SMALL-SCALE TIMBER STAND MANAGEMENT TECHNIQUES: A CASE
STUDY OF WOODLOTS IN ISANGATI, TANZANIA
By
Paul D. Francis
A THESIS
Submitted in partial fulfillment of the requirements for the degree of
MASTER OF SCIENCE
(Forestry)
MICHIGAN TECHNOLOGICAL UNIVERSITY
2012
©2012 Paul D. Francis
This thesis, “Small-Scale Timber Stand Management Techniques: A Case Study of
Woodlots in Isangati, Tanzania,” is hereby approved in partial fulfillment of the
requirements for the Degree of MASTER OF SCIENCE IN FORESTRY.
School of Forest Resources and Environmental Science
Signatures:
Thesis Advisor
__________________________________
Dr. Blair Orr
Dean
__________________________________
Dr. Margaret R. Gale
Date
__________________________________
TABLE OF CONTENTS
LIST OF FIGURES .........................................................................................................v
LIST OF TABLES ....................................................................................................... vii
ACKNOWLEDGEMENTS ............................................................................................ix
ABSTRACT .................................................................................................................... x
CHAPTER 1 INTRODUCTION ..................................................................................... 1
CHAPTER 2 COUNTRY BACKGROUND ....................................................................3
CHAPTER 3 STUDY AREA .......................................................................................... 8
Mbeya region ............................................................................................................8
Isangati ................................................................................................................... 10
Plant species............................................................................................................ 18
CHAPTER 4 METHODS .............................................................................................. 23
Household surveys .................................................................................................. 23
Woodlot sampling methods ..................................................................................... 23
Supplementary surveys............................................................................................ 25
CHAPTER 5 WOODLOT TREE SPECIES................................................................... 27
Eucalyptus spp. ....................................................................................................... 27
E. globulus .............................................................................................................. 28
E. saligna ................................................................................................................ 28
P. patula .................................................................................................................. 29
C. lusitanica ............................................................................................................ 30
CHAPTER 6 DATA ...................................................................................................... 32
iii
CHAPTER 7 RESULTS ................................................................................................ 39
Harvesting ............................................................................................................... 39
Spacing ................................................................................................................... 50
Pruning ................................................................................................................... 52
Thinning ................................................................................................................. 53
Summary of woodlot owners ................................................................................... 55
Thoughts from farmers without woodlots ................................................................ 55
CHAPTER 8 CONCLUSIONS...................................................................................... 57
Management conclusions ........................................................................................ 57
General conclusions ................................................................................................ 58
LITERATURE CITED .................................................................................................. 60
APPENDIX A: COPYRIGHT PERMISSIONS ............................................................. 68
APPENDIX B: INTERVIEW QUESTIONS.................................................................. 70
APPENDIX C: WOODLOT DATA .............................................................................. 74
iv
LIST OF FIGURES
Figure 2.1: Location of Tanzania .....................................................................................3
Figure 2.2: Tanzanian religious affiliations. .....................................................................5
Figure 2.3: Vegetation cover types………………………………………………………..7
Figure 3.1: Mbeya region is located in southwestern Tanzania .........................................8
Figure 3.2: Monthly mean temperatures…………………………………………………10
Figure 3.3: The village of Isangati……………………………………………………….11
Figure 3.4: Location of Isangati within the Mbeya region .............................................. 12
Figure 3.5: Children helping with family chores ............................................................ 13
Figure 3.6: Mean annual rainfall………………………………………………………....14
Figure 3.7: Farming on a slope ...................................................................................... 15
Figure 3.8: Farming with the entire family……………………………………………....16
Figure 3.9: Young boy feeding stall fed cows ................................................................ 17
Figure 3:10: Farms on steep hillsides. ............................................................................ 17
Figure 3.11: E. globulus coppicing from a cut stump ..................................................... 21
Figure 4.1: Measuring tree spacing ................................................................................ 25
Figure 4.2: Discussing and sharing ideas about woodlots ............................................... 26
Figure 5.1: E. globulus sapling in farmer’s woodlot ....................................................... 28
Figure 5.2: Young E. saligna in an un-weeded woodlot ................................................. 29
Figure 5.3: Two year old P. patula in a farmer’s woodlot .............................................. 30
Figure 5.4: C. lusitanica in a farmer’s woodlot .............................................................. 31
Figure 6.1: Luwole: Woodlot 4 ...................................................................................... 34
v
Figure 6.2: Yisega: Woodlot 1 ....................................................................................... 35
Figure 6.3: Jim Roger: Woodlot 1 .................................................................................. 36
Figure 6.4: Elias: Woodlot 1 .......................................................................................... 37
Figure 6.5: Amoni: Woodlot 1 ....................................................................................... 38
Figure 7.1: Pit-sawing.................................................................................................... 41
Figure 7.2: Machine sawing ........................................................................................... 42
Figure 7.3: Effect of spacing on standing volume of 19 year old P. patula and C.
lusitanica at Rongai, Northern Tanzania. ......................................................51
Figure 7.4: Pruning over 60% of the tree crown ............................................................. 52
Figure 7.5: Volume increment after pruning in a 3.5 year old plantation of P. patula in
Columbia .....................................................................................................53
vi
LIST OF TABLES
Table 3.1: Field observations of common trees, shrubs, and grasses in Isangati. ............. 19
Table 3.2: Field observations of plant species consumed, used or sold in Isangati. ......... 20
Table 6.1: Data from woodlots owned by Matei. ............................................................ 32
Table 6.2: Data from woodlots owned by Luwole. ......................................................... 33
Table 6.3: Data from the woodlot owned by Yisega. ...................................................... 34
Table 6.4: Data from woodlots owned by Jim Roger. ..................................................... 35
Table 6.5: Data from woodlots owned by Elias. ............................................................. 37
Table 6.6: Data from woodlots owned by Amoni. .......................................................... 38
Table 7.1: The average age of trees in woodlots. ............................................................ 39
Table 7.2: Two 10-year rotations of pine at a discount rate of 8%. ................................. 44
Table 7.3: Two 10-year rotations of pine at a discount rate of 12%.. .............................. 45
Table 7.4: One 20-year rotation of pine at a discount rate of 8%.. .................................. 45
Table 7.5: One 20-year rotation of pine at a discount rate of 12%. ................................. 46
Table 7.6: Two 8-year rotations of eucalypts at a discount rate of 8%.. .......................... 46
Table 7.7: Two 8-year rotations of eucalypts at a discount rate of 12%. ......................... 47
Table 7.8: One 16-year rotation of eucalypts at a discount rate of 8%.. .......................... 47
Table 7.9: One 16-year rotation of eucalypts at a discount rate of 12%.. ........................ 48
Table 7.10: Two 10-year pine rotations compared to one 20-year pine rotation and two
8-year eucalypt rotations compared to one 16-year eucalypt rotation. .......... 49
Table 7.11: The average tree spacing figures for each of the farmers’ woodlots.
Recommended tree spacing is 2.5m. ........................................................... 51
vii
Table 7.12: Stems per hectare in each of the farmers’ woodlots. Initial stocking should be
1111-1372 stems/ha. ................................................................................... 54
Table 8.1: Summary of woodlot management techniques and recommendations. ........... 57
viii
ACKNOWLEDGEMENTS
First and foremost I would like to thank my advisor and committee member Blair
Orr. Without his tireless effort and direction none of this would have been possible.
Thanks to my other committee members Catherine Tarasoff and Gary Campbell for their
support.
I want to thank everyone in Tanzania who helped me out along the way. Noah
Mpunga, Sophy Machaga, and Omary at the Southern Highlands Conservation
Programme in Mbeya, all of the foresters at the Natural Resource office in Mbeya for
supporting my research, the great Peace Corps Tanzania staff, especially the Associate
Peace Corps Director for the environment program Eligard Dawson and Country Director
Andrea Wojnar-Diagne, as well as David Tye and Andrew Zacharias at Trees for the
Future.
I am forever indebted to all of the farmers of Isangati who helped me throughout
my research. Special thanks to Matei, Luwole, Yisega, Jim Roger, Elias, Amoni,
Msaropa, and Boto.
Thanks to all of the wonderful people that I met while working with the Student
Conservation Association and thank you for sparking my interest in forestry. Bil Grauel
your encouragement and guidance made it easy for me to choose my future career and
academic plans. Kyle Earnshaw your sarcasm and humor made it a bit easier to survive
the U.P.
Last but certainly not least I would like to thank my family. Many thanks to my
wonderful wife Jenna Francis who I met and married while in Tanzania. She contributed
greatly to my research by helping me take photos, collect data at the woodlots, and
translate questionnaires. A lot of love to my mom, brothers, sisters, nieces, nephews,
grandparents, aunts and uncles. Most importantly, this is dedicated to my dad who passed
away during my first semester of graduate school. He is the one that taught me about
determination and was always my biggest supporter in any endeavor that I chose to
pursue.
Thanks everyone, it was a fun ride. But it is only just beginning.
ix
ABSTRACT
Small-scale village woodlots of less than 0.5ha are the preferred use of land for
local farmers with extra land in the village of Isangati, a small community located in the
southern highlands of Tanzania. Farmers view woodlots as lucrative investments that do
not involve intensive labor or time. The climate is ideal for the types of trees grown and
the risks are minimal with no serious threats from insects, fires, thieves, or grazing
livestock. It was hypothesized that small-scale village woodlot owners were not
maximizing timber outputs with their current timber stand management and harvesting
techniques. Personal interviews were conducted over a five month period and field data
was collected at each farmer’s woodlots over a seven month period. Woodlot field data
included woodlot size, number of trees, tree species, tree height, dbh, age, and spacing.
The results indicated that the lack of proper woodlot management techniques results in
failure to fully capitalize on the investment of woodlots. While farmers should continue
with their current harvesting rotations, some of the reasons for not maximizing tree
growth include close spacing (2m x 2m), no tree thinning, extreme pruning (60% of tree),
and little to no weeding. Through education and hands-on woodlot management
workshops, the farmers could increase their timber output and value of woodlots.
x
CHAPTER 1 INTRODUCTION
Small-scale tree planting initiatives have been present in Tanzania for decades.
These initiatives were established to benefit the environment and increase household
income through the sale of timber from individual woodlots. The villagers of the
mountainous southern highlands in Tanzania and more specifically the villagers of
Isangati have grasped this idea. They understand the environmental and financial benefits
of planting trees.
After arriving at my Peace Corps site of Isangati in the Mbeya region of
Tanzania, I was shocked by the lush green landscape and cool foggy mornings. Once I
settled down at my new site, I began to talk with farmers about their land and many
invited me to farm with them as their kibarua (laborer). Walking through the trails out to
the farmer’s land I saw people not only planting crops but also planting trees. As a
forester, I was excited to see they were planting trees through their own initiative; they
were thinking “outside of the box” by not just planting crops. They were thinking about
the future. They would use these trees as a form of a living bank. The sales of the trees
would help fund their children’s education, and some of the wood would be used as fuel
to cook their meals.
The first time I visited a farmer’s woodlot I found myself trapped in a thick maze
of tightly spaced trees. This helped me realize that maybe their woodlot management
techniques could use some work.
Before leaving for the Peace Corps, I remembered reading journal articles about
how small-scale tree farmers in many parts of the world are willing to plant trees but the
education component is missing. I began to wonder if the same was true for woodlot
owners in the village of Isangati.
The purpose of this study was to determine if small-scale woodlot owners are
maximizing timber outputs based on their current timber stand management and
harvesting techniques.
Chapter two describes the country of Tanzania. Country background information
includes history, people, economy, and environment.
1
Chapter three consists of three sections: Mbeya region, Isangati, and plant species.
The first section covers the broad study area of the Mbeya region. Mbeya region statistics
that are presented include location, economy, people, environment and climate. The
Isangati section focuses on the specific study area of the village. Village life involving
work, leisure, and the local environment are discussed. The final section of the chapter
discusses the local plant species planted around homes and in farms.
Chapter four explains the qualitative and quantitative methods used for gathering
and analyzing information concerning woodlot management.
Chapter five mentions the common tree species that are found in village woodlots.
Each tree species taxonomy and recommended management techniques are presented in
detail.
Chapter six presents the data gathered in the field from six farmer’s woodlots,
presented individually.
Chapter seven discusses the results of the woodlot study. The four main issues
discussed in the results section include tree harvesting, spacing, thinning and pruning.
Current farmer woodlot management techniques, recommendations and the difference
between management techniques and recommendations are discussed with each of the
four main issues.
Chapter eight finishes with conclusions that are based on the provided results.
2
CHAPTER 2 COUNTRY BACKGROUND
Tanzania is located in East Africa along the Indian Ocean (Figure 2.1). The
bordering countries are Kenya, Uganda, Rwanda, Burundi, Democratic Republic of
Congo, Zambia, Malawi, and Mozambique. The country consists of a mainland as well as
the three islands of Mafia, Pemba, and Zanzibar, totaling 587,249 square kilometers
(Tanzania Embassy 2011). There are a total of 26 regions, 21 on the mainland, three on
Zanzibar and two on Pemba. The continental terrain consists of the central plateau,
northern and southern highlands, the plains along the coast, and the Great Rift Valley cuts
through the middle of the country. The lowest point in elevation is the Indian Ocean at
sea level and the highest is Mt. Kilimanjaro at 5,895 meters, which is the highest point on
the African continent (Central Intelligence Agency 2011).
Figure 2.1: Location of Tanzania.
Source: Central Intelligence Agency 2011 (See Appendix A for documentation that this
material is in the public domain).
3
Millions of years after the early humans roamed this part of Africa, the
Portuguese explorer Vasco de Gama, in 1498, became the first European to reach and
control the coast of Tanzania (Tanzania Embassy 2011). By the middle 1880s, the
German Carl Peters began exploring the area and helped to establish the colony of
German East Africa (Perras 2004). After the First World War, the German rule came to
an end and the colony was renamed Tanganyika. The League of Nations gave
Tanganyika to the British as a mandate (U.S. Department of State 2011). Tanganyika
eventually gained independence from the United Kingdom on December 9, 1961.
Tanganyika merged with Zanzibar on April 26, 1964 to become the United Republic of
Tanzania (Hyden 1980). Julius K. Nyerere, the father of the nation (Baba wa taifa),
became the first political leader of Tanzania and initiated the socialist ideology of
Ujamaa (familyhood). Ujamaa was based on communal living and co-operative
agriculture (Wily and Dewees 2001). Nyerere and his political party Chama Cha
Mapinduzi (Revolutionary State Party) ruled the country until his retirement in 1985.
Since Nyerere, there have been three other Presidents of Tanzania including the current
President, Jakaya Kikwete.
The population of Tanzania is 44.8 million with 3.3 million people living in the
commercial capital of Dar es Salaam (World Bank 2011). The national language is
Kiswahili, however English is an official language that is used for commerce,
administration and secondary and higher education. There are estimated to be more than
120 ethnic groups (U.S. Department of State 2011) and 156 languages spoken with the
most common languages being Sukuma, Kiswahili, Ha, Gogo, Nyamwezi and Haya
(Muzale and Rugemalira 2008). Throughout Tanzania, 99% of the people are of African
descent while the other 1% are of Asian, European or Arab descent (Central Intelligence
Agency 2011). Christian, Muslim, and traditional African religions are the primary
religions within Tanzania (Figure 2.2). The Muslim religion dominates Zanzibar and
coastal Tanzania, with over 99% of Zanzibari’s being Muslim (Fujii 2010). The farther
one travels inland from the coast the more Christianity and traditional African beliefs
become the dominant religions.
4
70
Percent of Population
60
50
40
30
20
10
0
Christian
Muslim
Traditional African
Religions
Other
Figure 2.2: Tanzanian religious affiliations.
Data Source: The Pew Forum 2010
Life expectancy for males is 56 years and for females is 57 years of age (World
Bank 2011). The major infectious diseases include bacterial diarrhea, hepatitis A, typhoid
fever, malaria, and schistosomiasis (Central Intelligence Agency 2011). Malaria is the
primary cause of death among children under the age of five and overall is the third
leading cause of death in the country (World Health Organization 2002). However, the
prevalence of malaria has decreased over the past years with the increased use of
mosquito nets. The Tanzanian government and local nongovernmental organizations
(NGOs) have played a major role in the distribution of mosquito nets and malaria
education. Similar to many countries in Africa, the leading cause of death in Tanzania is
human immunodeficiency virus (HIV) / acquired immunodeficiency syndrome (AIDS).
