Software for management and economic analysis of

1
Software for management and economic analysis
of forest plantations
Edilson Batista de Oliveira
[email protected]
SisPinus
P.taeda
P.elliottii
P.caribaea hond.
SisBracatinga
Mimosa scabrella
SisEucalipto
E.grandis
E.urograndis
E.dunnii
SisAcacia
Acácia mearnsii
SisAraucaria
Araucaria angustifolia
SisCedro
Toona ciliata
SisTeca
Tectona grandis
Planin
Economic analysis
Foto: Rodolfo Buhrer
2
Index
1.
Introduction.........................................................................................................................4
2.
Who uses this software suite? ..........................................................................................5
3.
Forest management.............................................................................................................6
4.
The software.........................................................................................................................6
5.
Data required for simulations.............................................................................................7
6.
Dominant Height and Site Index.........................................................................................9
7.
Volume equations...............................................................................................................11
8.
Taper equations..................................................................................................................12
9.
Thinning...............................................................................................................................13
10.
The software: step by step.................................................................................................14
10.1.
Simulation............................................................................................................14
10.2.
Inventory..............................................................................................................17
10.3.
List options..........................................................................................................19
10.4.
Thinning...............................................................................................................20
10.5.
Equations............................................................................................................22

Site equations.................................................................................23

Volume equations...........................................................................23

Taper equations..............................................................................24
Editing or inserting equations.........................................................25
10.6.
Log diameter and stock.....................................................................................26
10.7.
Catalogue............................................................................................................28

Products........................................................................................28

Formulas.......................................................................................29
10.8.
Carbon................................................................................................................30
10.9.
Results................................................................................................................32

Example 1....................................................................................32

Saving............................................................................................34

Printing..........................................................................................34
10.10. Illustrations........................................................................................................35

Hart-Becking Index or Relative Spacing Index ........................36

Percent of Maximum Population Density - Reineke.................36
3
11.
Diagram of Management Density - DMD........................................................37
11.1.
Diagram of Management Density in the Software.......................................40

12.
Example 2...............................................................................42
Others................................................................................................................46
1.
The Manual..............................................................................46
2.
Economic Analysis – Planin..................................................47
3.
Production Systems...............................................................49
4.
Taper Equations......................................................................50
5.
Video........................................................................................51
6.
About the software.................................................................51
11.
Statistical basis of simulations....................................................................................52
12.
Site classification tables .............................................................................................55
1.
Black wattle (Acacia mearnsii).................................................55
2.
Araucaria (Araucaria angustifolia)...........................................55
3.
Bracatinga (Mimosa scabrella).................................................56
4.
Australian red cedar (Toona ciliata).........................................56
5.
Eucalyptus (grandis and urograndis) ......................................57
6.
7.
Eucalyptus dunnii.....................................................................57
Honduras Pine (Pinus caribaea var hondurensis)....................58
8.
Slash Pine (Pinus elliottii).........................................................58
9.
Loblolly Pine (Pinus Taeda)......................................................59
10.
Teak (Tectona grandis).............................................................59
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1. Introduction
The software suite presented herein is the result of almost three decades of scientific
research. The programs were developed to fulfill significant demand for such products in
the forestry sector, considering that forest management practices conducted without a
solid scientific foundation are likely to lead to substantial waste of economic resources
and environmental damage.
The work has relied on the unwavering support of forestry companies that look to
technology to help define suitable management regimes for their plantations. These
companies have collaborated by making available their inventory databases that track
growth and production in their forests.
Each software, called ‘Sis’ followed by the popular name of the species or the genera
(SisAraucaria, SisPinus, SisTeca, etc.), describes forest growth and production
according to management regimes defined by the user. The software Planin provides
parameters for the economic analysis of forest production.
The objective of the software suite is to inform rural producers about suitable technologies
that can be used in the planning and management of forests and provide information that
can help optimize production and increase revenue.
Through the software, users can consider various climate and soil conditions and test
options for forest management, predict current and future production, conduct economic
analyses, and finally, implement the best alternative in the field.
The software possesses a flexible process of data entry and integration. Simulations can
be done for forest thinning with estimates of annual population growth and production and
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sorting of wood by diametric class for multiple uses of both the thinned trees and the final
harvest.
Because the software allows the quantification of wood according to type of end use, the
producer can manage wood production within forests directed at the most profitable
market.
“Production Systems” for each species, developed by Embrapa Forestry, can be accessed
directly or through links in the software. Through these guidelines, users can find a wide
range of techniques to be used in production, from seedling production to harvest and
commercialization.
2. Who uses these systems?

Companies and institutions in various sectors, particularly those working in
forest management and strategic forest planning.

Organizations, such as outreach organizations (rural technical assistance
companies), environmental institutions, cooperatives, municipal secretariats,
unions and associations have used these systems to provide technical
assistance and support the implementation of reforestation incentives.

Universities and Technical Colleges, in teaching, research, and outreach.

Independent Professionals.

