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Effects of local neighbourhood diversity on crown structure and productivity of individual trees in mature mixed-species forests

Effects of local neighbourhood diversity on crown structure and productivity of individual trees... Background: Species-specific genotypic features, local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate. In mixed-species forests, diversity-mediated biomass allocation has been suggested to be a fundamental mechanism underlying the positive biodiversity-productivity relationships. Empirical evidence, however, is rare about the impact of local neighbourhood diversity on tree characteristics analysed at a very high level of detail. To address this issue we analysed these effects on the individual-tree crown architecture and tree productivity in a mature mixed forest in northern Germany. Methods: Our analysis considers multiple target tree species across a local neighbourhood species richness gradient ranging from 1 to 4. We applied terrestrial laser scanning to quantify a large number of individual mature trees (N = 920) at very high accuracy. We evaluated two different neighbour inclusion approaches by analysing both a fixed radius selection procedure and a selection based on overlapping crowns. Results and conclusions: We show that local neighbourhood species diversity significantly increases crown dimension and wood volume of target trees. Moreover, we found a size-dependency of diversity effects on tree productivity (basal area and wood volume increment) with positive effects for large-sized trees (diameter at breast height (DBH) > 40 cm) and negative effects for small-sized (DBH < 40 cm) trees. In our analysis, the neighbour inclusion approach has a significant impact on the outcome. For scientific studies and the validation of growth models we recommend a neighbour selection by overlapping crowns, because this seems to be the relevant scale at which local neighbourhood interactions occur. Because local neighbourhood diversity promotes individual-tree productivity in mature European mixed-species forests, we conclude that a small-scale species mixture should be considered in management plans. Keywords: Biodiversity, Tree growth, Crown architecture, Quantitative structure models, Terrestrial laser scanning, Neighbour classification * Correspondence: louis.georgi@tu-dresden.de Technische Universität Dresden, Institute of General Ecology and Environmental Protection, Pienner Straße 7, 01737 Tharandt, Germany Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Georgi et al. Forest Ecosystems (2021) 8:26 Page 2 of 12 Background crown volumes (CV) for beech and Norway spruce Forest canopies play a decisive role in shaping the local (Picea abies (L.) H. Karst.) when growing in mixture. and global climatic conditions due to evaporation and They also found species specific tree crown adaptions: in carbon fixation (Li et al. 2015; Bastin et al. 2019), and mixtures beech had flatter branch angles, whereas constitute an important habitat for a multitude of spe- spruce showed longer branches. Metz et al. (2013) cies (Ozanne et al. 2003). Canopies are formed by showed that neighbourhood diversity significantly influ- crowns of individual trees, which strive for the optimisa- enced beech growth and that intraspecific competition tion of their own light access in order to maximize the from beech is stronger than interspecific competition photosynthesis potential. The crown architecture is of from other, more translucent species. These patterns particular importance here, because of its direct link to a were more pronounced when crown dimensions and tree’s light absorption (Ishii and Asano 2010; Sapijanskas shapes were derived from TLS data compared to the use et al. 2014; Forrester et al. 2018). While the fundamental of conventional geometric crown shapes. Moreover, architecture of the crown is embedded in the species- Juchheim et al. (2017) detected that beech trees in mix- specific genotype (Costes and Gion 2015), the actual tures were associated with longer branches with flatter stature and allometry is strongly influenced by the local angles, a lower height-to-diameter ratio and a lower tree species composition and resource supply (De Kroon height of the maximal lateral crown extension. Corres- et al. 2005; Bayer et al. 2013; del Río et al. 2019). Besides pondingly, Barbeito et al. (2017) showed that beech trees abiotic factors, e.g. slope inclination (Lang et al. 2010), in mixed stands with Scots pine (Pinus sylvestris L.) had biotic interactions at the local level, e.g. crowding and larger crowns, especially in the lower canopy. However, species composition, are most crucial for the realized the site productivity had a strong impact on this mixing crown shape in closed-canopy stands (Pretzsch and effect. In a biodiversity-ecosystem functioning (BEF) ex- Schütze 2009; Fichtner et al. 