EOS Sustainability Office presentation during the International Conference on Biodiversity, Climate Change, and Food Security, 3 July 2013

1. The Valuation of Conservation Options
Versus Tropical Deforestation
1
Edmund Hoh,
Project Leader
Gunung Palung National Park , West Kalimantan, Indonesia.
International Conference on
Biodiversity, Climate Change,
and Food Security
3 July 2013

2. Outline
• Project Objectives
• Context
• Study Site
• Methods
• Data Collection
• Results & Discussions
• Conclusion
2

3. 30-Year Net Present Values
US$
Non-Timber Forest Products
Illegal Woodfuel Collection Ecotourism
Illegal Agriculture Biodiversity Credits
Bioprospecting
Illegal Logging
Carbon Credits
BAU Portfolio
GHG emissions
High in tons of CO2e Low
Project Objectives
Assess the economic case for reducing greenhouse gas
emissions (GHG) from deforestation in Gunung Palung
National Park.
Compares ‘Business As Usual’ (BAU)
high GHG emissions activities …
[hypothetical chart,
for illustration only]
… a Portfolio of low
emission alternatives
… versus
Frequently proposed
‘solutions’ but …
… are these viable
alternatives to
BAU practices?

4. Context – Deforestation & CO2 Emissions
4
bursts of faunal reproduction (Curran et al., 1999). Although 64% of Kalimantan’s land area
were allocated to production forest uses from 1967 to 1972, protected areas were delineated or
redrawn in 1984 and 1985 to maintain representative ecosystems and to be managed by the
government (MacKinnon et al., 1996). Since then, however, protected areas have experienced
concomitant threats from logging, forest fires, and conversions (Curran et al., 2004).
Nelleman et al. (2007) illustrated the extent of deforestation in this island and its projection
towards 2020 as depicted in Figure 2.1.
Figure 2.1. Extent of deforestation in Borneo 1950 – 2005, and its projection towards 2020
Rapid deforestation in Borneo:
Indonesia is the world’s third largest emitter of greenhouse gas,
accounting for 2.1 billion tons of CO2e in 2005.
bursts of faunal reproduction (Curran et al., 1999). Although 64% of Kalimantan’s land area
were allocated to production forest uses from 1967 to 1972, protected areas were delineated or
redrawn in 1984 and 1985 to maintain representative ecosystems and to be managed by the
government (MacKinnon et al., 1996). Since then, however, protected areas have experienced
concomitant threats from logging, forest fires, and conversions (Curran et al., 2004).
Nelleman et al. (2007) illustrated the extent of deforestation in this island and its projection
towards 2020 as depicted in Figure 2.1.
Source: Nelleman et al 2007; NCCC Indonesia GHG Cost Curve.
Project Site

5. Study Site – West Kalimantan, Indonesia
5
oRich in bio-diversity*
oHistory of empirical data
Gunung Palung National Park (GPNP) - 90 000ha.
*One of the most species rich parks, orangutan, clouded leopards, sun bears, others.
Credits: Google Earth
oAccess to local stakeholders
oHistory of illegal deforestation
HealthinHarmony.org
NatGeo
Edmund Hoh Edmund Hoh

6. Study Site – Illegal Deforestation @ GPNP
6
Illegal logging on the
edge of GPNP.
Credits: Edmund Hoh, 2011.
GoogleEarth
Over 9,000ha lost
within GPNP in 2002
(Curran et al 2004)
NatGeo Surrounding area slated for
palm oil developments.

7. Methods - Project Phases
7
Stakeholder
Buy-in
Model
Validation
Model
Design
• Project briefing to
key local
stakeholders
 Bupati.
 GPNP Admini-
stration .
 Ministry of
Forestry.
 Local
Community
and NGO’s.
• Literature review
of existing models.
• Meta architecture
design and key
modules.
• Mapping of socio-
economic drivers
and assumptions.
• Scenario
generation.
• Model feedback
from experts:
 Bogor
Agriculture
University.
 Centre for
International
Forestry
Research.
 UN FAO Forestry
Department.
Data
Collection
• Secondary research
+ literature data
gathering .
• Primary research
 EOS Household
Survey of
villages
surrounding
GPNP.
Findings &
Stakeholder
Review
• Interim results:
• Final results:
• Final stakeholder
discussions.
• Final publications.
Develop a valuation tool that allows for decision making
- valuation based on Discounted Cash Flow (DCF)

8. Methods - Model Design, meta architecture
Toggles between scenarios, which
are based on 3 scenarios parameters
that drive the value levels of key
assumptions.
Calculates physical units in the model
for BAU (e.g. volume of timber extracted in m3)
and for Portfolio (e.g. CO2 emissions).
Scenario Layer
Physical Layer
Economic Layer
Output Layer
Calculates economic values for key
stakeholders by converting physical
units into values using prices, costs,
margins, etc.
Displays key model outputs via tables
and graphs.
8

