Proyecto ArBolivia

Transcription

Proyecto ArBolivia

Plan Vivo Technical Specification for
Forestry Plantations for sustainable Wood Production
Anko A. Stilma
Dennis Berger
SICIREC Bolivia ltda.
Casilla 6511, Cochabamba, Bolivia
Email: [email protected]
2011
Language review:
David Vincent (Ethical investments)
1
Content
1.
Summary ..................................................................................................................................................... 4
2.1
Eligible land types................................................................................................................................ 7
2.1.1
Procedure used to demonstrate that reforestation activities are to be developed on
deforested land ........................................................................................................................................... 7
2.2.
3
BASELINE .................................................................................................................................................... 9
3.1
5.
2
Description of the project area ........................................................................................................... 9
3.1.1
Location of project area .............................................................................................................. 9
3.1.2
Recording of site information ...................................................................................................12
3.1.3
Site description..........................................................................................................................13
3.1.4
Site assessment .........................................................................................................................19
3.2
Baseline methodology applied ..........................................................................................................19
3.3
GHG sources considered in the baseline...........................................................................................19
3.4
Change in carbon stocks in the absence of the project ....................................................................19
3.4.1
Change in carbon stock per stratum .........................................................................................20
3.4.2
Most likely baseline scenario – Change in carbon stock in the absence of the project............21
3.5
4.
Land Use Types for which the activities will be developed................................................................. 8
Quantification of existing carbon stocks per stratum .......................................................................21
3.5.1
For above-ground biomass........................................................................................................22
3.5.2
For below-ground biomass........................................................................................................23
3.5.3
Overall baseline scenario .........................................................................................................24
Project activities and Management System ..............................................................................................25
4.1
Reforestation activities .....................................................................................................................25
4.2
Integrated Land Use Planning ...........................................................................................................27
4.3
Technical support and review: ..........................................................................................................27
Quantification of carbon services .............................................................................................................31
5.1
Crediting period.................................................................................................................................31
5.2
Estimation of the project’s net GHG removals by sinks ....................................................................31
5.2.1
For above-ground biomass........................................................................................................32
5.2.2
Carbon stocks for below-ground biomass.................................................................................35
5.2.3
Carbon stocks for above and below-ground biomass ...............................................................35
6.
5.3
Carbon loss due to plantation activity ..............................................................................................37
5.4
Net anthropogenic GHG removals ....................................................................................................39
Leakage......................................................................................................................................................41
6.1
7.
Risk of Carbon loss attributable to the project activity.....................................................................41
6.1.1
Displacement of households .....................................................................................................41
6.1.2
Displacement of cropland: ........................................................................................................41
6.1.3
Displacement of pasture land: ..................................................................................................42
6.2
Monitoring leakage and mitigation ...................................................................................................42
6.3
Risk management ..............................................................................................................................43
Monitoring.................................................................................................................................................44
7.1
Planting progress and tree survival monitoring ................................................................................44
7.2
Tree growth and plantation development .......................................................................................44
7.2.1
7.3
8.
Variables to measure.................................................................................................................44
Installation of permanent sample plots ............................................................................................46
7.3.1
Stratification ..............................................................................................................................46
7.3.2
Size and shape of the plots.- .....................................................................................................46
7.3.3
Demarcation and marking of plots............................................................................................47
7.3.4
Measurement of the trees ........................................................................................................47
7.3.5
Number of plots.- ......................................................................................................................48
7.4
Carbon stock monitoring ...................................................................................................................48
7.5
Summary of data to be collected for Carbon Stock Monitoring and Recording Frequency .............50
7.6
Data for monitoring of leakage .........................................................................................................51
7.7
Procedures and Responsibilities .......................................................................................................51
7.7.1
Data gathering and processing ..................................................................................................51
7.7.2
Quality control...........................................................................................................................51
Buffer level ................................................................................................................................................52
Literature ...........................................................................................................................................................53
Annex 1: Simplified baseline and monitoring methodologies for small-scale afforestation and reforestation
project activities under the CDM, implemented on grasslands or croplands AR-AMS0001 vs5
Annex 2: Field Forms
Annex 3: Plantation design protocol
Annex 4: Carbon calculations:
4.a Tree growth estimation per tree species (M3/ha/year)
4.b Annual Carbon Increment per specie(tC/ha/year)
4.c Yearly and Average Net GHG removals per specie (tCO2e/year) for the whole project
Annex 5: IPCC TABLES 3A.1.8 & 3A.1.10
3
1.
Summary
This document is a Plan Vivo technical specification for small-scale plantations in the settler areas of the
Cochabamba Tropics, the Province of Ichilo in the department of Santa Cruz, Northern La Paz, and Western
Beni.
Carbon estimates for forest plantations are based on the approved CDM small-scale methodology ARAMS0001 vs5 (annex 1),
Ex-ante carbon calculations are calculated according the long term average carbon stock approach and is
calculated over a 40 year crediting period.
All activities are embedded in a proper land use planning system. If land use can be improved, agriculture
will become more efficient and the deforestation due to traditional method of slash and burn can be
reduced. In addition more land can be officially registered and once identified and categorized, this land and
its use will be protected.
This technical specification refers to one of the project activities, which is the establishment of plantations
for sustainable wood production. A brief description of the proposed land use type under this technical
specification can be seen in table 1.1
Table 1.1: summary of activity under TS-FP
Title
FP
Type of
activity
Forestry
Plantations for
sustainable
wood
production
Objectives Brief description
Target areas
/ groups
Income
Only native tree species will be planted, except for the naturalised Farmers
improvement Tectona grandis, which will be planted only on a small scale.
participating in
the project
Environmental
The native tree species proposed are: Aspidosperma
benefits
macrocarpon, Buchanavia sp, Cedrela fissilis, , Calophyllum
brasiliense, Centrolobium tomentosum, Dipteryx odorata, Guarea
rugby, Schlizobium amazonicum, Stryphnodendron purpureum ,
Swietenia macrophylla, Tapirira guianensis, Terminalia
amazonica, Terminalia oblonga, Virola flexuasa
Trees are planted in small sectors of one single specie after
concluding a site selection process, matching tree requirements
with site conditions, only in a few cases more than one treespecie is planted per sector, the species swietenia macrophylla
and cedrela fissilis might be planted with about 50 trees per
hectare in plantations with other species, this to avoid the attack
of Hypsipyla grandella.
Estimations on long term average GHG removals per hectare and per tree species over the validation period
of 40 years are shown in table 1.2 below.
4
Table 1.2: Long term average carbon over a 40 years crediting period
Above and
Gross
Below
project
Ground
GHG
Growth class
Scientific name
Common name
Carbon
removal
(tC/ha)
(tCO2e/ha)
Fast
Schyzolobium amazonicum Serebo
68
248
Fast
Stryphnodendron purpureum Palo yugo
72
263
Medium
Aspidosperma macrocarpon Jichituriqui
88
323
Medium
Calophyllum basiliense
Palo María
59
215
Medium
Centrolobium tomentosum
Tejeyeque
63
231
Medium
Guarea rusby
Trompillo de altura
78
286
Medium
Tapirira guianensis
Palo román
83
303
Medium
Tectona grandis
Teca
68
249
Medium
Virola flexuosa
Gabún
55
203
Slow
Buchenavia oxycarpa
Verdolago negro (pepa)
64
234
Slow
Dipteryx odorata
Almendrillo
76
277
Slow
Terminalia amazonica
Verdolago negro (de ala)
76
278
Slow
Terminalia oblonga
Verdolago amarrillo de ala
62
228
For the main species the above and below ground carbon removals per hectare are shown in the figure 1.1.
Figure 1.1: above ground an below carbon removals per hectare in time
The ex-ante estimate of net anthropogenic GHG removals for the different species per ha is the result of:
5
Long term Average net GHG removals MINUS The sum of Long term average Negative removals MINUS
the sum of average net baseline GHG removals.
In table 1.3 the long term average net GHG removals for each baseline type per tree species is given.
Table 1.3: Ex-ante estimate of net long term average anthropogenic GHG removals per hectare over a 40 year crediting period
Net average GHG removal (CO2e/ha) over
crediting period for Baseline
Growth class
Fast
Fast
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Scientific name
Common name
Schyzolobium amazonicum
Stryphnodendron purpureum
Aspidosperma macrocarpon
Guarea rusby
Tapirira guianensis
Tectona grandis
Virola flexuosa
Buchenavia oxycarpa
Dipteryx odorata
Terminalia oblonga
Serebo
Palo yugo
Jichituriqui
Palo María
Tejeyeque
Trompillo de altura
Palo román
Teca
Gabún
Almendrillo
Grassland
Grassland
with trees
247
262
322
213
229
285
302
248
202
233
276
277
227
247
262
322
213
229
285
302
248
202
233
276
277
227
Annual
crops
Perennial
crops
248
263
323
215
231
286
303
249
203
234
277
278
228
246
261
321
212
228
284
301
247
201
232
275
276
226
For the entire project actual net GHG removals are multiplied with the surface of each stratum.
Considering the planting schedule, the distribution of tree species and the application of the formulas
mentioned in this paragraph for the calculation of above and below ground biomass per specie and per
hectare, it is estimated that for the whole project activity the long term average GHG removals in tons of
CO2e will be: 1,264,299 tCO2e, over the 40 year crediting period.
Figure 1.2 shows the accumulated GHG removals by the trees in CO2e within the project boundary until
2047.
Figure 1.2: total actual net GHG removals in tons/ha/year
6
2.
Scope of the Technical specification
2.1
Eligible land types
Arbolivia’s requirements for tree planting activities are:
• Smallholder owned land
• Land on which trees will be planted should have secure land tenure as stated in paragraph 3.1.2
• Tree planting should not adversely affect food security or the short term income security of the
participating farmers, see PDD section 3.5
• No negative environmental impacts should occur as a result of tree-planting, see PDD section E
• Trees will be planted only on deforested land as defined by the DNA of Bolivia.
The following paragraph outlines the procedure adopted in order to demonstrate whether land deforested
10 years prior to the proposed reforestation activities is eligible.
2.1.1
Procedure used to demonstrate that reforestation activities are to be developed on
deforested land
In Bolivia the DNA has defined forests as land which has:
• A minimum area of 0.5 hectare
• A minimum tree crown cover of 30 %
• Trees that potentially reach a height of >4 m.
The procedures used to decide whether land is to be included within the ArBolivia project are those used for
CDM Afforestation and Reforestation project activities (http://cdm.unfccc.int/EB/035/eb35_repan18.pdf).
The only exception is that a different date of deforestation has been used. In the eligibility procedures of
the UNFCCC areas for reforestation activities are only eligible if can be demonstrated that these areas were
deforested prior to the 31st of December 1989. For this project and in compliance with the Plan Vivo
standard this has been changed to 10 years prior to the date on which planting in a specific area
commenced.
Land eligibility is demonstrated by classified LANDSAT 5-TM from the year 2000 and 2001.
Step 1: A non-supervised classification of the Landsat images is made
Step 2: Major land use and land cover types within the portfolio area, even those with no potential for an
A/R CDM project activity (dense tropical forest), are identified for the purpose of training in Remote
Sensing image analysis
Step 3: Field data gathering in transects on land cover units and land use units:
i. Description of land cover, using classification criteria established by the ENCOFOR project,
vegetation type, biomass estimation measured in sample plots, height of vegetation,
vegetation density, crown cover.
ii. Defining in the field whether the area is currently eligible
iii. Description of land use
iv. Measuring land unit boundaries: by GPS with a positional accuracy of 10 m or less
7
Step 4: As a result of the above steps, three types of area are distinguished:
1. Areas not eligible
2. Eligible areas
3. Areas which may be eligible, but which need a more detailed analysis since there is some
doubt as to whether these areas are indeed eligible or not, because Remote Sensing (RS)
analysis does not clearly define the characteristics of the vegetation. In these cases additional
site visits are carried out with the objective of gathering the following data:
a. Actual land cover
b. Statement from the farmer on historical land-use and land cover, going back to 10
years from the proposed planting date, if there was re-grown vegetation which
according to the forest definition should be considered to be forest, the farmer should
clarify whether this vegetation was removed with the specific intention of establishing
reforestation activity.
c. Field indicators, which prove that the area is used as agricultural land. This can be
proven by an evaluation of historical land use as stated by the farmer and the
existence of indicator species. Different pioneer species are good indicators of how
many times vegetation has been cut down for cropping purposes and how many times
it has been left as fallow land. This shows that the land is part of an agricultural
system, even though at some stage during the period between deforestation and the
start of the project fallow land existed that met the forest definition. The Area is not
forest and has no potential to be used as forest in the future.
2.2.
Land Use Types for which the activities will be developed
To be eligible for AR-AMS0001, the project must occur on grasslands or croplands, and <10% of the total
surface project area may disturbed as result of soil preparation for planting.
In compliance with the eligibility criteria, land use types on which the proposed activities are applicable are:
• Annual crops
• degraded grassland
• degraded grassland with trees
• Cropland: perennial crops in their final stage of production
The distribution of planting activities in the first phase of the project is shown in table 2.1:
Table: 2.1: Land use types eligible for tree planting
Surface (ha)
Northern
Cochabamba
Ichilo province
La Paz and Beni
Tropics
Annual crops/fallow land
364
16
665
Grassland
23
287
Grassland with existing trees
18
2
Perennial crops
31
64
101
Total
436
80
1055
Land Use Types
Total
1044
310
20
196
1571
Area (%)
66%
20%
1%
13%
100%
This distribution of land use types is representative of the project as a whole. Specific plantation design and
choice of tree species depends on site selection as described in paragraph 4.3.
8
3
BASELINE
3.1
Description of the project area
3.1.1 Location of project area
The Plan Vivo activities will be implemented in the settler areas of the Cochabamba Tropics, the Province of
Ichilo in the department of Santa Cruz, Northern La Paz, and Western Beni. See map figure3.1
Figure 3.1: Project areas
Within these four departments the projects implements its activities in 13 municipalities. (see table 3.1) The
project established until November 2010, 1571 hectares, with 907 farmer families.
Table 3.1: Municipalities in which project activities take place (per department)
Dep. Beni
Reyes
Rurrenabaque
San Borja
Dep. La Paz
Ixiamas
San Buenaventura
Dep. Cochabamba
Chimoré
Entre Rios
Puerto Villarroel
Shinahota
Dep. Santa Cruz
Buena Vista
San Carlos
San Juan
Yapacani
The project areas are all located at the foot of the Andes mountain range within the Amazon River basin. All
project areas have in common that they have similar ecological characteristics and all project areas are
settler areas. The settler areas have been a destination for migrants coming from the High Valley and
Altiplano regions of Bolivia since the 1930s. This migration has intensified during recent decades due to
increasing poverty, the “coca boom” and the deterioration of the mining and agricultural economic bases
that have traditionally supported the people of the Bolivian highlands. Smallholders own 95% of the land in
the portfolio regions. The sizes of the properties vary, but they are on average 20 hectares per family and
9
are usually 100 by 2,000 m in the Cochabamba Tropics, and 25 to 50 ha in the other regions. Only few
farmers have land less than 20 ha. The settlers are organised into syndicates of 20 to 60 farmer families.
Approximately 5 syndicates form a “central”, which in turn belongs to a federation.
Tree planting activities in the first phase took place exclusively on lands deforested prior to 1990 (UNFCCC
eligibility criteria), but in the roll-out phase this will be on land deforested 10 years prior to the start of the
reforestation activity.
For organisational purposes the project areas are divided into three main zones:
Rurrenabaque
The Rurrenabaque area comprises the province of José Balivian in the department of Beni and the province
of Abel Ituralde in the department of La Paz. It is located near the national parks of Madidi (La Paz) and
Pilon Lajas (Beni) and contains the municipalities of Rurrenabaque (Beni), San Borja (Beni), San
Buenaventura (La Paz) and Ixiamas (La Paz). See map figure 3.2.
Figure 3.2: Location of the “Rurrenabaque” area
10
Ichilo Province.
This is situated in the department of Santa Cruz, bordering the Amboro National Park to the south. It
contains the municipalities of Yapacani, San Juan, San Carlos, Buena Vista. See map figure 3.3.
Figure 3.3: Location of the “ichilo” area
Cochabamba Tropics
The Cochabamba Tropics region lies in the department of Cochabamba, bordering the Carrasco National
Park to the south. It contains the provinces Chapare and includes the municipalities of Villa Tunari, Tiraque,
Shinahuota, Carrasco, Chimoré, Puerto Villarroel and Entre Rios. See map figure 3.4
Figure 3.4: Location of the “Cochabamba Tropics” area
11
3.1.2 Recording of site information
For all sites land tenure and actual land use is recorded. In the table 3.2 an example is given of a report on
land tenure, and current land use. Information for all individual participants in the project is stored in the
database.
Table 3.2: Data on land tenure and land use for the plantation areas
Planting areas
in the Smallscale CDM AR
project
activity
Unique ID of planting
areas
Municipal
ity
Community
Name/Surname
Status of land
ownership
Surfac
e (has)
Actual land use
1
SCZ-ICH-SCS-14S-12-S2-P1
San Carlos
14 DE SEPTIEMBRE
Catari Mamani Gregorio
Notarized certificate
1.0 Annual crops/fallow land
2
San Carlos
14 DE SEPTIEMBRE
Arancibia Miranda Crispin
Provisional title
0.5
3
San Carlos
14 DE SEPTIEMBRE
Provisional title
0.5
4
San Carlos
14 DE SEPTIEMBRE
Provisional title
0.5
5
San Carlos
14 DE SEPTIEMBRE
Provisional title
0.5
6
San Carlos
14 DE SEPTIEMBRE
Provisional title
0.5
7
San Carlos
14 DE SEPTIEMBRE
Provisional title
0.5
8
San Carlos
14 DE SEPTIEMBRE
Provisional title
0.2
(in the digital version, click twice to obtain the complete set of data)
Examples of specific areas identified to be planted or already planted are shown on ArBolivia´s website:
www.arbolivia.org/index.php?mc=24
The geographical coordinates of the boundaries of each of the sites where project intervention will take
place (project sites) will be and have been determined by GPS (Positional accuracy 10 m). All parcels have a
unique identification code, generated automatically by the database system of the project.
Examples of coordinates in UTM-WGS84 of the different parcels where small-scale A/R CDM project activity
will take place are shown in table 3.3. The complete set of data is available on request.
Table 3.3 Example of coordinates for planting areas
Planting areas in the Sm all- Unique ID of planting areas
12
1
2
3
Easting
Northing
409069
408964
408986
409088
409069
410635
410420
410425
410640
410469
410473
410769
410765
8103033
8103066
8103153
8103126
8103033
8104127
8104195
8104215
8104150
8104405
8104421
8104336
8104321
An example of one farm with a parcel selected for the reforestation activity is shown in the figure 3.5.
3.5. Example of farmers parcel and the selected area for the plantation
3.1.3 Site description
3.1.3.1 Biophysical characterization
From a biophysical perspective the portfolio area is quite uniform; the terrain is relatively flat, the
precipitation and temperature patterns do not fluctuate significantly and the soil texture and depth remain
relatively homogeneous throughout. The Andes mountains are located immediately south of the portfolio
area. The rivers flow in a north-easterly direction. The portfolio area ranges in elevation from 250 to 450
meters above sea level. More than 75% of the area has a slope angle of less than 5%.
3.1.3.2 Land cover / land use
Farm land in the portfolio area comprises a heterogeneous mix of different land cover and land use types.
Each of these classes exhibit unique biomass accumulation curves through the course of their rotations, as
agriculture crops shift within the land use system. In table 3.4 and figure 3.5a and b the land cover types are
show.
13
Table 3.4: Land cover types in the program area.
Actual Land cover type
Surface (Ha)
Primary forest
961,160
Secondary vegetation/fallow
295,019
Crops
328,223
Pasture land
134,806
Water
62,535
Total
1,781,742
Fig. 3.5a Veg. cover in the Rurrenabaque area
Surface (%)
53.9
16.6
18.4
7.6
3.5
100.0
Fig. 3.5b Veg. cover in the Cochabamba and Ichilo area
The most common types of agricultural land use in the portfolio area are:
• Cattle grazing for beef and milk production
• Annual cropping (rice, maize, cassava)
• Perennial cropping (banana, palm heart, papaya, pineapple, citrus)
3.1.3.3 Ecosystem
Biogeographical zonation
According to the biogeographical zonation of Bolivia, the Cochabamba Tropics and Ichilo province belong to:
Biogeographic province of Acre and Madre de Dios (South West Amazone), Sector biogeographic Amazon
Andean foothill. District A.5. biogeographic district Amazon Chapare and A.3. bio geographic district
Amazon Alto Beni, Characterised by the following species: Aspidosperma rigidum, Astorcaryum murumur,
Attalea phalerata, Brosimum acutfolium, B. lactescens, Cariniana estrellensis, Cedrela odorata, Celtis
schippi, Cetrolobium ochtryxylum, Clarisia biflora, C.racemosa, Coussapoa ovalifoloa. C. villosa, Erythrina
poeppigiana, Guarea macrophylla, Iriartea detoidea, Leonia glycicarpa, Porcelia steinbachii, P. ponderosa,
Poulsenia armata, Pourouma cecropiifolia, Protium opacum, Pseudolmedia laevis, P. macrophylla,
Ruizodendron ovale, Sloanea guianensis, Socratea exorhiza, Spaattosperma leucanthum, Swietenia
macrophylla, Tabebuia serratifolia, Tapura acreana, Terminalia amazonica, T. oblonga, Trichilia pleeana,
Thrihis caucana (Navarra, 2002 1).
14
Rare endangered species
The project sites are poor in the variety of flora and fauna, however on most farms near to the planting
areas residual primary forests with a high variety of fauna and flora do still exist. The project area as a whole
contains a wide variety of fauna, including avifauna and aquafauna. Inhabitants of the region have reported
a decline in the number of animals and fish, due to hunting, fishing and the destruction of their natural
habitat.
The following mammal species have been reported in the project areas by people from the communities:
jochi pintado (Agouti paca), jochi colorado o calucha (Dasyprocta sp.), chichilos (Saimiri sciureus), taitetú
(Tayassu tajacu), parabas (Ara spp), loro cenizo (Amazona farinosa), venado o huaso (Mazama americana),
tropero (Tayassu pecari), anta (Tapirus terrestris) y oso hormiguero (Tamandua tetradactyla). All of these
species except the jochi pintado and the jochi Colorado are protected under CITES. People from the
communities have reported a decline in all mammal species due to the conversion of forest to crop- and
pasture land in the portfolio area. In other words natural habitats for these species have already been and
continue to be lost. Another reason they give for the decline of these species is pressure from hunting.
3.1.3.4 Climatic conditions
As shown in figure 3.5a and b there are six climate stations within the portfolio region. Monthly rainfall and
temperature is shown in figure 3.6. Average annual rainfall is highest in the La Jota station with an average
of 4449 mm, with most precipitation falling between the months of November and March, going further to
the north and east average annual rainfall decreases to 1725 mm. The average annual temperature is
24.7oC. Temperatures are between 6 oC and 39 oC. Temperature declines during the dry season.
Fig 3.5a Meteorological climate stations in Rurr. area.
15
Fig 3.5b Meteorological in Cochabamba and Ichilo area
3.6 a. Average Monthly Precipitation
3.6 b. Average Monthly Temperature
o
Average temperature ( C)
Precipitation (mm)
800
30
Puerto Villarroel
Todos-Santos
700
La Jota
25
Colonia San Juan de Yapacani
Average Temperature (oC)
Yapacani
600
Precipitation (mm)...
Rurrenabaque
500
400
20
15
Todos-Santos
10
La Jota
300
Colonia San Juan de Yapacani
Yapacani
5
Rurrenabaque
200
0
100
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
0
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
Source: FAO, 2003
3.1.3.5 Flood occurrence
In the northern and eastern (see map figure 3.7a&b) part of the portfolio area flooding may occur with a
frequency of 1 to 2 times a year, for a period of less than 5 days. In the site selection procedures this is
taken into account and tree species will be selected according to their resistance to flooding.
Fig. 3.7a: Map of flooding risk in Rurrenabaque area.
Fig. 3.7a: Map of flooding risk in Cochabamba and Ichilo area.
3.1.3.6 Other site conditions
Drought occurrence: July, August and September are the driest months in which generally no tree planting
will take place. Once established, drought does not affect the development and growth of the trees.
16
There is no frost occurrence in the area.
Occurrence of other extreme events: Strong winds have been reported in the area with a frequency of 1 to
2 times a year. Plantation design, including wind breaks, will avoid major damage to plantations and
infrastructure.
3.1.3.7 Soil and terrain conditions
The maps, figure 3.8a & 3.8b delineate soil types using the Fertility Capability Classification (FCC) System.
The FCC groups soils according to edaphic criteria that directly influence interactions between nutrient
availability and plant growth. Map units; see table 3.5 represents the dominant soil type in this unit, which
should be the soil type in at least 70% of the area. For the individual tree-planting areas the scale of this
map is not detailed enough, therefore for each individual planting area a soil classification is made, also
based on the FCC system. A species-site matching assessment is done based on the data obtained during
this site selection process.
Figure 3.8a Soil map Rurrenabaque area
Figure 3.8b: Soil map of the Cochabamba and Ichilo area
Source: Based on Map of Soil Texture Classes (Montieth and Quiroga, 1993)and Soil map of Bolivia (ISRIC, 1995) and own field
evaluations
In all areas clayey and loamy soils prevail. Some areas to the north have a greater clay component, while the
areas surrounding the central river bed are sandier. The FCC map indicates soil textures but also it indicates
the deficiencies present in the soil. Within the area there are a number of factors influencing growth, the
main limiting factors are:
• Aluminum toxicity: Within the entire area aluminium toxicity poses a limiting factor for plant growth.
• Gleying: Gleying and poor soil drainage is also a limiting factor in the north-eastern part of the area.
• Low cation exchange: The central area has a low cation exchange capacity.
• Stoniness/ Rockiness: In some areas located along the southern border and along the rivers.