2013; Forrester et al. 2017). periment with young subtropical trees in China, Kunz Photomorphogenetic responses of individual trees result et al. (2019) observed significant diversity effects on the in considerable crown plasticity, i.e. the environmentally crown architecture along a broad gradient of local neigh- driven intraspecific variability in crown architecture bourhood species richness. (Schröter et al. 2012; Pretzsch 2014). These light-related To fill the knowledge gap for mature European forests tree interactions for physical niche partitioning in can- we extended previous studies by analysing further decidu- opy space have been found to be severely impacted by ous tree species that might play an important role (besides species mixing and are thought to be an important beech we also included Common oak (Quercus robur L.), process in explaining the positive biodiversity – product- Common hornbeam (Carpinus betulus L.), sycamore ivity relationships (BPRs) in forests (Morin et al. 2011; (Acer pseudoplatanus L.), Common ash (Fraxinus excel- Huang et al. 2018; Kunz et al. 2019). sior L.) and European larch (Larix decidua Mill.) and con- The diversity-driven modifications in the individual- sidered a longer tree species richness gradient of up to tree crowns are based on variations in crown size and four in the local neighbourhood. Furthermore, most of the shape (Pretzsch 2014; Williams et al. 2017; Kunz et al. previous studies incorporated a relatively low number of 2019). The underlying mechanisms operate at multiple target trees (mainly because traditional crown measure- hierarchical levels, ranging from shifts in branch morph- ments in mature forest are highly time-consuming and ology and ramification to modifications in the biomass modern high-resolution inventory tools such as TLS are allocation ratio between trunk and branches (Kunz et al. analytically demanding). In this study we extended sub- 2019; Guillemot et al. 2020). However, empirical evi- stantially the number of trees analysed to obtain more dence is rare about the impact of local neighbourhood valid results. For analysing effects occurring on the local species richness on tree crown architecture analysed at a tree-to-tree scale it is of great advantage when the spatial very high level of detail. resolution of the analysis is very high. Airborne laser scan- Such analyses, with a very high spatial resolution, can ning (ALS) and TLS have been successfully applied to cap- be carried out effectively making use of terrestrial laser ture crown characteristics (for an overview see Vosselman scanning (TLS) (Liang et al. 2016). The few studies cited and Maas 2010). The earlier generations of laser scanners, below which have been conducted with high-resolution however, mostly lack a high-resolution acquisition of the TLS in mature forests of Central Europe mainly com- complex tree crowns in dense mature forests. In this study pared the effects between intra- and interspecific tree in- we make use of state-of-the-art technology of full- teractions in pure and mixed stands and/or focused on waveform TLS with online waveform processing to meas- only one tree species, namely European beech (Fagus ure a large number of individual trees in a highly accurate sylvatica L.). In addition, the gradient in the number of manner (Bienert et al. 2018;Georgiet al. 2018). neighbouring tree species was often short. In compari- Of particular importance in examining a tree’s local son to pure stands, Bayer et al. (2013) observed larger neighbourhood interactions is the identification of Georgi et al. Forest Ecosystems (2021) 8:26 Page 3 of 12 potential competitors and facilitators and hence, the rele- investigated trees growing inside permanent circular in- vant scale the local neighbourhood interactions in situ. Dif- ventory plots, each with a size of 500 m (radius = 12.62 ferent distance-dependent approaches exist for neighbour m). These plots were established in 1992, and inventory inclusion (Biging and Dobbertin 1992; Rivas et al. 2005). In data were recorded in 1992, 2003 and 2013. Based on contrast to tree plantations and experiments, the stem and the inventory data of 2013, 11 plots with two or more size distribution in natural forests is much more heteroge- tree species and a minimum age of 60 years were se- neous, resulting in potentially large differences when using lected. In order to capture all possible neighbouring different neighbour inclusion approaches (Rivas et al. 2005). trees for the analysis, all trees in a circular plot area of Hence, Metz et al. (2013) points out the importance of un- 1600 m (radius = 22.62 m) were sampled. Additionally, standardized approaches to consider the crown size vari- for exceptionally large individuals growing near the plot ation among equally thick and tall trees. boundary, we manually selected also even more remote Given the technical progress of surveying instruments, neighbours