Tree growth as affected by stem and crown structure

Abstract

Key message Prediction of tree growth based on size or mass as proposed by the Metabolic Scaling Theory is an over-simplification and can be significantly improved by consideration of stem and crown morphology. Tree growth and metabolic scaling theory, as well as corresponding growth equations, use tree volume or mass as predictors for growth. However, this may be an over-simplification, as the future growth of a tree may, in addition to volume or mass, also depend on its past development and aspects of the current inner structure and outer morphology. The objective of this evaluation was to analyse the effect of selected structural and morphological tree characteristics on the growth of common tree species in Europe. Here, we used eight long-term experiments with a total of 24 plots and extensive individual measurements of 1596 trees in monospecific stands of European beech (Fagus sylvatica L.), Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.) and sessile oak (Quercus petraea (Matt.) Liebl.). Some of the experiments have been systematically surveyed since 1870. The selected plots represent a broad range of stand density, from fully to thinly stocked stands. We applied linear mixed models with random effects for analysing and modelling how tree growth and productivity are affected by stem and crown structure. We used the species-overarching relationship $$\mathrm{iv}={{a}_{0}\times v}$$ iv = a 0 × v between stem volume growth, $$\mathrm{iv}$$ iv and stem volume, $$v,$$ v , as the baseline model. In this model $${a}_{0}$$ a 0 represents the allometric factor and α the allometric exponent. Then we included tree age, mean stem volume of the stand and structural and morphological tree variables in the model. This significantly reduced the AIC; RMSE was reduced by up to 43%. Interestingly, the full model estimating $$\mathrm{iv}$$ iv as a function of $$v$$ v and mean tree volume, crown projection area, crown ratio and mean tree ring width, revealed a $$\alpha \cong 3/4$$ α ≅ 3 / 4 scaling for the relationship between $$\mathrm{iv}\propto {v}^{\alpha }$$ iv ∝ v α . This scaling corresponded with Kleiber’s rule and the West-Brown-Enquist model of the metabolic scaling theory. Simplified approaches based on stem diameter or tree mass as predictors may be useful for a rough estimation of stem growth in uniform stands and in cases where more detailed predictors are not available. However, they neglect other stem and crown characteristics that can have a strong additional effect on the growth behaviour. This becomes of considerable importance in the heterogeneous mixed-species stands that in many countries of the world are designed for forest restoration. Heterogeneous stand structures increase the structural variability of the individual trees and thereby cause a stronger variation of growth compared with monocultures. Stem and crown characteristics, which may improve the analysis and projection of tree and stand dynamics in the future forest, are becoming more easily accessible by Terrestrial laser scanning.

Problems with models assessing influences of tree size and inter-tree competitive processes on individual tree growth: a cautionary tale

“…One approach that may have promise would initially involve derivation of a model that would describe size effects on individual tree growth rates for a species when trees were open-grown and not subject to competitive interactions with neighbors. A number of model systems have been based on that approach (e.g., Pommerening and Maleki 2014;Lamonica et al 2020;Bhandari et al 2021;Pretzsch 2021). Once that was determined, competition indices that describe above-and below-ground competitive processes separately might then be added to the system to attempt to quantify symmetric and asymmetric processes.…”

“…Many studies of the effects of competitive process on forest growth behavior have been based on this type of testing (Nystrom and Kexi 1997;Gourlet-Fleury and Houllier 2000;Lessard et al 2001;Mabvurira and Miina 2002;Mailly et al 2003;Monty et al 2008;Pérot et al 2010;Pedersen et al 2012;Carr et al 2020;Barros de Oliveira et al 2021). However, of recent times it has become common to use 'Akaike's Information Criterion' (AIC) (and allied criteria) to suggest which of a number of possible models is the most appropriate when fitted to a particular data set; a number of studies of competitive processes have used this method (Miina and Pukkala 2002;Papaik and Canham 2006;Yang et al 2009;Pretzsch 2021). Some studies have used both methods (Pommerening and Maleki 2014;Cordonnier and Kunstler 2015;Kahriman et al 2018;Acquah and Marshall 2020;Bhandari et al 2021) or, indeed, have used other methods altogether (Verzelen et al 2006;Kuehne et al 2019).…”

“…Given a forest growing on a particular site, with particular climatic characteristics and soil fertility, the growth rate at any time of a tree will depend, firstly, on its size (Pretzsch et al 2012;Cordonnier et al 2019;Ogawa 2019;Pretzsch 2021) and, in particular, the amount of living tissues that it has accumulated to undertake metabolic processes. This growth rate will decline as the tree grows larger, possibly as a result of greater respiratory demands to maintain and renew its live tissues (West 2020).…”

The Past Matters: Previous Management Strategies Modulate Current Growth and Drought Responses of Norway Spruce (Picea abies H. Karst.)

“…In our study, we modeled tree growth and drought responses in dependence on the basal area of each tree. However, it has recently been shown that the crown structure is also an important growth determinant [143]. Thus, if crown morphology had been surveyed more than once, it also could have been included in our modeling approach.…”

Quantifying effects on tree growth rates of symmetric and asymmetric inter-tree competition in even-aged, monoculture Eucalyptus pilularis forests

“…These, together with the physiological capabilities of the species concerned, will determine the size the tree might reach by any particular age. That size is then the second factor that determines how fast it may grow subsequently (Pretzsch 2021a); this reflects the amount of living tissue it contains to undertake growth processes (Weiskittel et al 2011, Chap 12). The third factor is the availability to the tree of the resources it requires for growth, light, carbon dioxide, water and nutrients.…”