SMALL-SCALE TIMBER STAND MANAGEMENT TECHNIQUES: A …

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 __________________________________

iii

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

iv

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

v

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

vi

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

vii

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

viii

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

ix

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.

x

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.

1

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.

2

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.

3

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).

4

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.

5

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).

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Christian Muslim Traditional African Religions

Other

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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

7

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.

Figure 2.3: Vegetation cover types.

Data Source: United Republic of Tanzania 1997

Forest Cover 3%

Woodland 42%

Bushland 20%

Grassland 22%

Open Land 2% Cultivated

Land 11%

8

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).

9

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.

10

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.

0

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Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Mon

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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.

12

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.

© 2011 Google –Map data © 2011

13

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.

14

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).

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1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

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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,

16

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

17

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

18

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.

19

Table 3.1

Field observations of common trees, shrubs, and grasses in Isangati.

Scientific Name English Kiswahili Kimalila

Tree

Acacia mearnsii Black wattle Muwati Naluyami

Albizia schimperiana Long-pod albizia Mruka Intanga

Callistemom citrinus Bottlebrush tree - -

Cupressus lusitanica Mexican cypress Mkambokambo -

Eucalyptus globulus Tasmanian blue gum Mkaratusi mweupe Ilongoti

Eucalyptus saligna Sydney blue gum Mkaratusi laini Ilongoti

Euphorbia bussei - - Ilangale

Grevillea robusta Grevillea Mgrivea -

Hagenia abyssinica Hagenia Mturunga Iliuguti

Leucaena leucocephala Leucaena Mlusina -

Mangifera indica Mango Mwembe Membe

Morus alba Mulberry Mfurusadi -

Musa sapientum Sweet banana Ndizi Igawo li ntonki

Persea americana Avacado Mparachichi Itakapera

Pinus patula Mexican weeping pine Msindano -

Prunus persica Peach Pindigesi Mafurisi

Cordia africana Large leafed cordia Makobokobo -

Shrub

Arundinaria alpinia Mountain bamboo Mianzi Malanzi

Datura suaveolens Angels trumpet - Ipopoti

Latana camara Latana - -

Grass

Pennisetum purpureum Elephant grass - -

Saccharum officinarum Sugar cane Muwa -

Tripsacum andersonii Guatemala grass - -

Cynodon dactylon Bermuda grass - -

20

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 Mango Mwembe Membe

Morus alba Mulberry Mfurusadi -

Musa sapientum Sweet banana Ndizi Igawo li

ntonki

Persea americana Avacado Mparachichi Itakapera

Prunus persica Peach Pindigesi Mafurisi

Passiflora edulis Passion Fruit - Ipohola

Chrysophyllum magalismontanum Wild Plum Matunda Damu -

Prunus domestica Plum Pindigesi Mafurisi

- - - Maswiza

Vegetables and Others

Phaseolus vulgaris Beans Maharage Imbonzo

Brassica oleracea Cabbage Kabichi Ikabiki

Pisum sativum Field pea Njegere Isyababa

Zea mays Maize Mahindi Amangagu

Cucurbita spp. Pumpkin Boga Iliungu

Helianthus annuus Sunflower Alizeti Abangayeye

Lycopersicon esculentum Tomatoes Nyanya Inyanya

Amaranthus spp. Amaranth Mchica Inzembwe

- - Sungwe Insungwe

- - Fagili Igagala

Roots and Tubers

Solanum tuberosum Irish Potatoes Viazi Viringo Intofwanya

Ipomoea batatas Sweet Potatoes Viazi Vitamu Imbatata

Colocasia esculenta Taro Mjimbi Isimbi

Non-Food Plants

Tanacetum cinerariifolium Pyrethrum Pareto Amaua

21

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

22

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.

23

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.

24

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).

25

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, follow-

up 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.

26

Figure 4.2: Discussing and sharing ideas about woodlots. Photo: Jenna Francis (See Appendix A for documentation of permission to use this

material).

27

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 8-

12 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.

28

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 blue-

green 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 greenish-

white 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

29

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

30

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

31

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).

32

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) 1088 840

Average age (years) 2.3 6.3

Standard deviation 1.1 1.3

Number of trees 284 78

Trees species Pipa Eusa,Pipa

Stand basal area (m²/ha) 2.8 45.4

Average dbh (cm) 3.0 22.6


Average height (m) 1.5 6.6


Average tree spacing (m) 2.1 2.4

Average number of trees 7.0 3.3

within 3m radius Eusa = E. saligna, Pipa = P. patula

33

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 1 2 3 4

Area (m²) 1926 551 196 540

Average age (years) 3.1 2.3 2.7 3.2

Standard deviation 3.3 0.7 1.9 2.3

Number of trees 153 72 34 129

Trees species Culu,Eusa Culu,Eusa Culu,Eusa Culu,Eugl

Pipa Eusa

Stand basal area (m²/ha) 17.0 2.0 16.3 105.2

Average dbh (cm) 13.3 3.8 9.8 16.4


Average height (m) 3.8 1.6 4.7 6.0


Average tree spacing (m) 1.8 2.0 2.0 1.8

Average number of trees 5.7 2.8 9.0 5.6

within 3m radius 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.

34

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 1

Area (m²) 860

Average age (years) 3.6

Standard deviation 2.0

Number of trees 222

Trees species Eusa,Pipa

Stand basal area (m²/ha) 74.3

Average dbh (cm) 15.1


Average height (m) 4.6


Average tree spacing (m) 2.0

Average number of trees 7.7

within 3m radius Eusa = E. saligna, Pipa = P. patula

35

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 1 2 3 4

Area (m²) 1797 1564 1296 153

Average age (years) 5.3 2.4 1.9 1.7


Number of trees 501 478 365 76

Trees species Culu,Eugl Culu,Eugl Eusa Eusa

Eusa Eusa

Stand basal area (m²/ha) 99.2 38.4 31.9 3.2

Average dbh (cm) 22 9.5 9.0 2.8


Average height (m) 8.0 4.1 3.9 1.5


Average tree spacing (m) 2.2 2.1 2.1 2.1

Average number of trees 11.6 7.4 7.4 6.7

within 3m radius Culu = C. lusitanica, Eugl = E. globulus, Eusa = E. saligna

36

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).

37

Table 6.5

Data from woodlots owned by Elias.

