griscom_rel_e_kali
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1) Three alternative methods for predicting deforestation rates at the district level in East Kalimantan were compared: simple historical rate, historical rate adjusted based on reference regions determined by cluster analysis, and spatially explicit modeling of future rates. 2) The predicted deforestation amounts from 2006-2009 generated by each method were compared to actual deforestation over that period. The reference region method, which used the historical rate of similar reference regions, performed best with errors less than 20% of actual deforestation. 3) The presenter suggested using the reference region method for sub-national scale RELs, while using a combination of modeled projections and book-keeping of planned events for project scales.
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3) Results from the Amazon Scenarios model have been used to estimate baseline deforestation and emissions reductions for several specific REDD+ projects in Brazil, including in the states of Amazonas, Rondonia, Acre, and Mato Grosso.
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This document summarizes the baseline deforestation rates projected for the Cordillera Azul REDD project area in Peru from 2008-2017. Historic deforestation trends were analyzed using satellite imagery from 1989-2003 to model baseline rates for districts surrounding the project area. Baseline projections estimated annual deforestation rates of 0.3-0.9% for the project area, which is higher than Peru's national average deforestation rate of 0.1%. The multi-stakeholder project aims to reduce deforestation through conservation and protection activities in the 1.4 million hectare Parque Nacional Cordillera Azul.
ApproachesToBaseline dganz
This document discusses approaches to establishing a baseline or reference emission level (REL) for measuring reductions in greenhouse gas emissions from forestry projects. It presents three common methods for projecting business-as-usual emissions: using historic data, modeled projections, or negotiated levels. Nested RELs set baselines at multiple scales from project to national. Key challenges include measuring forest carbon stocks and developing RELs simply yet credibly across scales in a transparent process.
Financing bfcp 14 july 2010 gt
This document discusses financing for the Berau Forest Carbon Program (BFCP) in Indonesia. BFCP aims to reduce deforestation and emissions while improving livelihoods. It requires $50 million in "core funding" by 2010 to achieve key outcomes through 2015. TNC will contribute $10 million and seek $2 million in private funds and $48 million in public funds. Public funding sources for REDD include commitments from several countries totaling $3.5 billion from 2010-2013. However, funding has not yet flowed to Indonesia at the level expected. Challenges include lack of GOI coordination, competing funds, scaling plans, and donor interests being spread thinly. Additional issues concern transparency, accountability, and
Benefit_sharing_reddex_natalie
- Indigenous lands in the Amazon account for 27% of the total area of Amazonas state in Brazil, playing an important role in protecting the forest.
- Traditional peoples in the Amazon depend on the forest for their livelihoods and have historically conserved the Amazon forest through their stewardship of the land.
- Programs like Bolsa Floresta provide payments to local communities in exchange for conserving the forest through reduced deforestation, benefiting biodiversity, ecosystem services, and climate change mitigation. The program supports over 6,000 families across 14 conservation units.
Helsinki benefit sharing
This document discusses partnerships for REDD+ programs and benefit sharing arrangements. It finds that effective partnerships are characterized by common expectations, communication, fully bargained agreements, incentives, legal recognition, mutual respect, understanding of conflicts, practicality, self-determination, trust, and verifiable obligations. Context also matters - where communities rely heavily on forests, clear understanding is most important. Benefit sharing arrangements should be open, verifiable, and promote social and economic development through cash payments, assistance, or alternative benefits. Identifying legitimate beneficiaries and mechanisms to transfer benefits requires learning from other experiences and considering transaction costs and capacity.
ImpactAssesment mrichards
The document summarizes a manual for conducting social impact assessments of land-based carbon projects. It outlines 7 stages of social impact assessment: 1) original conditions study and stakeholder identification, 2) social reference scenario, 3) project design and theory of change, 4) negative impacts and mitigation, 5) indicator selection, 6) monitoring plan, and 7) data analysis and reporting. It emphasizes using a theory of change approach to link project activities to outcomes and impacts. Participatory methods are recommended for cost-effective data collection. The manual was field tested in 2019 and will be published in early 2011.
conservation and low carbon Leonel
Mexico has opportunities to pursue REDD+ conservation and low carbon development. It can build institutional capacity, improve existing programs like payments for ecosystem services, promote sustainable forest management, and improve monitoring of land use change using its national forest inventory. Mexico's GHG emissions include around 10% from land use and forestry, mainly from deforestation and degradation. The country is developing a national REDD+ strategy with implementation at different scales, from community projects to national programs. This will help transition Mexico's forest sector from a source of emissions to a carbon sink through activities like reforestation, sustainable forest management, and payments for environmental services.
Reflection on Pilots Ithompson
The document discusses Brazil's use of pilot projects to test methods for reducing emissions from deforestation and forest degradation (REDD). It notes that pilots must be carefully nested within state, national, and global carbon accounting and regulatory frameworks. Successful pilots engage a variety of stakeholders and address key issues within Brazil like ranching, logging, land ownership and monitoring, reporting and verification of emissions reductions. Pilots are an important part of developing the tools and lessons needed to build large-scale REDD programs.