The HIV adult prevalence rate is 5.6%, with 1.4 million Tanzanians living with
HIV/AIDS (Central Intelligence Agency 2011). Through community action, education,
and government support the HIV prevalence rate has been declining since 2003 (World
Health Organization 2011).
5
Per capita income is around 1,400USD, with 57.8% of the population earning less
than 1USD per day (World Health Organization 2011). The country’s annual gross
domestic product (GDP) growth rate has been around 7% since 2000, which is
attributable to large gold deposits and world class tourist sites (Central Intelligence
Agency 2011). The industrial sector accounts for 22.6% of the GDP, with most industry
located in the commercial capital of Dar es Salaam (U.S. Department of State 2011). The
majority of the industrial sector consists of food processing, fruits and vegetables
preservation, textiles production, wood production and gold, diamond and tanzanite
mining (U.S. Department of State 2011). In 2010 Tanzania was ranked fourth in gold
production throughout Africa (Mutarubukwa 2010). Along with gold, Tanzania also
mines diamonds, salt, gypsum, gemstones, iron ore, natural gas, phosphate, coal, nickel,
cobalt, and tanzanite (Kitula 2006). The only part of the world in which tanzanite is
found is in northern Tanzania (Schroeder 2010). With rich biodiversity, Tanzania ranks
fifth in Africa for income earned through tourism (Wade et al. 1999). The country boasts
some of the finest natural wonders of the world including Mt. Kilimanjaro, Ngorongoro
Crater, Serengeti Plains, and the pristine beaches of Zanzibar.
Agriculture contributes about 28% to the GDP annually (World Bank 2011), and
85% to exports, while employing 80% of the labor force (Central Intelligence Agency
2011). Export cash crops include coffee, tea, cotton, cashews, sisal, cloves, and
pyrethrum (U.S. Department of State 2011). The most relied upon crops for both
commercial and subsistence use are maize and rice, grown by over 50% of Tanzanian
farmers (Maliyamkono and Bagachwa 1990).
The central plateau is the driest part of Tanzania receiving on average 550mm of
rainfall annually and is characterized by grasslands, arable land, and miombo woodlands
(Shayo 1997). The miombo woodlands are the largest vegetation type in East Africa, and
encompass 40% of the landscape in Tanzania (Sunseri 2009). The woodlands are found
between 300-1300m in elevation (Rodgers 1996) and contain over 175 tree species, with
the majority of trees belonging to the families Caesalpiniaceae and Papilionaceae
(Malimbwi et al. 1994). The northern highlands are dominated by the two inactive
volcanoes of Mt. Meru and Mt. Kilimanjaro. Montane forests are found in the higher
6
elevations while grasslands and bushlands dominate the lowlands. The coastal plains are
hot and humid with mangroves and extensive mosaic forests (Rodgers et al. 1992).
Major vegetation cover types include forest, woodland, cultivated land, bushland and
grassland (Figure 2.3).
In the mountainous southern highlands the elevation ranges between 400-3000m
and the area receives an annual rainfall of between 750-3000mm (Bisanda et al. 1998).
Grasslands in the lowlands and montane rain forests in the highlands characterize the area
with a wide range of temperatures depending on elevation. The Mbeya region, as well as
the study site of Isangati, are both located in this mountainous expanse.
Forest Cover
3%
Open Land
2%
Cultivated
Land
11%
Grassland
22%
Woodland
42%
Bushland
20%
Figure 2.3: Vegetation cover types.
Data Source: United Republic of Tanzania 1997
7
CHAPTER 3 STUDY AREA
Mbeya region
The Mbeya region is located in southwest Tanzania and shares borders with
Zambia and Malawi (Figure 3.1). The region covers 60,000 km² which is approximately
15% of the area of the entire mainland of the country (Tanzania in Figures 2010). The
region is divided into seven administrative districts. The districts are separated into 25
divisions with 135 wards and 577 villages (Mbeya Region 1997).
Relatively old data sources are used throughout this section because current data
is not available. The Mbeya region, as well as many regions throughout the developing
world, do not have the resources available to allocate towards regional census and data
collection. However, the available, although dated information represents a reasonable
picture of the region as a whole.
Figure 3.1: Mbeya region is located in southwestern Tanzania.
Data Source: GoogleMap (See Appendix A for documentation of
permission to republish this material).
8
The GDP of the Mbeya region contributed 5.7% to the National GDP in 1993
(Mbeya Region 1997). Similar to many areas in Tanzania, 80% of the population in the
Mbeya region depends on agriculture for food production and income (Mbeya Region
1997). The people produce surplus foods such as maize, paddy, beans, potatoes, pulses,
and green vegetables, as well as cash crops such as coffee, tea, pyrethrum, cotton,
cardamom, sunflower, cocoa and tobacco (Mbeya Region 1997).
The population of the region in 2002 was around 2 million people and was
projected to reach 2.7 million in 2010 (Tanzania in Figures 2010). The main ethnic
groups are Nyakyusa, Safwa, Malila, Sangu, Nyika, Nyamwanga, Ndali, and Bunguu
(Mbeya Region 1997). The Masai, Sukuma, and Chagga ethnic groups have begun to
migrate to Mbeya in search of more available land.
The topography of the Mbeya region has been created by rift faulting. The
faulting formed the Poroto Mountains as well as the Njombe and Rungwe volcanoes
which are between 2500-3000m in elevation (Karlsson 1982). Evergreen forests and
mountain bamboo thrive in the moist highlands which can receive up to 2600mm of rain
annually (Mbeya Region 1997). The volcanic activity in this area has produced fertile
soils in the highlands that make for productive farming. Crops planted in the highlands
include maize, beans, wheat, potatoes, coffee, bananas, tea, cocoa and pyrethrum. The
lower elevations of the Usangu Plains are between 500-1000m in elevation and receive
less than 1000mm of rainfall annually (Mbeya Region 1997). The warmer temperatures
and lack of rain make the lowlands an ideal environment for grasslands, bushlands, and
miombo woodlands. Crops planted in the lowland area are tobacco, maize, sorghum,
finger millet, cassava, groundnuts, cocoa, cashews, and bananas.
The climate varies depending on relief and altitude. Overall the temperatures can
range from 5ºC to 26ºC (Figure 3.2), (Igbadun et al. 2006). June through September tend
to be the drier and cooler months of the year. The short rains typically begin in November
and last until January while the long rains start in March and last until May.
9
Monthly Mean Temps (ºC)
30
25
20
15
Max
Min
10
Avg
5
0
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Months (1975-1990)
Figure 3.2: Monthly mean temperatures 1975-1990 from the Mbeya Weather Station.
Data Source: Igbadun et al. 2006
Isangati
Isangati is a village within the Mbeya rural district of the Mbeya region (Figure
3.3). The village is located between Mbalizi and Rungwe about 30km from Mbeya town
(Figure 3.4). It was founded in 1975 by the first village chairman, Mr. Aloni Kaseka
Mwambyalo. The village is 4km² containing 4 subvillages, with a total of around 200
households and a population of 800-1100 people. The population and household statistics
are based on rough estimates gathered through field observation, discussions with
villagers, and household surveys.
10
Figure 3.3: The village of Isangati.
Photo: Paul Francis
The people are of either Malila or Safwa ethnic background, with Kimalila and
Kisafwa being the tribal languages spoken. As a result of the influence of early
missionaries near the area, the villagers are Roman Catholic, Baptist, or Pentecostal with
a minority following traditional African religious beliefs.
There is one dispensary located in the village with three nurses and one doctor.
Common diseases or sicknesses affecting people are diarrhea, acute respiratory tract
infection, pneumonia, malaria, various skin infections, intestinal worms, and HIV/AIDS.
Villagers are not as affected by malnutrition as much as in other parts of
Tanzania; year round farming produces ample crops. Their staple diet consists of ugali,
beans, leafy greens and fruit. Ugali is made from maize flour and is a thick porridge of
dough like consistency. Ugali is typically served with a bean sauce and a side of leafy
greens, avocado, or sour milk.
11
© 2011 Google –Map data © 2011
Figure 3.4: Location of Isangati within the Mbeya region.
Source: GoogleMap (See Appendix A for documentation of permission to republish this
material).
Children are a critical part of the household structure and farming system (Figure
3.5). Girls help by going to the river to fetch water, collecting fuel-wood, farming,
cooking, and washing dishes and clothes. Boys help to take care of livestock and the
farms. From an early age, all children learn how to farm. They learn by observing and
accompanying their families at the farm and from farming activities at school.
12
Figure 3.5: Children helping with family chores.
Photo: Paul Francis
There are no primary or secondary schools located in Isangati. Primary school
students must either walk 1.5km to Madugu or 2km to Isangati (not in the village) if they
wish to attend primary school. The closest secondary school is 10km away in Iyunga
Mapinduzi. The major reasons why the youth in the village would not attend school are
either pregnancy, parents did not attend school, mental illness, or too much work at
home. Costs for children to attend primary school are for a school uniform which is
approximately 19,000 Tanzanian shillings (TZS) (1USD = 1,450-1,750 TZS in 2011).
The costs for secondary school students are similar but they must also pay for school
tuition.
Isangati is located between 2,000-2,100m in elevation, with an average rainfall of
1,500-2,700mm per year (plus mist effect) and an average annual temperature between
12º-21ºC (Mbeya District 1997). The mist effect consists of frequent morning mist
throughout nine or ten months of the year. The closest weather gauge to Isangati is
located at the Rungwe Tea Estate (Figure 3.6). Rungwe is approximately 30km southeast
of Isangati.
13
250
Mean Rainfall mm
200
150
100
50
0
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
Years
Figure 3.6: Mean annual rainfall, Rungwe Tea Estate, 1999-2008.
Data Source: Rainfall Data 1999-2008.
The weather and environment are ideal for farming with plenty of rain and rich
volcanic soils. Unlike many parts of Tanzania or the world, villagers in Isangati cultivate
crops year round and harvest maize twice a year. According to soil samples from nearby
areas (Karlsson 1982, Mashalla 1988, Mbeya District 1997) and from field observations,
it would be an educated guess to conclude that the soils are of volcanic origin, often
mollic andisols. The soil is typically well drained with dark brown topsoil and reddish
subsoil. Texture varies from sandy loams to loamy sands.
Farming is the main source of income for villagers. The primary food crops
grown in the village include maize, beans, potatoes, green peas, various leafy greens and
cabbage, with pyrethrum being grown as a cash crop. The only tool used for farming is a
jembe (hand-hoe). Tractors and draught power are not advantageous for farmers to use
because of the small-scale landholdings and hilly topography (Figure 3.7).
14
Figure 3.7: Farming on a slope.
Photo: Paul Francis
Farming is the main source of income for families but other sources of income are
utilized throughout the year. The only people in the village who do not make most of
their money from farming are the nurses and carpenters. The nurses are paid by the
government and the carpenters engage in building construction projects in the village or
make furniture. Village men can earn money by selling meat, livestock, and timber, or
make money from skilled trades such as tailoring clothes, shoe repair, and tool making.
Women also earn an income by selling surplus maize, beans, cabbage, leafy greens, milk,
and eggs, or by cooking food to sell during market day. On market day, women also sell
housewares, soda, beer, rice, fruits and vegetables that were purchased and brought in
from outside the village. Market day is held every Saturday, and this is when villagers
and people from surrounding villages or town come to buy and sell goods. Market day is
the busiest day in the village; it is similar to a party atmosphere with thousands of people.
People not only come to buy and sell goods but they also come to talk with friends, listen
to music, watch generator-powered television, get their hair cut, drink beer or pombe, or
eat chipsi and meat.
The farming system used by farmers in the area is a small-scale mixed farming
system. According to Beets the mixed farming system is “the most sound system and the
most sustainable” (Beets 1990). Refer to the media packet to view a detailed farm system
diagram of Isangati. Farms are acquired through inheritances, bought from farmers, or
leased by relatives. Farmers feel secure with their landholdings and because of this are
willing to invest in their land (Dejene et al. 1997, Gebremedhin and Swinton 2003,
15
Nyangena 2008). The land tenure system in Tanzania is based on three primary
principles; “all land in Tanzania is public land, the power of control and administration is
vested in the President on behalf of all citizens, and the right of occupancy, whether
granted or deemed, is the primary mode of access to and use of land in Tanzania”
(Dejene et al. 1997). In most rural areas, land is not sold through the law, but through
more informal channels such as verbal or written agreements between community
members (Vincent and Kihiyo 1996).
Figure 3.8: Farming with the entire family.
Photo: Paul Francis
Family members involved in farming typically include any family member
capable of the task, regardless of age (Figure 3.8).
Livestock are kept as a supplemental income for households. On average, families
have five chickens and the wealthier families also have two head of cattle, two goats and
possibly one pig. Larger livestock such as cattle are stall fed by using a cut and carry
system of feeding (Figure 3.9). The farmer collects grass from a nearby location, fills the
bag with grass, and carries it back to the homestead to feed the cattle.
The primary environmental problems in the area are soil erosion and
deforestation. There have been rare cases of severe flooding during El Nino season when
farmers’ potatoes have been washed down the mountain side onto other farmers’ fields at
the base of the mountain. Soil erosion is a severe environmental problem because the
majority of the farms are on steep hill sides (Figure 3.10). The ground is left bare or with
little ground cover during many months of the year, so it is easy for the soil to wash
16
away. Some farmers plant grasses on the contours to slow erosion and a few farmers
plant trees to reduce erosion.
Figure 3.9: Young boy feeding stall fed cows.
Photo: Paul Francis
Figure 3.10: Farms on steep hillsides.
Photo: Paul Francis
17
With the large demand for wood, villagers must search for wood and many end up
illegally cutting trees from the nearby forest reserve. Wood is used for numerous aspects
of life such as for cooking, building, making furniture, and making tools. With an
increasing population and deforestation, finding wood may be critical in the future
(Mashalla 1988). To combat this problem many villagers have opted to plant woodlots.
Woodlots are an area of land set aside by an individual farmer for the purpose of planting
trees, in order to harvest timber, building materials or fuelwood (Van Gelder and
O’Keefe 1995). Around half of the villagers own a woodlot. The average individual
woodlot size is 0.25ha, with woodlot owners typically owning three woodlots. Woodlots
are a vital soil and water conservation strategy as well as a critical source of woody
biomass and household income (Jagger et al. 2005). Woodlots also enhance the landscape
aesthetically and help to preserve biodiversity by supplying habitat for plants and small
animals (Holding and Roshetko 2003). This trend is increasing throughout Tanzania,
with 70,000ha of total area being used for tree farms in the 1970’s, and 150,000ha in the
1990’s (URT 2001).
Plant species
Trees and grasses are frequently planted around homes and farms (Table 3.1). It is
common to see fruit trees (Table 3.2), flowering shrubs, and grasses planted around the
homestead. In farms, other trees are also planted which are used for timber, poles, and
fuelwood. Vegetation data was gathered through field observation of the study area.
Unknown plants were verified by a local botanist and previous vegetation research was
consulted (Latham 2006). Villagers shared their insights and helped with the Kimalila
translations for the vegetation.
18
Table 3.1
Field observations of common trees, shrubs, and grasses in Isangati.
Scientific Name
English
Kiswahili
Tree
Acacia mearnsii
Albizia schimperiana
Callistemom citrinus
Cupressus lusitanica
Eucalyptus globulus
Eucalyptus saligna
Euphorbia bussei
Grevillea robusta
Hagenia abyssinica
Leucaena leucocephala
Mangifera indica
Morus alba
Musa sapientum
Persea americana
Pinus patula
Prunus persica
Cordia africana
Black wattle
Muwati
Long-pod albizia
Mruka
Bottlebrush tree
Mexican cypress
Mkambokambo
Tasmanian blue gum Mkaratusi mweupe
Sydney blue gum
Mkaratusi laini
Grevillea
Mgrivea
Hagenia
Mturunga
Leucaena
Mlusina
Mango
Mwembe
Mulberry
Mfurusadi
Sweet banana
Ndizi
Avacado
Mparachichi
Mexican weeping pine Msindano
Peach
Pindigesi
Large leafed cordia
Makobokobo
Naluyami
Intanga
Ilongoti
Ilongoti
Ilangale
Iliuguti
Membe
Igawo li ntonki
Itakapera
Mafurisi
-
Shrub
Arundinaria alpinia
Datura suaveolens
Latana camara
Mountain bamboo
Angels trumpet
Latana
Mianzi
-
Malanzi
Ipopoti
-
Grass
Pennisetum purpureum
Saccharum officinarum
Tripsacum andersonii
Cynodon dactylon
Elephant grass
Sugar cane
Guatemala grass
Bermuda grass
Muwa
-
-
19
Kimalila
Table 3.2
Field observations of plant species consumed, used or sold in Isangati.