Rural producers, independently or through technical assistance.
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3. Forest management
Unlike agricultural crops, forests do not possess fixed production systems. Each
population requires a specific type of management that involves various treatments, with
thinning of various types, intensities, and periods, and variations in the age of final
harvest. These treatments vary in relation to factors such as: end use of the product, site
quality (soil, climate), genetic composition of the population, spacing, and density. If one
of these factors is modified, the ideal management regime could also change.
These factors are important for the following reason: the rate at which trees grow in a
forest plantation increases competition among individuals for water, sunlight, and
nutrients. As such, thinning of the forest is conducted to reduce excess competition, while
looking to generate income for the producer. The most common strategy is to remove the
trees of inferior quality (suppressed, bifurcated, crooked, and diseased). When
competition returns to a high level of intensity, a new thinning must be conducted by
removing lines of trees or individuals and preserving the trees of the highest quality.
4. The software
To operate the simulations in “Sis”, the user provides the forest inventory data and the
software predicts growth and production, calculating the quantity of wood the forest would
produce at any age. The software can also simulate thinning and test any management
regime that the user would like to apply to the population (Figure 1).
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Volume
Semdesbastes
a
c
b
Comdesbastes
IDADE
Figure 1. Schematic showing growth in volume as a function of age for a forest with thinning
(a, b, and c) and without thinning.
The software suite supports decision making related to:
when, how much, and how to thin the forest,
and when to conduct the final harvest.
The programs show:
forest growth and production,
production by diameter class,
and volume of wood for each type of end use (Figure 2).
Altura
DAP
Diâmetro
mínimo
Diâmetro
mínimo
30cm
20cm
Toras I
Figure 2. Trunk divided into log types.
Toras II
Diâmetro
mínimo
10cm
Toras III
Lenha
8
The software suite can also calculate the biomass and carbon pool of trees, based on
equations entered by the user. In the case of black wattle, for example, the user can
estimate the bark weight.
The Planin program was developed to incorporate economic analyses into the
simulations, thus enabling predictions of both biological and economic variables. In
combination with the Sis programs, Planin allows for a rapid configuration of scenarios for
forest production planning with the goal of optimizing wood production and increasing
financial returns.
Planin enables the calculation of economic-financial parameters and the analysis of the
profit sensitivity to different rates of attractiveness. The program considers diverse
segments of operational costs involved in planting, maintenance, and forest exploitation.
As a result, it estimates cash flow, sensitivity analysis, and other frequently used
economic-financial analysis criteria. Furthermore, it enables the user to track costs and
produce reports of annual expenditures.
5. Data required for simulations
1. Minimum configuration: Site index, number of trees per hectare, and age
of forest.
2. Complete configuration: Site index, number of trees per hectare, age of
forest, and average diameter or basal area per hectare.
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6. Dominant Height and Site Index
Tree growth is directly affected by LOCAL or SITE characteristics (soil and climate).
Therefore, the site index is a measure of the potential productivity of the site, or the
capacity of an area to support the growth of a specific species.
The quality of the site can be evaluated using the height of the dominant trees (Dominant
Height).
The most common definition of Dominant Height considers the average height of the 100
trees with the largest diameter in a hectare. Another definition considers the average
height of the 100 tallest trees in a population or the average height of 20% of the trees
with the greatest diameter or greatest height. In practice, it is common to calculate
Dominant Height as the average height of the four tallest trees, or the four trees with the
greatest diameter, in a sample plot of 400 m².
In forest science, the Site Index (S) is the most practical and widespread method to
determine levels of site quality using the dominant height variable and an age of
reference (e.g., 15 years). As such, the higher the ‘S’, the greater the production capacity
at that site. To obtain ‘S’, we can use graphs, as shown in Figure 3, or Site Tables, as
shown in Table 1 for Tectona grandis, based on the equation:
3.0339[(1/ Age)
H = S {e
0.53
(1/ 15)0.53 ]
} , where H is the Dominant Height and S is the Site Index.
For example, considering the growth information for Tectona grandis (Figure 3), if the
Dominant Height at 5 years is 11 meters, the Site Index (at 15 years) would be 19.5
meters. In looking at Table 1, if the Dominant Height at 8 years is 12 meters, the SI (at 15
years) would be 16 meters.
10
33,0
30,6
30,0
29,1
27,5
27,1
27,0
26,1
24,5
24,0
24,4
24,3
Altura Dominante (m)
23,1
21,0
22,0
21,6
19,5
18,8
21,2
20,6
20,2
18,5
18,1
18,0
16,4
15,0
13,8
14,3
17,0
17,2
16,1
15,0
14,5
13,3
14,2
12,4
12,2
12,0
12,0
11,0
10,1
9,6
9,0
8,2
6,8
6,0
3,0
0,0
0
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Idade (anos)
Figure 3. Dominant height as a function of age in different site index types for Tectona grandis.
Table 1. Site classification table for Tectona grandis
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The software suite possesses Site Equations that can be substituted with other equations
available in the literature or for those developed by the user. The equations represent
average dynamic growth behavior for each species in the growing regions of Brazil. This
does not mean “average production” because the same equation could describe both low
and high growth values, depending on the Site Index.
The Site Classification Tables corresponding to the equations used in the software are
presented at the end of this manual.
7. Volume equations
The most simple equations to estimate tree volume or forest plantation volume are based
on: tree diameter (D) at 1.3 m above ground level, or DBH (diameter at breast height); the
height of the tree (H); and the form factor (f), obtained by dividing the actual volume of the
tree by the volume of a cylinder with diameter D and height H. As such, a model of the
volume equation (v) is:
V  0.7854. f .D 2 H
The more cylindrical the trunk, the closer the form factor will get to 1.0. An araucaria of
advanced age, for example, can obtain a form factor greater than 0.8. As the form factor
tends to increase with age, the software allows for the inclusion of this variable. In
SisAraucaria the expression is V = 0.7854.( 0.35 + 0.004.Age ).D 2 H . In this case, the form
factor at 20 years is 0.43 and at 40 years, it could be 0.51.
8. Taper equations
The taper equations (or log taper equations) describe mathematically the longitudinal
profile of a tree trunk. They permit the construction of volume tables for different log
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dimensions as set by the market. Using these tables, we can calculate separately, with
mathematical methods of partial integration, the volume for laminate, sawlogs, pulp and
fuel from the diameters and lengths of the logs, as specified by the user.
The following model is frequently used for volumetric calculations of logs from forest
plantations:
2
3
di
h 
h 
h 
h 
 b1  i   b2  i   b3  i   b4  i 
D
H
H
H
 
