As the Earth's climate continues to change with anthropogenic forcing, rising temperatures and extreme hydrological events are impacting vegetation and soil, directly altering wildfire dynamics. Recent decades have witnessed large-scale human modifications of natural land cover, amplified rates of ecosystem changes, and an increase in the intensity, extent, and frequency of wildfires. Our understanding of the dynamics of vegetation and fire and their links with atmospheric and surface conditions is mainly derived from in-situ observations and remote sensing products which are limited to the past few decades. While historical records extend our knowledge, these only add a few centuries at most. Paleo-environmental proxy records provide insights into a wide range of interactions between land cover, wildfire and climate predating human land management and anthropogenic climate change. Documenting these interactions and inferring their drivers is of utmost importance for understanding ongoing and future changes in climate and continental ecosystems. Recent years have seen an increasing number of high-resolution and multi-proxy reconstructions of vegetation dynamics, land cover, and wildfire regimes as well as novel paleo-environmental proxies and improved analysis methods. Coupled with significant improvements in simulating ecosystem dynamics and land-atmosphere interactions, these advances allow fresh insights into spatio-temporal dynamics of ecosystems in response to climatic perturbations.
We invite contributions aimed at understanding land cover, vegetation, soil, sub-surface, and wildfire dynamics from present-day, through the Quaternary into deep time, and their interactions with climate on seasonal to orbital timescales. These include: (a) regional and global-scale reconstructions of vegetation cover and composition from paleo-environmental data, (b) the development and application of innovative proxies and archives, (c) Earth system model simulations, (d) studies combining data and models, and (e) proxy system modeling and novel statistical methods to constrain vegetation and wildfire dynamics and their drivers. We also welcome contributions related to technical and analytical advancements in organic and inorganic chemical analyses, and in-situ calibration studies. Special attention is given to studies focusing on understudied regions and time intervals, and research that has the potential to inform future land management policies.