Scientific Name
English
Kiswahili
Kimalila
Food Derived from Trees
Mangifera indica
Morus alba
Musa sapientum
Mango
Mulberry
Sweet banana
Mwembe
Mfurusadi
Ndizi
Persea americana
Prunus persica
Passiflora edulis
Chrysophyllum magalismontanum
Prunus domestica
-
Avacado
Peach
Passion Fruit
Wild Plum
Plum
-
Mparachichi
Pindigesi
Matunda Damu
Pindigesi
-
Membe
Igawo li
ntonki
Itakapera
Mafurisi
Ipohola
Mafurisi
Maswiza
Vegetables and Others
Phaseolus vulgaris
Brassica oleracea
Pisum sativum
Zea mays
Cucurbita spp.
Helianthus annuus
Lycopersicon esculentum
Amaranthus spp.
-
Beans
Cabbage
Field pea
Maize
Pumpkin
Sunflower
Tomatoes
Amaranth
-
Maharage
Kabichi
Njegere
Mahindi
Boga
Alizeti
Nyanya
Mchica
Sungwe
Fagili
Imbonzo
Ikabiki
Isyababa
Amangagu
Iliungu
Abangayeye
Inyanya
Inzembwe
Insungwe
Igagala
Roots and Tubers
Solanum tuberosum
Ipomoea batatas
Colocasia esculenta
Irish Potatoes
Sweet Potatoes
Taro
Viazi Viringo
Viazi Vitamu
Mjimbi
Intofwanya
Imbatata
Isimbi
Non-Food Plants
Tanacetum cinerariifolium
Pyrethrum
Pareto
Amaua
20
The most common fruit tree species or shrub species found around homesteads
include Callistemom citrinus, Mangifera indica, Morus alba, Musa sapientum, Persea
americana and Datura suaveolens. Fruit trees and shrubs are planted around the
homestead so the family has easy access to the fruits. Shrubs, such as Datura suaveolens,
make quality fences. Pennisetum purpureum is typically planted around the homestead or
in the farm. It is planted close to the homestead to provide easy access for animal fodder.
It is planted in the farm to serve two purposes, the deep wide roots of the grass serve as a
good soil erosion control and the grass is harvested to feed cattle. Indigenous trees and
shrubs found throughout the village include Albizia schimperiana, Euphorbia bussei, and
Arundinaria alpina. Introduced shrubs found throughout the village include Latana
camara, and Prunus persica. The most common trees planted in woodlots are Eucalyptus
spp., Pinus patula, and Cupressus lusitanica. These trees are sometimes mixed in with
crops but are planted predominately in defined woodlots. Villagers prefer to plant these
trees in their woodlots because they are all fast growing trees. The extra benefit of
planting Eucalyptus spp. is that it is a coppicing tree (Figure 3.11). Coppicing is when
new tree shoots emerge from a cut stump producing three to four repeated harvests from
a single planting (Evans and Turnbull 2004).
Figure 3.11: E. globulus coppicing from a cut stump.
Photo: Paul Francis
21
Farmers have established woodlots for different reasons. They have started
woodlots to help fund their children’s education, have savings for later, protect land from
soil erosion, add nutrients to the soil, have easy access to fuelwood, for building material
and timber. The primary reason farmers have planted woodlots is to gain an income
source other than farming. To understand if farmers are maximizing their timber output,
it is important to take a critical look at their woodlot management techniques.
22
CHAPTER 4 METHODS
To gain an inside perspective on woodlot management among farmers in Isangati,
it is essential to understand their reasoning behind their management techniques.
Quantitative and qualitative data were gathered about the woodlot management system.
The qualitative data was gathered through household surveys and discussions with
woodlot owners while the quantitative data was collected through woodlot field
assessments.
Household surveys
Survey field data was collected through interviews from February 2011 to July
2011. The interview questions were approved by the Michigan Technological University
Institutional Review Board (IRB No. M0653). Consent was given by each farmer to use
their names and photos. Using structured questions (Bernard 1995), six woodlot owners
were surveyed. The survey consisted of 20 open-ended questions focused primarily on
woodlot management, marketing of woodlot products and reasons for owning a woodlot
(complete survey is shown in Appendix B).
Woodlot sampling methods
Woodlot field data was collected from December 2010 to July 2011. First, the
initial assessment of the woodlots was conducted with each of the farmers on site. During
this time, several broad questions were asked about the woodlot and the length and width
of the woodlot were measured. The length and width dimensions of the woodlot were
then entered into an excel spreadsheet to gather the tree sampling interval data. This
spreadsheet was created to ensure that random tree samples were gathered throughout the
woodlot. The excel spreadsheet calculated a random starting point and sampling interval.
Once the tree sampling interval data was calculated, a date was scheduled with the
farmer to go back out to the woodlot to gather further information and individual tree
data. At the woodlot, a handheld Garmin 72H Global Positioning System (GPS) (Garmin
Ltd., Olathe, Kansas) was used to calculate elevation, aspect, and latitude and longitude.
23
After the data using the GPS was collected, the individual tree data was gathered.
The first tree counted, but not necessarily measured, was the tree that was closest to the
point of entering the woodlot. If for example, the excel spreadsheet showed to start at tree
two and count at an interval of 11, then the second tree that was counted was the first tree
measured. Subsequently, each 11th tree was sampled. Also, the direction in which the
trees were counted differed in each woodlot. Once in the woodlot, it was determined
which direction would be taken while counting the trees, depending on how the farmer
planted the trees. The data collected for each sampled tree was tree species, diameter at
bread height (dbh), height, age, and distance from other trees.
The dbh (1.3m above ground level) was gathered for each sample tree. Exceptions
occurred when trees grew from a coppice stump (i.e. Eucalyptus spp.) each tree’s dbh and
heights were measured at the point that it came off the stump and not at the bottom of the
stump. Also, if a stump was higher than 1.3m, coppice sprouts coming off it were
counted as one tree and measured as a typical tree, not individually. If a tree was recently
planted by the farmer, it was counted as a tree even if it was less than one inch dbh, but if
it was coming off of a stump and less than one inch dbh, it was not counted as a tree. This
was done to eliminate counting 30 or more small (<1 inch dbh) coppice sprouts coming
off of a single stump. Tree height was calculated using the ocular estimate method
(Husch et al. 1982). Tree age was discussed with the farmer during the initial assessment
of the woodlot. Woodlot owners typically plant the entire or at least half of the woodlot
in the same year. The last measurement taken was tree spacing. A tape measure was held
at the sample tree and walked out three meters. Every tree planted within the three meter
radius was counted and the distance from each tree to the sample tree was documented
(Figure 4.1).
24
Figure 4.1: Measuring tree spacing.
Photo: Paul Francis
Every tree in the woodlots was counted by hand. If the grass was over 1 meter tall
in the woodlots, then small seedlings may have been missed. Pictures were taken of
selected measured sample trees.
Supplementary surveys
After the primary survey was conducted with all of the woodlot owners, followup questions were then conducted. An informal discussion with the woodlot owners was
facilitated on April 19, 2011 to help gain a better insight on the woodlot process and to
see if the owners agreed with the data that had been gathered (complete survey is shown
in Appendix B). An informal discussion with farmers without woodlots was held on May
17, 2011 to determine why people decide not to own woodlots (complete survey is shown
in Appendix B). Informal questions and discussions were used throughout the entire
research process (Figure 4.2).
Tree species, woodlot data, reasons for owning a woodlot, and management
techniques were studied to determine the woodlot system in its entirety.
25
Figure 4.2: Discussing and sharing ideas about woodlots.
Photo: Jenna Francis (See Appendix A for documentation of permission to use this
material).
26
CHAPTER 5 WOODLOT TREE SPECIES
Woodlot trees are typically planted on a plot of land where a farmer previously
had grown crops. When the soil is exhausted from cropping, the farmers turn the area into
a woodlot. Farmers plant fast growing exotic tree species that grow well in the southern
highlands climatic zone. The three most common trees found in the woodlots are
Eucalyptus spp., P. patula and C. lusitanica.
Eucalyptus spp.
Eucalypts are an evergreen hardwood tree native to Australia and planted in
tropical and subtropical areas throughout the world (Eldridge et al. 1993). The genus
includes over 800 species, with only 30 species being planted commercially because of
their fast growth and climatic adaptability (Brooker and Kleinig 2001). Eucalypts are
planted for timber, poles, fuelwood, and other wood products by large scale timber
enterprises and small-scale woodlot owners.
The type of management techniques carried out for eucalypts depends on the
species and the final goal after harvest. For timber production, various thinning and
stocking regimes are conducted depending on the owners need. Initial stocking of
eucalypts ranges anywhere from 1330 stems/ha with 4-6 thinnings carried out throughout
a 30 year rotation with about 100 stems/ha remaining just before harvest (The Wattle
Research Institute 1972) to 1111 stems/ha with 3 thinnings carried out throughout an 812 year rotation with about 300 stems/ha before harvest (Jacovelli et al. 2009). Tree
spacing ranges from 2.0 x 2.0m – 2.7 x 2.7m for fuelwood and poles to 2.5 x 2.5m to 3.0
x 3.0m for timber (Kenya Forest Service 2009, Jacovelli et al. 2009). When pruning
eucalypts it is important not to prune more than 25% of the tree crown since over-pruning
could reduce final timber yields (The Wattle Research Institute 1972). Eucalypts should
be weeded after planting.
The two primary species of eucalypts planted by woodlot owners in Isangati are
Eucalyptus globulus and Eucalyptus saligna.
27
E. globulus
E. globulus is native to Australia and Tasmania (Figure 5.1), (Turnbull and Pryor
1983). The tree prefers loams to well drained heavy clays, thrives in mild climates that
are not prone to drought, and an elevation range of sea level to 1,100m (Doughty 2000).
In ideal climates, the tree can reach 75m in height (Turnbull and Pryor 1983) but
typically grows to 55m (Dharani 2002). The bark is grayish and peels in long strips
(Duke 1983). Young leaves are bluish grey, while the mature thin leaves are deep bluegreen growing to about 30cm in length (Dharani 2002). Green buds are top shaped about
12-15mm long with white flowers at the base of the leaf (Duke 1983).
Figure 5.1: E. globulus sapling in farmer’s woodlot.
Photo: Paul Francis
E. saligna
E. saligna grows extensively in New Zealand, Brazil, East Africa, and Hawaii
(Doughty 2000), but is only native to Australia (Figure 5.2), (Turnbull and Pryor 1983).
The tree grows best in regions with annual rainfall ranging from 800-1500m on
moderately fertile loams (Doughty 2000). Typically this tree grows between 40-50m in
height (Turnbull and Pryor 1983) with brownish flaky bark at the base and greenishwhite smooth bark on the upper portion of the tree (Dharani 2002). The mature leaves are
alternate lanceolate shaped (FAO 1979), while the young leaves are shortly stalked
opposite with three or four pairs (Skolmen and Little 1989). Flowering begins at around
28
three to four years old producing yellowish white flowers (Skolmen and Little 1989) with
four to eight flowers in each group (Dharani 2002). The fruit is dark brown, conical
shaped, with four to eight fruits grouped together (Dharani 2002).
Figure 5.2: Young E. saligna in an un-weeded woodlot.
Photo: Paul Francis
P. patula
P. patula is an evergreen conifer commonly known as Mexican weeping pine
because the foliage has a drooping or weeping look (Figure 5.3). P. patula is native to
Mexico and prefers sites with annual rainfall of 1000-2000mm and higher elevations of
1000-3000m (Orwa et al. 2009). It thrives in moist sandy loam soils to sandy clay soils
(Wormald 1975). The tree starts to flower at two to three years of age in many parts of
southern Africa, with the two reproductive periods being January – May and September –
October (Dvorak 1997). The female cone is borne in the upper crown, while the male
remains in the lower crown of the tree (Orwa et al. 2009). The small cones are hard with
dark brown seeds and do not open wide; the yellow male catkins are small tight clusters
(Perry 1991). The needles are 15-22cm long, pale green in color, and are in bundles of
three, sometimes four (Dharani 2002). The bark is rutted at the base with reddish peeling
bark near the top portion of the tree. Many people throughout the world enjoy planting P.
patula primarily because it is a fast growing straight tree with around 40% of the bole
branchless. The tree can grow over 30m in height and when seedlings are planted at 2.4m
spacing, can fully occupy an area after two years (Wormald 1975). Natural regeneration
is uncommon so many people direct sow seeds into nursery beds and then transplant the
29
seedlings to their woodlot or plantation (Wormald 1975). There are many uses for the
tree but the most common are for timber, fuelwood and pulp. The wood is white to
yellowish white with pinkish heartwood and is strong enough for most construction jobs
(Gillespie 1992).
P. patula is grown by major timber companies throughout the world with similar
management techniques. For example, Border Timbers Limited in Zimbabwe harvest
sawlogs every 22 years and prune four times over a 10 year period at heights of 1.5m,
3.5m, and 7m (Border Timbers Limited 2010). Plantations of P. patula in South Africa
are planted at 1370 trees/ha and thinned out on five year intervals until there is a
remaining stock of 300 trees/ha in which the trees are then harvested between 25-30 years
of age (Sabie 2006). Recommended thinning in Tanzania based on a spacing of 2.5m,
starts at age 9.5-11 and consists of four thinnings (Malimbwi et al. 1992b). Although, if
a wider spacing of 3.0m is used no thinning is needed and the stand will still produce
quality saw logs based on a 25 year rotation (Malimbwi 1987). It is also expected that the
area around the trees are weeded two to three times after the first year of planting the
seedlings (Nigro 2008).
Figure 5.3: Two year old P. patula in a farmer’s woodlot.
Photo: Paul Francis
C. lusitanica
C. lusitanica is an evergreen native to North America commonly known as
Mexican cypress (Figure 5.4), (Orwa et al. 2009). The tree favors moist, deep, loamy
soils (Brink 2007) between 1000-4000m in elevation (Orwa et al. 2009). Reaching
30
heights up to 35m, it has a straight trunk with reddish brown bark and widely spread
hanging branches (Dharani 2002). The dull blue-green leaves are decussately opposite
with a simple scale-like texture (Brink 2007). The male cone is small and oblong while
the female cone is even smaller and subglobose (Orwa et al. 2009). Female cones are
1.5cm across and take two years to mature (Brink 2007). Reproduction occurs in the
driest parts of the year (Brink 2007) with the first cone production occurring between six
to nine years of age (Orwa et al. 2009). Male and female cones occur at different sections
of the tree crown and after pollination female cones take two years to produce seeds
(Orwa et al. 2009).
Figure 5.4: C. lusitanica in a farmer’s woodlot.
Photo: Paul Francis
The recommended spacing for C. lusitanica is 2m x 2m or 3m x 3m (Orwa et al.
2009). The trees should be pruned 30% of the stem height, four times before harvest, at
age three, six, nine and 13 (Orwa et al. 2009). Trees should be thinned three to four times
with a final density of 250 trees/ha (Brink 2007). At age four to five years unproductive
trees should be thinned to leave 555 trees/ha, another thinning when trees are 8-12m tall
and the last thinning should occur between 10-14 years of age (Department of Primary
Industries 2011). The harvesting rotation for timber is between 25-30 years and the trees
will produce poles after 10 years (Brink 2007). Weeding is critical during the first year of
planting (Orwa et al. 2009).
