  Natural climate solutions (NCS) are critical for mitigating climate change
through ecosystem-based carbon removal and emissions reductions. NCS
implementation can also generate biodiversity and human well-being co-benefits
and trade-offs ("NCS co-impacts"), but the volume of evidence on NCS co-impacts
has grown rapidly across disciplines, is poorly understood, and remains to be
systematically collated and synthesized. A global evidence map of NCS
co-impacts would overcome key barriers to NCS implementation by providing
relevant information on co-benefits and trade-offs where carbon mitigation
potential alone does not justify NCS projects. We employ large language models
to assess over two million articles, finding 257,266 relevant articles on NCS
co-impacts. We analyze this large and dispersed body of literature using
innovative machine learning methods to extract relevant data (e.g., study
location, species, and other key variables), and create a global evidence map
on NCS co-impacts. Evidence on NCS co-impacts has grown approximately ten-fold
in three decades, although some of the most abundant evidence is associated
with pathways that have less mitigation potential. We find that studies often
examine multiple NCS pathways, indicating natural NCS pathway complements, and
each NCS is often associated with two or more coimpacts. Finally, NCS
co-impacts evidence and priority areas for NCS are often mismatched--some
countries with high mitigation potential from NCS have few published studies on
the broader co-impacts of NCS implementation. Our work advances and makes
available novel methods and systematic and representative data of NCS
co-impacts studies, thus providing timely insights to inform NCS research and
action globally.
