WRI develops practical solutions that improve people’s lives and ensure nature can thrive. Programs focus on solving seven major challenges at the intersection of environment and human development: Cities, Climate, Energy, Food, Forests, the Ocean and Water. The organization works with partners in more than 50 countries and currently have offices in 12 countries: Brazil, China, Colombia, Ethiopia, India, Indonesia, Kenya, Mexico, the Netherlands, Turkey, the United Kingdom and the United States.
How to integrate the different scales from local to global in the preservation and restoration of forests?
Any attempt to conserve or restore forests will only be sustainable if it fulfills the aspirations and rights of local stakeholders, including Indigenous peoples, local communities and smallholder farmers. At the same time, humanity is putting unprecedented pressure on the world’s land, and barreling toward climate, biodiversity, and humanitarian crises. This pressure is driving increasing competition over finite land resources – a global land squeeze.
While there is no simple way of reconciling local and global perspectives on forest use, the “landscape” is a scale where markets and investors across multiple sectors intersect with the specifics of local governance, ecology and rural development aspirations. Landscapes provide a challenging, yet feasible scale to develop sustainable land-use mosaics and assess and negotiate trade-offs amongst competing land-uses. In addition, the accuracy and timeliness of global geospatial data, means it is becoming easier to assess the forest impacts of local action within a landscape or across multiples landscapes.
Initiatives to fight deforestation or restore forests as well as funding are launched by both private and public actors. How can we strengthen cooperation between these sectors to accelerate action for forests?
Carbon markets and the need to restore degraded land to productivity provide opportunities for strong cooperation between private and public actors on forests. As a carbon markets example, the Lowering Emissions by Accelerating Forest Finance (LEAF) Coalition mobilized $1 billion USD in financing in 2021, kicking off the largest-ever public-private effort to protect tropical forests. Ahead of COP26, dozens of jurisdictions submitted proposals to the LEAF Coalition and five countries have signed Letters of Intent with Emergent, the body that coordinates and facilitates LEAF transactions.As a restoration example, 32 African countries have pledged to begin restoring 128 million hectares of degraded and deforested land by 2030, through the AFR100 Initiative. In its second phase through 2026, AFR100’s finance architecture will combine development assistance funding, investments from the private sector, and domestic budget allocations from African governments and efficiently disburse billions of dollars to community leaders.
What are the 3 priority actions to implement to reach the Global Forest Goals by 2030 in your opinion?
Humanity cannot keep warming below 1.5 degrees without forests. COP26 delivered powerful pledges on forests, yet past commitments have gone unmet. This time, we need to make sure countries and companies are accountable for achieving their promised impacts. Geospatial data is ushering in a new era of monitoring, reporting and verification because it shows where forest cover is contracting or expanding and where CO2 is being emitted or removed from the atmosphere. If timely and open, such data informs decisions on what needs to be done where and shows whether efforts to protect or restore forests are succeeding.
Three actions – monitoring, reporting and verification – can drive accountability for realization of forest pledges. This will require continued investment in improving data, e.g., via WRI’s Land & Carbon Lab, and its access via open data platforms such as Global Forest Watch. The accountability will come through a combination of monitoring, reporting and verification done by governments and companies making pledges, and what can be observed from independent geospatial data.