 
 
H
4
where:
h
di
= relative diameter and i = relative height
H
D
D = DBH or diameter at breast height (D1.3m) and H = total height of tree
di = diameter measured at height hi of the trunk
b1 to b4 = coefficients.
hi
The model can also use (1- H ) instead of
hi
H
. Although these two expressions
generate graphs with opposite directions, they describe the longitudinal profile of the
trunk in a similar way (Figure 4A and B). The software uses the second expression
(Figure 4B). To convert one model to the other, a program can be accessed from the
‘Other’ menu.
1,2
1
Diâmetro relativo
Diâmetro relativo
1,2
0,8
0,6
0,4
0,2
0
1
0,8
0,6
0,4
0,2
0
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
0
0,1
0,2
Altura relativa
A
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
Altura relativa
B
hi
Figure 4. Longitudinal profiles of a trunk using the variables H
hi
and (1- H ).
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9. Thinning
Thinning allows for a reduction in the number of trees per area, thus providing trees with a
greater amount of space as they grow. One method of thinning involves the preservation
of the best trees, eliminating those that are suppressed, bifurcated, broken and those with
symptoms of disease or extensive damage from pests. Well planned and executed
thinning increases the likelihood of obtaining a high quality final product, increases the
economic profitability of the population, as well as allows the producer to receive some
economic return before the final harvest.
The methods that can be used for thinning a population include:

Systematic: when trees are removed using a chosen, fixed regime,
depending on the available stand. For example, the removal of an entire
line of trees, with other lines of trees remaining intact;

Selective: in this case, the smallest trees in the population are removed
(low thinning). Both the diameter as well as the height can be used as a
variable in choosing the trees to be removed;

Mixed: this method integrates both types described above by first
conducting a systematic thinning and subsequently a selective thinning in
the remaining tree lines.
The thinning process should promote the use of space available in the population, while
avoiding the formation of gaps. As such, smaller trees that have potential for growth
should be maintained. When choosing the age, type, and intensity of thinning to be
applied, the producer should consider various factors, especially the management
objectives and the maximization of economic profitability. Each population may require a
specific type of management, including thinning and variations in age at final harvest. The
most appropriate forest management strategy, considering thinning, varies in relation to
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factors such as: a) site quality (soil, climate); b) genetic material of the planted population;
c) initial spacing within the plantation; d) actual density; and e) the intended end use of
production material. When any of these factors are altered, the ideal management regime
may change as well.
10. The software suite: step by step
10.1. Simulation
When opening the software, the Simulation screen appears showing a summary of the
information to be processed. The screen also contains a menu that provides access to all
the data entry screens.
Along the top and left hand side of the screen, there are toolbars with nearly all the menu
items needed to access the most common commands. The toolbars are context specific;
therefore, during some tasks, some of the buttons may be hidden.
The horizontal bars on the screen allow you to switch quickly between the “Data Entry”
and “Results” screens. A click on one of these toolbars results in an immediate screen
change.
15
16
If the operation system being used is LINUX, click on ‘File’ (Arquivo) to see the options in
the toolbar (green column).
The first step in entering data is to provide the Site Index in the appropriate text box. This
index forms the basis for the software environment in relation to forest production
potential, which enables it to produce accurate results for both good and bad sites.
You can also enter a brief description to identify the simulation:
The button Verify, on the right of the screen, enables you to verify the data to ensure they
have been correctly entered before beginning the simulation process. By clicking on the
button Calculate, the software will both verify and run the calculations.
At the bottom of the screen, the section called Results provides the tables and graphs
resulting from the data provided.
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10.2. Inventory
The menu item Inventory is nested under Simulation.
In the Inventory screen, you can input the population data you would like to include in the
simulation, as well as the level of homogeneity of the population.
You must choose one of the three forms of inventory available on the screen. The Site
Index is always required.
Number of trees planted per hectare:
This option assumes that the data provided corresponds to a recently planted forest, or a
forest that has not yet experienced much growth. In the appropriate boxes, indicate the
number of trees planted per hectare and the rate of survival in the first year. The rate of
survival only has an effect on the initial number of trees and does not have a direct impact
on any other moment in the simulated life of the forest.
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Number of trees per hectare at a defined age:
The available input parameters are: number of trees per hectare and age of the
population. In choosing this option, the previous data input option is deactivated.
Number of trees per hectare and basal area or quadratic mean diameter at a defined age:
The available input parameters are: number of trees per hectare, age of the population,
and basal area or quadratic mean diameter. This data input option is the most complete,
resulting in a more precise and accurate simulation.
Homogeneity index of the population:
This parameter, which allows an input ranging from 1 to 10, provides some flexibility in the
method used to calculate homogeneity. It can be based on statistical analyses (such as
variance and coefficient of variance) or on empirical measurements. Clone plantations do
not always have a value of 10 because the parameter considers not only the genetic
variability, but also the site variability.
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10.3. List options
In this screen, you can provide the ages for which you would like to obtain results.
Two options are available to format the generated list. For the first, provide the Starting
Age (or age at inventory) and the Final Age (age at final harvest). The beginning of the list
will always start at the age of inventory. The software will not show previous ages.
On the List option screen, the required input includes planting (Starting Age = 1), final
harvest (Final Age = 22), and interval of assessment (Interval = 1). If you would like to
assess longer intervals, for example every three years, provide this information in the text
box (Interval = 3). To obtain results for specific ages, use the Age List option where you
can indicate the desired ages, separated by a space or comma.
On this screen, you can also indicate the End-Use Diameter Class Intervals. This value
defines the DBH classes for the Stock Production Table, in the Results menu. A value of
‘2’ indicates that volume tables will be generated using 2 cm DBH diameter classes.
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10.4. Thinning
On the Thinning screen, navigation options appear for the first time. These navigation
tools are also used in other screens in the software related to formulas or lists of records.
The navigation tools are used to move from one record to another and to edit records
(add, delete, edit).
Button
Hot key
Description
[Up]
Positions the cursor in the previous listed record
[Down]
Positions the cursor in the next listed record
[Insert]
Insert a new record before the current record
[Ctrl+Delete]
Exclude the current record
[Up] or [Down]
Confirm the edited data
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To apply a thinning, click on the ‘+’ and the following screen appears:
Provide the Age, Type, and Intensity of the desired thinning.
The thinning Intensity can be input as Basal Area or Number of Trees per Hectare. In both
cases, indicate the amount that should remain in the population after the thinning. In other
words, indicate what is left after thinning, not what is to be thinned.
For Type, if the Systematic followed by selective thinning option is chosen, first provide
the Line to be thinned (systematic), followed by the population that should remain after
the application of selective thinning in the lines that were not removed. In the screen
above, the value 5 indicates thinning of one line of trees every five lines. The value 1000
is the number of trees remaining, or those that are not to be removed during selective
thinning.
22
After completing this process, if the thinning regime was changed, a summary of the
results of the previous thinning will appear on the screen.
To include other thinning episodes, return to the previous screen and click on the ‘ + ’
button again; to delete a thinning, select the thinning from the list and click on the ‘ – ’
button.
10.5. Equations
In this set of menus, you can specify the equations to be used in the calculations.
The buttons located on the right of each equation allow access to the equations available
in the Formula Catalogue.
23
To verify or alter the model that is being used, click on the button to the right of each item
and the following screens will appear:


