1. The document analyzes smallholder timber farming systems (STS) in West Java, Indonesia. STS account for over 50% of land in Ciamis Regency and contribute significantly to the local economy. 2. The study finds correlations between levels of timber extraction and household income/land size. Poorer households with smaller land sizes practice selective cutting and harvest trees for immediate income needs, while better-off households clear cut and reinvest profits. 3. The study concludes that land ownership and off-farm income determine the economic yield from forests. Small land sizes and low incomes limit poorer households' forest management practices and ability to sustainably utilize forest assets.

1. management strategy of smallholder timber farmers in
West Java, Indonesia
M. Siarudin
Forestry Research and Development Agency (FORDA)
Ministry of Forestry, Republic of Indonesia 1
WORLD CONGRESS ON AGROFORESTRY
Delhi, 2014

2. 2
Smallholder Timber System (STS) in Java Island
paddy field
STS
fishpond
traditional agricultural land useIrrigated/wet landdry land
(see app. 1.a)
• Land size: small scale forest: < 5 ha/household
Average = 0.3 ha (0.01 – 2 ha)
• Location: 0 - > 2 km
• Management: family/individual based

3. BACKGROUND
• The largest STS in West Java
Province, (124,430 ha; 50.9 % of
total area of Ciamis Regency) [4;11]
• More timber is cut and sold in STS
than the state forest[5]
(app. 1.b)
• Triggering local economic
development-transaction value
17 million USD/year
800s small scale saw mill industries[5]; 911 small to
medium scale of furniture and handicraft[10]
3
STS development in Ciamis
Regency
STS
State forest

4. PROBLEM
4
Problem statement
Many landowners/forest owners are typically rural
poor households and do not get significant return
from their forest assets
Preliminary observation: Despite high value of timber on
the market, the poor landowners receive extremely low
income from timber (about 12 USD annually) (see app.2)

5. QUESTIONs and RESEARCH OBJECTIVEs
5
Questions
Objectives
• To identify household and farm characteristics that
become key in the STS enterprise
• To explore how those characteristics are related to
the pattern of forest extraction and management
• What are the key factors for the farmers to get
significant benefits?
• How do those factors affects the forest
utilisation and management pattern and the
outcome?

6. HYPOTHESIS
6
There are different patterns of forest utilisation and
management among different level of socio-economic groups,
due to different level of their capabilities in functioning the
forest assets.
This leads to the poor households receiving inadequate income
from their forest asset.

7. RESEARCH LOCATION
 Research site
Cipaku sub-district
Cijeungjing sub-district
Bunesuri village
Utama village and Bojongmengger
village
7
(see app. 3)

8. RESEARCH METHOD
Fieldwork Time frame: February- September 2011
Data
collection
method
• Questionnaires and in-depth interview = 59
landowners (25 better-off households and 34
poor households) (see app. 4)
• In-depth Interview to key persons =
head of villages (3), government officials (2),
community leaders (3)
• Observation
Focus of
exploration
- Household and farm characteristics:
household income, family size, education attainment, age of
household head, land size, distance of forest to house
- Timber extraction: earning from timber, number of tree
harvested, volume of timber harvested
- Forest utilization and management patterns:
harvesting system, use of on-farm income, forest regeneration
system 8

