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).