17
Table 3.5: Soil legend
Soil
L'''aK
L''aK
L''aKe
L'aK
L'aK+ S'''aKe
L'aKe
L'g-aK
L'gaK+ S''gaK
L'gK
L'gK+ S''gK
LaK
LaK+
LaK+e
LaK+ SaK+
LaKe
Chk
LCaK
LCaK+
LCg-aK
LCgaK
LCghK
LC"ghK
Lg-aK
Lg-hK
Lg-hK+
Lg-K
LgaK
LgaK+
LghK
LgK
LhK
LS'''aKg+S''a
K
LS''aK
LSaK
S''gK
SaK
Sg-hK
SgehK+
18
Characteristics
Loamy soils, presence of >gravel, soils are presenting Aluminium saturation of the effective CEC, low potassium reserves.
Loamy soils, presence of >35% gravel, soils are presenting Aluminium saturation of the effective CEC, low potassium reserves and low cation Exchange
capacity (CEC)
Loamy soils, presence of >35% gravel, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves and low Cation Exchange
capacity (CEC)
Loamy soils, presence of gravel, soils are presenting Aluminium saturation >60% of the effective CEC, low potassium reserves.
Loamy soils over a sandy layer, presence of gravel in upper layer and high presence of gravel in sandy layer, soils are presenting Aluminium saturation
>60% of the effective CEC, low potassium reserves, <10% weatherable minerals. Low Cation Exchange Capacity in the under layer.
Loamy soils, low presence of gravel, soils are presenting Aluminium saturation >60% of the effective CEC, low potassium reserves and low cation
Exchange capacity (CEC)
Loamy soils, low presence of gravel and presence of some mottles <2chroma within 50 cm of the soil service, soils are presenting Aluminium saturation
>60% of the effective CEC, low potassium reserves
Loamy soils over a sandy layer, low presence of gravel and presence of mottles <2chroma within 50 cm of the soil service, soils are presenting Aluminium
saturation >60% of the effective CEC, low potassium reserves. <10% weatherable minerals. Sandy layer, has a high presence of gravel or coarse
particles, and soil or mottles <2crhoma, Aluminium saturation>60%, low potassium reserves
Loamy soils, low presence of gravel, with soil or mottles <2chroma within 50 cm of the soil service, low potassium reserves
Loamy soils over a sandy layer. Upper layer with presence of gravel or coarse particles, with soil or mottles <2chroma within 50 cm of the soil service, low
potassium reserves. Sandy layer has a high presence of gravel or coarse particles, and soil or mottles <2crhoma, low potassium reserves
Loamy soils, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves
Loamy soils, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves and <10% weatherable minerals.
Loamy soils, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves and <10% weatherable minerals and low cation
Exchange capacity (CEC)
Loamy soils over a sandy layer, soils are presenting Aluminium saturation >60% of the effective CEC, low potassium reserves. <10% weatherable
minerals.
Loamy soils, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves and low cation Exchange capacity (CEC)
Clayay soils, presenting Aluminium saturation 10-60% of the effective CEC, low potassium reserves
Loamy to clayey soils, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves
Loamy to clayey soils, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves and <10% weatherable minerals.
Loamy to clayey soils, presence of some mottles <2chroma within 50 cm, presenting Aluminium saturation >60% of the effective CEC, low potassium
reserves
Loamy to clayey soils, presence of mottles <2chroma within 50 cm, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves
Loamy to clayey soils, presence of mottles <2chroma within 50 cm, presenting Aluminium saturation10-60% of the effective CEC, low potassium
reserves
Loamy to clayey soils, with high presence of gravel or coarse particles, presence of mottles <2chroma within 50 cm, presenting Aluminium saturation1060% of the effective CEC, low potassium reserves
Loamy soils, presence of some mottles <2chroma within 50 cm, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves
Loamy soils, presence of some mottles <2chroma within 50 cm, presenting Aluminium saturation 10-60% of the effective CEC, low potassium reserves
Loamy soils, presence of some mottles <2chroma within 50 cm, presenting Aluminium saturation 10-60% of the effective CEC, low potassium reserves
and <10% weatherable minerals.
Loamy soils, presence of some mottles <2chroma within 50 cm, presenting, low potassium reserves
Loamy soils, presence of mottles <2chroma within 50 cm, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves
Loamy soils, presence of mottles <2chroma within 50 cm, presenting Aluminium saturation >60% of the effective CEC, low potassium reserves and <10%
weatherable minerals.
Loamy soils, presence of mottles <2chroma within 50 cm, presenting Aluminium saturation 10-60% of the effective CEC, low potassium reserves
Loamy soils, presence of mottles <2chroma within 50 cm, low potassium reserves
Loamy soils, presenting Aluminium saturation 10-60% of the effective CEC, low potassium reserves
Loamy soils with high content of sand over a Sandy layer, with high presence of gravel, soils are presenting Aluminium saturation >60% of the effective
CEC, low potassium reserves and low cation Exchange capacity (CEC), soil or mottles <2chroma are dominant within 50 cm of the soil surface , soils
saturated with water during part of the year.
Loamy soils with high content of sand, with high presence of gravel, soils are presenting Aluminium saturation >60% of the effective CEC, low potassium
reserves and low Cation Exchange capacity (CEC),
Loamy soils with high content of sand, soils are presenting Aluminium saturation >60% of the effective CEC, low potassium reserves
Sandy soil with high presence of gravel, with soil or mottles <2chroma within 50 cm of the soil service, low potassium reserves
Sandy soils, soils are presenting Aluminium saturation >60% of the effective CEC, low potassium reserves
Sandy soils, with low presence of soil or mottles <2chroma within 50 cm of the soil surface, soils are presenting Aluminium saturation 10-60% of the
effective CEC, low potassium reserves
Sandy soils, with presence of soil or mottles <2chroma within 50 cm of the soil surface, low Cation Exchange Capacity (CEC) soils are presenting
Aluminium saturation 10-60% of the effective CEC, low potassium reserves and <10% weatherable minerals
3.1.4 Site assessment
Each individual farm property will be assessed for the above mentioned criteria, using forms 1,2,3,4, 5,6
(annex 2). On this basis the most appropriate land type for the specific project activities will be selected, as
well as selection of the most appropriate species.
3.2
Baseline methodology applied
The approved methodology AR-AMS0001/version 05 has been used.
This choice of methodology is justified because:
• The proposed activity is “grasslands to forested lands” and “cropland to forest land”;
• Project activities are implemented on lands where < 10% of the total surface project area is disturbed as
a result of soil preparation for planting;
• The displacement of households or activities due to the implementation of the project activity is less
than 50%;
• The displacement of grazing animals is less than 50% of the average grazing capacity of the project area.
• The proposed activity is not a de-bundled component of a larger project activity.
3.3
GHG sources considered in the baseline
According to AR-AMS0001/version 05 those project emissions that need to be taken into account are
limited to emissions from the use of fertilisers.
The trees are planted on previous cropland, the farmers will be allowed to grow crops and use fertilisers as
they did before the project activity started. However in line with Annex 15A(b) of the EB22 report 1, this
does not result in an increase in emissions compared with the pre-project activity and thus does not need to
be counted as leakage.
3.4
Change in carbon stocks in the absence of the project
As mentioned in paragraph 2.2, project activities are developed on 4 different land use types.
•
•
•
•
Annual crops
degraded grassland
degraded grassland with trees
Cropland: perennial crops in their final stage of production
All 4 land use types are considered as different strata in the project. For all 4 strata a separate baseline
analysis is carried out, since change in carbon stocks in time might be different.
1
http://cdm.unfccc.int/EB/022/eb22_repan15.pdf:(b)Pre-project GHG emissions by sources which are displaced outside the project
boundary in order to enable an afforestation or reforestation project activity under the CDM shall not be included under leakage if
the displacement does not increase these emissions with respect to the pre-project conditions. Otherwise, leakage for the
displacement of pre-project activities is equal to the incremental GHG emissions compared with the pre-project conditions.
19
3.4.1 Change in carbon stock per stratum
Annual crops
Annual crops are generally part of a slash and burn system in which the main crop is rice. After the rice
harvest the land will be used for a few months more for maize and after that, will become fallow land for
several years. Since these lands have been part of such a system for a long time, they are becoming very
poor and no significant crop production can be expected for the next 10 years or so. The fallow period is
getting gradually longer over time. In all cases the fallow period is not sufficient to allow the soil to recover
and the level of fallow vegetation as well as agricultural production declines, leading to a further
degradation of the soil.
In a few cases trees are planted on land used for mechanized annual cropping. This type of agriculture can
be found in the province of Ichilo. These lands have been used almost continuously for more than a decade
and the use of agricultural inputs such as fertilizers and pesticides increased over these years while yield
was reported to decrease (Sejas, 2008). Once the cost of these inputs exceeds the revenues received,
farmers simply leave the area as waste land. No natural regeneration is expected since after a few years of
fallow the farmer will use the land again for some marginal crop production. Land degradation will continue.
Since multi-temporal satellite image analysis show an increase of agricultural land and a decrease in forest
land. Pressure on land will continue, resulting in progressive degradation of productive soils.
Perennial crops
The perennial crops are predominantly full grown, low productive banana plantations, or citrus plantations
at the end of their rotation, which are expected to show a decline in biomass in future rather than an
increase. The changes in carbon stocks are therefore assumed to be zero. Once perennial crops are no
longer productive or production is very low, farmers might let their cattle onto the land, resulting in a
decline of biomass, or they just leave it for a few years more after which they slash and burn the perennials
and use the land for annual crops. In both cases natural regeneration is expected to be zero, since the
farmer will continue to use the land for some marginal crop production, contributing further to the
degradation of the land.
Grassland and Grassland with trees
In the project areas, the principal cause of degradation of pastures is bad management, which leads to
extreme compaction of the soil, giving way to the gradual invasion of native grasses which end up choking
and displacing the cultivated foraging species. Bad management can be caused by overgrazing or under
grazing. According to Sejas and Espinosa (2007) the management in the zone consists of burning the
pastures every 2 to 3 years in order to eliminate ticks and its eggs, and a burning every 4 to 5 years in order
to renew and improve the pastures. The productive period of the pastures is generally considered to be
about 20 years. Degraded pasture land is used as leisure areas or shelters.
The cause of degradation can be either: overgrazing or under grazing. Overgrazing results in a significant
deterioration of production and soil quality. Undergrazing results in grassland with trees, since the partially
abandoned and degraded grasslands are invariably invaded by shrubs and small trees. In the absence of the
project the most likely scenario is that these areas will be rehabilitated for grazing activities through
burning, which means a further degradation of the soils and a decrease of biomass stock in time compared
with the biomass which can be found currently in this land use type.
20
3.4.2 Most likely baseline scenario – Change in carbon stock in the absence of the project
However it can be evidenced that, without intervention, carbon stocks would in fact decline in future. The
Project has assumed a conservative approach, assuming a static baseline.
This is in line with the applied baseline methodology AR-AMS0001-Section II.5.
II-5
The most likely baseline scenario of the small-scale A/R CDM project activity is considered to be land-use prior
to the implementation of the project activity, either grassland or croplands in which changes in carbon stocks
are assumed to be zero, for grassland if:
And section II-6
II-6b
If the carbon stock in the living biomass pool of woody perennials and in below-ground biomass of grasslands
is expected to decrease in the absence of the project activity, the baseline net GHG removals by sinks shall be
assumed to be zero. In this case, the baseline carbon stocks in the carbon pools are constant and equal to
existing carbon measured at the start of the project activity.
Biomass in annual crops is ignored since it is considered transient.
The perennial crops are predominantly full grown, low yielding banana plantations, at the end of their
rotation, which are expected to show a decline in biomass in future rather than an increase, and therefore
the changes in carbon stocks, are assumed to be zero.
3.5
Quantification of existing carbon stocks per stratum
The baseline scenarios for the 4 different land use types show that changes in carbon stocks in all scenarios
can be assumed to be zero. However, it is still necessary to quantify the carbon stocks for each stratum
since due to project activity carbon removals will occur due to site preparation, or canopy closure which
competes with the vegetation in the baseline.
Therefore, for each stratum (grassland, grassland with trees, perennial crops and annual crops), the
following calculations are performed as shown below.
Baseline net GHG removals by sinks are determined by the equation:
I
B(t) =
∑ (BA(t) i + BB(t) i) * Ai
i=1
where:
B(t) = carbon stocks in the living biomass pools within the project boundary at time t in the
absence of the project activity (t C)
BA(t) i = carbon stocks in above-ground biomass at time t of stratum i in the absence of the project
activity (t C/ha)
BB(t) i = carbon stocks in below-ground biomass at time t of stratum i in the absence of the project
activity (t C/ha)
Ai
= project activity area of stratum i (ha)
i
= stratum i (I = total number of strata)
21
3.5.1 For above-ground biomass
BA(t) is calculated per stratum i as follows:
BA(t) = M(t) * 0.5
where:
BA(t) = carbon stocks in above-ground biomass at time t in the absence of the project activity (t C/ha)
M(t) = above-ground biomass at time t that would have occurred in the absence of the project
activity (t dm/ha)
0.5 = carbon fraction of dry matter (t C/t dry matter)
3.5.1.1 Stratum: Grassland
M(t=0) = M(t) = Mgrass + Mwoody
Mgrass = above-ground biomass in grass on grassland at time t that would have occurred in the
absence of the project activity (t dm/ha) = 11 t dm/ha (Zomer et al., 2006)
Mwoody = no woody perennials in this stratum
M(t=0) = M(t) = 11 + 0 = 11 t dm/ha
Thus Carbon stock in Above ground biomass for Grassland is:
BA(t) = M(t) * 0.5
BA(t) = 11 t dm/ha * 0.5= 5.5 t C/ha
3.5.1.2 Stratum: Grassland with trees
With reference to Zomer et al. a figure of 5.5 tC/ha (= 11 t dm/Ha) was used for grassland and a figure of
8tC/ha (16t dm/ha was used for a mixture of pasture/bare soil/banana). These areas can also be defined as
invaded pasture lands, or overgrown pastures or pastures with trees. A conservative approach was taken
since recently overgrown pasture lands have relatively more grass which in time may disappear. Therefore
the highest carbon stock possible was taken which is all the grass (11t dm/ha) + a high stock of carbon in
shrubs or banana of (max 16tdm/ha). Once the shrub layer is fully developed the grass layer will start to
disappear and the shrub layer will take over so the highest carbon stock in this case is the sum of grass and
these shrubs.
Mgrass = above-ground biomass in grass on grassland at time t that would have occurred in the
absence of the project activity (t dm/ha) = 11 t dm/ha (extracted from Zomer et al., 2006)
Mwoody (t)= above-ground woody biomass of woody perennials at time t that would have occurred in
the absence of the project activity (t dm/ha) = 16 t dm/ha (extracted from Zomer et al., 2006)
M(t=0) = M(t) = 11 +16 = 27 t dm/ha
22
Thus Carbon stock in Above ground biomass for Grassland with trees is:
BA(t) = M(t) * 0.5
BA(t) = 27 t dm/ha * 0.5= 13.5 t C/ha
3.5.1.3 Stratum: Biomass in annual crops
Biomass in annual corps is ignored since it is considered transient
3.5.1.4 Stratum: The perennial crops
Mwoody (per) (t) = above-ground woody biomass of perennial crops at time t that would have occurred
in the absence of the project activity (t dm/ha) = 24 t dm/ha (extracted from Zomer et al., 2006)
M(t=0) = M(t) = 0 + 24 = 24t dm/ha
Thus Carbon stock in above ground biomass for perennial crops is:
BA(t) = M(t) * 0.5
BA(t) = 24 t dm/ha * 0.5= 12 t C/ha
3.5.2 For below-ground biomass
BB(t) is calculated per stratum i as follows:
Because living biomass carbon pools are expected to be constant, the average below-ground carbon stock is
estimated as the below-ground carbon stock in grass and in woody biomass; biomass in crops is ignored
since it is considered transient:
BB(t=0) = BB(t) = 0.5 * (Mgrass * Rgrass+ Mwoody (t=0) * Rwoody)
where:
BB(t) = carbon stocks in below-ground biomass at time t that would have occurred in the absence of
the project activity (t C/ha)
3.5.2.1 Stratum: BB Grassland
We have not been able to find any local studies of root-to-shoot ratios for grasses and woody perennials in
grassland in Bolivia. As a default we have used the value listed in IPCC GPG Table 3A.1.8. sub
tropical/tropical grasslands in tropical moist and wet climates, which for grasslands is 1.58 tdm/ dm.
BB (grassland)= 0.5 * (11*1.58 + 0*1.58) = 8.69t C/ha
3.5.2.2 Stratum: BB Grassland with trees
Over time grassland is converted to fallow land with secondary woody vegetation, which without human
disturbance (which is not the case) will become a secondary forest. With this in mind the root to shoot ratio
23
should be less than 1.58 (IPCC default value) and more than the ratio for secondary forest (0.42 IPCC default
value). Since no information currently exists and the areas are still far from being a secondary forest we
took a conservative approach, using for Rwoody the same value as for Rgrass.
BB (grassland with trees)= 0.5 * (11*1.58 + 16*1.58) = 21.33 t C/ha
3.5.2.3 Stratum: BB perennial crops
The basic perennial crops are banana and palm heart. Based on the literature available, a conservative root
to shoot ratio of 1 tdm/ dm is used.
BB (perennials) = 0.5 * (0*1.58 + 24*1) = 12 t C/ha
3.5.3
Overall baseline scenario
The project will be rolled out to 5.000 ha plantation; the most likely distribution of project activities per
stratum will be as shown in table 3.6.
Table 3.6: distribution of activities in different strata
Ai
ha
1218
487
2947
349
5000
Stratum (i)
1. Grassland
2. Grassland with existing trees
3. Annual crops/fallow land
4. Perennials
Totals
Ai
relative
24%
10%
59%
7%
100%
Carbon stocks for each specific baseline per stratum are summarized in table 3.7
Table 3.7: Existing carbon stocks per stratum
Stratum (i)
1. Grassland
4. Perennials
Totals
Ai
ha
1218
487
2947
349
5000
Ai
relative
24%
10%
59%
7%
100%
M(t)
tdm/ha
11.00
27.00
0.00
24.00
BA(t)
tC/ha
5.50
13.50
0.00
12.00
r/s ratio
1.58
1.58
1.00
BB
tC/ha
8.69
21.33
0.00
12.00
Bt
tC/ha
14.19
34.83
0.00
24.00
B(t)
tC
17,284
16,946
8,365
42,596
Carbon benefits will be calculated for each of the different baseline strata. Assuming the plantations will be
distributed among the strata as shown in table 3.7 this means the average amount of existing carbon in the
baseline is 8.52 tC/ha which equals to 31.2 tCO2e.
24
4.
Project activities and Management System
4.1
Reforestation activities
Reforestation activities will be carried out on land which is at risk of becoming degraded by inefficient land
use practices. Once productivity falls significantly as a result of soil degradation, farmers move on to nearby
forest areas.
The proposed activity contributes to sustainable development by introducing an Integrated Land Use
system which seeks to improve the efficiency of land use practices over the entire farm, whilst also taking
into account the current and future needs of the farmer family. Sustainable crop and timber production will
generate income in the short, mid, and long term.
Tree species selection for specific sites is based on site evaluations according to protocols developed by the
project (annex 3). Tree selection depends on proven suitability for the specific site conditions and purposes
of the trees species in the (agro) forestry systems (timber production, shade, soil improvement, etc).
Plantations for sustainable wood production: Only native tree species will be planted, except for the
Tectona grandis, which will be planted only on a small scale. The tree species proposed for this project can
be found in table 4. 1, additional to this plantation might be mixed with a maximum of 50 plants of the
species: Cederela fissilis and, Swietenia macrophylla. These high valuable species are only planted in very
small numbers due to their sensitivity to diseases and attacks of the Hypsipyla grandella, which can be
avoided by planting these species in very low densities.
Table 4.1: proposed tree species for the ArBolivia project
Nr
Scientific name
1 Aspidosperma macrocarpon
2 Buchenavia oxycarpa
3 Calophyllum basiliense
4 Centrolobium tomentosum
5 Dipteryx odorata
6 Guarea rusby
7 Schyzolobium amazonicum
8 Stryphnodendron purpureum
9 Tapirira guianensis
10 Tectona grandis
11 Terminalia amazonica
12 Terminalia oblonga
13 Virola flexuasa
Common name
Jichituriqui
Palo María
Tejeyeque
Almendrillo
Trompillo de altura
Serebo
Palo yugo
Palo román
Teca
Gabún
In almost all cases trees are planted in blocks, these blocks are distinguished as separated sectors with an
own unique waypoint (identification code).
The average size of a sector is: 0.84 hectares. As can be shown in figure 4.1, in almost 70% of the surface
planted until now, sectors have a surface of 1 hectare or less.
25
Figure 4.1: surface planted per sector sizes
5.6%
1.5%
2.0%
0.6%
surface <=1 ha
1< surface <= 2 ha
20.8%
2< surface <= 3 ha
3< surface <= 4 ha
69.5%
4< surface <= 5 ha
5< surface <= 8 ha
As shown in the figure 4.2 almost 87% of the sectors have a size up to 1 hectare.
Figure 4.2: Distribution of sectors per surface class
1.7%
0.4%
0.4%
0.1%
10.9%
surface <=1 ha
1< surface <= 2 ha
2< surface <= 3 ha
3< surface <= 4 ha
4< surface <= 5 ha
86.6%
5< surface <= 8 ha
All sectors are identified with a unique waypoint number. For each sector all relevant site data are stored in
paper files and in the database, data like; site quality characteristics, historic and actual land use,
coordinates, species planted, number of trees, plantation development , growth rates and management
activities executed.
Sectors with the same characteristics belong to a stratum, for each stratum single species tree-growth will
be monitored by measuring permanent sample plots.
Project strata are defined based on:
1. Tree species planted
2. Former land use (grassland, grassland with trees, annual and perennial crops)
26
4.2
Integrated Land Use Planning
All activities are embedded within a comprehensive land use planning system. If land use can be improved,
agriculture will become more efficient and the deforestation due to traditional slash and burn methods can
be reduced. In addition specific land use will be officially registered and specific areas will be registered as
protected areas. The land use plan is based on the elaboration of the field forms annex 2 (form1,2,3,4,5,6).
Integrated land use planning is based on major land use planning, in other words the most intensive use of
land units considering the carrying capacity according biophysical criteria which is defined in a ‘Plan de
Ordenamiento Predial’ (POP), which has to be submitted for approval to the ABT (Authority for Territories
and Forests). Farmers participate in the process of gathering of date and in the preparation of the final
documents.
The reforestation activities must be embedded in the integrated land Use Planning order to mitigate the risk
of forest plantations conflicting with short term income or food security.
4.3
Technical support and review:
Species-site matching
CETEFOR established procedures for trees species and site selection, annex 3.
Tree species selection for specific sites is based on site evaluations and depends on proven suitability for the
specific site conditions and function of the trees species in the (agro) forestry systems. The functions
include, amongst others, timber production, shading and nitrogen fixation.
Step 1: Selection of potential sites for reforestation activities
Site selection and the potential for reforestation is defined together with the small holder, taking account of
the current and future needs of the farmer family and the biophysical characteristics of the area. This phase
results in an integrated farm plan (PIF). Based on this plan and the eligibility criteria area where trees will be
planted is defined.
Step 2: Matching site and species
For these sites tree species selection is based on site evaluations, using the species-site selection and
plantation design procedures developed by CETEFOR (annex 3).
Species selection
The site selection criteria ensure that the species most appropriate to the specific site and the species can
be recommended. Account may also be taken of the owner’s preference in terms of the type of production
and the goals of the plantation. Table 4.2 shows the species used in this project and their individual
characteristics. The design of each plantation is formulated using this table.
27
Table 4.2: Species requirements
Light
t
e
Shadow
Soil compaction
f
f
Illumination
Soil fertility
Loamy
t
Clay
Sandy
Texture
Soil depth
Tolerates Flooding
Poor
imperfect
Drainage
Free
pH
pH-tolerance
Species
Scientific name
Buchanavia sp
Calophyllum brasiliense
Cedrela fisillis
Dipteryx odorata
Dipteryx sp
Guarea rusby
Hymenaea courbanil
Schlizobium amazonicum
Stryphnodendrum purpureum
Swietenia macrophylla
Tabebuia sp.
Tapirira guianensis
Tectona grandis
Terminalia oblonga
Virola flexuosa
Common name
Jichituriqui
Verdolago negro de pepa
Palo maría
Cedro
Tejeyeque
Almendrillo
Almendrillo amarillo
Trompillo de altura
Paquio
Serebo
Palo yugo
Mara
Tajibo
Palo román
Teca
Verdolago negro de ala
Verdolago amarillo
Gabún
L-M f
M
f
L-M
M
e
L-M f
L-M f
L-M f
f
L
f
L - M ne
L-M
M
f
ne
L-M f
M
f
M
f
L-M
L
L = Low
f = favourab le
ne = not very demanding
e y = demanding when young
e = demanding
em = demanding on maturity
t y = tolerant when young
nty = no tolerant when young
M = Medium
t = tolerant
H = High
nt = not tolerant
Source: Cetefor 2007 and np field data Sicirec Bolivia ltda
nt nt
t t t
t t t
nt nt nt
t nt nt
nt
nt t
t nt nt
t nt t
t t t
t t t
t nt nt
t t t
t t t
nt nt nt
nt nt t
t t t
t t t
ne
ne
f
f
f
f
nt ne
t
f
f
f
f
f
f
nt
nt
ne
ne
nt
f
ne ne ne ne nt
ne ne ne ne t
f
f
f nt
f f
f
e
f
f nt
ne f f
ne
f
nty
em
e
e
e
e
e
t
em
ty
e
e
nty
nt
t
ey
ey
nt
nt
nt
nt
ey
nt
f
ey
ey
tj
nt
nt
t
ey
Plantation design and forest management system
Based on site characteristics, species requirements and production criteria of the farmer and the AACS, the
plantation will be designed according to protocols developed by the project.
