Major axes of variation in tree demography across global forests

Aim Global forests and their structural and functional features are shaped by many mechanisms that impact tree vital rates. Although many studies have tried to quantify how specific mechanisms influence vital rates, their relative importance among forests remains unclear. We aimed to assess the patterns of variation in vital rates among species and in space and time across forests to understand and provide a baseline for expectations of the relative importance of the different mechanisms in different contexts. Location 21 forest plots worldwide. Time period 1981-2021 Major taxa studied Woody plants Methods We developed a conceptual and statistical framework (variance partitioning of multilevel models) that attributes the variability in growth, mortality, and recruitment to variation in species, space, and time, and their interactions, which we refer to as organising principles (OPs). We applied it to data from 21 forest plots covering more than 2.9 million trees of approximately 6,500 species. Results Differences among species, the species OP, were a major source of variability in tree vital rates, explaining 28-33% of demographic variance alone, and in interaction with space 14-17%, totalling 40-43%. Models with small spatial grain sizes (quadrats at 5 × 5 m) retained most of the spatial OP, but a large proportion of variance remained unexplained (31-55%). The average variability among species declined with species richness across forests, indicating that diverse forests featured smaller interspecific differences in vital rates. Main conclusions Decomposing variance in vital rates into the proposed OPs showed that taxonomy is crucial to predictions and understanding of tree demography. Our framework has a high potential for identifying the structuring mechanisms of global forest dynamics as it highlights the most promising avenues for future research both in terms of understanding the relative contributions of mechanisms to forest demography and diversity and for improving projections of forest ecosystems.

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