A presentation by Dony Indiarto, Sonya Dewi, Andree Ekadinata, and Alfa Nugraha at ATBC from the 12-16th of July 2015.

1. Increasing effectiveness of Kerinci Seblat
National Park, Sumatera, through a
landscape approach:
Lessons learnt from Merangin
Dony Indiarto, Sonya Dewi, Andree Ekadinata, and Alfa Nugraha
52nd Annual Meeting ATBC 2015
12-16 July 2015
Honolulu, Hawaii

2. Background
• This study focuses on Kerinci Seblat National Park
(TNKS), the largest National Park in Sumatra,
which spans lowland, montane, and pine forest
ecosystems.
• TNKS is home to rich biodiversity, which lately is
threatened by loss and fragmentation of habitat.
• The role of agroforestry is not recognized while
rich literatures show that matrix matters within
landscape mosaics.

3. Kerinci Seblat National Part
• Establishment: 1982
• Area: 1,342,662 Ha
• Shape: elongated cover about 350
km of Barisan Range Forest from
Northwest to Southeast
• Mosaics of undisturbed forest
• Elevation ranges from 100 to 3400
a.s.l
Ecoregion
• 1.46% of Sumatran montane forest
• 12.79 % of Sumatran lowland forest
• 20.33 of Sumatran Tropical pine
forest

4. • Proximity to NP is used to delineate zones: from core, to buffer
area outside NP up to 15 km
• Sixteen districts in three provinces share the NP and buffer zones

5. LULCC in NP and surroundings
• Due to high population growth, in-migration, and
external market demand, encroachment to TNKS
during 20 years period is rampant (240,262 ha
forest loss or 17% area)
• In the area surrounding TNKS, conversion of more
integrated land-use system such as agroforestry
into more intensified uses, especially estate
crops, has been active (109,389 ha less of
agroforest area and 212,981 ha of increased in
estate crops).

6. Dominant changes, 2000-2010
0 100 200 300 400 500
Forest conversion to others
Forest conversion to shrub
Forest conversion to cropland
Tree cover conversion to others
Tree cover conversion to cropland
Forest conversion to Agroforest
Forest conversion to Rubber
Forest conversion to Oilpalm
Forest degradation
Thousands of hectares

7. Characterizing habitat changes
• Similarity in habitat qualities across land
use/cover classes
• Landscape configuration
• Integration of focal area to the landscape
• Land sparing or land sharing?

8. Contrast Table –
Plot level
Land Cover Type Forest
Undisturbed forest 0
Logged over forest-high
density 0.147
Logged over forest-low
density 0.246
Agroforest 0.4
Timber plantation 0.9
Estate crop 0.9
Shrub 0.6
Configuration: Total Edge
Contrast Index (TECI) –
Landscape level
Total edge contrast index (TECI) of
dense forest is calculated using
Fragstat (McGarigal, 2002) as:
for each pixel of size 1 ha in the
landscape, where:
– ei is total length (m) of edge in the sub-
landscape between dense forest pixel
and any other land use/cover type i
– di is the dissimilarity (edge contrast
weight) between dense forest pixel (or
other defined focal habitat) and any
other land use/cover type i
(100)

9. TECI as landscape configuration index
Land-cover Map 2010 TECI Map
(McGarigal, 2002)
Undisturbed forest as focal area (source of tree diversity)
Moving Window
Analysis

10. Degree of Integration of Focal Area (DIFA)
as tree diversity indicator at landscape scale (Dewi, et al., 2013)
Cumulativeshareofdenseforest(%)
I =
where:
I = degree of
integration
f(x) = cumulative share
of dense forest for
TECI = x

11. How integrated Forests are?
0
20
40
60
80
100
1990 2000 2005 2010
DegreeofIntegrationofFocal
Areas(%)
CORE -5-0 Km 0 - 5 KM 5 - 10 KM 10-15 KM

12. APPLICATION OF LANDSCAPE
APPROACH IN MERANGIN DISTRICT

13. Drivers
Incentive structure through policy change (tax, subsidy etc)
LU rights (e.g. community forest mngmnt)
PES and conditional ES incentives
Response/
feedback
options
Biodiversity, Watershed
functions, GHG emissions,
Landscape beauty
Actors/
agents
Land
use/cover
changes
Conse-
quences &
functions
Livelihoods, provisioning &
profitability
Land use policies, spatial development planning
Van Noordwijk, M., B. Lusiana, G. Villamor, H. Purnomo, and S. Dewi. 2011. Feedback loops added to four conceptual models linking land change with driving forces and actors. Ecology and
Society 16(1): r1. [online] URL: http://www.ecologyandsociety.org/vol16/iss1/resp1/

14. Land-Use planning for Multiple
Environmental Services (LUMENS)
• Build common visions and understandings among working groups of
multiple stakeholders
• Collect and compile best available relevant dataset: land admin, plans,
land use/cover maps, biophysical, demographic, socio-economics
• Strengthen capacities in:
– quantifying ecosystem functions
– analyzing trade offs between conservation-development
– developing options and simulating scenarios
– negotiating best scenarios over ex-ante impact analysis
– implementation, monitoring and evaluation within the existing policy
framework
• Facilitate and negotiate public consultations and high level discussions
to mainstream plans into programs of local government and identify
other potential financing mechanisms
• Align and engage with policy processes at the local and national levels