All plantations will be managed according to a management plan and adjusted periodically in line with
evaluations of the plantations by project staff. Specific silvicultural and forest management tasks will be set
in discussion with the farmer. The forest plantations will be harvested in the future, but a forest
management system will be adopted to minimise CO2 emissions (by minimising clear-cutting) and thereby
maximizing carbon sequestration. The application of a poly-cyclic harvesting system will guarantee a
relatively high average carbon storing capacity in the plantations.
Nursery techniques
Seed collection is carried out by the project’s Plant Production Unit. Plant production is certified by the
National Institute for Innovation of Agriculture and Forestry (INIAF), which is the regulatory agency for seed
28
and plant propagation (formerly the Programa Nacional de Semillas PNS). Seed sources are registered
sources, and selected on specific characteristics for quality. Since the Asocación Accidental CETEFOR SICIREC
has control over the seed sources, nurseries and the distribution of plants to the plantation site, monitoring
of the chain from seed tree to planting in the field is guaranteed.
Nursery: For plant production genetic material is used according to the standards and regulations of the
National Institute for Innovation and Forestry (INIAF) and is certified by the same governmental agency
(formerly conducted by the Regional Seed Office-Cochabamba). Plant production is done in nurseries
according to the standards and regulations of the same entities for all species, except Schizolobium
amazonicum, a species sown directly in the field.
Site preparation
Sites will be prepared to enhance the early growth and development of the planted seedlings. The area
around the planting spots will be weed free before planting. Planting holes of 20 cm deep and 20 cm wide
on cropland and 35 cm deep and 30 cm wide on pasture land will be dug. CO2 emissions will not be
significant due to the low soil disturbance caused by this form of site preparation.
Planting
Tree plantations for wood production
Planting distances will be such as to maximize stand development for timber production: the norm is 3.0 m
x 3.0 m (1,111 plants per hectare) or 3 x 4 m (833 plants per hectare) according to tree species and specific
site conditions. Accurate alignment of planting lines and spacing within the lines is important for
subsequent tending operations. Since there is no pronounced dry season, planting can be done throughout
the year. Plants will be delivered to the farmer once site preparation is done, while planting should be done
within 2-3 weeks after delivering the plants.
After this period plantation quality and survival rate will be checked to determine whether any replanting is
necessary. Where survival is less than 90%, replanting will be carried out.
Tending and weed control
Weed control, especially in the first few years is crucial for growth, survival rates and quality of the
plantation. Weed control will be manual and no herbicides will be used to avoid damage to the plantations
and the environment.
Thinning and pruning
Thinning and pruning of the plantations will be important to ensure that they maximise the proportion of
large stems with clear timber. The purpose of thinning is: i) to focus the growth of the stand on the most
vigorous stems and ii) to reach the targeted final product diameter as soon as possible. The object of
pruning is to produce high quality timber. Thinning and pruning regimes depend on species and the growth
rates achieved in the project area. The impact of thinning and other silvicultural measures on carbon
sequestration is accounted for in the quantification of the actual net GHG removal by sinks. The impact of
pruning is accounted for by application of a reduced biomass expansion factor (1.4 for all tree species).
Harvesting
Although these forest and agro-forestry plantations will be harvested in the future, a forest management
system will be introduced to minimize CO2 emissions and maximize CO2 sequestration. The application of a
poly-cyclic harvesting system in forest plantations will guarantee a relatively high average carbon storing
capacity.
29
Wind
If there is risk that a specific plantation may be subject to extreme winds (no natural wind barriers exist) this
will be considered in species selection and the establishment of wind breaks within the project.
Fire control
Fire risks exist since farmers are used to burn old pastures to promote the renewal of pasture and this might
cause fire in the plantations if no mitigation measures are taken. To reduce the risk of fire the following
measures are taken:
1. Capacity building in the whole community on the control of renewal (burning) of pasture lands
2. Fire breaks, between pasture land and the newly established plantations (10-20m)
3. Removal of dry weeds and other vegetation in the most delicate parts of the plantations.
Animal control:
Risks exist since most farmers manage husbandry (cows, pigs and chickens) for their livelihood income. In
order to protect forestry plantations from cattle or pig invasions that can generate enormous damage
especially during the initial stage, protective fencing will be placed around the planting site. The famer is
obliged to fence the area identified while the project supports the farm household with a maximum of 1000
mts of barbwire per hectare.
Pest control
Due to proper site selection and good silvicultural management procedures, risk for pest and diseases is
minimized, since pest and diseases usually occur in stressed crops. However, the project area will be
routinely assessed for any pest and disease problems that may arise. If pests or diseases appear, these will
be controlled by using organic products and in the worst case scenarios chemical control methods may be
used as a last resort but only after careful consideration of the environmental impacts.
30
5.
Quantification of carbon services
5.1
Crediting period
The crediting period is 40 years from 2007.
Credits will be claimed ex-ante. This option has been selected on the basis that neither the communities nor
the project coordinator have sufficient funds to carry out the ongoing reforestation activities without
further up front funding.
Payments to the farmers are made during this period. However these payments are not directly related to
carbon offsets but are based instead on the satisfactory execution of specific forest management activities,
as described in section G of the PDD.
5.2
Estimation of the project’s net GHG removals by sinks
The actual net GHG removal by sinks relates only to the changes in carbon pools for the project scenario.
GHG removals due to project activities are estimated per stratum (grassland, grassland with trees, perennial
and annual crops) for each of the different tree species and for each plantation design.
Total carbon stock for the project scenario at the starting date of the project activity (t=0) is the same as for
the projection of the baseline carbon stock (t=t), therefore, for each different tree species and for each
different plantation design:
N(t=0) = B(t=0)
For all other years, the carbon stocks within the project boundary at time t (N(t)) will be calculated as
follows:
I
N(t) = ∑(NA(t) i + NB(t) i) * Ai
i
where:
N(t) =
total carbon stocks in biomass at time t under the project scenario (t C/ha)
NA(t) i = carbon stocks in above-ground biomass at time t of stratum i under the project scenario (t
C/ha)
NB(t) i = carbon stocks in below-ground biomass at time t of stratum i under the project scenario (t
C/ha)
Ai =
project activity area of stratum i (ha)
i=
stratum i (I = total number of strata)
The long term average GHG benefit (LA) is determined by averaging the expected total GHG benefit for the
length of the crediting period
31
5.2.1 For above-ground biomass
The following calculations will are performed for each stratum:
NA(t) is calculated per stratum i as follows:
NA(t) =
where:
NA(t) =
T(t) =
0.5 =
T(t) =
where:
T(t) =
SV(t) =
BEF =
WD =
T(t) * 0. 5
carbon stocks in above-ground biomass at time t under the project scenario (t C/ha)
above-ground biomass at time t under the project scenario (t dm/ha)
carbon fraction of dry matter (t C/t dm)
SV(t) * BEF * WD
stem volume at time t for the project scenario (m3 /ha)
biomass expansion factor (over bark) from stem volume to total volume (dimensionless)
basic wood density (t dm/m3)
SV estimates are based on preliminary data from on-site measurements of DBH and height in sample plots
of reference stands, for the species S. amazonicum (fast growing), G. rusby, C.tomentosum (medium), D.
odorata and T.amazonica (slow). These reference stands are located in the Cochabamba Tropics with similar
characteristics as the rest of the project areas. Stands are still young, so no complete data set for the whole
rotations exists, but based on the preliminary data of these species, added with expert knowledge
(Chaurara B., Juchasara F., Goitia J., Orosco F., Stilma A 2), the best possible estimations are made.
These growth estimations will be adjusted as soon more accurate data is coming from permanent sample
plots established in the reference stands and the new planted areas.
The mentioned species are representative for tree species proposed, regarding volume and biomass
increment, see table 5.1.
2
Former employees in charge of the plantation schemes of the FAO project Manejo Integral de los Recursos Naturales
en el Tropico de Cochabamba y los Yungas de La Paz,
32
3
Table 5.1: Growth estimation for 5 trees species in M per hectare
Age in
years
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
33
34
35
Dipteryx odorata
Guarea rusby
Schizolobium amazonicum
Standing wood Extracted wood Standing wood Extracted wood Standing wood Extracted wood Standing wood Extracted wood Standing wood Extracted wood
0
0
0
0
0
0
0
0
0
0
15
0
8
0
19
0
28
0
12
0
30
0
16
0
38
0
56
0
24
0
45
0
24
0
57
0
84
0
36
0
45
15
32
0
76
0
84
28
48
0
60
0
40
0
67
29
112
0
60
0
75
0
36
12
86
0
140
0
72
0
90
0
44
0
105
0
126
42
84
0
79
26
52
0
124
0
154
0
64
32
94
0
60
0
143
0
182
0
76
0
109
0
68
0
162
0
158
53
88
0
124
0
76
0
135
45
186
0
100
0
104
35
63
21
154
0
214
0
112
0
119
0
71
0
173
0
0
242
124
0
134
0
79
0
192
0
28
0
105
31
149
0
87
0
211
0
56
0
117
0
123
41
95
0
184
46
84
0
129
0
138
0
103
0
203
0
84
28
141
0
153
0
83
28
222
0
112
0
153
0
168
0
91
0
241
0
140
0
165
0
137
46
99
0
260
0
126
42
136
41
152
0
107
0
279
0
154
0
148
0
167
0
115
0
0
298
182
0
160
0
182
0
123
0
19
0
158
53
172
0
197
0
131
0
38
0
186
0
184
0
0
212
104
35
57
0
214
0
196
0
15
0
112
0
76
0
0
242
208
0
30
0
120
0
67
29
28
0
220
0
30
15
128
0
86
0
56
0
232
0
45
0
136
0
105
0
84
0
244
0
60
0
108
36
124
0
84
28
0
256
75
0
116
0
143
0
112
0
12
0
64
26
124
0
162
0
140
0
24
0
79
0
132
0
136
45
126
42
36
0
94
0
140
0
155
0
154
0
48
0
109
0
0
148
174
0
182
0
60
0
MAI = 8 m3/year
MAI = 28 m3/year
MAI = 15 m3/year
MAI = 19 m3/year
MAI = 12 m3/year
375 m3 per whole rotation
Mean annual increment (MAI) of the other species are estimated within these ranges, and can be found in
annex 4a. Since sufficient growth data does not exist for all species, estimations are made based on local
expert knowledge.
First species were grouped into fast growing, medium growing and slow growing tree species, see table 5.2.
In the preparation phase of the ArBolivia project, several small woodlots and solitary trees of: Aspidosperma
macrocarpon, Buchanavia sp, Cedrela fissilis, , Calophyllum brasiliense,, Stryphnodendron purpureum ,
Swietenia macrophylla, Tapirira guianensis,, Terminalia oblonga, Virola flexuosa were revised, based on
measurements of these trees and expert knowledge potential growth of these species was estimated.
Table 5.2: Tree species grouped for growth class
Short - rotation 10 - 15 years
Medium rotation 15 - 30 years
Long rotation > 30 years
Scientific name
Common name
Scientific name
Common name
Scientific name
Common name
Serebo
Jichituriqui
Buchenavia oxycarpa Verdolago negro (pepa)
Palo yugo
Palo María
Dipteryx odorata
Almendrillo
Tejeyeque
Terminalia amazonica Verdolago negro (de ala)
Guarea rusby
Trompillo de altura Terminalia oblonga Verdolago amarrillo de ala
Tapirira guianensis
Palo román
Tectona grandis
Teca
Virola flexuosa
Gabún
33
The estimated Mean Annual Increment (MAI)per species is shown in table 5.3
Table 5.3: Estimated Mean Annual Increment (MAI) in M3/ha for the whole rotation
Growth
class
Fast
Fast
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Scientific name
Common name
Guarea rusby
Tapirira guianensis
Tectona grandis
Virola flexuosa
Buchenavia oxycarpa
Dipteryx odorata
Terminalia oblonga
Serebo
Palo yugo
Jichituriqui
Palo María
Tejeyeque
Trompillo de altura
Palo román
Teca
Gabún
Almendrillo
MAI
(M3/ha)
28
28
18
15
15
19
19
15
15
8
8
8
12
In annex 4a per tree specie the growth estimations per year of all species are shown.
Consistent application of BEF will be secured over total stem volume. A default BEF of 1.5 proposed in table
3A1.10 of the IPCC good practice guidance for LULUCF (see annex 5) is used in order to obtain a
conservative estimate of total biomass
Values for WD are used and shown in table 5.4 below.
Table 5.4: Oven dry wood density (g/cm3) per tree specie
Growth
class
Fast
Fast
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Scientific name
(g/cm3)
Guarea rusby
Tapirira guianensis
Tectona grandis
Virola flexuosa
Buchenavia oxycarpa
Dipteryx odorata
Terminalia oblonga
Sources: 1) FAO 2002 2)Brown, 1997 3) INIA
34
Common name
Wood
density
Serebo
Palo yugo
Jichituriqui
Palo María
Tejeyeque
Trompillo de altura
Palo román
Teca
Gabún
Almendrillo
0.49
0.52
0.67
0.55
0.58
0.52
0.60
0.52
0.44
0.77
0.91
0.66
0.75
1
2
3
1
1
2
1
2
1
1
1
1
1
5.2.2 Carbon stocks for below-ground biomass
NB(t) is calculated per stratum i as follows:
NB(t) =
where:
NB(t) =
T(t) =
R=
0.5 =
T(t) * R * 0.5
carbon stocks in below-ground biomass at time t under the project scenario (t C/ha)
root to shoot ratio (dimensionless)
carbon fraction of dry matter (t C/t dm)
The conservative default value for R, of 0.42 (secondary tropical and sub tropical forest) of the IPCC´s good
practice guidance for LULUCF, Table 3A.1.8 are used (annex 5)
5.2.3 Carbon stocks for above and below-ground biomass
Figure 5.1 shows the sum of the accumulative above and below ground carbon per hectare during the
crediting period, for the proposed species mentioned. These increments per hectare will not vary
significantly, since appropriate site selection is done and if expected tree growth is expected to be low,
different specie will be selected for the site, which will be better adapted to specific site conditions.
Figure 5.1: Above and below ground carbon increase per hectare per year (tn/C)
Table 5.5 shows the long term average carbon benefit of the above and below ground carbon per hectare,
over the 40 years crediting period and its equivalent in CO2e/ha. The complete set of data on yearly carbon
increment per hectare and the long term average GHG removal per specie can be found in annex 4b.
35
Table 5.5: Long term average C and CO2e in tn/C/ha
Above and
Gross
Below
project
Ground
GHG
Growth class
Scientific name
Common name
Carbon
removal
(tC/ha)
(tCO2e/ha)
Fast
Schyzolobium amazonicum Serebo
68
248
Fast
Stryphnodendron purpureum Palo yugo
72
263
Medium
Aspidosperma macrocarpon Jichituriqui
88
323
Medium
Palo María
59
215
Medium
Tejeyeque
63
231
Medium
Guarea rusby
Trompillo de altura
78
286
Medium
Tapirira guianensis
Palo román
83
303
Medium
Tectona grandis
Teca
68
249
Medium
Virola flexuosa
Gabún
55
203
Slow
Buchenavia oxycarpa
64
234
Slow
Dipteryx odorata
Almendrillo
76
277
Slow
76
278
Slow
Terminalia oblonga
62
228
Once carbon per hectare is calculated per hectare carbon calculation is made for the whole surface
proposed to be planted, based on the following planting scheme as shown in table 5.6
Table 5.6: planted areas and projected surface
Surface
(ha)
Year
2007
16
2008
538
2009
675
2010
342
Subtotal established
1,571
2011
500
2012
1,000
2013
1,000
2014
929
Subtotal scheduled
3,429
Total
5,000
A projection for the distribution of tree species types is made for tree class as shown in table 5.7.
Table 5.7; relative distribution of tree types
distribution
Tree type
as % of total
(growth)
surface
Fast
6%
Intermediate
Slow
36
80%
14%
A projection per tree species is shown in annex 4c. However it must be mentioned that this is not the
definitive tree species choice, since this depends mainly on the following three factors:
• Site selection: Species have to match with sites, so the decision made on what tree species will be
planted will be done after the site survey is done.
• Availability of seed: Genetic material of almost all species is recalcitrant which means it can´t be stored
and has to be distributed within a very short period to the nurseries. Since these seed can´t be stored
and the harvest fluctuates from year to year due to nature of the specie and the climatic circumstances,
the availability of seeds from some species varies and as a consequence the supply of plant material per
specie might vary from year to year.
• Farmer’s opinion: Farmers are partners within the project and they take the final decision on tree
species considering the two points mentioned before.
5.3
Carbon loss due to plantation activity
Due to weeding within the plantation and also to closure of the canopy, which results in the competition for
light, the light-demanding grasses and perennials will disappear over time. This will result in some removal
of carbon.
The level of removal is calculated using the same equations as for the planted trees:
I
N(t) = (NA(t) i + NB(t) i) * Ai
I
The level of carbon loss is based on the existing biomass stock in the baseline scenario per stratum
compared to the project scenario.
N(t=0) = B(t=0)
This means per stratum at the start of the project
1.
2.
3.
4.
Grassland
Perennials
B(t=0) = N(t=0) = 14.19 tC
B(t=0) = N(t=0) = 34.83 tC shrubs and trees represents 20.64tC
B(t) = N(t) = transient
B(t=0) = N(t=0) = 24
A summary of the above data is summarized in table 5.8 and extrapolated for the whole project area.
Table 5.8: Carbon stocks in the baseline
Stratum (i)
Ai
ha
1. Pasture
4. Perennials
Total surface
GHG stock/Ha
37
1,218
487
2,947
349
5,000
24%
10%
59%
7%
100%
8.52 tn C/Ha
M(t)
BA(t)
r/s ratio BB
Bt
B(t)
tdm/ha tC/ha
tC/ha
tC/ha
tC
11.0
5.5
1.58
8.69
14.19 17,284
27
13.5
1.58
21.33
34.83 16,946
0
0
24
12
1.00
12.00
24.00
8,365
42,596
Weeding is one of the maintenance activities of the plantations and is carried out regularly until canopy
closure is reached. After this no weeding is necessary because the light-demanding grasses and perennials
disappear almost completely due to competition for light. Planting distances and management of the
plantations are determined on the assumption that complete canopy closure will be complete after 4 years.
After this grasses and perennials will have disappeared almost completely and existing shrubs and trees will
be maintained, as shown below and summarized for the whole area in table 5.9. The rest of the carbon will
be disappearing as a result of site preparation and shade from the growing trees.
1.
2.
3.
4.
Pasture
Perennials
N (t=4) 0 tC
N (t=4) = 20.64 tC
N(4) = transient
N(t=4) = 0
Table 5.9: carbon stocks maintained after site-preparation
Stratum (i)
1. Grassland
4. Perennials
Total surface
GHG stock/Ha
Ai
ha
1218
487
2947
349
5000
2.01
24%
10%
59%
7%
100%
tn C/Ha
M(t)
tdm/ha
0.00
16.00
0.00
0.00
BA(t)
tC/ha
0.00
8.00
0.00
0.00
r/s ratio
1.58
1.58
1.00
BB
tC/ha
0.00
12.64
0.00
0.00
B(t)
tC/ha
0.00
20.64
0.00
0.00
B(t)
tC
10,042
10,042
For the full project the carbon loss per hectare is multiplied for the surface of the stratum:
I
N(t) = (NA(t) i + NB(t) i) * Ai
I
This is shown in shown in table 5.10
Table 5.10: carbon loss due to site preparation and shade of the trees
Stratum (i)
1. Pasture
4. Perennials
Total surface
Negative GHG removals/Ha for N(t>4)
Ai
ha
1218
487
2947
349
5000
6.51
24%
10%
59%
7%
100%
tn C/Ha
M(t)
tdm/ha
11.00
11.00
24.00
BA(t)
tC/ha
5.50
5.50
12.00
r/s ratio
-
BB
tC/ha
8.69
8.69
12.00
B(t)
tC/ha
14.19
14.19
24.00
B(t)
tC
17,284.46
6,903.99
8,365.29
32,554
This is a conservative approach, since not necessarily all weeds will disappear and, in the case of the
perennial stratum, some of the perennials will survive as undergrowth within the plantations. However
since it is hard to estimate what proportion will survive it has been assumed that all undergrowth will
disappear by the fourth year, when canopy closure is assumed to be complete.
After t=4 no extra loss of carbon which existed in t=0 is expected.
38
Carbon loss is equally distributed over the first 4 years. Table 5.11 shows the carbon loss distributed over
the first 4 years per hectare.
I
N(t) = (NA(t) i + NB(t) i)
I
Table 5.11: Carbon loss per ha per stratum (i) in tC/ha
Stratum
NA
NB
NA
NB
NA
NB
pasture
pasture
grassland with existing trees
grassland with existing trees
Perennials
Perennials
1
1.38
2.17
1.38
2.17
3.00
3.00
Year
2
1.38
2.17
1.38
2.17
3.00
3.00
3
1.38
2.17
1.38
2.17
3.00
3.00
4
1.38
2.17
1.38
2.17
3.00
3.00
Year
2
13.01
13.01
22.00
3
13.01
13.01
22.00
4
13.01
13.01
22.00
Total loss
5.50
8.69
5.50
8.69
12.00
12.00
In table 5.12 this is summarized in CO2e.
Table 5.12: Carbon loss per ha per stratum (I) in tCO2e/ha
Stratum
Grassland
Grassland with trees
Annual
Perennial
5.4
1
13.01
13.01
22.00
Total loss
52.03
52.03
88.00
Net anthropogenic GHG removals
The ex-ante estimate of net anthropogenic GHG removals for the different species per ha is the result of:
Long term Average net GHG removals MINUS The sum of Long term average Negative removals MINUS
the sum of average net baseline GHG removals.
Leakage = 0
The result of this equation for a crediting period of 40 years, is shown in table 5.13, yearly net GHG
removals” per hectare are shown in annex 4b in annex 4c the total long term average net GHG removal for
the whole project is shown.
39
5.13: Ex-ante estimate of net long term average anthropogenic GHG removals per hectare over a 40 year crediting period
Net average GHG removal (CO2e/ha) over
crediting period for Baseline
Growth class
Fast
Fast
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Scientific name
Common name
Guarea rusby
Tapirira guianensis
Tectona grandis
Virola flexuosa
Buchenavia oxycarpa
Dipteryx odorata
Terminalia oblonga
Serebo
Palo yugo
Jichituriqui
Palo María
Tejeyeque
Trompillo de altura
Palo román
Teca
Gabún
Almendrillo
Grassland
Grassland
with trees
247
262
322
213
229
285
302
248
202
233
276
277
227
247
262
322
213
229
285
302
248
202
233
276
277
227
Annual
crops
Perennial
crops
248
263
323
215
231
286
303
249
203
234
277
278
228
246
261
321
212
228
284
301
247
201
232
275
276
226
For the entire project actual net GHG removals are multiplied with the surface of each stratum.
Considering the planting schedule, the distribution of tree species and the application of the formulas
mentioned in this paragraph for the calculation of above and below ground biomass per specie and per
hectare, it is estimated that for the whole project activity the long term average GHG removals in tons of
CO2e will be: 1,264,299 tCO2e, over the 40 year crediting period.
Figure 5.2 shows the accumulated GHG removals by the trees in CO2e within the project boundary until
2047.
Figure 5.2: total actual net GHG removals in tons/ha/year
40
6.
6.1
Leakage
Risk of Carbon loss attributable to the project activity
The risk of leakage or an unintended loss of carbon stocks outside the project boundary, attributable to the
project activities is considered to be insignificant, for the reasons outlined below:
The project is managed so as to avoid leakage. This means that forestry production will not replace
agricultural production.
6.1.1 Displacement of households
There is no displacement of households due to the project, since only a small portion of the farmland is
reforested. In fact, the project will actually serve to reduce the risk of migration from the area to nearby
forest areas due to better land use practices. There is a current tendency for farmlands to become degraded
through inefficient land use practices. Once productivity has fallen excessively as a result of soil
degradation, farmers simply move to new areas of forest in the vicinity. The “Integrated Land Use”
approach outlined above is intended to introduce efficient land use practices across the entire farm, whilst
also taking into consideration the current and future needs of the farmer family. Sustainable crop and
timber production will generate income in the short, mid, and long term, a factor which subsequently
reduces the risk of farmers moving to other, e.g. forested, places.
As outlined below evidence shows that the displacement of pre-project activities will not cause
deforestation attributable to the project activity:
6.1.2 Displacement of cropland:
Land deforested 10 or more years prior to reforestation had previously been subjected to a “slash and burn”
system. After rice cropping, maize is normally planted and after that it is left fallow. In the first fallow period
it normally takes at least 4 years before the land can be used for agriculture again. After a second cultivation
period, it takes at least 7 years before it can be used again for cropping and after that it takes approximately
10 years, even on the better soils, before land can be recovered. On the poorer soils this period can be up to
15 years. Moreover, crop production per hectare decreases as the fallow period increases. If the fallow
period is not extended crop yields fall even further.
On croplands established 10 years ago or more and which are now in the second and third cycle, yields fall
to 70% or less to of yield levels in the 1st cycle. On croplands established before 1990 and which are now in
the 4th or subsequent cycle, the average annual crop yield falls to 50% or less of yield levels in the 1st cycle.
Some farmers are using their cropland almost continuously making use of fertilizers. In areas where
fertiliser is used, soil degradation also continues and annual crop yield decreases, rendering the use of
fertiliser uneconomic. Due to the relatively small level of foregone crop production, it can be evidenced that
shifted activities due to tree planting can be absorbed by the surrounded lands. Therefore, in accordance
with AR-AMS0001/version 05 (28), leakage due to displacement of crop production is considered
insignificant.
