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Concepts: Trees in Landscapes
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Transcript of Concepts: Trees in Landscapes
ICRAF Seminar, Nairobi 27 November, 2009 Concepts, methods and experience with supporting negotiations and
incentives for trees in multifunctional landscapes
Meine van Noordwijk
Preview of contents• Science quality: the challenges of food security
and climate change, REF and RAF
• Sustainagility
• Agroforestry falling through the cracks?
• 5 INRM examples
• K2A and boundary work
• Multi-scale ES incentives to bring sustainability and sustainagility into the efficiency sphere
Boundary objects
Boundary agents
http://www.fotocommunity.com/pc/pc/mypics/1307401/display/15930189
Climate change and science
• How many Nobel prizes have been awarded for climate change related science?
None for Physics, Medicine, Economics*, Literature
One for Chemistry (early atmospheric chemistry: Crutzen)
One for PEACE (CC communication and IPCC)
* 2009 Economics price to Prof. Eleanor Ostrom is based on her work on institutional economics of the commons*
Artist Impression of the Human Perturbation of the Carbon Cycle
The Bali roadmap (2006): focus on ‘Nationally Appropriate Mitigation Actions (NAMA)’. Which form of RED/REDD/REDD+/REDD++ would be a NAMA for Indonesia?
4th most popu-lous country,
high per-capita emissions,
mostly due to AFOLU
…occur in between sectoral
responsibilities
Large parts of emissions
…are ‘planned’ for development
…are in breach of rules
AFOLU = Agriculture, Forestry and Other Land Use
…High vulnera-bility of coastal
zones
Need for adaptation, due to
…Landslides, floods and droughts
…Still rural, primary resource-
based economy
…Discrepancies in wealth and power
Agroforestry falling through the cracks of the UNFCCC forest definition
in REDD?
intensive agriculture
natural forest
integrated, multifunctional
landscape: crops, trees, meadows and forest
patches
Tree plan- tations
intensive
extensive
conservation
protection
production
Agr
ofor
estr
y
Agr
icu
ltu
re
F
ores
try
Segregate Integrate functions
Current legal, institutional & educational paradigm
Current reality
‘deforestation’
‘loss of forest functions’
Zomer et al. (2009) Trees on Farm: Analysis of Global Extent and Geographical Patterns of Agroforestry. ICRAF Working Paper no. 89. Nairobi, Kenya: World Agroforestry Centre. 60pp
50% of ‘agricul-tural land’ has
>30% tree cover in SEA & CA
Relative agricultural function (RAF) - provisioning
Re
lativ
e e
colo
gic
al f
un
ctio
n (
RE
F) A
Initial use
BDegra-
dationC
Rehabilitation
EUCritical loss of
ecological functions
D
Trade-off REF/RAF: convex, concave, win-win after lose-lose
Low
Low
Agricultural productivity
Degrading agricultural landscapes
High
Core wilderness/ natural forest
Polyculture
attractors
High
Intensive agroecosys-tem domain
Agroforest domain
Degraded, aban-doned land
Low external input agro-ecosystems
Bio
dive
rsity
& a
ssoc
iate
d ec
osys
tem
ser
vice
s
Current dominant trend
Biodiversity-ba-sed alternative pathway
Landscape position
Lan
d u
se i
nte
nsi
fica
tio
n &
do
mes
tica
tio
n o
f b
iota
100 67 33 0
100
6
7
3
3
0 0 33 67 100
‘Forest’
Protected
areaGame
ranches
NTFP-zoneSelective logging
AgroforestFastwood plantation
Open fieldcrops
Leys
Off-farm Cut&carry
Feed-based bioindustry
Timber-enriched
forest
On-farm Cut&carry
‘Forest’
Centrifugal forces towards ‘pure’ conservation,
intensive animal, annual & tree-crop
production
‘Forest’ world pulled towards 2
opposites
Multifunctionality attractor?
Smallholder far-mer/agroforester
here and nowGene
Product value chains
Patch/field
Organism
Population
Farm
Land-scape
Desakota network
Globe
National economy
Community
Watershed
Nation
Global institutions
National institutions
time
spa
ce
in
stitu
tions
Gene
Product value chains
Patch/field
Organism
Population
Farm
Land-scape
Desakota network
Globe
National economy
Community
Watershed
Nation
Global institutions
National institutions
time
spa
ce
in
stitu
tions
Resilience according to the most popular WWW sources::
•The physical property of a material that can return to its original shape or position after deformation that does not exceed its elastic limit•an occurrence of rebounding or springing back•Resilience in psychology is the positive capacity of people to cope with stress and catastrophe. • The positive ability of a system or company to adapt itself to the consequences of a catastrophic failure caused by power outage, a fire, a bomb or similar event•Resilience is a 4 piece punk rock group from Santa Rosa, California, United States. •Resilience is the ability to provide and maintain an acceptable level of service in the face of faults and challenges to normal operation •In ecology, resilience is the rate at which a system returns to a single steady or cyclic state following a perturbation •The mental ability to recover quickly from depression, illness or misfortune
Adaptive capacity,according to Wikipedia, is
• the capacity of a system to adapt if the environ-ment where the system exists is changing.
In human social systems, it is determined by : • the ability of institutions and networks to learn, and store
knowledge and experience.• creative flexibility in decisionmaking and problem solving• the existence of power structures that are responsive and
consider the needs of all stakeholdersIn ecological systems, it is determined by :• genetic diversity of species• biodiversity of particular ecosystems• heterogeneous ecosystem mosaics as applied to
specific landscapes or biome regions
• Agility is the ability to change the body's position efficiently, and requires the integration of isolated movement skills using a combination of balance, coordination, speed, reflexes, strength, endurance,and stamina.
• In sports, agility is described in terms of response to an opposing player, moving target, as seen in field sports and racket sports. Sheppard and Young (2006) define agility as "a rapid whole body movement with change of velocity or direction in response to a stimulus."