9. Methods - Main Scenarios
9
Scenarios
Scenario
Parameters
Base Case Pessimistic Optimistic
Economic
Growth
Medium
Moderate Indonesian GDP
growth at ~5.5% p.a.
High
Strong economic growth
at 7% p.a., higher prices.
Low
Lower economic growth
at 4% p.a., lower prices.
Physical Impact
of Climate
Change
Medium
IPCC A1B scenario, 25%
reduction in crop yields by
2100, pro-rated annually.
High
Up to 40% rice yield
reduction by 2100.
Low
No reduction in rice yield
assumed.
Policy Support
for the
Environment
Medium
No change in CO2 emissions,
log extraction rates from
GPNP.
Low
Illegal logging
accelerates; no carbon
credit program.
High
Lower log extraction rate
in GPNP; 70% of CO2
results in credits.
Remarks
Most assumptions follow
historical trends.
Table shows assumption levels of scenario parameters for each scenario.

10. Data Collection - EOS Household Survey
10
255 households (HH) from 21 villages around GPNP and Sukadana were
surveyed in 2011 to obtain data on farming, logging practices, socio-economic.

11. EOS Household Survey – Profile of Loggers, GPNP
• Households (HH) income of active loggers was 22%
lower compared to non-logging HH’s.
• Had 20% fewer common HH assets.
11
Cash Income
& Assets
Motivation
& Perception
• Engage in logging due to lack of alternative jobs* (40%),
(perceived) higher income (58%).
• Willing to stop logging if there were alternative steady
higher paying jobs.
Other Illegal
Forest Activities
• Also tended to engage in other illegal forest
activities: land clearing for farming, woodfuel and
NTFP collection inside GPNP.
Active loggers tend to come from householders with significantly
lower incomes; driven by cash income needs.
*Health in Harmony survey: to pay medical bills
• 2.4% of the HH around GPNP may be actively logging, potentially representing ~250 HH’s.

12. EOS Household Survey – Logging Statistics
Survey data suggests that the current logging activity at GPNP
has fallen compared to historical data.
12
1991,1999: Hiller et al 2004.

13. EOS Household Survey – Estimated Deforestation Rates
13
Deforestation from illegal timber
extraction estimated at 11-24 ha,
potentially understated; 50ha assumed
(inclusive of land clearing for farming)
• Total Households = 250
• Members/HH = 1.04
• Ave team size = 6.6
• #teams = 39
• Trips/team = 1.7
• Total trips = 67 p.a.
• Timber/trip = 14 to 30 m3
• Total timber = 940 – 2000 m3
• Timber Yield = 50%
• Growing Stock (GS) = 1900-4000 m3
• GS density = 170m3/ha
• Calculated area cleared = 11 – 24 ha.
Deforestation rate at GPNP appears to have fallen significantly*.
*2011: EOS-MRI household survey in Oct 2011.
Subject to verification
e.g. by satellite imaging and
analysis, land surveys.

14. Outline
• Project Objectives
• Context
• Study Site
• Methods
• Data Collection
• Results & Discussions
• Conclusion
14

15. Results & Discussion
15
‘Business As Usual’ (BAU) :
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ alternatives:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products
Food Security implications

16. 16
Illegal Timber Module – Overall Demand
Annual TIMBER DEMAND
Potential in GPNP (m3)
Physical
Layer
Local* Demand (m3) External Demand (m3)
Population
Size
GDP
Growth Rate (%)
Indonesia Timber
Consumption
Indonesia Timber
Exports
Ave Per Capita
Consumption
(m3/person)
Annual
Deforestation Rate
in GPNP (ha)
Population growth
rate (%)
Literature Data
Market/other Data
HH-Survey
Calculated
Sawnwood + Panels + Pulp
Indonesia
Timber Production
Log extraction rate
from GPNP (%)
Growing stock
density (m3/ha)
Farmland
Demand (ha)
Indonesia
Timber Supply
Indonesia
Timber
Sub-Module
*Around GPNP

17. Timber Sub-Module – External Demand (Indonesia)
17
Indonesia Timber Supply
(m3)
Plantation Forests
Natural Forest (legal)
Natural Forest (illegal)
Others
Planting Rate *(ha/yr)
Deforestation Rate
& Forest Cover (ha)
Sawnwood
Panels
Pulp
Indonesia Timber Production
(m3)
Conversion
Factors
Indonesia Timber Consumption
(m3)
Ave Per Capita
Consumption
(m3/person)
Population
Size
GDP
Growth Rate (%)
Population
growth rate (%)
*7-8 years to harvest
Exports
(m3)
Industrial Roundwood
or ‘Logs’
Timber Products
Timber & forestry data obtained from various sources including
Ministry of Forestry (Indonesia), FAO, ITTO, others

18. Global Timber Industry
18
Industrial
Roundwood (logs)
Panels Sawnwood
(veneers)
Pulp
Paper & PaperboardSecondary Products
Hardwoods vs Softwoods
Woodfuel
Globally, 1.5 billion m3 of
logs produced in 2008.