in order to meet the requirements of the the options for more precise and accurate neighbour in- neighbour inclusion approach based on realised crown clusion approaches are improving. In the past this pro- overlap (see below). gress led to a selection by overlapping tree crowns with TLS data were recorded in March 2017, using a the help of crown mirrors instead of being confined to RIEGL VZ-400i full-waveform terrestrial laser scanner the use of circular plots with fixed radii around a target (RIEGL Laser Measurement Systems GmbH, Horn, tree. Using this approach, von Oheimb et al. (2011) Austria). Each plot was scanned in a multiple scan found no significant impact of neighbourhood diversity mode from five scanner positions (Liang et al. 2016), on tree growth. However, they only used the average with one scanning position in the centre of the plot crown radius of the horizontal projection of each tree, and the other four distributed in the cardinal direc- disregarding the actual overlap. In this study, we proceed tions at a distance of 23 to 25 m from the centre a step further by using full-waveform TLS to detect (slightly variable distances were used to select posi- every single branch with full extend and with the precise tions that most effectively reduced occlusions). The location in three-dimensional space to identify poten- angular resolution was 0.04 deg (corresponding to a tially interacting neighbours. resolution of 7 mm at 10 m). At the centre positions, The aim of this study is to address two questions: the scanner was also tilted by 90° to overcome the limitation of the panoramic field of view. The instru- (1) How does local neighbourhood tree species ment was mounted on a tripod and operated at a diversity influence the tree morphology in mature height of 1.30 m. All scans were performed under European forests? clear skies and nearly windless conditions. (2) How does local neighbourhood tree species TLS point clouds were co-registered using the registra- diversity impact individual-tree productivity? tion tools “Automatic Registration 2” and “Multi Station Adjustment” of Riegl RiSCAN Pro 2.6.1, resultant in a Methods registration accuracy between 2.2 and 2.7 mm (Fig. 1a). Study area To achieve a higher quality point cloud, stray and noise This study was performed in the Lauerholz Forest, located points with a so-called surface reflectance less than − 25 in south-eastern Schleswig-Holstein, Northern Germany, dB or a pulse shape deviation greater than 15, both at a mean altitude of 20 m above sea level (53°88′ N, terms defined by the scanner manufacturer Riegl, were 10°74′ E). The study area is dominated by mixed-species removed (Pfennigbauer and Ullrich 2010). The reflect- deciduous forest, with a large number of different tree ance value in dB ranges from − 25 up to 5. The project species (in particular F. sylvatica, Q. robur, C. betulus, F. coordinate system was defined by the plot centre point excelsior, A. pseudoplatanus, Acer platanoides L., Prunus cloud and the other scanning positions were registered avium L., Betula pendula Roth, L. decidua). With a mean to this point cloud. annual temperature of 8.3 °C and an annual precipitation of about 800 mm, the study area is characterised by a sub- TLS data post-processing oceanic climate (Deutscher Wetterdienst 2017). The dom- All trees of the 11 plots with a diameter at breast height inant soil texture is till with the associated soil types luvi- (DBH) ≥ 7cm (n = 920) were segmented in a stepwise sols and pseudogleyic luvisols. The geological substrate procedure. First, the TLS point clouds were automatic- originates from the last (Weichselian) glaciation. ally segmented in trees with the SimpleTree (4.33.06) software, a plugin of Computree (5.0.054b) (Hackenberg TLS data acquisition and registration et al. 2015). Second, the automatically extracted trees For some of the analyses the growth data of the last de- were visually checked, and falsely classified tree seg- cades were required (see below). Therefore, we ments were manually corrected using RiSCAN PRO Georgi et al. Forest Ecosystems (2021) 8:26 Page 4 of 12 Fig. 1 a) Registered point cloud with multiple trees and ground; b) single segmented tree in red; c) crown volume in blue and crown projection area in yellow Table 1 Morphologic traits measured for each sample tree Measure Abbreviation Origin Reference/Calculation 2 2 Basal area (cm ) BA Point cloud/Inventory DBH × π/4 Diameter at breast height (cm) DBH QSM Raumonen et al. (2013) Crown volume (m ) CV Point cloud See methods this publication Tree height (m) TH Point cloud Z – Z max min Total wood volume (m ) V QSM Raumonen et al. (2013) tot Merchantable wood volume (m ) V QSM See methods this publication mw Volume of fine woody material (m ) V QSM See methods this publication fwm Crown base height (m) CBH Point cloud See methods this publication Crown projection area (m ) CPA Point