• In business, agility means the capability of rapidly and cost efficiently adapting to changes. Recently agility has been applied e.g. in the context of agile software development and agile enterprise
wikipedia
Properties of a system that sup-port actors to cope with change,
to be adaptive and resilient.
Sustainable livelihoods somewhere on the globe
Sustainable livelihoods at current location
Sustainable farmsat current location
Sustainability of currentfarming system
Sustainability of current trees/crops/animals
Sustainability of current cropping system
Sustainagility E:human migration
Sustainagility D:shift to non-ag
sectors
Sustainagility C:other farming
system
Sustainagility B:other cropping
system
Sustainagility A:other trees/crops/
animals
Meeting today’s needs without compromising the future
10. Earth system re-
source governance
9. Natural resource ma-
nagement institutions
8. Agri-food systems
7. Rural landscapes
6. Desakota liveli-
hood networks
5. Agroecosystems
4. Farms, forests
3. Populations, fields
2. Organism during its
life cycle
1. Access to genetic
diversity
SustG10: New global deals (S)
SustG_9: New environmentality (H,S)
SustG_8: New food securities (H,I,S,F,N)
SustG_7: New landscape value chains (N,S,H,I,F)
SustG_6: New livelihood systems (H, S, F, I, N)
SustG_5: New interdependencies for lateral flows (N, H)
SustG_4: New farming systems and farm-scale resource management (N,H)
SustG_3: New cropping/AF systems and associated knowledge (N,H)
SustG_2: New crop/tree/animal management techniques (N,H)
SustG_1: New crop/tree/animal types domesticated on farm or accessible from external sources (N, H, S)
Sustainable global agreements
Sustainable iNRM institutions
Sustainable value chains
Sustainable Ecosystem Service incentives
Sustainable livelihoods
Sustainable agro-ecosystems
Sustainable farming systems
Sustainable soil fertility management
Sustainable cropping systems and practices
Sustaining genebanks releasing robust varieties
Ecosystem Services: The benefits people obtain from ecosystems
RegulatingBenefits obtained from
regulation of ecosystem processes
• climate regulation• disease regulation
• flood regulation
ProvisioningGoods produced or
provided by ecosystems
• food • fresh water• fuel wood
• genetic resources
CulturalNon-material benefits
from ecosystems
• spiritual • recreational
• aesthetic• inspirational• educational
Supporting Services necessary for production of other ecosystem services
• Soil formation, • Nutrient cycling, • Primary production
Innovation options resources necessary for new goods & services
The view is better if I go a little further High efficiency (the place
provides a nice view on a neighbouring waterfall)
Sustainability is ok, (1 m of supporting services…)
Sustainagility question-able, don’t jump around...
As the weather lost its discipline…
So must we
Govt plans to rehabilitate 2.5 million hectares of forest
The Jakarta Post , Jakarta | Thu, 11/26/2009 6:24
Forestry Minister Zulkifli Hasan says the government will reha-bilitate 2.5 million hectares of critical forest area over the next five years through a program that involves local residents
Under the community forest program, a family will be granted the right to manage up to 15 hectares of forest area for a maximum 35 years. The family will be allowed to cultivate plants of their choice, including rubber trees.
Local Govt, foreign investors (Korea, Taiwan), local investors
Govt MoF
APP, Local Govt, MoF, Central Govt
ICRAF, WARSI
WARSI
BirdLife, WARSI
Local govt, NGO
MoF, WARSI
Intensified rubber
Oil palm (farmer)
Mining
Road
Transmigration
HTR
HTI
Illegal logging
Community forest, old RAF
Rubber - sisipan
Certified logging
Protected and customary forest
National Park More ES
Less ES
Conservation concession
Transmigration
Oil palm (company)
Farmer, CIFOR, ICRAF, WARSI, RUPES
Local govt Local govt
Govt, BRI through agric. revitalization program
National and Malaysian investors, Govt
Less income More income
Q1Q2
Q3 Q4
Globally Appropriate Mitigation Actions (GAMA)
Nationally Appropriate Mitigation Actions (NAMA)
Locally Appropriate Mitigation Actions (LAMA)
Landscapemosaic
resourceinteractions
new components &technologies
spontaneous
change
agreedchanges
performanceindicators
actors,stake-holders
Negotiationsprocess
Plots (land use s.s.)
Matrix (filter)
Roads/streams (channel)
Negotiation Support Systems
5 case studies1. Local conflict resolution in forest margin in
Sumberjaya (Lampung, Indonesia)
2. Emergence of Payments for Watershed Servi-ces in Singkarak (W. Sumatra, Indonesia)
3. Adjustments in China’s Sloping Land Conversion Program (SLCP) in Baoshan
4. Global debate on forests and floods
5. Emerging global policies for Reducing Emis-sions from Deforestation and Degradation (REDD) and their inconvenient truths
Lessons for R&D institutions
the ‘Universal Soil Loss Equation’ can predict what happens
in such plots
but not what happens here...
Landscape-scale assessment of water and sediment flows:
Filter effects in the valleys
Or where the sediment at the dam comes from
1. Local conflict resolution in forest margin in Sumberjaya (Lampung, Indonesia)
the ‘Universal Soil Loss Equation’ can predict what happens
in such plots
14
2
3
5
Myth-use of forest hydrology for maintaining political control over land
Landscapemosaic
resourceinteractions
new components &
technologies
spontaneous
change
agreed
changes
performanceindicators
actors,stake-holders
Negotiationsprocess
Plots (land use s.s.)
