceeds. Although this is a simple procedure it requires care to ensure that tree identity and measurements are accurate and are correctly recorded. Data can also be tallied into a hand held field computer which enables data to be downloaded later into an office computer for processing.

· If practicable, the approximate tree falling direction should be marked on the tree base using an arrow or line in order to assist the cutter.

Tree Labelling

Tree labelling requirements are:

· Trees that are mapped and measured should also be labelled, numbered and recorded, using differently coloured waterproof plastic labels for trees to be cut and for "mother" trees (also called seed or nucleus trees) which are to remain and be protected from harvesting. Paint can be used to mark tress but it tends to disappear in a short time depending mainly on weather conditions, making re-repainting necessary. Trees that are to be harvested must be very clearly marked on the ground and located on a map which should be carried constantly by the sawyer, as a reference, in order to make sure that the right trees are cut down.

· The name, or a locally determined identity code for each species, and the estimated log dimensions of trees that are to be cut are tallied against a tree number, as follows:

- on a tally sheet which forms part of the inventory record,

- on a tree label, plastic or aluminum, using a permanent felt-tipped pen or a hard tip device, respectively. Labels should be brightly coloured (yellow or red) and preferably having a "tear-off duplicate section. The identity code, tree number and log dimensions are repeated on the duplicate section of the label.

· The species identity code that is marked on the tree label should also be marked in the "tree triangle" on the graph paper record.

· Mother, or nucleus trees, which are not to be cut, must also be located on the map, and labelled on the ground using a differently coloured label. Again, the locally determined identity code for each species, and the estimated log dimensions of trees are tallied against a tree number. This label will remain as a permanent mark on each mother tree and the sawyers should be aware of this.

Tree Tallying and Volume Calculations

Tree tallying and volume calculations requirements are:

· Tree species, dimensions (especially stem diameter) and tree condition (forking, decay, etc) are tallied and volumes calculated in the office using a calculator or a database software computer system. Readers are referred to FAO Forestry Paper No. 22/1 (1980), Forest Volume Estimation and Yield Prediction; Vol. 1 - Volume.

Figure 10. Cruising Map Showing Tree Distribution, Contours and Part of a Proposed Road Line.


- triangles and circles show tree location, circles denoting harvestable trees.
- a number within a circle or triangle are species codes.
- a number beneath the triangle or circle is the booking number.
- the parallel dotted lines are the edges of 20 metre wide cruising strips, the curved lines are contours
- the three heavy lines mark the alignment of a new roadline.

(Source: Pt. Sumalindo Lestari Jaya: Batu Putih, East Kalimantan, Indonesia) Scale: 1:1,000

Case Study 3: PT. Sumalindo Lestari Jaya: Batu Putih, East Kalimantan, Indonesia.

PT. Sumalindo Lestari Jaya conducts its own pre-harvest inventory and does not engage local consultants. The cruising team, about eight in number, comprises a team leader, tree cruisers (measurers), tree identifiers, field survey workers and porters/cooks. Each team spends up to a month in the bush but is in periodic contact with HQ through visits made by trekkers who bring food, other supplies and retrieve field data.
The work of cruising teams is field checked at random by company supervisory staff and also by provincial forestry officials. Forest is cruised in 20 metre wide parallel strips, trees are mapped, labelled and numbered, using coloured waterproof plastic labels for trees to be cut (red) and for nucleus trees (yellow). Topographic contours and tree positions/numbers are sketched on graph paper as the work proceeds along each 20 m strip. This is a practical arrangement as it allows tree positions to be digitised and also assists in the contour definition of topography, in association with remote sensing imagery. Although tree positions are estimated in relation to the edges of cruising strips and the traverse distance (the distance walked by the cruising team along each strip), it is unlikely that trees are more than three or four metres from true positions.

· Computer methods are to be preferred over the use of calculators for processing inventory data because of their ease and efficiency for handling large amounts of data, the ability to undertake comprehensive data analysis and because data can be entered directly into and used in a GIS. Specialist assistance from foresters having a sound background in the application of computer technology in forestry is necessary.

· Estimation, for detailed descriptions on tree volume estimation, especially the use of tariffs, for indirect measurement of forest volumes from stem diameter measurements.

Pre-harvest Inventory Field Manual

The foregoing guidelines should be adapted to the local prevailing conditions on a forest management unit and be incorporated into a pre- harvest inventory manual to provide clear and readily accessible guidance to field workers.

1.3.6 Check cruising

An essential feature of every preharvest inventory is random checking of the work of a cruising team. Known as check cruising, it should be carried within two or three weeks of a pre-harvest inventory by a team led by a planning forester. Where a forest management unit is being managed by a concession holding company or an NGO on behalf of customary landowners, check cruising should be undertaken by a team comprising company or NGO supervisory staff. Government forestry officials should make separate field checks, at random, on the pre-harvest inventory where forest land is in State ownership.

Check cruising should involve monitoring of sections of inventory strips selected at random. All aspects of inventory practice are examined, as follows:

· Inventory strip traverse distances and widths.
· The identity of trees to be harvested and reserved as mother trees.
· Tree labelling and numbering practices.
· Tree measurements and tree condition assessments.

