Increasing effectiveness of Kerinci Seblat National Park, Sumatera, through a landscape approach: lessons learnt from Merangin

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 201512-16 July 2015Honolulu, Hawaii

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.

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

• 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

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).

Dominant changes, 2000-2010

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

0 100000 200000 300000 400000 500000

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?

Contrast Table – Plot level

Land Cover Type Forest

Undisturbed forest 0Logged over forest-high density 0.147Logged 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)

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

Degree of Integration of Focal Area (DIFA) as tree diversity indicator at landscape scale (Dewi, et al., 2013)

Cum

ulati

ve s

hare

of d

ense

fore

st (%

)

I =

where:I = degree of

integration

f(x) = cumulative share of dense forest for TECI = x

How integrated Forests are?

1990 2000 2005 20100

102030405060708090

100

CORE -5-0 Km 0 - 5 KM 5 - 10 KM 10-15 KM

Deg

ree

of In

tegr

ation

of F

ocal

Ar

eas

(%)

APPLICATION OF LANDSCAPE APPROACH IN MERANGIN DISTRICT

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/coverchanges

Conse-quences &functions

Livelihoods, provisioning & profitability

Land use policies, spatial development planning

Rights-based approaches

Economic incentives

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/

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

• 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

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

•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

Developing scenarios that change trajectories of future LULCC from BAU scenario based on local plans to others


• “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.

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 factors2005

2010

2025


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


Ex-ante impact:Emission and biodiversity



Green Development Scenario

2025 20252025




2025 2025

2010 2015 2020 202517800000.0

18000000.0

18200000.0

18400000.0

18600000.0

18800000.0

19000000.0

19200000.0

19400000.0

BAU EXP GREEN

GDP

in U

SD

• 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




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

2010 2015 2020 202575000.0

80000.0

85000.0

90000.0

95000.0

100000.0

BAU EXPAND GREEN

Fine-tuning scenarios• Modified Green Scenario by maintaining SFM, high

economic value and labor intensive cropland and tree crop (paddy rice and cinnamon)

2010 2015 2020 202517600000.0

17800000.0

18000000.0

18200000.0

18400000.0

18600000.0

18800000.0

19000000.0

19200000.0

19400000.0

BAU

EXP

GREEN

Modi-fied-GREEN

GD

P in

USD

2010 2015 2020 202580000.0

82000.0

84000.0

86000.0

88000.0

90000.0

92000.0

94000.0

96000.0

98000.0

100000.0

BAU

EXPAND

GREEN

Modi-fied-GREEN

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

Current activities

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

MAHALO!THANK YOU! TERIMA KASIH!