9. FINDING 1: Link: STS and household attributes
Correlations
1 .954** .724** .237 .348** -.235 -.034 .020 .680** .488** .784** -.126
.000 .000 .070 .007 .073 .797 .880 .000 .000 .000 .368
59 59 59 59 59 59 59 59 54 53 53 53
.954** 1 .758** .171 .123 -.122 -.020 -.006 .692** .520** .785** -.073
.000 .000 .195 .355 .359 .883 .965 .000 .000 .000 .604
59 59 59 59 59 59 59 59 54 53 53 53
.724** .758** 1 .302* .137 -.178 -.037 -.029 .805** .734** .836** .028
.000 .000 .020 .302 .176 .782 .827 .000 .000 .000 .844
59 59 59 59 59 59 59 59 54 53 53 53
.237 .171 .302* 1 .406** -.524** .333* -.096 .063 .026 .114 -.140
.070 .195 .020 .001 .000 .010 .469 .650 .852 .415 .317
59 59 59 59 59 59 59 59 54 53 53 53
.348** .123 .137 .406** 1 -.450** -.038 .066 .172 .118 .191 -.315*
.007 .355 .302 .001 .000 .775 .617 .212 .399 .172 .022
59 59 59 59 59 59 59 59 54 53 53 53
-.235 -.122 -.178 -.524** -.450** 1 -.187 .261* -.027 -.004 -.143 .136
.073 .359 .176 .000 .000 .155 .045 .847 .976 .306 .332
59 59 59 59 59 59 59 59 54 53 53 53
-.034 -.020 -.037 .333* -.038 -.187 1 .097 -.055 -.053 -.063 .032
.797 .883 .782 .010 .775 .155 .464 .692 .707 .655 .822
59 59 59 59 59 59 59 59 54 53 53 53
.020 -.006 -.029 -.096 .066 .261* .097 1 .107 .055 .050 .111
.880 .965 .827 .469 .617 .045 .464 .441 .697 .725 .429
59 59 59 59 59 59 59 59 54 53 53 53
.680** .692** .805** .063 .172 -.027 -.055 .107 1 .890** .927** .041
.000 .000 .000 .650 .212 .847 .692 .441 .000 .000 .771
54 54 54 54 54 54 54 54 54 53 53 53
.488** .520** .734** .026 .118 -.004 -.053 .055 .890** 1 .772** .050
.000 .000 .000 .852 .399 .976 .707 .697 .000 .000 .722
53 53 53 53 53 53 53 53 53 53 52 52
.784** .785** .836** .114 .191 -.143 -.063 .050 .927** .772** 1 .024
.000 .000 .000 .415 .172 .306 .655 .725 .000 .000 .863
53 53 53 53 53 53 53 53 53 52 53 53
-.126 -.073 .028 -.140 -.315* .136 .032 .111 .041 .050 .024 1
.368 .604 .844 .317 .022 .332 .822 .429 .771 .722 .863
53 53 53 53 53 53 53 53 53 52 53 53
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Pearson Correlation
Sig. (2-tailed)
N
Household income (Rp)
Income per capita
(Rp/person)
Land ownership
education attainment
(y ear)
f amily size
age of household (year)
distance of f orest f rom
house (km)
f requency of harvesting
(times)
number of tree harvested
v olume estimation of tree
harvested (m3)
earning f rom tree
harvested (Rp)
percentage of earning
f rom tree harvested to
total income (%)
Household
income (Rp)
Income per
capita
(Rp/person)
Land
ownership
education
attainment
(y ear) f amily size
age of
household
(y ear)
distance of
f orest f rom
house (km)
f requency of
harvesting
(times)
number of
tree harv ested
v olume
estimation of
tree harv ested
(m3)
earning f rom
tree harv ested
(Rp)
percentage of
earning f rom
tree harv ested
to total
income (%)
Correlation is signif icant at the 0.01 lev el (2-tailed).**.
Correlation is signif icant at the 0.05 lev el (2-tailed).*.
Correlation among variables
timber extraction is:
• correlated to off-farm income
(household and per capita) and to
land size
• not correlated to education
attainment of household head,
family size, age of household head,
or distance of forest from house

10. FINDING 1: Link: STS and household attributes
Regression
R = 0.84, R2 = 0.699
R = 0.78, R2 = 0.617
the rate of earning from timber can be explained by land
size and off-farm income
Land size (ha) Off-farm income
Earningfromtimber(Rp/10years)
Earningfromtimber(Rp/10years)