15. • One of Jambi’s 11 districts. Area: 7,680 km2 with 336,000 people in 2010. The
district’s population density of 45 per km2
• The upper watershed of Merangin is located in Kerinci Seblat National Park. It is an
“average” district within the surroundings of NP, in terms of poverty, oil palm
establishments, GDP, road density, etc.
• About 71% of area is allocated as forest land. The rest is non-forest land, owned
privately or managed by communities or estate companies
• In 2011, ICRAF facilitated the establishment of a working group in Merangin that
included various stakeholders in land-use planning: the District planning and
Development agency, Forestry office, researchers and NGOs
Merangin Merangin

16. Planning units: Spatial land allocation, permits, de
facto management and practices

18. •Understanding drivers
•Where are likely changes will
happen based on the driver
modelling
•Changes in drivers can be
accommodated, i.e., new road.
•Projected conversion areas can be
resulted from:
(i) Exogenous process, perhaps
from regional or global models,
(ii) Historical LULCC rates in each PU,
(iii) Forward-looking scenario, with
considering future needs for
lands to improve economics and
social performance
2005
2010
Driving factors
2025
Business As
Usual Scenario
Scenario development

19. Developing scenarios that
change trajectories of
future LULCC from BAU
scenario based on local
plans to others
Scenario development
• “Business as usual” (BAU):
historical changes in each PU
were retained, assuming a
stationary process and drivers,
2005–2010 and 2010–2015;
• “Expansive agricultural
development” (Expand):
increased conversion of forests to
oil-palm and acacia plantations
and agroforests;
• “Green development” (Green):
all undisturbed and most logged-
over forests were retained and
degraded areas in protected
forests were rehabilitated. Oil-
palm, acacia and rubber
plantations and agroforests were
only established on shrub-, grass-
and cleared land.

20. Developing scenarios that
change trajectories of future
LULCC from BAU scenario
based on local plans, e.g.
• Green development scenario:
all undisturbed and most
logged-over forests were
retained and degraded areas in
protected forests were
rehabilitated. Oil-palm, acacia
and rubber plantations and
agroforests were only
established on shrub-, grass-
and cleared land.
Green
Development
Scenario
Driving factors
2005
2010
2025
Scenario development

21. Developing scenarios that
change trajectories of
future LULCC from BAU
scenario based on local
plans, e.g.
•Expansive agricultural
development scenario:
increase the conversion of
forest to oil palm, acacia
plantation, forest
degradation
Faktor pemicuDriving factors
Expansive agric.
scenario
2005
2010
2025
Scenario development

22. Ex-ante impact:
Emission and
biodiversity
Expansive agric.
scenario
Business As
Usual Scenario
Green Development
Scenario
2025 20252025

23. Expansive agric.
scenario
Business As
Usual Scenario
Green Development
Scenario
2025 2025
17800000.0
18000000.0
18200000.0
18400000.0
18600000.0
18800000.0
19000000.0
19200000.0
19400000.0
2010 2015 2020 2025
GDPinUSD
BAU EXP GREEN
• Decrease of GDP due to decreasing area of
forest cover that supports two key sectors:
Wood log and Wood chips
• GDP decreases: 0.7% with GREEN Scenario),
1% with EXPAND Scenario and 1.7 % with BAU
• Although GDP from Oil palm, Rubber, Coconut
and Coffee are increased it does not
significantly contributes to Merangin GDP
• No oil palm processing facility in the district ->
multiplier effect to other sectors are low
2025

24. Expansive agric.
scenario
Business As
Usual Scenario
Green Development
Scenario
2025 20252025
• Decrease of Labour absoption mostly due
to two key sectors: Wood log and Wood
chips
• Labour absorption will decrease: 5% with
GREEN Scenario), 9% with EXPAND, and14
% with BAU
• Although labor absorption in Oil palm,
Rubber and Coffee sectors will increase,
labor absorption in other land based
sector will mostly decrease, esp. since
there was no oil palm processing facility in
the district
75000.0
80000.0
85000.0
90000.0
95000.0
100000.0
2010 2015 2020 2025
BAU EXPAND GREEN

25. Fine-tuning scenarios
• Modified Green Scenario by maintaining SFM, high
economic value and labor intensive cropland and
tree crop (paddy rice and cinnamon)
17.6
17.8
18.0
18.2
18.4
18.6
18.8
19.0
19.2
19.4
2010 2015 2020 2025
GDPinUSDMillions
BAU
EXP
GREEN
ModifiedGR
EEN
80.0
82.0
84.0
86.0
88.0
90.0
92.0
94.0
96.0
98.0
100.0
2010 2015 2020 2025
Thousands
BAU
EXPAND
GREEN
Modified
GREEN

26. BAU
Expansive
Green
Modified green
Emission
Reduction
DIFA - biodiv WS buffering cap GDP, LUP, Labor
Emission
Reduction
DIFA –
biodiv
WS buffering cap,
Flooding risks
GDP, LUP
Scenarios

27. Current activities

28. Conclusions
• Inclusive, informed, integrative LUP process to LEDS and beyond are
needed
• Linking science-policy-practices is more feasible with negotiation
support systems rather than decision support systems
• No one size fits all: local specificity is crucial, understanding drivers
to identifying leverage points
• Capacity strengthening is key to transformation of landscape
governance
• Aligning local and global agenda is an important entry point to
sustainable actions
• Multiple ES, beyond carbon, such as water through land-based
sector can bring together mitigation and adaptation
• Synergy across levels and modalities through landscape approach is
key to implementation at local level

29. MAHALO!
THANK YOU!
TERIMA KASIH!