Woodlot 1 2

Area (m²) 508 1299

Average age (years) 3.1 4.0


Number of trees 194 237

Trees species Eugl,Eusa Acme,Culu,Eugl,Eusa,Pipa

Stand basal area (m²/ha) 67.0 126.4

Average dbh (cm) 12.9 19.9

Standard deviation 6.4 31

Average height (m) 6.2 5.9


Average tree spacing (m) 1.6 1.8

Average number of trees 13.3 10.3

within 3m radius 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.

38

Table 6.6

Data from woodlots owned by Amoni.

Woodlot 1 2 3

Area (m²) 114 300 1452

Average age (years) 1.0 2.2 1.0

Standard deviation 0.1 1.7 0.0

Number of trees 238 84 208

Trees species Pipa Culu,Pipa Culu,Pipa

Stand basal area (m²/ha) 0.7 10.8 0.4

Average dbh (cm) 2.0 5.7 1.9


Average height (m) 1.1 2.0 0.7


Average tree spacing (m) 2.1 2.1 2.4

Average number of trees 6.2 6.1 2.7

within 3m radius Culu = C. lusitanica, Pipa = P. patula

Figure 6.5: Amoni: Woodlot 1.

Photo: Paul Francis

39

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 Matei Luwole Yisega Jim Roger Elias Amoni

Average age 4.3 2.8 3.6 3.5 3.9 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.

40

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).

41

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

42

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

43

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 16-

year 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.

44

Table 7.2

Two 10-year rotations of pine at a discount rate of 8%. All values in USD/ha.

Operation Year Value Disc. Value

Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -6

Prune 3 0 0

Harvest 10 5519 2556

Total

2536


Site prep 10 -12 -6

Plant 10 -3 -1

Weed 11 -6 -3

Prune 13 0 0

Harvest 20 5519 1184

Total

1175

Grand Total 3711

45

Table 7.3

Two 10-year rotations of pine at a discount rate of 12%. All values in USD/ha.


Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -5

Prune 3 0 0

Harvest 10 5519 1777

Total

1757


Site prep 10 -12 -4

Plant 10 -3 -1

Weed 11 -6 -2

Prune 13 0 0

Harvest 20 5519 572

Total

566

Grand Total 2323

Table 7.4

One 20-year rotation of pine at a discount rate of 8%. All values in USD/ha.


Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -6

Prune 3 0 0

Weed 3 -6 -5

Thin 10 1200 556

Prune 12 0 0

Thin 15 1600 504

Harvest 20 2335 501

Total

1536

46

Table 7.5

One 20-year rotation of pine at a discount rate of 12%. All values in USD/ha.


Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -5

Prune 3 0 0

Weed 3 -6 -4

Thin 10 1200 386

Prune 12 0 0

Thin 15 1600 292

Harvest 20 2335 242

Total

896

Table 7.6

Two 8-year rotations of eucalypts at a discount rate of 8%. All values in USD/ha.


Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -6

Prune 3 0 0

Thin 4 1800 1323

Harvest 8 3600 1945

Total

3247


Prune 11 0 0

Thin 12 1800 715

Harvest 16 3600 1051

Total

1766

Grand Total 5013

47

Table 7.7

Two 8-year rotations of eucalypts at a discount rate of 12%. All values in USD/ha.


Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -5

Prune 3 0 0

Thin 4 1800 1144

Harvest 8 3600 1454

Total

2578


Prune 11 0 0

Thin 12 1800 462

Harvest 16 3600 587

Total

1049

Grand Total

3627

Table 7.8

One 16-year rotation of eucalypts at a discount rate of 8%. All values in USD/ha.


Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -6

Prune 3 0 0

Weed 3 -6 -5

Thin 4 900 662

Prune 6 0 0

Thin 8 900 486

Thin 12 1200 477

Harvest 16 1500 438

Total

2037

48

Table 7.9

One 16-year rotation of eucalypts at a discount rate of 12%. All values in USD/ha.


Site prep 0 -12 -12

Plant 0 -3 -3

Weed 1 -6 -5

Prune 3 0 0

Weed 3 -6 -4

Thin 4 900 572

Prune 6 0 0

Thin 8 900 363

Thin 12 1200 308

Harvest 16 1500 245

Total 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).

49

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 8 5013 2037

Eucalypts 12 3627 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

50

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.

51

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) Avg. number of trees within 3m spacing

Matei 2.18 6.16

Luwole 1.84 5.39

Yisega 1.99 7.68

Jim Roger 2.12 8.83

Elias 1.70 11.62

Amoni 2.20 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).

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

0

50

100

150

200

250

300

350

400

450

500

1.13 1.46 1.88 2.43 3.14

Vo

lun

e (m

³/h

a)

Tree Spacing (m²)

Pinus Patula

Cupressus lusitanica

52

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).

53

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

0

50

100

150

200

250

300

350

400

0 30 50 70

Vo

lum

e (m

³/h

a)

% of Pruning

54

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 2610 929 - -

Luwole 794 1307 1735 2389

Yisega 2581 - - -

Jim Roger 2788 3056 2816 4967

Elias 3819 1824 - -

Amoni 2088 2800 1433 -

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).

55

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

56

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.

57

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.

Current

Recommended

based on

literature

Recommended

based on study

Regular weeding - X X

Conduct scheduled

thinnings - X X

Prune 30% of tree crown - X X

Harvest using short

rotations X - X

58

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

59

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.

60

LITERATURE CITED

Appiah M, Pappinen A. 2010. Farm forestry prospects among some local communities in

Rachuonyo district, Kenya. Small-Scale Forestry. 9(3):297-316.

Baynes J, Herbohn J, Russell I. 2010. The influence of farmers' mental models on an

agroforestry extension program in the Pillippines. Small-Scale Forestry. 10(3):377-387.

Beets W. 1990. Raising and sustaining productivity of smallholder farming systems in the

tropics. Alkmaar (Holland): AgBe Publishing.

Bernard H. 1995. Research methods in anthropology. Walnut Creek (CA): Altamira

Press.

Bisanda S, Mwangi W, Verkuijl H, Moshi A, Anandajayasekeram P. 1998. Adoption of

maize production technologies in the southern highlands of Tanzania. Mexico City

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68

APPENDIX A: COPYRIGHT PERMISSIONS

Figure 2.1:

Copyright Notice

Unless a copyright is indicated, information on the Central Intelligence Agency Web site

is in the public domain and may be reproduced, published or otherwise used without the

Central Intelligence Agency's permission. We request only that the Central Intelligence

Agency be cited as the source of the information and that any photo credits or bylines be

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 Intelligence Agency Web site.