Matrix (filter)
Roads/streams (channel)
First farmer-forest agreements (HKM)
Location-specific boundary object – can be replicated in similar circumstances based on ‘policy precedent’
effect
Generic boundary object – can be repli-
cated in similar circum-stances based on stepwise protocol
Rapid/replicable Appraisal Tools (6 months, 5-10 k$) integrating 3 types of knowledge
LocalEcological Knowledge
Public/PolicyEcologicalKnowledge
HydrologistEcologicalKnowledge
RHA Guideline Fig. 6
7 stages in development of RUPES reward mechanism
ES Reward support for action
RHAAwareness
RHAIdentifying partners
Monitoring
Action Plans
Negotiations
RHAScoping
Beneficiaries, buyers of ES
Interme-diaries
Providers, sellers of ES
Stage
II
I
III
IV
V
VI
VII
Scoping: K K
Realistic
Stakeholder identifi-cation: AA
Voluntary
Negotiation: (K K) (AA), aiming for (unified K unified A)
ConditionalImplementation, Monitoring and Learning:
unified K unified A (or reverting to (K K) (AA)
2. Emergence of Payments for Watershed Servi-ces in Singkarak (W. Sumatra, Indonesia)
Context Issue
Salience/PEK Legitimacy/LEK Credibility/MEK
Impact on stakeholder action Key to successOmbilin
river
Solok town
Paninggahan
Coffee enclave
Padang
Bukittinggi
Maninjau
Singkarak
PLTA
Kesem
patan
pengem
bangan
CDM
CDM
opportuniti
es
RHA = Rapid hydrological appraisal
LocalEcologicalKnowledge
Modellers’EcologicalKnowledge
Public/PolicyEcologicalKnowledge
Based on ‘categories’
Based on ‘processes’
direct ‘observables’
includes balance sheets
LawsCity folks
Localgovt
Nationalgovt
Economist
Engineers
ForestersEcohydro-
logist
women
men
women
menlowland
upland
Privatesector
Impacts 2 years after RHA SingkarakBefore RHA Singkarak• Deforestation seen as
the main culprit of all problems, including blackouts
• Tree planting as main solution
• Village with most tree cover should get highest share in royalties
• Problems with the Ikan bilih fish linked to deforestation
After RHA + disc.• Focus on lake & its water
quality; adjust scale of institution
• More awareness of climatic dependence
• Less blaming the upland deforestation for blackouts
• Less focus on ‘tree planting’ as the only or main solution
• More care in planning coffee re-intensification: Kopi Ulu
• Ikan bilih problem is about breeding grounds & overfishing
New LGU forum
Now with ICCRI
support
Riparian tree focus
3. Adjustments in China’s Sloping Land Conver-sion Program (SLCP) in Baoshan
Context Issue
Salience/PEK Legitimacy/LEK Credibility/MEK
Impact on stakeholder action Key to success
Sloping land conversion program (1998) not based on trees farmers want, and does not allow for intercropping in the early years of tree growth
Participatory technology development with farmers and forestry officials actively involved finds that there are trees with real value for farmers, while intercropping with locally domesticated medicinals opens the door for food crop intercropping
as well
Through local forest department, the success starts to spread, higher level authorities do at least tolerate, some support
Trust between researchers & village, researchers & forestry officials => trust between village a& forestry staff
4. Global debate on forests and floods
The forest ‘myth’ is sometimes benign and can be left
unchallenged, in other cases leads to mis-investment and
conflict
5. Emerging global policies for Reducing Emis-sions from Deforestation and Degradation (REDD) and their inconvenient truths
Context Issue
Salience/PEK Legitimacy/LEK
Credibility/MEK
Impact on stakeholder action Key to success
Agroforest
Trees out-side forest
Sustainable forest
manage-ment Soil C
CH4
N2O
Attempts to broaden the target to emissions from all land use to increaseplatform
Challenge current ‘framing’ Solid data + Politics
Opportunity cost ana-lysis for REALU
1. Forest definition too broad, yet many
avoidable emissions not covered
2. Indigenous people’s claim on forest rights
need respect
Avoidable GHG emissions from land use change, linked to ‘forest’
Fossil Fuel Emissions and Cement ProductionCO
2 em
issio
ns (P
gC y
-1)
9
8
7
6
1990 2000 2010
Growth rate: 1.0% per year
Growth rate: 3.4% per year
2008: Emissions: 8.7 PgCGrowth rate: 2.0%1990 levels: +41%
2000-2008Growth rate: 3.4%
Le Quéré et al. 2009, Nature-geoscience; CDIAC 2009
[1 Pg = 1 Petagram = 1 Billion metric tonnes = 1 Gigatonne = 1x1015g]
Fossil Fuel Emissions: Actual vs. IPCC Scenarios
Raupach et al. 2007, PNAS, updated; Le Quéré et al. 2009, Nature-geoscience; International Monetary Fund 2009
1990 1995 2000 2005 2010 2015
Fo
ssil
Fu
el E
mis
sio
n (G
tC y
-1)
5
6
7
8
9
10
A1B
A1FI
A1T
A2
B1
B2
Carbon Dioxide Information Analysis Center
International Energy Agency
Le Quéré et al. 2009, Nature-geoscience; CDIAC 2009
CO2 Fossil Fuel Emissions
Annex B (Kyoto Protocol)
Developed Nation
Developing Nations Non-Annex B
1990 2000 2010
5
4
3
2
CO2 e
miss
ions
(PgC
y-1)
55%
45%
Balance of Emissions Embodied in Trade (BEET)
Peters and Hertwich 2008, Environ, Sci & Tech., updated
MtCBEET
Warm colors Net exporters of embodied carbonCold colors Net importers of embodied carbon
Year 2004
developed countries are partially outsourcing their emissions to developing countries
Human Perturbation of the Global Carbon Budget
atmospheric CO2
ocean
land
fossil fuel emissions
deforestation
7.7
1.4
4.1
3.0 (5 models)
2000-2008PgC
CO
2 flu
x (P
gC y
-1)
Sink
Sour
ce
Time (y)0.3 Residual
2.3 (4 models)
Global Carbon Project 2009; Le Quéré et al. 2009, Nature-geoscience
Emissions from land use change
Land use change was responsible for estimated net emissions of 1.5 PgC per year over the last 15 years. In 2008, estimated emissions declined to 1.2 Pg C. Wet La Niña con ditions probably contributed to limited fire use and deforestation rate in Southeast Asia. Emissions from Brazil and Indonesia account for 61% of all emissions from land use change. The contribution of land use change emissions to the total emissions from human activities was 12% in 2008, down from 20% in the 1990s.
http://www.globalcarbonproject.org/carbonbudget/08/hl-brief.htm
Energy use
Construction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, …
Fossil fuel com-bustion
Industry
Industry
Human welfare
Energy use
Human welfare
Energy use
Construction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, …
Fossil fuel com-bustion
Industry
IndustryConstruction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, …
Human welfare
Energy use
Human welfare
Deforestation is often measured in ‘football fields per hour’; is football compatible with
avoided deforestation?
