The status of science to support REDD+ based mitigation policies of Mexico Bernardus de Jong, El Colegio de la Frontera Sur Fernando Paz, Colegio de Postgraduados Marcela Olguin, El Colegio de la Frontera Sur Jorge D. Etchevers, Colegio de Postgraduado Carlos Omar Cruz, Instituto Nacional de Estadística y Geografía 3rd NACP ALL-INVESTIGATORS MEETING, New Orleans January 31- Febr 4 NACP: Science to Inform Carbon Management and Future Projections Thursday, February 3
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The status of science to support REDD+ based mitigation policies of Mexico
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The status of science to support REDD+ based mitigation policies of Mexico
Bernardus de Jong, El Colegio de la Frontera SurFernando Paz, Colegio de PostgraduadosMarcela Olguin, El Colegio de la Frontera Sur Jorge D. Etchevers, Colegio de Postgraduado Carlos Omar Cruz, Instituto Nacional de Estadística y Geografía
3rd NACP ALL-INVESTIGATORS MEETING, New Orleans January 31-Febr 4NACP: Science to Inform Carbon Management and Future Projections
Thursday, February 3
REDD+ is accepted at COP16:
Emission reductions
Stock conservation and enhancement (removals)
1. Stock * LU-change
2. Stock change * LU-change
Deforestation
Degradation Deforestation
ReforestationRecovering
1.2.1.2.2.
National
State
Region
Land owners Land owners
Region
Land owners
Bottom up-Top down Strategy
Reference emission scenario
Annual rates of change (ha/yr), based on national LU maps 1993-2002 2002-2007Gross Deforestation 595,400 590,400Reforestation (natural and planted) 264,600 392,700Net Deforestation 330,800 197,700 Degradation 633,000 415,800Recovering 176,000 109,400Net Degradation 457,000 306,400
Historical rates of forest conversion
5 * 5 km in forested areas (1600 m2) 20 * 20 km in non-forested areas Quantitative data on trees and shrubs Semi-quantitative data on other pools Litter, CWD and Soil carbon
measurements from 2009 onward 20% re-measured every year
Develop biomass density maps to estimate level of emissions from LU-change.
National inventory data and national database of biomass equations
Allometric equations to convert inventory and other data to volume or biomass
BiomassVolume
Addionally:
4 Generic equations for trees according to ecosystem (Tropical humid, tropical dry, cloud forest, scrub desert)
- 50.0 100.0 150.0 200.0 250.0 300.0 350.0
BABA/VSA
BBBB/VSa
BCBGBJ
BJ/VSaBM
BM/VSABP
BP/VSABPQ
BPQ/VSABQ
BQ/VSaBQP
BQP/VSABS
BS/VSa
Av Biomass and 95% CI
Estimate biomass density in each forest type
123456789
1011121314151617181920212223242526272829303132
0 50 100 150 200
Oak primary
Oak secondary
Mg Biomass ha-1
Stat
e ID
Assign biomass densities to each polygon of the LU maps
(Trees and shrubs)
250
0
y = 52.432Ln(x) - 48.869R2 = 0.9667
y = 50.553Ln(x) - 42.742R2 = 0.7897
0
20
40
60
80
100
120
140
160
180
200
0 20 40 60 80 100
Age
Biomass (Mg/ha)
Methodologies to estimate growth
• Chronosequence• Growth ring analysis• Permanent monitoring plots
Stock change:
Identify forest areas that are under high risk due to drivers
National
State
Region
Land owners Land owners
Region
Land owners
Bottom up-Top down Strategy
81.3% forests and 18.2% grasslands73.3% with tree dominated canopy.66.1% are degraded forest.
BIOSPHERE RESERVE «EL OCOTE»
SCALE EFFECT
1:250,000 1:5,000
88.2% forests y 10.5% grasslands.70.1% with tree dominated canopy.30.2% are degraded forests.
Intact forestDegraded forestNon-forest
Detailed mapping from
satellite images to develop
community-based reference
scenarios and monitoring systems
Satelllite derived LU maps combined with land tenure maps