MatoGrosso Micol
This document discusses building a REDD strategy for Mato Grosso State in Brazil. It provides context on Mato Grosso's geography, economy, and deforestation rates. A process is outlined for developing the state's REDD strategy from 2007-2010, which includes establishing baselines and targets, technical frameworks, programs and projects. Key components of the planned REDD plan are described, such as scope, legal frameworks, and funding strategies. Main challenges are identified, including integrating with federal efforts, adopting technical guidance, and defining a funding strategy.
Amazonas Natalie
The document summarizes actions taken by the state government of Amazonas, Brazil to reduce deforestation and address climate change between 2003-2010. It notes that deforestation decreased 73.94% while GDP increased in Amazonas during this period. Key actions included establishing protected areas, implementing programs like Bolsa Floresta to support sustainable communities, and developing legal and policy frameworks around ecosystem services and REDD+.
Indonesia discussion
This document discusses three main topics: policies, institutions and coordinating mechanisms; finances and financial management; and low carbon development strategies. It likely focuses on climate change mitigation and outlines the key factors that need to be addressed at a strategic policy level to support a transition to a low carbon economy and sustainable development.
reddex bfcp hartanto
The Berau Forest Carbon Program is a REDD+ demonstration project in Berau district, Indonesia that aims to reduce deforestation and forest degradation emissions by 20 million tons of CO2 per year. The program will test strategies like sustainable forest management, oil palm best practices, and community livelihood improvements over 5 years. It seeks $50 million in funding to manage 800,000 hectares of land and benefit 5,000 communities while documenting lessons for national REDD+ policies. Challenges include securing funding and enhancing local capacity under Indonesia's developing REDD+ framework.
Global Environment Facility - Ulrich Apel
The Global Environment Facility (GEF) unites 182 member governments and partners to address global environmental issues like biodiversity, climate change, land degradation, and forests. It is the largest financier of forests, investing $1.5 billion to supplement over $4.5 billion in co-financing for over 300 forest conservation and management projects. GEF provides grants to developing countries for sustainable forest management and REDD+ projects that generate multiple environmental benefits. It works through 10 implementing agencies and focuses on reducing deforestation pressures while strengthening policies to reduce emissions and increase carbon sinks from land use.
WWF Forest Carbon (Liliana)
The document discusses WWF's Forest Carbon Initiative (FCI) and its strategy for engaging with REDD+ between 2010-2013. The strategy focuses on 5 components: 1) influencing global REDD+ policy, 2) supporting national REDD+ readiness, 3) implementing early action REDD+ projects, 4) mobilizing REDD+ financing, and 5) developing MRV systems. The goal is to help ensure REDD+ effectively reduces emissions and benefits biodiversity, livelihoods and indigenous peoples' rights.
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- 2. REDDeX Conference, Cancun, July 14, 2010 Comparison of REL Methods for Districts of East Kalimantan, Indonesia. Bronson Griscom, Sr. Scientist Forest Carbon John Kerkering, Conservation Analyst
- 3. Question: What is the most accurate method for predicting the amount of deforestation within districts of East Kalimantan?
- 6. Rate derived from “reference region.”
- 7. Spatially explicit modeling3 “Planned” (e.g. legal license to log/convert) 2
- 8. 1 Predicted deforestation in each district = Historic rate in each district 2000 2005
- 9. 2 Predicted deforestation in each district = Historic rate of reference region …where reference regions are determined by cluster analysis Cluster Anal.
- 10. 3 Predicted deforestation in each district = Modeled future rate in each district …using spatially explicit model at regional (province) scale.
- 12. Selection of Model “Drivers” 3
- 13. Selection of Model “Drivers” 3
- 15. Comparison of Three Methods Predicted area deforested from 2006-2009 minus Actual area deforested from 2006-2009 (as % of actual area deforested) 3 2 1
- 16. Comparison of Three Methods 3 2 1
- 17. Comparison of Three Methods 3 2 1
- 18. Why do cluster reference regions seem to work? 2
- 19. Question: What is the most accurate method for predicting the amount of deforestation within districts of East Kalimantan?
- 21. I suggest reference region method 2
- 22. Nested RELs National Scale: Historic mean, with negotiated adjustments? Sub-National Scale (e.g. State/Province): Modeled projection, to determine proportion of national emissions pie? Separate models for deforestation vs. degradation? Project Scale: Mixed. Modeled projection for unplanned events? Book-keeping for planned events / strategies?
- 23. thanks! Bronson Griscom bgriscom@tnc.org
Editor's Notes
- Let’s consider reference region method 2 because:Seems to be relatively accurate.Pretty intuitive (even though some geeky stats).Facilitates nesting to national scale.Might encourage competition to reduce deforestation rates.