cloud See methods this publication Crown surface area (m ) CSA Point cloud See methods this publication 2 −1 Basal area increment (cm ∙year ) BAI Point cloud/Inventory ΔBA/Δyears Branch length sum (m) QSM Raumonen et al. (2013) Mean branch angle 1st order (°) QSM See methods this publication Mean branch angle 2nd order (°) QSM See methods this publication Formula wood volume (m ) V Inventory Bergel (1973, 1974) 3 −1 Formula wood volume increment (m ∙year)V I Inventory ΔV I/Δyears f f Georgi et al. Forest Ecosystems (2021) 8:26 Page 5 of 12 (Fig. 1b). The original point density was not reduced with a concave hull (alpha-shape with α-value = 0.3) during the whole procedure to get the most accurate using the Point Cloud Library (Rusu and Cousins 2011) results. and the Computational Geometry Algorithms Library Several tree characteristics (Table 1) and the above- (Kai et al. 2019) (Fig. 1c). ground wood volumes were derived for each seg- mented tree individual using quantitative structure Target and neighbour tree selection models (QSMs). QSMs are a state-of-the-art approach The primary aim of this study was to analyse the neigh- (Raumonen et al. 2013) to quantify the 3D structure bourhood diversity effect on an individual-tree level. In of atreeand itsbranching topology.QSMsdeliver addition to the selection of the affected trees (in the fol- estimates of the aboveground wood volume with a lowing “target tree”), the determination of influencing high accuracy (Calders et al. 2015; Bienert et al. neighbours is of central importance. 2018). These models are a description of the tree as a To focus on vigorous trees as target trees, we included hierarchical collection of geometric primitives (here: only trees taller than two-thirds of the highest tree grow- cylinders). They are embedded into the point cloud ing in the plot for all analyses. Tree species with rare oc- from which geometric and topological tree character- currence (N ≤ 2) were excluded as target trees and one istics can be derived. To create the QSMs, we applied tree which was the only one having five neighbour tree the TREEQSM (2.30) software developed by Raumo- species. A total of 920 trees was extracted from the TLS nen et al. (2013), which runs within Matlab® (Math- point clouds of which 148 were dedicated as target trees Works, Natick, MA, USA) version R2018b on the (61% F. sylvatica, 20% Q. robur, 12% C. betulus,3% F. Taurus high-performance cluster (HPC) of the TU excelsior,2% A. pseudoplatanus and 2% L. decidua). For Dresden. The method categorizes the point cloud in 47 target trees a full set of DBH measurements from the the stem and single branches and captures the tree’s past three inventories was available. topology. Afterwards a volume model is compiled by Two approaches to identify the local neighbours were fitting cylinders in the point cloud segments (Raumo- used. The first approach was a fixed radial distance of nen et al. 2015;Kunzetal. 2017). Due to the param- 10 m from the target tree. Parameters which have been eter sensitivity of the modelling process, we calculated with these trees are subscripted with “ ”. radius conducted a parameter optimisation test with a subset In the second approach, we used the highly accurate of trees. This led to the following parameter values: point cloud to classify all trees as neighbours which first minimum patch size: 5 cm; second minimum crowns were overlapping with that of the target tree patch size: 1 cm; second maximum patch size: 2 cm; (with alpha-shape; α-value = 1). Examples for the differ- relative cylinder length: 4 cm; relative radius for out- ent outcomes resulting from the two neighbour selection lier removal: 5 cm. approaches are shown in Fig. 2. We extracted the basal area (BA), tree height (TH), A total of 238 trees were determined as neighbour- total wood volume (V ) and branch length of the TREE only trees (63% F. sylvatica, 17% Q. robur, 15% C. betu- tot QSM output. We also computed the merchantable wood lus,3% F. excelsior,1% P. avium and 1% L. decidua). volume (V ), defined as all aboveground woody struc- mw tures with a diameter > 7 cm (i.e. the trunk and the lar- Data analysis ger branches). The volume of fine woody material (V ; We applied two different approaches to quantify tree di- fwm diameter < 7 cm) was calculated as the difference of V versity in the local neighbourhood of a target tree (Table tot and V . 