41
6.1.3 Displacement of pasture land:
Leakage on pasture land through shifting of activity will occur in less than 10% of cases, since the amount of
cattle which may be moved to areas outside the project boundary is not significant. It can be evidenced
that trees planted on pasture land will not cause deforestation, since the planted areas are only a small
portion of the total degraded pasture land, the total pasture land on a farmer’s parcel and the other
surrounding areas, such as pasturing on the side of the road, are likely to receive the shifted activities
(Knoblauch 2007, Sejas 2007). Therefore, in accordance with AR-AMS0001/version 05 (28), leakage due to
displacement of grazing activities is considered insignificant.
Moreover, grazing systems and silvipastoral systems will only be implemented on roughly 5% of the project
area. Therefore, in accordance with AR-AMS0001/version 05 (28), leakage due to displacement of grazing is
considered insignificant.
6.2
Monitoring leakage and mitigation
As evidenced in paragraph 6.1below, leakage is not significant. However potential leakage will nevertheless
be monitored over time, by monitoring land use change. This monitoring may also demonstrate a positive
effect or collateral carbon benefits.
In addition, measures such as the introduction of agroforestry systems and silvipastoral systems are also
being implemented within the project area, avoiding even a minimum risk of displacement of activities due
to the projects’ activities. These measures are summarized in table 6.1.
Table6.1: Mitigation measures to avoid leakage
Activity Type
Tree Planting
42
Potential Leakage
Tree planting might lead
to displacement of
household, farmers, and
displacement of crop
production and pasture
land
Mitigation measures
Integrated Land use Planning will ensure farmers
have sufficient land for their crops generating income
in the short, tree planning is not competing with
their income or food security in the short, mid and
long term
Introducing agro forestry systems, which are more
sustainable over time than rice, yield higher incomes
per hectare and per working day and generate
subsistence products for the farmer and his family
Improving grazing systems introducing silvopastoral
systems and improved pastures
6.3
Risk management
Risk management is based on the establishment of a common responsibility and the shared interests
between the farmers and the AACS. The aim of the AACS is not only to motivate famers in a participatory
process to plant trees, but also for the AACS to form a true partnership with the farmers and for both
parties to unite to form the ArBolivia project. In this way the social risks will be minimized. In table 6.2 a
description is made of the main risks, and the mitigation measures to minimize risks.
Table 6.2:: Main risk factors
Permanence Risks
Level of risk Management Measures
(low/medium
/high)
Legal
Conflicts land tenure
Illegal tree cutting
Medium
Medium
Verification of documents and by the community before starting the activities
Forest Committees in coordination with community authorities responsible for
control
Registration of plantations in the municipality and National Forest Authority
Natural
Drought
Floods
Wind fall
Low
Medium
Low
Medium
No planting in July, August and September
Adequate site selection, site-specie match according to strict protocols
Adequate site selection according strict protocols and introduction of wind breaks if
necessary
Project and forest committees implement measures to reduce this risk.
High
Fencing, the project provides barbed wire
Low
The AACS will monitor the level of knowledge and strengthen capacities among
famers and the contracted (community based) companies
Medium
Involvement of community authorities, legal aspects, involvement of forestry
committees can minimize these situations. The partial payments and the possibility of
obtaining loans, using the plantations as a guarantee will minimize the loss of interest
as well and will motivate to manage the plantations well.
Medium
Forestry committees control illegal logging, consciousness program, legal
announcements, which makes it impossible to sell the wood, project will provide
higher prices than on the local market, and Payments for environmental services
generate income and are therefore an incentive to leave the trees growing.
Lack of cash flow might affect the quality and growth of trees, but since tree-growing
is a shared activity between farmer and project it is expected that this will not result
in the complete failure of the plantations.
On the other hand the financing strategy is based on avoiding cash-flow shortage.
The level of payments to farmers for carbon credits is not market driven, but based
on maintenance costs agreed on beforehand. Payments are related solely to
compliance with the activities agreed and guaranteed by the project.
Forest fires
Social
Encroachment of
cattle
Lack of sufficient
knowledge on natural
resource management
Changes in
ownership, not
interested in trees, or
farmers losing interest
over the long term
Economic
Wood will be used and
cut before maturity,
sold elsewhere
Lack of cash flow
Low
within the project,
during project life time
Market driven
payments for
environmental
services might not
cover farmers´ costs
43
High
7. Monitoring
In this chapter, details on planting and tree survival monitoring, carbon stock monitoring and the design of a
permanent plot sampling design are presented. The Asociación Accidental Cetefor Sicirec will be responsible
for supervising these monitoring activities.
Monitoring of other performance indicators and social and environmental impact monitoring can be found
in section D-6 and annex.
Payments to farmers are not linked to the growth of the trees stated in this section but to activities carried
out to the required standard.
A full description of monitoring procedures for plantation establishment and development, including field
forms and the storing of data in a data base, is described in the monitoring section and annex 5 of the PDD.
7.1
Planting progress and tree survival monitoring
Two to three weeks after planting, quality and stock will be checked to determine whether replanting of
dead trees is necessary. Where survival is less than 90%, replanting will be carried out.
For monitoring purposes, mapping of the planted areas will be conducted by GPS to determine the planting
area. This data will be stored in a database. Periodic site visits will be carried out. In the first years all site
visits will be carried out at least every 3 months and will include an evaluation of survival rates, growth and
development of the plants, quality of the plantation, weed control, pests and diseases. Results of the
evaluations will be stored in a database. The frequency of evaluation visits will be reduced gradually to a
minimum of one yearly evaluation after 5 years post establishment.
7.2
Tree growth and plantation development
GENERAL OBJECTIVE
• Determine growth, yield and development of different species
SPECIFIC OBJECTIVES
• Define the growth, yield and development of the forestry plantations
• Define the increase of biomass within the forestry plantations
• Evaluate the quality of the site for each species
• Establish site indices and growth models
• Define the behavior of different species considering interactions with site and management.
7.2.1 Variables to measure
The following data will be gathered, for the data gathering different forms are used (annex 1)
The forms take into account some important aspects such as location co-ordinates, height and other
important data that we believe have an influence on the development of different species such as:
44
Site description (Form 1)
•
•
•
•
•
•
•
•
•
•
•
Location
Ownership status
Landscape
Gradient
Flood risk
Frost frequency
Fire risk
Erosion risk
wind risk
preponderance of stones
drainage
Description of the plantation (Form 1)
• Use and implementation of fertilizers (if used)
• Type of experimental design
• Planting method
• Topography
• Site preparation before planting
• Types of pre-existing crops (before tree planting)
• Sketch of the plantation
Soil characteristics (Form 2)
• Texture
• Colour
• pH values
• Compaction
• Indicator of drainage
• Prevalence of stones
• Quality of organic matter
• Soil depth
• Gradient
These measurements will initially be carried out bi-annually. After 4 years the measurements will be taken
every 5 years. However, this frequency can be adapted according to the growth and development of
different species. The main variables measured are (Form 3):
• DBH (cm)
• total height (m)
•
Mortality
• Competition
• Light/shade
• Health
After the first thinning other variables to be included are: area of coverage, position and shape of the
crown, form and stem quality and commercial height. (Form 4):
45
7.3
Installation of permanent sample plots
In order to gather reliable data on tree growth and development, permanent sample plots will be
established. The installation of permanent sample plots will be based on the strategy for forest sampling
developed by the school of forest science of the university San Simon in Cochabamba and the CETEFOR
foundation (Stilma, 2004).
7.3.1 Stratification
Each Tree species will respond differently for different types of site and therefore sample plots are
established for different strata. Stratification for sampling is based on the stratification, as described in
paragraph 2.2 for estimating the baseline net GHG removals by sinks, is performed according to ARAMS0001 version 05 (7).
This means a first stratification is made for the following land use types:
• Grassland
• Grassland with existing trees
• Perennial crops
• Annual crops/fallow land (slash and burn agriculture)
Furthermore area is stratified for tree species and plantation design (spacing).
Since the choice of species is based on site characteristics, no further stratification based on soil or
vegetation characteristics is necessary. However, if significant underperformance is detected, changes in
carbon stocks from such areas will be assessed as a separate stratum.
7.3.2 Size and shape of the plots.In order to select the size of the plots the following criteria are taken into account:
• Density of the plantation.- Various studies on the size of experimental plots have been conducted and
concluded that trials plots of 10-15 trees give sufficient precision with regard to relative growth, height
and diameter. Based on this information a plot size of 15 trees is used, which takes into account the
final projection of the plantation. In mixed plantations the number of trees is increased in proportion to
the number of different species present in the plantation (Wright 1964 in Stilma, 2007).
• Numbers of clearings which are realized in an entire rotation period.- It is considered that between 2
and 5 thinnings will be carried out before the final harvest, depending on the rotation period of the
tree species. Assuming 10-15 trees remain at the final harvesting stage; this means plots should contain
40 - 90 trees in the initial stage. Based on a tree density of 3x3 this means plots of 0.04 has for fast
growing tree species and plots of 0.08 has for slow growing tree species.
The plots are rectangular or square in shape. This makes it easier with a simple mark to measure every year
the same trees. It is important to know the exact surface of the sample plot; the 4 vertices have to be
measured, respecting the spacing of the trees. In case of slopes corrections for surface have to be made.
46
7.3.3 Demarcation and marking of plots
Account has been taken of the possibility that future measurements within the plots may be conducted by
different technicians than those who conducted the initial surveys, In order to ensure that no mistakes are
made, plastic tubes (1/2 or 1m) are used and are painted at the top to facilitate identification and to ensure
future measurements with no errors.
7.3.4 Measurement of the trees
Trees are measured on the following way: there will be started in the North East point (NE) of the simple
plot, carried out the measurement north - south – north. Trees are numbered according the sequence as
shown in figure 8.1.
Figure 8.1: measurement of trees in the permanent sample plot
NO
SO
NE
8
1
7
2
6
3
5
4
SE
Trees
1, 2,.. Sequential numbering
It is not necessary to put numbers on the trees but it is necessary to mark the place where the dbh is
measured. Measurement of trees always has to follow the same sequence to avoid future errors.
Trees which are not planted, have been cut or have died, all are considered as dead trees, these trees will
be assigned a code on the data sheets.
47
7.3.5 Number of plots.In compliance with the methodology AR-AMS0001/ vs5 (38-iii) the acceptable level of precision for
estimates of biomass stocks is set at +-10% of the mean at a 95% confidence level. To evaluate variance and
determine the number of sample plots necessary, data of 6 plots per stratum will be used to calculate the
number of plots per stratum using the formula below.
Source: Pearson 2005
Since 13 different tree species are to be used there will initially be 6 plots per stratum, and each species
might be planted in 2 strata, this means number of plots for the full project will be about 156( i.e. 13 X 2 X
6).
7.4
Carbon stock monitoring
Carbon stocks will be estimated for each stratum and multiplied by the surface of each stratum. The
following equations will be used:
I
P(t) = ∑ (PA(t) i + PB(t) i) * Ai
i
where:
P(t) = carbon stocks within the project boundary at time t achieved by the project activity (t C)
PA(t) i = carbon stocks in above-ground biomass at time t of stratum i achieved by the project activity during
the monitoring interval (t C/ha)
PB(t) i = carbon stocks in below-ground biomass at time t of stratum i achieved by the project activity
during the monitoring interval (t C/ha)
Ai = project activity area of stratum i (ha)
i = stratum i
For above-ground biomass
PA(t) is calculated per stratum i as follows:
PA(t) = E(t)* 0.5
where:
PA(t) = carbon stocks in above-ground biomass at time t achieved by the project activity during the
monitoring interval (t C/ha)
E(t) = estimate of above-ground biomass at time t achieved by the project activity (t dm/ha)
0.5 = carbon fraction of dry matter (t C/t dm)
E(t) will be estimated through the following steps:
48
Step 1: The diameter at breast height (DBH) or DBH and tree height will be measured
Step 2: Estimate the above-ground biomass (AGB) using algometric equations, as follows:
Biomass expansions factors and stem volume as follows:
E(t) = SV * BEF * WD
where:
E (t) = estimate of above-ground biomass at time t achieved by the project activity (t dm/ha)
SV = stem volume (m3/ha)
WD = basic wood density (t dm/m3)
BEF = biomass expansion factor (over bark) from stem volume to total volume (dimensionless)
Default BEF of 1.5 proposed by the IPCC good practice guidance (table 3A1.10) for LULUCF is used in order
to obtain a conservative estimate of total biomass.
SV will be estimated from on-site measurements using DBH and height. Consistent application of BEF will be
secured over total stem volume.
For below-ground biomass
PB(t) will be estimated for each stratum i as follows:
PB(t) = E(t) * R * 0. 5
where:
PB(t) = carbon stocks in below-ground biomass at time t achieved by the project activity during the
R = root to shoot ratio (dimensionless)
0.5 = carbon fraction of dry matter (t C/t dm)
Root to shoot ratios for the species concerned are not available. Therefore the conservative default value of
0.42 (secondary tropical and sub tropical forest) of the IPCC good practice guidance for LULUCF, Table
3A.1.8 are used.
49
7.5
Summary of data to be collected for Carbon Stock Monitoring and Recording Frequency
Data to be collected or used in order to monitor the verifiable changes in carbon stock in the carbon pools within the project boundary resulting from the project,
and how this data will be archived:
Data variable
Source of data
Data unit
Measured (m), Recording
Proportion of How will
Comment
calculated (c)
frequency
data to be
the data be
or estimated
monitored
archived?
(e)
(electronic
/ paper)
Location of the area
where the project
activity will be
implemented
GIS system based on
field surveys and
satellite imagery
UTM
WGS84
coordinate,
X,Y,Z
(m)
5 years
100%
Electronic,
paper,
GPS is used
Ai – size of the areas
where the project
activity has been
implemented for
each type of strata
GIS system based on
field surveys and
satellite imagery
Ha
(m)
5 years
100%
Electronic
GPS is used
Location of the
permanent sampling
plots
Project maps and
project design
UTM
WGS84
coordinate,
X,Y,Z
Defined
5 years
100%
Electronic, GPS is used to define exact
paper (field location, this is registered in a
form)
Data Base and on a map
Diameter of tree at
breast height (1.3 m)
Permanent plot
Cm
(m)
5 years
Each tree in
the sample
plot
Electronic
(field
forms)
Height of tree
Permanent plot
M
(m)
5 years
Each tree in
the sample
plot
Electronic, Measure height (H) for each
paper (field tree that falls within the
forms)
sample plot and applies to size
limit
Total CO2
Project activity
Metric
tonnes
(c)
5 years
All project
data
Electronic
50
Measure diameter at breast
height (DBH) for each tree that
falls within the sample plot
and applies the size limit
Based on data collected from
all plots and carbon pools
7.6
Data for monitoring of leakage
In compliance with the relevant methodology AR-AMS0001/version 05, monitoring is only needed in cases
where leakage is considered significant. In this case leakage is not considered significant and it is therefore
not necessary to be monitored. However, as mentioned in paragraph 6.1, potential leakage will
nevertheless be monitored over time, by monitoring land use change. This monitoring may also
demonstrate a positive effect or collateral carbon benefits. Land Use Change is monitored comparing the
land use changes, with the actual situation, every 5 years period.
7.7
Procedures and Responsibilities
7.7.1 Data gathering and processing
Data gathering and processing of data from the permanent sample plots is done by thesis students of the
universities for forest science in Cochabamba and Santa Cruz. The data gathering, processing and analysis
is supervised by the internal monitoring unit of ArBolivia and the supervisors assigned by the university.
Data is stored in the data base. An application in the data base makes it possible to extrapolate the data of
the permanent sample plots to the total volume of wood and biomass produced per species for each
specific stratum and geographic area.
7.7.2 Quality control
Quality control is conducted by the Internal Monitoring Unit as described in section G.1 of the PDD. Once
this process is completed the whole process of data gathering, processing and analysis can be verified by an
external entity.
51
8. Buffer level
Although growth projections are rather conservative the percentage of carbon credits sold upfront is 70%.
After validation a maximum of 90% of the existing carbon will be sold, leaving 10% as a risk buffer for the
project as insurance against unexpected losses or under-achievement later on in the project.
52
Literature
•
•
•
•
•
•
•
•
•
•
•
•
•
53
Brown, S. 1997. Estimating biomass and biomass change of tropical forests: a primer. FAO Forestry
Paper 134, Rome, Italy
CETEFOR, 2007, Protocol; forestry plantation design, Fundación CETEFOR, Cochabamba.
FAO-PAFBOL (GCP/BOL/028/NET), 2002, SERIIE TÉCNIICA XIIII, INFORMACIÓN TÉCNICA PARA EL
PROCESAMIENTO INDUSTRIAL DE 134 ESPECIES MADERABLES DE BOLIVIA. FAO. La Paz
INIA: http://www.inia.gob.pe/boletin/boletin0020/PUMAQUIRO.htm
ISRIC, 1995, Homogenized Soil Data File Global Environmental, International Soil Reference Centre
(ISRIC), Wageningen.
Knoblauch B., Berger D., 2007. Cattle production in grazing systems colonization areas in the area of
influence of the Biosphere reserve and communitarian grounds Pilon. DED. Rurrenabaque
Monteith,S. and A.Quiroga (1993). Mapeo de Suelos del Chapare con Sistema FCC , DevelopmentAlternatives-inc. Cochabamba
Navarro, 2002, Geografía Ecológica de Bolivia. Vegetación y Ambientes Acuáticos. Centro de Ecología
Simón I. Patiño-Departamento de Difusión. Cochabamba.
Sejas Bernal Rober, Rodriguez E., Stilma A.A. 2008. Mechanized agrcicultural production in the Ichilo
Province. Fundación Cetefor. Cochabamba.
Sejas Bernal Rober, Espinosa José, 2007, Cattle production in the pre-Amazon and sub-Andean
ecological region, Fundación Cetefor. Cochabamba.
Pearson T, Walker S., Brown S. 2005. Sourcebook for Land Use, Land-Use Change and Forestry
Projects, Winrock International. Washington
Stilma A, Davalos I, Salamanca P., Sanzetenea E., Sejas R. 2004, Estrategia Departamental para
Parcelas Permanentes de Muestreo, PROYECTO PD.17/99 Rev. 3 (F) - INFOBOL La Escuela de Ciencias
Forestales de la UMSS, Fundación CETEFOR, Cochabamba
Zomer Robert, Straaten Oliver van, Stilma Anko. 2006. WP1: Pre-Feasibility Report, Chapare Case
Study, Bio-physical Characterization, Land Suitability and Project Scenario Analysis. ENCOFOR, IWMI,
Colombo
Annex 1
Simplified baseline and monitoring methodologies for small-scale
afforestation and reforestation
project activities under the clean development mechanism
implemented on grasslands or croplands
AR-AMS0001 vs5
UNFCCC/CCNUCC
AR-AMS0001 / Version 05
Sectoral scope 14
EB 42
CDM – Executive Board
Simplified baseline and monitoring methodologies for small-scale afforestation and reforestation
project activities under the clean development mechanism implemented on grasslands or croplands
AR-AMS0001
I. Applicability conditions, carbon pools and project emissions
1.
The simplified baseline and monitoring methodologies are applicable if the conditions (a) - (d)
mentioned below are met.
(a)
Project activities are implemented on grasslands or croplands;
(b)
Project activities are implemented on lands where the area of the cropland within the
project boundary displaced due to the project activity is less than 50 per cent of the total
project area;
(c)
Project activities are implemented on lands where the number of displaced grazing
animals is less than 50 per cent of the average grazing capacity1 of the project area;
(d)
Project activities are implemented on lands where ≤ 10% of the total surface project area
is disturbed as result of soil preparation for planting.
2.
Carbon pools to be considered by these methodologies are above- and below-ground tree and
woody perennials2 biomass and below-ground biomass of grasslands (i.e. living biomass).
3.
Project emissions are considered insignificant and therefore neglected.
4.
Before using simplified methodologies, project participants shall demonstrate whether:
1
2
(a)
The project area is eligible for the A/R CDM project activity, using procedures for the
demonstration of land eligibility contained in Appendix A;
(b)
The project activity is additional, using the procedures for the assessment of additionality
contained in Appendix B.
See Appendix D.
Woody perennials refers to other than tree vegetation (for example coffee, tea, rubber or oil palm) and shrubs that
are present in croplands and grasslands below the thresholds (of canopy cover, and potential tree height) used to
define forests.
1/29
UNFCCC/CCNUCC
Sectoral scope 14
EB 42
II. Baseline net greenhouse gas removals by sinks
5.
The most likely baseline scenario of the small-scale A/R CDM project activity is considered to be
the land-use prior to the implementation of the project activity, either grasslands or croplands.
6.
The project participants shall provide documentation from literature and/or expert judgment, to
justify which of the following cases occurs:
7.
8.
(a)
If changes in the carbon stocks in the living biomass of woody perennials and the belowground biomass of grasslands are expected not to exceed 10% of ex-ante actual net GHG
removals by sinks, then the changes in carbon stocks shall be assumed to be zero in the
absence of the project activity;
(b)
If the carbon stock in the living biomass pool of woody perennials and in below-ground
biomass of grasslands is expected to decrease in the absence of the project activity, the
baseline net GHG removals by sinks shall be assumed to be zero. In the above case, the
baseline carbon stocks in the carbons pools are constant and equal to existing carbon
stocks measured at the start of the project activity;
(c)
Otherwise, baseline net GHG removals by sinks shall be equal to the changes in carbon
stocks in the living biomass pool of woody perennials and in below-ground biomass of
grasslands that are expected to occur in the absence of the project activity.
The project area should be stratified for purpose of the baseline calculation into:
(a)
Area of cropland with changes in the carbon stocks in the living biomass pool of woody
perennials and in below-ground biomass of grasslands expected not to exceed 10% of
ex ante actual net GHG removals by sinks multiplied by share of the area in the entire
project area;
(b)
Area of grassland with changes in the carbon stocks in the living biomass pool of woody
perennials and in below-ground biomass of grasslands expected not to exceed 10% of
ex ante actual net GHG removals by sinks multiplied by share of the area in the entire
project area;
(c)
Area of cropland with changes in the carbon stocks in the living biomass pool of woody
perennials and in below-ground biomass of grasslands expected to exceed 10% of ex ante
actual net GHG removals by sinks multiplied by share of the area in the entire project
area;
(d)
Area of grassland with changes in the carbon stocks in the living biomass pool of woody
perennials and in below-ground biomass of grasslands expected to exceed 10% of ex ante
actual net GHG removals by sinks multiplied by share of the area in the entire project
area.
Baseline carbon stocks will be determined by the equation:
I
B(t ) = ∑ ( BA(t )i + BB (t )i ) * Ai
(1)
i =1
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where:
B(t)
Carbon stocks in the living biomass within the project boundary at time t in the
absence of the project activity (t C)
BA(t) i
Carbon stocks in above-ground biomass at time t of stratum i in the absence of
BB(t) i
Carbon stocks in below-ground biomass at time t of stratum i in the absence of
Ai
Project area of stratum i (ha)
i
Stratum i (I = total number of strata)
Above-ground biomass
9.
For above-ground biomass BA(t) is calculated per stratum i as follows:
BA(t) =M(t) * 0.5
(2)
where:
BA(t)
Carbon stocks in above-ground biomass at time t in the absence of the project
activity (t C/ha)
M(t)
Above-ground biomass at time t that would have occurred in the absence of the
project activity (t d.m./ha)3
0.5
Carbon fraction of dry matter (t C/t d.m.)
M(t) shall be estimated using average biomass stock and growth rates specific to the region. In the
absence of such values, national default values should be used. If national values are also not available,
the values should be obtained from table 3.3.2 of the IPCC good practice guidance for LULUCF.
10.
If living biomass carbon pools are expected to increase according to paragraph 6.c, the average
biomass stock is estimated as the above-ground biomass stock in age-dependent above-ground biomass
stock in woody perennials:
M(t=0) = Mwoody (t=0)
(3)
if: Mwoody (t=n-1) + g * ∆t < Mwoody_max then
M(t=n) = Mwoody ( t=n-1) + g * ∆t
(4)
if: Mwoody (t=n-1) + g * ∆t ≥ Mwoody_max then
M(t=n) = Mwoody_max
3
(5)
d.m. = dry matter
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where:
M(t)
Above-ground biomass at time t that would have occurred in the absence of the
project activity (t d.m./ha)
Mwoody (t)
Above-ground biomass of woody perennials at time t that would have occurred in the
absence of the project activity (t d.m./ha)
Mwoody_max
Maximal above-ground biomass of woody perennials that would have occurred in the
g
Annual increment in biomass of woody perennials (t d.m./ha/year)
∆t
ment = 1 (year)
Running variable that increases by ∆t = 1 for each iterative step, representing the
number of years elapsed since the project start (years)
n
11.
Documented local values for g and Mwoody_max should be used. In the absence of such values,
national default values should be used. If national values are also not available, the values should be
obtained from the IPCC good practice guidance for LULUCF: from table 3.3.2 for g and for Mwoody_max.
Below-ground biomass
12.
For below-ground biomass BB(t) is calculated per stratum i as follows:
If living biomass carbon pools are expected to be constant according to paragraph 6.a and 6.c, the average
below-ground carbon stock is estimated as the below-ground carbon stock in grass and in biomass of
woody perennials:
where:
BB(t)
Mgrass
Mwoody (t=0)
(6)
Carbon stocks in below-ground biomass at time t that would have occurred in the
absence of the project activity (t C/ha)
Above-ground biomass in grass on grassland at time t that would have occurred in the
Above-ground biomass of woody perennials at t=0 that would have occurred in the
Rwoody
Root to shoot ratio of woody perennials (t d.m./t d.m.)
Rgrass
Root to shoot ratio for grassland (t d.m./t d.m.)