31
CHAPTER 6 DATA
The data included in this study are from woodlot information gathered in the field
from six farmer’s woodlots. The data from the woodlot assessment include area of
woodlot, age of trees, total number of trees, tree species, stand basal area, tree dbh, tree
height, tree spacing, and the number of trees within a three meter radius. Every tree with
a dbh less than 2.5cm is listed as 1.9cm. If the height of a tree is less than 0.30m (1ft) it is
listed as 0.23m (0.75ft). A tree with an age less than one year is listed as 0.5 years. The
complete data set is shown in Appendix C. Since farmers’ individual woodlots tend to be
less than 0.2ha, if only one or two larger trees exist in the woodlot and they happen to be
included in the sample, this overestimates the basal area for the woodlot.
The first woodlots assessed were those of Matei (Table 6.1). Matei’s woodlots
consisted primarily of pine with few eucalypts planted in woodlot two. Woodlot one was
a larger, younger woodlot with a smaller stand basal area.
Table 6.1
Data from woodlots owned by Matei.
Woodlot
1
2
Area (m²)
Average age (years)
Standard deviation
Number of trees
Trees species
Stand basal area (m²/ha)
Average dbh (cm)
Standard deviation
Average height (m)
Standard deviation
Average tree spacing (m)
Average number of trees
within 3m radius
1088
2.3
1.1
284
Pipa
2.8
3.0
2.2
1.5
2.8
2.1
7.0
840
6.3
1.3
78
Eusa,Pipa
45.4
22.6
13.1
6.6
11.1
2.4
3.3
Eusa = E. saligna, Pipa = P. patula
32
Luwole had a total of four woodlots consisting of pine, cypress and eucalypts
(Table 6.2). The stand basal area ranges from 2.0m²/ha in woodlot two to 105.2m²/ha in
woodlot four. There were a total of 388 trees throughout all of the woodlots with the
average age ranging from 2.3-3.2 years.
Table 6.2
Data from woodlots owned by Luwole.
Woodlot
Area (m²)
Average age (years)
Standard deviation
Number of trees
Trees species
Stand basal area (m²/ha)
Average dbh (cm)
Standard deviation
Average height (m)
Standard deviation
Average tree spacing (m)
Average number of trees
within 3m radius
1
2
1926
3.1
3.3
153
Culu,Eusa
Pipa
17.0
13.3
11.3
3.8
8.1
1.8
5.7
551
2.3
0.7
72
Culu,Eusa
2.0
3.8
5.2
1.6
6.0
2.0
2.8
3
196
2.7
1.9
34
Culu,Eusa
16.3
9.8
4.3
4.7
6.0
2.0
9.0
4
540
3.2
2.3
129
Culu,Eugl
Eusa
105.2
16.4
17.4
6.0
15.2
1.8
5.6
Culu = C. lusitanica, Eugl = E. globulus, Eusa = E. saligna, Pipa = P. patula
Woodlot four had a mixture of different trees, sizes and ages (Figure 6.1). Trees
found in this woodlot included Leucaena spp., avocado, cypress, pine, and eucalypts. The
farmer had used this land strictly for planting crops, but because it is located along a
frequented trail, the crops would be stolen. He decided to convert the area into a woodlot,
but continues to plant cabbage in the understory.
33
Figure 6.1: Luwole: Woodlot 4.
Photo: Paul Francis
Yisega owned one woodlot and the land was handed down to him from his father.
The woodlot was dominated by pine with eucalypts scattered throughout the area (Figure
6.1). Yisega planted 222 trees with a stand basal area of 74.3m²/ha (Table 6.3). The
average tree dbh was 15.1cm with an average height of 4.6m.
Table 6.3
Data from the woodlot owned by Yisega.
Woodlot
Area (m²)
Average age (years)
Standard deviation
Number of trees
Trees species
Stand basal area (m²/ha)
Average dbh (cm)
Standard deviation
Average height (m)
Standard deviation
Average tree spacing (m)
Average number of trees
within 3m radius
1
860
3.6
2.0
222
Eusa,Pipa
74.3
15.1
12.2
4.6
7.3
2.0
7.7
Eusa = E. saligna, Pipa = P. patula
34
Figure 6.2: Yisega: Woodlot 1.
Photo: Paul Francis
Jim Roger primarily plants eucalypts but there were patches of cypress in
woodlots one and two. Jim Roger has planted 501 trees in woodlot one and this was the
largest number of trees planted in a single woodlot among the farmers (Figure 6.3). The
trees in woodlot one also had the the tallest average height, 8.0m, and the largest dbh of
22cm among the farmers (Table 6.4).
Table 6.4
Data from woodlots owned by Jim Roger.
Woodlot
Area (m²)
Average age (years)
Standard deviation
Number of trees
Trees species
Stand basal area (m²/ha)
Average dbh (cm)
Standard deviation
Average height (m)
Standard deviation
Average tree spacing (m)
Average number of trees
within 3m radius
1
2
1797
5.3
0.4
501
Culu,Eugl
Eusa
99.2
22
12.0
8.0
13.3
2.2
11.6
Culu = C. lusitanica, Eugl = E. globulus, Eusa = E. saligna
35
1564
2.4
2.1
478
Culu,Eugl
Eusa
38.4
9.5
8.8
4.1
10.1
2.1
7.4
3
4
1296
1.9
0.9
365
Eusa
153
1.7
0.5
76
Eusa
31.9
9.0
8.3
3.9
10.7
2.1
7.4
3.2
2.8
1.0
1.5
2.4
2.1
6.7
Figure 6.3: Jim Roger: Woodlot 1.
Photo: Paul Francis
Elias plants eucalypts with few pine and black wattle planted throughout the
woodlots. A small number of black wattle trees six years of age or older, were planted in
each woodlot. The stand basal area of woodlot two was 126.4m²/ha with an average dbh
of 19.9cm (Table 6.5). Woodlot two had 194 trees with an average tree spacing of 1.63m
and an average tree height of 6.2m. The understory weeds and vines were thick
throughout the woodlots (Figure 6.4).
36
Table 6.5
Data from woodlots owned by Elias.
Woodlot
Area (m²)
Average age (years)
Standard deviation
Number of trees
Trees species
Stand basal area (m²/ha)
Average dbh (cm)
Standard deviation
Average height (m)
Standard deviation
Average tree spacing (m)
Average number of trees
within 3m radius
1
508
3.1
0.2
194
Eugl,Eusa
67.0
12.9
6.4
6.2
5.7
1.6
13.3
2
1299
4.0
3.1
237
Acme,Culu,Eugl,Eusa,Pipa
126.4
19.9
31
5.9
8.6
1.8
10.3
Acme =Acacia mearnsii, Culu = C. lusitanica, Eugl = E. globulus, Eusa = E. saligna,
Pipa = P. patula
Figure 6.4: Elias: Woodlot 1.
Photo: Paul Francis
Amoni had three woodlots which consisted of cypress and pine. The average
spacing between trees in woodlot three was 2.4m with an average of 2.7 trees within a 3m
spacing of the sampled trees (Table 6.6). The trees in woodlots one and two had an
average age of one year old. Forage grass for cows was planted throughout woodlot one
(Figure 6.5), and trees were planted together with maize and potatoes in woodlot three.
37
Table 6.6
Data from woodlots owned by Amoni.
Woodlot
Area (m²)
Average age (years)
Standard deviation
Number of trees
Trees species
Stand basal area (m²/ha)
Average dbh (cm)
Standard deviation
Average height (m)
Standard deviation
Average tree spacing (m)
Average number of trees
within 3m radius
1
2
3
114
1.0
0.1
238
Pipa
0.7
2.0
0.4
1.1
1.2
2.1
6.2
300
2.2
1.7
84
Culu,Pipa
10.8
5.7
4.2
2.0
3.1
2.1
6.1
1452
1.0
0.0
208
Culu,Pipa
0.4
1.9
0.0
0.7
1.0
2.4
2.7
Culu = C. lusitanica, Pipa = P. patula
Figure 6.5: Amoni: Woodlot 1.
Photo: Paul Francis
38
CHAPTER 7 RESULTS
To maximize timber values the woodlot owners must continue with their current
harvesting rotations. However, the management techniques in which the farmers should
improve upon include increased spacing between trees, reduced tree pruning, thin trees as
needed and weed the individual woodlot when necessary. Through hands-on workshops
and educational seminars the farmers could be equipped with the knowledge to help them
improve and maximize their timber outputs. The four main issues that will be discussed
in this chapter are harvesting, spacing, thinning and pruning of the woodlot trees.
Harvesting
Harvesting of pine and cypress is typically recommended with a rotation length
between 20-25 years after planting (Border Timbers Limited 2010, Brink 2007, Sabie
2006). In contrast, eucalypts are faster growing trees than both pine and cypress. Harvest
of eucalypts is recommended between 12-15 years and poles can be harvested after 8
years (Jacovelli et al. 2009).
All of the farmers who were interviewed harvest their timber between 8-12 years
after planting. The only farmer who has woodlots over an average of 4 years old is Matei
(Table 7.1).
Table 7.1
The average age of trees in woodlots.
Farmer
Average age
Matei
4.3
Luwole
2.8
Yisega
3.6
Jim Roger
3.5
Elias
3.9
Amoni
1.4
The oldest tree sampled throughout all of the woodlots was a 40 year old pine in
Elias’s woodlot. Any tree over 10 years of age is rare and does not characterize the young
woodlots. However, contrary to recommended harvest rotation guidelines, these short
rotations that the farmers implement are to their advantage.
39
Farmers tend to harvest their trees on shorter rotations for two primary reasons,
financial constraints and persistent buyers. When asked why he sold timber early Amoni
said, “What is better, to have your child dismissed from school, or harvest timber early?”
and went on to say, “It is better to harvest timber early so my kids can continue to study.”
Another farmer, Elias, said that, “If I have a problem today with money, I can sell trees
and get the cash when needed.” Other financial constraints requiring readily available
funds through cut trees include family emergencies, celebrations, weddings, funerals, or
the purchase of farming equipment or seeds. The same occurs in parts of Turkey, Kenya,
Costa Rica and Ecuador; when cash is needed during lean periods, trees will be cut
(Chavangi et al. 1985, Foley and Barnard 1984).
Persistent buyers coupled with inadequate market knowledge on the part of the
farmers make it easy for a buyer from the city to come and persuade farmers to sell their
timber for an unreasonably low price (Holding and Roshetko 2003, Nawir et al. 2007). In
logging communities in the Brazilian Amazon 94% of farmers felt that the price they
were receiving for their timber was unfair, while 50% had little to no understanding of
the logging process (Menton et al. 2009). Persistent buyers can pressure villagers of
Isangati to sell timber when they may otherwise be reluctant. Farmers feel exploited by
knowledgeable and pushy buyers. For example, Luwole sold several trees on his woodlot
to a buyer from town simply because the buyer was persistent. When Luwole sold nine of
his trees for the low price of 10,000TZS each, he said, “I felt pressured to sell because the
customer invaded to ask about the trees with force.” When negotiating deals with buyers
woodlot owners want to avoid conflict, they often use words such as “invaded” or “force”
to describe how they are treated. This is a common problem seen throughout the world
when it comes to small-scale woodlot owners selling timber and thus they are left with
little money. In Amazonia, while some community members have “quietly protested” the
sales of timber, “passivity and a strong proclivity towards avoidance of conflict both
among community members and with loggers, have allowed sales to continue” (Mendina
and Shanley 2004). With these relationship dynamics established, the loggers can easily,
“convince households to sell their trees- many times over- for scant cash” (Mendina and
Shanley 2004).
40
Selling timber trees typically consists of the farmer and buyer standing in the
woodlot negotiating a selling price by estimating the tree volume and value. This type of
pricing is not beneficial to the farmer because, “the dealers buy a whole tree and sell the
timber in cubic meters”, or individual boards (Malimbwi et al. 2009). A Tanzanian
logging report shows that villagers receive 1/100 of the market price when selling timber
or logs while the dealers retain the large profit (Milledge et al. 2007).
Farmers either decide to have the buyer hire the fellers and sawyers to harvest the
trees and saw logs, or the seller will do all of the hiring and the buyer will simply
purchase the end product. The trees are cut by hand using a pit-sawing technique (Figure
7.1) and infrequently a large circular saw and chainsaws are brought to the village from
town (Figure 7.2). When the buyer oversees the felling process, the remaining trees may
be damaged. The buyer is not vested in the land, thus has no motivation to be careful
during the timber production process. Luwole complained about damaged trees during
the harvest of his trees and other studies have had similar observations with damaged
plants, trees, and soil disturbance after a small-scale timber harvest (Kweka et al. 2007).
Figure 7.1: Pit-sawing.
Photo: Paul Francis
41
Figure 7.2: Machine sawing.
Photo: Paul Francis
In order to quantify whether current harvesting rotations are advantageous for
farmers in Isangati, discount tables were created (Table 7.2, Table 7.3, Table 7.4, Table
7.5, Table 7.6, Table 7.7, Table 7.8, and Table 7.9). The discount tables are based on the
number of stems/ha that farmers are currently planting and the number of stems/ha larger
plantation projects are planting and recommend (Border Timbers Limited 2010, Sabie
2006). Two 10-year harvest rotations of pine are being compared to one 20-year harvest
rotation of pine, and two 8-year harvest rotations of eucalypts are being compared to one
16-year harvest rotation of eucalypts; this compares what farmers are currently doing in
Isangati to the recommended harvest rotation (Border Timbers Limited 2010). Typical
survival rates of trees planted is also factored in with the final harvest (Gebremedhin et
al. 2000, Malimbwi et al. 1992b, Moore 1983). Site preparation, tree planting, and
weeding are all valued at the current amount in USD/ha that village laborers receive for
day labor employment. Farmers receive about 12USD/ha for land preparation, 3USD/ha
for digging holes and planting trees, and 6USD/ha for weeding. Pruning is valued at zero,
because farmers do not view this as work, and they tend to prune during down time or
while casually walking through their woodlots. The discount rate of 8% and 12% was
used because the social rate of discount used in most developing countries is between 8%
and 15% (Gittinger 1982, Symons 2008).
Two 10-year rotations of pine have a final harvest value of 5,519USD/ha after 10
years. This number is derived from 2,830 stems/ha at a 65% tree survival rate multiplied
42
by 3USD, which is the lowest amount farmers receive for their trees. One 20-year
rotation of pine has a value of 1,200USD/ha for the first thinning, 1,600USD/ha for the
second thinning, and 2,335USD/ha for the harvest. This rotation is based on a
recommended 1690 stems/ha at a 75% tree survival rate. The value of the first thinning is
400 trees multiplied by 3USD, the seconding thinning is 400 trees multiplied by 4USD,
and the final harvest is 468 trees multiplied by 5USD. Two 8-year rotations of eucalypts
are based on 3,000 stems/ha at a tree survival rate of 60%. The value of the tree thinning
is 1,800USD/ha and the harvest value is 3,600USD/ha. The thinning value is 600 trees
multiplied by 3USD and the harvest value is 1,200 trees multiplied by 3USD. One 16year rotation of eucalypts is based on 1200 stems/ha. The first thinning value is
900USD/ha, the second thinning value is 900USD/ha, the third thinning value is
1,200USD/ha, and the harvest value is 1,500USD/ha. The first and second thinning value
is 300 trees multiplied by 3USD, the third thinning value is 300 trees multiplied by
4USD, and the harvest value is 300 trees multiplied by 5USD.
As with many financial discount tables, the numbers entered into the table are
representative of a range of observed values. The numbers entered into these discount
tables are based upon field observations and literature. The smaller value used for the
amount of money farmers receive using their current harvesting rotations helps to
illustrate the point that even when smaller values are used for current harvesting rotations
these shorter rotations are still more economically beneficial than the longer
recommended rotation.
43
Table 7.2
Two 10-year rotations of pine at a discount rate of 8%. All values in USD/ha.
Operation
Site prep
Plant
Weed
Prune
Harvest
Total
Year
0
0
1
3
10
Value
-12
-3
-6
0
5519
Disc. Value
-12
-3
-6
0
2556
2536
Operation
Site prep
Plant
Weed
Prune
Harvest
Total
Year
10
10
11
13
20
Value
-12
-3
-6
0
5519
Disc. Value
-6
-1
-3
0
1184
1175
Grand Total
3711
44
Table 7.3
Two 10-year rotations of pine at a discount rate of 12%. All values in USD/ha.
