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).