If living biomass carbon pools are expected to increase according to paragraph 6.c, the average belowground carbon stock is estimated as follows:
BB(t=0) = 0.5 * (Mgrass * Rgrass + Mwoody (t=0) * Rwoody)
(7)
if: Mwoody (t=n-1) + g * ∆t < Mwoody_max then
BB (t=n) = 0.5 * [Mgrass * Rgrass + (Mwoody (t=n-1) + g * ∆t) * Rwoody ]
if: Mwoody (t=n-1) + g * ∆t ≥ Mwoody_max then
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BB (t=n) = 0.5 * (Mgrass * Rgrass + Mwoody_max * Rwoody)
(9)
where:
BB(t)
Carbon stocks in below-ground biomass at time t that would have occurred
in the absence of the project activity (t C/ha)
Mgrass
Above-ground biomass in grass on grassland at time t that would have
occurred in the absence of the project activity (t d.m./ha)
Mwoody (t)
Above-ground biomass of woody perennials at time t that would have
occurred in the absence of the project activity (t d.m./ha)
Rwoody
Root to shoot ratio for woody perennial (t d.m./t d.m.)
Rgrass
Root to shoot ratio for grassland (t d.m./t d.m.)
g
Annual increment in biomass of woody perennials (t d.m./ha/year)
∆t
Time increment = 1 (year)
n
Running variable that increases by ∆t = 1 year for each iterative step,
representing the number of years elapsed since the project start (years)
0.5
13.
Documented local values for Rgrass and Rwoody should be used. In the absence of such values,
national default values should be used. If national values are also not available, the values should be
obtained from table 3 A.1.8 of the IPCC good practice guidance for LULUCF.
14.
The baseline net GHG removals by sinks can be calculated by:
∆ CBSL,t = (B(t) - B(t-1))*(44/12)
(10)
where:
∆ CBSL,t
Baseline net GHG removals by sinks (t CO2-e)
B(t)
Carbon stocks in the living biomass pools within the project boundary at
time t in the absence of the project activity (t C)
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III. Actual net greenhouse gas removals by sinks (ex ante)
15.
Stratification of the project area should be carried out to improve the accuracy and precision of
biomass estimates.
16.
For the ex ante calculation of the project biomass, the project area should be stratified according
to the project planting plan that is, at least by tree species (or groups of them if several tree species have
similar growth habits), and age classes.
17.
The carbon stocks for the project scenario at the starting date of the project activity4 (t=0) shall be
the same as the baseline stocks of carbon at the starting date of the project (t=0). Therefore:
N(t=0) = B(t=0)
(11)
For all other years, the carbon stocks within the project boundary (N(t)) at time t shall be calculated as
follows:
I
N(t) = ∑(NA(t) i + NB(t) i) * Ai
(12)
i=1
where:
N(t)
Total carbon stocks in biomass at time t under the project scenario (t C)
NA(t) i
Carbon stocks in above-ground biomass at time t of stratum i under the project scenario
(t C/ha)
NB(t) i
Carbon stocks in below-ground biomass at time t of stratum i under the project scenario
(t C/ha)
Ai
Project activity area of stratum i (ha)
i
18.
For above-ground biomass NA(t) i is calculated per stratum i as follows:
NA(t) i =T(t)i * 0. 5
(13)
where:
NA(t) i
Carbon stocks in above-ground biomass at time t under the project scenario (t C/ha)
T(t)i
Above-ground biomass at time t under the project scenario (t d.m./ha)
0.5
4
The starting date of the project activity should be the time when the land is prepared for the initiation of the
afforestation or reforestation project activity under the CDM. In accordance with paragraph 23 of the modalities
and procedures for afforestation and reforestation project activities under the CDM, the crediting period shall
begin at the start of the afforestation and reforestation project activity under the CDM (see UNFCCC website at
<http://unfccc.int/resource/docs/cop9/06a02.pdf#page=21>).
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19.
If biomass tables or equations are available then these shall be used to estimate T(t)i per stratum i.
If volume table or equations are used then
T(t)i=SV(t)i * BEF * WD
(14)
where:
T(t)i
SV(t)i
Stem volume at time t for the project scenario (m3 /ha)
BEF
Biomass expansion factor (over bark) from stem to total above-ground biomass
(dimensionless)
WD
Basic wood density (t d.m./m3)
20.
Values for SV(t)i shall be obtained from national sources (such as standard yield tables).
Documented local values for BEF should be used. In the absence of such values, national default values
should be used. If national values are also not available, the values should be obtained from
table 3A.1.10 of the IPCC good practice guidance for LULUCF. If national default values for wood
density are not available, the values should be obtained from Table 3A.1.9 of the IPCC good practice
guidance for LULUCF.
21.
For below-ground biomass, NB(t) is calculated per stratum i as follows:
NB(t) i=T(t) * R * 0.5
(15)
where:
NB(t) i
Carbon stocks in below-ground biomass at time t under the project scenario (t C/ha)
T(t)
R
Root to shoot ratio (t d.m./ t d.m. )
0.5
22.
Documented national values for R should be used. If national values are not available,
appropriate values should be obtained from Table 3A.1.8 of the IPCC good practice guidance for
LULUCF.
23.
If root to shoot ratios for the species concerned are not available, project proponents shall use the
allometric equation developed by Cairns et al. (1997)
NB(t) = exp(–1.085 + 0.9256 * ln T(t)) * 0.5
(16)
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where:
NB(t)
Carbon stocks in below-ground biomass at time t achieved by the project activity during
T(t)
Estimate of above-ground biomass at time t achieved by the project activity
(t d.m./ha)
0.5
or a more general equation taken from the IPCC good practice guidance for LULUCF, Table 4.A.4 5.
24.
The removal component of actual net GHG removals by sinks can be calculated by:
∆ CPROJ,t = (Nt - Nt-1)*(44/12)/∆t
(17)
where:
∆ CPROJ,t
Removal component of actual net GHG removals by sinks per annum (t CO2-e/year)
N(t)
Total carbon stocks in biomass at time t under the project scenario (t C)
∆t
25.
Project emissions are considered insignificant and therefore:
GHG PROJ ,t = 0
where:
GHGPROJ, t
26.
Project emissions (t CO2-e/year)
The ex ante actual net greenhouse gas removals by sinks in year t are equal to:
∆ CACTUAL,t = ∆C PROJ ,t − GHG PROJ ,t
(18)
where:
∆ CACTUAL,t
Ex ante actual net greenhouse gas removals by sinks in year t (t CO2-e/year)
∆ CPROJ,t
Project GHG removals by sinks (t CO2-e/year)
GHGPROJ, t
5
Cairns, M.A., S. Brown, E.H. Helmer, G.A. Baumgardner (1997). Root biomass allocation in the world’s upland
forests. Oecologia (1):1–11.
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IV. Leakage (ex ante)
27.
According to decision 6/CMP.1, annex, Appendix B, paragraph 9: “If project participants
demonstrate that the small-scale afforestation or reforestation project activity under the CDM does not
result in the displacement of activities or people, or does not trigger activities outside the project
boundary, that would be attributable to the small-scale afforestation or reforestation project activity under
the CDM, such that an increase in greenhouse gas emissions by sources occurs, a leakage estimation is
not required. In all other cases leakage estimation is required.”
28.
If evidence can be provided that there is no displacement, or the displacement of pre-project
activities will not cause deforestation attributable to the project activity, or the lands surrounding the
project activity contain no significant biomass (i.e. degraded land with no or only a few trees or shrubs
per hectare) and if evidence can be provided that these lands are likely to receive the shifted activities,
leakage can be considered zero. Such evidence can be provided by scientific literature or by experts’
judgment.
29.
In all other cases, project participants should assess the possibility of leakage from the
displacement of activities by considering the following indicators:
(a)
Area under cropland6 within the project boundary displaced due to the project activity;
(b)
Number of domesticated grazing animals within the project boundary displaced due to
the project activity;
(c)
For domesticated roaming animals, the time-average number of grazing animals per
hectare within the project boundary displaced due to the project activity.
30.
If the area of the cropland within the project boundary displaced due to the project activity is
lower than 10 per cent of the total project area, and the number of domesticated grazing animals displaced
is less than 10% of the average grazing capacity (see appendix D for calculations) of the project area, and
the time-average number of domesticated roaming animals displaced is less than 10% of the average
grazing capacity per hectare (see appendix D for calculations) of the project area, then:
Lt=0
(19)
where:
Lt
Leakage attributable to the project activity at time t (t CO2-e/year)
31.
If the value of one of these indicators is higher than 10 per cent and less than or equal to
50 per cent, then the entire leakage shall be equal to 15 per cent of the ex-ante actual net GHG removals
by sinks achieved during the first crediting period, that is the average annual leakage is equal to:
Lt=∆ CACTUAL,t * 0.15
6
(20)
Cropland also includes lands which are currently under a fallow state as part of the agricultural cycle (eg. slash and
burn).
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where:
Lt
Average annual leakage attributable to the project activity at time t (t CO2-e/year)
∆ CACTUAL,t
Ex ante actual net greenhouse gas removals by sinks in year t (t CO2-e / year)
32.
If the value of any of these indicators calculated in paragraph 28 is higher than 50 per cent, then
this simplified methodology cannot be used.
V. Net anthropogenic greenhouse gas removals by sinks
33.
The net anthropogenic GHG removals by sinks for each year during the first crediting period are
calculated as,
ERAR CDM, t = ∆CPROJ, t – ∆CBSL, t - GHGPROJ, t – Lt
(21)
where:
ERAR CDM, t
Net anthropogenic GHG removals by sinks (t CO2-e/year)
∆CPROJ, t
Project GHG removals by sinks at time t (t CO2-e/year)
∆ CBSL,t
Baseline net GHG removals by sinks (t CO2-e/year)
GHGPROJ, t
Lt
Leakage attributable to the project activity at time t (t CO2-e / year)
For subsequent crediting periods Lt=0.
34.
The resulting temporary certified emission reductions (tCERs) at the year of assumed verification
tv are calculated as follows:
tv
tCER( tv ) = ∑ ERAR − CDM ,t * ∆t
(22)
t =0
where:
tCER(t)
Temporary certified emission reductions (tCERs) at the year of assumed verification tv
ERAR CDM, t
Net anthropogenic GHG removals by sinks (t CO2-e/year)
tv
Assumed year of verification (year)
∆t
35.
The resulting long-term certified emission reductions (lCERs) at the year of assumed verification
tv are calculated as follows:
tv
lCER( tv ) = ∑ ERAR CDM,t * ∆t − lCER(t − k )
(23)
t =0
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where:
lCER(tv)
Long-term certified emission reductions (lCERs) at the year of verification tv
ERAR CDM, t
Net anthropogenic GHG removals by sinks; (t CO2-e/year)
k
Time span between two verifications (year)
tv
Year of assumed verification (year)
VI. Simplified monitoring methodology for small-scale afforestation and reforestation projects
under the clean development mechanism
A. Ex post estimation of the baseline net greenhouse gas removals by sinks
36.
In accordance with decision 6/CMP.1, Appendix B, paragraph 6, no monitoring of the baseline is
requested. Baseline net GHG removals by sinks for the monitoring methodology will be the same as
using the simplified baseline methodology in Section II above.
B. Ex post estimation of the actual net greenhouse gas removals by sinks
37.
Stratification of the project area should be carried out to improve the accuracy and precision of
biomass estimates.
38.
For ex post estimation of project GHG removals by sinks, strata shall be defined by:
(i) Relevant guidance on stratification for A/R project activities under the clean development
mechanism as approved by the Executive Board (if available); or
(ii) Stratification approach that can be shown in the PDD to estimate biomass stocks according to
good forest inventory practice in the Host country in accordance with DNA indications; or
(iii) other stratification approach that can be shown in the PDD to estimate the project biomass
stocks to targeted precision level of ±10% of the mean at a 95% confidence level.
39.
Carbon stocks (expressed in t CO2-e) shall be estimated through the following equations:
I
P(t) =∑(PA(t) i + PB(t) i) * Ai*(44/12)
(24)
i=1
where:
P(t)
Carbon stocks within the project boundary at time t achieved by the project activity
(t CO2-e)
PA(t) i
Carbon stocks in above-ground biomass at time t of stratum i achieved by the project activity
PB(t) i
Carbon stocks in below-ground biomass at time t of stratum i achieved by the project
activity during the monitoring interval (t C/ha)
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Ai
Project activity area of stratum i (ha)
i
40.
The calculations shown in paragraphs 41 - 47 shall be performed for each stratum.
41.
For above-ground biomass PA(t) i is calculated per stratum i as follows:
PA(t) i =E(t) i* 0. 5
(25)
where:
PA(t) i
Carbon stocks in above-ground biomass at time t achieved by the project activity during the
E(t) i
Estimate of above-ground biomass at time t achieved by the project activity (t d.m./ha)
0.5
42.
Estimate of above-ground biomass at time t achieved by the project activity E(t) shall be estimated
through the following steps:
(a)
Step 1: Establish permanent plots and document their location in the first monitoring
report;
(b)
Step 2: Measure the diameter at breast height (DBH) or DBH and tree height, as
appropriate this measure and document it in the monitoring reports;
(c)
Step 3: Estimate the above-ground biomass using allometric equations developed locally
or nationally. If these allometric equations are not available:
(i)
Option 1: Use allometric equations included in Appendix C to this report or in
annex 4A.2 of the IPCC good practice guidance for LULUCF;
(ii)
Option 2: Use biomass expansion factors and stem volume as follows:
E(t) i = SV(t) i * BEF * WD
(26)
where:
E (t) i
Estimate of above-ground biomass of stratum i at time t achieved by the project activity
(t d.m./ha)
SV(t) i
Stem volume (m3/ha)
WD
Basic wood density (t d.m./m3)
Biomass expansion factor (over bark) from stem to total above-ground biomass
(dimensionless)
BEF
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43.
Stem volume SV(t)i shall be estimated from on-site measurements. Consistent application of BEF
should be secured on the definition of stem volume (e.g. total stem volume or thick wood stem volume
requires different BEFs). National default values for wood density should be used. If national values are
also not available, the values should be obtained from table 3A.1.9 of the IPCC good practice guidance
for LULUCF.
44.
The same values for BEF and WD should be used in the ex post and in the ex ante calculations.
45.
Carbon stocks in below-ground biomass at time t achieved by the project activity during the
monitoring interval PB(t) shall be estimated for each stratum i as follows:
PB(t) i=E(t) i * R * 0. 5
(27)
where:
PB(t) i
Carbon stocks in below-ground biomass at time t achieved by the project activity
E (t) i
Estimate of above-ground biomass of stratum i at time t achieved by the project
activity (t d.m./ha)
R
Root to shoot ratio (dimensionless)
0.5
46.
Documented national values for R should be used. If national values are not available, the values
should be obtained from table 3A.1.8 of the IPCC good practice guidance for LULUCF.
If root to shoot ratios for the species concerned are not available, project proponents shall use the
allometric equation developed by Cairns et al. (1997)
PB(t) i =exp(–1.085 + 0.9256 * ln E(t) i) * 0.5
(28)
where:
PB(t) i
Carbon stocks in below-ground biomass at time t achieved by the project activity during
E(t) i
Estimate of above-ground biomass at time t achieved by the project activity (t d.m./ha)
0.5
or a more representative equation taken from the IPCC good practice guidance for LULUCF,
Table 4.A.4:
47.
Project emissions are considered insignificant and therefore:
GHG PROJ ,t = 0
where:
GHGPROJ, t
Project emissions (t CO2-e / year)
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C. Ex post estimation of leakage
48.
In order to estimate leakage, project participants shall monitor each of the following indicators
during the first crediting period:
49.
then
(a)
Area under cropland7 within the project boundary displaced due to the project activity;
(b)
Number of domesticated grazing animals within the project boundary displaced due to
the project activity;
(c)
For domesticated roaming animals, the time-average number of domesticated grazing
animals per hectare within the project boundary displaced due to the project activity.
If the values of these indicators for the specific monitoring period are not greater than 10 per cent,
Ltv=0
(29)
where:
Ltv
Total GHG emission due to leakage at the time of verification (t CO2-e)
If the value of any of these indicators is higher than 10 per cent and less than or equal to 50 per cent
during the first crediting period, then leakage shall be determined at the time of verification using the
following equations:
for the first verification period:
Ltv= 0.15 * ( P( tv ) − B( t =0 ) −
tv
∑ GHG
t =0
PROJ ,( t )
)
(30)
for subsequent verification periods:
Ltv= 0.15 * ( P( tv ) − P( tv −k ) −
tv
∑ GHG
tv − k
PROJ ,( t )
)
(31)
where:
P(t)
GHG emission due to leakage at the time of verification (t CO2-e)
Carbon stocks within the project boundary achieved by the project activity at time t
(t CO2-e)
GHGPROJ, (t)
B(t=0)
Carbon stocks in biomass at time 0 that would have occurred in the absence of the
project activity (t C/ha)
tv
Year of verification (year)
κ
Ltv
7
Cropland also includes lands which are currently under a fallow state as part of the agricultural cycle (eg. slash and
burn).
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As indicated in chapter IV, paragraph 31, if the value of one of these indicators is larger than 50 per cent
net anthropogenic GHG removals by sinks cannot be estimated using this methodology.
At the end of the first crediting period the total leakage equals to:
LCP1 = 0.15 * ( P( tc ) − B( t =0) −
tc
∑ GHG
t =0
PROJ ,( t )
)
(32)
where:
Total GHG emission due to leakage at the end of the first crediting period (t CO2-e)
LCP1
GHGPROJ, (t)
B(t=0)
Carbon stocks in biomass at time 0 that would have occurred in the absence of the
project activity (t C/ha)
tc
Duration of the crediting period
D. Ex-post estimation of the net anthropogenic GHG removals by sinks
50.
Net anthropogenic greenhouse gas removals by sinks is the actual net greenhouse gas removals
by sinks minus the baseline net greenhouse gas removals by sinks minus leakage as appropriate.
51.
The resulting tCERs at the year of verification tv are calculated as follows
for the first crediting period:
tCER(tv)= P( t ) −
tv
∑ (GHG
t =0
PROJ ,( t )
− ∆C BSL ,t ) – Ltv
(33)
for subsequent crediting periods:
tCER(tv)
=
tv
P( t ) − ∑ (GHGPROJ ,(t ) − ∆C BSL ,t ) – LCP1
(34)
t =0
where:
P(t)
(t CO2-e)
GHGPROJ, (t)
∆ CBSL,t
Ltv
LCP1
tv
Year of verification
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52.
The resulting lCERs at the year of verification tv are calculated as follows:
for the first crediting period:
lCER(tv)= P( t ) −
tv
∑ (GHG
t =0
PROJ ,( t )
− ∆C BSL ,t ) –Ltv – lCER(tv-k)
(35)
for subsequent crediting periods:
lCER(tv)= P( t ) −
tv
∑ (GHG
t =0
PROJ ,( t )
− ∆C BSL ,t ) –LCP1 – lCER(tv-k)
(36)
where:
P(t)
GHGPROJ, (t)
(t CO2-e)
∆ CBSL,t
Ltv
LCP1
lCER(tv-k)
Units of lCERs issued following the previous verification
tv
Year of verification (year)
κ
E. Monitoring frequency
53.
Monitoring frequency for each variable is defined in the Tables 1 and 2.
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Table 1. Data to be collected or used in order to monitor the verifiable changes in carbon stock in
the carbon pools within the project boundary from the proposed afforestation and reforestation
project activity under the clean development mechanism, and how these data will be archived
Measured,
calculated
or
Frequency
Source
Data unit estimated
(years)
Proportion Archiving Comment
Measured
5
100 per
Electronic, GPS can be used
latitude
Field survey
for field survey
cent
paper,
and
or cadastral
photos
information or longitude
aerial
photographs
or satellite
imagery
ha
Measured
5
100 per
Electronic, GPS can be used
Field survey
cent
paper,
for field survey
or cadastral
photos
information or
aerial
photographs
or satellite
imagery or
GPS
Data
variable
Location of
the areas
where the
project
activity has
been
implemented
Ai - Size of
the areas
where the
project
activity has
been
implemented
for each type
of strata
Location of
Project maps
the permanent and project
sample plots design
latitude
and
longitude
Defined
5
cm
Measured
5
Height of tree Permanent
plot
m
Measured
5
Basic wood
density
Literature
Total CO2
Project
activity
tonnes of Estimated
dry matter
per m3
fresh
volume
Mg
Calculated
Diameter of
tree at breast
height
(1.30 m)
Permanent
plot
Once
17/29
5
100 per
cent
Electronic, Plot location is
paper
registered with a
GPS and marked
on the map
Each tree in Electronic, Measure diameter
the sample paper
at breast height
plot
(DBH) for each
tree that falls
within the sample
plot and applies
to size limits
Each tree in Electronic, Measure height
the sample paper
(H) for each tree
plot
that falls within
the sample plot
and applies to
size limits
Electronic,
paper
All project
data
Electronic
Based on data
collected from all
plots and carbon
pools
UNFCCC/CCNUCC
Sectoral scope 14
EB 42
Table 2. Data to be collected or used in order to monitor leakage
and how these data will be archived
Measured,
calculated or
Data unit estimated
Hectares or Measured or
other area
estimated
units
Data variable
Area under cropland
within the project
boundary displaced
due to the project
activity
Source
Survey
Number of
domesticated grazing
animals within the
project boundary
displaced due to the
project activity
Survey
Number of
heads
Estimated
Time-average number Survey
of grazing
domesticated roaming
animals per hectare
within the project
boundary displaced
due to the project
activity
Number of
heads
Estimated
18/29
Frequency
(years)
One time
after
project is
established
but before
the first
verification
One time
after
project is
established
but before
the first
verification
One time
after
project is
established
but before
the first
verification
Proportion Archiving
30%
Electronic
30%
Electronic
30%
Electronic
Comment
UNFCCC/CCNUCC
Sectoral scope 14
EB 42
Table 3. Abbreviations and parameters (in order of appearance)
Parameter or
abbreviation
B(t)
Refers to
Units
carbon stocks in the living biomass within the project boundary at time t in the
absence of the project activity
tC
BA(t) i
carbon stocks in above-ground biomass at time t of stratum i in the absence of the
project activity
t C/ha
BB (t) i
carbon stocks in below-ground biomass at time t of stratum i in the absence of the
project activity
t C/ha
Ai
project area of stratum i
ha
i
stratum index
I
total number of strata
M(t)
above-ground biomass at time t that would have occurred in the absence of the
project activity
t d.m./ha
0.5
carbon fraction of dry matter
tC / t d.m.
Mwoody (t)
above-ground biomass of woody perennials at time t that would have occurred in
the absence of the project activity
t d.m./ha
Mwoody_max
maximal above-ground biomass of woody perennials that would have occurred in
t d.m./ha
g
annual increment in biomass of woody perennials
t d.m./ha/year
∆t
time increment = 1 (year)
year
n
running variable that increases by ∆t = 1 year for each iterative step, representing
the number of years elapsed since the project start
years
Rwoody
root to shoot ratio of woody perennials
t d.m./t d.m.
Mgrass
Above-ground biomass in grass on grassland at time t that would have occurred in
t d.m./ha
Rgrass
root to shoot ratio for grassland
t d.m./t d.m.
baseline net GHG removals by sinks at time t
t CO2-e
total carbon stocks within the project boundary at time t under project scenario
tC
NA(t) i
carbon stocks in above-ground biomass at time t of stratum i under project
scenario
t C/ha
NB(t) i
carbon stocks in below-ground biomass at time t of stratum i under project
scenario
t C/ha
∆ CBSL,t
N(t)
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Parameter or
abbreviation
T(t)i
Refers to
Units
above-ground biomass at time t for the project scenario
t d.m./ha
root to shoot ratio
t d.m./t d.m.
SV(t) i
stem volume at time t for the project scenario
m3 /ha
WD
basic wood density
t d.m./m3 (fresh
volume)
BEF
biomass expansion factor (over bark) from stem to total biomass
dimensionless
DBH
diameter at breast height (130 cm or 1.30 m)
cm or m
removal component of actual net GHG removals by sinks per annum
t CO2-e/ year
ex-ante actual net greenhouse gas removals by sinks over the first crediting period
t CO2-e/ year
duration of the crediting period
year
project emissions at time t
t CO2-e/ year
Lt
leakage attributable to the project activity at time t
t CO2-e/ year
Ltv
total GHG emission due to leakage at the time of verification
t CO2-e
total GHG emission due to leakage at the end of the first crediting period
t CO2-e
net anthropogenic GHG removals by sinks
t CO2-e / year
tCER(tv)
tCERs emitted at year of verification tv
t CO2-e
lCER(tv)
lCERs emitted at year of verification tv
t CO2-e
R
∆ CPROJ,t
∆ CACTUAL,t
tC
GHGPROJ, t
LCP1
ERAR CDM, t
tv
year of verification
k
time span between two verifications (years)
years
carbon stocks within the project boundary at time t achieved by the project
activity
t CO2-e
PA(t) i
carbon stocks in above-ground biomass at time t of stratum i achieved by the
project activity during the monitoring interval
t C/ha
PB(t) i
carbon stocks in below-ground biomass at time t of stratum i achieved by the
project activity during the monitoring interval
t C/ha
E(t) i
estimate of above-ground biomass at time t achieved by the project activity
t d.m./ha
B(t=0)
carbon stocks in biomass at time 0 that would have occurred in the absence of the
project activity
t C/ha
LCP1
total GHG emission due to leakage at the end of the first crediting period
t CO2-e
P(t)
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Appendix A
Demonstration of land eligibility
1.
Eligibility of the A/R CDM project activities under Article 12 of the Kyoto Protocol shall be
demonstrated based on definitions provided in paragraph 1 of the annex to the Decision 16/CMP.1 (“Land
use, land-use change and forestry”), as requested by Decision 5/CMP.1 (“Modalities and procedures for
afforestation and reforestation project activities under the clean development mechanism in the first
commitment period of the Kyoto Protocol”), until new procedures to demonstrate the eligibility of lands
for afforestation and reforestation project activities under the clean development mechanism are
recommended by the EB.
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Appendix B
Assessment of additionality
1.
Project participants shall provide an explanation to show that the project activity would not have
occurred anyway due to at least one of the following barriers:
2.
3.
4.
5.
6.
Investment barriers, other than economic/financial barriers, inter alia:
(a)
Debt funding not available for this type of project activity;
(b)
No access to international capital markets due to real or perceived risks associated with
domestic or foreign direct investment in the country where the project activity is to be
implemented;
(c)
Lack of access to credit.
