The most robust attribution studies use data from many species, individual locations with minimal confounding factors, particularly observed recent LULCC, and scale up by analysing multiple locations across a large zone between biomes, providing multiple lines of evidence . Multivariate statistical analyses aid attribution studies by allowing the assessment of relative weights among multiple factors, including variables related to climate change . However, drivers often have strong, significant interactions with one another, complicating quantitative assessment of the strength of individual drivers . In these cases, manipulative experiments are critical in assessing attribution to the drivers of climate change.
IPCC
Climate Change 2022: Impacts, Adaptation and Vulnerability
IPCC Report