For example, “Amazon destruction has accelerated to record le-vels, according to figures released by the Brazilian government. The annual rate has reached 26,130 square km, the second highest ever - an area equivalent to about six football fields a minute are destroyed.
http://www.greenpeace.org/international/news/amazon-destruction
Is the goal achievable?
Is the playing field level?
Are the lines clearly marked?
What is the ball?
Is one tree + 30% grass enough to qualify as forest?
The white-man referee in the shade?
Who is watching on the sideline?
Who are the defenders?
Made from cer-tified wood?
Who is at play?
….are included under forest, as are areas normally forming part of the forest area which are temporarily
unstocked as a result of human intervention such as harvesting or
natural causes but which are expected to revert to forest;
[FCCC/CP/2001/13/Add.1]
Signs of deforestation?
Temporarily unstocked…
“FORESTers Forest” – the FAO definitionLand spanning more than 0.5ha with trees higher than
5m and a canopy cover of more than 10%, or trees able to reach these thresholds in situ. It does not include
land that is predominantly under agricultural or urban land use.
Forest without
trees
Non-forest without trees
Trees outside forest
Forest with trees
Forest definition based on insti-tutions & intent
Forest definition based on X% canopy cover
Including e.g. agroforests, oil palm plantation
Clearfelling/ re-plant is accep-
ted as forest; no time-limit on
‘replant’
REDD = idem, + (forest) degradation, or the shifts to lower C-stock densities within the forest; details very much depend on the operational definition of ‘forest’
RED = Reducing emissions from (gross) deforestation: only changes from ‘forest’ to ‘non-forest’ land cover types are included, and details very much depend on the operational definition of ‘forest’
REDD+ = idem, + restocking within and towards ‘forest’ ; in some versions RED+
will also include peatlands, regardless of their forest status ; details still depend on the operational definition of ‘forest’
REDD++ = REALU = idem, + all transitions in land cover that affect C storage, whether peatland or mineral soil, trees-outside-forest, agroforest, plantations or natural forest. It does not depend on the operational definition of ‘forest’
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
REDD_C
REDD+_C
REALU
REDD+_AB
REDD_AB
RED_B
RED_C
RED_A
Rule set
Fra
cti
on
of
ma
xim
um
em
iss
ion
s in
clu
de
d
Lampung
Jambi
Kaltim
Details of REDD accounting rules and forest definition have a major impact on the volume of ‘eligible’ emission reduction under a REDi+j scheme. Data for 3 provinces of Indonesia show low consistency when partial accounting rules are followed
REALU draft material for COP15
Agroforest
Trees out-side forest
Sustainable FOREST management Soil C
CH4
N2O
Replicable Processes:Boundary
objects
Independence:Boundary
organizations
TRUSTBoundary
agents
1. Local conflict resolution in forest margin in Sumberjaya
2. Emergence of Payments for Watershed Services in Singkarak
3. Adjustments in China’s Sloping Land Conversion Program (SLCP)
4. Global debate on forests and floods
5. Emerging global policies for REDD and their inconvenient truths
Local ecological knowledge
ModelersEcologicalknowledge
Public/policyecological knowledge
Context, Mechanism,
Consequence, outcome
Lessons for R&D institutions: science quality
Knowledge
Concepts, ideas, logical relations:
“how does it work?”
Achieving goals:
“so what…”
Space-time variation:
“when,where,what”
Stakeholder knowledgeand preferences:
Local (LEK) and Policy (PEK)
Market value chains (input & output)Farming praxis & experimentationNegotiated re- source accessPolicy reform & implementation
Monitoring & evaluation
Concepts, ideas, logical relations:
“how does it work?”
Achieving goals:
“so what…”
Space-time variation:
“when,where,what”
Models, specifichypotheses: MEK
K - sharing
MEK production
Experi-ments
Surveys & maps
Controlled
variability
Biophysical, socio-economic variation
Packaged technology
Tools
Q-con-trol
K-map-ping
Concepts, ideas, logical relations:
“how does it work?”
Achieving goals:
“so what…”
Space-time variation:
“when,where,what”
Stakeholder knowledgeand preferences:
Local (LEK) and Policy (PEK)
Models, specifichypotheses: MEK
K - sharing
MEK production
Experi-ments
Surveys & maps
Controlled
variability
Biophysical, socio-economic variation Packaged
technology
Tools
Q-con-trol
Market value chains (input & output)Farming praxis & experimentationNegotiated re- source accessPolicy reform & implementation
K-map-ping
Monitoring & evaluation
Local ecological knowledge
ModelersEcologicalknowledge
Public/policyecological knowledge
Local stakeholders,
peripheryScientists
Centralstakeholders
Knowledge
Action
Globally Appropriate Mitigation Actions (GAMA)
Nationally Appropriate Mitigation Actions (NAMA)
Locally Appropriate Mitigation Actions (LAMA)
‘NestedBaseline’
CO2 benefits: reducing emis-sions that are due to:
Planned change
Legitimate local actions
‘Illegal’ activities
CO-benefits:
Sustainable livelihood op-tions for the longer term, enhancing buffering of water flows and conser-vation of biodiversity
Actual emissions (or chan-ges in stock) in relation to Reference Emission Level
Additionality: difference with ‘business as usual’ development pathway
Leakage: effects on emissions elsewhere
Permanence: effects on future emissions (~ insu-rance & spreading risk)
certification
Registry and ‘rights to in-
vest’, attribution
Sale and use as off-sets
Local actors (incl
private sector, NGO’s,CBO’s)
Dis- trist & provin-ce govt
Natio-nal
Interna-tional
Independent verification
Rules of the game, eligibility of types of emission reduction
Transac-tion
costs
rights to land
use
Fairness& effi-ciency
RMARHA
RaCSA RABA
RaTAPALA
Tools for negotiation support: TUL-SEA
F,P,N,H,S capital F,P,N,H,S capital Goods&services Investment, payments
At every scale transition we need to consider:Realistic: Is it ‘additive’ or non-linear scaling?Voluntary: Does the currency need to change?