Institutional barriers, inter alia:
(a)
Risk relating to changes in government policies or laws;
(b)
Lack of enforcement of legislation relating to forest or land-use.
Technological barriers, inter alia:
(a)
Lack of access to planting materials;
(b)
Lack of infrastructure for implementation of the technology.
Barriers relating to local tradition, inter alia:
(a)
Traditional knowledge or lack thereof, of laws and customs, market conditions, practices;
(b)
Traditional equipment and technology;
Barriers due to prevailing practice, inter alia:
(a)
7.
The project activity is the “first of its kind”. No project activity of this type is currently
operational in the host country or region.
Barriers due to local ecological conditions, inter alia:
(a)
Degraded soil (e.g. water/wind erosion, salination);
(b)
Catastrophic natural and/or human-induced events (e.g. land slides, fire);
(c)
Unfavourable meteorological conditions (e.g. early/late frost, drought);
(d)
Pervasive opportunistic species preventing regeneration of trees (e.g. grasses, weeds);
(e)
Unfavourable course of ecological succession;
(f)
Biotic pressure in terms of grazing, fodder collection, etc.
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8.
Barriers due to social conditions, inter alia:
(a)
Demographic pressure on the land (e.g. increased demand on land due to population
growth);
(b)
Social conflict among interest groups in the region where the project activity takes place;
(c)
Widespread illegal practices (e.g. illegal grazing, non-timber product extraction and tree
felling);
(d)
Lack of skilled and/or properly trained labour force;
(e)
Lack of organization of local communities.
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Appendix C
Default allometric equations for estimating above-ground biomass
Annual
DBH
rainfall
limits
Equation
Broad-leaved species, tropical dry regions
<900 mm
3–30 cm
AGB = 10^{-0.535 + log10(π *DBH2/4)}
900–1500 mm 5–40 cm
AGB = exp{-1.996 + 2.32 * ln(DBH)}
Broad-leaved species, tropical humid regions
< 1500 mm
5–40 cm
AGB = 34.4703 – 8.0671*DBH +
0.6589*(DBH2)
1500–4000 mm < 60 cm
AGB = exp{-2.134 + 2.530 * ln(DBH)}
1500–4000 mm 60–148 cm AGB = 42.69 – 12.800*(DBH) +
1.242*(DBH)2
1500–4000 mm 5–130 cm AGB = exp{-3.1141 + 0.9719*ln(DBH2*H)
1500–4000 mm 5–130 cm AGB = exp{-2.4090 +
0.9522*ln(DBH2*H*WD)}
Broad-leaved species, tropical wet regions
> 4000 mm
4–112 cm AGB = 21.297 – 6.953*(DBH) +
0.740*(DBH2)
> 4000 mm
4–112 cm AGB = exp{-3.3012 +
0.9439*ln(DBH2*H)}
Coniferous trees
n.d.
2–52 cm
AGB = exp{-1.170 + 2.119*ln(DBH)}
Palms
n.d.
> 7.5 cm
AGB = 10.0 + 6.4 * H
n.d.
> 7.5 cm
AGB = 4.5 + 7.7 * WDH
R2
0.94
Author
0.89
Martinez-Yrizar et al.
(1992)
Brown (1997)
0.67
Brown et al. (1989)
0.97
0.84
Brown (1997)
Brown et al. (1989)
0.97
0.99
Brown et al. (1989)
Brown et al. (1989)
0.92
Brown (1997)
0.90
Brown et al. (1989)
0.98
Brown (1997)
0.96
0.90
Brown (1997)
Brown (1997)
Note: AGB = above-ground biomass; DBH = diameter at breast height; H = height; WD = basic wood density
References:
Brown, S. 1997. Estimating biomass and biomass change of tropical forests. A primer. FAO Forestry Paper 134.
Food and Agriculture Organization of the United Nations, Rome, Italy.
Brown, S., A.J.R. Gillespie, and A.E. Lugo. 1989. Biomass estimation methods for tropical forests with applications
to forest inventory data. Forest Science 35: 881–902.
Martínez-Y., A.J., J. Sarukhan, A. Perez-J., E. Rincón, J.M. Maas, A. Solis-M, and L. Cervantes. 1992.
Above-ground phytomass of a tropical deciduous forest on the coast of Jalisco, Mexico. Journal of Tropical
Ecology 8: 87–96.
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Appendix D
Calculating average grazing capacity
A. Concept
1.
Sustainable grazing capacity is calculated by assuming that the grazing animals should not
consume more biomass than is annually produced by the site
B. Methodology
2.
The sustainable grazing capacity is calculated using the following equation:
GC =
ANPP ∗ 1000
365 ∗ DMI
(37)
where:
GC
Grazing capacity (head/ha)
ANPP
Above-ground net primary productivity in tonnes dry biomass (t d.m.)/ha/yr)
DMI
Daily dry matter intake per grazing animal (kg d.m./head/day)
3.
Annual net primary production ANPP can be calculated from local measurements or default
values from Table 3.4.2 of IPCC good practice guidance LULUCF can be used. This table is reproduced
below as Table 1.
4.
The daily biomass consumption can be calculate from local measurements or estimated based on
the calculated daily gross energy intake and the estimated dietary net energy concentration of diet:
DMI =
GE
NE ma
(38)
where:
DMI
Dry matter intake (kg d.m./head/day)
GE
Daily gross energy intake (MJ/head/day)
NEma
Dietary net energy concentration of diet (MJ/kg d.m.)
5.
Daily gross energy intake for cattle and sheep can be calculated using equations 10.3 through
10.16 in 2006 IPCC Guidelines for National Greenhouse Gas Inventories Volume 4: Agriculture, Forestry
and Other Land Use (AFOLU).8 Sample calculations for typical herds in various regions of the world are
provided in Table 2; input data stems from Table 10A.2 of the same 2006 IPCC Guidelines. Dietary net
energy concentrations as listed in Table 3 can be calculated using the formula listed in a footnote to
Table 10.8 of the same 2006 IPCC Guidelines.
8
Paustian, K., Ravindranath, N.H., and van Amstel, A., 2007. 2006 IPCC Guidelines for National Greenhouse Gas
Inventories Volume 4: Agriculture, Forestry and Other Land Use (AFOLU). Intergovernmental Panel on Climate
Change (IPCC)
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Table 1: Table 3.4.2 from GPG LULUCF
TABLE 3.4.2
DEFAULT ESTIMATES FOR STANDING BIOMASS GRASLAND (AS DRY MATTER) AND
ABOVEGROUND NET PRIMARY PRODUCTION, CLASSIFIED BY IPCC CLIMATE ZONES
IPCC Climate Zone
Peak above- ground live biomass
Tonnes d.m. ha-1
Above-ground net primary production
(ANPP)
Tonnes d.m. ha-1
Average
No. of studies
Error1
1.8
5
±75%
Boreal-Dry & Wet2
Average
1.7
No. of studies
3
Error#
±75%
Cold Temperate-Dry
1.7
10
±75%
2.2
18
±75%
Cold Temperate-Wet
2.4
6
±75%
5.6
17
±75%
Warm Temperate-Dry
1.6
8
±75%
2.4
21
±75%
Warm Temperate-Wet
2.7
5
±75%
5.8
13
±75%
Tropical-Dry
2.3
3
±75%
3.8
13
±75%
Tropical-Moist & Wet
6.2
4
±75%
8.2
10
±75%
Data for standing live biomass are compiled from multi-year avaerages reported at grassland sites registered in the ORNL
DAAC NPP database [http://www.daac.ornl.gov/NPP/html_docs/npp_site.html ]. Estimates for above-ground primary
production are from: Olson, R. J.J.M.O. Scurlock, S.D. Prince, D.L. Zheng, and K.R. Johnson (eds.). 2001. NPP MultiBiome: NPP and Driver Data for Ecosystem Model-Data Intercomparison. Sources available on-line at
[http://www.daac.ornl.gov/NPP/html_docs/EMDI_des.html ].
1
Represents a nominal estimate of error, equivalent to two times standard deviation, as a percentage of the mean.
2
Due to limited data, dry and moist zones for the boreal temperate regime and moist and wet zones for the tropical
temperature regime were combined.
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Table 2: Data for typical cattle herds for the calculation of daily gross energy requirement
Cattle - Africa
Mature Females
Mature Males
Young
Weighted Average
Weight (kg) Weight Gain (kg/day) Milk (kg/day) Work (hrs/day) Pregnant DE Coefficient for NE m equation
Mix (of grazing)
200
0.00
0.30
0
33% 55%
0.365
8%
275
0.00
0.00
0
0% 55%
0.370
33%
75
0.10
0.00
0
0% 60%
0.361
59%
152
0.06
0.02
0
3% 58%
0.364
100%
Cattle - Asia
Mature Females
Mature Males
Young
Weighted Average
Mix (of grazing)
300
0.00
1.10
0
50% 60%
0.354
18%
400
0.00
0.00
0
0% 60%
0.370
16%
200
0.20
0.00
0
0% 60%
0.345
65%
251
0.13
0.20
0
9% 60%
0.350
100%
Cattle - India
Mature Females
Mature Males
Young
Weighted Average
Mix (of grazing)
125
0.00
0.60
0.0
33% 50%
0.365
40%
200
0.00
0.00
2.7
0% 50%
0.370
10%
80
0.10
0.00
0.0
0% 50%
0.332
50%
110
0.05
0.24
0.3
13% 50%
0.349
100%
Cattle - Latin America
Mature Females
Mature Males
Young
Weighted Average
Mix (of grazing)
400
0.00
1.10
0
67% 60%
0.343
37%
450
0.00
0.00
0
0% 60%
0.370
6%
230
0.30
0.00
0
0% 60%
0.329
57%
306
0.17
0.41
0
25% 60%
0.337
100%
Sheep
Mature Females
Mature Males
Young
Weighted Average
Weight (kg) Weight Gain (kg/day) Milk (kg/day) Wool (kg/year) Pregnant DE Coefficient for NE m equation
Mix (of grazing)
45
0.00
0.70
4
50% 60%
0.217
40%
45
0.00
0.00
4
0% 60%
0.217
10%
5
0.11
0.00
2
0% 60%
0.236
50%
25
0.05
0.28
3
20% 60%
0.227
100%
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Table 3: Daily energy requirement and dry matter intake calculation
Cattle
Region
Africa
Asia
India
Latin
America
Average Characteristics
Weight Weight
Milk
Work Preggain
nant
(kg) (kg/day) (kg/day) (hrs/day
)
152
0.06
0.02
0.0 3%
251
0.13
0.20
0.0 9%
110
0.05
0.24
0.3 13%
306
0.17
0.41
0.0 25%
DE
CF
58%
60%
50%
60%
0.364
0.350
0.349
0.337
Energy (MJ/head/day)
Consumption
Mainte Activity Growth Lactation Power Wool Preg- REM REG Gross NEma
DMI
-nance
nancy
(note 1)
(note 2)
(MJ/kg - (kg/head/
note 5)
day)
15.7
5.7
1.2
0.0
0.0
0
0.0 0.49 0.26
5.2
84.0
16.2
22.1
8.0
2.8
0.3
0.0
0
0.2 0.49 0.28 119.8
5.5
21.9
11.8
4.3
1.0
0.4
0.3
0
0.2 0.44 0.19
4.0
87.6
21.6
24.6
8.9
3.8
0.6
0.0
0
0.6 0.49 0.28 139.5
5.5
25.5
Sheep
Region
Average Characteristics
Energy (MJ/head/day)
Consumption
Weight Weight
Milk
Work Preg- DE CF Mainte Activity Growth Lactation Power Wool Preg- REM REG Gross NEma
DMI
gain
nant
-nance
nancy
(kg) (kg/day) (kg/day) (hrs/day
(note 3)
(note 4)
(MJ/kg - (kg/head/
)
note 5)
day)
All regions
25
0.05
0.28
3.0 20% 60% 0.227
2.5
0.6
1.5
1.29
0 0.2
0.0 0.49 0.28
5.5
25.0
4.6
Notes
1. Assumes grazing
2. Assumes 4% milk fat
3. Assumes grazing on hilly terrain
4. Assumes 7% milk fat
5. Calculated using equation listed in Table 10.8
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History of the document
Version
05
Date
EB 42, Para 35
September 2008
04.1
29 November 2007
04
EB 33, Annex 13
03
EB 28, Annex 18
02
EB 26, Annex 17
01
CMP.1,
9 December 2005
Nature of revision
Section requiring estimation of project emissions from fertilizer application
revised to apply the guidance provided in para 35 of EB 42 meeting report.
According to EB 42 guidance GHG emissions from fertilizer application are
considered insignificant and can therefore be neglected.
To correct the reference to GPG tables for biomass (para 11) and root
shoot ratios (para 13) and other minor editorials.
Improved and simplified procedures for the estimation of (i) biomass stocks
in the baseline; (ii) leakage of GHG emissions related to the shift of preproject activities; and (iii) GHG emissions resulting from the use of fertilizer
as a result of the implementation of the A/R activity
changes to the calculations of biomass in baseline and improvement of
leakage calculations related to the grazing capacity of lands and
procedures for demonstration of the
eligibility of land in accordance with the COP/MOP 2 decision
To correct the equation for estimation of the below-ground biomass and
include some minor editorial changes.
Initial adoption.
29/29
Annex 2
Field Forms
Proyecto ArBolivia
Planillas de Campo (ver. Ago_ 09)
Formulario 1. CONCERTACIÓN
Información de la Propiedad
Nombre del Observador:
Nombre
Ap. Paterno
Fecha:
Ap. materno
Nº del Lote:
Superficie del Lote
Nombre de la Propiedad:
Altitud:
Ubicación (punto GPS):
UTM Coord_ X:
Día / Mes / Año
Has.
msnm
UTM Coord_Y:
Información del Agricultor
Nombre Entrevistado:
Nombre Dueño:
Nombre
Ap. Paterno
Ap. materno
Nombre
Ap. Paterno
Ap. materno
Comunidad/Sindicato
SCZ
BEN
LPZ
Departamento
¿Hay alguna Asociación
Productiva en el lugar?
¿Es miembro?
Nº de hijos que trabajan en el lote
¿Factible aplicar “AYNI”
para la PFC?
Nº de trabajadores disponibles para
la PFC
Comentarios:
Dpto.
Central
Otro
Provincia
Municipio
SI
SI
Derecho Propietario
Titulo Saneado
Documento
compra/venta
Titulo Ejecutorial
Titulo en
tramite
NO
NO
Sin Titulo
SI
NO
Especificar tipo de
Documento:
Información de la Concertación
Superficie Concertada 2:
Trabajador
C.I.
Datos Organización
Nº Total de hijos
Superficie Concertada 1:
Encargado
CBA
Datos Familiares
Nº Total Miembros Familia
Dueño
Has.
Has.
Especie concertada 1
Especie concertada 2
___________________________
Proyecto ArBolivia
Formulario 2. DATOS GENERALES (Selección, POP & PIF)
Información de la Propiedad
Nombre
Ap. Paterno
Fecha:
Ap. materno
Día / Mes / Año
Nº del Lote:
Superficie del Lote
Has.
Nombre de la Propiedad:
Altitud:
msnm
Coordenada Vivienda
Tipo de vivienda:
Nombre Entrevistado:
Nombre Dueño:
SCZ
X:
Y:
Coordenada Acceso Lote:
X:
Y:
Madera
Choza
Material
Nombre
Ap. Paterno
Ap. materno
Nombre
Ap. Paterno
Ap. materno
Comunidad/Sindicato
BEN
LPZ
CBA
Departamento
Fue el primero en ocupar el lote:
SI
NO
Datos Familiares
Nº Total Miembros Familia
Nº Total de hijos
Nº de hijos que trabajan en el lote
Nº de trabajadores disponibles para la PFC
Datos Organización
SI NO
¿Hay una asociación Productiva en el lugar?
¿Cuál?: _____________________________
¿Es miembro?
¿Factible aplicar “AYNI” para la PFC?
Coordenadas UTM – WGS84
X1
Y1
X2
Y2
X3
Y3
X4
Y4
X5
Y5
X6
Y6
X7
Y7
X8
Y8
X9
Y9
X10
Y10
Problemas con Insectos
1.
Ligero
Medio
Alto
2.
Ligero
Medio
Alto
3.
Ligero
Medio
Alto
Maquinaria Agrícola
Vías de Acceso
Tractor
Pavimento
Cosechadora
Terraplén
Motocultor
Senda
Row plow
Brecha
Arado
Ferrocarril
Sembradora
Fluvial
Rastra
Otro
Fumigador
Ninguno
Ninguna
Dueño
Encargado
C.I.
Dpto.
Central
Otro
Provincia
Municipio
Tiempo que ocupa:
Trabajador
Año(s)
Meses
Derecho Propietario
Titulo Saneado
Documento compra/venta
Titulo Ejecutorial
Titulo en tramite
Sin Titulo
Otro (especificar)
______________________________________________________________
Colindancias
Norte
Este
Sud
Oeste
Problemas con fuego (incendios)
No hay información
Frecuente
Nunca
Raro
Anual
Problemas con plagas
1.
2.
3.
Recursos Hídricos
Pozo
Rio
Arroyo
Potable
Otro
Acceso al lote
Camino transitable
Con problemas época de lluvia
Solo estación seca
No hay acceso vía terrestre
Ligero
Medio
Ligero
Medio
Ligero
Medio
Infraestructura
Casa
Galpones
Potreros
Alambrado
Riego
Otro
Alto
Alto
Alto
Proyecto ArBolivia
Formulario 3. CROQUIS (Selección, POP & PIF)
Croquis de la parcela
El croquis debe mostrar los sectores de PFC, mejoramiento de pasto y SAF; además Indicar los diferentes tipos de uso de suelo, localización de los puntos GPS, en lo
posible incluir fechas del historial de uso del suelo, lugar y número de fotografía que corresponde, anotar los nombres de los cuerpos de agua presentes en el lote e
identificar las servidumbres ecológicas definidas con el agricultor. Utilizar el reverso de la hoja para sectores adicionales
Coordenadas UTM-WGS84
Sector:
Sector:
Sector:
X1
Y1
X1
Y1
X1
Y1
X2
Y2
X2
Y2
X2
Y2
X3
Y3
X3
Y3
X3
Y3
X4
Y4
X4
Y4
X4
Y4
X5
Y5
X5
Y5
X5
Y5
X6
Y6
X6
Y6
X6
Y6
X7
Y7
X7
Y7
X7
Y7
X8
Y8
X8
Y8
X8
Y8
X9
Y9
X9
Y9
X9
Y9
X10
Y10
X10
Y10
X10
Y10
Proyecto ArBolivia
Formulario 4. UNIDADES DE USO DE SUELO, (Selección & POP)
Cód
Abrev.
muestra
1
2
3
4
5
6
7
8
9
10
11
12
Formulario obligatorio para POP
Tipo uso
actual
Área
(Ha)
Edad
actual
% Uso personal
/comercial
Rendimiento
Por Ha Unidad
Rotación Ganado
(años) Cant/Ha
Uso Anterior
Tiempo
USO DE SUELO
Razón del cambio
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Económico
Cosecha
Proyecto
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Poca Fertilidad
Otro
Uso Futuro
Proyecto ArBolivia
Formulario 5. VEGETACION DE LA UNIDAD (Selección, POP & PIF)
Información General
Fecha:
Nombre
Ap. Paterno
Ap. materno
Nombre
Ap. Paterno
Ap. materno
Día / Mes / Año
Nombre del propietario:
Coordenada UTM Punto de muestreo :
Coordenada UTM punto inicio de la unidad
Coordenada UTM punto fin de la unidad
X:
X:
X:
Nº Lote
Y:
Y:
Y:
Comunidad
Altitud:
Altitud:
Altitud:
msnm
msnm
msnm
Historial del uso o manejo de suelo y tendencia de uso futuro (información de la unidad de uso de suelo)
Código
% de uso personal/comercial
Uso Anterior
Abrev. muestra
Tipo de uso
actual
Área (has)
Rendimiento (por Ha)
Tiempo uso anterior
Edad actual
Ganado Nº/Ha
Unidad rendimiento
Suministro de agua:
(Practica de Riego)
Evidencia del tipo de uso anterior
Estrato
Arboles
Arboles
Arbustos
Arbustos
Herbáceos
Herbáceos
Razón del cambio:
Periodo de rotación (años)
Nº
Otro:
Uso futuro
Lluvia
Riego por inundación
Riego por aspersión
Riego por goteo
Tocones
Otro
Residuos de cultivos
Descripción:
Disturbio de suelo
Ninguno
Altura media (m)
<1
2-3
3-4
4-7
7-10
<1
2-3
3-4
4-7
7-10
<1
2-3
3-4
4-7
7-10
<1
2-3
3-4
4-7
7-10
<1
2-3
3-4
4-7
7-10
<1
2-3
3-4
4-7
7-10
Poca fertilidad
Proyecto
Económico
Cosecha
10-15
15-20
20-25
25-30
>30
10-15
15-20
20-25
25-30
>30
10-15
15-20
20-25
25-30
>30
10-15
15-20
20-25
25-30
>30
10-15
15-20
20-25
25-30
>30
10-15
15-20
20-25
25-30
>30
Cobertura
%
Tipo Vegetación
Huerto
Cultivo
Plantación
Vegetación Natural
Huerto
Cultivo
Plantación
Vegetación Natural
Huerto
Cultivo
Plantación
Vegetación Natural
Huerto
Cultivo
Plantación
Vegetación Natural
Huerto
Cultivo
Plantación
Vegetación Natural
Huerto
Cultivo
Plantación
Vegetación Natural
Nombre de la Cobertura
Edad (años)
Proyecto ArBolivia
Formulario 6. SUELOS DE LA UNIDAD (Selección, POP & PIF)
Fecha:
Nombre
Ap. Paterno
Ap. materno
Nombre
Ap. Paterno
Ap. materno
Día / Mes / Año
Nombre del propietario:
Nº Lote
Comunidad
Datos por horizonte de suelo
Profundidad
Horizontes
cm
Clase textura (Clas. FAO)
Color
Compactación
pH (acidez)
Indicador de impedimento
de drenaje e intensidad de
la evidencia
Presencia de piedras
(impide tomar muestras)
Materia orgánica
SI
cm
NO
SI
No evidente
Oxidación +/++
Gleyzación +/++
NO
cm
SI
No evidente
Oxidación +/++
Gleyzación +/++
cm
NO
SI
No evidente
Oxidación +/++
Gleyzación +/++
NO
No evidente
Oxidación +/++
Gleyzación +/++
SI
NO
SI
NO
SI
NO
SI
NO
SI
NO
SI
NO
SI
NO
SI
NO
Observaciones
Características del sitio
0-5
Pendiente (%)
5-10
Paisaje ( micro-relieve)
Pedregosidad superficial
Rio
Arroyo
>45
Micro-accidentado
Libre (15%)
Moderada (15-50% 10-30 m distancia)
Pedregoso (50-90% 2-10 m distancia)
Muy Pedregoso (>90% 1-2 m distancia)
Planta indicadora
Poco profunda (<0,5m)
Especie:
Indicadora de:
Moderada (0,5-0,9m)
Profunda (>0,9m)
Alta
Media
Baja
Nula
Alta
Media
Baja
Nula
Alta
Media
Baja
Alta
Media
Baja
Laminar
Surcos
Zanjas
Cárcavas
Eólica
Derrumbe
Mazamorra
Nombre:
Reptación lenta
Ancho (m)
Nombre:
Ancho (m)
Fenómenos de erosión
Forestal
Comercial
30-45
Ondulado
Deficiencia de Nutrientes (evidente en la vegetación)
Napa freática
Disponibilidad agua para ganado
Rendimiento de madera
Tasa est. crecimiento del bosque
Rendimiento productos no maderables
TIPO DE
PLANTACION:
15-30
Ondulado suave
No evidente
Presencia de plantas indicadoras
Cursos y cuerpos de agua
10-15
Plano
Sistema
Agroforestal
Sin datos
Ninguna
Permanente
Intermitentes
Riesgo de desborde
Permanente
Intermitentes
Riesgo de desborde
SOLO SELECCIÓN DE SITIOS
Sistema
Unidades de Protección
Silvopastoril (Franja de protección ribereña, curiches, laderas, rompe vientos, otras):
Manejo propuesto:
Nombre
Cantidad
Unidad
Superficie del sector
Especie 1
Has.
Especie 2
Especie 3
Fecha de entrega de plantines Forestal:
1ra
- 2da
- 3era
- 4ta
Semana
Fecha de entrega de plantines Sistemas:
1ra
- 2da
- 3era
Semana
Medidas de mitigación y protección necesarias
para proteger las plantaciones a establecer:
Mes
Año
- 4ta
Mes
Alambrar para evitar invasión de ganado
Establecer corta-fuegos
Año
Otro:
(en caso de establecimiento de franjas de protección o alambrado indicar la ubicación de estos en un croquis)
Proyecto ArBolivia
Formulario 7. ESTABLECIMIENTO DE PLANTACIONES FORESTALES
Nombre
Ap. Paterno
Ap. materno
Fecha:
Día / Mes / Año
Nombre Propietario:
Nombre
Ap. Paterno
Comunidad/ Sindicato
SCZ
BEN
LPZ
Fecha de Plantación
Mes
Año
Central
Otro
Provincia
Municipio
Especie
%
Sector
Superficie
Nombre
Hectáreas
Nº de Recibo
1.
2.
3.
Distanciamiento
x
x
x
Colindancias
Norte:
Este:
Sud:
Oeste:
Referencia fija
en el terreno:
Calidad de la plantación
Competencia con
maleza:
Iluminación
Sin o muy poca competencia (maleza baja, no influye al desarrollo del árbol)
Regular (retarda al crecimiento del árbol, casi igual en altura)
3.
1.