Online: https://www.cia.gov/library/publications/the-world-factbook/geos/tz.html

Accessed: September 7, 2011.

Figure 3.1 and Figure 3.4:

Google Maps and Google Earth Content Rules & Guidelines

Thank you for your interest in using content such as maps or satellite images

from Google Maps or Google Earth (referred to in these guidelines as “Content”). The

tool below will ask you up to four questions about the Content you plan to use and how

you will use it and then display the relevant usage requirements and guidelines.

Unless mentioned in your results, Google does not need to provide you explicit

permission to move forward with your project and no contact with Google is necessary so

long as you follow the requirements mentioned.

Online: http://maps.google.com/support/bin/static.py?page=ts.cs&ts=1342531

Accessed: October 5, 2011.

69

Figure 4.2:

From: Jenna Francis ([email protected])

Sent: October 25, 2011 1:31 PM

To: Paul Francis ([email protected])

Paul Francis has my permission to use any photographs of mine that he wishes.

Jenna Francis

70

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?

71

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?

72

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?

73

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

74

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

75

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Pip

a 1.9

1.5

1

2.4

2

.6

1.9

2

2.2

4

41

Pip

a 1.9

4

1

1.6

2

.4

1.8

1

.4

1.7

1.8

5

53

Pip

a 1.9

4

1

1.9

2

.2

1.3

2

.6

2.2

1

.65

2.3

1.9

2.6

2.1

9

65

Pip

a 1.9

2.5

1

2

2.5

2

2

.5

1.7

2

.3

1.6

2.1

7

77

Pip

a 3.3

5.5

1

2.1

1

.5

2.2

1

.8

2.9

2.1

5

89

Pip

a 1.9

4

1

1.6

2

.2

1.7

2

.6

1.9

2.0

5

101

Pip

a 1.9

3

1

2.1

2

.5

2.2

3

1

.3

2.3

1.8

2.6

2.2

8

113

Pip

a 1.9

2

1

1.8

2

.5

2

2

1.5

2

.3

2.3

1.2

2.0

8

125

Pip

a 2.5

5

1

1.8

2

.7

2

2.5

2

.5

1.7

2.1

2.2

7

137

Pip

a 2.5

5

1

1.7

2

.2

1.8

2

.3

1.6

2

.5

2

2.9

2.1

8

149

Pip

a 1.9

4.5

1

2.4

1

.7

2.2

2

.1

2.1

2

.5

1

2.0

7

161

Pip

a 1.9

4

1

1.7

2

.2

1.7

2

.2

1.7

2

.6

2.2

2.0

7

173

Pip

a 1.9

4.5

1

1.7

1

.7

2.2

1

.6

1.7

2

.4

1.9

6

185

Pip

a 1.9

4.5

1

1.8

2

.8

1.7

2

1

.4

2.2

2.3

2.0

7

197

Pip

a 1.9

4.5

1

1.7

2

.7

1.9

2

.5

1.9

2

.2

2.1

3

2.3

8

209

Pip

a 1.9

3

1

1.6

2

.5

1.7

1

.9

2.6

2.1

5

221

Pip

a 1.9

3

1

1.6

2

.5

2.7

2.3

3

233

Pip

a 1.9

2.5

1

1.8

2

.6

1.7

1

.85

2.4

1

.8

2.4

2.1

7

238 t

ota

l tr

ees

76

A

mon

i

2065m

E 9

0°

2

Farm

er

Ele

vat

ion

Asp

ect

Wo

odlo

t #

20 X

15

S09°0

5'1

2.8

" E

03

3°2

6'0

4.6

"

31

/01/2

01

1

Lan

d (

m)

Lat

itude

L

on

git

ude

D

ate

Mea

sure

d W

oo

dlo

t

Tre

e #

Spec

ies

Dbh

H

eight

Ag

e S

pac

ing

(m

)

A.T

.S. 3

M.R

.

(cm

) (f

t)

1

2

3

4

5

6

7

8

9

2

Pip

a 1.9

3

1

1.3

1

.5

1.4

2

2

.2

2.3

1.8

6

8

Culu

7.1

8

6

1.9

2

.6

2

2.7

0

.9

1.9

1.9

2.9

0.6

1.9

9

14

Pip

a 3.8

6

1

1.9

2

.8

2.5

2

.6

2.9

2.5

5

20

Pip

a 7.9

10

2

1.6

5

1.4

1

.7

2.5

2

.4

2.8

1

2.1

1.9

8

26

Pip

a 6.4

8

2

1.5

2

.1

1.4

2

2

.65

1.8

2.5

2.0

7

32

Culu

18.0

11

6

2

2.6

2

.1

2.4

2

.6

2.3

5

38

Pip

a 7.6

8

2

1.6

2

.9

2.1

1

.8

2.2

1

.4

2.0

6

44

Pip

a 4.6

6.5

2

1.9

2

1

.6

2.7

1

.6

2.0

5

50

Pip

a 6.4

9

2

2.3

2

.4

1.4

1

.6

1.9

4

56

Pip

a 3.6

7

2

1.7

2

.4

1.6

1

.9

1.9

1

.8

2.1

1.9

7

62

Pip

a 1.9

2

1

1.6

2

.3

1.8

2

.7

2.1

2

.5

1.6

2.2

2.1

8

68

Pip

a 7.1

9

2

1.7

2

.2

1.4

2

.2

2.4

1

.8

2.4

2.0

7

74

Pip

a 1.9

2.5

1

2.7

2

.6

2.1

1

.7

2.9

2.4

5

80

Pip

a 1

.9

2

1

2.3

2

2

.7

1.5

2.1

4

84 t

ota

l tr

ees

77

Am

on

i

20

45

N

W 3

30

°

3

Farm

er

Ele

vat

ion

Asp

ect

Wo

odlo

t #

44 X

33

S0

9°0

5'0

6.2

" E

03

3°2

5'5

8.6

"

31

/01/2

01

1

Lan

d (

m)

Lat

itu

de

L

on

git

ude

D

ate

Mea

sure

d W

oodlo

t

Tre

e #

Spec

ies

Db

h

Hei

ght

Ag

e S

pac

ing

(m

)

A

.T.S

. 3M

.R.