The extent of checking will depend upon the confidence limits imposed by a forestry authority or set by a concession company. As an easily understood and practical guideline, two per cent of the area traversed by a pre-harvest inventory should be check cruised and the following checking standards applied:

· Where more than one team is conducting pre-harvest inventories, the work of all inventory teams should be checked.

· The area of a section of an inventory strip that has been selected at random for a check cruise should be within 95 per cent of the actual area measured by the check cruise team.

· The identity of trees should be correct for 95 per cent of all trees examined in the check cruise, that is, 19 trees in 20 should have been correctly identified.

· All trees meeting species and stem diameter criteria for harvesting or for reservation as mother trees must have been recognised, labelled and measured in a pre-harvest inventory.

· There should not be more than a+/- 5 per cent difference between the pre-harvest inventory and the check cruise for stem diameter measurements and volumes calculated from these.

Check-cruising data must be processed in exactly the same way as the pre-harvest inventory in order that valid comparisons can be made. Consistent differences between a check cruise and a pre-harvest inventory should be examined to determine the reasons for this. They should also be discussed with the cruise team leader and members with a view to eliminating any differences.

1.4 Forest growth and yield

1.4.1 The components of forest growth in tropical forests
1.4.2 Sampling and measurement of forest growth and yield

1.4.1 The components of forest growth in tropical forests

A knowledge of forest growth provides a confident basis for the measurement of increment which can be used to derive wood yields for a production forest. Growth data are also required for planning operational aspects of management, for technical and for economic studies. In these Guidelines only the most basic methods for measuring tropical forest growth are described in order to show the main stages involved and to encourage forest managers to take the first steps for making growth measurements from which forest yields can be derived. Readers are referred to specialized references listed at the end of this chapter for details.

Growth in a mixed tropical forest comprising a large number of species has three separate components:

· Individual tree increment,
· Mortality, or the death of trees,
· Ingrowth (or recruitment), the growth of new trees into measurable size classes from regeneration.

Forest growth relationship can be expressed as follows:

G={(Itrees * n)-(M+ Re)}/n


G = the net forest increment, usually expressed as m3/ha/yr.

Itrees = the sum of increments of trees, usually expressed as m3/ha/yr., that survive during a specified measurement period.

M = the volume of trees that have died during a specified measurement period and no longer contribute to net forest growth.

Re = the volume of ingrowth, or recruitment, measured at the end of a specified measurement period.

n = period in years.

Measurements of ingrowth and mortality are as important in determining net forest increment as are measurements of tree growth. Tree growth and forest growth in a tropical forest cannot be equated as they can be in plantations. The methods used for growth measurement and prediction of wood yields have four components:

· Measurement of growth and estimation of yield.
· Making of a yield model and fitting it to growth and yield data.
· Testing of the yield model for its validity.
· Application of the model to the required end-use.

Apart from the measurement of growth and estimation of yield, other components will require the assistance of technical specialists in forest mensuration and yield modelling. The basic features of sampling and the measurement of growth and yield are explained later in this chapter. Technical references listed at the end of this chapter explain the methodology.

1.4.2 Sampling and measurement of forest growth and yield

Four Basic Components of Forest Sampling

There are four basic aspects of forest sampling for the measurement of growth and yield which should be considered during management planning and in plan implementation. These are:

· Define the "Yield": Be quite specific and clearly define what the yield is intended to be. The "yield" could be the volume of wood of specific trees, or the wood volume of the whole forest, or it might be non-wood products, or it may be a mix of wood and non-wood products.

· Permanent Sample Plot Design: The design of PSP system will be determined by the definition of the yield and should also consider the most effective way of measuring the yield. Permanent sample plots are used for the measurement of wood growth and also to measure the growth of non-wood products.

· The Sampling Pattern for Permanent Sample Plots: Sampling can either be systematic or random. Irrespective of forest variability, it can be more important to achieve an adequate number of sample plots, using either systematic or random sampling, than it is to aim at achieving pre-determined sampling intensity.

· Regular Remeasurement of Permanent Sample Plots: The establishment and regular remeasurement of permanent sample plots throughout the forest over a long period of time is essential. This practice monitoring the effect of site variation on forest growth and the real effects of log harvesting operations to be measured and included within a yield model.

Continuous Forest Inventory

Continuous forest inventory means the measurement of forest growth and development through making repeated measurements of trees in permanent plots. CFI provides a record of growth in volume and of changes in other forest variables over time. Data on forest growth are needed for the construction of yield tables and growth models which may be used, together with current inventory data, for growth and yield forecasting and for yield regulation. Continuous Forest Inventory comprises a network of regularly measured permanent sample plots; it provides the most reliable data for estimation of:

· Changes in the characteristics of forest stands over time.

· Variations in forest composition and productivity with site and silvicultural treatment.

· The relationships between tree variables, stand variables and increments which may be used for yield forecasting.

· Long-term changes in the site and its continuous productive capacity.

The closeness of the results actually gained from CFI to true values will depend on the sampling method, on variability within a forest and on the sampling intensity. The variability of a forest after the first logging operation should be determined using a pilot field study in respect of tree volume, the growth variable having greatest commercial and planning significance.

Permanent Sample Plots

Permanent sample plots are permanently defined areas of forest that are periodically but regularly remeasured to provide data on stocking, tree dimensions and volume. Information on changes in the composition, structure and growth of a forest over time can be derived from PSP's.