Site Equation
Volume Equation
24

Taper Equation
On the Taper Equation screen, input the squared integral of the taper equation. To obtain
this integral, click on the Other button on the top horizontal toolbar, and choose the option
‘Taper Equation’. A previously configured spreadsheet is available for this calculation.
In the second textbox called ‘Expression’, the equation must be added and the letter D
(representing DBH) should be included as a multiplier of the expression, as shown in the
screen above.
The letter ‘X’ represents the Relative Height as (1-
hi
) (see section 8).
H
25
Edit or Insert Equations
In order for an altered equation to be saved, you must click on SAVE or SAVE AS. If you
do not save the alteration, the edited equations will be lost when the software is closed.
The following rules apply to expressions used in the ‘Equations’ as well as ‘Catalogue’.
They are:

Operator norms
A+B*C equals A+(B*C)
A*B^-C equals A*(B^(-C))
A*B/C equals (A*B)/C
A-B+C equals (A-B)+C
A+B*C differs from (A+B)*C

Spaces cannot be used
A+B is a correct expression
A +B is an incorrect expression.

The expression accepts constants in all formats as well as floating points.
.
The separation character is ‘ ’ (period).
1
3.141593
6.02E23
5.67E-8
0,1
500m

valid
valid
valid
valid
invalid
invalid
The following functions are valid within expressions:
SIN(X)
COS(X)
TAN(X)
COTAN(X)
SINH(X)
COSH(X)
ARCTAN(X)
EXP(X)
LN(X)
LOG10(X)
LOG2(X)
SQR(X)
SQRT(X)
ABS(X)
TRUNC(X)
INT(X)
CEIL(X)
FLOOR(X)
MAX(X, Y)
MIN(X, Y)
POWER(X, Y)
LOGN(X, Y)
ZERO(X)
SIGN(X)
HEAV(X)
INTPOWER(X,Y)
Seno
Co-seno
Tangente
Co-tangente
Seno hiperbólico
Co-seno hiperbólico
Arco tangente
Exponencial
Logaritmo natural
Logaritmo base 10
Logaritmo base 2
Quadrado
Raiz quadrada
Valor absoluto
Truncamento
Truncamento
Inteiro imediatamente maior
Inteiro imediatamente menor
Maior número entre X e Y
Menor número entre X e Y
Potência (X^Y)
Logaritmo de X na base Y
Retorna 1 se X = 0 e 0 em caso contrário
Retorna 1 se X > 0, -1 se X < 0 e 0 em caso contrário
Retorna 1 se X >= 0 e 0 em caso contrário
Potência inteira (X^TRUNC(Y))
26
10.6. Log diameter and stock
This menu item allows you to calculate the productive output of thinnings and the final
harvest. This output is calculated by segmenting trees into logs for different end products,
with dimensions indicated by the user.
To add or remove log types, use the navigation tools by clicking on ‘ +’ or ‘-’ as described
above in the Thinning section.
Indicate the desired end products (for example, laminate, sawlogs, pulp, or fuel) and the
dimensions of each: Diameter of Smallest Extremity (cm) and Log Length (meters). Also
indicate the Market Price and the Percent Annual Increase, which can be accessed using
the Planin software.
27
In the case of logs that do not have restrictions on dimensions (generally fuel), put a value
of 0 (zero) in the fields Diameter and Log Length. If not specified, the software will not
show product from the tip of the tree, but the tip will be included in the total production
output presented in the thinning and final harvest tables.
The button ‘Catalogue...’, in the top right corner, offers options to import ‘Log types’ from a
previously created list. Click on the button to see the names of all log types available. To
import a type, select one from the list and click ‘OK’. To import all types at once, you can
click on ‘All’.
In the following example, the Sawlog type will be imported:
To ensure any changes made are saved, you must click on SAVE or SAVE AS. If you do
not save the changes, they will be deleted when the program is closed.
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10.7. Catalogue
In the Catalogue menu item, you can insert and alter ‘Formulas’ and ‘Products’, as well as
save them to ensure quick access and use during processing. This registry provides an
organized and flexible system to allow you to work with many products and equations. An
unlimited number of options can be included, with the goal of meeting the specific
conditions of each simulation.
Alterations to the catalog are not used in the current simulation. In order to use altered
equations or products, you must add the altered formulas by clicking on the ‘Catalogue’
button and choose the desired formulas, as noted in the previous sections.

