Allometric relationships, functional differentiations, and scaling of growth rates across 151 tree species in China

Abstract

Chinese trees adapted to wet, warm, highly heterogeneous, and dynamic light environments might be expected to systematically differ from other non-Chinese trees based on stem allometry and life em allo. However, our understanding of the extent to which how differentiation in forest architecture and species size influences tree allometry relates to fundamental physiological and ecological trade-offs, climate, forest structure, and function is limited. We quantified height-diameter allometries and growth increments of 13,594 individuals of 151 tree species across China. Although trees grew statistically indistinguishably from the theoretically predicted exponent, the height-diameter allometries for trees in China deviated from tree patterns in other continental forests worldwide. Chinese trees showed substantially lower heights at a given diameter for larger trees and asymptotic heights (33.05 m), with values were 5.5% to 43.3% lower than those estimated for continental rain forest trees in South America, Australia, Southeast Asia, and Africa. In total, 149 of 151 species showed significant nonlinearity of height-diameter allometry with asymptotic heights ranging from 6.33 to 50.54 m; additionally, half (74/149 species) fell in the range of 20-33.5 m, averaging 21.98 AE 8.70 m (SE) for canopy trees. In subsets of canopy trees sampled from larger-statured species and deciduous trees, the approximated maximum heights were 14-42% larger than those of smaller-statured and evergreens and those in other wet and warmer regions found worldwide. These results suggest flexible phenotypic responses of height-diameter allometries to heterogeneous light conditions along understory-canopy gradients. Average growth rates, varying from 0.02 to 0.78 cm/yr (mean of 0.25 cm/yr), were positively related to the asymptotic height, diameter at inflection, and allometric intercept but negatively correlated with the shape of the asymptotic curve and allometric slope. Species with asymptotic heights above 30 m or inflection sizes larger than 20 cm clearly depicted higher growth rates than smaller ones.

On the link between tree size and ecosystem carbon sequestration capacity across continental forests

“…The H – D relationships (obtained using both Equations () and ()) were estimated by NLME models ( nlme package in R software 3; Pinheiro et al, 2013), where the “continent” (referring to China, Asia, Africa, America, or Australia), “family group,” and “ecosystem” were fixed effects and the “site or plot” was specified as a random effect. The general model form is given as follows (Zhao et al, 2021): $$$$ H=f\left(D,{u}_i\right)+{u}_j+\upxi, $$$$ where the height ( H ) is modeled by a nonlinear function f (Equation () or ()) of diameter ( D ), the fixed effect term represents the “continent, family group, ecosystem” ( u i ), and the random effect term “site or plot” ( u j ) and the residual term (ξ) are associated with variability among individuals, functional groups, and measurement errors. Here, parameters H max and β, the measures of the forest canopy height asymptote and stem allometry, respectively, were considered to be regressed for both the entire Chinese tree growth data and the grouped datasets, including regional forest types, ecosystem communities, and species‐specific biogeographic components.…”

“…The chosen plots corresponded to the following criteria (see also Zhao et al, 2021): (1) the plots were located in the monsoon region of eastern China (lat 21 54 0 -42 24 0 N, long 101 12 0 -128 30 0 E), covering the typical climate zones from south to north (tropical, subtropical, warm temperate, and temperate) and humid to subhumid areas from southeast to northwest (Ge et al, 2019); (2) the plots were 40-2450 m above sea level (asl); (3) in each plot, the mean annual temperature (MAT) was approximately 4.8-21.7 C and the mean annual precipitation (MAP) was approximately 650-1931 mm; (4) the middle-aged forests (30-to 60-yearold stands) in which the plots were located spanned warm temperate and subtropical climate zones and hosted frequent but not massive disturbances (e.g., logging for forest management or extreme climate events, such as ice storms) (Tong et al, 2020;Zhao et al, 2020), whereas the old-growth forest stands (≥200 years in age) spanned all temperate, subtropical, and tropical climate zones and were free from anthropogenic disturbances (e.g., industrial logging) or large-scale natural disturbances (e.g., major cyclone disturbances, wind or fire).…”

“…The H-D relationships (obtained using both Equations ( 1) and ( 2)) were estimated by NLME models (nlme package in R software 3; Pinheiro et al, 2013), where the "continent" (referring to China, Asia, Africa, America, or Australia), "family group," and "ecosystem" were fixed effects and the "site or plot" was specified as a random effect. The general model form is given as follows (Zhao et al, 2021):…”

“…From each plot and/or species, we included freestanding trees ≥1 cm diameter but excluded the following (see also Zhao et al, 2021): (1) trees for which their heights were estimated by eye or from their diameters;…”

Functional evaluation of height–diameter relationships and tree development in an Australian subtropical rainforest

“…The parameters of the NRH provide easily comprehended linear descriptions of three elements of tree growth in a specific environment, namely a, H a and b. Application of the NRH across different environments would require modifications, as have been made to power (Lines et al 2012;Zhao et al 2021), logarithmic (Feldpausch et al 2012;Chave et al 2014;Cysneiros et al 2021), Weibull and exponential (Banin et al 2012;Mensah et al 2018) models. An advantage of the NRH is that variations in environmental resource availability as reflected in forest type (Cysneiros et al 2020), site quality (Vanclay 2009) and tree density (Vanclay 1992;Deng et al 2019) may be identified and described quantitatively as factors independently altering a, b and H a , and other dependent parameters, including crown dimensions and biomass.…”