Operation
Site prep
Plant
Weed
Prune
Harvest
Total
Year
0
0
1
3
10
Value
-12
-3
-6
0
5519
Disc. Value
-12
-3
-5
0
1777
1757
Operation
Site prep
Plant
Weed
Prune
Harvest
Total
Year
10
10
11
13
20
Value
-12
-3
-6
0
5519
Disc. Value
-4
-1
-2
0
572
566
Grand Total
2323
Table 7.4
One 20-year rotation of pine at a discount rate of 8%. All values in USD/ha.
Operation
Site prep
Plant
Weed
Prune
Weed
Thin
Prune
Thin
Harvest
Total
Year
0
0
1
3
3
10
12
15
20
Value
-12
-3
-6
0
-6
1200
0
1600
2335
45
Disc. Value
-12
-3
-6
0
-5
556
0
504
501
1536
Table 7.5
One 20-year rotation of pine at a discount rate of 12%. All values in USD/ha.
Operation
Year
Value
Site prep
Plant
Weed
Prune
0
0
1
3
-12
-3
-6
0
-12
-3
-5
0
Weed
Thin
Prune
Thin
Harvest
3
10
12
15
20
-6
1200
0
1600
2335
-4
386
0
292
242
Total
Disc. Value
896
Table 7.6
Two 8-year rotations of eucalypts at a discount rate of 8%. All values in USD/ha.
Operation
Site prep
Plant
Weed
Prune
Thin
Harvest
Total
Year
0
0
1
3
4
8
Value
-12
-3
-6
0
1800
3600
Disc. Value
-12
-3
-6
0
1323
1945
3247
Operation
Prune
Thin
Harvest
Total
Year
11
12
16
Value
0
1800
3600
Disc. Value
0
715
1051
1766
Grand Total
5013
46
Table 7.7
Two 8-year rotations of eucalypts at a discount rate of 12%. All values in USD/ha.
Operation
Site prep
Plant
Weed
Prune
Thin
Harvest
Total
Year
0
0
1
3
4
8
Value
-12
-3
-6
0
1800
3600
Disc. Value
-12
-3
-5
0
1144
1454
2578
Operation
Prune
Thin
Harvest
Total
Year
11
12
16
Value
0
1800
3600
Disc. Value
0
462
587
1049
Grand Total
3627
Table 7.8
One 16-year rotation of eucalypts at a discount rate of 8%. All values in USD/ha.
Operation
Site prep
Plant
Weed
Prune
Weed
Thin
Prune
Thin
Thin
Harvest
Total
Year
0
0
1
3
3
4
6
8
12
16
Value
-12
-3
-6
0
-6
900
0
900
1200
1500
47
Disc. Value
-12
-3
-6
0
-5
662
0
486
477
438
2037
Table 7.9
One 16-year rotation of eucalypts at a discount rate of 12%. All values in USD/ha.
Operation
Site prep
Plant
Weed
Prune
Weed
Thin
Prune
Thin
Thin
Harvest
Total
Year
0
0
1
3
3
4
6
8
12
16
Value
-12
-3
-6
0
-6
900
0
900
1200
1500
Disc. Value
-12
-3
-5
0
-4
572
0
363
308
245
1464
Contrary to current harvesting recommendations (Malimbwi et al. 2010) for
small-scale woodlot owners, the tables show that woodlot owners in Isangati are
harvesting trees with efficient rotations given their circumstances and based upon their
needs. Tables 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, and 7.9 illustrate that farmers are better off
staying with their shorter rotations as opposed to following recommended longer
harvesting regimes. Current rotations of pine at an 8% discount rate are more profitable
to farmers than the recommended one long rotation (Table 7.10). When the discount rate
is increased to 12%, the same is true for current pine rotations as compared to
recommended rotations (Table 7.10). The rotation profitability for eucalypts at each
discount rate is the same as for pine. The largest price difference is 2,976USD/ha, which
is between a two rotation harvest of eucalypts compared to a recommended long harvest
at a discount rate of 8% (Table 7.10). The smallest, yet still crucial, price difference of
1,427USD/ha is between a two rotation harvest of pine compared to a recommended long
harvest at a discount rate of 12% (Table 7.10).
48
Table 7.10
Two 10-year pine rotations compared to one 20-year pine rotation and two 8-year
eucalypt rotations compared to one 16-year eucalypt rotation.
Tree Species Discount Rate (%) Two short
One long
rotations ($/ha) rotation ($/ha)
Pine
8
3711
1536
Pine
12
2323
896
Eucalypts
Eucalypts
8
12
5013
3627
2037
1464
Village prices for timber increase only slightly as trees grow larger, consequently
farmers are not at any advantage if they wait longer to harvest timber. Field observations
indicate that the majority of woodlot owners sell individual timber trees for between
2.90-7.00USD. The individual tree dbh for these prices ranges from 8cm – 50cm.
Contrary to a report from the Makete district in Tanzania that urges woodlot owners to
harvest timber at least 15 years after planting (Malimbwi et al. 2010), the data show
villagers should not wait this long before harvesting. The same report stated that, “Most
farmers in Makete district harvest premature woodlots at the age of eight years to solve
family financial problems.” Harvesting younger woodlots can be more profitable.
Woodlot owners should continue with their current harvesting rotations since they will
receive nearly the same amount of money for a 10 year old tree as they would for a tree
on a longer rotation. Until a premium is paid for larger and higher quality trees, farmers
should continue with 8-12 year rotations. In the future, if small-scale farmers receive
appropriate payments for trees based on exact size, volume, and form, then a longer
rotation might be recommended. However, during times of financial constraints and
persistent buyers, when small-scale timber sales are estimates on a tree by tree basis, it is
more profitable for farmers to harvest trees on a shorter rotation.
By educating the farmers about timber market prices and trends, they would be
equipped with the knowledge to harvest and sell their timber products in an economically
wise fashion. The farmers would not be as predisposed to feel pressured by pushy buyers
49
to sell their timber for unfair amounts. Once the education component is there, farmers
may find that the longer harvest rotations become more profitable based on better prices
received for their timber.
Spacing
Woodlot owners are unsure of the proper spacing between trees; they tend to copy
their neighbor’s tree planting techniques. When asked about the planting spacing between
trees in the woodlot Luwole said, “I use only an estimate of where I think the trees should
be planted, I don’t use measurements only an estimate.” Many farmers try to plant as
many trees as they can in their woodlots, thinking they will be able to increase their
timber yields. Similarly, a study in the Philippines found that some small-scale farmers
were advised to plant trees closely because planting more trees produces more wood
(Yeo et al. 2005). According to Jim Roger, “Some people plant trees close together
because they have many seedlings with only one small plot of land to plant them on.”
Woodlot owners use irregular spacing and plant trees throughout their woodlot as they
acquire seedlings. If they are planting eucalypts for fuelwood and poles it is to be
expected that a closer planting regime is established, such as 1-2m x 1-2m in order to get
small logs for fuelwood or small poles for building (Evans and Turnbull 2004). For
timber harvesting, a spacing of 2.5-4.5m x 2.5-4.5m should be established for maximum
timber output (Evans and Turnbull 2004). Numerous sources use the guideline of
planting trees for timber production 2.5m x 2.5m with a thinning after six to eight years
and 3m x 3m with no thinning (Jacovelli et al. 2009, Malimbwi et al. 2010). Some
villagers plant trees with the same spacing they use for their crops and do not realize they
need to be planted farther apart (Table 7.11). Improved spacing could reduce tree
competition, thus helping to increase growth rates, tree size, tree form, and total stand
volume.
50
Table 7.11
The average tree spacing figures for each of the farmers’ woodlots. Recommended tree
spacing is 2.5m.
Farmer
Avg. tree spacing (m)
Matei
Luwole
Yisega
Jim Roger
Elias
Amoni
Avg. number of trees within 3m spacing
2.18
1.84
1.99
2.12
1.70
2.20
6.16
5.39
7.68
8.83
11.62
4.81
For both P. patula and C. lusitanica increased tree spacing decreases mortality
while increasing branch diameter and diameter breast height (Malimbwi et al. 1992a,
Malimbwi et al. 1992b). However, since C. lusitanica is a shade tolerant tree, unlike pine,
the total volume decreased with increased spacing (Figure 7.3), (Malimbwi et al. 1992a).
500
450
Volune (m³/ha)
400
350
300
250
Pinus Patula
200
Cupressus lusitanica
150
100
50
0
1.13
1.46
1.88
2.43
3.14
Tree Spacing (m²)
Figure 7.3: Effect of spacing on standing volume of 19 year old P. patula and C.
lusitanica at Rongai, Northern Tanzania.
Data Source: Malimbwi et al. 1992a and Malimbwi et al.1992b
51
Pruning
Pruning is the removal of lower tree branches to reduce knots in sawn timber and
to increase tree growth. On average, farmers prune 40%-60% of the tree crown two to
three years after planting (Figure 7.4). By removing such a high percentage of the tree
crown, farmers are negatively affecting the growth of their woodlot trees.
Figure 7.4: Pruning over 60% of the tree crown.
Photo: Paul Francis
Many farmers understand the benefits of pruning but the technical knowledge is
missing. When discussing tree pruning Elias said, “I prune my trees because it helps them
to grow larger, for instance if the tree is 30ft tall, I will usually prune 20ft up the tree.”
Luwole said, “I prune so that the trees will grow straighter with no bends. I prune up the
tree until I cannot reach any higher.” All of the farmers prune their trees because they
understand that it can help benefit the trees growth. During group discussions, farmers
indicated that they are unsure of how high up the tree to prune. As with other
management techniques they simply follow their neighbors. By reducing the amount of
the tree crown the farmers prune, they could increase tree growth rates. Light pruning of
30% of the tree crown can be established without reducing wood production (Endo and
Mesa 1992). In fact, 4.5 years after various pruning regimes were conducted, the trees
that were pruned 30% had the lowest mortality rate and the highest volume m³/tree and
m³/ha (Figure 7.5), (Endo and Mesa 1992).
52
400
350
Volume (m³/ha)
300
250
200
150
100
50
0
0
30
50
70
% of Pruning
Figure 7.5: Volume increment after pruning in a 3.5 year old plantation of P. patula in
Columbia
Data Source: Endo and Mesa 1992
Pruning cypress is especially important since the dead branches do not fall off,
causing knots in the wood (Malimbwi et al. 1992a). Woodlot owners should prune 30%
of the tree crown and begin pruning two to three years after the tree has been planted.
These pruned branches could also be a good source of fuelwood.
Thinning
Villagers are uncertain about appropriate thinning regimes (Table 7.12). During
the final workshop in the field with the woodlot owners, they were discussing how they
had heard that once a tree gets to its maximum height and width, it will not continue to
grow. In their eyes, it does not matter if trees are thinned after a few years. Some farmers
believe the remaining trees will not continue to grow even though other trees have been
thinned out allowing the remaining trees to gather more soil nutrients.
Generally speaking, recommended thinning schedules for a 9-12 year rotation
have initial stocking of around 1111-1372 stems/ha with two to three tree thinnings
53
conducted before harvest (Jacovelli et al. 2009). The stocking at final harvest should be
350-500 stems/ha (Jacovelli et al. 2009).
Table 7.12
Stems per hectare in each of the farmers’ woodlots. Initial stocking should be 1111-1372
stems/ha.
Farmer
1
2
3
4
Matei
Luwole
Yisega
Jim Roger
Elias
Amoni
2610
794
2581
2788
3819
2088
929
1307
3056
1824
2800
1735
2816
1433
2389
4967
-
Weeding is critical during the first few years of tree establishment (Jacovelli
2009). Certain grass species have been shown to limit root density of eucalypts by up to
40% in Ethiopian woodlots (Getahun 2010). Although weeding uses labor and time, the
benefits may be worth it. Once the canopy starts to close, weeding will be reduced and
less labor will be needed. Weeding is regularly done by woodlot owners on their farms,
so it may not be that difficult for them to carry this over into their woodlots. All of the
farmers interviewed said they do not weed their woodlots. Amoni prefers to keep taller
weeds around his trees during the first few years after planting because, “The tall weeds
help to protect the trees from the wind.” Elias’s woodlots were overgrown with weeds, if
weeding was carried out in his woodlots, the trees may have more soil nutrients and water
available to them and grow faster and larger (Evans and Turnbull 2004). Weeding may
benefit the trees but the extra labor involved might not be worth it for the farmers. Spot
weeding for example could help to reduce the amount of labor involved and still benefit
the trees throughout the woodlot. Spot weeding 1-2m in diameter around the trees is less
labor intensive than other manual types of weeding such as weeding the entire area or
strip weeding (Fujimori 2001).
54
Summary of woodlot owners
All woodlot owners are satisfied with their decision to use their extra land as a
woodlot. They tend to be some of the most educated people in the village and have more
land than most. All of the woodlot owners interviewed used their woodlots as a second
income source. Three of the woodlot owners’ primary income source is farming, two of
the woodlot owners are leaders of village churches, and one owns a small village store.
This information is consistent with research conducted in Kenya, which concluded that
farmers with more income per household will plant more trees than farmers with less
income per household (Patel et al. 1995).
Thoughts from farmers without woodlots
In order to gain a perspective of woodlots from villagers with lower household
incomes, farmers without woodlots were also asked for their ideas about woodlots.
Farmers without woodlots are interested in starting woodlots and they all view it
as a good investment for the future but they do not have the money or extra land
available. One farmer said, “Owning a woodlot is a good business, if you are lucky
enough to be able to wait a long time for the big pay-out.” Land is becoming scarce in the
area so if a farmer does not already own enough land it is hard for them to obtain more
land. A farmer stated, “We have the time to plant trees and work, the extra land is what
we do not have.” When asked why they choose not to own woodlots one farmer said,
“The problem is enough land, if you do not have enough land and you plant trees
you will be hungry. You will need to wait 10 years before you can sell your trees and
during those 10 years how will you pay for your children’s education. That is why we
plant maize, after 6 months we get enough money to pay for our children’s education. If
you only have a small farm and you plant trees your family will go hungry.”
Many farmers without woodlots are not willing to decrease annual field crop
production in order to dedicate some of their land to trees. This is consistent with tree
55
planting views of farmers in Panama who were reluctant to start any activity that may
reduce crop production (Fischer and Vasseur 2002).
Throughout the village, owning woodlots is seen as a living form of a bank
account. Some people refer to woodlots as a benki shamba (farm bank). People without
woodlots even view it as a good investment. If the land and extra income were available,
all of the interviewed farmers without woodlots said they would invest in a woodlot.
56
CHAPTER 8 CONCLUSIONS
Woodlots are a worthwhile investment for small-scale rural farmers. Once the
farmers receive proper education dealing with woodlot management this may enable
them to fully capitalize on their woodlot investment.
Management conclusions
Woodlot owners must continue with their current harvesting rotations to
maximize timber outputs based on current economic and social dynamics. The
management techniques in which the farmers should improve upon include increased
spacing between trees, reduced tree pruning, thin trees as needed and weed the individual
woodlot when necessary (Table 8.1). Table 8.1 shows the woodlot management
techniques currently conducted by woodlot owners, recommended based on literature,
and recommended based on this study. The woodlot owners clearly have the desire to
plant trees and once the technical knowledge is obtained, this will allow them to
maximize the productivity of their woodlots.
Table 8.1
Summary of woodlot management techniques and recommendations.
-
Recommended
based on
literature
X
-
X
X
-
X
X
X
-
X
Current
Regular weeding
Conduct scheduled
thinnings
Prune 30% of tree crown
Harvest using short
rotations
57
Recommended
based on study
X
General conclusions
Planting woodlots are a way for farmers to help the environment while earning an
extra household income. It is a secure investment in the area because the risks are
minimal with little to no fire, insects, cattle grazing, and theft. Woodlot owners, as well
as farmers without woodlots, view woodlots as little demand on household labor and time
with high rewards. Matei and Luwole said that woodlots are a good investment because
unlike crops that can be easily stolen, trees are much larger and would take more work to
steal them. According to Matei, “While someone is stealing trees it is likely that a
neighbor would see them.” Also, Luwole went on to say that trees have the potential to
pay off more than crops because trees do not rot as quickly as crops. Luwole stated,
“When someone harvests a crop, all that is harvested is crops, but when a tree is
harvested, you can harvest building poles, fuelwood, or timber to sell.”