Sampling Designs

Systematic sampling and random sampling designs can be used for setting out a network of permanent sample plots.

· Systematic Sampling: It is a square or rectangular pattern where plots are established on grid format. It has the advantages that it is simple to design and implement in a forest and the plot coverage is uniform. The systematic sampling design is shown diagrammatically in Figure 11. It has the disadvantage that it does not include stratification. Systematic samples may have bias, caused by any uniform natural variation, such as hills, and by the layout of the grid. Sampling error of variables (from which confidence limits are derived) cannot be determined in systematic sampling.

Figure 11: Systematic Sampling Design for Locating PSPs in a Forest

· Stratified Random Sampling: Stratified random sampling is an effective, and practical procedure for tropical forests which allows reliable confidence limits to be calculated for tree and other forest variables. There are two designs, unrestricted stratified random sampling and two-stage stratified random sampling. An example of this type of sampling is shown diagrammatically in Figure 12.

· Unrestricted Stratified Random Sampling:

- Unrestricted stratified random sampling involves sub-division of a forest into several uniform or near uniform zones, or strata, on the basis of ecological, geographical or administrative similarities. Major forest types, or groups of compartments, are examples of sampling strata. Strata are permanently defined on a management inventory map.

Figure 12: Stratified Random Sampling for Locating Pairs of Plots Within Sampling Blocks in a Forest

- Strata should be as small as possible and may involve subdivision of major strata into smaller and more uniform sampling zones, such as specific forest or site types.

- Strata should be large enough to enable at least two permanent sampling plots to be located at random within each stratum without increasing the number of plots beyond the sampling intensity target of the inventory. Two or more plots are necessary within each stratum to allow confidence limits of the volume estimate to be calculated.

· Two-stage Stratified Random Sampling:

-Two-stage sampling is a variant of stratified random sampling which has the benefit of enabling limited staff and technical resources to be focused on particular areas thus helping to reduce the costs of the CFI programme.

Stage One: The primary sampling units are defined as for stratified random sampling. Units are called blocks, not strata. An objective sample is then made of the blocks by listing these and selecting at random from the list.

Stage Two: The selected blocks are sub-sampled with PSPs being located at random (or systematically). - A combination of two-stage sampling with stratified pairs of PSP's is a practical and efficient design for a CFI. It has the disadvantage that only selected, not all, blocks are sampled and therefore it cannot be used as a part of a forest management monitoring system.

Pilot Survey for Deriving Permanent Sample Plot Numbers

If there is insufficient growth information about a particular forest from earlier inventory data then an ad hoc pilot study, involving five, six or more temporary one hectare plots, should be carried out to derive the coefficient of variation for volume to provide a guide to the PSP sampling intensity. The coefficient of variation for volume is calculated because volume is the variable of greatest management interest. The number of PSPs required to achieve a specified level of precision in an inventory can be calculated from the equation:

PSP's = (CVv/p2)


PSPs = Number of PSP's required
CVv = Coefficient of variation for volume,
p = the acceptable limit of precision, e.g. for 5%, p = 0.05.

Because the study is made once, it is unable to indicate a coefficient of variation for growth over a period of time. Detailed guidance on the calculation of the coefficient of variation, standard error and confidence interval of the mean volume is described in Annex 3. Other methods are described in references at the end of this chapter.

As a general guide and based on experience in several tropical forests, 50 -100 randomly distributed plots, each of 1 ha, are likely to be adequate for acquiring growth data over areas of several thousand hectares, or several compartments within one stratum, or several blocks in two-stage sampling. Initially, one plot for each 100 - 150 ha of forest will probably be sufficient, depending on the uniformity of the forest, intensity of silviculture applied and the precision of growth data required.

Plot Size and Shape

The most efficient plot area is a compromise between the total forest area sampled and the physical effort needed to establish, maintain and regularly remeasure plots. The aim is to minimise the plot edge to area ratio. The most efficient plot size in any particular forest will depend on inventory objectives, the level of precision required, forest variability and the costs of PSP establishment, maintenance and remeasurement. One hectare square plots are widely used in many tropical forests, with the following advantages:

· They are easily subdivided into 25 sub-plots of 0.04 ha, or 100 sub-plots of 0.01 ha, for sub-sampling within a plot.

· They represent values per hectare for stocking and other measured parameters, thereby avoiding conversion problems.

· They provide good representation of species diversity.

Square plots have the following advantages:

· They have shorter boundaries than an equal area of strips, thus reducing the effort and cost of plot establishment and maintenance. The shorter boundaries will reduce errors which might be caused by trees located on plot boundaries.

· Square plots are easier to locate than strips without introducing bias and are less likely to be interfered with by tracking or roading. Edges and boundaries of square plots are easier to relocate than circular plots.

· Square plots are more practical to establish and maintain in many tropical forests than are circular plots. It is impractical to set out large circular plots accurately in dense vegetation because trees near the plot boundary cannot be seen from the centre. Circular plots cannot easily be sub-divided into sub-plots.

The following guidelines can assist in the establishment of square plots:

· They should be numbered to ensure that tree data will be systematically recorded for each plot at establishment and at each remeasurement.