11. FINDING 1: Link: STS and household attributes
-
0.50
1.00
1.50
2.00
2.50
3.00
forest land ownership (ha)
Percapita income (x10,000 Yen)
land size 0.08 Ha
better-off households: poor households:
23.7 USD/month/personOff-farm income
Mostly (66.67 %) from purchasing Mostly (74.29 %) from inheritance
Feature of initial assets: off-farm income and forest land
0.55
78
How this condition relate to the pattern of forest utilisation
and management?
Off-farm income (x100 USD)
STS land ownership (ha)

12. FINDING 2: Forest utilization patterns & management
1. Timber harvesting pattern
Among them (25 %) practice clear cutting Mostly (82.9 %) practice selective cutting
Harvest timber with normal rotation
(harvest timber when the tree is ready/big diameter)
Harvest timber with “by need” rotation
(harvest timber when they need urgent income/
small diameter)
Large number of trees
and higher price
small number of trees
and lower price
(See app. 7)
12
clear cutting
selective
cutting
Better-off Poor

13. 65.2
13.0
4.3
4.3
13.0
0.0
0.0
0.0
0.0
0.0
0.0
29.4
17.6
0.0
5.9
5.9
5.9
5.9
5.9
5.9
5.9
11.8
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
percentage(%)
Expenditure of cash income from selling timbers
the poor
the better-off
FINDING 2: Forest utilization patterns & management
(cont.)
2. Different use of cash income from timber
For capital investments
(children’s school, buy new land, cost re-plantation)
Mostly (65.2 %)
for immadiete consumption
(food)
Expansion of assets and
production survival
13
Better-off Poor

14. FINDING 2: Forest utilization patterns & management
(cont.)
Usually buying nursery transplant
(20.8%) or combination of nursery
transplant and natural seedling (66.67%)
Mostly (54.29 %) using natural
seedlings or/and re-grow from root
3. Forest regeneration pattern
Better forest culture techniques (usage of improved genetic-
seedling, regulated plantation spacing, maintenance etc.) can result in
better wood quality and its price (Punches, 2004; Haygreen and
Bowyer, 1996)  only the better-off afford to do this
transplant with seed from nursery re-grow from rootrely on natural seedlings
(See app. 8)
14
Better-off Poor

15. CONCLUSIONs
• Land ownership and off-farm income level are the key
determinants for significant yield of forest utilization.
• Small landownership (natural capital) combined with
low income (financial capital) cause the poor
households’ utilisation and management pattern on
their forest asset do not result in better return.
15
Expected outcome:
Policy implications: can be bases for appropriate policy
formulation for the poor as the main target in order to achieve
rural sustainable livelihood

16. Thank you for your attention..
16
“If immediate livelihoods are a priority of the poor,
sustainability is a priority of the enlightened rich”
(Chambers, 1986:10)
Special thanks to:
Lynn Thiesmeyer, M. Umegaki,
J. Roshetko, B. Lusiana
for your inputs

17. • Promote multi sector partnerships with smallholders
 Shifting the individual management to collective
management to reduce cost and risk and enhance
benefits
 Parties: large landowners, smallholders, landless
farmers, investors, governments/NGOs
• diversification of income from forest
 to create various sequences of income
 promote non-timber/multipurpose tree species (MPTS)
to mix with timber species
Further consideration for local government policy
17

18. STS utilization and
management
Different level of
capability
not meet short
term income need
not concern to
forest asset
The Poor The Better-off
• Selective cutting
• “by need” rotation
• Spent money for
immediate
consumption
• Poor reforestation
techniques
• clear cutting
• normal rotation
• Spent money for
capital investment
• Better reforestation
techniques
survival
Expansion of asset
and production
Collective
management
Income
diversification
not sustainable/
Loss of resource
Framework of Conclusion
proposals