Competencia fuerte (tapa, está tapando a la planta)
Emergente (todos los individuos cuya copa está totalmente expuesta y libre de competencia lateral)
Luz total de arriba (recibe plena iluminación vertical; esta a lado a otra de igual o mayor altura que impide la luz
lateral)
Algo de luz de arriba (recibe luz superior de la copa en forma parcial, ya que son sombreados parcialmente por
otras copas)
Algo de luz lateral (la copa se encuentra totalmente sombreada verticalmente, pero expuesta a alguna luz
directa debido a claros o discontinuidad del dosel.
Sin luz directa (copa totalmente sombreada, tanto vertical como lateralmente)
Climáticas
Enfermedades
Falta de mantenimiento
Material vegetal malo
Ataque de plagas
Fuego
Ganado
Mala selección de sitio
5.
Causas
%
Actividad
Otra
Actividades realizadas en
el sector de plantación
Sanidad
Sano
No sano
2.
4.
Mortandad
Y1
Y2
Y3
Y4
Y5
Y6
Y7
Y8
Y9
Y10
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
1.
3.
NO
Observación:
Cultivo asociado:
2.
SI
Nº Lote
CBA
Departamento
Día
Ap. materno
Limpieza completa
Limpieza circular
Limpieza en fajas
Poda
Observaciones:
Firma del Técnico
…………………….…………………………………….
Deshije
Deschuponado
Protección contra fuego
Protección a ganado
Recomendaciones:
Refalle disperso
Refalle en bloques
Reposición
Raleo
Firma del Agricultor
Proyecto ArBolivia
Formulario 8. ESTABLECIMIENTO DE SISTEMAS AGROFORESTALES
Nombre
Ap. Paterno
Fecha:
Ap. materno
Día / Mes / Año
Nombre Propietario:
Nombre
Ap. Paterno
Ap. materno
SCZ
BEN
LPZ
Nº Lote
Central
Otro
Provincia
Municipio
CBA
Departamento
Sector
Superficie
X1
Día
Mes
Año
Y1
X2
X3
X4
X5
X6
X7
CULTIVOS SEMI-PERENNES (Agroforestales)
Distancias Nro. Recibo Sanidad Maleza Iluminación
Nombre
Hectáreas
Colindancias
Norte:
Este:
Sud:
Oeste:
Especie (nombre)
Cantidad plts/ha
X
X
Especie (nombre)
Cantidad plts/ha
ESPECIES FORESTALES DEL SISTEMA
X
Cultivo
Sano
No sano
Sano
No sano
Fecha de siembra
Sano
No sano
CULTIVOS ANUALES
Fecha de cosecha
Rendimiento
Y2
Y3
X4
X5
X6
X7
% Mortandad
Causa mortandad
% Mortandad
Causa mortandad
Unidad
Estado
Bueno
Regular
Malo
Bueno
Regular
Malo
Estado y Calidad de la plantación
Calidad del Sistema:
Cultivo asociado:
Competencia con maleza:
1. Sin o muy poca competencia (maleza
baja, no influye al desarrollo del árbol)
2. Regular (retarda al crecimiento del
árbol, casi igual en altura)
3. Competencia fuerte (tapa, está
tapando a la planta)
Observaciones:
Iluminación
1. Emergente (todos los individuos cuya copa está totalmente expuesta y libre de
competencia lateral)
2. Luz total de arriba (recibe plena iluminación vertical; esta a lado a otra de igual o
mayor altura que impide la luz lateral)
3. Algo de luz de arriba (recibe luz superior de la copa en forma parcial, ya que son
sombreados parcialmente por otras copas)
4. Algo de luz lateral (la copa se encuentra totalmente sombreada verticalmente,
pero expuesta a alguna luz directa debido a claros o discontinuidad del dosel.
5. Sin luz directa (copa totalmente sombreada, tanto vertical como lateralmente)
Mortandad
1. Climáticas
3. Falta mantenimiento
5. Ataque de plagas
7. Fuego
9. Otro:
Recomendaciones:
Firma del Técnico
2. Enfermedades
4. Ganado
6. Material vegetal malo
8. Mala selección de sitio
Proyecto ArBolivia
Formulario 9. ESTABLECIMIENTO DE SISTEMAS SILVOPASTORILES
Nombre
Ap. Paterno
Fecha:
Ap. materno
Día / Mes / Año
Nombre Propietario:
Nombre
Ap. Paterno
Ap. materno
SCZ
BEN
LPZ
Mes
Central
Otro
Provincia
Municipio
CBA
Departamento
Día
Año
Sector
Superficie
Nombre
Hectáreas
Colindancias
Norte:
Este:
Sud:
Oeste:
Especie
Cantidad plts/ha
Nro. Recibo
(*) Sistema de pastoreo
(**) Estado de la Pastura
Especie (nombre)
Nº Lote
Cantidad plts/ha
PASTURAS
Distanciamiento
1. Libre (1 potrero)
X1
Y1
X2
X3
X4
X5
X6
X7
Y2
Y3
X4
X5
X6
X7
Sistema de pastoreo (*)
- 2
- 3
Bueno
Regular
Malo
1
- 2
- 3
Bueno
Regular
Malo
2. Alterno (2 potreros)
3. Rotacional (>3 potreros)
En caso de “malo” o regular”, describa la causa del Problema
ESPECIES FORESTALES DEL SISTEMA
X
X
Estado pastura (**)
1
Sano
No sano
Sano
No sano
% Mortandad
Causa mortandad
Estado y Calidad de la plantación
Calidad del Sistema:
Competencia con maleza:
1. Sin o muy poca competencia (maleza
baja, no influye al desarrollo del árbol)
2. Regular (retarda al crecimiento del
árbol, casi igual en altura)
3. Competencia fuerte (tapa, está
tapando a la planta)
Observaciones:
Cultivo asociado:
Iluminación
1. Emergente (todos los individuos cuya copa está totalmente expuesta y libre de
competencia lateral)
2. Luz total de arriba (recibe plena iluminación vertical; esta a lado a otra de igual o
mayor altura que impide la luz lateral)
3. Algo de luz de arriba (recibe luz superior de la copa en forma parcial, ya que son
sombreados parcialmente por otras copas)
4. Algo de luz lateral (la copa se encuentra totalmente sombreada verticalmente,
pero expuesta a alguna luz directa debido a claros o discontinuidad del dosel.
5. Sin luz directa (copa totalmente sombreada, tanto vertical como lateralmente)
Mortandad
1. Climáticas
3. Falta mantenimiento
5. Ataque de plagas
7. Fuego
9. Otro:
2. Enfermedades
4. Ganado
6. Material vegetal malo
8. Mala selección de sitio
Recomendaciones:
……………………………………….
Firma del Técnico
…………………………………………………………
Nº 00012345
-Original -
Proyecto ArBolivia
Formulario 10. MANTENIMIENTO DE PLANTACIONES FORESTALES
Nombre
Ap. Paterno
Fecha:
Ap. materno
Día / Mes / Año
Nombre Propietario:
Nombre
Ap. Paterno
SCZ
BEN
LPZ
Ap. materno
Nº Lote
Central
Otro
Provincia
Municipio
CBA
Departamento
Superficie
Sector
1
6
Día
Mes
Año
Especie
Nombre
%
Altura promedio
Nº Mantenimiento
-2 -3 -4 -5
- 7 - 8 - 9 - 10
Hectáreas
% Mortandad
Coordenadas PFC (UTM–WGS84)
1.
mts.
X1
Y1
2.
mts.
X2
Y2
3.
mts.
X3
Y3
X4
Y4
Obs.:
Cultivo asociado:
1.
2.
3.
1.
Competencia con
maleza:
2.
Iluminación
3.
4.
5.
NO
Mortandad
(general)
Causas
SI
Sanidad
Sano
No sano
Luz total de arriba (recibe plena iluminación vertical; esta a lado a otra de igual o mayor altura que
impide la luz lateral)
Algo de luz de arriba (recibe luz superior de la copa en forma parcial, ya que son sombreados
parcialmente por otras copas)
Algo de luz lateral (la copa se encuentra totalmente sombreada verticalmente, pero expuesta a
alguna luz directa debido a claros o discontinuidad del dosel.
Climáticas
Enfermedades
Ataque de plagas
Fuego
Ganado
%
Actividades realizadas en
el sector de plantación
Actividad
Otra
Limpieza completa
Limpieza circular
Limpieza en fajas
Poda
Observaciones:
Firma del Técnico
…………………….…………………………………….
Deshije
Deschuponado
Protección contra fuego
Protección a ganado
Recomendaciones:
Refalle disperso
Refalle en bloques
Reposición
Raleo
Nº 00012345
-Original -
Proyecto ArBolivia
LIBRO DE ORDENES
FORMULARIO 11 - LIBRO DE ÓRDENES
Nombre
Ap. Paterno
Fecha:
Ap. materno
Día / Mes / Año
Nombre Propietario:
Nombre
Ap. Paterno
Ap. materno
SCZ
BEN
LPZ
Central
Provincia
Sector
Mes
Especie
Año
Tipo iluminación
Iluminación
Sanidad
Sano
No sano
2.
3.
1.
Emergente (todos los individuos con copa está totalmente expuesta y libre de competencia lateral)
lateral)
otras copas)
Climáticas
Enfermedades
2.
3.
4.
Causas
%
NO
X1
X2
Coordenadas PFC (UTM–WGS84)
Zona UTM:
Y1
Y2
1.
5.
Mortandad
SI
% Mortandad
Cultivo asociado:
Tipo de
competencia
Nº Visita
1 -2 -3 -4 -5 -6 7 - 8 - 9 - 10 - 11 - 12
Hectáreas
Altura promedio
mts.
mts.
mts.
1.
2.
3.
Municipio
Superficie
Nombre
%
Competencia
con maleza:
Otro
CBA
Departamento
Día
Nº Lote
Ataque de plagas
Ganado
Fuego
Otra
Recomendaciones
1. Refallar/replantar
2. Control de plagas
3. Limpieza (deshierbe)
4. Poda
5. Control de fuego
6. Protección contra ganado (animales)
…………………….…………………………………….
¿Qué? (Insumo/practica)
Rodales
Fajas
- Fajas
¿Cuánto?
¿Cuándo?
- Total
- Limpieza
7. Otro:
Observaciones:
Fecha de la próxima visita:
Día / Mes / Año
Firma del Técnico
Hora
Proyecto ArBolivia
Formulario 12. ESTABLECIMIENTO DE PLANTACIONES DE PROTECCIÓN
Nombre
Ap. Paterno
Ap. materno
Fecha:
Día / Mes / Año
Nombre Propietario:
Nombre
Ap. Paterno
SCZ
BEN
LPZ
Nº Lote
Central
Otro
Provincia
Municipio
CBA
Departamento
Día
Ap. materno
Mes
Año
Especie
%
Sector
Superficie
Nombre
Hectáreas
Nº de Recibo
1.
2.
3.
Distanciamiento
x
x
x
Colindancias
Norte:
Este:
Sud:
Oeste:
Referencia fija
en el terreno:
X1
X2
X3
X4
X5
X6
X7
X8
X9
X10
X11
X12
X13
Y1
Y2
Y3
Y4
Y5
Y6
Y7
X8
X9
X10
Y11
Y12
Y13
Datos de la verificación de estado de la plantacion
Competencia con
maleza:
1.
2.
3.
1.
lateral)
otras copas)
Climáticas
Enfermedades
Fuego
Anegamiento del suelo
Mala selección de especie
2.
Iluminación
3.
4.
SI
Tipo de protección
realizada
%
Tipo
Mortandad
NO
Causas
5.
Otra
…………………….…………………………………….
Cortinas rompimientos
Riberas de ríos, arroyos, lagos y laguna
Laderas con pendiente
superiores a 40%
Humedales, pantanos, curiches, bofedales y áreas afloramiento
natural de aguas y de recarga
Recomendaciones:
Observaciones:
Firma del Técnico
Annex 3
PLANTATION DESIGN PROTOCOL
Protocol
Forestry plantation design
Revised version 2007
CETEFOR
1
Antecedents
1.1.
Species selection
The site selection criteria ensure that the species most appropriate to the specific site
and the species can be recommended. Account may also be taken of the owner’s
preference in terms of the type of production and the goals of the plantation. The
following table shows the range of species and their individual characteristics.
requirements. The design of each plantation is formulated using this table.
Table 1: Species requirements
Tapirira guianensis
Virola peruviana
Hymenaea courbanil
Calophyllum brasiliense
Guarea rusby
A-N
A
A
A-N
Stryphnodendrum purpureum
Schlizobium amazonicum
A=Acido
f = favourable
N=Neutro
t = tolerant
C=Calizos
nt = not tolerant
Source: CETEFOR foundation
N
N
f
t
t
t
t
A-N
f
f
t
t
t
t
t
t
t
t
t
t
nt t
t
t
nt nt
nt nt
A-N
A-N
ne
t
t
t
t
f
f
f
f
f
f
f
f
f
ne
ne
ne
ne
f
f
Shadow
f
nt
f
nt
ne t
t
f nt nt
f
t
t
f
Light
A-N
A-N
f
f
Soil compaction
Dipteryx odorata
Dipteryx sp
Tabebuia sp.
Buchanavia sp
Light
Clay
t nt nt
nt nt nt
Loamy
f
e
Sandy
N-C
Soil depth
imperfect
Swietenia macrophylla
Cedrela fisillis
Poor
Free
Precious wood species
Mara
Cedro
Hardwood species
Almendrillo
Almendrillo amarillo
Tajibo
Verdolago negro de ala
Verdolago negro de pepa
semi-hardwood species
Palo román
Gabún
Paquio
Palo maría
Trompillo de altura
Tejeyeque
Soft wood species
Palo yugo
Serebo
Texture
Soil fertility
Drainage
Floodings
pH
pH-tolerance
Species
nt
nt
em
em
ej
ej
e
e
nt
nt
rj
nt
t
e
t
f
tj
ntj
nt
e
e
tj
ej
ej
ej
nt
nt
ne ne ne ne t
ne ne ne ne nt
t
e
f
nt
f
ntj
f
f
t
t
ne = not very demanding
e = demanding
em = demanding on maturity
f
f
f
nt
ej = demanding when young
tj = tolerant when young
ntj = no tolera cuando joven
Once the sites have been selected a table of potential species is drawn up,
according to the specific characteristics of the site. Based on this list the field agent
and the farmer decide and define together the objective of the plantation and the
specie(s) to be planted, according to the following factors:
I. The productive characteristics and socio economics of the area. The site
may be suitable for a certain type of plantation, but account also needs to
be taken of the following:
• Availability of financing resources and the desired pay-back period
• Corresponding markets
Protocol: Design of Forestry Plantations (rev2007)
Foundation Cetefor
2
•
The infrastructure of the area and the accessibility to the markets. If the
infrastructure and the accessibility are low, it is more favourable to
invest in species that produce timber of high value, in order to reduce
the relative costs of extraction and transport.
II. The objectives and requirements of the owners of the plantation; It is
necessary to define the owner’s objectives for the plantation clearly.
III. The rotation of the plantation; fast growing species or slow growing species.
1.2.
THE TIMBER PRODUCTION
The success of the plantation in productive terms depends on growth and risk
management. The financial result of a plantation depends on the quality of the
timber, the administrative and operative costs, the demand, the market price and
the access to the markets.
1.2.1 Growth
The growth of the trees depends on the species, age, site quality and the forestry
management. The site quality is a way of measuring the productive capacity of the
species. When a site contains all planting requirements the site has a better
productive capacity. In the plantation design one has to strive for optimum growth
and development for the selected species.
The initial results of the PPMs and the revised literature indicated that in the zones
where CETEFOR works the increase of the short term species (fast growth) will be
between 27 to 35 m3/ha/year, the species of average term growth (average
growth) will be between 15 to 22 m3/ha/year; and the long term species (slow
growth) will be between 7 and 14 m3/ha/year.
Table 2: Native forest species
Fast growth (10-15 years)
Palo Yugo
Serebo
Average growth (15-30 years)
Cedro
Palo Roman
Gabún
Palo Maria
Trompillo de altura
Tejeyeque
Foundation Cetefor
Small growth (>30 years)
Almendrillo
Mara
Paquio
Tajibo
Verdolaga negro de ala
Verdolaga negro de pepa
3
Plantation design
2.
2.1.
Geo-referencing and marked space for planting
Most of all it is important to demarcate the position and the exact surface of the parcel; this
is done using GPS and maps of the property. Once these criteria are confirmed, the
plantation design is completed and the quantities of planting material to be sent to the
plantation are determined.
2.2.
Plantation systems
The physiographic characteristics of the terrain determine which plantation system is
to be applied. The most frequently used plantations systems are:
a.
The real mark.- The planting material is distributed in a rectangular pattern at
equal distances. This system is applied to light terrains with small slopes.
Figure Nº 1:-The real mark system
b.
The three points system or triangular.- The planting material is distributed in a
triangular pattern; this system is realized in terrains with small or steep slopes.
Figure Nº 2.-Three points plantation system.
Foundation Cetefor
4
2.3.
Plantation density.-
The plantation density is determined by the distance between plants and furrows,
usually the distances are 2.5 x 3, 3 x 3 y 3 x 4 m. In commercial plantations the final
distance depends on the terrain, the specie(s) and the product to be generated. For
example if one needs to produce timber for triplex, trunks should be long without
branches and the diameter is less important. The density in this case would be
relatively greater compared with timber, where diameter is more important.
In the same way, the location of the fire breaks, wind breaks, corridors, and other
mitigation measures are planned to reduce the risks to the plantation.
Foundation Cetefor
5
3.
ESTABLISHMENT.-
3.1.-
Site preparation.-
Consist in the elimination of vegetation of the selected plantation area.
Depending on the species one eliminates the complete vegetation or maintains it part of it.
3.2.- Plantation outline and marking.One measures and distributes the distances according to the elected plantation system
using a surveying rod with wire previously marked with predetermined measures of 3 x 3
or 3 x 4m.
3.3. – Digging holes.Consists out of digging holes in the marked spaces according to the design, in light
terrains the holes have a diameter and depth of 20 x 20 cm, and in compacted terrains the
holes minimally need to measure 50 x 50 cm (for example pastures). The first 5 or 10 cm
of ground taken out for making the holes are separated because they have the highest
organic matter content and humus (Horizon A). The rest of the material extracted contains
less organic matter and humus (Horizon B). In the plantation first the material of Horizon A
is put to fill up the hole and afterwards Horizon B.
Foundation Cetefor
6
4
Pure and mixed plantations: Plantation Protocols
They distinguish between plantations of one single species or mixed plantations with
different forest species. One respects the following designs of the forestry plantations or if
not consult the person in charge, who can authorize adjustments to the designs, after a
technical justification.
Type 1: Plantations with one specie
1.1
Almendrillo, Dipteryx odorata
Spacing 3x3 (1.111 plants per hectare)
Sites: Light soils of low pH up to neutral, deep soils, without flooding, good to regular
drainage, specie is tolerant to short time inundations
1.2
Gabún, Virola peruviano
Sites: Acid up to neutral soils with poor drainage, tolerates inundations. This species does
not develop well in open spaces, requires semi-shade. It is possible to realize direct
sowing below fallow vegetation or secondary forest.
1.3
Palo maría, Calophyllum brasiliense
Sites: In light soils, humid with springs, moderate drainage, tolerates inundations.
Requires some semi-shade.
1.4
Palo yugo, Stryphnodendron purpureum
In acid up to neutral soils, fine structure, imperfect up to very poor drainage, tolerates
inundations and tolerates compact soils.
1.5
Serebo, Schizolobium amazonicum
Spacing 2.5x2.5 (1.600 trees per hectare)
The Serebo plantations one realizes by means of direct sowing, 2 seeds per hole.
Sites: Light soils, sandy, or light, low up to neutral pH, deep soils, not compacted, regular
up to good drainage.
1.6
Tejeyeque, Centrolobium tomentosum
Sites: Light soils of pH 5 up to neutral, deep soils, without inundations, with good
drainage.
1.7
Trompillo de altura, Guarea rusby
Sites: Light sandy or sandy soils, with low up to neutral pH, soils can not be compacted,
the drainage needs to be regular up to good, doesn’t tolerate inundations not even for
short periods.
1.8
Verdolago negro de ala, Terminalia amazonica
Sites: light soils of low up to neutral pH, tolerates superficial soils, but the drainage needs
to be regular up to good, does not tolerate inundations.
Foundation Cetefor
7
1.9
Verdolago negro de pepa, Buchanavia sp.
Sites: In acid up to neutral soils, light structure, imperfect up to very poor drainage,
tolerates inundations.
1.10 Teca, Tectona grandis
Spacing 3x3 (1,111 plants per hectare)
Sites: A deep soil, pH > 5.3, does not tolerate inundations, for climatologically reasons this
specie shall only be introduced in areas with a more pronounced dry period. For the
project area this means; east of de river Sajta and in the provinces of Iturralde y Balivian.
Type 2: Mixed plantations
Type 2.1
Serebo (556) with Tejeyeque (555)
Sites: Light soils with low up to neutral pH, deep soils, without inundations, drainage needs
to be regular up to good.
Type 2.2
Serebo (450 plants), with Tejeyeque (450 plants), with Almendrillo (211 plants)
Sites: Light soils with low up to neutral pH, deep soils, without inundations, the drainage
needs to be regular up to good.
Type 2.3
Serebo (450), Tejeyeque (400), Verdolago negro de ala (261)
Sites: Light soils with low up to neutral pH, deep soils with regular up to good drainage.
Type 2.4
Serebo (450), Gabun (400), Verdolago negro de pepa (261)
Sites: Light soils, low up to neutral pH, deep soils, tolerate inundations, but the drainage
needs to be regular up to good.
Type 2.5
Gabun (761), Almendrillo (350)
Sites: In light soils, well drained, tolerates inundations.
Type 2.6
Serebo (550), Palo maría (300), Almendrillo (261)
Sites: In light soils, humid with springs, moderate drainage and tolerate inundations.
Type 2.7
Serebo (550), Gabún (300), Verdolago negro de pepa (261)
Sites: In acid up to neutral soils, fine texture, imperfect up to poor drainage, tolerate
inundations.
Type 2.8
Serebo (500), con Verdolago negro de ala (300), con Almendrillo (311).
Sites: Acid soils, well drained with a fine and sandy texture
Type 2.9
Foundation Cetefor
8
Serebo (500), Gabún (391), Almendrillo (220 plants)
Sites: In acid and poor soils, with imperfect up to poor drainage, also tolerates inundations
Observations:
1. The species cedro and mara can be planted in small amounts (max 50/ha) in areas with
deep soils and good drainage.