· Each plot should be laid out as five adjacent 100 m long strips, each 20 m wide. Each strip is laid out 10 m to the left and 10 m to the right of a centre line.

· Each strip is divided into 10 m long sections giving 25 square sub-plots, each of 0.04 ha, in each 1 ha PSP.

· Once a starting point has been determined, the centre lines should be cut in E-W or W-E directions on flat land using a compass for direction. On sloping land centre lines may be cut across the contour.

· Sub-plots are numbered from the NW comer of the plot in the sequence of proposed measurement.

· Pegs are placed on each strip centre line at 10 m intervals to mark the limits of each sub-plot. Each is numbered sequentially.

· Distances indicated are horizontal distances. On sloping land, the actual distance should be read from a slope reduction table after measuring the slope using a clinometer.

When each PSP is established the exact plot area, corrected for slope, should be calculated. The following basic site information should also be recorded:

· Latitude, longitude and altitude.
· Aspect, slope, soil profile.
· Monthly rainfall and temperature data (from the nearest meteorological station).
· Forest history and past forest use.

Plot Subdivisions

Small quadrants, or sub-plots, should be permanently laid out during plot establishment to ensure that a plot can be fully covered at each assessment with the minimum number of trees being missed. Plot subdivisions help each tree to be found easily, to ensure uniform distribution of crop or potential crop trees that are to be measured and to allow tree measurements to be checked. Each quadrant should be numbered in the plot records.

A quadrant size of 20 m × 20 m (0.04 ha) is a useful size for measuring a selection of trees on a plot. A 10 m × 10 m quadrant (0.01 ha) allows for assessment of potential stocking of final crop trees and, in practice, is the minimum size for locating and relocating saplings.

Plot Location and Access for Growth Sampling

Initial plot location should be determined on a management inventory map in the office. Plot location in stratified random sampling is derived from random numbers which define two coordinates for each plot. Random numbers can be derived from random number tables, by using the random number generator available in many calculators or by using spreadsheet software (use the @RAND function) in a personal computer.

If a pair of coordinates fall outside the boundaries of each stratum they are rejected and the next pair are selected. A plot position should also be rejected if it falls wholly or partially in an unproductive vegetation type or on unproductive ground, such as a road, river, rocky land or an industrial site; these are unproductive areas from a yield determination point of view. The plot should be rejected if it falls within 100 m of the nearest edge of a previously selected plot.

When plot positions have been determined they should be mapped and written as field instructions (bearings, distances and be marked on aerial photographs) to guide the field workers to each plot site. Plot comers, boundaries and sub-plots should be permanently defined using posts which should be clearly visible.

Each plot should be carefully located by survey on a management inventory map, including survey of the access track from a roadside or a clearly defined physical point of reference. Survey helps with plot relocation. Access tracks and roadside notices should be clearly defined and maintained. Mounds and corner trenches help to define the location of plot boundaries and access lines.

Tree Numbering

Each tree within a sub-plot for which a long-term measurement record is made should be permanently numbered to enable individual tree increments, plot growth, recruitment and losses to be calculated. It is impractical to derive a long-term record of individual tree growth, tree mortality and recruitment without making repeated measurements on individually numbered trees. Numbers should be attached to trees using a combination of non-rust labels and scribing, depending on the characteristics of bark, wood and tree size.

Tree Diameter Measurements

Measurement of tree diameters is an important variable for determining forest growth, and care is needed to ensure that an accurate tree measurement history is assembled. Successive tree diameter measurements should be taken at the same point on a tree, 1.3 m above ground (the dbh point), using a diameter tape that measures diameter directly, not girth. The dbh point should be paint marked on each tree or, where paint does not hold permanently to bark, by using a galvanised nail holding a tree number label. Trees which are buttressed or branched at the dbh point should be marked at a permanently defined, and painted, point on the stem and buttress.

Measurements of recruitment and mortality are recorded by comparing tree counts between successive remeasurements. Detailed information about sapling and seedling numbers and species can be collected by PSP sub-sampling.

Plot Remeasurement Interval

The interval between PSP remeasurements depends upon tree growth rate. A new plot should be remeasured after a shorter than normal interval in order to capture the growth data the measurements will provide. The longer the interval between measurements the more accurately tree increments can be determined. As a general guide the remeasurement interval for many tropical forests is three to five years but the plot remeasurement interval should be determined for a specific forest in respect of the prevailing local conditions.

Data Processing and Database Management

Data processing and the management of inventory data are specialized topics and are not explained in these Guidelines. Readers are referred to publications listed at the end of this chapter for detail on these topics. FAO Forestry Papers No. 22/1 & 22/2, Forest Volume Estimation and Yield Prediction; Vol. 1 - Volume Estimation; Vol. 2 - Yield Prediction (1980) and Oxford Forestry Institute, Tropical Forestry Paper No. 30, Growth Modelling for Mixed Tropical Forests (1995) are especially helpful. Computer systems using commercially available database software are essential for data processing and storage. Statistical and spreadsheet computer software should be used for growth modelling and yield prediction.

Inventory and Database Administration

Administrative office support for forest inventories and database management should be as carefully organized as are other aspects of forest management. The planning and practical implementation of inventories and the processing of inventory data is a forest operation, comparable with protection, harvesting, silviculture and other forest operations.