19. Illegal Logging in Indonesia
19Source: A road map for the revitalization of Indonesia’s forestry industry, Ministry of Forestry (MoF) 2007. EOS estimated based on other sources.
Illegal logging
volumes fell
since the peak
in 2002-3.
0
10
20
30
40
50
60
2000 2005 2010
2010
EOS estimate
Manurung et al 2007
EOS estimate based on
recent FAO data using
similar methodology.

20. 20
Assumption - Timber Consumption Per Capita
Timber consumption
per capita tends to
increase with higher
levels of income.
(Bhati 2006)
Indonesia = 19 m3/1000
persons in 2010, assumed to
grow to 28m3/1000 persons by
2041 if GDP rises to US$12,000
per capita.Source: FAO
28
?!
Developed Economies
(e.g. US: 154, US$47,100)
45
EOS Base Case

21. 21
Indonesia Timber - Demand
Indonesia’s demand for logs could double over next 30 years
EOS timber projections output falls
within projections of other models.
UN FAO 2007; and CFPS (Ministry of
Forestry, Indonesia) 2008.
EOS Projections.
2x

22. 22
Indonesian Timber - Supply
Level of
illegal
logging may
depend on
potential
new supply
from forest
plantations.
Million m3
[sustainable?]
[achievable?]
EOS projections.
[competition
from palm oil?]

23. Illegal Timber – Projections for GPNP
This deforestation rate (ha) will be
used as the baseline projections for
the carbon credit calculations.
23EOS projections.
Implications:
Deforestation rate
at GPNP could
triple over the
next 30 years
144
m3 Ha
Assumes similar extraction rates

24. Log Prices
24
International log price have been increasing at about 4% p.a. for the last 30
years (up 3x), with two significant surges.
CAGR:
5.0% $455
4.0% $340
3.0% $250
Malaysian meranti hard logs, import price Japan, US$/m3. http://www.indexmundi.com
US$320, Feb 2013
US$100
US$500

25. Timber Pricing Value Ladder and Local Price Components
25
International Prices for Meranti logs, Japan in Dec 2011 (Source: IndexMundi);
Domestic – ITTO; Illegal Domestic prices - EOS estimate based on Obidzinski, 2003)
365
200
100
0
50
100
150
200
250
300
350
400
International
Prices
Domestic Prices Illegal Domestic
Prices
US$ / m3
Illegal Domestic Price Components (%)Pricing Value Ladder
Source: Estimates based on various studies including Obidzinski
(2003), Klassen, (2010), Yonariza (2007), EIA/Telapak.
Most of illegal logging proceeds goes to the financiers (‘cukong’) and ‘informal
payments’ to bribe takers; only a fraction goes to the villagers (as labor wages).
Extraction
Costs

26. Illegal Logging in Indonesia - a US$ 3 Billion Industry
26Note: International prices - Meranti logs, Japan cif (indexmundi). Domestic prices – ITTO.
Illegal logging
estimated at
~US$3 billion
in 2012.

27. Illegal Timber – NPV Results
• Base case NPV = ~ US$3.7m
(over 30 years @ 20% discount rate).
27
US$3.7m
Other stakeholders = takers of bribes
Rhett A. Butler, Mongabay, 2011.

28. Illegal Timber - Summary
Demand for timber in Indonesia may double over the next
30 years; log extraction rate may triple in GPNP.
• Illegal logging in GPNP driven by local and external
demand, and high profits.
• Illegal logging across Indonesia could be reduced if more
plantation forests are developed.
• Local loggers around GPNP tend to come from much poorer
households and get only a fraction of the proceeds; are
prepared to stop if there were alternative livelihood options.
• Deforestation at GPNP ~50ha in 2011, projected to triple over
next 30 years; base case NPV ~ US$3.7m.
28

29. Modules
29
‘Business As Usual’ (BAU) Activities:
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ Activities:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products
Food Security
implications

30. Illegal Farming in GPNP
30
Newly opened (illegal) land inside GPNP (2007)
Credits: Zamzani (2007)Credits: Ano Afuera (2011)
Lowland farm on the edge GPNP (2007)

