Williams, L.J.Gallagher, R.V.Rifai, S.W.Adeleye, M.A.Baker, P.J.Bowman, D.M.J.S.Eckersley, J.England, J.R.Fletcher, M.Grierson, P.F.Inbar, A.Knauer, J.Stephens, C.M.Trouvé, R.Medlyn, B.E.2025-10-302025-10-302025Plants, People, Planet, 2025; 1-252572-26112572-2611https://hdl.handle.net/2440/148061OnlinePubl. Available online 28 August 2025Climate change is expected to affect vegetation: associated rising atmospheric CO₂, higher temperatures and more variable and extreme rainfall regimes can all cause major shifts in vegetation composition, structure and function. Such effects need to be detected to confirm understanding and to inform models that can predict future vegetation change and guide management efforts. However, many change drivers— some related to, and others distinct from, climate change—simultaneously affect vegetation. These drivers include altered land management practices and shifts in fire and grazing regimes. Untangling the signals of climate-change-induced vegetation change from these other drivers of variation poses significant challenges. These challenges are amplified in regions with high interdecadal climate variability and enduring legacies of shifting human activities. Here, we assess attempts to detect and attribute vegetation change across Australia, a continent that exemplifies such complexities. We develop a scheme to classify attribution efforts according to whether they consider (1) qualitative or quantitative evidence, (2) mechanistic explanations and (3) alternative plausible change drivers. While a significant body of evidence demonstrates vegetation change in Australia, we find that it is difficult to confidently attribute changes to recent climate shifts—noting that few studies have attempted to do so. Several recommendations emerge that may improve attribution worldwide, including explicitly considering attribution strength, committing to long-term monitoring of vegetation and change drivers and recognising multiple drivers of change, especially past and present human influences. Finally, achieving the strongest level of attribution requires linking observations and mechanistic modelsen© 2025 The Author(s). Plants, People, Planet published by John Wiley & Sons Ltd on behalf of New Phytologist Foundation. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.anthropogenic climate change; attribution; change detection; disturbance regimes; historical legacies; land use change; process-based models; vegetation monitoringJournal article10.1002/ppp3.70090858908Rifai, S.W. [0000-0003-3400-8601]