The practical steps required for inventory and database administration are:

· Appointment of a senior forester responsible for inventory, database management and yield modelling activities.

Case Study 4: Growth Studies in the Tapajos National Forest, Brazil

Successive inventories of a silvicultural experiment in rain forest within the Tapajos National Forest in Brazil have been examined to provide guidelines for operational forest management on a sustainable basis. The study site was logged in 1979 using chainsaws and attempts at directional felling. On average, logging removed 75 m3/year from 16 trees/ha, all over the felling limit of 45 cm dbh. There was no additional silvicultural treatment, but the site was protected from further logging and encroachment ('log and leave'). Thirty six PSPs established in 1981 were remeasured in 1987 and 1992. Logging had changed the canopy structure and altered the composition of the stand, reducing the number of shade tolerant species and stimulating the light demanding species.

There was a net increase in stem number and stand basal area during the 11 year observation period, and this trend also holds for most of the individual species. The stand basal area 13 years after logging was about 75% of that in a comparable unlogged forest. Logging stimulated growth, but this effect was short-lived, lasting only about three years, and current growth rates are similar to those in the unlogged forest. Between the first and second measurements, average diameter increment decreased from 0.4 to 0.2 cm/year, mortality remained relatively constant at 2.5% per year, while recruitment (at 5 cm dbh) decreased from 5 to 2%. Total volume production declined from approximately 6 to 4 m3/ha/year, while commercial production remained about 0.8 m3/ha/year. New commercial species increased the commercial volume in 1992 from 18 to 54 m3/ha, and the increment of 1.8 m3/ha/year.

Results from this experiment provide the first quantitative information for management planning in the Tapajos Forest, and may guide the choice of cutting cycle and annual allowable cut. Silvicultural treatment to stimulate growth rates in forest areas zoned for timber production should be considered as a viable management option. Extrapolations of these results to an anticipated 30 to 35 year cutting cycle must be interpreted with caution. On-going remeasurement and analysis of these and other plots over the next 30 years are necessary to provide a stronger basis for their use in management planning.

· Adequate long-term funding for salaries, logistical support, staff training, equipment and other arrangements to enable an inventory programme to proceed efficiently.

· Thoughtful planning of all aspects of inventory and database management, including objectives, technical design, staffing, logistical arrangements and time schedules.

· Appropriate in-company or external training of all personnel who are involved in inventory and database management.

Personnel Training for Continuous Forest Inventory

It is essential that both planning and field personnel involved with inventories be technically well qualified for the exacting role they have in PSP establishment, data collection and plot remeasurement. Basic qualifications and practical experience in forest mensuration, map reading and tree identification are essential. Equally important is the need for periodic training and retraining of staff in the use of new and existing techniques to ensure that high standards of tree and plot measurement practice are maintained.

1.5 Diagnostic sampling

1.5.1 The purpose of diagnostic sampling
1.5.2 Benefits
1.5.3 Diagnostic sampling methodology

1.5.1 The purpose of diagnostic sampling

Diagnostic sampling provides information on the condition of a forest. Such information can then be used to determine forest management interventions required before or after logging or after silvicultural treatments have taken place. It is a practical field sampling method for collecting information on forest composition, structure and potential productivity before or after selective harvesting, that can be used for making realistic and ecologically sound decisions on silvicultural tending.

Diagnostic sampling aims to look forward in time and to visualise and project the development possibilities for future crops, based on the species, spatial distribution and size of individual trees that are already present. It is not a detailed regeneration survey, a botanical or ecological survey, nor a wood resources inventory and its aim is to provide a quantitative estimate of the silvicultural conditions of a forest.

1.5.2 Benefits

Diagnostic sampling has the following benefits:

· It can establish priorities for commencing silvicultural tending in different forest types where sustainable management is planned.

· It provides information for defining forest types and stand structure and for determining an appropriate initial sequence and design of silvicultural operations.

· It can provide an estimate of the likely cutting cycle in relation to ingrowing size classes of commercially desirable trees.

· With experience, it is a simple and rapid procedure to apply and the results are not difficult to interpret.

1.5.3 Diagnostic sampling methodology

Selection of a "Leading Desirable"

The primary feature of diagnostic sampling is the recognition and selection within a small sample area of one Leading Desirable (LD) within a sample area, usually a plot of 10 × 10 m or 0.01 ha. The "Leading Desirable" is the "best" tree or sapling present. It is the tallest and with the largest dbh of a desirable species present in the sample plot in terms of its potential value as a future crop tree. Furthermore, the "Leading Tree" must have a: dbh of at least 5 cm but not greater than the predetermined "minimum cutting diameter"; (b) straight bole of 4 m long or more, without defects, malformation, decay and large knots and (c) vigorous and well formed crown. Being oriented towards future harvests, diagnostic sampling should include Leading Desirables only up to the minimum cutting diameter. This can vary, depending upon forest type and species. In many forests a minimum cutting diameter between 50 - 60 cm is adopted although it is advisable to determine it by species or groups of similar ones.