31. 31
Physical
Layer
ILLEGAL VILLAGE
FARMLAND DEMAND (ha)
Average HH Size
(persons)
Annual HH Income
(Rp/mth)
Changes in HH Income (%)
Changes in
HH Size (%)
Population
Size
Growth Rate
(%)
Calorie Needs Per HH
(kCal/HH)
Food Needs Per HH
- By Category (kg/HH)
Food Crops Grown
(kg/HH)
Food Purchased
(kg/HH)
Cash Crops Grown
(kg/HH)
Land Productivity by Crop (kg/ha)
Cultivated Land Per HH (ha/HH)
Crop Mix
# or % of HH with land
inside GPNP per
village
# Villages around
GPNP
Crop Income
(Rp/HH)
Crop Costs
(Rp/ha)
Price Per Unit
(Rp/kg)
Food Expenses
(Rp/HH)
Inflation (% p.a.)
Net Crop Income
(Rp/HH)
2450kcal/
person/day
44kg/mth
/person
Literature Data
Market/other Data
HH-Survey
Calculated
i.e. area planted inside GPNP
If
Food Production
<
Food Needs
If
Cash Crop Income
>
Food Deficit Value
Yes
No
No change
in
planted area
Yes
Increase
planted area
No
Illegal Farming - Flowchart
*Impact of climate change on crop yields

32. EOS Household Survey – Farming Practices
At least 80ha being cultivated within GPNP, potentially more.
• Less than 3% of respondents admitted to having cleared land within the park, averaging 0.3ha.
• Main reason cited for clearing land or planting inside GPNP was for the income to feed the family.
32
• Crop Mix – mainly
rice, rubber, and some
palm oil, vegetables.
• Value of Crops - estimated
at ~Rp9 million per HH per
year (US$1,000)
• Costs - planting &
harvesting cost of Rp1
million.
B4. Crop Mix
Planted area
(m2)
Crop Mix
(as % of
area)
Ave #
harvest per
year
Claimed Yield
(kg)/season
orha
Adjusted
Est. Annual
Production
Qty (tons)
Unit Value
(Rp/kg)
Est. Total Value
(Rp)
Rice - upland 152,525 16% 1.1 660 30.0 5,944 178,615,249
Rice - lowland 407,787 43% 1.4 1,411 135.4 2,559 346,397,965
Cassava 1,300 0.1% 1.5 132 2.0 500 1,001,000
Vegetables 1,220 0.1% 2.7 113 - 3,500 -
Food Crops 562,832 167.4 526,014,214
Palm oil 40,070 4% 9.1 1,400 12,790,344
Rubber 338,855 36% 11.2 13,574 151,791,999
Others 512 0.1% - 1,000 -
Cash Crops 378,925 20.3 690,596,557
TOTAL 941,757 100% 187.8 1,216,610,770
Numberof HH's 136
Average 6,925 m2 (Rp/HH/yr) 8,945,667

33. Climate Change
33
Temperature Scenario’s
• The IPCC 2007 AIB scenario
projects a temperature
change of 2.5-3.0°C in
Borneo (EOS Base Case).
• In 2011, Hadley Centre
projected a potential
change of 6°C for Borneo by
2100.
 Increased weather
volatility, changes in season
timings.
Apsnet.org
Up to +6°C for Borneo by 2100.

34. Rice Yields
34
Source: Walker et al
A temperature rise of 2-3°C would
reduce grain yields by 7-25%
(Hundal and Kaur).
• With 6°C increase in
temperature, yield falls by
~40% (Walker et al).
• Fertility of rice falls from 90%
to 20% only after a 2 hour
exposure to temperatures
above 38°C (Yoshida).  risk of
sterility beyond this level.

35. Illegal Farming – Projected Food Production
• Potential food production deficit after 2025, but income from
(high value) cash crops (e.g. palm oil) projected to offset
shortfall value  no increase in planted area/HH inside GPNP.
35
0
100
200
300
400
500
600
700
2011
2013
2015
2017
2019
2021
2023
2025
2027
2029
2031
2033
2035
2037
2039
2041
Food Production Requirements vs Achieved
Food production achieved (tons)
Own food production requirements (tons)
Source: EOS projections. *Assumes a 25% decline in rice yields by 2100, pro-rated annually.
Production deficit
0
100
200
300
400
500
600
700
800
900
1000
0
2000
4000
6000
8000
10000
12000
2011
2014
2017
2020
2023
2026
2029
2032
2035
2038
2041
TonsRp'm
Value of Food Deficit & Cash
Crops
Food deficit volume (tons) [RHS]
Value of food deficit (Rp'm)
Value of cash crops(Rp'm)

36. Illegal Farming – Historical Rice Prices
36
Wholesale Rice Prices
30 years (US$/ton)
CAGR: 3.0%
Risk of steep rises in international price of rice in event of actual
production shortfall.
IndexMundi
Perceived shortage only, no actual
shortage in rice production volumes

37. Illegal Farming - Summary
Farming within GPNP by poor families, lack of land; risk of food
production deficit in future; cultivated area likely to increase.
• Those engaged in illegal farming within GPNP (<3% of HH, >80ha) tend
to be illegal loggers; farmers have relatively small plots
(0.6ha), significantly below province average (1.9ha).
• Potential rice yield reduction of 25% by 2100 due to climate change.
• Potential food production deficit after 2025, but income from cash
crops expected to neutralize risk of further land clearing.
• Cultivated area could increase from 80ha to 108ha over 30 years.
• Base case NPV of ~US$2.3m
37

