Wildlife Works is thrilled to announce a publication, ‘A novel deforestation risk and baseline allocation model for the next generation of nested REDD+ projects’ in the Nature’s Portfolio Journal, Scientific Reports, from a team of scientists from Everland and our own staff. This achievement underscores our commitment to in-house expertise, which is critical for ensuring the high-quality of our projects and for effectively leading the voluntary carbon market towards higher integrity.
Key takeaways:
There is an urgent need to scale REDD+ projects across jurisdictions; however, methodologies for allocating national baselines have not been standardized nor tested. This new research represents the first time a risk allocation model has been tested, providing a tool for jurisdictions to standardize how they set baselines.
The Baseline Allocation for Assessed Risk (BAAR) is a tool for predicting and allocating deforestation risk, based on the proximity to recent deforestation hotspots.
This innovative approach enables higher baseline deforestation rates to be allocated to REDD+ projects facing higher future deforestation risks, without the risk of inflated baselines jeopardizing the integrity of jurisdictional programs.
BAAR enables REDD+ finance to be allocated fairly and effectively to Indigenous Peoples and Local Communities on the frontlines of tropical deforestation.
BAAR provides an efficient tool for national governments to protect their most threatened forests while achieving their Nationally Determined Contributions (NDCs) towards the Paris Agreement.
The BAAR model allows nested baselines to be shared with developers, investors and communities in advance of project commitments. Early knowledge of project baselines elevates market integrity as it supports crucial decision making processes for these stakeholders.
The next iteration of the BAAR approach has already begun to incorporate advancements in remote sensing science and updated carbon market policies and regulations.
“The BAAR model marks a practical advance in predicting and allocating deforestation risk, based on the proximity of remaining forests to recent deforestation hotspots," said Jeremy Freund, Chief Technology Officer at Wildlife Works and co-author of the paper. “Wildlife Works has used the BAAR approach for more than 10 years, and we are now making this work publicly available to enrich the current discussions on how best to design jurisdictional programs with nested projects as the carbon market for NBS is rapidly advancing.”
The Need for Standardized Baselines in the Voluntary Carbon Market
Protecting tropical forests is crucial in the fight against climate change. REDD+ (Reducing Emissions from Deforestation and forest Degradation) projects have emerged as a powerful tool, paying local communities and governments in developing countries to reduce deforestation. REDD+ projects work by comparing deforestation levels to the “baseline” scenario of what would have happened without the project. Recent media scrutiny has questioned the accuracy of baseline deforestation predictions in these projects.
In pursuit of continuous improvement, the REDD+ sector has been working to transition how it sets these baselines. Traditionally, a project would use a reference region with no REDD+ activities to serve as a basis to set its baseline. While intuitive, this approach does not always align with national / jurisdictional REDD+ strategies, which is a component to high-integrity credits.
To enable this alignment, projects will have “nested” baselines; this involves taking a reference level of deforestation emissions from an entire jurisdiction (e.g., country or state), and allocating portions to projects.
There are different ways to allocate nested baselines. One way to do this is based on how likely an area is to be deforested in the future. This approach is important because it can be used by governments to focus voluntary carbon market finance in areas where it is most needed.
There is an urgent need to scale REDD+ projects across jurisdictions; however, methodologies for allocating national baselines have never been tested nor standardized. This new research represents the first time a risk allocation model has been tested. BAAR provides an intuitive and science-backed tool for jurisdictions to standardize how they set baselines.
Introducing The Baseline Allocation for Assessed Risk (BAAR) Method
The Baseline Allocation for Assessed Risk (BAAR) method maps deforestation risk and allocates baselines using past deforestation data to predict where forests will be most at risk in the future.
The model uses a historical dataset of at least 10 years of land cover change data to map future deforestation risk across standing forests within a jurisdiction. The historical dataset is split temporally into two five year periods: a prediction and validation period. In this approach, the most significant spatial driver of future deforestation is mapped using the proximity to past deforestation. The model's predictive power is evaluated by comparing the predicted risk with observed deforestation in the validation period.