(cm

) (f

t)

1

2

3

4

10

C

ulu

1

.9

3

1

2.6

1

.9

2.3

2

26

P

ipa

1.9

2

1

2.3

2

.7

2.2

5

2.4

3

42

P

ipa

1.9

2

1

2.5

2.5

1

58

P

ipa

1.9

1

1

2.2

2.2

1

74

C

ulu

1

.9

3

1

2.1

5

2.5

2

.5

2.4

3

90

P

ipa

1.9

1

1

2.5

2

.5

2.1

2.4

3

106

Pip

a 1

.9

0.5

1

2

.3

2.4

3

2.6

3

122

Cu

lu

1.9

2

.5

1

2.6

2

.3

2.5

2

.1

2.4

4

138

Cu

lu

1.9

4

1

2.2

5

2.3

1

154

Pip

a 1

.9

2

1

2.4

5

2.4

2

.6

2.5

3

170

Pip

a 1

.9

3

1

2.2

5

3

2.3

2

.5

2.5

4

186

Cu

lu

1.9

3

1

2

2

2.9

2

.3

2.3

4

202

Pip

a 1

.9

2

1

2.8

5

2.6

2

.85

2.8

3

208 t

ota

l tr

ees

78

Lu

wole

2075m

NE

30°

1

Fa

rmer

E

levat

ion

Asp

ect

Wo

odlo

t #

18

X1

07

S09°0

4'2

4.1

" E

03

3°2

5'4

7.9

'

11

/12/2

01

0

Lan

d (

m)

Lat

itude

L

on

git

ude

D

ate

Mea

sure

d W

oo

dlo

t

Tre

e #

Spec

ies

Dbh

H

eight

Ag

e S

pac

ing

(m

)

A

.T.S

. 3

M.R

.

(cm

) (f

t)

1

2

3

4

5

6

7

8

9

10

9

Eusa

10.9

14

2

2.8

1

.1

2.4

2.1

3

47

E

usa

11.4

15

2

0.6

0

.6

1.8

2

1.3

4

85

C

ulu

29

20

8

2.6

5

2.2

1

.1

1.6

5

1.5

1

.5

2.4

5

2.9

3

1.6

2.1

10

12

3

Pip

a 1.9

1

0.5

15

3 t

ota

l tr

ees

79

Lu

wole

2057m

NE

30°

2

Farm

er

Ele

vat

ion

Asp

ect

Wo

odlo

t #

19X

29

S

09°0

4'2

4.5

" E

03

3°2

5'5

0.8

'

11

/12/2

01

0

Lan

d (

m)

Lat

itude

L

on

git

ude

D

ate

Mea

sure

d W

oo

dlo

t

Tre

e #

Spec

ies

Dbh

H

eight

Ag

e S

pac

ing

(m

)

A.T

.S. 3M

.R.

(cm

) (f

t)

1

2

3

4

5

6

7

8

9

1

Culu

1.9

2

2

2

.5

1.6

2.1

2

7

Culu

1.9

3

3

2

1

.4

2.9

2.1

3

13

Culu

1.9

3

3

0

19

Culu

1.9

2.5

2

2

.1

2.4

2.3

2

25

Culu

1.9

2.5

2

2

.5

2.6

2

.2

2.4

3

31

Culu

1.9

5

3

2

.7

2.8

2

.1

2.6

2.6

4

37

Eusa

(st)

6.4

15

2

0

.1

0.1

0

.2

0.3

5

0.5

2

.4

0.1

2.3

2.9

1.0

9

43

Culu

1.9

1

1

1

.4

2.9

2

.4

2.2

3

49

Eusa

(st)

19.6

20

3

0

55

Culu

1.9

6

3

1

.9

2

2.0

2

61

Culu

1.9

2

2

1

.6

2.7

2

.1

2.1

3

67

Culu

1.9

1.5

2

2

.1

0.6

1.4

2

72 t

ota

l tr

ees

80

Lu

wole

20

53

m

N

E 4

5°

3

Farm

er

Ele

vat

ion

Asp

ect

Wo

odlo

t #

8.5

X23

S

09

°04

'24

.5"

E0

33

°25

'51

.9'

1

9/1

2/2

01

0

Lan

d (

m)

Lat

itu

de

L

on

git

ude

D

ate

Mea

sure

d W

oodlo

t

Tre

e #

Spec

ies

Db

h

Hei

ght

Ag

e S

pac

ing

(m

)

(cm

) (f

t)

1

2

3

4

5

6

7

8

1

Eusa

4.6

9

7

2.7

2

.8

5

Culu

9.4

1

2

0.5

1

.05

1.1

2

.2

2.9

2.2

0.9

5

1.9

2.7

9

Eusa

15

.2

25

4

2.1

2

.1

2.0

5

2.9

5

2.6

2.5

0.7

2.5

13

E

usa

10

.7

16

2

1.8

5

0.8

5

1.7

2

.65

2.0

5

2.7

1.3

2.0

17

E

usa

9.1

1

5

2

1.3

2

0

.7

1.5

2.5

2.4

2.5

3.0

21

E

usa

9.9

1

5

2

1.7

2

.3

1.4

1

.75

2.5

1.6

2.9

25

E

usa

14

.2

22

3

0.8

5

1.6

2

2

.5

1.8

5

2.1

2.9

1.1

29

E

usa

13

.2

19

3

1

1

1

2.3

2.7

2.2

5

2.1

1.0

33

E

usa

1.9

6

1

34 t

ota

l tr

ees

*C

onti

nued

on n

ext

pag

e

81

Tre

e #

Sp

acin

g (

m)

A

.T.S

. 3M

.R.

9

1

0

11

1

2

13

1

2

.8

2

5

1.4

2

.9

2.9

2

.0

11

9

2.9

5

2.3

1

.75

2.2

11

13

2.5

0

.7

1

1.8

1.8

12

17

1.1

1

.7

2.2

2

.3

2.5

2

.0

13

21

2

.0

7

25

1

.9

8

39

1

.7

8

33

0

0

*C

on

tin

ued

fro

m p

rev

iou

s pag

e

82

Lu

wole

20

68

m

S

W 2

25

°

4

Farm

er

Ele

vat

ion

Asp

ect

Wo

odlo

t #

54X

10

S

09

°04

'32

.5"

E0

33

°25

'47

.1'

1

7/1

2/2

01

0

Lan

d (

m)

Lat

itu

de

L

on

git

ude

D

ate

Mea

sure

d W

oodlo

t

Tre

e #

Spec

ies

Db

h

Hei

ght

Ag

e S

pac

ing

(m

)

(cm

) (f

t)

1

2

3

4

5

6

7

8

8

Eugl(

st)