2). The number of tree species (neighbourhood species mw The trees mean branch angle was derived from all richness, NSR) and the exponential Shannon index (eH ) single branches and was calculated with the same based on the abundance of neighbouring trees (Shannon method for the first- and second-order branches, re- 1948; Jost 2006). B is the sum of BA of all neighbouring spectively. To measure the branch’s vertical orienta- trees of a given species i and B is the BA of all neigh- tion in space, we focused on the branch’sexit angle bours. Based on BA, this index has been used in former by considering the first ten cylinders after the branch studies to describe forest diversity (Liang et al. 2007; base, derived from theQSM.Fromthose,the angle Ratcliffe et al. 2015). between the Z-axes of the coordinate system and the B B mean branch axes was computed. i i eH ¼ exp − ln Moreover, we extracted numerous crown morpho- B B i¼1 logical traits. The crown base height (CBH), defined as the height of the lowest living branch, was measured in RiSCAN Pro. The crown projection area (CPA), CV and The partitioning of canopy space was analysed using crown surface area (CSA) for each tree were calculated the crown complementarity index (CCI) according to Georgi et al. Forest Ecosystems (2021) 8:26 Page 6 of 12 Fig. 2 Examples for the variable outcomes resulting from different tree neighbour selection approaches: left: overlapping tree crowns; right: fixed radius of 10 m. A: C. betulus, DBH = 19.4 cm, height = 23.6 m; B: Q. robur, DBH = 81.0 cm, height = 31.0 m. Solid circle radius = 12.62 m; dashed circle radius = 22.62 m. NN = Number of neighbours; NSR = Neighbourhood species richness (Williams et al. 2017). Crown complementarity (CC) was sylvatica, C. betulus, L. decidua) and Bergel (1974; Q. calculated for two trees as the difference in crown vol- robur, F. excelsior, A. platanoides). ume (V) between the two individuals (i and j) in each We applied linear mixed-effects models to assess the ef- stratum (k) summed across all strata. The CCI of a tree fects of tree diversity and space occupation on growth of is the mean of all its neighbour CCs. We calculated the target trees at the local neighbourhood scale. Explanatory CCI with a strata height of 0.5 m. variables were NSR, eH or CCI (either based on the fixed radius or crown overlap neighbour selection approach) and V −V the current BA or, for the increment models, the BA . ik jk init CC ¼ ij Target tree species identity and study plot were used as V −V i j crossed random effects. The following response variables were used: CV, CPA, CSA, branch length sum, mean first CC ij CCI ¼ order branch angel, mean second order branch angel, V , tot V , V ,BAI andV I. To improve the linear model fit mw fwm f 2 − 1 Basal area increment (BAI, cm ∙year ) and the mer- and reduce the residual variance, we log-transformed the chantable formula wood volume increment (V I, response variables and the BA. The model assumptions 3 − 1 m ∙year ) was calculated using DBH (by caliper) and were tested and validated according to Zuur et al. (2009). height measurements (with vertex) from inventories in Due to co-linearity of the competition (according to Hegyi 1992 and 2013. Calculations for merchantable wood vol- 1974;Martinand Ak 1984; Biging and Dobbertin 1992) ume were based on volume functions by Bergel (1973; F. with the BA, we excluded these from the models. Georgi et al. Forest Ecosystems (2021) 8:26 Page 7 of 12 Table 2 Biodiversity and space partitioning indices measured for each target tree Measure Abbreviation Origin Reference/Calculation Neighbour species richness NSR Inventory See methods this publication Exponential Shannon-Index eH Point cloud/Inventory Shannon (1948) Crown complementarity index CCI Point cloud Williams et al. (2017) All statistical data analysis was performed with R was found for the NN of large-crowned trees (see ex- (3.6.1; R Core Team 2019) using the packages nlme (Pin- ample in Fig. 2). heiro et al. 2019), lmerTest (Kuznetsova et al. 2019), MuMIn (Bartoń 2019) and effects (Fox et al. 2019). Neighbourhood diversity effects on crown architecture and wood volume Results Besides the strong positive effect of the BA, NSR and Neighbourhood definition effect eH significantly positively influenced the tree crown di- The two neighbour selection approaches yielded highly mensions (CV, CPA, CSA), branch length sum and the variable results regarding the number of neighbours wood volumes based on the neighbour selection ap- (NN) and NSR: the median ΔNN was 3, spanning a proach “crown overlap” (Table 3 and Fig. 3). In contrast, range from min = 0 to max = 18 and the median ΔNSR no significant influence of NSR and eH on the response was 0, with a range of min = 0 and max = 2. An import- variables was found when using the fixed radius selec- ant factor to explain the differences between the two ap- tion approach (with the only exception of a positive NSR proaches is the tree dimension, especially the CPA. For effect on CV, Table 2). With both selection approaches, trees with relatively small crowns, the NN is consider- no impact of the diversity measures on the mean first or ably higher using the fixed radius compared to the second order branch angel was observed. Moreover, the crown overlap approach. In contrast, an opposite pattern Fig. 3 Neighbourhood species richness (NSR) effect on trees crown architecture and wood volume, based on the neighbour selection