Species Diversity of Canopy Versus Understory Trees in a Neotropical Forest: Implications for Forest Structure, Function and Monitoring

Abstract

Species composition and diversity of the canopy layer of tropical forests have rarely been described, yet they are important to many aspects of ecosystem structure and function. Species composition was compared among canopy trees (defined as sun-exposed crowns), understory trees, trees ‡10-cm diameter at breast height (DBH), and the tree community as a whole in a Neotropical moist forest. High-resolution stereophotographs were used to map all individual canopy tree crowns in 8.6 ha of a 50-ha forest dynamics plot on Barro Colorado Island (BCI), Panama. The canopy was found to have high species diversity in relation to the understory and the whole forest. Only 5% of the stems were found in the canopy, but it contained 70% of the species. Diversity, standardized by stem count, for the canopy (%135 species per 1000 trees) was higher than that of the forest as a whole (%108 species per 1000 trees), and species composition was different between the two communities. Although only 50% of trees ‡10-cm DBH, the typical size range used in many forest inventories, were in the canopy, the species diversity and composition of the canopy and trees ‡10-cm DBH were nearly identical. The percentage of gap species in the canopy increased with tree size, providing evidence of the dynamic nature of the BCI forest. To the degree that tree function, such as carbon uptake and transpiration, vary among species, the rarified species richness of the canopy will generate high functional diversity at local-to-landscape scales.

Interspecific variation in tropical tree height and crown allometries in relation to life history traits

“…On the other hand are shade-tolerant species whose saplings persist in the shaded understory, until they eventually reach taller heights in the canopy where they overgrow and suppress other trees (Bohlman and O'Brien, 2006;Bohlman and Pacala, 2012;Farrior et al, 2016). In old growth forests like BCI, shade-tolerant species dominate in numbers overall, whereas opportunistic light-demanding species thrive when tree-fall events open gaps in the canopy and constitute approximately half of canopy basal area (Bohlman, 2015;Farrior et al, 2016).…”

Integrating high resolution drone imagery and forest inventory to distinguish canopy and understory trees and quantify their contributions to forest structure and dynamics

“…Defining canopy status. For the purposes of this study, canopy trees were defined as those directly exposed to overhead light; other trees were classified as understory trees (as in Bohlman [27]). Specifically, trees were classified as being in the canopy if their crowns were totally or partially visible in the orthomosaic, and had a visible crown diameter greater than1 .5 m. We note that some trees classified as canopy trees under this definition may have most of their crowns shaded and only a small part of the crown in direct light, and that small trees can be classed as canopy trees if they do not have larger trees above them.…”

“…in the canopy and decreased with tree size [27]. Future studies should evaluate if the PPA can explain differences in the numbers and sizes of canopy trees among forests such as those between our site and BCI and explore differences in species and functional group compositions between canopy and understory.…”

“…But few studies have quantified how canopy position varies with tree size and growth rates or how canopy trees contribute to growth rates and carbon stocks and fluxes. A rare exception is work combining airborne imagery and ground-based data for the old-growth moist tropical forest of Barro Colorado Island, Panama, to evaluate the canopy status of individual trees, quantify the proportion of trees in the canopy, and compare diameter growth of canopy and understory trees [ 26 , 27 ].…”

NEON Crowns: a remote sensing derived dataset of 100 million individual tree crowns

“…Similarly, habitat classification and species abundance curves can depend on the dominant forest structure that can be inferred from coarse resolution airborne data (Shirley et al, 2013) and could be improved using this dataset. It may be possible to establish relationships between understory and canopy measures using field data that could allow this dataset to be used as part of a broader analysis (Bohlman, 2015). However, this would require significant additional research to validate the potential for this type of approach.…”