3.0

6

1

2.9

2

.5

1.4

0

.5

0.5

2.9

2.8

2

19

E

ugl(

st)

4.8

9

1.5

1

.3

0.8

2

.7

0.7

30

E

ugl(

st)

2.8

6

1

0.3

2

.5

0.2

1

.6

1.9

2.1

2.1

1.4

41

E

ugl(

st)

4.1

8

1

0.2

0

.45

0.4

2

.7

2.7

5

2.8

1.9

2.1

52

E

ugl

63

.2

60

8

1.6

1

.5

2.2

2

.15

2.5

2.6

2.2

2.2

63

E

usa

16

.5

25

4

1.8

2

.1

74

E

usa

14

.2

17

3

1.7

2

.4

85

P

eam

36

.6

28

3

1.9

5

1.4

2

96

E

usa

8.6

1

1

1.5

107

Eusa

17

.5

30

4

0.2

5

0.4

0

.45

0.3

5

0.5

5

1.6

3

118

Culu

13

.5

19

7

1.3

2

.4

1.2

1

.4

129

Eusa

11

.9

16

3

2

129 t

ota

l tr

ees

*C

onti

nued

on n

ext

pag

e

83

Tre

e #

Sp

acin

g (

m)

A

.T.S

. 3M

.R.

9

10

11

12

1

3

8

2.9

2

.7

2.4

1

.4

2

.1

12

19

1

.4

4

30

1.7

1

.8

0.3

2

.6

1.2

1

.5

13

41

2.3

1

.9

2.6

1

.8

11

52

2

.1

8

63

2

.0

2

74

2

.1

2

85

1

.8

3

96

0

0

10

7

0

.9

7

11

8

1

.6

4

12

9

2

.0

1

*C

on

tin

ued

fro

m p

rev

iou

s pag

e

84

Yis

ega

2

02

5 m

90

°

1

Farm

er

Ele

vat

ion

Asp

ect

Wo

odlo

t #

20 X

43

S 0

9°

04' 4

6.1

" E

033

° 2

5'2

5.5

"

9/1

2/2

01

0

Lan

d (

m)

Lat

itu

de

L

on

git

ude

D

ate

Mea

sure

d W

oodlo

t

Tre

e #

Spec

ies

Db

h

Hei

ght

Ag

e S

pac

ing

(m

)

(cm

) (f

t)

1

2

3

4

5

6

7

8

4

Pip

a 2

2.1

2

0

5

2.1

2

.3

2.4

14

E

usa

(st)

3.8

1

0

1

2.5

0

.25

0.2

5

0.2

5

2.6

2.7

1.6

1.6

24

E

usa

(st)

10

.2

16

2

0.5

0

.5

0.2

0

.5

0.7

0.7

5

0.6

1.7

34

E

usa

(st)

1.9

6

1

0

.3

0.3

1

.8

2.1

2

.2

2.2

5

2.2

1.8

44

E

usa

4

8.5

3

5

6

2.8

1

.3

1.2

1

.5

1.5

1.7

1.1

1.2

54

E

usa

(st)

