Advances on the nested approach and specific VCS methods for unplanned deforestation

C A R B O N D E C I S I O N SI N T E R N A T I O N A L

MEASUREMENT, REPORTING AND VERIFICATION IN LATIN AMERICAN REDD+ PROJECTSA CIFOR WORKSHOP – MARCH 8-9, 2012 – PETRÓPOLIS, BRAZIL

Advances on the nested approach and specific VCS methods for

unplanned deforestation Juan Felipe Villegas

Álvaro Vallejo, Diego Navarrete,Lucio PedroniMarlon Ortega, Peter Schlesinger

What does a country need to be prepared for REDD +?

International REDD+ system

Country X (Forestlandia)

National government

Sub-National governments

Civil Society & local

communities

REDD+ Mechanism

UNFCCC

Regulated schemes

outside of UNFCCC

Voluntary markets

NATIONAL REDD + PROGRAM

REDD+ PROJECTS IN AREAS THAT ARE UNDER THE

NATIONAL GOVERNMENT JURISDICTIONS

SUB-NATIONAL REDD + PROJECTS

REDD+ PROJECTS IN AREAS THAT ARE UNDER THE SUB-

NATIONAL GOVERNMET JURISDICTIONS

REDD + PROJECTS IN PRIVATE AREAS

Distribution of the international incentives for REDD +

National government

International incentives for REDD+

1

Sub-national governments

Projects

5

4

6

UNFCCC model:

Incentives will go to the central governments (“Sub-national” = interim option).


Projects


Voluntary marketsmodel

3

National government

Sub-national governments

Projects

5


1

2

3

4

6

“Nested Appraoch”

VCS: Jurisdictional

and Nested REDD Initiative (JNRI)


Region

The “region” is the scale at which reference emission levels (RELs) are established. What is a “region” is determined by the country.

CountryThe national reference emission level (REL) is built from the regional RELs following a bottom-up approach.

ProjectAt the local level, RELs are derived directly from the regional REL following a top-down approach (“cookie cut” method).

Nested Reference Emission Levels in Guatemala and Peru

Guatemala5 sub-national regions

• 2 national workshops to define the regions.

• Each region has different agents and drivers.

• A REL will be developed for each region.

• The Northern Lowlands were chosen to develop the first REL.

Northern Lowlands

(4.12 Mha)

Mexico

Belize

El Salvador

Honduras

Guatemala: Northern Lowlands

Sierra del Lacandón

REDD+ Initiative

CONAP-Forestry Concessions REDD+ Initiative

Lachuá EcoregionREDD+ Initiative

• Most of the remaining forest is located in the Northern Lowlands.

• Three sub-regional REDD+ initiatives are in preparation. They cover most of the remnant forest in the Northern Lowlands.

Projection of the future deforestation rates according to the VM0015 methodology

1-) Approach “A”: Mean annual historical deforestation rate The average mean annual deforested area during the historical

referenced period is calculated and projected2-)Approach “B”: Deforestation as function of time

Deforestation is projected as a function of time when statistical relationships can be found3-)Approach “C”: Deforestation as a function of some other

variables.Deforestation could be projected using some other independent variables (Population, opportunity cost ,roads density)

Project developers normally want to show aggressive models but dataare not available and the criteria of the models are difficult to justify

Land use land cover map 2000



Technical limitations were found in the classification of the images

• Forest definition of the country or the jurisdiction

• Cloud cover

• Creation of LU maps for the last year of the historical reference period can be problematic

• Separation of heterogeneous carbon density land use classes is a challenge.

¿How good are the classifications for thehistorical reference period?

Accuracy assessment for the land use and land cover mapping

A global accuracy of 92.49% was achieved and an accuracy of 86 % for each of the classes. The requirements of the VCS methodology are 90

% for the overall accuracy and 80 % within the classes.

High deforestation rate

STRATUM 1: .Area (ha) = 1,227.05 * year - 2,450,993.30R² = 0.77 .

