Julen Astigarraga

Global change is altering forests worldwide, with multiple consequences for ecosystem functioning. Temporal changes in climate, and extreme, compounded weather events like hotter droughts are affecting the demography, composition and function of forests, leading to a highly uncertain future. To accurately predict future forest responses to hotter droughts, we highlight the need for considering a broad temporal perspective. So far, most ecological studies do not integrate different timespans and temporal resolutions, making it difficult to assess two critical time-related aspects of forest responses to hotter droughts: the legacies of past disturbances (i.e. the effect of past events on current responses) and their role in non-stationary responses (i.e. changing effects over time). To incorporate the effect of past hotter droughts on today's forest distribution, structure, composition and function, we identify and define key forcings and forest responses operating across three key timescales, ranging from hours to millennia. First, the shortest timescale considered (i.e. from hours to a decade) usually addresses physiological processes as well as individual tree and population performance. Second, the intermediate timescale (i.e. from decades to centuries) encompasses changes in community composition, stand structure and forest dynamics. Last, the longest timescale (i.e. from centuries to millennia) is crucial for understanding biogeographical processes that shape current species and trait pools. Then, we assess how the contrasting timespans and temporal resolutions used by different ecological subfields and approaches provide critical insights into characterising and understanding the influence of past events on ongoing responses to hotter droughts. We conclude that the holistic view gained from integrating disciplines with complementary temporal perspectives will result in a more comprehensive understanding of forest functioning and we provide a roadmap for achieving this, thereby improving our ability to predict forest responses to climate change.