38. Modules
38
‘Business As Usual’ (BAU) Activities:
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ Activities:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products

39. Annual Illegal
WOODFUEL
EXTRACTION (m3)
Non-Woodfuel HHKerosene
(MJ/litre)
Others
(MJ/kWH)
Cooking Energy Needs per HH
(MJ/HH/day)
Price Per Energy
Unit by Source
(Rp/unit)
Population Growth
Rate (%)
Changes in
HH Size (%)
Population Size
around GPNP
Changes in
HH Income (%)
Inflation (%)
BAU: Illegal Woodfuel Extraction
Average HH Size
(Persons / HH)
Literature Data
Market Data
HH-Survey Results
Calculated
Cooking Energy Needs
per Person
(18MJ/Person/day)
Woodfuel HH
Avg. HH Income
(Rp/mth)
Woodfuel
(15MJ/kg)
# HH around GPNP
39
Physical
Layer
Collected
Food-Income Distribution
(food expenses~ cooking
energy needs
Purchased
Cooking Energy Purchases (Rp/HH)
Kg to m3
conversion
Energy
Source
(Energy/unit)
Quantity
Required
(units)
Within GPNP
(kg/HH)
Outside GPNP
(kg/HH)
# & % of HH with illegal
woodfuel collection
43 kg/HH/mth

40. Illegal Woodfuel (WF) – Conclusion
40Credits: Allianz.Source: EOS 2011 Household Survey conducted by MRI, Indonesia.
Estimated woodfuel volume collected
annually potentially equivalent to 2ha …
… but not likely to result in actual
deforestation, according to experts*.
NPV = ~ $2m (based on
charcoal market prices as
proxy)
*Due to re-growth of
forest, dead limbs used.

41. Modules
41
‘Business As Usual’ (BAU) Activities:
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ Activities:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products

42. Carbon Credit Market
42
• Mandatory (or “Cap and Trade”), and the voluntary systems.
• The main market of the EU Emissions Trading Scheme traded volume was at 5.5 billion tons
CO2 in 2010, (accounts for 80% of global transacted volume).
• Reducing Emissions from Deforestation and Degradation (REDD) – voluntary.
• 20 million tons CO2 in 2010
Prices (Mandatory)
BlueNext CER Spot Prices (EUR)
Trading Volume
(Forestry)
Previous high of ~EUR35 in mid 2008

43. 43
Baseline
Deforestation
rate (ha p.a.)
Projected/Actual
Deforestation
Rate* (ha p.a.)
Reduction in deforestation*
(ha/yr)
Above ground growing
stock removed (tonnes/yr)
Growing stock density
(m3/ha)
CO2 content
(tonnes/m3)
Credits to
‘buffer’ account
CO2 available for carbon
credits to project (tonnes)
Verified CO2 emissions
reductions (tonnes)
Gross
Revenue for
carbon credit
project ($)
Carbon credit prices
($/tonne)
30%
~174 m3/ha
1.84 tonnes/m3
Carbon content
(tonnes/m3)
0.47x
3.67x
Literature Data
Market Data
HH-Survey Results
Calculated
*Resulting directly from the Emission
Reduction Activities of the carbon credit
project.
Historical
Deforestation
rate (ha p.a.)
Emission Reduction
Activities
Demand for Timber
Forestry Dept
Monitoring
Credits available for sale
by Project company
Third party
Physical
Layer
Carbon Credit Program
• Carbon standards, methodologies.

44. Carbon Credits – Assumptions & Projections
Carbon credit project possible only in the optimistic scenario
44
50 144
60
-
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
2…
2…
2…
2…
2…
2…
2…
2…
2…
2…
2…
2…
2…
Ha
GPNP Baseline & Projected
Deforestation Rate
Baseline Scenario Projections
EOS Projections
• Deforestation rates are projected need
to be lower that the baseline (reference
levels).
• Carbon credit prices are significantly
higher.
• Multiple challenges to overcome

45. Carbon Credits – Conclusion
• Currently not viable from project developer/investor perspective;
• Needs international treaty, and stronger prices.
45Credits: Arbre Billets
?
• Low NPV of US$0.6m comprising:
(a) $1.1 m to local community*, (b) -
$0.5m to investor/project
developer/government.

46. Modules
46
‘Business As Usual’ (BAU) Activities:
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ Activities:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products

47. Ecotourism Industry
47
• There were 7.7
million visitors to
Indonesia in 2011.
• Spent an average of
US$143/day over 8
days.
• 80% headed to Bali.
• Less than 8,000 to
West Kalimantan.
About 90,000 foreigners visited its 50+ national parks in
2009, where the top 5 sites accounted for 70 % of visitors.

