Building a baseline for the Cordillera Azul REDD project, Peru

David ShochTerraCarbon LLC

14 July 2010

REDDex conferenceCancun, Quintana Roo, Mexico

An effort beyond the skill set of any one person or organization

TerraCarbon• David Shoch• Scott Settelmyer• Victor Barrena

(Facultad de Ciencias Forestales, Universidad Nacional Agraria La Molina)

• Marlon Ortega• Jedi Rosero

Centro de Conservación, Investigación y Manejo de Areas Naturales (CIMA)•Lucia Ruiz•Tatiana Pequeño•Roxana Otarola•Raul Tinoco•35 PNCAZ guardaparques

The Field Museum• Debby Moskovits• Elizabeth

Anderson• Mario Pariona• Alaka Wali• Christy

Magerkurth• Helen Howes

Parque Nacional Cordillera Azul (PNCAZ)

• 1.4 million hectares spanning 7 provinces in 4 departments

• National park status established in 2001

• CIMA and Field Museum support park management since 2002

• CIMA and Government of Peru (SERNANP) signed a 20-year full management contract in 2008

Parque Nacional Cordillera Azul (PNCAZ)

• For >30 years, San Martin and Loreto departments have had the highest deforestation rates in the Peruvian Amazon

• Classic agricultural frontier readily apparent from satellite imagery

Projecting baseline rates of deforestation:

Historic trends and

Modeling from drivers

Baseline rate of deforestation

• Modeled on basis of historic trends and driver (population)

• Reference region = PNCAZ and surrounding districts (3.8 million ha)

• Fairly uniform ecological and geographic features and demographic and socioeconomic pressures

• Timeframe: 1989 to 2003 (in the absence of conservation/ protection activities)

Districts with < 50% forest cover in 1999 = “settled”

• Longer history of occupation with more urbanized population less directly dependent on land-use

• No strong correlation between population and deforested area

Districts with > 50% forest cover in 1999 = “frontier”

• Mostly districts directly bordering the park, represent earlier stage of colonization along the frontier gradient

• As expected, strong correlation between population and deforested area

Projecting historic rates forward in settled districts

• Rates assessed from a time series of classified Landsat imagery (CIMA and CI): 1989 -1999 - 2003

• Net deforestation assumed to be equal to gross conservative (net deforestation always < gross)

• “Negative” deforestation (i.e. net increase forest cover) set to zero – gross deforestation can never be negative

• 10-year projection of average historic rate 1989-2003 conservative (average rate increased from 1989-1999 to 1999-2003)

• Applied as a nominal value (not %) – realistic where agricultural frontier is unconstrained (i.e. approaching an unprotected wilderness area)

Projecting rates of deforestation in frontier districts based on correlation between population and forest area

Lugo, Schmidt and Brown 1981

Correlating population and non-forest cover

• Data sources: – Time series of classified Landsat imagery to

produce district level forest : non-forest cover for 1989, 1999 and 2003

– Official GoP district level population data from Instituto Nacional de Estadística e Informática (INEI) for 1989, 1999 and 2003

– Official GoP district level population projections from INEI 2008-2017 (projected forward from 2007 census)

• Units: – Hectares non-forest in district– Population (total individuals) in district

Methods and results

• Data combined for all years (n=37)• Significant correlation:

deforested area = 593 + 4.4 * population size• For each year analyzed independently, model

parameters similar and all significant (and slopes did not differ significantly among years, even though pop ↑41% and non-forest area ↑13% over the period) significance of relationship not a product of

autocorrelation Indicates relationship is stable over time and

appropriate for projections

Projecting rates of deforestation in frontier districts based on correlation between population and forest area

• Apply relationship as a predictor 4.4 ha deforested per additional person

• Not important that the relationship be directly causal

• Assume districts with ↓ pop have zero gross deforestation conservative because deforestation continued in these districts between 1989 and 2003

Area deforested used as the dependent variable in the model, rather than area deforested per year (i.e. annual rate)Advantages• Improved resolution – as compared with annual

rate estimates, errors around area deforested estimates (i.e. cumulative of rates) were low compared with the absolute values of the area deforested estimates

• Area deforested is more conservative than area deforested per year, because the former incorporates any reversion back to forest, i.e. is a better reflection of long-term loss of forest cover

Disadvantages• No explicit time element• Application in baseline employs simplistic

assumptions that deforestation occurs simultaneously with population increase

Baseline projections of deforestation – overall results

• Projections to be revised every < 10 years to account for changes in land-use and population dynamics

• Resulting deforestation projected annually equivalent to 0.3 to 0.9% deforestation from 2008 to 2017 (Peru national average 0.1% annual deforestation 1990-2005; FAO Global Forest Resources Assessment)

Thank you!

David Shoch

+1-434-326-1144david.shoch@terracarbon.com

About TerraCarbon

• TerraCarbon LLC was established in 2006 as a carbon markets advisory firm specialized in the agriculture, forestry, and other land use (AFOLU) sector.

• Our mission: To provide technical and business expertise to develop high quality forest and land-based carbon projects that mitigate climate change.www.terracarbon.com.