Although woodlots can be beneficial to the farmers, it is also important to note
that the trees woodlot owners are planting pose environmental challenges. It has been
well established through research that eucalypts planted off-site can degrade soil nutrient
status and hydrologic function (Doughty 2000) and pine needles acidify the soil. Farmers
should consider incorporating more nitrogen fixing trees throughout their woodlots in
order to benefit the soil while still harvesting timber and poles. Some examples of
nitrogen fixing tree species they may want to consider planting include Leucaena spp.,
Sesbania spp., and Grevillea robusta (Trees for the Future 2008). Nitrogen fixing trees
can be planted throughout farmers’ crops to increase yields by adding nutrients to
degraded soils, or along contours on hillsides to minimize soil erosion. Agroforestry
techniques not only help to produce higher crop yields and reduce soil erosion, but also
produce fuelwood, natural fertilizer, and animal forage, all at various times throughout
the year. This technique may also be beneficial to land disadvantaged farmers without
woodlots because it would allow them to take advantage of their circumstances.
Environmental education is critical in regard to woodlot management (Appiah and
Pappinen 2010). The lack of technical training when it comes to woodlot management
was consistently mentioned as a key inhibitor to maximizing timber outputs. The farmers
in Isangati and throughout the southern highlands lack the knowledge that can enable
58
them to capitalize on their investments. This lack of technical training seems to affect the
productivity of small-scale tree farmers throughout the world (Baynes et al. 2010,
Bukenya 2008, Malimbwi et al. 2009). Conversely, when farmers are equipped with
proper tools such as education, they can benefit greatly. For example, in northern
Tanzania where the majority of environmental NGOs are based, farmers have more
knowledge of tree management and soil erosion control techniques, such as terracing and
agroforestry. Woodlot owners in Isangati are clearly making that first step by showing a
desire to plant trees for income, but lack the technical training that comes with tree
management. The majority of their woodlot knowledge comes from neighbors or friends
who may tell them a few things about tree planting. It is critical for extension workers,
NGOs, local government officials, or environmental educators to go to these villages,
conduct seminars or hands-on workshops for interested villagers. It is understood that
extension workers do not get paid enough and do not have the desire to work in these
small villages but the farmers need it. With workshops and farmer field schools, the
farmers in the area would be able to gain technical tree management knowledge. With an
increase in woodlot management knowledge, the small-scale woodlot owners would be
able to improve their living conditions through increased household income and
improved environmental conditions.
59
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67
APPENDIX A: COPYRIGHT PERMISSIONS
Figure 2.1:
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Central Intelligence Agency's permission. We request only that the Central Intelligence
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similarly credited to the photographer or author or Central Intelligence Agency, as
appropriate.
If a copyright is indicated on a photo, graphic, or any other material, permission to copy
these materials must be obtained from the original source.
This copyright notice does not pertain to information at Web sites other than the Central
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Accessed: September 7, 2011.
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Figure 4.2:
From: Jenna Francis (jmcovey4@gmail.com)
Sent: October 25, 2011 1:31 PM
To: Paul Francis (pdfranci@mtu.edu)
Paul Francis has my permission to use any photographs of mine that he wishes.
Jenna Francis
69
APPENDIX B: INTERVIEW QUESTIONS
Interview questions for woodlot owners
1. Why did you decide to start a woodlot?
2. Do you own the land that your woodlot is on? If so, how did you become the owner
and why did you choose your specific plot of land?
3. What land preparation do you do to your woodlot and why?
4. Do you grow your trees from seeds?
5. Where do you buy seedlings or seeds?
6. What tree species do you use and why?
7. How do you manage your trees (i.e. weeding, thinning, pruning)? Why do you use
these management techniques?
8. Are there things you would like to do to your woodlot but do not? What are the
constraints (i.e. money, labor, seedlings)?
9. Do you manage your woodlot differently now than you use to?
10. When and why do you harvest? Do you encounter any problems while harvesting?
11. What is the wood used for?
12. How much and to whom is the timber sold?
13. If you want to sell timber, what is the process?
14. Do you receive any benefits from the Tanzanian government by owning a woodlot?
15. How does your woodlot benefit your land?
16. How many farmers in the village engage in agroforestry or in woodlot management
(% of village)?
17. Why is having a woodlot a good business?
18. What are the difficulties with owning a woodlot?
19. What do you do to maintain your woodlot?
20. What are the benefits of owning a woodlot?
Interview questions for woodlot owners (Kiswahili)
1. Kwa nini uliamua kuanza shamba la miti?
2. Wewe ni mwenye wa shamba la miti? Umefanaje kuwa mwenye? Kwa nini
umechagua eneo hili na sio linguine?
3. Baadaya kuchagua eneo unafanyaje kabla ya kupanda miti kuandaa eneo? Kwa nini?
4. Unaotesha mbegu mwenyewe? Kwa nini?
5. Wapi unanunua miche au mbegu za miti? Bei gani?
6. Unapanda miti gani shambani? Kwa nini?
7. Unafanyaje kutunza shamba la miti? Fyeka, pruni, au kata miti?
8. Unatunza shamba la miti lako tafauti siku hizi kuliko zamani?
9. Lini na kwa nini unavuna mbao? Kuna shida wakati unapovuna mbao?
10. Wadudu au maradhi wanaharibu miti au mbao? Miti gani?
11. Watu wanatumia mbao kwa ajili ya nini?
12. Nani ananunua mbao? Kwa kiasi gani na bei gani?
70
13. Ukitaka kuuza mbao taratibu za kuuza mbao ni nini?
14. Unapata faida kutoka serikali kuu sababu una shamba la miti?
15. Je, shamba la miti lina faida gani kwa ardhi?
16. Watu wangapi kutoka kijiji cha Isangati wanafanya kilimo cha mchanganyiko/cha
mseto ua wana shamba la miti? Nipe asilimia cha kijiji?
17. Je, kuwa na shamba la miti ni biashara nzuri? Kwa nini?
18. Matatizo ni nini kuwa na shamba la miti?
19. Unafanya nini kusitawisha shamba lako?
20. Faida ya shamba la miti ni nini?
April 19, 2011 questions for woodlot owners
1. Is fire or livestock grazing a problem during the dry season? If yes, what do you do to
protect your trees?
2. Do you agree that approximately 50% of people in Isangati have a woodlot?
3. Is it better to use a hand hoe or machete to make the hole for planting your trees?
4. Why do you harvest timber between 8 to 12 years?
5. Why do woodlot owners use various tree spacing distances for trees within their
woodlots?
6. When do you start to harvest your Eucalyptus trees?
7. Do you plant Eucalyptus for fuelwood, building poles, timber and charcoal? Cypress
and pine strictly for timber sales?
8. What problems do woodlots create?
9. Throughout my research the main issues that I see with the woodlots is that:
 Timber is harvested very early
 Trees are planted too closely
 Have yet to start a woodlot group – may help to receive government assistance
 Many trees are pruned half way up or higher
 Trees are not thinned
10. Do you agree with this assessment? Would you like to add anything else in which I
may have forgotten to write?
11. Can you elaborate on or explain some of these issues?
12. What do you think are the solutions to some of these issues?
April 19, 2011 questions for woodlot owners (Kiswahili)
1. Je, moto unaharibu miti wakati kiangazi? Au mifugo wanaharibu miti kwenye shamba
la miti? Kama ndiyo, mnafanyaje kuhifadhi miti?
2. Mnafikiri watu asilimia 50 hapa Isangati wana shamba la miti?
3. Ni nzuri zaidi kutumia jembe au panga wakati unachimba shimo kwa miche? Kwa
nini?
4. Kwa nini mnaangusha miti baada ya miaka nane hadi miaka kumi na mbili?
5. Kwa nini watu wanatumia kipimo mbalimbali kati ya miti kupanda miti?
6. Lini utapoanza kuangusha milingoti?
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7. Mnapanda milingoti kwa ajili ya kuni, ujenzi, mbao, na mkaa? Mkambokambo na
msindano kwa ajili ya mbao tu?
8. Kuna matatizo gani ya shamba la miti?
9. Kutoka vitu vingi nimeona wakati tumekwenda mashamba yenu mimi nafikiri matatizo
ni haya:
 Mnaanza kupasua mbao mapema
 Mnapanda miti karibu karibu
 Bado kuanza kikundi cha shamba la miti
 Mnapruni nusu miti
 Wachache wanapunguzia miti
10. Mnakubali matatizo haya ni matatizo kweli? Au mnataka kuongeza matatizo ambalo
nimesahau kuandika?
11. Mnafikiri mnaweza kutatua matatizo haya?
12. Mnafikiri ufumbuzi/utatuzi kwa matatizo haya ni nini?
May 17, 2011 questions for farmers without woodlots
1. Why have you decided not to own a woodlot?
2. What do you use your land for? Why is what you do with your land better than using it
for a woodlot?
3. Do you think that having a woodlot is a good business?
4. What are the difficulties with having a woodlot?
5. If you were to plant a woodlot what would the benefits be?
6. If you received education about tree planting, would you use some of your land to
plant trees?
7. Do both men and women plant trees? Also, which sex does the work in the woodlot,
such as: weeding, pruning and cutting trees?
8. Did any of your parents own a woodlot?
9. These are ideas of the people with woodlots, do you agree with the following:
 Farmers here need more education about woodlot management (i.e. pruning,
weeding, harvesting, etc.)
 If a woodlot committee is started the government would not help with loans
 50% of people here have woodlots
 Wild fire is not a problem here
 Woodlots are a good investment for the future
 There is not enough land here to expand farms or woodlots
May 17, 2011 questions for farmers without woodlots (Kiswahili)
1. Kwa nini mmeamua msipande shamba la miti?
2. Je, mnatumia eneo yenu kwa ajili ya nini? Kwa nini ni nzuri zaidi kuliko kupanda
miti?
3. Je, mnafikiri kuwa na shamba la miti ni biashara nzuri? Kwa nini?
4. Kuna matatizo gani kuwa na shamba la miti?
72
5. Mkiamua kupanda shamba la miti utapata faida gani kutoka shamba la miti?
6. Je, mkipata elimu kuhusu shamba la miti, mnafikiri utatumia eneo yenu kupanda miti?
7. Je, wanawake na wanaume wanapanda miti? Jinsia gani wanafanya kazi ya miti kama
kupruni, kuangusha, kupalilia, na kupanda?
8. Wazazi wenu walikuwa na shamba la miti?
9. Haya ni maoni kutoka watu ambao wana shamba la miti, mnakubali iliofuata:
 Wakulima wanahitaji elimu za kutosha kuhusu shamba la miti
 Wakulima wakianza kikundi cha shamba la miti serikali kuu hawataki kuwasaidia
 Watu asilimia 50 hapa Isangati wana shamba la miti
 Moto wa kuchoma miti siyo tatizo hapa
 Kuwa na shamba la miti ni nzuri kwa uwekezaji akiba kwa baadaye
 Maeneo hayatoshi
73
APPENDIX C: WOODLOT DATA
The following are field notes, all of this data was later converted to metric units.
Each table describes one woodlot.
The following are a list of notes that may useful while viewing the woodlot data
from each of the farmers’ woodlots:

Tree # - The number of the sample tree that was measured.

Species – Acme – Acacia mearnsii, Culu – C. lusitanica, Eugl – E. globulus, Eusa
– E. saligna, Peam – Persea Americana, Pipa – P. patula. Trees marked with a
(st) shows that the sample tree measured was off of a cut stump.

Dbh – every tree with a dbh less than 2.5cm is listed as 1.9cm

Height – every tree that is smaller than 1ft in height is listed as .75ft

Age – every tree younger than 1 year old is listed as .5 years

Spacing – The number of trees and distance from sample tree within a 3 meter
radius from sample tree

A.T.S. – The average spacing of trees from the sample tree within a 3 meter
radius

3M.R. – The number of trees tallied within a 3 meter radius from the sample tree
74
75
238 total trees
1.9
1.9
1.9
1.9
1.9
1.9
3.3
1.9
1.9
1.9
2.5
2.5
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
0.5
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1.5
2.5
1.5
4
4
2.5
5.5
4
3
2
5
5
4.5
4
4.5
4.5
4.5
3
3
2.5
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
5
17
29
41
53
65
77
89
101
113
125
137
149
161
173
185
197
209
221
233
2.7
1.9
1.8
1.3
2
2.2
1.7
2.2
2
2
1.8
2.2
1.7
2.2
1.7
1.9
1.7
2.7
1.7
1.7
2.2
1.7
2.9
1.9
1.3
1.5
2.5
1.6
2.1
1.7
1.7
1.4
1.9
2.6
2.4
1.85
1.2
5
3
2
1.4
2.6
2.5
1.8
2.6
3
2
2.5
2.3
2.1
2.2
1.6
2
2.5
1.9
4
6
7
8
9
1.8
2.3
2.3
1.7
2.5
2.5
2.6
2.4
2.2
2.2
1.65
2.3
1.5
2.4
2.3
2.1
1.8
2.3
2.1
2
1
2.2
2.3
1.6
1.3
3
2.9
2.6
1.2
1.9
2.6
1
7
4
5
9
7
5
5
8
8
7
8
7
7
6
7
8
5
3
7
1.8
1.9
2.2
1.8
2.1
2.1
2.1
2.0
2.2
2.0
2.2
2.1
2.0
2.0
1.9
2.0
2.3
2.1
2.3
2.1
1.9
2.6
2.4
2.2
2.5
1.5
2.2
2.5
2.5
2.7
2.2
1.7
2.2
1.7
2.8
2.7
2.5
2.5
2.6
3
1
1.8
2
2.4
1.6
1.9
2
2.1
1.6
2.1
1.8
1.8
1.7
2.4
1.7
1.7
1.8
1.7
1.6
1.6
1.8
2
A.T.S. 3M.R.
31/01/2011
Date Measured Woodlot
1
Woodlot #
Spacing (m)
E033°26'0.5"
Longitude
Height Age
(ft)
S09°05'20.2"
Latitude
57 X 20
Land(m)
SE 150°
Aspect
Tree # Species Dbh
(cm)
2079m
Elevation
Amoni
Farmer
76
84 total trees
1.9
7.1
3.8
7.9
6.4
18.0
7.6
4.6
6.4
3.6
1.9
7.1
1.9
1.9
1
6
1
2
2
6
2
2
2
2
1
2
1
1
3
8
6
10
8
11
8
6.5
9
7
2
9
2.5
2
Pipa
Culu
Pipa
Pipa
Pipa
Culu
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
Pipa
2
8
14
20
26
32
38
44
50
56
62
68
74
80
4
2
2.7
2.6
2.5
2
2.4
1.8
2.7
1.6
1.9
2.7
2.2
1.7
1.5
1.9
2.1
2.4
2.9
5
2.2
0.9
2.9
2.4
2.65
2.6
2.2
1.6
7
1.8
2.5
1.8
2.1
1.6
2.4
1
2.5
2.8
1.8
1.4
1.9
6
2.3
1.9
8
9
2.2
2.1
2.9
0.6
6
9
5
8
7
5
6
5
4
7
8
7
5
4
1.8
1.9
2.5
1.9
2.0
2.3
2.0
2.0
1.9
1.9
2.1
2.0
2.4
2.1
3
1.4
2
2.5
1.7
1.4
2.1
2.1
1.6
1.4
1.6
1.8
1.4
2.1
2.7
1
1.3
1.9
1.9
1.65
1.5
2
1.6
1.9
2.3
1.7
1.6
1.7
2.7
2.3
2
1.5
2.6
2.8
1.4
2.1
2.6
2.9
2
2.4
2.4
2.3
2.2
2.6
2
A.T.S. 3M.R.
31/01/2011
Date Measured Woodlot
2
Woodlot #
Spacing (m)
E033°26'04.6"
Longitude
Height Age
(ft)
S09°05'12.8"
Latitude
20 X 15
Land (m)
E 90°
Aspect
Tree # Species Dbh
(cm)
2065m
Elevation
Amoni
Farmer
77
208 total trees
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1.9
1
1
1
1
1
1
1
1
1
1
1
1
1
3
2
2
1
3
1
0.5
2.5
4
2
3
3
2
Culu
Pipa
Pipa
Pipa
Culu
Pipa
Pipa
Culu
Culu
Pipa
Pipa
Culu
Pipa
10
26
42
58
74
90
106
122
138
154
170
186
202
2.5
2.1
3
2.5
2.6
2.3
2.9
2.85
2.5
2.5
2.4
2.3
2.4
3
2
2.6
2.5
2.3
2.1
4
2
3
1
1
3
3
3
4
1
3
4
4
3
2.3
2.4
2.5
2.2
2.4
2.4
2.6
2.4
2.3
2.5
2.5
2.3
2.8
2.25
3
1
2.6
2.3
2.5
2.2
2.15
2.5
2.3
2.6
2.25
2.45
2.25
2
2.85
2
1.9
2.7
A.T.S. 3M.R.