Practical Application

Diagnostic sampling can be applied in unlogged, previously logged and in secondary forest. It can be applied before or immediately after logging or at intervals after this operation has been completed. Sampling should be based upon the use of temporary systematically located plots within selected compartments or sub-compartments. The field procedure is rapid and the work involved in setting out and assessing the forest in each temporary plot usually takes only a few minutes. The practical sampling unit of 10 × 10 m or 0.01 ha leads to the widely used number of 100 evenly-spaced potential final crop trees per hectare. This is a convenient standard against which actual stocking may be compared. In most forests, a commercially viable and sustainable harvest of logs is usually less than 100 stems per hectare and consequently this figure provides an allowance for natural mortality. The sample plot area is related to the predicted, or expected, optimum stocking.

The steps involved in conducting diagnostic sampling are as follows:

· Define a List of Commercially Desirable Tree Species

Prior to any field work a list of commercially desirable tree species should be compiled jointly by planning foresters, wood utilization and marketing specialists. The species must be ranked in order of priority, preferably by groups of similar species, before sampling and should not be changed during field sampling. Tree identification during sampling must be accurate and carried out by a reliable observer.

· Define Criteria for Selection of a "Leading Desirable"

The criteria for defining and selecting a Leading Desirable need to be set out before field sampling commences, usually by government forestry officials. Defining criteria for selection of a Leading Desirable is particularly important where the forest to be assessed comprises a wide range of species having variable growth rates and variable stem and crown form. Selection criteria for a Leading Desirable can be adapted to the characteristics of each specific forest management unit. A list of criteria for defining "Leading Desirables" are summarized in Figure 13.

· Field Sheet Design

Field sheets should be designed in the office before sampling and the design should be improved from time to time with the benefit of experience. A flexible approach to design is suggested, depending upon the characteristics of the forest being sampled, but the field sheet should provide spaces for making the following additional entries:

Figure 13: Criteria for Defining "Leading Desirables"

· Define a list of commercially desirable species;

· Define tree types:




10- 19 cm dbh.

20 - 29 cm dbh

5 - 9 cm dbh

less than 4.9 cm dbh and more than 30 cm high.

30 - 39 cm dbh

40 - 49 cm dbh

50 - 59 cm dbh

Over 60 cm dbh

· Define stem quality for commercially acceptable species

- current log, -future log, deformed, rejected and decayed steins

· Forest name, compartment, sub-compartment and plot numbers, date:

Commercial species

- stem quality for a future log (10-39 cm, upper stem)
- rejected stems (deformed, damaged, decayed)

Non-commercial species

- stem quality for a current log (40 cm +, butt log)
- stem quality for a future log (10-39 cm, upper stem)
- rejected stems (deformed, damaged, decayed)

Depending upon the local conditions the field sampling form could make provision for recording information on trees having non-wood forest products potential. This information may have planning value in respect of the interests of local communities. It could include:

· Species name, dbh, crown illumination class, stem condition (acceptable, deformed, damaged, decayed),

· The characteristic of interest, for example, fruit, foliage and resins.

An example of a field form (entries are in some boxes) is shown in Table 7. It can be adapted to specific local conditions by a user.

· Define the Area to Be Sampled

If available, select aerial photographs covering the area to be sampled, and using a photo marking pencil or crayon, the broad limits of the area of interest. Mark existing roads, ridges, tracks or other features that can be used for gaining access and enable a survey team to recognise its position on the ground. Select maps, preferably at a scale of 1:10,000, covering the area defined on aerial photographs and make copies for use when sampling in a forest.

· Plot Location and Establishment for Diagnostic Sampling

The following guidelines are suggested:

· Plots should be adjacent to each other and located in either strips or blocks. Strips, or blocks, can be 100 m to 200 m apart, depending on local forest conditions, and should be aligned to cross the topography. A sample strip could be 5 m wide on either side of a centre line and 10 m in length along the strip.

· Experience indicates that a minimum of 100 plots should be established but a larger number is preferable.

· Another widely followed guideline is to sample between 3 and 5 per cent of the area of the forest selected to be surveyed.

· Selection and Recording of Information on a Leading Tree

Identify and record information on one "Leading Tree", if present. A "Leading Tree" has a diameter larger than the minimum cutting diameter. Record whether it is a commercial or non-commercial species and the stem quality (good, deformed, damaged or decayed). If more than one tree greater than the minimum diameter is present, select and record information on the best one, in terms of species and stem quality.

Table 7: An Example of a Diagnostic Sampling Plot Form

Forest Name:



Plot No:

Compartment/Sub-compartment No:

LEADING TREES: (larger than the minimum cutting diameter; ONE only)


dbh: (cm)

e.g. 58.2

Quality of the Best Potential Log: (tick one)

Commercially Acceptable

Not Commercially Acceptable

Stem Quality:

Stem Quality:

Current Log.Ö

Current Log.

Future Log. Ö

Future Log.

Rejected Stems:

Rejected Stems:







LEADING DESIRABLE: (less than the minimum cutting diameter; ONE only)






No Leading Desirable

tick one®




dbh: (cm)

e.g. 32.3

Crown Illumination Class: (tick one)

Full Vertical & Lateral

Full Vertical

Partial Vertical





· Selection of a Leading Desirable

Examine the vegetation on each plot and determine which tree meets the criteria for selection as a "Leading Desirable". It can be either a tree, a sapling or a seedling. Plots that do not contain a "Leading Desirable" are recorded as being unstocked. The procedure is explained in Figure 14.