0

2.000

4.000

6.000

8.000

10.000

12.000

14.000

16.000

1998 2000 2002 2004 2006 2008 2010

Are

a d

efo

rest

ed

(h

a)

StratumHistorical Projected

2000-2007 2007-2010 2010-2020

1 0.58% 1.52% IncreasingSee

below

2 5.17% 8.66% Historical average 6.23%


1

2

3

Projected deforestation rates with the constraint analysis

0,00%

1,00%

2,00%

3,00%

4,00%

5,00%

6,00%

7,00%

8,00%

9,00%

10,00%

2005 2010 2015 2020 2025 2030 2035 2040 2045

De

fore

stat

ion

rat

e

Year

Estratum 1:Approach "B"

Estratum 2:Approach "A"

Estratum 3:Approach "A"

According to the JNRI ,Jurisdictions shall present a minimum of two potential baselines and shall justify the selected baseline

Year 2010

Projected deforestation

Year 2011


Year 2012


Year 2013


Year 2014


Year 2015


Year 2016


20Year 201717


20Year 201817


20Year 201917


20Year 202017


20Year 202117


220Year 2022022


220Year 2023022


220Year 2024022


220Year 2025022


220Year 2026022


220Year 2027022


220Year 2028022


220Year 2029022


220Year 2030022


Guatemala:Northern Lowlands

• 812 existing plots.

• 762 passed screening.

• Carbon stocks in above-ground and below-ground tree biomass (CO2-e/ha):

� 356.8 ± 25.0

� 460.9 ± 9.4

� 501.2 ± 23.7

� No-Forest

� Field measured plot

Carbon stocks

Carbon stock requirements

• A carbon density map would be needed for the jurisdictions, this would need to have consistency at the national level as well.

• Project developers need to have in mind that also carbon stock changes are methodological requirements.

• Carbon data for different pools are not always available but it could economically attractive to collect them when financial analysis are done

Estimation of baseline carbon stock changes

0

1.000.000

2.000.000

3.000.000

4.000.000

5.000.000

6.000.000

7.000.000

8.000.000

9.000.000

2005 2010 2015 2020 2025 2030 2035 2040 2045

An

nu

al T

CO

2e e

mis

sio

ns

Year

Emissions were estimated considering above ground biomass, below ground biomass, dead wood and wood products for the CONAP-

Forestry Concessions REDD+ Initiative

Peru

• Diverse country: deserts, dry forest, rainforest, mountain forest, paramo…

• ~68 Mha of forests: ranks 4th among high forest cover tropical countries.

Peru

• Reference levels are being established at the sub-national level:- Madre de Dios (8.52 Mha)

- San Martin (5.16 Mha)- Selva Central (10.36 Mha)- Cusco (6.60 Mha)

• Almost 50% of forested areas are being covered (30.64 Ma).

• 100% civil society funded.

• More than 40 REDD+ projects in preparation.

• Governments are participating.

Peru: San Martin

Governance of the REDD+ readiness process:

• Regional REDD+ roundtable: Regional gov. , National gov.(MINAM) Civil Society

• 3 REDD+ initiatives How to deal with baselines at

different scales occurring over the

same forest?

Peru:San Martin

Forest cover 2000

No-Forest

Forest

Peru:San Martin

Forest cover 2007

Deforested 2000-2007

No-Forest

Forest

Peru:San Martin

Forest cover 2010

Deforested 2000-2010

No-Forest

Forest

• 466 existing plots.

• 433 passed screening.

• Carbon stocks in above-ground tree biomass (CO2-e/ha):

� 317.0 ± 12.8

� 267.2 ± 11.0

� 253.3 ± 53.5

� 261.4 ± 96.4

� 201.8 ± 78.7

� Field measured plot

Peru:San Martin Carbon stocks

• Stratification for projecting the rate.

• Factor maps for projecting the location:- Distance to roads- Elevation- Slope- Distance to

settlements- etc.

• Model calibration using historical data.

Peru:San Martin Deforestation

projection

StratumHistorical rate Projected rate

2000-2005 2005-2010 2010-2030





2010-2030

Peru:San Martin Projected

deforestation

San Martín

Selva Central

Cusco

Madre de Dios

Projected deforestation(Work in progress)

2010-2020

San Martín

Selva Central

Cusco

Madre de Dios

Projected deforestation(Work in progress)

2010-2030

Lessons learned1. Nesting is a viable approach to create a consistent

framework of reference levels at multiple scales.

2. Some level of standardization of the methods used to develop regional (subnational) RELs is necessary.

3. Creating historical references has been more time consuming than expected (clouds!).

4. Models are only as good as the data collected to develop them.

5. The + of REDD (“Conservation”) is important: there are limitations in the capacity of models to capture the perceived deforestation threat.

6. Sub-national REDD+ initiatives have a great potential to help building national REDD+ schemes, but there is a need for coordination to ensure consistency and transparency.

C A RBON

DEC ISIONS

IN TERNATIONAL

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Advances on the nested approach and specific VCS methods for unplanned deforestation

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