11

.4

14

2

1.3

0

.2

0.3

5

0.4

1

.7

2.7

2.2

1.3

64

P

ipa

19

.1

16

5

2.9

1

.6

1.6

1

.7

1.8

2.9

2.5

1.8

74

P

ipa

11

.4

18

5

0.6

2

.4

2.4

2

.8

84

P

ipa

21

.8

17

5

2.7

1

.1

1.9

94

P

ipa

17

.0

16

5

2.1

2

.7

2.1

2

.8

2.4

104

Pip

a 2

2.9

1

9

5

2.1

2

.1

2.2

2

.9

2.1

1.3

1.3

2.4

114

Pip

a 1

5.5

1

5

5

1.7

2

.8

2.6

1

.8

1.7

124

Pip

a 3

4.3

2

4

6

2.1

2

.9

2.4

2

.8

1.6

2.4

2

134

Pip

a 3

3.0

2

4

6

2.6

2

.5

2.6

1

.9

2.2

1.7

144

Pip

a 1

9.1

1

8

5

1.9

2

.4

1.7

2

.8

2.3

2.5

2.2

1.8

154

Eusa

1

.9

5

1

1

2.6

1

.8

1.5

3

2.2

1.4

2.6

164

Pip

a 1

.9

5

1

2.6

2

.3

1.8

2

.5

1.7

2.7

2.6

1.9

174

Pip

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2.7

1

4

5

1.7

2

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2.3

1

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2.2

1.1

2.2

2.8

184

Pip

a 6

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12

3

2.9

1

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2.4

2

.8

1.6

3

2.1

1.5

194

Pip

a 1

3.0

1

3

3

2.4

2

.8

1.9

1

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1.7

1.4

2.9

2.9

204

Pip

a 1

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6

1

1.6

3

1

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2.8

2

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2.7

214

Pip

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5

1

1.4

2

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2.6

2

1.8

2.1

222 t

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1

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34

1

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1

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9

44

1

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9

54

1

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1.7

2

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1

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11

64

2

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9

74

2

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10

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4

5

6

7

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2

Pip

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1

1

1.2

2

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1.5

1

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1.6

0.6

13

P

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1.9

2

1

2

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1.6

1

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1.4

2

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2

2.6

0.3

24

P

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1.9

5

3

2

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2

2.2

2

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0.9

2.1

0.8

2.8

35

P

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1.9

6

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3

2.2

2

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2.7

2

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2.9

46

P

ipa

1.9

3

1

2

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2.2

0

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1.4

1

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57

P

ipa

10

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12

4

2.2

2

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2.4

2

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2.7

1.5

2.9

68

P

ipa

1.9

2

1

1

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2.6

2

.1

2.7

2

.8

2.4

2.9

1.9

79

P

ipa

1.9

6

2

2

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1.5

3

2.5

2

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1.5

2.8

90

P

ipa

1.9

2

1

2

.1

2.9

2

.4

2

1.8

2.4

1.4

1

101

Pip

a 1

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1

1

2.9

1

.8

2.2

2

.9

2.3

2.3

2.8

112

Pip

a 1

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6.5

3

2

2

.3

2.1

2

.3

123

Pip

a 1

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4

2

1.9

1

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1.9

2

.9

1.8

1.3

1.8

134

Pip

a 1

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6

3

2.3

2

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0.9

2

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2.1

145

Pip

a 1

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4

2

2.3

2

1

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2.7

1

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2.9

156

Pip

a 1

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6

3

1.2

2

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1.5

2

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2.4

1.1

2.1

2

167

Pip

a 6

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8

4

2.6

2

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2.9

2

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178

Pip

a 1

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5

3

2.7

1

2

.4

2.3

1

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1.5

2

2.9

189

Pip

a 1

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2

1

2

2.7

1

2.4

1

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200

Pip

a 6

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9

3

2

2.6

2

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2.8

211

Pip

a 5

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8.5

4

1

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2.8

2

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2.9

2

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222

Pip

a 1

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3

2

1.5

1

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2.7

1

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1.6

2.1

1.3

2.9

233

Pip

a 1

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6

3

2

2.9

1

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2.4

2

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1.9

1.6

2.3

244

Pip

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8

3

1.5

2

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1

2.1

2

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1.6

1.3

2.9

255

Pip

a 1

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3

2

1.7

1

.8

1.5

1

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2.5

1.4

266

Pip

a 5

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8

4

2.9

1

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1.7

277

Pip

a 1

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3

1

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1.6

2

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2.9

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284 t

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2.4

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2.4

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2.8

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Spec

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6

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2.6

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56

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26

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2.6

2

75

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3

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5

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2.6

1

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78 t

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Jim

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Spec

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6

7

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1.7

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73

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3

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2

6

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2.5

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3

3

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195

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256

Culu

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14

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2.9

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2.9

1.8

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317

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378

Eusa

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2

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2

2.9

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2.5

2.4

0.6

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408 T

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12

13

1

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15

1

6

17

18

19

12

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73

2.3

1.3

2

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2.7

2.2

12

134

2.1

6

195

2.4

2.6

1

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2.4

2

.3

2.9

2.2

14

256

1.9

5

1.3

2

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2.6

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1.7

3

2

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2.2

1.2

5

2

2.1

19

317

2.3

1.1

5

2.5

5

2.6

2

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2.8

2

2

.8

2.4

16

378

1.1

1.3

5

2.6

1

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2.6

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2.2

1.9

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91

Jim

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Spec

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5

6

7

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14

C

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3

5.8

3

4

7

2

2.3

2

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1.5

2

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1.4

2.4

1.1

33

C

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2

2.9

2

5

7

2.7

3

3

2.4

2

1.9

2.8

52

E

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4

8.0

4

2

6

2.1

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1.4

1

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2.8

2.8

2.7

5

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71

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1

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1

5

7

2.4

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2.4

2

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3

2.4

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1.3

90

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usa

3

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6

5

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2.3

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93 t

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2

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7

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8

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93

Jim

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34

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6

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09°0

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6.7

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eight

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1

2

3

4

5

6

7

8

9

10

22

E

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1.9

2.5

1

2.5

1

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1.9

1

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1.3

2

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1.9

6

92

E

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1.9

1

1

1.6

2

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2.3

2

2

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1.4

2

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2.8

7

16

2

Culu

22.9

21

7

2.8

2

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2.8

2

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1.2

3

2

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1.8

3

3

2.6

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23

2

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2.5

2

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2.5

1

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2.6

2.6

2.5

2.1

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30

2

Eusa

10.2

16

2

2.5

2

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1.8

2

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1.5

1

2

.4

2.0

7

37

2

Eusa

5.8

18

2

2

2.2

3

1

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2.5

2

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2.3

6

44

2

Eusa

20.3

28

3

1.5

2

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2.3

2

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1.8

1

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2.0

6

47

8 t

ota

l tr

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94

Jim

Roger

2066m

NW

33

0°

3

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vat

ion

Asp

ect

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odlo

t #

36

X36

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09°0

4'4

6.9

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1

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1

2

3

4

5

6

7

8

9

21

E

usa

26.7

28

3

1.2

1

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1.6

2

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1.5

2

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2.9

2.2

2.1

8

47

E

usa

20.8

28

3

3

1.9

2

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1.7

2

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1.6

5

1.5

2.5

2.1

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73

E

usa

15.2

25

3

1.8

2

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2

2.3

2

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1.4

2.6

1.3

3

2.2

9

99

E

usa

17.8

30

3

2

1.6

0

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1.2

5

2.9

5

1.9

5

2.2

2.1

1.5

5

1.8

9

12

5

Eusa

11.4

14

2

2.1

5

2.6

1

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1.4

5

2.9

2

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2.5

2.6

1.9

2.3

9

15

1

Eusa

1.9

6

1

1.6

1

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2.1

1

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1.7

4

17

7

Eusa

1.9

4

1

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1

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1.3

2

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2.1

1

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2

1.9

7

20

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1

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1.6

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22

9

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1.9

4

1

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1

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1.8

1

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3

1.8

2.5

1.8

2.3

2.1

9

25

5

Eusa

6.1

9

2

1.7

2

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1.7

2

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2.6

1

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2.9

1.9

2.2

8

28

1

Eusa

8.6

12

2

1.7

1

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2.9

1

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2.6

1

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2

1.9

7

30

7

Eusa

8.1

13

2

2

2.2

1

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2.9

2

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1.6

2.4

1.8

2.3

2.2

9

33

3

Eusa

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1

1

1.8

2

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2.1

2

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2.4

1

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1.7

2.1

7

35

9

Eusa

1.9

0.7

5

1

2.2

2

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2.6

2

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2.6

2.4

5

36

5 t

ota

l tr

ees

95

Jim

Roger

2062m

SE

16

0°

4

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Ele

vat

ion

Asp

ect

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t #

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9

S

09°0

4'4

8.1

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03

3°2

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1.7

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15

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1

Lan

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m)

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itude

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ate

Mea

sure

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Spec

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t)

1

2

3

4

5

6

7

8

6

Eusa

1.9

2

1

2

1

2.4

2

1

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1.8

5

14

E

usa

3.6

6

2

1.4

3

2

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2.9

1

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2.4

2.3

6

22

E

usa

1.9

1

1

2.2

2

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1.1

2

.7

2.7

3

1.6

5

1.7

2.2

8

30

E

usa

4.6

8

2

2.5

2

3

1

.6

2.8

1

.6

2.2

1.7

2.2

8

38

E

usa

1.9

3

1

2.2

1

.9

2.8

2

.9

2.1

2

.85

2.5

6

46

E

usa

3.0

6

2

2.3

1

.4

2

2

1.7

2

1.3

1.8

7

54

E

usa

1.9

6

2

2

1

2.4

2

.6

1.7

1.9

5

62

E

usa

3.0

6

2

1.9

1

.7

2.9

2

.2

2.8

1

.5

2.9

2.1

2.3

8

70

E

usa

3.3

7

2

1.5

2

.1

1.4

2

.1

1.8

1

.9

2.4

1.9

7

76 t

ota

l tr

ees

96

Eli

as

20

59

m

S

18

0°

1S

ecti

on A

Farm

er

Ele

vat

ion

Asp

ect

Wo

odlo

t #

10X

36

S

09

°04

'29

.7"