48. Input Sought from Leading Operators
Borneo Adventure - Malaysia’s most established
inbound tour operators, which offers a range of
over 100 tours of Borneo.
• Local community
• Carrying capacity
• Attractions
Ecotourism in GPNP
• Low Traffic. In 2011, a total of 219
persons visited GPNP including
foreigners who numbered 119 , spent
an average of $138/person over 2 days.
• Monopoly at GPNP by Nasalis Tour &
Travel, limited marketing.
• Options:
(a) Increase marketing for existing
facilities,
(b) Develop higher priced mid-range
accommodation,
(c) Develop more attractions.
(d) Partner with larger player.
48
Credits: Edmund Hoh
Low traffic, basic
facilities, monopoly.

49. 49
Literature Data
Market/other Data
HH-Survey
Calculated
TOTAL DEMAND
(total stay-days)
# of arrivals in
GPNP annually
# of arrivals
West Kalimantan
# of arrivals
Indonesia
Growth rate tourist
arrivals(%)
Average Stay Days
Per Person
Capacity
# of lodges
No of operators
# Rooms/lodge
Occupancy rate
(%)
# Room Days
Available
Global Economic
Growth (%)
Visitors to
National Parks
BAU Existing
Ecolodge
‘Enhanced’ Mid
Range Ecolodge
[growth rate
in visitors to
GPNP]
Portfolio: Ecotourism in GPNP

50. Ecolodges – a study by IFC
Average
Number of rooms 11 - 35
Occupancy rates 30 – 67%
Daily Room Rates
- economical
- mid range
- luxury
($/day) % of Total (#)
< $60 73%
$61 – 200 18%
> $200 7%
Annual revenue > $100,000 to $3 million
No of staff per room 2
Operating costs
- personnel
- marketing & sales
22%
6-10%
Start-up costs $500,000 - $1 million
Ave cost per room $58,000
50
Source: International Finance Corporation, ‘Ecolodges: Exploring
opportunities for sustainable businesses’, 2004.
Key Success Factors
• No more than 1 hour from a local
airport, reasonable connection to
international gateway.
• Capable entrepreneurs, with sufficient
capital, good business plan.
• Cost < $60,000 per room.
• Well trained local staff with foreign
language skills, <2 staff per room.
• Long term community programs.
• Word of mouth, does not depend on
advertising.
• Part of a multi-lodge model, with
additional products and services.
Performance and impact varies widely, 10% growth expected, consumer
demand for certification not demonstrated, considered a risky market.
Survey of 15 enterprises, comprising 73 ecolodges located worldwide.

51. Ecotourism - Key Assumptions/Projections
51
GPNP can potentially support
a 3-room mid-priced
ecolodge, (potentially at expense of
existing ecolodge).
Range of
occupancy
rate for most
ecolodges
EOS Projections
Carrying Capacity

52. Ecotourism in GPNP - Conclusion
52
Breakeven is after 2 years, and base case NPV is estimated at S$0.7 million
with a new mid-priced ‘enhanced’ ecolodge.
• Investor’s base case IRR of 15% not that compelling.
• Marketing effort require, competition from the 50 other national parks.
At discount rate of 10%

53. Modules
53
‘Business As Usual’ (BAU) Activities:
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ Activities:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products

54. Biodiversity Credits - Approach
54Source: http://wwffm.org/wp-content/uploads/2012/06/journal.pone_.0038437.g001.png
The mitigation hierarchy is widely regarded as a best practice
approach to manage biodiversity risk.
• Efforts should first be made to
prevent or avoid impacts to
biodiversity.
• This should be followed by
minimizing (reducing)
• Followed by restoration
(repair, reinstate) and finally
• Those externalities which cannot be
restored must be offset.
1. Avoid
2. Minimize
3. Restore
4. Mitigate/Offset

55. Biodiversity Programs Globally
55
Region Program Legislation Methodology
US (1) Wetlands Compensatory Mitigation
(2) Conservation Banking
(3) FWS’ Conservation Banking Guidance
Yes Yes
EU (1) Birds and Habitats Directives
(2) European Liability Directive
Yes Yes
Australia (1) Habitat Hectares Method (Victoria)
(2) The Biodiversity Banking and Offsets Scheme
Yes Yes
Brazil Forest Regulation and National System of Conservation Units Yes Yes
World Bank Operational Policy 4.04: Natural Habitats No No
IFC Performance Std. 6: Biodiversity Conservation and Sustainable
Natural Resource Management
No No
EBRD Performance Requirement 6: Biodiversity Conservation and
Sustainable Management of Living Resources
No No
Malaysia Malua Biobank No No

56. 56Source: http://maluabank.com/MaluaBrochure.pdf
Malaysia - Malua ‘Biobank’, Sabah.
• Who: Sabah
Government-owned
company license to the
Malua Forest Reserve;
ceased all logging
operations end 2007.
• What: US$10 million
fund to rehabilitate the
Malua Forest Reserve
, sell Biodiversity
Conservation
Certificates.
• Status: few sold to-
date; seeking new
investors and
strategies. Voluntary
basis.