Products
The process to insert, delete, and edit products in this section are similar to the steps
described above in section 10.6. Log Diameter and Stock.
29
Remember that to save any changes, you much click on the SAVE or SAVE AS button. If
the changes are not saved, they will be deleted when the program is closed.

Formulas
The screen below shows an example of adding a Site Equation. The first step is to click
on ‘+’ in the navigation bar. Next, you can fill in the text boxes Description and Author.
From the dropdown menu for ‘Type’, choose the type of equation you would like to
include, for example, ‘Site Equation’ as shown in the example below.
In the text box called ‘Expression’, type in the Equation.
30
The functionality of the Equation can be tested by typing in the variables that the
expression uses and values to test the equation, as shown below. By clicking on ‘Assign’,
‘Compile’, and then ‘Evaluate’, the test will run and the ‘Results’ will be presented.
10.8. Carbon
The software suite allows for the quantification of Carbon based on equations published
in technical-scientific work (see the table below). Furthermore, the user can input new
equations using variables found in the growth and production tables, such as DBH and
tree height, which are generally part of carbon calculation models.
31
Software and Species
Equations to estimate (tC)
To obtain the level of CO2, multiply tC by the Conversion Factors of C
for CO2 = 3.6667
SisAcacia
Acacia mearnsii De Wild
SisAraucaria
Araucária angustifolia (Bertol.) Kuntze
SisBracatinga
Mimosa scabrella Benth
SisEucalipto
Eucalyptus grandis Hill ex Maiden
SisPinus
(Vol+33%).(Dry biomass: 0.41).(C:0.4248)
From Saidelles et al. (2009)
(Vol+53%).(Dry biomass: 0.41).(C:0.43)
From Watzlawick et al. (2003)
(Vol+43%).(Dry biomass: 0.48).(C:0.44)
From Machado et al. (2006)
(Vol+25%)x(BD: 0.49)x(C: 0.42)
From Silva (1996) and others
2
(0.0001-0.0040.D+0.0193.D H+0.5728 I).(C:0.41)
Pinus taeda L.
From Corte and Sanquetta (2007)
SisTeca
(Vol+30%)x(BD:0.53)x(C:0.41)
Tectona grandis L.F.
From Rondon (2006), Gouveia and Ângelo (2002)
Vol. = Volume of trunk with bark; C = Level of Carbono (tC); D = DBH (cm), H = Total Height (m); I =
Age (years), BD: Basic Density.
Corte, A.P.D, Sanquetta, C.R. Quantificação do estoque de carbono fixado em reflorestamentos
de Pinus na área de domínio da floresta ombrófila mista no Paraná. Cerne, Lavras, v. 13, n. 1, p.
32-39, jan./mar. 2007
Gouveia,V.M., Ângelo. H. Análise econômica do serviço de fixação de e armazenamento de
carbono por um povoamento de Tectona grandis L. f. Brasil Florestal, v. 21, n. 74, 2002.
Machado, S.A., Urbano, E., …Relações Quantitativas entre Variáveis Dendrométricas e Teores
de Carbono para Mimosa scabrella Bentham da Região Metropolitana de Curitiba. Boletim de
Pesquisa Florestal, Colombo, n. 52, p. 37-60 jan./jun. 2006
RONDON, E. V. Estudo de biomassa de Tectona grandis L.f. sob diferentes espaçamentos no
estado de Mato Grosso. Revista Árvore, Viçosa, v. 30, n. 3, p. 337-341, 2006
Saidelles, F.L.F.; Caldeira, M.V.W.; Schumacher, M.V.S.; Balbinot, R. Uso de equações para
estimar o carbono orgânico em plantações de Acacia mearnsii De Wild. no Rio Grande do Sul –
Brasil. Revista Árvore. Viçosa. v.33, n.5, p. 907-915. 2009
SILVA, H.D. Modelos matemáticos para a estimativa da biomassa e do conteúdo de
nutrientes em plantações de Eucaliptus grandis Hill (ex-maiden) em diferentes idades.
UFPR, Tese de Doutorado. 1996. 101p.
Watzlawick, L.F., Sanquetta, C.R., Arce, J., Balbinot,R. Quantificação de biomassa total e
carbono orgânico em povoamentos de Araucaria angustifólia (Bert.) O. Kuntze no sul do Estado
do Paraná, Brasil. Revista Acadêmica: ciências agrárias e ambientais, Curitiba, v.1, n.2, p. 6368, abr./jun. 2003.
32
10.9. Results
Click on the horizontal bar called ‘Results’ located at the bottom of the screen to run the
simulations. To return, click on ‘Data Entry’ at the top of the screen.

