A global evidence map of human well-being and biodiversity co-benefits and trade-offs of natural climate solutions
Charlotte H. Chang, James T. Erbaugh, Paola Fajardo, Luci Lu, Istv\'an Moln\'ar, D\'avid Papp, Brian E. Robinson, Kemen Austin, Susan Cook-Patton, Timm Kroeger, Lindsey Smart, Miguel Castro, Samantha H. Cheng, Peter W. Ellis, Rob I. McDonald, Teevrat Garg, Erin E. Poor

TL;DR
This paper creates a comprehensive global evidence map of natural climate solutions' co-benefits and trade-offs for biodiversity and human well-being, using machine learning to analyze over two million articles.
Contribution
It introduces novel machine learning methods to systematically synthesize a vast and dispersed body of literature on NCS co-impacts, providing a global evidence map.
Findings
Evidence on NCS co-impacts has increased tenfold over three decades.
Studies often examine multiple NCS pathways and co-impacts.
There is a mismatch between evidence and NCS priority areas globally.
Abstract
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.,…
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Taxonomy
TopicsSustainable Development and Environmental Policy