19. Bibliography
1. Chambers, R., and G.R. Conway, 1991. Sustainable rural livelihood: practical concepts for 21th century. Discussion paper 296.
Institute of Development Studies.
2. Chambers, R., 1986. Sustainable livelihoods: an opportunity for the World Commission on Environment and Development.
Institute of Development Studies. University of Sussex, UK.
3. Ciamis Forestry Office, 2011. Kebijakan Pembangunan Kehutanan dan Perkebunan Kabupaten Ciamis. Slide Presentation on
Forum SKPD Dinas Kehutanan dan Perkebunan Kabupaten Ciamis. Local Government of Ciamis Regency.
4. Ciamis Forestry Office, 2010. Masukan/Penjelasan terhadap Raperda RTRW Kabupaten Ciamis 2010-2030. Local Government of
Ciamis Regency.
5. Ciamis Forestry Office, 2009. Strategic Plan of Ciamis Forestry Office. Local Government of Ciamis Regency.
6. Dorward, A., S. Anderson, S. Clark, B. Keane and J. Moguel, 2001. Asset Functions and Livelihood Strategies: a Framework for Pro
Poor Analysis, policy and Practice. CONTRIBUTED PAPER TO eaae Seminar on Livelihoods and Rural Poverty.
www.nda.agric.za/docs/AAPS/Articles/Goats/.../R7823%20(02).pdf. Accessed in January, 24th, 2011.
7. Harrison, S.R, J.L. Herbohn, and A.J. Niskanen, 2002. Non-industrial, Smallholder, Small-scale and Family Forestry:What’s in a
Name?. Journal of Small-scale Forest Economics, Management and Policy, 1(1): 1–11.
8. Haygreen, J.G. dan J.L Bowyer, 1966. Hasil Hutan dan Ilmu Kayu. Terjemahan Sutjipto A.H. Gadjah Mada University
Press, Yogyakarta.
9. Hindra, B., 2006. Potensi dan Kelembagaan Hutan Rakyat. Prosiding Seminar Hasil Litbang Hasil Hutan: “Kontribusi Hutan Rakyat
dalam Kesinambungan Industri Kehutanan”. Pengembangan Hasil Hutan. Pusat Penelitian dan Pengembangan Hasil Hutan. Bogor.
P14-23.
10. ITCOC (Industry, Trade and Cooperative Office of Ciamis Regency), 2009. Potensi Industri di Kabupaten Ciamis.
11. Ministry of Forestry, 2009. Potensi Kayu dan Karbon Hutan Rakyat di Jawa Tahun 1990-2008. Balai Pemantapan Kawasan Hutan
Wilayah XI Jawa-Madura dan Multistakeholder Forestry Program.
12. Ministry of Forestry, 2004. Potensi Hutan Rakyat Indonesia 2003. Pusat Inventarisasi dan Statistik Kehutanan, Departemen
Kehutanan and Direktorat Statistik Pertanian, Badan Pusat Statistik.
http://www.dephut.go.id/INFORMASI/BUKU2/PHRI_03/PHRI_03.htm. Acessed in November 25th, 2010.
13. Punches, J., 2004. Tree Growth, Forest Management and Their Implication for Wood Quality.
http://www.forestandraadeasia.org/doc_hit.html . Diakses pada tanggal May, 9th 2011.
14. Statistic Centre Bureau of Ciamis Regency, 2008. Analisis Kemiskinan Kabupaten Ciamis Tahun 2008 (Poverty Analysis in Ciamis
Regency Year 2008). Ciamis
15. Statistic Centre Bureau of Ciamis Regency, 2010. Ciamis dalam angka (Ciamis in figure) 2010. Ciamis
16. Huvio, T., J. Kola and T Lundstrom (ed), 2004. Small-Scale Farmers in Liberalised Trade Environment. Proceeding of the Seminar
on October 2004 in Haikko Finland. University of Helsinki, Departmen of Economics and Management. Publications no 38. 19

