Question 1: How are precipitation, temperature and three-dimensional forest structure related?
Neither precipitation nor temperature are correlated with forest structure as strongly as expected, and many structure metrics are largely independent of these variables. The correlation between lidar derived structure covariates and climate variables is consistent with other studies (Carrasco et al., 2019; LaRue at al., 2020); however, Ehbrecht et al. (2021) used different methods to measure structural complexity and found higher correlations between structure and mean annual precipitation but no significant correlation with mean annual temperature. For our study, precipitation and temperature were both weakly to moderately correlated with structure metrics. For example, precipitation had a larger influence on vegetation density, measured by mean LAD, than temperature in most forest ecosystems. In forests with more annual precipitation, forests tend to have denser canopies, while the forest canopy appears to be patchier in more arid regions. However, temperature is more correlated with metrics describing the spatial organization of LAD. The heterogeneity in LAD, measured as Shannon’s Diversity of LAD, tends to increase with temperature. All of which suggests that warmer forests tend to be more heterogeneous and colder forests more homogeneous and denser. However, structural complexity and vegetation density were not always opposed to each other in extreme temperatures. For example, forest structure and density increase together at sites with lower mean temperatures and high precipitation, such as boreal forests, where our models predict taller, yet denser forests. Denser closed canopy forests can have a buffering effect in extreme cold, creating warmer microclimates underneath the canopy (Li et al., 2015; De Frenne et al., 2019), which can affect niche space by increasing the amount of suitable habitat in response to temperature regimes (Frey et al., 2016). This would help explain the increase in richness and functional diversity within boreal forests that our models predict, supporting the strength of forests serving as microrefugia for biodiversity under future climate change (De Lombaerde et al., 2022).