· Record Data on the Leading Desirable

Record two types of data, as follows:

· The dbh of the "Leading Desirable".

· The crown illumination class of the "Leading Desirable" using the following set of classes.

- full vertical and lateral illumination (top and upper sides of a crown are emergent and fully exposed)

- full vertical illumination (the whole of the top of a crown is exposed but the crown is not emergent)

- partial vertical illumination (small parts of the top of a crown are exposed, other parts are shaded by other trees)

- oblique (small parts of the upper sides of a crown are exposed)

- indirect (no direct exposure of the crown at all).

· Summarise Data

Field data can be summarized using a calculator or, preferably, a personal computer using commercially available database or spreadsheet software. Although a summary should reflect the specific data collected, the following headings are a guide for presenting information:

· Leading Trees:

- species and per cent of trees > minimum cutting diameter,
- number of trees/ha,

· Leading Desirables:

- per cent and dbh classes of trees and saplings
- species and number of LD/ha,
- percent of seedlings
- distribution of crown illumination, type of LD and dbh classes.

Figure 14: Example of the Steps Involved in the Selection of a Leading Desirable.

Step One: The plot contains a TREE meeting the following criteria for selection as a Leading Desirable:

· it is the best (and often the tallest or having the largest dbh) among the commercially trees present,

· it is 10 cm dbh, or larger, but is less than the minimum cutting diameter,

· it has a single, well-formed trunk, containing one straight section at least 4 m long, free of defects, large knots or deformations,

· it has a well formed, vigorous crown.

Step TWO: The plot does not contain a tree meeting the criteria for a Leading Desirable listed in Step One, but it does contain a SAPLING meeting the following criteria:

· it is a merchantable or commercially acceptable species,

· it has a dbh between 5 cm and 9.9 cm,

· it has a single straight trunk, taller than 30 cm, that is free of defects, deformations and heavy branches,

· it has a vigorous and well-formed crown.

Step Three: The plot does not contain a sapling meeting the criteria for a Leading

Desirable listed in Step Two, but it does contain a SEEDLING meeting the following criteria:

· it is a merchantable, or commercially acceptable species,
· it has a height not greater than 30 cm,
· it has a stem not greater than 4.9 cm dbh,
· it has a single, straight, defect free stem,
· it has a vigorous crown.

Step Four: The plot does not contain a tree, sapling or seedling meeting the criteria for a Leading Desirable. It is technically unstocked.

· If the plot is assessed to be "potentially productive" (soils, proximity to plots having a Leading Desirable, vegetation similarities) this should be recorded.

· If the plot is located on a site assessed to be "permanently unproductive" (rock, permanent water, swamp) and is unlikely to ever support productive forest this should be recorded.

Silvicultural Decision-making

The results of diagnostic sampling should be used for making decisions on the priorities for silvicultural tending in different forest types, for determining an appropriate initial sequence and design of silvicultural operations, including the intensity of liberation thinning, and the need for, the extent and density of enrichment planting. The following guidelines are suggested:

· Results of sampling should be plotted onto compartment maps and entered into compartment records. This allows areas of forest having similar characteristics and topography to be defined and where similar silvicultural treatments can be applied.

· For practical reasons, the areas defined should be reasonably large, for example, at the scale of a sub-compartment.

A silvicultural decision-making structure, based on the results of diagnostic sampling, is shown in Figure 15.

Figure 15: A Silvicultural Decision-making Structure Following Diagnostic Sampling.

1.6 Further reading

Alder, D. 1992. Simple Methods for Calculating Minimum Diameter and Sustainable Yield in Mixed Tropical Forest in "Wise Management of Tropical Forests". Oxford Forestry Institute, University of Oxford.

Alder, D. 1995. Growth Modelling for Mixed Tropical Forests. Tropical Forestry Paper No. 30, Oxford Forestry Institute, University of Oxford.

Alder, D. and Synnott, T. J. 1992. Permanent Sample Plot Techniques for Mixed Tropical Forest. Tropical Forestry Paper No. 25. Oxford Forestry Institute, University of Oxford.

Brasnett, N. V. 1953. Planned Management of Forests. Alien & Unwin, London.

Catinot, René. 1997. The Sustainable Management of Tropical Rainforests. General Secretariat, Association technique internationale des bois tropicaux, ATIBT. Paris.

Cedergren, J. 1996. A Silvicultural Evaluation of Stand Characteristics, Pre-felling Climber Cutting in a Primary Dipterocarp Forest in Sabah, Malaysia. Swedish University of Agricultural Sciences, Umeå.

Davis, K. P. 1966. Forest Management. Second Edition. McGraw-Hill Inc., USA.

Dawkins, H. C. 1958. The Management of Natural Tropical High-Forest with Special Reference to Uganda. Imperial Forestry Institute; University of London.

FAO. 1980. Forest Volume Estimation and Yield Prediction; Vol. 1 - Volume Estimation; Vol. 2 - Yield Prediction. Forestry Paper No. 22/1 & 22/2, Rome.

FAO. 1984. Intensive Multiple-Use Forest Management in Kerala. Forestry Paper No. 53, Rome.

