The ASB Partnership for the

Tropical Forest Margins

Benchmark Sites Experience

Peter A Minang, Meine van Noordwijk & Glenn Hyman

CRP6 MEETING, 30 SEPTEMBER 2011,

BOGOR, INDONESIA

Meadow 1996 2006 Fallow XP 2011 Vineyard

Land cover change….

3101 Fremont Drive, Sonoma, California, United States

10% TREE cover in agricultural lands…

Enough to qualify as forest?

Purpose of ASB Benchmark

sites (A mix of objectives)

• Understanding of key issues

• Cross-site comparison

• Observation

• Technology transfer for impact (But this did

not quite happen as funds ran short )

Key Issues

• Reducing

deforestation and

forest degradation

• Reducing Emissions

from All Land Use

(REALU)

• Trade-offs at Forest

Agriculture

interface …..

Ucayali, Peru

Southern Cameroon Jambi /Lampung,

Indonesia

Chiang Mai, Thailand

Site locations

Western Amazon, Brazil

Source: WWF Global 200 Ecoregions (WWF 2001).

Notes: The Biomes displayed are only forest biomes that

are present in the warm humid and subhumid tropics.

NEOTROPICALAFROTROPICAL

INDOMALAY

AUSTRALASIA

1000 0 1000 2000 Kilometers

Terrestrial Forest Biomes

Tropical and Subtropical Moist Broadleaf ForestsTropical and Subtropical Dry and Monsoon Broadleaf Forests

Focus area

Dividing line between humid and subhumid tropics

ASB site locations#S

Criteria for ASB Benchmark sites (I)

Tropical & Subtropical Moist Broadleaf Forest Biome

HIGH EXTRAPOLATION POTENTIAL: PANTROPIC PROBLEM DOMAIN

HIGH INTERPOLATION POTENTIAL?

Criteria for Choice of ASB Benchmarks (II)

Representation of Biome types

SITE BIOME

Sumatran (Jambi and lampung),

Indonesia

Equatorial rainforests of the

Indonesian and Malaysian

archipelago.

Claveria and Lantapan, Philippines Moonsoonal forests

Pedro Peixoto, Acre and

Theobroma, Rondônia Western

Brazil

Amazon

Southern Cameroon Congo Basin

Ma Chaem watershed, Chiang Mai,

Thailand

Subtropical hill forests of

mainland mountain Southeast Asia

found in Thailand, Myanmar, Laos,

Vietnam, and southern China.

Criteria for Choice of ASB

Benchmarks (II)

• DOMAIN SIMILARITY VALUE (Multiple

Criteria- Largely bio-physical determinants

of plant growth)

• elevation, potential evapotranspiration, total

annual precipitation, precipitation in the driest

month, precipitation range, minimum average

monthly temperature, and maximum average

monthly temperature (Gillison 2000).

• Using domain potential mapping procedure

(Carpenter et al., 1993)

DOMAIN SIMILARITY VALUES

Criteria for Choice of ASB Benchmarks (III)

Range of Socio-Economic Conditions

A range of socio-economic conditions

under which deforestation occurs

• Some Examples:

• Western Brazilian Amazon encompasses two

colonization, and areas along the BR-362 highway

• Cameroon, Congo Basin – low but increasing

population density and traditional indigenous

slash-and-burn practices

• Relatively High Population Density and migration

dynamic in Jambi and

• Working partnership in sites

• Long term perspective of partnership (often including a

local and national partner involved)

• Ensures multiple perspectives / roles / skills

• Access

Criteria for Choice of ASB Benchmarks

(IV) Partnership and infrastructure

Range of partners (national

partners crucial)

BENCHMARK SITE CHARACTERISTICS

Specific Characteristics

• Gradients within sites: Land Use, agro-ecology

and Population Density = useful for capturing

dynamics

• Examples:

• Population and land use gradients in Cameroon Site

• Broad gradient from primary forests in the Jambi

area to degraded Imperata grasslands in Lampung

Province, including both indigenous farmers and

colonization projects as well as large-scale

plantations and logging companies

Cameroon- Site Gradients

FROM RELATIVELY INTENSE MARKET GARDENING IN HIGH

DENSITY AREAS TO FOREST IN LOW DENSITY AREAS

Sumatra- Site Gradients

Lessons: some fundamental

considerations

• Use of comparative Methodological

framework (site characterization, meta-land

use)

• The ASB Matrix

• Multiple scales (nesting)

• Long-term commitment and co-location

• Expect surprises

Meta-Land Use Framework

The ASB Matrix

Multiple-scale (nesting)/ The

relevance of the question….

• Started out in ASB as

a 10km x 20km

• -40- 80000ha ( in

four blocks in Jambi;

80000ha in Chiang

Mai

• Broadened to 1.5 M

ha for landscape

type interaction

questions

• Now 5 Million ha in

Cameroon looking at

deforestation drivers

at sub-national level

• In Tanjabar ( Tanjung

Jabung Barat District

looking at district

level planning

Scenarios of REALU

(Reduced Emissions

from all Land Use)

500k ha

Expect Surprises – therefore

be flexible(i)

• Despite

methodological

harmonization, data

quality can still be

varied

• Funding challenges

long term can

disrupt plans ( I.e.

technology aspects

of ASB not financed

for long time

• You can often stitch

up data of different

periods to have an

impact story from

different projects as

long as methods

match- e.g. ASB h/h

surveys in Ucayali,

Peru and RAVA data

(though not

planned

Expect Surprises, hence be

flexible (ii)

• Jambi was chosen

to be more towards

left of curve, but in

a short time moved

more to the right

(Mining becoming

more important due

to change in

government;

emergence of oil

palm)

Expect Surprises, hence be

flexible (iii)

• Vietnam added to

enable

understanding of

extreme left hand

side of the forest

transition curve

(which was of

course not very

prominent at

inception of ASB)

More information (www.asb.cgiar.org)

THANK YOU