57. Biodiversity Credits - Conclusion
• Success in developed markets due to supporting legislation.
• Credits are not “transportable” i.e. they are location specific.
• Deemed not viable in Indonesia, lack of a regulated market.
• Insufficient studies on GPNP in terms of impact on
biodiversity; additionality clause makes the park not eligible
under current methodology.
Therefore, unlikely to be viable in the case of GPNP (hence no
NPV calculated for biodiversity credits).
57

58. Modules
58
‘Business As Usual’ (BAU) Activities:
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ Activities:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products

59. Bio-prospecting
59
Bio-prospecting is the systemic search for
genes, compounds, designs and organisms that might have a
potential economic use and might lead to a product being
developed.
3 20
75
(Laird’2002)
Cosmetics and Personal Care
Botanical Medicines
Pharmaceutical Industry
• Annual sales derived from Traditional
Knowledge using genetic resource
estimated at around US$100 billion.

60. Regulations - International
• Convention on Biological Diversity (CBD)
– conservation of biological diversity the sustainable use of its components and the fair
and equitable sharing of the benefits arising out of the utilization of genetic resources
• UN Convention on Law of the Sea (UNCLOS)
– contains provisions relating to the seabed, the high seas, marine scientific research, and
protection of the marine environment which may be relevant to bioprospecting
activities.
• Trade-Related Aspects of Intellectual Property Rights Agreement
– inter alia, minimum standards for the protection of patents in all fields of technology
including the use of biological and genetic resources in Biotechnology
60

61. Regulations - Indonesia (1/2)
Indonesia is signatory to the Nagoya Protocol on fair and equitable sharing of
benefits arising from use of genetic resources, but there are no regulations at
the national level to ensure that it is implemented.
• Convention on Biological Diversity
– Signatory to the Convention
– Ratify the Nagoya Protocol on Access to Genetic Resources and the Fair and Equitable Sharing
of Benefits Arising from their Utilization
• Trade-Related Aspects of Intellectual Property Rights Agreement
– Law No.29/2000 on Plant Variety Protection
– regulation No. 13/2004 on the denomination, registration, and utilization of initial variety to
develop essentially derived variety
• International Treaty on Plant Genetic Resources for Food and Agriculture
– international agreement aimed at guaranteeing food security through
the conservation, exchange and sustainable use of the world's plant genetic resources for food
and agriculture
– Implemented through Law No. 4/2006
61

62. Regulations - Indonesia (2/2)
• Cultural Practices Law - 12/1992
– Regulates access to genetic resources
• Conservation of Biodiversity and Ecosystems Law – 5/1990
– Based on conservation and potential use of biodiversity and ecosystems in a balanced
and compatible manner to support community prosperity and quality of life
– Regulates protection of life support systems and conservation and sustainable use of
biodiversity
• Ministerial Decree No. 1X/2001 on Agrarian Reform and Natural Resources
Management
– Implement policies on agrarian reform and management of natural resources according
to principles of sustainable development
– Recognizes and protects the rights of traditional communities in management of natural
resources in Indonesia
62

63. Case Study: INBio-Merck Agreement, Costa Rica
• Type of Genetic Resource
– Plants, insects and environmental samples across all national parks in Costa Rica
• Stakeholders
– National Institute of Biodiversity of Costa Rica (INBio): a non-profit association
established under Costa Rican Law
– Merck and Co Inc.: one of the largest pharmaceutical companies in the world based out
of USA
• The Agreement
– Merck provided INBio with a research fund of US$ 1million over two years, plus
laboratory equipment and materials worth $130,000.
– Royalty rate not disclosed, 27 patents filed till 2004
63

64. Potential Revenue to Local Communities
64
Item Range Comments/Reference
Sample Collection fee (US$) 50-200 Figures indented to cover actual costs
(packaging, transport etc.)
Hit rate 1:6,000 –
1:30,000
Probability of developing one
commercially viable product;
averages 1 in 12,000
Development Period (yrs) 10 – 12 Average duration to develop a
marketable commercial product
Product revenues (US$) 100m -1bn Total worldwide sales over the
lifespan of the product.
Royalty payment (%) 1-5 % of gross revenues payable
Two potential sources of revenue to local communities:
(1) Sample collection fee, and/or
(2) Royalties from success development of a
commercial product.
Stakeholders
• Local Communities
• Host Governments
• Companies
• International Donor Agencies
• Brokers
• NGO’s

65. Bio Prospecting : Conclusion
• Low revenues from sample collection (while upfront).
• Royalty payments are uncertain, as it may take over 10 years
to develop a product.
• No recent successful cases of bioprospecting in Indonesia.
• GPNP has a confirmed database of 500 plant species, but
deemed low given the above ‘hit’rate of one in 12,000.
Therefore, no NPV is attributed to bioprospecting.
65