Example 1
Consider the following screen that shows a plantation of 2000 trees per hectare, Site
Index of 21 meters, and harvest at 22 years.
The results show the variables that describe the structure of the forest plantation. All
results are by hectare. Basal area refers to the sum of the cross-sectional areas of all
trees, using DBH for the calculation. The MAI is the mean annual increment, obtained by
dividing the total production by age. This simulation considers the sum of the volume at
the age of harvest as well as the volume that has been thinned.
33
34

Save
The results can be saved in a text file using the .rtf extension, and the file will be
compatible with text editing software. To save, click on the SAVE or SAVE AS button
located on the green toolbar.
By highlighting the results table (either part of the table or the full table), you can copy and
paste the results into a spreadsheet program, as shown below. Each value is placed in a
separate cell enabling you to perform further calculations.
SisPinus
GROWTH AND PRODUCTION TABLE (Pinus taeda)
Description: Example 1
Site Index: 21.0
Density (trees per hectare): 2000
Percentage of survival: 95%
CO2 eq. = (Vol+34%)x(Basic Density: 0.36)x(C: 0.50)x(CO2: 3.66)
Age
1
2
3
4
5
6
7
8
9
10
Dominant Height
0,6
2,5
4,7
6,8
8,7
10,4
12,0
13,5
14,8
16,1
No. Trees
1900
1900
1900
1900
1899
1898
1895
1889
1879
1866

Avg. Diameter
0,2
2,2
5,3
8,3
10,8
12,8
14,4
15,8
17,0
18,0
Avg. Height
0,4
2,1
4,0
5,9
7,6
9,1
10,5
11,8
12,9
14,0
Basal Area
0,0
0,7
4,2
10,3
17,3
24,4
31,1
37,2
42,8
47,7
Total Volume
0,0
0,7
7,6
27,1
59,0
100,0
147,0
197,3
249,1
300,7
Print
To print the results, simply click on the Print button in the green toolbar.
A.M.I.
0,0
0,3
2,5
6,8
11,8
16,7
21,0
24,7
27,7
30,1
tCO2
1,6
3,8
11,1
28,7
56,5
91,7
131,9
174,8
218,8
262,7
35
10.10. Graphics
A ‘Graphic’ with several variables can be produced by clicking on the Graphic button on
toolbar at the top of the screen. The increments and indexes presented help to define the
ideal forest management strategy. To print the graphic, use the ‘Print Screen’ function and
paste the image in a text-editing software.
 Red dots = Percent of maximum density that could be achieved by the
population (Reineke Model); (Available in SisPinus and SisEucalipto);
 Blue dots = Relative spacing index (Hart-Becking Index);
 X = indicates high risk of wood wasp occurrence (Available in SisPinus);
 Pink line = Basal area by hectare;
 Pink triangles = upper and lower limits of the suggested management range;
 Blue line = Mean annual increment (MAI)
 Green line = Total volume (divided by 10).
36

Hart-Becking Index or Relative spacing index – (%)
The Hart-Becking Index (S%) is the relation between the average distance between trees
(EM) and the dominant height (H):
S (%)  100 .
EM
H
The average distance between trees (EM) can be calculated with the following
expression:
EM 
10000
N
where N is the number of trees per hectare.
The Index S (%) has significant application in determining weights for thinning in forest
management to prevent forest fires and pests, as well as in the development of
agroforestry systems.

Percentage of Maximum Population Density – (Reineke)
The Reineke model, adjusted for overstocked plantations in the producing regions of
Brazil, creates a curve that represents the maximum density that the population could
achieve in a condition of complete occupation or complete stock. The graph created by
the software shows the percent occupation of the site for the analyzed population. A value
of 100% indicates that the site is completely stocked, or at the limit of productive capacity.
In the graph created in Example 1, we can see that at 6 years the population occupies
46% of the site and this increases in subsequent years. At 9 years, the occupation
reaches 70%; however, beyond this age, the program reveals a high risk of attack by
wood wasps which requires preventative thinning. The risk of attack by wood wasps is
based on population characteristics that are favorable to the insect, such as excessive
37
competition between trees which provokes significant weakening and mortality in
dominant trees.

Density Management Diagram (DMD)
The DMD shows the mathematical interrelations between several diverse variables of a
forest population, including the number of trees per hectare, the basal area, and the
average diameter of the trees. It allows for the monitoring of the density of a population as
a function of the magnitude of growth variables. Monitoring enables you to define the
intensity and age of thinning, adequate levels of competition in relation to the wood
production objectives, which in turn allows for the optimal use of the site. Other models
also include the dominant height.
A Density Management Diagram is constructed based on a curve of maximum density, as
well as other proportion curves based on the maximum density, and these serve as
references for site occupation. The maximum density curve marks the maximum
occupation limits of site.
To define the maximum density curve, despite all the advances made in forest biometry,
the Reineke method (1933) continues to be used as a reference. For its application, the
maximum density curve is estimated from the measurements of a population at full
density. The model is:
N = Exp(a + Ln(Dg))
where N is the number of trees per hectare and Dg is the quadratic mean diameter.
Based on the maximum density curve, the Diagram can be constructed considering
variations in quadratic diameters as reference points.
38
In SisPinus, for Pinus taeda, the equation used was obtained through data from various
stands that enabled the construction of the software, as:
N = Exp(12.1333 – 1.4933Ln(Dg))
Which results in the following diagram:
The Plantation Density Index (Reineke Index), obtained by using a Dg of 25cm, was 1520.
The recommended management range for log production, suggests upper limit values of
up to 60% maximum stock to a lower limit fixed at 30% maximum stock. By maintaining the
population in this density range, the trees will have the dominant characteristics of being
large with a well-formed shaft.
39
Note that above the range, there is excessive competition, and below the range there is
surplus space with the consequent waste of site resources. Within the range, the option to
implement a thinning regime closer to the upper or lower limit depends on the production
objective. If the objective is for smaller logs with shorter rotations, the thinning should be
kept closer to the upper limit of 60%.
40