E0

33

°25

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.2"

2

1/1

2/2

01

0

Lan

d (

m)

Lat

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de

L

on

git

ude

D

ate

Mea

sure

d W

oodlo

t

Tre

e #

Spec

ies

Db

h

Hei

ght

Ag

e S

pac

ing

(m

)

(cm

) (f

t)

1

2

3

4

5

6

7

8

11

E

ugl

27

.9

35

6

2

.6

0.5

5

0.8

1

.2

1.3

23

E

ugl(

st)

6.9

1

3

2

0.1

0

.4

0.7

0

.4

0.9

5

0.8

0.8

1.9

35

E

ugl(

st)

15

.7

24

4

1

.2

1.4

0

.7

1.9

5

2.1

2.6

2.8

1.4

5

47

E

ugl(

st)

4.8

1

0

2

1.6

2

.6

0.3

2

.1

2

2.5

1.1

5

1.5

59

E

ugl(

st)

11

.4

20

3

2

.75

2.8

2

.9

2.9

5

2.8

2.8

0.2

0.4

71

E

ugl(

st)

14

.7

30

5

0

.35

0.4

0

.5

1.2

1

.5

1.7

1.6

2.6

83

E

ugl(

st)

18

.0

33

5

0

.7

1.4

2

.8

1.9

5

2.2

2.1

1

1.3

5

95

E

ugl(

st)

3.0

6

1

0

.55

1.8

2

.1

1.5

0

.45

0.7

2

1.9

107

Eugl(

st)

16

.0

21

3

0

.25

2.5

2

.3

2.5

1

.6

1.6

5

2.8

5

1.2

119

Eugl(

st)

3.8

1

0

1

0.2

0

.25

1

1.6

5

2.5

2.3

2.5

2.5

5

131

Eu

gl(

st)

5.3

1

3

2

1.1

1

.3

2

2.4

2

.6

2.4

1.6

1.7

143

Eugl(

st)

17

.0

26

4

1

.15

2.4

0

.55

0.9

0

.7

0.9

1

1.3

5

144 t

ota

l tr

ees

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on n

ext

pag

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97

Tre

e #

Sp

acin

g (

m)

9

10

11

12

13

1

4

15

16

17

11

23

2

.4

2.2

5

2.4

35

1

.4

1.9

47

1

.7

1.5

1

.3

1.7

2

.2

2.4

2

.9

59

0

.4

71

2

.55

1.3

5

1.7

2

.65

1

2.7

1

.4

1.3

5

2.9

83

2

.7

2.7

5

1.8

1

.6

1.8

5

1.9

0

.5

1.4

5

1.7

95

2

.2

1.7

2

.2

2.6

2

.6

3

107

2.5

2

.85

2.6

2

.6

2.7

2

.9

1.2

1.8

1.5

5

119

1

1.3

2

.1

2.4

2

.45

2.2

2

.6

2.3

5

1.1

131

1

1.3

1

.5

1.9

2

.4

2

2.5

5

1.5

143

2.4

*C

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nu

ed f

rom

pre

vio

us

pag

e

98

Tre

e #

Sp

acin

g (

m)

A.T

.S. 3

M.R

.

18

19

20

2

1

22

2

3

11

1

.3

5

23

1

.2

11

35

1

.8

10

47

1

.8

15

59

2

.0

9

71

1

.1

1.5

2

2

.15

1.6

21

83

2

.2

2.3

2

.6

1

.8

20

95

1

.8

14

10

7

1.3

2.1

18

11

9

1

2.1

2

.4

2.4

2

.5

2.6

1

.9

23

13

1

1.8

16

14

3

1.3

9

*C

on

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fro

m p

rev

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99

Eli

as

20

58

m

S

18

0°

1 S

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on

B

Farm

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Ele

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Asp

ect

Wo

odlo

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10.8

X13.7

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33

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3

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01

0

Lan

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m)

Lat

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L

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ude

D

ate

Mea

sure

d W

oo

dlo

t

Tre

e #

Spec

ies

Db

h

Hei

ght

Ag

e S

pac

ing

(m

)

(cm

) (f

t)

1

2

3

4

5

6

7

8

4

Eugl(

st)

12

.7

20

3

0.5

5

1

2

0.5

1

.5

1.8

1.8

5

2.4

9

Eugl

6.4

1

2

2

2.6

5

2

2.1

1

.05

1.6

5

1.3

1.5

5

1.5

5

14

E

ugl(

st)

25

.9

32

4

0.3

0

.3

0.3

5

0.5

2

.25

1.6

5

1.3

1.4

19

E

ugl(

st)

10

.2

15

2

0.5

0

.5

0.3

0

.8

1.2

1.4

2.2

1.4

5

24

E

ugl(

st)

7.6

1

5

2

0.5

0

.45

1.9

1

.75

1.2

1.7

5

1.2

1.7

5

29

E

usa

(st)

7.1

1

1

2

0.4

0

.3

0.3

34

E

ugl(

st)

22

.1

27

4

0.5

2

.3

1.7

1

.7

2.5

2.6

2.9

1.7

39

E

usa

(st)

17

.8

24

4

0.6

2

.2

2.4

1

.75

2.1

1.6

1.9

1.8

5

44

E

usa

(st)

10

.2

15

2

0.4

1

.05

1.2

1

.05

2.2

2.3

0.9

0.7

49

E

usa

(st)

31

.5

35

5

0.5

1

.4

50 t

ota

l tr

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on n

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100

Tre

e #

Spac

ing (

m)

A

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. 3

M.R

.