20. Appendix 1.a
Formal definition of STS
Forest that grows at private/right land (Law no 41/1999)
+ Forests that grows at private land and are covered by > 50 % of tree vegetations, or
minimum 500 trees/ha (Ministry of Forestry Decree No 49/Kpts-II/1997)
+ Forest that grows at private land and are dominated by tree vegetations (Ministry of Forestry
Decree No. P 26/Menhut-II/2005)
Terminology used in some journals:
farm forest, non-industrial forest, smallholder forest, small scale forest, family forest, community
forest (Harrison at al, 2002)
Government policy
- National government has contributed the development of STS through some financing
support such as subsidy, micro-credit for STS, reforestation fund, and national
movement for forest and land rehabilitation program (Gerakan Nasional Rehabilitasi
Hutan dan Lahan/GNRHL). However the development of STS are dominated (62%) by
self financing (Hindra, 2006).
- Local government of Ciamis regency reports to give seedling aid to landowners about
1 to 2 million seedling annually (Forestry Office of Ciamis Regency, 2011)
20

21. Appendix 1.b
21
2005 2006 2007 2008 2009 2010
local government's aid 1,127,200 415,000 873,492 521,250 2,126,610 2,155,488
self financing 1,250,500 2,561,728 6,304,920 5,480,765 3,560,848 4,069,999
-
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
numberoftreeplanted(tree)
tree plantation in SSFF
Tree plantation and timber production in Ciamis Regency
Source: Forestry Office of Ciamis Regency, 2011
-
100,000
200,000
300,000
400,000
500,000
2003 2004 2005 2006 2007 2008 2009
2010
annualtimberproduction(m3)
comparison of timber production from SSFF and state forest
SSFF
State forest

22. assets
people
activities
outcome
SSFF land
Financial capital
The poor
The better-off
Forest extraction
Forest management
Cash income
Immediate consumption
Livelihood components
(Chambers and Conway, 1991): Case study:
Sustainable rural
livelihood
Sustainable
development
Poverty
reduction
Rural poverty
reduction
Research frameworkAppendix 1.c

23. 23
wealth status
earning from timber harvesting (Yen/year)*
average min max
the poor 1,216.67 150.00 4,050.00
the better-off 6,031.30 500.00 25,000.00
all respondents 3,306.03 150.00 25,000.00
Value of earning from timber harvesting
Note: * this value are average from total earning during the last 10 years.
The average frequency of harvesting are 2-3 times during that period.
want more land
7%
want aid in form of
capital for forest
enterprise
7%
want aid inf form of
seedling
8%
get better earning
from forest
29%
forest can be better
managed
3%
next generation
willing to manage
forest
5%
next generation
can get benefit
from his forest
2%
government
more serious in
supporting SSFF
5%
Do not know
34%
Expectation of respondents towards SSFF
Appendix 2
Value of earning from timber harvesting and expectation

24. Appendix 3
Characteristic of research site:
Buniseuri
village
Utama village
Bojongmengger
village
Total area (ha) 422.22 224.79 635.55
Number of citizen (person) 7573 3510 6004
male 3776 1802 3001
female 3797 1708 3003
Population density (peron/ha) 17.94 15.61 9.45
distance from capital district (km) 12 3 10
altitude (meter above sea level) 285 124 240
topography hilly flat flat and hilly
wetland farming (paddy field) 151 60.919 21.5
dryland farming (including private forest) 203.415 85.26 333.6
24
Source: Statistic Centre Bureau of Ciamis Regency, 2010
poor
22.39%
better-
off
77.61%
Ciamis Regency
poor
24.94%
better-
off
75.06%
Buniseuri village
poor
23.43%
better-
off
76.57%
Utama village
poor
21.86%
better-
off
78.14%
Bojongmengger village