approach “crown overlap”, with the shaded area representing the 95% confidence interval of the prediction. NSR levels jittered for better clarity Georgi et al. Forest Ecosystems (2021) 8:26 Page 8 of 12 Table 3 Results of mixed-effects models for the effects of neighbourhood tree species richness (NSR), exponential Shannon index (eH ), crown complementarity index (CCI) and target tree basal area (BA ) on crown dimensions, branch length and wood volume S log based on the two tree neighbour selection approaches fixed radius and “overlapping crowns” (n target trees = 148). In all models BA p =.: p < 0.1; *: p < 0.05; **: p < 0.01; ***: p < 0.001; n.s. = not significant log Response variable Fixed Fixed radius Overlapping crowns effects 2 2 Estimates pR Estimates pR c c Crown volume (log) NSR + BA 0.08 + 0.98 * 0.89 0.09 + 0.95 * 0.89 log eH +BA 0.01 + 0.95 n.s. 0.89 0.08 + 0.96 * 0.89 S log CCI + BA 0.04 + 0.95 n.s. 0.89 −0.10 + 0.93 ** 0.89 log Crown projection area (log) NSR + BA 0.04 + 0.70 n.s. 0.85 0.10 + 0.70 ** 0.86 log eH +BA −0.01 + 0.69 n.s. 0.85 0.08 + 0.71 * 0.86 S log CCI + BA 0.04 + 0.69 n.s. 0.85 −0.02 + 0.69 n.s. 0.84 log Crown surface area (log) NSR + BA 0.06 + 0.93 n.s. 0.89 0.10 + 0.92 ** 0.90 log eH +BA 0.00 + 0.91 n.s. 0.89 0.08 + 0.93 * 0.90 S log CCI + BA 0.01 + 0.91 n.s. 0.89 −0.05 + 0.89 n.s. 0.89 log Branch length sum (log) NSR + BA 0.09 + 0.70 n.s. 0.76 0.17 + 0.68 ** 0.77 log eH +BA 0.00 + 0.68 n.s. 0.75 0.13 + 0.69 * 0.77 S log CCI + BA 0.01 + 0.68 n.s. 0.76 −0.07 + 0.67 n.s. 0.74 log Total wood volume (log) NSR + BA 0.02 + 0.96 n.s. 0.97 0.06 + 0.96 ** 0.97 log eH +BA 0.00 + 0.96 n.s. 0.97 0.05 + 0.96 ** 0.97 S log CCI + BA −0.03 + 0.96 n.s. 0.97 −0.05 + 0.95 *** 0.97 log Fine woody material volume (log) NSR + BA 0.06 + 0.70 n.s. 0.81 0.14 + 0.69 ** 0.82 log eH +BA −0.01 + 0.69 n.s. 0.81 0.12 + 0.70 ** 0.82 S log CCI + BA −0.01 + 0.70 n.s. 0.81 −0.07 + 0.67 ** 0.80 log Merchantable wood volume (log) NSR + BA 0.01 + 1.07 n.s. 0.98 0.03 + 1.06 . 0.98 log eH +BA 0.02 + 1.07 n.s. 0.98 0.03 + 1.06 . 0.98 S log CCI + BA −0.04 + 1.08 ** 0.98 −0.04 + 1.07 ** 0.98 log CV and the wood volumes significantly increased with Discussion lower CCI. In the mature mixed-species forests examined in this study we observed significant impact of the local neighbourhood tree diversity on crown architecture Neighbourhood diversity effects on individual-tree as well as on wood volume and growth. These find- productivity ings were, however, very sensitive to the approach The effects of NSR on tree productivity (BAI and V I) used to select neighbouring trees. Whereas the fixed strongly depended on the initial size (i.e. BA) of a radial distance approach barely yielded significant re- target tree. For small-sized trees, BAI was higher in sults, this was always the case using the neighbour conspecific than in heterospecific neighbourhoods, selection based on overlapping crowns. Mature for- while large-sized trees benefitted from increasing NSR ests composed of late successional tree species dis- (Table 4 and Fig. 4). Interacting with the BA , play a wide range of tree sizes at small spatial scales. init.log NSR and eH had significant positive impacts on The large differences in the performance of the two both, BAI and V I, over the past 21 years. The local approaches points to an important role of above- CCI interacting with the BA also showed a ten- ground interactions, i.e. competition for physical init.log dency towards a positive influence on tree growth. space and light. Previous studies used various differ- Again, there is a high sensitivity of the results to- ent approaches to calculate a tree’s zone of influence wards the neighbour selection approach, because most or its competitors (Bachmann 1998). Earlier methods the investigated effects solely occurred or were stron- to determine the exact crown dimensions and neigh- ger with the neighbour selection approach “crown bours of a tree using a compass, hypsometer and overlap” than with “fixed radius” definition (data not crown mirror are error-prone and time-consuming. shown). Hence, an often-used simple neighbour selection is Georgi et al. Forest Ecosystems (2021) 8:26 Page 9 of 12 Table 4 Results of mixed-effects models for effects of target tree initial basal area (BA ), neighbourhood tree species richness init (NSR), exponential Shannon index (eH ) and crown complementarity index (CCI) on basal area increment and wood volume increment with the neighbour selection approach “crown overlap” (n = 47)..: p < 0.1; *: p < 0.05; **: p < 0.01 Fixed effects Basal area increment (log) Volume formula increment (log) 2 2 Estimate pR Estimate pR C C NSR × BA 0.161 . 0.79 0.186 * 0.82 init.log eH ×BA 0.177 * 0.80 0.205 ** 0.83 S init.log CCI × BA 0.116 . 0.76 0.110 . 