66. Modules
66
‘Business As Usual’ (BAU) Activities:
• Illegal Timber
• Illegal Farmland
• Illegal Woodfuel
‘Portfolio’ Activities:
• Carbon Credits
• Ecotourism
• Biodiversity Credits
• Bio-prospecting
• Non Timber Forest Products

67. NTFP in Indonesia
Examples:
• Rattan and bamboo
• Rubber sap
• Gaharu (resin wood)
• Honey
• Plants, flowers, fruits
• Animals (pets, meat)
including birdsnest
67
• Used for own consumption or
for sale.
• Rattan used to be a major
export for Indonesia.
• Gaharu is highly prized
internationally.
• More sustainable methods
for wild honey being
promoted.
Historical exploitation of NTFP has led to almost complete
depletion of these resources [Sellato].
www.flickr.com Durian collectors in Gunung Palung, 2009.

68. NTFP Collection in GPNP - Household Survey Results (1/2)
In 2011, less than 2% of the population entered GPNP to collect NTFPs.
68
• Key items were fruits, gaharu
(resin wood) and traditional
medicinal plants.
• Collectors tended to be also
engaged in (illegal) logging.
Gaharu (resin wood)
Ignasnoreng.blogspot.com

69. NTFP Collection in GPNP - Household Survey Results (2/2)
The highest value
NTFP collected
was gaharu (resin
impregnated
wood).
69
NTFP
Total Qty
Collected Rp/unit
Total Value
(Rp) Total Qty Total Value (Rp)
Total Value
(US$)
Gaharu 3 30,000,000 90,000,000 56 1,681,035,930 186,782
Fruits 104 3,558 370,000 1,943 6,910,925 768
Honey 3 50,000 150,000 56 2,801,727 311
Obattraditional 7 11,429 80,000 131 1,494,254 166
Rattan 25 1,200 30,000 467 560,345 62
Others 30 2,000 60,000 560 1,120,691 125
Total 172 30,068,186 90,690,000 3,213 1,693,923,872 188,214
#of HH 10 187
EOS Household Survey Est. forwhole population
*Unit price of Rp30m or US$3,150 (figure provided by respondents) are only for the highest quality.
Actual market values could be as low as a few dollars for the lowest quality.
• Historical exploitation led to almost complete depletion
e.g. extraction of gaharu in GPNP let to almost 98% of trees being
‘liquidated’ (Paoli et al 2001).

70. NTFP - Conclusion
Sustainable NTFP will have to be cultivated outside GPNP -
some potential, but a number of issues remain; values (if any) are speculative
and considered unlikely to be significant.
70
• Any collection of flora and fauna within GPNP is illegal, hence any
‘sustainable’ collection of NTFP has to be from cultivation of such
products outside the park.
• Efforts to cultivate the Aquilaria trees (gaharu) have not been successful.
• Limited value of other NTFP collected from GPNP.
• Some preliminary development of other NTFP (palm sugar, honey) but no
evidence of significant success yet.
Therefore, no NPV projections/values were projected.

71. • Project Overview
• Modules
• Key Challenges & Issues
• Summary of Key Results
• Conclusions
• Appendix
71
Contents

72. Results – NPV Summary
72
Conservation based activities offer some value but lower
Excludes non-
monetary ‘value’
from other
forest uses.
$8m <$2m
US$ values
over 30
years

73. Results – NPV Summary
73
Local communities do not benefit much from illegal logging
US$ values
over 30
years

74. Outline
• Project Objectives
• Context
• Study Site
• Methods
• Data Collection
• Results & Discussions
• Conclusion
74

75. Food Security Implications
• Potential climate change effects may reduce rice yields and
due to higher temperature, and/or changes in
weather/seasons.
• Possible food reduction or food deficit (rice) in 15-20
years, and resulting significantly higher rice prices.
• Farming plots are also becoming smaller, harder for
households to produce enough, especially for the poor.
• Impact may be mitigated by: planting cash crops, more
farming land, higher yielding genetic planting
material/technology, reorganization of farming practices
(economies of scale), or migration/urbanization (for higher
incomes).
75

76. Overall Conclusion
76
Current BAU activities provide significant value; and apart from
ecotourism, the other portfolio options show limited value.
• Alternative jobs/livelihood options needed
• Park surveillance and monitoring needed.
• Commercial plantation forests as alternative
• Global legal framework for environmental conservation.
Continued conservation efforts are likely to remain
critical in minimizing future deforestation rates.

77. Thank You!
Contact:
Earth Observatory of Singapore (EOS)
Andreas Schaffer, Sustainability Director (Principal Investigator)
Edmund Hoh, Project Leader
Ankit Joshi, Researcher
c/o Nanyang Technological University
50 Nanyang Avenue, Block N2-01a-03,
Singapore 639798.
Tel: (65) 6592-7709
Email: a.schaffer@ntu.edu.sg
edmundhwm@ntu.edu.sg edmundhoh@yahoo.com.sg
Website: www.earthobservatory.sg