25. 25
CONSUMPTION POVERTY CHARACTERISTICS
FOOD:
Fulfillment of 2100 calorie per capita per day
1. Meal frequency
2. the ability to
buy meat, chicken and milk
NON-FOOD:
clothing, housing and facilities, the cost of
education, health care, transport,
miscellaneous goods and services
1. ability to buy clothing per year
2. floor area
3. type of floor
4. type of wall
5. type of roof
6. source of clean water
7. type of lighting
8. sanitation facility
9. education attainment of household
head
10. employment status of household head
11. ability of health care
12. asset ownership
Characteristic of poverty
Government (Statistical Center Bureau) analyze the poverty line based on 14 criteria below:
In the process of measuring poverty line, government also included verification and public examination as a
part of poverty measurement by community themselves, using values and norm prevailed in the society.
Source: Statistical Center Bureau, Ciamis Regency (2008)
Appendix 4

26. 76%
24%
Gender of household head
male female
44, 75%
6, 10%
7, 12%
2, 3%
education attainment of household
head
ES
JHS
SHS
UG
Characteristic of respondents
Appendix 5
Note: * The wealth status is based on the classification set by Statistic Centre Bureau of Ciamis Regency in 2008 26
58%
42%
wealth status*
the poor the better-off
0
2
4
6
8
10
12
14
16
18
20-29 30-39 40-49 50-59 60-69 70-79 80-89
numberofrespondents(person)
Head of household by age

27. Farm
worker
15%
Farmer
34%
Trader
22%
Service
5%
Governmen
t employee
10%
Private
employee
10%
Freelance
worker
4%
main livelihood
Farm worker
3%
Farmer
19%
Trader
2%
service
7%
None
69%
complementary livelioods
average of
household
income
(US$/month)
average of
household
expenses
(US$/month)
Income-
Expenses
(US$/month)
Percentage of
Income -
Expenses to
total income
(%)
the poor 65.15 59.14 6.01 9.22
the better-off 274.83 130.36 144.48 52.57
-
50
100
150
200
250
300
Incomeandexpenses(RUS$/month)
household income and expenses
Characteristic of respondents
Appendix 5 (cont.)
27
3
1
6
-
1.00
2.00
3.00
4.00
5.00
6.00
7.00
average min max
numberoffamilymember(person)
famili size

28. 28
Appendix 6.b
Land tenure and regression analysis
R = 0.76, R2 = 0.574
74.29 20.00 5.71
0% 20% 40% 60% 80% 100%
1
land acquisition of the poor household
heritage purchase both heritage and purchase
33.33 37.50 29.17
0% 20% 40% 60% 80% 100%
1
land acquisition of the better-off household
R = 0.84, R2 = 0.699
R = 0.78, R2 = 0.617

29. 9
43
23
the poor the better-off total
respondent
number of tree harvested per
household during the last 10
years
6
28
15
the poor the better-off total
respondent
volume estimation of tree
harvested per household during
the last 10 years (m3)
34.3
2.9 2.9 2.9
57.1
28.6
11.4
17.1
5.7
37.1
0.00
10.00
20.00
30.00
40.00
50.00
60.00
need wood for
self use
trees have been
ready to harvest
plan to change to
other tree species
timber collector
offers to buy
need urgen cash
income
percentage(%)
reason for selling trees
the poor
the better-off
82.9
2.9 0.0
14.3
70.8
12.5 12.5
4.2
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
90.00
selective cutting clear cutting clear and selective
cutting
not yet
percentage(%)
percentage of respondent by type of cutting
the poor
the better-off
Appendix 7
Type of harvesting and reason for selling trees
29

30. 75.00
20.00
12.50
60.00
12.50
20.00
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
the poor
the better-off
plantation and maintenance activities
do by himself hire other farm workers both do by himself and hire other farm workers
Appendix 8
Post harvesting management
30
20.00
20.83
54.29
12.50
25.71
66.67
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
the poor
the better-off
forest regeneration technique
buying nursery transplant natural seedling seed and natural seedling
24,980.2
527,407.4
231,707.4
the poor the better-off all respondents
real cost spent for replanting and
maintenance per household
(Rp/household)
329,216.7
960,063.4
863,050.1
the poor the better-off all respondents
cost spent for replanting and
maintenance per hectare
(Rp/ha/household)