2. If one establishes forestry plantations and at the same time perennial crops like banana
or palmito the distance and the selection of species changes. Always one has to take into
account the requisites and characteristics of the trees planted, every change in the
protocol has to be authorized by the technical responsible of CETEFOR
Foundation Cetefor
9
Annex 4
4.a Tree growth estimation per tree species (M3/ha/year)
4.b Annual Carbon Increment per specie(tC/ha/year)
4.c Annual Net GHG removals per specie (tCO2e/year)
and average NET GHG removals per specie for the
whole project
Annex 4.a
Tree growth estimation per tree species
(M3/ha/year)
annex 4a
Age
in
years
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
33
34
35
36
37
38
39
40
Stem volume per hectare (m3)
Schizolobium
Standing Extracted
wood
wood
0
28
56
84
84
112
140
126
154
182
158
186
214
0
28
56
84
84
112
140
126
154
182
158
186
214
0
0
0
0
28
0
0
42
0
0
53
0
0
242
0
0
0
28
0
0
42
0
0
53
0
0
242
28
0
56
0
84
0
84
28
112
0
140
0
126
42
154
0
182
0
158
53
186
0
214
0
0
242
28
0
MAI = 28 m3/year
Stryphnodendron
Standing Extracted
wood
wood
0
28
56
84
84
112
140
126
154
182
158
186
214
0
28
56
84
84
112
140
126
154
182
158
186
214
0
0
0
0
28
0
0
42
0
0
53
0
0
242
0
0
0
28
0
0
42
0
0
53
0
0
242
28
0
56
0
84
0
84
28
112
0
140
0
126
42
154
0
182
0
158
53
186
0
214
0
0
242
28
0
MAI = 28 m3/year
Guarea rusby
Standing Extracted
wood
wood
0
19
38
57
76
67
86
105
124
143
162
135
154
173
192
211
184
203
222
241
260
279
0
0
0
0
0
29
0
0
0
0
0
45
0
0
0
0
46
0
0
0
0
0
298
19
0
38
0
57
0
76
0
67
29
86
0
105
0
124
0
143
0
162
0
135
45
154
0
173
0
192
0
211
0
184
46
203
0
222
0
MAI = 19 m3/year
Aspidosperma
Standing Extracted
wood
wood
0
18
36
54
57
75
93
111
94
112
130
148
121
139
157
175
148
166
184
202
175
193
211
229
247
0
0
0
0
15
0
0
0
35
0
0
0
45
0
0
0
45
0
0
0
45
0
0
0
0
265
18
0
36
0
54
0
57
15
75
0
93
0
111
0
94
35
112
0
130
0
148
0
121
45
139
0
157
0
175
0
MAI = 18 m3/year
Centrolobium
Standing Extracted
wood
wood
0
15
30
45
45
60
75
90
79
94
109
124
104
119
134
149
123
138
153
168
137
152
167
182
197
0
0
0
0
15
0
0
0
26
0
0
0
35
0
0
0
41
0
0
0
46
0
0
0
0
212
15
0
30
0
45
0
45
15
60
0
75
0
90
0
79
26
94
0
109
0
124
0
104
35
119
0
134
0
149
0
MAI = 15 m3/year
Tectona Grandis
Standing Extracted
Standing Extracted
wood
wood
wood
wood
0
0
0
0
9
0
15
0
22
0
30
0
36
0
45
0
51
0
45
15
43
28
60
0
69
0
75
0
100
0
90
0
135
0
79
26
164
0
94
0
113
76
109
0
133
0
124
0
151
0
104
35
167
0
119
0
182
0
134
0
160
36
149
0
174
0
123
41
186
0
138
0
197
0
153
0
208
0
168
0
182
35
137
46
190
0
152
0
198
0
167
0
203
0
182
0
207
0
197
0
213
212
9
0
15
0
22
0
30
0
36
0
45
0
51
0
45
15
43
28
60
0
69
0
75
0
100
0
90
0
135
0
79
26
164
0
94
0
113
76
109
0
133
0
89
35
151
0
104
0
167
0
119
0
182
0
134
0
160
36
108
41
MAI = 0 m3/year
MAI = 15 m3/year
annex 4a (continuation)
Age
in
years
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
33
34
35
36
37
38
39
40
Tapirira guianensis
Standing Extracted
wood
wood
0
19
38
57
76
67
86
105
124
143
162
135
154
173
192
211
184
203
222
241
260
279
0
0
0
0
0
29
0
0
0
0
0
45
0
0
0
0
46
0
0
0
0
0
298
19
0
38
0
57
0
76
0
67
29
86
0
105
0
124
0
143
0
162
0
135
45
154
0
173
0
192
0
211
0
184
46
203
0
222
0
MAI = 19 m3/year
Stem volume per hectare (m3)
Virola flexuasa
Standing Extracted
wood
wood
0
15
30
45
45
60
75
90
79
94
109
124
104
119
134
149
123
138
153
168
137
152
167
182
197
0
0
0
0
15
0
0
0
26
0
0
0
35
0
0
0
41
0
0
0
46
0
0
0
0
212
15
0
30
0
45
0
45
15
60
0
75
0
90
0
79
26
94
0
109
0
89
35
104
0
119
0
134
0
108
41
MAI = 15 m3/year
Dipteryx odorata
Standing Extracted
wood
wood
0
8
16
24
32
40
36
44
52
60
68
76
63
71
79
87
95
103
83
91
99
107
115
123
131
104
112
120
128
136
108
116
124
132
140
0
0
0
0
0
0
12
0
0
0
0
0
21
0
0
0
0
0
28
0
0
0
0
0
0
35
0
0
0
0
36
0
0
0
0
148
8
0
16
0
24
0
32
0
40
0
MAI = 8 m3/year
Buchenavia oxycarpa
Standing Extracted
wood
wood
0
8
16
24
32
40
36
44
52
60
68
76
63
71
79
87
95
103
83
91
99
107
115
123
131
104
112
120
128
136
108
116
124
132
140
0
0
0
0
0
0
12
0
0
0
0
0
21
0
0
0
0
0
28
0
0
0
0
0
0
35
0
0
0
0
36
0
0
0
0
148
8
0
16
0
24
0
32
0
40
0
MAI = 8 m3/year
Terminalia oblonga
Standing Extracted
wood
wood
0
8
16
24
32
40
36
44
52
60
68
76
63
71
79
87
95
103
83
91
99
107
115
123
131
104
112
120
128
136
108
116
124
132
140
0
0
0
0
0
0
12
0
0
0
0
0
21
0
0
0
0
0
28
0
0
0
0
0
0
35
0
0
0
0
36
0
0
0
0
148
8
0
16
0
24
0
32
0
40
0
MAI = 8 m3/year
Standing Extracted
wood
wood
0
12
24
36
48
60
72
84
64
76
88
100
112
124
105
117
129
141
153
165
136
148
160
172
184
196
208
220
232
244
0
0
0
0
0
0
0
0
32
0
0
0
0
0
31
0
0
0
0
0
41
0
0
0
0
0
0
0
0
0
256
12
0
24
0
36
0
48
0
60
0
72
0
84
0
64
32
76
0
88
0
MAI = 12 m3/year
Annex 4.b
Annual Carbon Increment per specie(tC/ha/year)
4.b.1 Tables
4.b.2 graphics
Below Ground Carbon per hectare
Year
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
Schizolobium
amazonicum
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
14.6
29.2
43.8
43.8
58.4
73.1
65.8
80.4
95.0
82.2
96.8
111.4
126.0
14.6
29.2
43.8
43.8
58.4
73.1
65.8
80.4
95.0
82.2
96.8
111.4
126.0
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
Stryphnodendron
purpureum
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
15.5
31.0
46.5
46.5
62.0
77.5
69.8
85.3
100.8
87.2
102.7
118.2
133.7
15.5
31.0
46.5
46.5
62.0
77.5
69.8
85.3
100.8
87.2
102.7
118.2
133.7
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
Guarea rusby
GHG
removal
(tC)
0.0
10.5
21.0
31.6
42.1
36.8
47.3
57.9
68.4
78.9
89.4
75.0
85.5
96.0
106.5
117.1
102.1
112.6
123.2
133.7
144.2
154.7
165.0
10.5
21.0
31.6
42.1
Long
term
average
storage
(tC)
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
Aspidosperma
macrocarpon
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
12.8
25.7
38.5
40.7
53.5
66.4
79.2
67.1
79.9
92.8
105.6
86.3
99.2
112.0
124.9
105.6
118.4
131.3
144.1
124.9
137.7
150.6
163.4
176.2
189.1
12.8
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
Centrolobium
tomentosum
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
9.3
18.5
27.8
27.8
37.1
46.3
55.6
48.8
58.1
67.3
76.6
64.2
73.5
82.8
92.0
76.0
85.2
94.5
103.8
84.6
93.9
103.2
112.4
121.7
131.0
9.3
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
Tectona Grandis
GHG
removal
(tC)
0.0
5.0
12.3
20.2
28.5
24.0
38.4
55.6
75.0
91.0
62.5
73.6
83.6
92.4
100.7
88.8
96.3
102.9
109.3
115.4
101.0
105.4
109.8
112.6
114.8
118.0
5.0
Long
term
average
storage
(tC)
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
Calophyllum
basiliense
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
8.8
17.6
26.4
26.4
35.1
43.9
52.7
46.3
55.1
63.8
72.6
60.9
69.7
78.5
87.3
72.0
80.8
89.6
98.4
80.2
89.0
97.8
106.6
115.4
124.2
8.8
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
Schizolobium
amazonicum
27
28
29
30
31
32
33
34
35
36
37
38
39
40
14.6
29.2
43.8
43.8
58.4
73.1
65.8
80.4
95.0
82.2
96.8
111.4
126.0
14.6
68
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
67.7
Stryphnodendron
purpureum
15.5
31.0
46.5
46.5
62.0
77.5
69.8
85.3
100.8
87.2
102.7
118.2
133.7
15.5
72
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
71.9
Guarea rusby
36.8
47.3
57.9
68.4
78.9
89.4
75.0
85.5
96.0
106.5
117.1
102.1
112.6
123.2
78
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
78.1
Aspidosperma
macrocarpon
25.7
38.5
40.7
53.5
66.4
79.2
67.1
79.9
92.8
105.6
86.3
99.2
112.0
124.9
88
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
88.1
Centrolobium
tomentosum
18.5
27.8
27.8
37.1
46.3
55.6
48.8
58.1
67.3
76.6
64.2
73.5
82.8
92.0
63
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
62.9
Tectona Grandis
12.3
20.2
28.5
24.0
38.4
55.6
75.0
91.0
62.5
73.6
83.6
92.4
100.7
88.8
68
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
68.0
Calophyllum
basiliense
17.6
26.4
26.4
35.1
43.9
52.7
46.3
55.1
63.8
52.1
60.9
69.7
78.5
63.3
59
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
58.5
Tapirira guianensis
Year
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
GHG
removal
(tC)
0.0
11.1
22.3
33.4
44.5
39.0
50.1
61.2
72.3
83.5
94.6
79.3
90.4
101.6
112.7
123.8
108.0
119.1
130.3
141.4
152.5
163.6
174.6
11.1
22.3
33.4
44.5
Long
term
average
storage
(tC)
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
Virola flexuasa
GHG
removal
(tC)
0.0
8.3
16.6
24.9
24.9
33.2
41.5
49.8
43.8
52.1
60.4
68.7
57.6
65.9
74.2
82.5
68.1
76.4
84.7
93.0
75.9
84.2
92.5
100.8
109.1
117.4
8.3
Long
term
average
storage
(tC)
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
Dipteryx odorata
GHG
removal
(tC)
0.0
7.8
15.5
23.3
31.0
38.8
34.9
42.6
50.4
58.1
65.9
73.7
61.1
68.8
76.6
84.3
92.1
99.8
80.7
88.4
96.2
103.9
111.7
119.4
127.2
101.2
109.0
Long
term
average
storage
(tC)
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
Buchenavia
oxycarpa
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
6.6
13.1
19.7
26.2
32.8
29.5
36.1
42.6
49.2
55.8
62.3
51.7
58.2
64.8
71.3
77.9
84.5
68.1
74.6
81.2
87.7
94.3
100.9
107.4
85.3
91.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
Terminalia
oblonga
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
6.4
12.8
19.2
25.6
32.0
28.8
35.1
41.5
47.9
54.3
60.7
50.3
56.7
63.1
69.5
75.9
82.3
66.5
72.9
79.3
85.7
92.1
98.4
104.8
83.4
89.8
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
Terminalia
amazonica
Long
GHG
term
removal average
(tC)
storage
(tC)
0.0
8.4
16.9
25.3
33.7
42.2
50.6
59.0
45.0
53.4
61.9
70.3
78.7
87.2
73.8
82.2
90.7
99.1
107.5
116.0
95.6
104.0
112.5
120.9
129.3
137.8
146.2
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
Tapirira guianensis
27
28
29
30
31
32
33
34
35
36
37
38
39
40
39.0
50.1
61.2
72.3
83.5
94.6
79.3
90.4
101.6
112.7
123.8
108.0
119.1
130.3
83
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
82.6
Virola flexuasa
16.6
24.9
24.9
33.2
41.5
49.8
43.8
52.1
60.4
49.3
57.6
65.9
74.2
59.8
55
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
55.3
Dipteryx odorata
116.7
124.5
132.2
105.0
112.7
120.5
128.2
136.0
143.8
7.8
15.5
23.3
31.0
38.8
76
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
75.6
Buchenavia
oxycarpa
98.4
105.0
111.5
88.6
95.1
101.7
108.2
114.8
121.4
6.6
13.1
19.7
26.2
32.8
64
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
63.8
Terminalia
oblonga
96.2
102.6
109.0
86.5
92.9
99.3
105.7
112.1
118.5
6.4
12.8
19.2
25.6
32.0
62
Terminalia
amazonica
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
62.3
154.6
163.1
171.5
179.9
8.4
16.9
25.3
33.7
42.2
50.6
59.0
45.0
53.4
61.9
76
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
75.9
Annex 4b-2
C on time t(tn/ha) and average carbon (tn/ha) per specie
Schizolobium amzonicum
140.0
160.0
120.0
140.0
120.0
100.0
100.0
80.0
tC
tC
GHG removal (tC)
GHG removal (tC)
80.0
60.0
Long term average storage (tC)
60.0
40.0
40.0
20.0
20.0
0.0
0.0
0
5
10
15
20
25
30
35
40
0
5
10
15
Year
20
25
30
35
40
Year
Guarea rusby
180.0
200.0
160.0
180.0
140.0
160.0
140.0
120.0
120.0
100.0
GHG removal (tC)
tC
tC
GHG removal (tC)
100.0
80.0
80.0
60.0
40.0
60.0
40.0
20.0
20.0
0.0
0.0
0
5
10
15
20
Year
25
30
35
40
0
5
10
15
20
Year
25
30
35
40
Annex 4b-2 (continuación)
Tectona Grandis
140.0
140.0
120.0
120.0
100.0
100.0
tC
GHG removal (tC)
80.0
GHG removal (tC)
tC
80.0
60.0
60.0
40.0
40.0
20.0
20.0
0.0
0.0
0
5
10
15
20
25
30
35
0
40
5
10
15
20
25
30
35
40
Year
Year
Tapirira guianensis
140.0
200.0
180.0
120.0
160.0
100.0
140.0
120.0
tC
GHG removal (tC)
60.0
tC
80.0
GHG removal (tC)
100.0
80.0
40.0
60.0
40.0
20.0
20.0
0.0
0.0
0
5
10
15
20
Year
25
30
35
40
0
5
10
15
20
Year
25
30
35
40
Virola flexuasa
Dipteryx odorata
140.0
160.0
120.0
140.0
120.0
100.0
100.0
tC
GHG removal (tC)
tC
80.0
GHG removal (tC)
80.0
60.0
60.0
40.0
40.0
20.0
20.0
0.0
0.0
0
5
10
15
20
25
30
35
0
40
5
10
15
20
25
30
35
40
Year
Year
Terminalia oblonga
Buchenavia oxycarpa
140.0
140.0
120.0
120.0
100.0
100.0
80.0
tC
GHG removal (tC)
GHG removal (tC)
tC
80.0
60.0
60.0
40.0
40.0
20.0
20.0
0.0
0.0
0
5
10
15
20
Year
25
30
35
40
0
5
10
15
20
Year
25
30
35
40
200.0
180.0
160.0
140.0
tC
120.0
GHG removal (tC)
100.0
80.0
60.0
40.0
20.0
0.0
0
5
10
15
20
Year
25
30
35
40
Annex 4.c
Surfaces planted and Average Net GHG removals per
specie
Yearly Net GHG removals per specie
(tCO2e/year)
Annex 4c -1 Average Net GHG removals per specie (tCO2e/year) for the whole project
Surface per planting year per specie
Growth class
Fast
Fast
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Scientific name
Guarea rusby
Tapirira guianensis
Tectona grandis
Virola flexuosa
Buchenavia oxycarpa
Dipteryx odorata
Terminalia oblonga
Common name
Serebo
Palo yugo
Jichituriqui
Palo María
Tejeyeque
Trompillo de altura
Palo román
Teca
Gabún
Almendrillo
2007
2008
2009
2010
13.38
0.40
0.00
0.00
0.00
0.00
2.21
0.00
0.00
0.00
0.00
0.00
0.00
16.00
22.10
34.38
41.14
15.54
76.19
10.05
75.10
171.54
22.93
2.57
31.43
19.23
15.81
538.00
18.03
0.00
23.03
4.20
40.31
2.75
48.27
64.95
242.76 153.48
23.27
7.30
60.25
34.88
141.42
17.96
6.58
0.00
11.00
6.29
40.96
40.22
16.66
9.98
2.47
0.00
675.00 342.00
Promedio
actual
52.42
61.09
82.65
132.41
477.34
40.45
172.21
325.56
28.89
20.04
114.17
45.88
17.90
1571.00
2011
2012
2013
25.00
50.00
50.00
15.00
30.00
30.00
30.00
60.00
60.00
85.00
170.00
170.00
125.00
250.00
250.00
15.00
30.00
30.00
50.00
100.00
100.00
40.00
80.00
80.00
5.00
10.00
10.00
15.00
30.00
30.00
60.00
120.00
120.00
25.00
50.00
50.00
10.00
20.00
20.00
500.00 1000.00 1000.00
2014
46.45
27.87
55.74
157.93
232.25
27.87
92.90
74.32
9.29
27.87
111.48
46.45
18.58
929.00
Total surface
223.87
163.96
288.39
715.34
1334.59
143.32
515.11
599.88
63.18
122.91
525.65
217.33
86.48
5000.00
Net GHG removal per planting year
Average CO2 approach = Average CO2e = total cumulative Net GHG removal (in ton CO2e) for the whole rotation of the specie divided by the length (years) of the rotation
Growth class
Fast
Fast
Medium
Medium
Medium
Medium
Medium
Medium
Medium
Slow
Slow
Slow
Slow
Scientific name
Guarea rusby
Tapirira guianensis
Tectona grandis
Virola flexuosa
Buchenavia oxycarpa
Dipteryx odorata
Terminalia oblonga
Common name
Serebo
Palo yugo
Jichituriqui
Palo María
Tejeyeque
Trompillo de altura
Palo román
Teca
Gabún
Almendrillo
2007
2008
2009
3,315
5,473
4,465
106
9,037
6,055
13,259
12,992
3,325
10,331
17,519
55,820
2,871
6,650
669
22,699
18,211
42,678
35,186
4,640
1,332
599
2,567
8,692
11,324
5,345
4,630
3,601
563
4,090 139,741 170,124
2010
1,103
888
13,901
35,290
2,085
10,544
4,470
1,468
11,120
2,773
83,641
N GHG
Removal
Total Net
2011
2012
2013
2014
from
GHG
Removal tn
planted
CO2e
areas
12,984
6,192
12,385
12,385
11,506
55,452
16,060
3,944
7,887
7,887
7,327
43,105
26,638
9,669
19,339
19,339
17,966
92,951
28,341
18,193
36,386
36,386
33,803
153,109
109,759
28,743
57,485
57,485
53,404
306,876
11,559
4,286
8,572
8,572
7,964
40,953
52,052
15,113
30,226
30,226
28,080
155,696
80,999
9,952
19,904
19,904
18,491
149,249
5,846
1,012
2,023
2,023
1,880
12,783
4,679
3,502
7,003
7,003
6,506
28,693
31,568
16,590
33,180
33,180
30,824
145,342
12,749
6,947
13,895
13,895
12,908
60,393
4,076
2,278
4,556
4,556
4,232
19,697
397,309 126,420 252,840 252,840 234,889
1,264,299
Annex 4c -2 Yearly Net GHG removals per specie (tCO2e/year) for the whole project
Year
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
Schizolobium
amazonicum
Stryphnodendron
purpureum
-80
505
2,330
5,068
7,021
9,748
15,445
23,528
32,487
40,774
48,974
54,458
60,793
68,699
68,195
64,886
64,561
71,102
70,291
58,272
46,016
33,361
41,350
49,251
54,458
60,793
68,699
68,195
64,886
64,561
71,102
70,291
58,272
46,016
33,361
41,350
49,251
54,458
60,793
68,699
68,195
-2
-185
1,695
4,783
8,025
10,301
14,994
22,196
27,702
33,672
40,945
43,784
48,296
54,491
59,518
48,663
44,869
49,018
48,908
42,261
36,477
28,226
34,017
41,112
43,784
48,296
54,491
59,518
48,663
44,869
49,018
48,908
42,261
36,477
28,226
34,017
41,112
43,784
48,296
54,491
59,518
Guarea rusby
-60
229
1,352
2,710
4,618
7,141
10,191
15,275
20,003
23,863
27,710
30,594
34,161
38,909
42,951
45,620
47,349
48,327
53,062
57,078
59,692
62,307
65,113
64,435
57,630
58,620
54,937
41,596
27,670
15,800
20,349
24,029
27,710
30,594
34,161
38,909
42,951
45,620
47,349
48,327
Aspisdosperma
macrocarpon
Centrolobium
tomentosum
Tectona
Grandis
Calophyllum
basiliense
Tapirira
guianensis
Virola
flexuasa
Dipteryx
odorata
Buchenavia
oxycarpa
Terminalia
oblonga
Terminalia
amazonica
-246
1,521
5,088
8,623
12,023
18,416
28,769
41,174
48,813
57,017
68,313
78,969
82,034
85,826
93,800
103,671
105,166
107,389
113,905
123,775
125,271
127,493
134,009
143,880
150,219
156,557
134,875
124,036
135,529
126,518
96,948
68,643
42,222
49,504
57,350
68,313
78,969
82,034
85,826
93,800
-455
1,103
9,930
24,141
39,719
59,799
90,305
130,885
163,478
188,156
216,695
253,415
276,733
289,399
307,637
341,808
358,996
363,704
375,122
407,595
420,522
419,448
425,971
457,029
475,063
493,097
476,397
419,365
389,753
371,225
288,112
206,938
135,255
166,356
189,543
216,695
253,415
276,733
289,399
307,637
-1,024
1,511
8,244
16,568
27,089
31,213
43,248
67,497
94,922
120,742
119,454
125,544
151,919
173,597
186,716
184,234
183,803
200,318
213,803
223,376
219,402
217,930
228,509
235,890
238,769
241,319
170,908
128,541
132,466
127,470
98,400
77,029
68,895
95,843
121,186
119,454
125,544
151,919
173,597
186,716
-93
203
1,665
5,099
10,357
20,355
35,341
55,832
73,224
89,145
104,095
122,070
134,130
144,211
153,232
169,564
178,138
184,394
189,524
204,761
210,978
214,593
216,991
231,315
237,241
243,167
243,212
246,869
240,019
223,538
167,505
110,730
58,804
75,181
90,088
104,095
120,902
130,983
139,329
146,842
-13
-371
2,528
7,608
14,034
22,501
30,395
43,763
62,630
80,870
96,050
110,973
118,712
134,350
151,674
167,532
178,325
181,918
188,455
205,712
221,476
232,301
243,123
253,172
225,767
212,993
211,331
199,817
151,841
105,268
64,378
82,021
96,604
110,973
118,712
134,350
151,674
167,532
178,325
181,918
188,455
-137
534
1,406
2,249
2,652
3,776
5,355
7,149
7,610
8,981
10,670
12,323
12,082
13,065
14,492
16,053
15,350
16,081
17,338
18,838
17,780
18,331
19,475
20,925
21,908
22,890
14,067
13,525
15,442
14,508
11,946
9,558
7,324
7,725
9,036
10,670
10,693
11,676
13,065
14,136
-188
532
2,196
4,885
9,109
16,730
26,540
40,128
53,874
66,776
77,069
86,696
94,341
106,435
118,178
128,445
134,235
140,025
143,350
154,592
165,370
174,198
177,110
180,021
183,773
194,628
204,978
214,748
222,070
221,969
217,835
214,230
223,815
230,860
230,207
229,554
213,424
209,443
202,990
186,109
-15
-0
253
606
1,246
2,639
4,664
7,326
10,195
12,750
14,751
16,586
18,335
20,650
23,170
25,139
26,162
27,185
28,126
30,240
32,627
34,282
34,673
35,064
35,635
38,282
40,195
42,450
43,788
43,548
43,030
41,981
44,218
45,511
45,181
44,850
43,608
42,279
42,398
38,640
-94
-2
686
1,047
1,677
2,692
3,617
5,629
7,776
9,571
11,007
12,331
12,733
14,629
16,656
18,069
18,866
19,664
19,263
21,117
23,144
24,359
24,761
25,163
25,680
26,096
27,905
29,932
30,940
30,928
29,245
29,151
31,179
32,149
32,061
31,973
25,168
26,265
28,292
25,975
-115
409
1,392
2,593
4,533
7,975
12,974
19,776
25,141
30,901
37,008
41,599
44,128
46,658
47,943
53,441
59,297
63,953
66,611
69,269
70,178
75,304
80,903
84,914
86,284
87,653
89,398
96,051
102,704
109,357
116,010
109,972
107,090
107,159
97,317
70,981
44,644
20,650
25,717
31,178
Total
-95
-2,476
12,593
49,671
97,600
155,572
231,571
350,492
513,490
660,352
793,872
895,985
1,007,927
1,118,137
1,212,765
1,285,855
1,373,800
1,429,401
1,478,690
1,526,349
1,614,610
1,638,853
1,686,735
1,751,049
1,802,644
1,834,282
1,896,830
1,784,401
1,622,502
1,555,079
1,469,359
1,290,601
1,089,401
939,978
1,021,180
1,115,846
1,177,529
1,225,092
1,285,016
1,353,070
1,395,527
Annex 5
IPCC TABLES
3A.1.8
3A.1.10
TABLE 3A.1.8
AVERAGE BELOWGROUND TO ABOVEGROUND BIOMASS RATIO (ROOT-SHOOT RATIO, R)IN NATURAL REGENERATION BY
BROAD CATEGORY (tonnes dry matter/tonnes dry matter)
(To be used for R in Equation 3.2.5)
Aboveground
biomass (t/ha)
Mean
SD
lower
range
upper
range
<125
0.42
0.22
0.14
0.83
5, 7, 13, 25, 28, 31,
48, 71
Primary tropical/sub-tropical
moist forest
NS
0.24
0.03
0.22
0.33
33, 57, 63, 67, 69
Tropical/sub-tropical dry
forest
NS
0.27
0.01
0.27
0.28
65
Conifer forest/plantation
<50
0.46
0.21
0.21
1.06
2, 8, 43, 44, 54, 61,
75
50-150
0.32
0.08
0.24
0.50
6, 36, 54, 55, 58, 61
>150
0.23
0.09
0.12
0.49
1, 6, 20, 40, 53, 61,
67, 77, 79
Oak forest
>70
0.35
0.25
0.20
1.16
15, 60, 64, 67
Eucalypt plantation
<50
0.45
0.15
0.29
0.81
9, 51, 59
Eucalypt plantation
50-150
0.35
0.23
0.15
0.81
4, 9, 59, 66, 76
Eucalypt forest/plantation
>150
0.20
0.08
0.10
0.33
4, 9, 16, 66
Other broadleaf forest
<75
0.43
0.24
0.12
0.93
30, 45, 46, 62
Vegetation type
Tropical/subtropical
forest
Conifer
forest/
plantation
Temperate
broadleaf
forest/
plantation
Grassland
Other
Secondary tropical/subtropical forest
References
75-150
0.26
0.10
0.13
0.52
30, 36, 45, 46, 62, 77,
78, 81
>150
0.24
0.05
0.17
0.30
3, 26, 30, 37, 67, 78,
81
Steppe/tundra/prairie
grassland
NS
3.95
2.97
1.92
10.51
50, 56, 70, 72
Temperate/sub-tropical/
tropical grassland
NS
1.58
1.02
0.59
3.11
22, 23, 32, 52
Semi-arid grassland
NS
2.80
1.33
1.43
4.92
17-19, 34
Woodland/savanna
NS
0.48
0.19
0.26
1.01
10-12, 21, 27, 49, 65,
73, 74
Shrubland
NS
2.83
2.04
0.34
6.49
14, 29, 35, 38, 41, 42,
47, 67
Tidal marsh
NS
1.04
0.21
0.74
1.23
24, 39, 68, 80
NS = Not specified
Intergovernmental Panel on Climate Change (IPCC), 2003. Good Practice Guidance for Land
Use, Land-Use Change and Forestry. Published by the Institute for Global Environmental
Strategies (IGES) for the IPCC. <http://www.ipcc-nggip.iges.or.jp>

Proyecto ArBolivia

Transcription

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