If so, what exchange rate?Conditional: How to ‘derive’ flow from stock and
build up stock through flows?
Crossing borders:
Passport – legitimacy
Currency
Language
Timezone
Trans-action costs
Sticks, sermons or carrots? What is the best way for the farmer to get the donkey to move towards the market?
Donkey, it is your due role in life to help me
move…
Discount rate for future
harvests
Farmer
benefit= (Price.Volume).(1-Risk)
Price.Input
+ REF . (Local + (1-t).PESexternal)
Harvested products
Climatic risk
Biotic riskEviction
risk
HH labour risk
Labour, Fertilizer, Pesticides, Drainage/ irrigation, Machinery
Transaction cost
Transfer/ compensation
*#^&$ ^&!!!
*#^&$ ^&!!!
Area * Yield
*#^&$ ^&!!!
Efficiency scale economics with REF appreciation
*#^&$ ^&!!!
Demand & control
Persuasion
Direct incentives
Farmer
benefit (Price.Volume).(1-Risk)
- Price.Input
+ESeffect . (Local +
(1-t).PESexternal)
=
Paradigm CES: ‘Commoditized ES’ or markets for commoditized environmental service procure-ment (or land use proxies with periodic full impact study)
Paradigm COS: ‘Compensating Opportunities Skipped’ or paying land users for accepting man-datory or volun-tary restrictions on their use of land
Paradigm CIS: ‘Co-investment in Stewardship’ and co-manage-ment of land-scapes for redu-cing poverty and enhancing ES, sharing risk and responsibility
Annex-I Emissions all sectors
Non-Annex-I CDM
REDD and SFM
PEAT SLM Agricult. intensi-fication
Alleviating rural poverty
Biofuel, agrocommoditiesExport of woodNon-accountable footprint
A/R
Ahead of COP15 negotiations, Indonesia's President Susilo Bambang Yudhoyono has committed cuts of up to 26 percent by 2020, or 41 percent with funding and technological support from developed countries.
Recap of contents• Science quality: the challenges of food security
and climate change, REF and RAF
• Sustainagility
• Agroforestry falling through the cracks?
• 5 INRM examples
• K2A and boundary work
• Multi-scale ES incentives to bring sustainability and sustainagility into the efficiency sphere
Meine van Noordwijk and Peter Akon Minang ETFRN Newsletter 50(2009): 5-10
“If we cannot define it, we cannot save it” Fuzzy forest definition as a major bottleneck in reaching REDD agreements at and beyond Copenhagen COP15
Meine van Noordwijk, Delia C, Catacutan, William C. Clark, 2009. Linking scientific knowledge with policy action in Natural Resource Management. ASB Policy Brief. http://www.asb.cgiar.org/publications/ view.asp?Pub_ID=1084
Meine van Noordwijk and Beria LeimonaCo-investment in natural capital or payments for
environmental ser vices? Paradigms, criteria and indicators for fairness and efficiency. Ecology and Society (under review)
Meine van Noordwijk, Jianchu Xu, Delia Catacutan, Rodel Lasco, Beria Leimona, Laxman Joshi, Ken E. Giller and Ujjwal Pradhan. Sustainagility science: A knowledge system for conservation, agricultural development and multifunctionality. PNAS (under review)
• Ma, X,, Xu, J. and van Noordwijk, M., 2009. Sensitivity of streamflow from a Himalayan catchment to plausible changes in land-cover and climate. Hydrological Processes in press
• Verbist, B., Poesen, J., van Noordwijk, M. Widianto, Suprayogo, D., Agus, F., Deckers, J., 2010. Factors affecting soil loss at plot scale and sediment yield at catchment scale in a tropical volcanic agroforestry landscape, Catena (2010)
• van Dijk, A.I.J.M., van Noordwijk, M., Calder, I.R., Bruijnzeel, L.A., Schellekens, Chappell, J.N.A., 2009. Forest-flood relation still tenuous – comment on ‘Global evidence that deforestation amplifies flood risk and severity in the developing world’ by C.J.A. Bradshaw, N.S. Sodi, K. S-H. Peh and B.W. Brook. Global Change Biology 15: 110-115
o Swallow, B. M., M. F. Kallesoe, U. A. Iftikhar, M. Van Noordwijk, C. Bracer, S. J. Scherr, K. V. Raju, S. V. Poats, A. Kumar Duraiappah, B. O.Ochieng, H. Mallee and R. Rumley. 2009. Compensation and Rewards for Environmental Services in the Developing World: Framing Pan-Tropical Analysis and Comparison. Ecology and Society 14 (2): 26. [online],o Leimona, B., Joshi, L. and van Noordwijk, M., 2009. Can rewards for environmental services benefit the poor? Lessons from Asia. International Journal of the Commons, Vol 3, No 1 http://www.thecommonsjournal.org/index.php/ijc/article/viewArticle/121
van Noordwijk M. 2009. Biofuel Emission Reduction Estimator Scheme (BERES): Land use history, current production system and technical emission factors. Bogor, Indonesia. World Agroforestry Centre - ICRAF, SEA Regional Office.
van Noordwijk M and Joshi L. 2009. REDD/REALU Site-level Feasibility Appraisal (RESFA). Bogor, Indonesia. World Agroforestry Centre - ICRAF, SEA Regional Office.