0.78 init.log the use of fixed radii, a worldwide uniform approach dimensions (D’Amato and Puettmann 2004). In het- which is also cost effective without the use of TLS. erogeneous forests the choice of one specific radius This method, however, has two disadvantages. First, will always remain a compromise. In our study, the it only considers the fixed stem base location. This minimum and maximum crown diameters were 3.48 is the position where the seed sprouted and the tree and 17.00 m or 4.59 and 23.45 m, derived from the individual has been able to prevail until today. How- CPA and from the maximal chord, respectively. As ever, the competition for light, water and nutrients an alternative to a single fixed radius, several studies at this spot changes in the course of decades. In our used either a variety of radii (Lin and Augspurger study area, water and nutrient supply are generally 2006; Antos et al. 2010; Ratcliffe et al. 2015)ortree not limiting tree growth. Rather, trees compete for size dependent radii (von Oheimb et al. 2011). How- light (Schwinning and Weiner 1998) and competition ever, the strong advantage of the crown overlap ap- effects occur on the crown distribution (Longuetaud proach is to focus on every individual tree and its et al. 2013). Therefore, it is reasonable to select actual surrounding structure in three dimensions neighbours based on the photosynthetically active (Zambrano et al. 2019). At this level of resolution, part of a tree, the crown. The actual shape of a the procedureisonlypossibledue to the application crown represents the accumulated competitive cir- of highly precise TLS for forest science and ecology. cumstances of the past. A second disadvantage of a Deploying this state-of-the-art technology enables fixed-radius approach is the neglection of tree size enhanced insights in the outcome of tree-tree inter- differences by using the same radius for a range of actions at the local scale, even in temperate mature different sizes. It has often been found that the opti- forests with canopy heights of up to 45 m. mal radial distances strongly depended on tree size Fig. 4 Size-dependency of neighbourhood species richness (NSR) effects on the annual basal area increment with the neighbour selection approach “crown overlap”, with the shaded area representing the 95% confidence interval of the prediction Georgi et al. Forest Ecosystems (2021) 8:26 Page 10 of 12 Our results confirm previous findings that an in- opportunity to shift crown growth to a less competing crease in neighbourhood tree species richness allows direction (Ali 2019). trees to enhance their crowns in size and shape Since different structural characteristics induce various (Bayer et al. 2013;Kunzetal. 2019). The diversity- reactions among species with different resource-use driven plasticity is gained by enhanced branch strategies, the mixing effect is species-specific (Fichtner lengths and an increased biomass allocation to fine et al. 2017; Forrester 2019). To analyse the species- woody material (V ), leading to larger CPA and specific neighbour effects in temperate European mixed fwm greater CSA and thus to larger crown volume. forests with precise laser scanning technology might be Pretzsch (2014) stated, the more species, the larger the next step, requiring even more trees to achieve sta- the sum of the crown area. A tree’s individual crown tistically solid results. growth is a modular reaction to micro- environmental light heterogeneity (Kawamura 2010) Conclusions and thus elementary in the compensatory feedback With our study, we provide evidence that neigh- loop between structure, environment and growth bourhood species mixing has a significant influence (Bayer et al. 2013; Pretzsch 2014). Through the com- on individual tree morphology and productivity in bination of species with different light ecology and mature European mixed-species forest. Moreover, crown morphology, the canopy is more diverse and weshowed theimportanceofa preciseneighbour- the individual trees can respond and therefore utilize hood definition and selection procedure to reveal the canopy space in a more complementary way diversity effects in mature natural and near-natural (Pretzsch 2014). Our results support the niche com- stands. plementarity hypothesis, postulating the more effi- For future studies in heterogeneous mixed forests, it cient use of resources, here the physical partitioning would be advantageous to include an even larger num- in canopy space, by coexisting species (Tilman 1999; ber of trees to facilitate analyses across extensive areas. Forrester and Bauhus 2016). Along with higher A possible approach to advance in this direction is the architectural plasticity of individual trees the whole application of mobile laser scanning (Bienert et al. 2018) canopy might be packed denser (Cianciaruso et al. in combination with largely automated individual-tree 2009). segmentation procedures. This can be used to clarify With the enlargement of the crown and an in- two important questions. On the one hand, it enables crease in