DMDs in the Software
The integration of DMD with the simulations described in this manual allows for the
variables considered by the Diagram to be processed alongside other variables of growth
and production that have a significant impact on stand density, particularly Dominant
Height and Average Height. As such, the dynamics and interactions between the diverse
variables can be monitored for each age, accompanied by a prediction of growth and
production.
At this point, the DMD considers Dominant Height and Average Height, Mortality, Average
Diameter, Basal Area, and Volume. Furthermore, the software provides a breakdown of all
timber harvested by diameter classes and height, as well as sorting for end use.
The model of the graph produced by SisPinus, considering Example 1, without thinning
and a final harvest at age 18, would be:
41
Considering the inclusion of a selective thinning at 9 years, leaving a basal area of 25m2,
to put the basal area within the management range recommended by the Density
Management Diagram, the resulting graphic would be:
With the thinning, the final MAI would be reduced by 10% (36.6m2 to 31.5m2). However,
logs above 20cm in diameter would increase by 23% (229m3 to 282m3).
42
 Example 2
While Example 1 looked at data from a plantation, Example 2 uses data from an
inventory. The species is Pinus taeda at 5 years of age. The dominant height is 9.0
meters and, based on the site classification table (pg. 60), results in a site index of 21.5m.
The number of trees per hectare is 1500, the quadratic mean diameter is 12cm and the
level of the homogeneity is 5.
For this example, we will first implement a mixed thinning at 9 years, with a systemic
removal of one in every five lines of trees, followed by a selective removal to achieve a
remaining population of 1000 trees.
A second thinning will be selective, at 13 years, leaving 400 trees and the final harvest
will be at 20 years. To calculate the resulting production, we will use a diameter class
interval of 2 cm, distributing the wood into the following end products:
End product
Length (m)
Minimum diameter (cm)
Sawlog I
2.4
25
Sawlog II
2.4
15
Pulp
1.0
8
Energy
No restriction
No restriction
The following two figures show how the data should be input for Inventory and Thinning.
43
The results are shown in the following three figures.
44
45
46
10.11. Other
The menu item ‘Other’, available from the top horizontal toolbar, shows the following
options:
1. Manual
Opens the manual for the software.
47
2. Economic Analysis – Planin
This option accesses the Planin software, which can be used to calculate parameters for
economic-financial evaluation and analysis of profit sensitivity to different rates of
attractiveness. In this program, we can consider different operational cost segments of
planting, maintenance, and forest harvesting. You can obtain cash flow, sensitivity
analysis, and other criteria of frequently used economic analysis. Furthermore, you can
track your costs and generate annual expenditure reports.
The complete Manual for Planin can be accessed through the ‘Help’ menu of the
program. Here, only a few screens are shown to demonstrate the basic structure of the
program.
48
49
3. Production System Guides
The Production Systems Guides are available on the Embrapa Forestry website. These
guides provide information about production techniques, from seed collection to final
harvest, uses for wood and non-wood forest products, commercialization, among many
others. These guides can be accessed through the ‘Other’ menu in the software. You can
also access the guides through the shortcut that is created when the software is installed.
The guides were written by Embrapa Forestry researchers and other invited experts, all of
whom are specialists in the respective theme. By clicking on each item, you can access
the corresponding guide and links to other sub-items.
Technical guides are available for the following themes:
Araucária
Acácia-negra
Bracatinga
Apresentação
Taxonomia
Descrição da
espécies
Biologia
reprodutiva e
fenologia
Ocorrência natural
Aspectos
econômicos e
ambientais
Aspectos
ecológicos
Clima
Solos
Sementes
Produção de
mudas
Características
silviculturais
Melhoramento
genético
Crescimento e
produção
Principais pragas
e doenças
Características da
madeira
Produtos e
utilizações
Espécies afins
Sistemas
agroflorestais
Referências
Glossário
Expediente
Autores
Importância
socioeconômic
a e ambiental
Espécies de
acácia para
plantio
Requerimentos
ecológicos das
espécies mais
importantes
Implantação
Manutenção
Manejo
Colheita e póscolheita
Sistemas
agroflorestais
Coeficientes
técnicos e
custos
Mercado e
comercializaçã
o
Legislação
pertinente
Referências
bibliográficas
Glossário
Equipe
Apresentação
Taxonomia
Descrição da
espécie
Biologia
reprodutiva e
fenologia
Ocorrência natural
Aspectos
econômicos e
ambientais
Aspectos
ecológicos
Clima
Solos
Sementes
Produção de
mudas
Características
silviculturais
Melhoramento
genético
Crescimento e
produção
Pragas e doenças
Características da
madeira
Produtos e
utilizações
Espécies afins
Sistemas agroflorestais
Referências
Glossário
Expediente
Autores
Erva-mate
Apresentação
Distribuição
geográfica da
erva-mate
Clima
Solo
Produção de
sementes
Produção de
mudas
Implantação
Adubação
Recuperação de
ervais
degradados
Cobertura do
solo
Controle de
plantas
espontâneas
Condução e
poda
Doenças
Pragas
Sistema
agroflorestal
Adensamento e
conversão
Interplantio
Processamento
Importância
socioeconômica
Eucalipto
Pinus
Importância
socioeconômica
e ambiental
Indicações de
espécies para
plantio
Produção de
mudas
Sistemas de
Plantio
Nutrição,
Adubação e
calagem
Pragas
Doenças
Manejo de
plantações para
desdobro
Sistemas
Agroflorestais
Coeficientes
Técnicos e
Custos
Mercado e
Comercialização
Referências
Glossário
Expediente
Autores
Apresentação
Espécies
Preparo de área
Produção de
mudas
Doenças
Pragas
Sistemas de
plantio
Adubação
Manejo
Importância
sócio-econômica
Coeficientes
Técnicos e
Custos
Sistemas
agroflorestais
Gerenciamento/
SISPINUS
Certificação
Referências
Glossário
Expediente
Autores
50
4. Taper Equations
Item 4 in the ‘Other’ menu, enables you to access the electronic spreadsheet and
transform the tapering function based on
hi
H
hi
to another that uses (1- H ). The
spreadsheet also calculates the form factor for the volume equations and integral used by
the software.
5. Video
Through this link, you can access a video explaining forest plantation management with
the help of the software. If the video is not available in your copy of the software, the
video can be accessed directly from YouTube.
51
6. About the software
This option provides information about the software.
52
11. Statistical foundation of the software
These systems were developed based on probabilistic distributions. As such, instead of
conventional regression models, we work with annual projections of the structure of each
forest, involving various parameters simultaneously.
The probabilistic distributions used were SB and SB bivariate (SBB). The SB distribution
describes the marginal distribution of diameter or height variable of the trees in a
population at different ages. The SBB describes the combined distribution of these
variables.
Field data were obtained from plots with continuous inventories through partnerships with
forest producers. This enabled the estimation of distribution parameters for each species,
in different conditions of soil, age, and spacing between trees.
The function of distribution SB is expressed as:

 (x  )  

 1
f  x 
exp     ln 

 (    x )  
2  x       x 
 2

2


,


The construction of the distribution SBB is based on the distribution SB, together with a
Normal bivariate distribution.
If we consider D and H, or DBH and total height of the trees, respectively, we have:
 xD   D 
z D   D   D ln

  D   D  xD 
zH  
H
and


xH   H
  ln

 H  H  XH 
where zD and zH have Normal bivariate distribution with correlation .

f  z D , z H   2 1   2


1
1
2
 exp  1 1   2
 2


 z
1
2
D

2 
 2 z D z H  z H ,

The parameters D and H represent the minimum values of D and H in the population,
respectively; D and H represent the ranges of D and H. The parameters D, H, D and H
cannot be related to individual characteristics of a forest population, but can be through
the expressions:
 

4 x
and
 
2xm    

 xm   
  ln

     xm 
53
where:
x = standard deviation of x (x= H or D ) and xm = mode of x.
The value of Xm is defined by the value of x that satisfied the expression:
2 x   


 x   
 1      ln

     x

To elaborate the model of growth and production, the estimates of the parameters were
associated through the function of the number of trees per hectare (S) and dominant
height (HD) or age of the populations, using the Richards model:
Parameter = f1S 1  exp H D f 2 S  f3 ( S )
Equations to estimate the SBB distribution parameters.
______________________________________________________


H D  exp a1 1 / A 1  1 / 15 1 IS
Hm  H D a2  b2 A
H1  H D a3 1  exp b3 A
c4
sH  a4 1  exp b4 A
c5
DD  a5 1  exp b5 H D 
Dm  DD a6 1  exp b6 H D 
6.
c7
D1  DD a7 1  exp b7 H D 
7.
c8
sD  a8 1  exp1  b8 H D 
8.
 Z D , Z H   a9  b9 cosc9 H D   d 9 H D
9.
_____________________________________________________
1.
2.
3.
4.
5.




b
b








Where:
IS = Site Index
HD = dominant height
A = age of population
DD = greatest diameter
Hm and Dm = mode of the Heights and diameters
H1 and D1 = smallest height and smallest diameter
sH and sD = standard deviations of the heights and diameters
ai, bi and ci (i = 1,2...9) are equations for each parameter that have as the dependent
variable the number of trees per hectare (S).
54
Figure 5 shows graphics demonstrating the distribution characteristics.
D
e
s
b
a
s
Desbaste
t
e
Aidade da florestaa:
Aidade da florestaa:
C
o
l
h
e
i
t
a
f
i
n
a
l
Figure 5. Graphics of the bivariate distribution and their projection.
A detailed description of the methodology can be found in the following references:
HAFLEY,W.L.; BUFORD,M.A. A bivariate model for growth and yield prediction. Forest Science, v.
31, n. 1, p. 237-47, 1985.
HAFLEY,W.L.; SCHREUDER,H.T. Statistical distribution for fitting diameter and height data in evenaged stand. Canadian Journal of Forest Research. v. 7, p. 481-487, 1977.
OLIVEIRA, E.B.de. Um sistema computadorizado de prognose de crescimento e produção de
Pinus taeda L. com critérios quantitativos para a avaliação técnica e econômica de regimes de
manejo. Curitiba, 1995. Universidade Federal do Paraná. 126p. Tese Doutorado.
SCHREUDER,H.T.; HAFLEY,W.L. A useful bivariate distribuition for describing stand structure of
tree heights and diameter. Biometrics. V. 33, P. 471-7, 1977.
55
12. Site classification tables
1. Black wattle (Acacia mearnsii)
2. Araucaria (Araucaria angustifolia)
56
3. Bracatinga (Mimosa scabrella)
4. Australian red cedar (Toona ciliate)
57
5. Eucalyptus dunnii
6. Eucalyptus (grandis / urograndis)
58
7. Honduras Pine (Pinus caribaea var hondurensis)
8. Slash Pine (Pinus elliottii)
59
9. Loblolly Pine (Pinus taeda)
10. Teak (Tectona grandis)