Dewi S, Khasanah N, Rahayu S, Ekadinata A and van Noordwijk M. 2009. Carbon Footprint of Indonesian Palm Oil Production: a Pilot Study. Bogor, Indonesia.World Agroforestry Centre - ICRAF, SEA Regional Office.
Swallow BM and van Noordwijk M. 2009. Agriculture and Climate Change: An Agenda for Negotiation in Copenhagen For Food, Agriculture, and the Environment Direct and Indirect Mitigation Through Tree and Soil Management (Policy Brief). Washington DC, USA. International Food Policy Research Institute (IFPRI).
C stock defi-cit
Water quan-tity & quality
Biodi-versity deficit
Local liveli-hood deficit
National economy and downstream ES beneficiaries (Goods and Services)
Climate Change Adaptation concepts and definitions
Anthropogenic greenhouse gas emissions, due to fossil fuel use, LU and ‘deforestation’
Vulnerability: human, biota & ecosystems
Adaptation: Shift and change to
reduce vulnerability
Mitigation: GHG
source control,
sink enhance-ment
Atmospheric change leading to climate change and shiftsPrimary
motivation for action
1
3
2
http://www.globalcarbonproject.org/carbonbudget/
China unveils emissions targets ahead of Copenhagen: Reduce "carbon intensity" by 40-45% by the year 2020, this means lower the amount of carbon dioxide emitted for each unit of GDP
0
10
20
30
40
50
60
70
80
90
100
1 6 11 16 21 26 31 36 41 46 51 56 61
Country rank
Cu
mu
lati
ve f
ore
st C
sto
ck (
%)
Lowest
Highest
Brasil + DR Congo + Indonesia contain 50% of
total forest C stock, 10 countries contain 2/3
Emissions from deforestationIndonesia +
Brasil + Malaysia cause 2/3 of REDD domain
emissions
ILUI = F E R T I L B O N D X
Energy (mechanization)
Number of crops per year
Crop diversity
Harvest index (1/organic
inputs to soil)
Fertilizer use
Irrigation
BiocidesLabour use
Non-used refugia and filters in the landscape
Invasive exotics
R = Time fraction for
crop & fallow (Ruthenberg)
Abiotic factors Biotic factors
(Climate Change Agriculture and Food Systems)
High human vulnerability to climate change coincides with low diversity parts of the world
High diversity parts of the world human may be less vulnerable to climate change, but loose diversity under CC
• We can predict the direction and size of the change, and plan to adjust what we do
• Uncertainty on di-rection of change but greater variabi-lity: we need to in-crease buffering & resilience: diversity
In both cases a ‘No regrets’ focus will focus on what makes sense anyway…
Limits to adaptation: plans or diversity approach
Two basic situations can be distinguished in adaptation:
http://portal.iri.columbia.edu/portal/server.pt
July 2009 Forecast of El Nino condi-tions: above-average rainfall in Kenya
In fact: late start of rains, below-average total as yet
Predictability of rainfall at gro-wing-season scale is still low
Hydraulic redistribution study in native tree species in an agroforestry parkland of West African dry
savannaJ. Bayala1, L. K. Heng2, M. van Noordwijk3, S. J. Ouedraogo1
1Département Productions Forestières, Institut de l'Environnement et de Recherches Agricoles, Ouagadougou, Burkina Faso,
2IAEA, Soil and water management and crop nutrition section, Vienna, Austria, 3World Agroforestry Center, South-East Asia, Bogor, Indonesia
Oecologia Plantarum – in press
Time (GMT)
-4.00
-3.50
-3.00
-2.50
-2.00
-1.50
-1.00
-0.50
0.00
111 21
717
313 23
919
515
111 21
0
10
20
30
40
50
60
70
Water potential (MPa)Temperature oCTranspiration (L hr-1)
-3.30
-3.20
-3.10
-3.00
-2.90
-2.80
-2.70
-2.60
-2.50
0
10
20
30
40
50
60
Water potential (MPa)Transpiration (L hr-1)
After the harvest of the millet crop, the soil shows the ‘normal’ day/night cycle of rewetting by tree roots (‘hydraulic redistribution’)…
but with an upward trend, suggesting that after the crop died off, the tree roots bring up more water at night than they themselves use during the day
Uncertainty, bias and its consequences in C accounting
Tree: size (diameter, height,…)
shape (allometrics)
wood density C-concentration
Species ID &lookup tables
Forest/Ag patch: frequency distribution . of trees of various types
Land area: mosaic of Forest/Ag patches
Time series: temporal change in mosaics
Mg C / year
Mg C
Mg C / ha
Mg C / tree
Trees / ha =
x
=
xha / LUtype
=
d /dt
Fernando Santos Martin: Australian J of Ag and Res Economics
(close to being ‘ac-cepted’…)
Profitability measures for farmers adopting high-Q trees are flat: no clear benefit…
..while national eco-nomic benefits would increase with more trees on farm
Primary reason:
Tax & levies on trees, subsidies for fertilizer and maize production;
Hydrological Processes, accepted
…The predicted changes in buffer indicator for land use + climate change scenarios reach up to 50% of the current (and future) range of inter-annual variability.