In the paper, BAAR is tested in the Democratic Republic of Congo (DRC) as an example jurisdiction.
Caption: An example of a deforestation risk map generated by BAAR. The risk map takes into account the risk of deforestation, as well as the DRC’s policy goals. Based on this risk map, 50,811,803 ha of forest (36%) were classified as high risk and the remaining 90,050,069 ha (64%) were classified as low risk.
The paper showcases how the BAAR model can handle scale and complexity to enable the standardization of nested project baselines. This allows alignment with the jurisdictional programs’ climate goals, while still reflecting the risk of future deforestation accurately for each project.
A key component that the BAAR model considers when allocating a FREL is the minimum project efficacy (MPE). The MPE represents the total high-risk area that must be conserved (i.e. remain forest) to meet the country’s Nationally Determined Contributions (NDCs) towards the Paris Agreement.
By presenting the BAAR method, our team aims to increase transparency around baseline setting in the voluntary carbon market.
Our team is already working on improving BAAR. The next version will use more advanced satellite data to include both complete deforestation and forest degradation, while considering updated carbon market policies and regulations.
Wildlife Works is Leading in the Transition to Nested Projects
Wildlife Works is leading in the transition to nesting projects within jurisdictional programs. The Mai Ndombe REDD+ Project was the first project to be nested into a jurisdictional program under the National Government of the Democratic Republic of the Congo (DRC). Our Developers Best Practice Guide, written in partnership with The Nature Conservancy, introduced the first application of the BAAR model.
Lastly, The BAAR method allows nested baselines to be shared with developers, investors and communities in advance of project commitments. Early knowledge of project baselines elevates market integrity as it supports crucial decision making processes for investors, project developers and Indigenous Peoples and local communities, who increasingly depend on fair and accurate baselines to create the financial opportunity needed to protect forests.
“BAAR is a transparent and intuitive method for producing large-scale deforestation risk maps that can be used to baseline any nested REDD+ project. And while this is a first iteration of this method, the DRC maps we’ve produced allow buyers, governments and developers to see clearly which forests are at the greatest risk – ultimately demonstrating where REDD+ projects could deliver greatest impact,” says, Dr Maren Pauly, co-author and Everland's Director of Evaluation and Research
BAAR, a risk-based mapping approach, has shown to be an effective tool for determining fit-for-purpose baselines that lead to more accurate predictions and enables finance to flow to communities who need it to halt tropical deforestation.
About the research team:
Emily Dangremond holds a PhD in Integrative Biology from the University of California, Berkeley. She formerly served as an assistant professor at Roosevelt University and has been working as a Scientific Writing Manager for Wildlife Works for two years. Emily enjoys spreading her love of biology with others, through teaching, her podcast, and her latest children’s book, “Meet the Trees.”
Will Gochberg received his PhD in political science from the University of Washington, Seattle in 2020. After completing a postdoctoral position in the Political Science department at Washington University in St. Louis, he joined the Wildlife Works team as a Technical Climate Policy Analyst in 2022.
Maren Pauly holds a PhD in Natural Sciences from the Free University of Berlin. She is currently the Director of Evaluation and Research at Everland. Everland represents the world’s largest portfolio of high impact REDD+ forest conservation projects.
Jeremy Freund is the Chief Technical Officer of Wildlife Works, and has been with the company for over 14 years. He received his Bachelor’s Degree in Aerospace Engineering from the University of Colorado Boulder and his Master’s Degree in Physical Geography from The University of California Santa Barbara. He has played a key role in creating and implementing foundational methodologies for Avoided Deforestation REDD+ projects since the market’s inception.
Mike Korchinsky is the Founder and President of Wildlife Works. With a BSc in Chemical Engineering from the University of Birmingham, Mike has applied his problem-solving engineer’s mindset to tackle the issues of global deforestation, and has 15+ years experience in creating and implementing foundational methodologies for Avoided Deforestation REDD+ projects since the market’s inception.