31/01/2011
Date Measured Woodlot
3
Woodlot #
Spacing (m)
E033°25'58.6"
Longitude
Height Age
(ft)
S09°05'06.2"
Latitude
44 X 33
Land (m)
NW 330°
Aspect
Tree # Species Dbh
(cm)
2045
Elevation
Amoni
Farmer
78
Eusa
Eusa
Culu
Pipa
153 total trees
9
47
85
123
10.9
11.4
29
1.9
14
15
20
1
2
2
8
0.5
2
1.65
4
1.5
5
6
7
8
9
10
1.5
2.45
2.9
3
1.6
3
4
10
2.1
1.3
2.1
3
2.4
1.8
1.1
1
2.8
0.6
2.65
2
1.1
0.6
2.2
A.T.S. 3M.R.
11/12/2010
Date Measured Woodlot
1
Woodlot #
Spacing (m)
E033°25'47.9'
Longitude
NE 30°
Aspect
Height Age
(ft)
S09°04'24.1"
Latitude
18X107
Land (m)
Tree # Species Dbh
(cm)
2075m
Elevation
Luwole
Farmer
79
72 total trees
2
3
3
2
2
3
2
1
3
3
2
2
2
3
3
2.5
2.5
5
15
1
20
6
2
1.5
Culu
1.9
Culu
1.9
Culu
1.9
Culu
1.9
Culu
1.9
Culu
1.9
Eusa(st) 6.4
Culu
1.9
Eusa(st) 19.6
Culu
1.9
Culu
1.9
Culu
1.9
1
7
13
19
25
31
37
43
49
55
61
67
9
2.1
2.2
2.1
0.2
2.4
2.6
0.35
0.5
2.4
0.1
2.3
2.9
2.0
2.1
1.4
2.3
2.4
2.6
1.0
2.2
2
3
0
2
3
4
9
3
0
2
3
2
2
2.7
0.6
8
1.9
1.6
2.1
7
2.4
2.6
2.8
0.1
2.9
6
2.1
2.5
2.7
0.1
1.4
5
2.1
2.1
2.9
4
2
1.6
1.4
1
2.5
2
3
A.T.S. 3M.R.
11/12/2010
Date Measured Woodlot
2
Woodlot #
Spacing (m)
E033°25'50.8'
Longitude
Height Age
(ft)
S09°04'24.5"
Latitude
19X29
Land (m)
NE 30°
Aspect
Tree # Species Dbh
(cm)
2057m
Elevation
Luwole
Farmer
80
*Continued on next page
34 total trees
4.6
9.4
15.2
10.7
9.1
9.9
14.2
13.2
1.9
7
0.5
4
2
2
2
3
3
1
9
12
25
16
15
15
22
19
6
Eusa
Culu
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
1
5
9
13
17
21
25
29
33
1
2.7
1.05
2.1
1.85
1.3
1.7
0.85
1
2
2.8
1.1
2.1
0.85
2
2.3
1.6
1
Spacing (m)
E033°25'51.9'
Longitude
Height Age
(ft)
S09°04'24.5"
Latitude
8.5X23
Land (m)
NE 45°
Aspect
Tree # Species Dbh
(cm)
2053m
Elevation
Luwole
Farmer
2.2
2.05
1.7
0.7
1.4
2
1
3
2.9
2.95
2.65
1.5
1.75
2.5
2.3
4
2.2
2.6
2.05
2.5
2.5
1.85
2.7
5
19/12/2010
Date Measured Woodlot
3
Woodlot #
0.95
2.5
2.7
2.4
1.6
2.1
2.25
6
1.9
0.7
1.3
2.5
2.9
2.9
2.1
7
1.1
1.0
2.7
2.5
2.0
3.0
8
81
1.4
2.95
2.5
1.1
9
2.9
2.3
0.7
1.7
10
2.9
1.75
1
2.2
11
*Continued from previous page
1
5
9
13
17
21
25
39
33
Tree # Spacing (m)
1.8
2.3
12
2.5
13
2.8
2.0
2.2
1.8
2.0
2.0
1.9
1.7
0
2
11
11
12
13
7
8
8
0
A.T.S. 3M.R.
82
*Continued on next page
129 total trees
3.0
4.8
2.8
4.1
63.2
16.5
14.2
36.6
8.6
17.5
13.5
11.9
1
1.5
1
1
8
4
3
3
1.5
4
7
3
6
9
6
8
60
25
17
28
11
30
19
16
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl
Eusa
Eusa
Peam
Eusa
Eusa
Culu
Eusa
8
19
30
41
52
63
74
85
96
107
118
129
2
2.5
0.8
2.5
0.45
1.5
2.1
2.4
1.4
0.4
2.4
1
2.9
1.3
0.3
0.2
1.6
1.8
1.7
1.95
0.25
1.3
2
Spacing (m)
E033°25'47.1'
Longitude
Height Age
(ft)
S09°04'32.5"
Latitude
54X10
Land (m)
SW 225°
Aspect
Tree # Species Dbh
(cm)
2068m
Elevation
Luwole
Farmer
0.45
1.2
2
3
1.4
2.7
0.2
0.4
2.2
0.35
1.4
4
0.5
0.7
1.6
2.7
2.15
1.6
2.1
2.8
2.6
1.9
2.75
2.5
0.55
6
2.9
5
0.5
17/12/2010
Date Measured Woodlot
4
Woodlot #
3
2.1
1.9
2.2
7
2.8
1.4
2.1
2.2
8
2
83
10
2.7
1.8
1.9
9
2.9
1.7
2.3
0.3
2.6
11
2.4
*Continued from previous page
8
19
30
41
52
63
74
85
96
107
118
129
Tree # Spacing (m)
2.6
12
1.4
1.2
13
2.1
1.4
1.5
1.8
2.1
2.0
2.1
1.8
0
0.9
1.6
2.0
12
4
13
11
8
2
2
3
0
7
4
1
A.T.S. 3M.R.
84
*Continued on next page
222 total trees
5
1
2
1
6
2
5
5
5
5
5
5
6
6
5
1
1
5
3
3
1
1
20
10
16
6
35
14
16
18
17
16
19
15
24
24
18
5
5
14
12
13
6
5
4
14
24
34
44
54
64
74
84
94
104
114
124
134
144
154
164
174
184
194
204
214
Pipa
22.1
Eusa(st) 3.8
Eusa(st) 10.2
Eusa(st) 1.9
Eusa
48.5
Eusa(st) 11.4
Pipa
19.1
Pipa
11.4
Pipa
21.8
Pipa
17.0
Pipa
22.9
Pipa
15.5
Pipa
34.3
Pipa
33.0
Pipa
19.1
Eusa
1.9
Pipa
1.9
Pipa
12.7
Pipa
6.9
Pipa
13.0
Pipa
1.9
Pipa
1.9
Height Age
(ft)
1
2.1
2.5
0.5
0.3
2.8
1.3
2.9
0.6
2.7
2.1
2.1
1.7
2.1
2.6
1.9
1
2.6
1.7
2.9
2.4
1.6
1.4
2
2.3
0.25
0.5
0.3
1.3
0.2
1.6
2.4
1.1
2.7
2.1
2.8
2.9
2.5
2.4
2.6
2.3
2.5
1.5
2.8
3
2.9
Spacing (m)
E 033° 25'25.5"
Longitude
S 09° 04' 46.1"
Latitude
20 X 43
Land (m)
Tree # Species Dbh
(cm)
90°
Aspect
2025 m
Elevation
Yisega
Farmer
3
2.4
0.25
0.2
1.8
1.2
0.35
1.6
2.4
1.9
2.1
2.2
2.6
2.4
2.6
1.7
1.8
1.8
2.3
2.4
1.9
1.7
2.6
2.6
0.7
2.2
1.5
1.7
1.8
2.4
2.1
1.7
1.6
2.2
2.3
3
1.7
2.2
1.6
1.7
2.2
1.8
2.8
2.9
1.8
2.8
1.9
2.8
1.5
2.5
1.9
2.8
1.5
2.8
2
5
0.25
0.5
2.1
1.5
0.4
1.7
2.8
4
9/12/2010
Date Measured Woodlot
1
Woodlot #
2
2.4
1.7
2.5
2.2
2.7
1.1
3
1.4
2.7
2.1
2.2
1.4
2.6
2.2
2.1
2.9
1.3
1.6
0.6
2.2
1.1
2.2
2.5
7
1.3
2.7
0.75
2.25
1.7
2.7
2.9
6
1.8
2.6
1.9
2.8
1.5
2.9
2.4
1.6
1.7
1.8
1.2
1.3
1.8
8
85
1.4
2.8
2.9
2.4
2.6
0.5
1.3
1.8
1.3
1.5
2.9
9
2.1
2.5
1.7
2.3
2.1
0.6
11
0.5
1.6
10
*Continued from previous page
4
14
24
34
44
54
64
74
84
94
104
114
124
134
144
154
164
174
184
194
204
214
Tree # Spacing (m)
2.7
12
2.3
1.2
0.8
1.6
1.5
1.4
2.2
2.1
1.9
2.4
2.1
2.1
2.3
2.3
2.2
1.9
2.3
2.2
2.2
2.2
2.3
2.1
AT.S.
3
11
10
9
9
11
9
4
3
5
9
5
7
6
8
9
10
12
9
8
6
6
3M.R.
86
2
Pipa
1.9
1
1
13
Pipa
1.9
2
1
24
Pipa
1.9
5
3
35
Pipa
1.9
6.5
3
46
Pipa
1.9
3
1
57
Pipa
10.7
12
4
68
Pipa
1.9
2
1
79
Pipa
1.9
6
2
90
Pipa
1.9
2
1
101
Pipa
1.9
1
1
112
Pipa
1.9
6.5
3
123
Pipa
1.9
4
2
134
Pipa
1.9
6
3
145
Pipa
1.9
4
2
156
Pipa
1.9
6
3
167
Pipa
6.4
8
4
178
Pipa
1.9
5
3
189
Pipa
1.9
2
1
200
Pipa
6.4
9
3
211
Pipa
5.1
8.5
4
222
Pipa
1.9
3
2
233
Pipa
1.9
6
3
244
Pipa
5.1
8
3
255
Pipa
1.9
3
2
266
Pipa
5.1
8
4
277
Pipa
1.9
3
1
284 total trees *Continued on next page
1
1.2
2.4
2.3
2.2
2.5
2.2
1.8
2.9
2.1
2.9
2
1.9
2.3
2.3
1.2
2.6
2.7
2
2
1.9
1.5
2
1.5
1.7
2.9
1.7
2
2.6
1.6
2
2.2
2.2
2.8
2.6
1.5
2.9
1.8
2.3
1.9
2.5
2
2.4
2.7
1
2.7
2.6
2.8
1.7
2.9
2.3
1.8
1.9
2.9
Spacing (m)
12°
Aspect
E 033°25'38.6"
Longitude
Height Age
(ft)
2026m
Elevation
S 09°05'11.0"
Latitude
Tree # Species Dbh
(cm)
Matei
Farmer
32 X 34
Land (m)
3
1.5
1.1
2.2
2.7
0.6
2.4
2.1
3
2.4
2.2
2.1
1.9
0.9
1.7
1.5
2.9
2.4
1
2.2
2.7
2.7
1.2
1
1.5
1.7
1.6
2.7
1.6
2.8
2.8
2.5
2.9
2.9
1.7
1.1
1.8
2.1
1.9
2.4
4
1.2
1.4
2.5
2.8
1.4
2.4
2.7
2.5
2
2.9
2.3
2.9
2.6
2.7
2.9
2.5
2.3
2.4
2.8
2.9
1.7
2.4
2.1
1.5
5
1.6
2.6
0.9
2.9
1.7
2.7
2.8
2.9
1.8
2.3
1
Woodlot #
7/12/2010
Date Measured Woodlot
1.2
2.1
1.9
1.6
1.4
2.5
1.3
1.6
1.3
2
2.1
2.9
1.1
1.5
1.8
2.9
2.9
2.8
1.4
2.8
1.5
2.4
1.5
2.4
2.3
1.3
2.6
0.8
7
6
0.6
2
2.1
2.9
2.3
2.9
2.9
2
1
1.9
0.3
2.8
8
87
1.6
2.2
2.3
1.5
1.1
1.5
2
2.8
10
1.6
1.5
1.6
9
2.9
2.2
2.5
11
*Continued from previous page
2
13
24
35
46
57
68
79
90
101
112
123
134
145
156
167
178
189
200
211
222
233
244
255
266
277
Tree # Spacing (m)
1.6
12
1.8
13
1.5
1.8
1.9
2.6
1.7
2.4
2.4
2.4
2.0
2.5
2.2
1.9
2.1
2.3
1.9
2.7
2.0
1.8
2.4
2.6
1.9
2.1
2.0
1.7
2.2
2.2
6
8
9
5
5
7
8
7
10
7
4
7
5
6
11
4
13
5
4
5
10
8
11
6
3
7
A.T.S. 3M.R.
88
Pipa
Pipa
Pipa
Eusa
78 total trees
18
37
56
75
14
8.9
31.8
35.6
14
11
26
35
6
6
8
5
4
2.9
2.2
5
2.5
5
4
2
2
2.6
2.5
2.6
2.0
3
2.3
2.6
1
2.8
2.7
2.2
2.6
2
2.3
2.4
2.9
1.4
A.T.S. 3M.R.
7/12/2010
Date Measured Woodlot
2
Woodlot #
Spacing (m)
E 033°25'37.2"
Longitude
12°
Aspect
Height Age
(ft)
S 09°05'10.8"
Latitude
28 X 30
Land (m)
Tree # Species Dbh
(cm)
2023
Elevation
Matei
Farmer
89
408 Total Trees
16.0
37.3
25.7
17.0
9.7
22.9
12.7
3
6
5
7
7
5
2
20
42
33
19
14
33
17
Eugl
Eusa
Eusa
Culu
Culu
Eugl
Eusa
12
73
134
195
256
317
378
1
2.4
2.1
1.4
1.2
1.1
1.45
1.75
2
1.7
2.7
2.9
1.9
2.9
2.8
2
Spacing (m)
E033°25'14.9"
Longitude
Height Age
(ft)
S09°04'45.0"
Latitude
27X51
Land (m)
SE 130°
Aspect
Tree # Species Dbh
(cm)
2062m
Elevation
Jim Roger
Farmer
3
2.9
2.2
2.4
3
1.7
2.85
2.9
4
2.7
1.35
2.8
2.5
3
2.85
1.5
5
0.9
2
1.7
1.2
2.9
3
2.5
13/01/2011
Date Measured Woodlot
1 Section A
Woodlot #
2
1.5
3
1.8
1.4
2.4
6
2.8
2.3
1.6
2.3
1.9
1.2
2.2
3
0.65
8
2.5
7
90
1.3
2.6
1.3
1.15
1.35
2.4
1.95
2.3
1.1
10
2.3
9
1.5
2.7
2.55
2.6
2.6
11
*Continued from previous page
12
73
134
195
256
317
378
Tree # Spacing (m)
2.4
2.6
2.6
1.3
2.7
12
2.3
0.8
2.7
2.65
13
2.9
1.7
2.8
2.2
14
3
2
15
2.7
2.8
16
2.2
17
1.25
18
2
19
2.1
2.2
2.1
2.2
2.1
2.4
1.9
A.T.S.
5
12
6
14
19
16
14
3M.R.