LowLow
Agricultural productivity
Degrading agricultural landscapes
High
Core wilderness/ natural forest
Polyculture
attractors
High
Intensive agroecosys-tem domain
Agroforest
domain
Degraded, aban-doned land
Low external input agro-ecosystems
Bio
dive
rsity
& a
ssoc
iate
d ec
osys
tem
ser
vice
s
Current dominant trend
Biodiversity-ba-sed alternative pathway
Landscape position
Jambi
Meeting today’s needs without compromising the future
10. Earth system re-
source governance
9. Natural resource ma-
nagement institutions
8. Agri-food systems
7. Rural landscapes
6. Desakota liveli-
hood networks
5. Agroecosystems
4. Farms, forests
3. Populations, fields
2. Organism during its
life cycle
1. Access to genetic
diversity
SustG10: New global deals (S)
SustG_9: New environmentality (H,S)
SustG_8: New food securities (H,I,S,F,N)
SustG_7: New landscape value chains (N,S,H,I,F)
SustG_6: New livelihood systems (H, S, F, I, N)
SustG_5: New interdependencies for lateral flows (N, H)
SustG_4: New farming systems and farm-scale resource management (N,H)
SustG_3: New cropping/AF systems and associated knowledge (N,H)
SustG_2: New crop/tree/animal management techniques (N,H)
SustG_1: New crop/tree/animal types domesticated on farm or accessible from external sources (N, H, S)
Sustainable global agreements
Sustainable iNRM institutions
Sustainable value chains
Sustainable Ecosystem Service incentives
Sustainable livelihoods
Sustainable agro-ecosystems
Sustainable farming systems
Sustainable soil fertility management
Sustainable cropping systems and practices
Sustaining genebanks releasing robust varieties
Sustainagility science: A know-ledge system for conservation, agricultural development and multifunctionality
Meine van Noordwijk1, Jianchu Xu1, Delia Catacutan1, Rodel Lasco1, Beria Leimona1, Laxman Joshi1, Ken E. Giller2 and Ujjwal Pradhan1
World Agroforestry Centre (ICRAF); correspondence: [email protected]
Wageningen University and Research Centre
Proc. Nat Acad. of Sci. (under review)
‘NestedBaseline’
CO2 benefits: reducing emis-sions that are due to:
Planned change
Legitimate local actions
‘Illegal’ activities
CO-benefits:
Sustainable livelihood op-tions for the longer term, enhancing buffering of water flows and conser-vation of biodiversity
Actual emissions (or chan-ges in stock) in relation to Reference Emission Level
Additionality: difference with ‘business as usual’ development pathwayLeakage: effects on emissions elsewhere
Permanence: effects on future emissions (~ insu-rance & spreading risk)
certification
Registry and ‘rights to in-
vest’, attribution
Sale and use as off-sets
Local actors (incl
private sector, NGO’s,CBO’s)
Dis- trict & provin-
ce govt
Natio-nal
Interna-
tional
Independent
verification
Rules of the game, eligibility of types of emission reduction
Transac-tion costs
rights to land
useFairness& effi-ciency
Landscape dynamics
Population density,Landscape resources, Cultural preferences
Migration
Carbon stocksWatershed function,
Biodiversity
Initial driversMarket access, Infrastructure,LU technology
Extension Access to land
New feedback mechanisms
External consequences
Land use & cover
change
Plot level soil
fertility
Aggregated
household
economics
Farmers’
decision making
& learning
Prices
Landscape dynamics
Population density,Landscape resources, Cultural preferences
Migration
Carbon stocksWatershed function,
BiodiversityInitial drivers
Market access, Infrastructure,LU technology
Extension Access to land
New feedback mechanisms
External consequences
Land use & cover
change
Plot level soil
fertility
Aggregated
household
economics
Farmers’
decision making
& learning
Land conversion & succession
Potential area for expansion
Land use& cover changeSpatial access & attractiveness
Farmers’ decision making & learning
Adjusting expected yield (Learning)
Labour allocation
Financial allocation
Learning style (α)
Land allocation
External information (β)
Plot level soil fertility
Soil fertility
Crop/plantgrowth & productivity
Yield Weather
Aggregated household economics
Trade
Food consumption Storage
Livelihoods (secon-dary consumption)
Financial capital
Profitability of land & labour
Plot level soil fertility
Soil fertility
Yield Weather
Land conversion & succession
Potential area for expansion
Land use& cover changeSpatial access & attractiveness
Farmers’ decision making & learning
Adjusting expected yield (Learning)
Labour allocation
Financial allocation
Learning style (α)
Land allocation
External information (β)
Aggregated household economics
Trade
Food consumption Storage
Livelihoods (secon-dary consumption)
Financial capital
Profitability of land & labour
Crop/plantgrowth & productivity
Migration
Extension Access to land
External ES consequences
Livelihoods
Carbon stocksWatershed function,
Biodiversity
Prices
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
0 50 100 150 200 250 300
Time-averaged C stock
V-i
nd
ex (
bio
div
ersi
ty)
Intensive rubber
Rubber agroforest
All trees in a sample area biomass per unit area
Single tree record: DBH, Species-ID, Height, …
Species-ID Wood density est.
Allo-metric equa-tion: biomass
+ understory + litter + soil + roots
Plot
Age i
Age nLand use system: typical C stock across its life cycle
Change in landscape-wide C stock sequestration/ emission estimate
Changing proportions of the different land use systems
In the landscape as a whole
Life-cycle cash-flow analysis (discounted): Net Present Value
Yearly input & output tables
Price vectors & wage rate
Discount rate
Bio-economic production model
Field data Mixed stand
growth modelField data
Opportunity cost curves
P
S
Business as Usual (BAU) or Alternative Scenario’s
All trees in a sample area biomass per unit area
Single tree record: DBH, Species-ID, Height, …
Species-ID Wood density est.
