Determinants of bird community structure
Structure,
topography, and precipitation were consistently important covariates for
species richness, functional richness, and redundancy models and
outperformed climate only models (Table S5). The average selection
frequencies were higher with structural variables for all three of our
diversity measures (Figure 5).
The strongest selection
frequencies varied for each functional diversity and species richness
model. However, the selection of maximum canopy height (9.1%, 8.1%,
and 5.9% for species richness, functional richness, and functional
redundancy respectively) and Shannon diversity of LAD (4.5%, 11.5%,
and 12.7% for species richness, functional richness, and functional
redundancy respectively) were consistently selected among the strongest
structure metrics in these models. In the case of functional richness,
the strongest single metric was elevation (18.2%) followed by the
coefficient of variation in LAD (13.5%). The strongest metrics for
species richness were elevation (14.8 %) as well as precipitation
(14.8%) followed by mean LAD (11.1%). The strongest metric for
functional redundancy was mean LAD (18.1%) followed by precipitation
(16.0%) and Shannon diversity of LAD (12.7%). On the other hand, the
least selected metrics included mean aspect and slope. In the case of
functional richness and species richness, temperature was much weaker
(3.4% and 4.5% respectively).
Smoothed surface models of forest structure metrics across temperature
and precipitation gradients revealed that maximum canopy height was
projected to be the shortest in areas with relatively low precipitation
and mean temperatures (Figure 6:A).
The tallest canopies were
projected across two major areas, one with a mean annual temperature of
about 10ºC and approximately 80 cm of precipitation per year and the
other with mean temperature of roughly 0ºC and annual precipitation
amounts greater than 125cm per year. Using the surface models to predict
species richness, functional richness, and redundancy across forest
ecosystems resulted in different patterns for each diversity metric.
Diversity metrics showed clear
maxima and minima that were not constrained by biomes but instead were
on a continuum or gradient across different forest biomes. Since each
diversity metric responded differently to temperature, precipitation,
and maximum canopy height, each resulting pattern was unique (Figure 6:
B-D).