91
*Continued on next page
93 total trees
35.8
22.9
48.0
12.7
30.5
7
7
6
7
5
34
25
42
15
36
Culu
Culu
Eusa
Culu
Eusa
14
33
52
71
90
1
2
2.7
2.1
2.4
2.1
2
2.3
3
2.1
1.5
2.9
Spacing (m)
E033°25'13.6"
Longitude
Height Age
(ft)
S09°04'45.8"
Latitude
20X21
Land (m)
SE 130°
Aspect
Tree # Species Dbh
(cm)
2059m
Elevation
Jim Roger
Farmer
3
2.5
3
1.4
2.4
1.5
4
1.5
2.4
1.3
2.7
1.9
5
2.25
2
2.8
3
1.7
13/01/2011
Date Measured Woodlot
1 Section B
Woodlot #
6
1.4
1.9
2.8
2.45
2.3
7
2.4
2.8
2.75
1.3
1.25
2.7
2.3
8
1.1
92
2.6
9
2.8
10
3
11
1.8
*Continued from previous page
14
33
52
71
90
Tree # Spacing (m)
2.1
2.5
2.2
2.3
2.0
11
7
9
7
8
A.T.S. 3M.R.
93
478 total trees
1.9
1.9
22.9
3.3
10.2
5.8
20.3
1
1
7
1
2
2
3
2.5
1
21
7
16
18
28
Eusa
Eusa
Culu
Eugl(st)
Eusa
Eusa
Eusa
22
92
162
232
302
372
442
4
1.7
2
2.5
2.2
2.05
1.5
2.4
5
1.3
2.3
1.2
2.5
1.5
2.5
1.8
6
2.4
1.4
3
1.2
1
2.4
1.7
7
8
9
10
2.9
2.8
2.6
2.4
1.8
2.6
3
2.5
3
2.1
6
7
10
10
7
6
6
1.9
2.8
2.6
2.0
2.0
2.3
2.0
3
1.9
2.3
2.8
2.5
1.8
3
2.3
1
2.5
1.6
2.8
0.1
2.5
2
1.5
2
1.8
2.7
2.9
1.5
2.6
2.2
2.5
A.T.S. 3M.R.
14/01/2011
Date Measured Woodlot
2
Woodlot #
Spacing (m)
E033°25'12.8"
Longitude
Height Age
(ft)
S09°04'46.7"
Latitude
34X46
Land (m)
SE 130°
Aspect
Tree # Species Dbh
(cm)
2066m
Elevation
Jim Roger
Farmer
94
365 total trees
26.7
20.8
15.2
17.8
11.4
1.9
1.9
1.9
1.9
6.1
8.6
8.1
1.9
1.9
3
3
3
3
2
1
1
1
1
2
2
2
1
1
28
28
25
30
14
6
4
4
4
9
12
13
1
0.75
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
21
47
73
99
125
151
177
203
229
255
281
307
333
359
4
2.9
1.7
2.3
1.25
1.45
1.8
2.4
1.9
1.8
2.7
1.5
2.9
2.2
2.4
6
2.7
1.65
1.4
1.95
2.5
1.5
1.8
1.6
1.4
1.6
1.8
5
1.5
2.5
2.8
2.95
2.9
7
2.9
1.5
2.6
2.2
2.5
8
2.2
2.5
1.3
2.1
2.6
9
2.1
3
2.6
2.6
2.8
2.4
2.6
2.5
2.9
2
2.4
1.7
2
2.3
2.3
1.8
1.9
1.8
3
1.55
1.9
8
8
9
9
9
4
7
4
9
8
7
9
7
5
2.1
2.1
2.2
1.8
2.3
1.7
1.9
2.0
2.1
2.2
1.9
2.2
2.1
2.4
3
1.6
2.3
2
0.2
1.8
2.1
1.3
1.6
1.8
1.7
2.9
1.6
2.1
2.6
1
1.2
3
1.8
2
2.15
1.6
2.5
2.5
2.4
1.7
1.7
2
1.8
2.2
2
1.85
1.9
2.45
1.6
2.6
1.2
1.7
2
1.7
2.7
1.4
2.2
2.4
2.4
A.T.S. 3M.R.
14/01/2011
Date Measured Woodlot
3
Woodlot #
Spacing (m)
E033°25'11.7"
Longitude
Height Age
(ft)
S09°04'46.9"
Latitude
36X36
Land (m)
NW 330°
Aspect
Tree # Species Dbh
(cm)
2066m
Elevation
Jim Roger
Farmer
95
76 total trees
1.9
3.6
1.9
4.6
1.9
3.0
1.9
3.0
3.3
1
2
1
2
1
2
2
2
2
2
6
1
8
3
6
6
6
7
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
Eusa
6
14
22
30
38
46
54
62
70
4
2
2.9
2.7
1.6
2.9
2
2.6
2.2
2.1
5
1.8
1.8
2.7
2.8
2.1
1.7
1.7
2.8
1.8
6
7
8
1.3
2.9
2.4
2.4
3
1.6
2.85
2
1.5
1.9
1.65
2.2
2.1
1.7
1.7
1.8
2.3
2.2
2.2
2.5
1.8
1.9
2.3
1.9
3
2.4
2.1
1.1
3
2.8
2
2.4
2.9
1.4
1
2
1.4
2.2
2.5
2.2
2.3
2
1.9
1.5
2
1
3
2.2
2
1.9
1.4
1
1.7
2.1
A.T.S.
15/01/2011
Date Measured Woodlot
4
Woodlot #
Spacing (m)
E033°25'11.7"
Longitude
Height Age
(ft)
S09°04'48.1"
Latitude
17X9
Land (m)
SE 160°
Aspect
Tree # Species Dbh
(cm)
2062m
Elevation
Jim Roger
Farmer
5
6
8
8
6
7
5
8
7
3M.R.
96
*Continued on next page
144 total trees
27.9
6.9
15.7
4.8
11.4
14.7
18.0
3.0
16.0
3.8
5.3
17.0
6
2
4
2
3
5
5
1
3
1
2
4
35
13
24
10
20
30
33
6
21
10
13
26
Eugl
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
11
23
35
47
59
71
83
95
107
119
131
143
1
2.6
0.1
1.2
1.6
2.75
0.35
0.7
0.55
0.25
0.2
1.1
1.15
2
0.55
0.4
1.4
2.6
2.8
0.4
1.4
1.8
2.5
0.25
1.3
2.4
Spacing (m)
E033°25'26.2"
Longitude
Height Age
(ft)
S09°04'29.7"
Latitude
10X36
Land (m)
S 180°
Aspect
Tree # Species Dbh
(cm)
2059m
Elevation
Elias
Farmer
3
0.8
0.7
0.7
0.3
2.9
0.5
2.8
2.1
2.3
1
2
0.55
4
1.2
0.4
1.95
2.1
2.95
1.2
1.95
1.5
2.5
1.65
2.4
0.9
5
1.3
0.95
2.1
2
2.8
1.5
2.2
0.45
1.6
2.5
2.6
0.7
21/12/2010
Date Measured Woodlot
1Section A
Woodlot #
0.8
2.6
2.5
2.8
1.7
2.1
0.7
1.65
2.3
2.4
0.9
6
0.8
2.8
1.15
0.2
1.6
1
2
2.85
2.5
1.6
1
7
1.9
1.45
1.5
0.4
2.6
1.35
1.9
1.2
2.55
1.7
1.35
8
97
2.4
1.4
1.7
0.4
2.55
2.7
2.2
2.5
1
1
2.4
9
1.3
1.7
1.8
2.2
2.6
2.1
1.5
1.35
2.75
1.7
2.85
1.3
1.3
2.4
11
2.25
1.9
1.5
10
*Continued from previous page
11
23
35
47
59
71
83
95
107
119
131
143
Tree # Spacing (m)
2.65
1.6
2.6
2.6
2.4
1.9
1.7
12
1
1.85
2.6
2.7
2.45
2.4
2.2
13
2.7
1.9
3
2.9
2.2
2
2.4
14
1.35
1.45
1.8
2.35
1.5
1.2
2.6
2.55
16
1.4
0.5
2.9
15
1.55
1.1
2.9
1.7
17
98
1.5
2.3
2.1
1.3
1
19
1.1
2.2
18
2.4
2
2.6
20
*Continued from previous page
11
23
35
47
59
71
83
95
107
119
131
143
Tree # Spacing (m)
2.4
2.15
21
2.5
22
2.6
23
1.3
1.2
1.8
1.8
2.0
1.6
1.8
1.8
2.1
1.9
1.8
1.3
5
11
10
15
9
21
20
14
18
23
16
9
A.T.S. 3M.R.
99
*Continued on next page
50 total trees
3
2
4
2
2
2
4
4
2
5
20
12
32
15
15
11
27
24
15
35
Eugl(st) 12.7
Eugl
6.4
Eugl(st) 25.9
Eugl(st) 10.2
Eugl(st) 7.6
Eusa(st) 7.1
Eugl(st) 22.1
Eusa(st) 17.8
Eusa(st) 10.2
Eusa(st) 31.5
4
9
14
19
24
29
34
39
44
49
1
0.55
2.65
0.3
0.5
0.5
0.4
0.5
0.6
0.4
0.5
2
1
2
0.3
0.5
0.45
0.3
2.3
2.2
1.05
1.4
Spacing (m)
E033°25'26.2"
Longitude
Height Age
(ft)
S09°04'29.2"
Latitude
10.8X13.7
Land (m)
S 180°
Aspect
Tree # Species Dbh
(cm)
2058m
Elevation
Elias
Farmer
3
2
2.1
0.35
0.3
1.9
0.3
1.7
2.4
1.2
5
1.5
1.65
2.25
1.2
1.2
2.5
2.1
2.2
4
0.5
1.05
0.5
0.8
1.75
1.7
1.75
1.05
30/12/2010
Date Measured Woodlot
1 Section B
Woodlot #
2.6
1.6
2.3
6
1.8
1.3
1.65
1.4
1.75
2.9
1.9
0.9
7
1.85
1.55
1.3
2.2
1.2
1.7
1.85
0.7
8
2.4
1.55
1.4
1.45
1.75
100
2.2
2.2
9
2.5
2.9
1.55
1.6
2
2.3
10
2.5
1.25
2.9
2.1
2.9
3
11
1
2.3
1.7
1.8
2
*Continued from previous page
4
9
14
19
24
29
34
39
44
49
Tree # Spacing (m)
2.7
1.75
1.3
1.9
1.1
2.1
13
1.2
12
1.5
2.2
2.95
14
1.6
2.7
15
2.4
16
1.8
17
1.8
18
1.65
19
1.6
1.9
1.3
1.4
1.7
0.3
2.2
1.8
1.3
1.0
14
11
11
14
19
3
13
8
9
2
A.T.S. 3M.R.
101
*Continued on next page
64 total trees
2
1
4
2
5
2
6
11
7
26
17
33
12
36
Eusa
6.9
Eusa
1.9
Eusa(st) 24.6
Eusa
9.1
Eusa(st) 44.7
Eugl
9.7
Eugl
47.0
8
17
26
35
44
53
62
1
2.9
1.5
0.25
2.3
0.45
2
E033°25'24.5"
Longitude
Height Age
(ft)
S09°04'28.5"
Latitude
16X28
Land (m)
SW 200°
Aspect
Tree # Species Dbh
(cm)
2054m
Elevation
Elias
Farmer
2
3
1.6
1.1
2.2
0.5
2.3
3
1.2
1.9
1.2
2.2
0.6
1.4
4
2
1.7
1.2
2.7
0.65
2.4
5
2.2
1.7
1.7
2.6
0.7
2.6
2/1/2011
Date Measured Woodlot
2 Section A
Woodlot #
6
2.4
2.6
1.6
2.1
1.7
2.8
8
2.4
2
1.2
1.8
7
2.6
2.3
2.2
1.7
3
102
1.5
9
2.9
1.5
2.6
1.5
10
2.9
1.3
11
*Continued from previous page
8
17
26
35
44
53
62
Tree # Spacing (m)
2.6
12
2.6
13
2.65
14
2.40
1.78
1.18
2.19
1.64
2.36
0
9
11
6
8
14
7
0
A.T.S. 3M.R.
103
*Continued on next page
57 total trees
10
40
3
3
7
1.5
1
2
2
1
30
40
20
20
40
9
7
6
10
2
Pipa
71.1
Pipa
87.1
Eusa(st) 12.7
Eusa(st) 12.2
Eusa
76.2
Eusa
5.1
Eugl(st) 3.6
Acme 1.9
Acme 3.3
Acme 1.9
2
8
14
20
26
32
38
44
50
56
1
2.4
1.2
0.65
0.35
2.8
1.3
0.1
1.5
0.3
1.9
2.75
0.45
2
2.3
0.6
2.1
0.35
2.3
0.5
1.9
2.8
0.5
2
0.3
2.1
3
0.35
2.1
1.4
0.4
0.2
0.7
2.3
4
0.55
2.4
1.6
0.5
1.4
1.2
2.4
5
2/1/2011
Date Measured Woodlot
2 Section B
Woodlot #
2
2.9
1.7
Spacing (m)
E033°25'24.0"
Longitude
Height Age
(ft)
S09°04'298.4"
Latitude
17X19
Land (m)
S 180°
Aspect
Tree # Species Dbh
(cm)
2056m
Elevation
Elias
Farmer
1.4
2.6
2.2
1.7
3
1
2.4
6
2.6
2.2
2.6
1
1.6
1.7
7
2.9
2.9
2.5
2
8
104
2
2.6
2.8
1.5
9
1.5
2.9
2.9
2.5
10
2.1
2.9
2.2
2.6
11
*Continued from previous page
2
8
14
20
26
32
38
44
50
56
Tree # Spacing (m)
1.2
2.2
2.8
12
1.1
2.95
13
1
1.8
14
1
2.2
15
1.2
3
16
2
17
2.3
18
2.4
19
2.8
20
2.7
1.9
0.7
0.8
2.3
2.0
1.3
2.0
1.7
2.2
2
3
1
7
6
7
11
20
16
12
A.T.S. 3M.R.
105
*Continued on next page
116 total trees
42.7
40.4
1.9
12.7
20.6
1.9
11.9
10.9
7.1
4.6
24.4
10.2
8
6
0.5
2
4
1
2
2
2
1
6
2
32
40
1
18
33
1
18
18
14
9
26
17
Culu
Eugl
Culu
Eugl(st)
Eugl
Culu
Eugl(st)
Eugl(st)
Eugl(st)
Eugl(st)
Acme
Eugl(st)
4
14
24
34
44
54
64
74
84
94
104
114
3
2.4
2.3
2.6
2.75
0.1
0.55
0.5
0.5
0.8
2
2.8
2.7
2
2.75
0.2
0.5
0.5
0.45
0.6
1.4
0.2
1.9
0.4
0.55
1.7
0.75
0.75
4
1.8
1.7
2
2.3
0.7
0.5
2.7
2.3
0.95
1.9
2.2
5
31/12/2010
Date Measured Woodlot
2 Section C
Woodlot #
1
1
2
2.4
0.25
2.2
0.2
0.35
0.45
0.35
0.6
Spacing (m)
E033°25'23.4"
Longitude
Height Age
(cm)
(ft)
S09°04'28.1"
Latitude
24X22
Land (m)
60°/240°
Aspect
Tree # Species Dbh
2053m
Elevation
Elias
Farmer
1.8
0.8
3
2.9
2.6
1.05
2.3
2.5
6
2.2
0.8
1.8
2.6
2.7
3
2
2.4
7
2.3
0.4
1.9
2.6
2.6
2.1
1.9
2.6
8
106
2.6
2.3
2.1
1.9
2
1.6
1.3
1
1.7
14
1.9
13
2.4
2.5
1.4
1.9
15
*Continued from previous page
4
14
24
34
44
54
64
74
84
94
104
114
Tree # Spacing (m)
2.1
2
1.5
2.4
16
2.6
2.5
1.4
2.3
17
2.8
1.8
1.8
2.3
18
2.4
1.6
2.2
1.9
19
2.8
1.8
2.3
2.2
20
2.7
1.5
2.1
2.1
21
107
2.2
2
2.1
2.6
1
23
1.9
1.9
2.4
2.7
22
2.3
1.9
2.1
24
*Continued from previous page
4
14
24
34
44
54
64
74
84
94
104
114
Tree # Spacing (m)
2
2.2
25
2.1
2.4
26
2.3
27
2.1
28
2.0
2.1
2.3
0.3
2.3
1.5
1.7
1.8
1.9
1.5
0
0.8
4
10
22
1
24
28
26
9
14
10
0
2
A.T.S. 3M.R.