FAO. 1985. Guidelines for Sustained Yield Management of Mixed Dipterocarp Forests of South East Asia. Field Document No. 8, Project GCP/RAS/106/JPN, Bangkok.

FAO. 1988. Geographic Information Systems in FAO. Rome.

FAO. 1989. Management of Tropical Moist Forests in Africa. Forestry Paper No. 88, Rome.

FAO. 1989. Review of Forest Management Systems of Tropical Asia. Forestry Paper No. 89, Rome.

FAO. 1992 (first printed 1981). Manual of Forest Inventory with Special Reference to Mixed Tropical Forests. Forestry Paper No. 27, Rome.

FAO. 1993. Management and Conservation of Closed Forests in Tropical America. Forestry Paper No. 101, Rome.

FAO. 1993. Common Forest Resource Management - an annotated bibliography of Asia, Africa and Latin America. Community Forestry Note No. 11, Rome.

FAO. 1994. Mangrove Forest Management Guidelines. Forestry Paper No. 117, Rome.

FAO. 1995. Planning for Sustainable Use of Land Resources: towards a new approach. Land and Water Bulletin No. 2, Rome.

Ford-Robertson, F. C. (Ed). 1971. Terminology of Forest Science, Technology Practice and Products: Multilingual Forestry Terminology Series No. 1. Society of American Foresters, Washington, D.C.

Freese, F. 1962. Elementary Forest Sampling. US Dept. Agriculture Handbook No. 232.

Howard, A. F. & Valerio, Juvenal. 1962. A Diameter Class Growth Model for Assessing the Sustainability of Silvicultural Prescriptions in Natural Tropical Forests. Commonwealth Forestry Review. Vol 71 (3/4).

Husch, B. 1971. Planning a Forest Inventory. FAO Forestry Series No, 4. and FAO Forestry and Forest Products Studies No. 17. Rome.

Hutchinson, Ian D. 1991. Diagnostic Sampling to Orient Silviculture and Management in Natural Tropical Forest. Commonwealth Forestry Review, Vol. 70 (3), No. 223.

Hutchinson, Ian D. 1993. Puntos departida y muestreo diagnóstico para la silvicultura de bosques naturales del trópico húmedo. CATIE. Serie Técnica. Informe Técnico No. 204. Colección y Manejo de Bosques Naturales No. 7.

Johnston, D. R. Grayson, A.J. Bradley, R. T. 1965. Forest Planning. Faber & Faber, London.

Kleine, M. Heuveldop, J. 1993. A Management Planning Concept for Sustained Yield of Tropical Forests in Sabah, Malaysia. In "Forest Ecology and Management". Vol. 61, pp. 277-297. Elsevier Science Publishers, Amsterdam.

Kofod, E. O. 1982. Standtable Projections for the Mixed Dipterocarp Forest of Sarawak, Malaysia. Field Document No. 9, FAO Project MAL/76/008, Forest Department, Kuching.

Leuschner, William A. 1984. Introduction To Forest Resource Management. Virginia Polytechnic Institute & State University. John Wiley & Sons.

Lugo, A. E. & Lowe, C. 1995. Tropical Forests: Management and Ecology. Ecological Studies 112, Springer, Berlin.

Mayers, J. Howard, C. et al. 1996. Incentives for Sustainable Forest Management: A Case Study in Ghana. IIED Forestry and Land Use Series No. 7, IIED, London.

Pancel, L. [Ed]. 1993. Tropical Forestry Handbook. Springer Verlag, Germany.

PCARRD. 1985. Technical Publication No. 58, The Philippines Recommends For Dipterocarp Production, Philippines Council For Agriculture and Resources Research and Development, Manila.

Schmidt, P. & Schotveld, A. [Eds] 1996. Sustainable Management of the Guyana Rain Forests. Proc. of a Seminar on Management Systems of Tropical Forests. Wageningen.

Snedecor, G. W. & Citron, W. G. 1967. Statistical Methods. Iowa State UP.

Spurr, Stephen H. 1952. Forest Inventory. The Ronald Press Company, New York.

Synnott, T.J. 1979. A Manual of Permanent Sample Plot Procedures for Tropical Forests. Tropical Forestry Paper No. 14. Commonwealth Forestry Institute, University of Oxford.

van Assen, B. W. 1996. Community-based Sustainable Timber Production in the Tropics: a preliminary survey of experiences and issues. National Reference Centre for Nature Management. Wageningen.

Vanclay, J. K. 1991. Review: Data Requirements for Developing Growth Models for Moist Tropical Forests. Commonwealth Forestry Review. Vol. 70 (4), No. 224.

Vanclay, J. K. 1994. Modelling Forest Growth and Yield: Applications to Mixed Tropical Forests. CAB International, Wallingford.

Vanclay, J. K. et al 1995. Growth and Yield of A Tropical Rain Forest in the Brazilian Amazon 13 Years After Logging. Forest Ecology and Management, Vol. 71 (3).

Vanclay, J. K. 1996. Lessons from the Queensland Rainforests: Steps towards Sustainability. Journal of Sustainable Forestry, Vol. 3 (2/3).

Wenger, K. F. [Ed] 1984. Forestry Handbook. Wiley & Sons, New York.

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