Global evidence of human well-being and biodiversity impacts of natural climate solutions

Natural climate solutions (NCS) play a critical role in climate change mitigation. NCS can generate win–win co-benefits for biodiversity and human well-being, but they can also involve trade-offs (co-impacts). However, the massive evidence base on NCS co-benefits and possible trade-offs is poorly understood. We employ large language models to assess over 2 million published journal articles, primarily written in English, finding 257,266 relevant studies on NCS co-impacts. Using machine learning methods to extract data (for example, study location, species and other key variables), we create a global evidence map on NCS co-impacts. We find that global evidence on NCS co-impacts has grown approximately tenfold in three decades, and some of the most abundant evidence relates to NCS that have lower mitigation potential. Studies often examine multiple NCS, indicating some natural complementarities. Finally, we identify countries with high carbon mitigation potential but a relatively weak body of evidence on NCS co-impacts. Through effective methods and systematic and representative data on NCS co-impacts, we provide timely insights to inform NCS-related research and action globally. Rich evidence of the potential co-benefits and trade-offs of natural climate solutions is available but remains poorly understood. Assessing the literature with machine learning methods, this study maps and analyses the growing evidence of trade-offs in natural climate solutions globally.