Allo-metric equa-tion: biomass
+ understory + litter + soil + roots
C
RED
REDD
REDD+
REDD+
+=REALU
Concerns
Tran
saction
co
sts1:
neg
otiatio
ns
Tran
saction
co
sts2:
Mo
nito
ring
Tran
saction
co
sts3:
Leakag
e con
trol
Avo
idab
le emissio
ns
Bio
diversity co
-ben
efits
Net b
enefits
Analysis of the negotiation options: to be filled with semi-quantitative estimates
Net cumulative emissions (t CO2-eq/ha/year)
0 5 10 15 20 25 30
Aba
tem
ent
cost
s ($
/t C
O2)
(lo
g sc
ale)
0.001
0.01
0.1
1
10
100
1000
Forested peat to
oil palm
Logged over p
eat to ru
bber
Forested peat to
settle
ment
Forested peat to
annual
cropping and sh
rub
Logged over fo
rest
to rubber
Net cumulative emissions (t CO2-eq/ha/year)
0 5 10 15 20 25 30
Aba
tem
ent
cost
s ($
/t C
O2)
(lo
g sc
ale)
0.001
0.01
0.1
1
10
100
1000
Forested peat to
oil palm
Logged over p
eat to ru
bber
Forested peat to
settle
ment
Forested peat to
annual
cropping and sh
rub
Logged over fo
rest
to rubber
Forested peat to
oil palm
Logged over p
eat to ru
bber
Forested peat to
settle
ment
Forested peat to
annual
cropping and sh
rub
Forested peat to
oil palm
Logged over p
eat to ru
bber
Forested peat to
settle
ment
Forested peat to
annual
cropping and sh
rub
Logged over fo
rest
to rubber
Jambi (peat lands included) : 31.2 t CO2 / ha / year,
92.7% below 5$/t CO2
$/t
CO
2
t CO 2 / (ha yr)
Huge percentage of emissions from luc areassociated with low economic benefit
Opportunity costs vary from place to place
Lampung
Emissions counted (annual cummulative emissions in t CO2-eq/(ha y))
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
log
$/t
CO
2_
eq
1e-3
1e-2
1e-1
1e+0
1e+1
1e+2
1e+3
RED_ARED_BRED_CREDD_ABREDD_CREDD+_ABREALU$ 5
Jambi
Emissions counted (annual cummulative emissions in t CO2-eq/(ha y))
0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0
log
$/t C
O2_
eq
1e-3
1e-2
1e-1
1e+0
1e+1
1e+2
1e+3
RED_ARED_BRED_CREDD_ABREDD_CREDD+_ABREDD+_CREALU$ 5
Kalimantan Timur
Emissions counted (annual cummulative emissions in t CO2-eq/(ha y))
2 4 6 8 10 12
log
$/t C
O2_
eq
1e-3
1e-2
1e-1
1e+0
1e+1
1e+2
1e+3
RED_A
RED_B
RED_C
RED_D
RED_E
REDD_AB
REDD_C
REDD_D
REDD_E
REDD+_AB
REDD+_C
REDD+_D
REALU
$ 5
Temporarily unstocked…
Energy use
Construction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, … Human welfare…
Fossil fuel combustion
IndustryForest and non-forest land cover are closely linked at 'driver' level, and cross-sectoral shifts in emission patterns ('leakage') needs to be accounted for in any emission reduction claim.
Forest Transition StagesForest Transition Stages
FOREST_COREFOREST_FRONTIER_1FOREST_FRONTIER_3FOREST_MOSAICS_1FOREST_MOSAICS_2
FOREST_FRONTIER1
FOREST_FRONTIER2
FOREST_MOS_2
FOREST_CORE
FOREST_MOS_1
2005 review
Policy focus
Certification in main export crops: cocoa, coffee, rubber, palm oil, biofuels
Local concerns:
1. Employment, la-bour absorption
2. Economic growth
Watershed concerns driving local EES
REDD/REALU implementation mechanisms: rights, institutions, governance
Global concerns:
1. C stocks & GHG emissions
2. Biodiversity
Landscapes with:
Natural Forest
Managed forest
Agroforest
Tree crops
Pasture
Food crops
…
Tropical forest margins
Tra
deo
ffs, ne
ed fo
r exte
rnal E
S
incentive
s, Ne
gotiatio
n Su
ppo
rt
Inten
sification h
ypo
the
sis re
jecte
d un
less…
NARS:(Tree) Crop
& Forest Managementinnovation
Climate change
2007 Bali agenda renewal
Interface with CC adaptation
Site network…
Eligibility of land-scape-scale ma- nagement for REDD incentives
Potential next steps…
Time
Emission outside the
REDD scheme
Sink outside A/R CDM scheme
C-stocks
t/ha
Fairness: the real conservation cost
Market Efficiency: the most real impact
Depend on definition
Forest
Conservation Production Conversion
Adapting livelihoods to climate change through multifunctional landscapes with trees
A1. CC Adaptation:
Basic concepts
A2. Multifunctional Landscapes
A3. Rural livelihoods and change
C4. Rights, institutional review and reform
C1. Methods to asses what is
‘Realistic’
C2. Methods to establish ‘condi-
tionality’
C3. Methods to create ‘Voluntary’ mechanisms for co-investment
Co
ncep
ts Targ
et Meth
od
s
B4. Current and future climate variability: global and local
B3. Tree growth and climate variability
B1. Trees and environmental services
B2. Supporting multi-functionality and
environmental services
0
0.1
0.2
0.3
0.4
0.5
0 0.1 0.2 0.3 0.4 0.5Fraction of land area
Fra
cti
on
of
fore
ste
d a
rea
Outside permanentforest estateConvertible pro-duction forestProduction forest
Limited productionforestWatershed pro-tection forestNature Reserve
1:1
1.5:1
1:1.5
Data for five provinces in Indonesia (one each in Sumatra, Kalimantan, Java, Sulawesi and Papua) show that actual tree cover does not differ much between the various ‘land use categories’ – the proportion of ‘non forest lands’ that has tree cover meeting the forest definition is close to that of ‘permanent forest estate’ lands in the same province
Source: Data for 2006 analyzed by BaPlan
Lesson 2
Lesson 4
Lesson 3
Gene
Product value chains
Patch/field
Organism
Population
Farm
Land-scape
Desakota network
Globe
National economy
Community
Watershed
Nation
Global institutions
National institutions
time
spa
ce
in
stitu
tions