9

10

1

1

12

13

14

15

1

6

17

18

19

4

2.5

2.5

1

1.5

1

.2

1.6

1.6

14

9

2.9

1.2

5

2.3

1.9

11

14

1.5

5

2.9

1

.7

1.3

11

19

1.6

2.1

1

.8

1.9

1

.75

2.2

1.4

14

24

2

2.9

2

1.1

1

.3

2.9

5

2.7

2

.4

1.8

1.8

1.6

5

1.7

19

29

0.3

3

34

2.2

2.3

3

2.1

2

.7

2.2

13

39

1.8

8

44

2.2

1.3

9

49

1.0

2

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rom

pre

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us

pag

e

101

Eli

as

20

54

m

S

W 2

00

°

2 S

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on

A

Farm

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vat

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Asp

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odlo

t #

16X

28

S

09

°04

'28

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E0

33

°25

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.5"

2

/1/2

01

1

Lan

d (

m)

Lat

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de

L

on

git

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D

ate

Mea

sure

d W

oodlo

t

Tre

e #

Spec

ies

Db

h

Hei

ght

Ag

e

(cm

) (f

t)

1

2

3

4

5

6

7

8

8

Eusa

6.9

1

1

2

2.9

3

1.2

2

2

.2

2.4

2.6

2.4

17

E

usa

1.9

7

1

1

.5

1.6

1

.9

1.7

1

.7

2.6

2.3

2

26

E

usa

(st)

24

.6

26

4

0

.25

1.1

1

.2

1.2

1

.7

1.6

35

E

usa

9.1

1

7

2

2.3

2

.2

2.2

2

.7

2.6

2.1

2.2

1.2

44

E

usa

(st)

44

.7

33

5

0

.45

0.5

0

.6

0.6

5

0.7

1.7

1.7

1.8

53

E

ugl

9.7

1

2

2

2

2.3

1

.4

2.4

2

.6

2.8

3

62

E

ugl

47

.0

36

6

64 t

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l tr

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on n

ext

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102

Tre

e #

Sp

acin

g (m

)

A

.T.S

. 3M

.R.

9

10

11

12

13

1

4

8

2.9

2.4

0

9

17

1

.5

1.5

1

.3

1

.78

11

26

1

.18

6

35

2

.19

8

44

1

.5

2.6

2

.9

2.6

2

.6

2.6

5

1.6

4

14

53

2

.36

7

62

0

0

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103

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2

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80

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Sec

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17X

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03

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4.0

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D

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Mea

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Spec

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Db

h

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Ag

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pac

ing

(m

)

(cm

) (f

t)

1

2

3

4

5

6

7

8

2

Pip

a 7

1.1

3

0

10

2

.4

2.9

8

Pip

a 8

7.1

4

0

40

1

.2

1.7

2

.75

14

E

usa

(st)

12

.7

20

3

0

.65

20

E

usa

(st)

12

.2

20

3

0

.35

0.5

0

.45

0.3

5

0.5

5

1.4

1.7

26

E

usa

7

6.2

4

0

7

2.8

1

.9

2

2.1

2.4

2.6

32

E

usa

5

.1

9

1.5

1

.3

2.8

2

.3

1.4

1.6

2.2

2.6

38

E

ugl(

st)

3.6

7

1

0

.1

0.5

0

.6

0.4

0.5

1.7

2.2

2.9

44

A

cme

1.9

6

2

1

.5

2

2.1

0

.2

1.4

3

2.6

2.9

50

A

cme

3.3

1

0

2

0.3

0

.3

0.3

5

0.7

1.2

1

1

2.5

56

A

cme

1.9

2

1

1

.9

2.1

2

.3

2.3

2.4

2.4

1.6

2

57 t

ota

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104

Tre

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Spac

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m)

A.T

.S. 3

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.

9

10

11

1

2

13

1

4

15

1

6

17

18

19

20

2

2.7

2

8

1.9

3

14

0.7

1

20

0.8

7

26

2.3

6

32

2.0

7

38

2

1.5

2.1

1.3

11

44

2.6

2.9

2.9

1

.2

1.1

1

1

1

.2

2

2.3

2.4

2.8

2.0

20

50

2.8

2.9

2.2

2

.2

2.9

5

1.8

2

.2

3

1.7

16

56

1.5

2.5

2.6

2

.8

2.2

12

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us

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105

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2

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3m

60

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Farm

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24X

22

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3

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m)

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Spec

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pac

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(m

)

(c

m)

(ft)

1

2

3

4

5

6

7

8

4

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4

2.7

3

2

8

1

2.8

2

.4

1.8

14

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40

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40

6

2

2.7

2

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1.7

1

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2.3

2

1.9

24

C

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1

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1

0.5

2

.4

2

2.6

2

2.2

2.5

2.4

2.6

34

E

ugl(

st)

12

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18

2

0.2

5

44

E

ugl

20

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33

4

2.2

2

.75

2.7

5

1.9

2

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1.8

2.2

2.3

54

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1

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1

1

0.2

0

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0.1

0

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0.7

0.8

0.8

0.4

64

E

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11

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18

2

0.3

5

0.5

0

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0.5

5

0.5

3

1.8

1.9

74

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10

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18

2

0.4

5

0.5

0

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1.7

2

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2.9

2.6

2.6

84

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st)

7.1

1

4

2

0.3

5

0.4

5

0.5

0

.75

2.3

2.6

2.7

2.6

94

E

ugl(

st)

4.6

9

1

0

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0.6

0

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0.7

5

0.9

5

1.0

5

3

2.1

104

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4.4

2

6

6

114

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17

2

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1

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116 t

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106

Tre

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m)

13

14

15

1

6

17

18

19

20

21

4

14

24

1

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1.7

1

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2.4

2

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2.3

1

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2.2

2.1

34

44

2

2

.3

2.4

2

.1

2.6

2

.8

2.4

2.8

2.7

54

1

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2.1

2

.5

2

2.5

1

.8

1.6

1.8

1.5

64

1

.3

1.9

1

.4

1.5

1

.4

1.8

2

.2

2.3

2.1

74

84

1

2

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94

104

114

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107

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acin

g

(m)

A

.T.S

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.R.

22

23

24

2

5

26

2

7

28

4

2.0

4

14

2.1

10

24

2

.7

2.3

22

34

0.3

1

44

1

.9

2.2

2

.3

2.3

24

54

1

.9

2

1.9

2

2

.1

2.3

2

.1

1.5

28

64

2

.4

2.1

2

.1

2.2

2

.4

1.7

26

74

1.8

9

84

1

2

.6

1.9

14

94

1.5

10

104

0 0

114

0.8

2

*C

onti

nu

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rom

pre

vio

us

pag

e

Documents

SMALL-SCALE TIMBER STAND MANAGEMENT TECHNIQUES: A …