Track: C1. Empowering Rapid Carbon Neutrality
Background/Objectives
Natural climate solutions (NCS) have the potential to cost-effectively mitigate a third of the global greenhouse gas (GHG) emissions needed to stabilize the climate, alongside significant reductions in fossil fuel emissions. As the number of NCS projects increase, so do the tools, approaches, and funding for leveraging nature to mitigate climate change. Teams experienced in conservation now must apply new technical skills and methodologies to be successful. However, there is a lack of unified approaches for evaluating NCS opportunity and measuring progress. Teams working in isolation are likely to repeat others’ mistakes, resulting in inefficient use of time and funds and inconsistent measurements of success. By investing in rapid learning cycles to define and pilot holistic monitoring, evaluation, and learning strategies we can identify best practices and enabling conditions across a range of NCS actions, and thus iteratively improve NCS projects and more rapid enable progress towards global climate change mitigation goals. The Nature Conservancy (TNC) with its global network is ideally placed to support local partners while harnessing insights from across a broad portfolio of field projects.
Approach/Activities
The NCS Prototyping Network is testing high-impact strategies around the world. TNC teams in Africa, Asia, and the Americas are filling critical knowledge gaps that will contribute to larger-scale and more effective implementation of the emerging and understudied NCS areas of peatlands, agroforestry, and blue carbon. Global and local teams are collaborating on interdisciplinary, cross-cutting approaches to natural, geospatial, and social science methods. We are pioneering new technologies and novel methods, including satellite remote sensing, drones, artificial intelligence, greenhouse gas analyzers, new field data collection methods, carbon market methodologies, econometrics, impact evaluation, and more. 15 TNC-led NCS projects are using these tools to improve mapping of ecosystems and NCS opportunity areas in data-poor systems; measure carbon stocks and GHG fluxes; evaluate project impact; and assess feasibility factors, such as costs and co-benefits to people and nature. To support field teams, we have built ecosystem-specific peer learning networks and developed capacity building opportunities on topics ranging from carbon accounting and science communication to systems thinking and human rights. We use a regular adaptive management process to identify and track conditions for success, common challenges, and areas for adjustment. In addition to informing iterative project improvements, lessons are shared and successes celebrated across the network.
Results/Lessons Learned
Using this adaptive management framework to track lessons over the last few years allows us to see key patterns emerging. First, the importance of building equitable solutions strongly rooted in community engagement and trust, including navigating gender roles and working across generations. Second, contingency planning for institutional factors such as permitting, electoral cycles and general bureaucratic turnover, and political instability. Third, overcoming data and knowledge gaps requires a strong investment in research, capacity building, and science infrastructure. Fourth, logistics of collecting field data across remote locations, variable weather patterns, and safety conditions should not be underestimated. Fifth, despite growing global interest in NCS, significant funding gaps for NCS persist, compounded by macroeconomic pressures. In addition to various forthcoming scientific results, we are learning how to structure and adapt NCS projects to succeed in the face of challenges, how to deploy innovative tools and technologies, and the value of a cross-project, international network for enabling success. Following from these learnings, now is the time to develop a roadmap to guide fast, effective, and equitable scaling of NCS by enabling rigorous monitoring of project progress, timely evaluation of project success, and collaborative learning to inform the next generation of NCS project development.