leaf-bearing branches of higher orders, the mixture effects to be examined for species-specific there is an increase in photosynthetically active area. mixing effects. On the other hand, the diversity effect Under the significant impact of local neighbourhood can be studied on several spatial scales with the help of diversity, the 47 observed trees in this study show a much larger dataset. an ambivalent growth pattern over 21 years. Smaller Abbreviations trees with a DBH smaller than 40 cm are impeded in ALS: Airborne laser scanning; BA: Basal area; BAI: Basal area increment; their radial growth whereas larger trees benefitted BEF: Biodiversity-ecosystem functioning; CBH: Crown base height; CC: Crown complementarity; CCI: Crown complementarity index; CPA: Crown projection from increasing NSR. These results are similar to area; CSA: Crown surface area; CV: Crown volume; DBH: Diameter at breast those of Lasky et al. (2015) and Fichtner et al. height; eH : Exponential Shannon-Index; HPC: High-performance cluster; (2017) who observed that taller tree individuals N: Number; NN: Number of neighbours; NSR: Neighbour species richness; QSM: Quantitative structure model; TH: Tree height; TLS: Terrestrial laser benefiting more from a diverse neighbourhood. This scanning; V : Formula wood volume; V I: Formula wood volume increment; f f might be due to size-asymmetric competition V : Volume of fine woody material; V : Merchantable wood volume; fwm mw (Schwinning and Weiner 1998) of larger trees receiv- V : Total wood volume tot ing disproportionally more light in comparison to Acknowledgments smaller individuals and thus the ability to occupy We thank the Forestry Offices of the City of Lübeck County for permission to free niches earlier. Divers tree species mixtures could conduct this study in their forests. The QSM calculations were made on the Taurus HPC cluster of the ZIH of the TU Dresden. Moreover, we would like to further enhance this effect. thank the anonymous reviewers for their comments and suggestions on the In contrast to Williams et al. (2017) who studied manuscript. young and comparatively small trees, we observed a Authors’ contributions negative effect of the CCI on CV and wood volume. LG and GvO conceptualized the study; KFR and GvO recorded the data; LG, However, a reverse reasoning is also plausible. The big- MK, AF and KFR analysed the data; LG prepared the original draft and all ger the crowns, the more equal they are. Since we have authors reviewed and edited the manuscript. The author(s) read and approved the final manuscript. studied mature trees, close to their maximum height, we suspect an upper growth limit and rather the CBH as a Funding decisive influence on this parameter. Moreover, the aver- LG was funded by the German Research Foundation (DFG 320926971) aging effect of the CCI is notable, neglecting a trees through the project “Analysis of diversity effects on above-ground Georgi et al. Forest Ecosystems (2021) 8:26 Page 11 of 12 productivity in forests: advancing the mechanistic understanding of spatio- Cianciaruso MV, Batalha MA, Gaston KJ, Petchey OL (2009) Including intraspecific temporal dynamics in canopy space filling using mobile laser scanning”. variability in functional diversity. Ecology 90(1):81–89. https://doi.org/10.1890/ 07-1864.1 Costes E, Gion JM (2015) Genetics and genomics of tree architecture. In: Plomion Availability of data and materials C, Adam-Blondon A-F (eds) Advances in botanical research. Land Plants - Data are available from the corresponding author on reasonable request. Trees. 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The funders had no role in the diversity. Ecol Lett 20(7):892–900. https://doi.org/10.1111/ele.12786 design of the study; in the collection, analyses, or interpretation of data; in Fichtner A, Sturm K, Rickert C, von Oheimb G, Härdtle W (2013) Crown size- the writing of the manuscript, or in the decision to publish the results. growth relationships of European beech (Fagus sylvatica L.) are driven by the interplay of disturbance intensity and inter-specific competition. For Ecol Author details Manag 302:178–184. https://doi.org/10.1016/j.foreco.2013.03.027 Technische Universität Dresden, Institute of General Ecology and Forrester DI (2019) Linking forest growth with stand structure: tree size inequality, Environmental Protection, Pienner Straße 7, 01737 Tharandt, Germany. tree growth or resource partitioning and the asymmetry of competition. For Leuphana University of Lüneburg, Institute of Ecology, Universitätsallee 1, Ecol Manag 447:139–157. https://doi.org/10.1016/j.foreco.2019.05.053 21335 Lüneburg, Germany. Technische Universität Dresden, Institute of Forrester DI, Ammer C, Annighöfer PJ, Barbeito I, Bielak K, Bravo-Oviedo A, Coll L, Photogrammetry and Remote Sensing, Helmholtzstraße 10, 01069 Dresden, del Río M, Drössler L, Heym M, Hurt V, Löf M, den Ouden J, Pach M, Pereira Germany. MG, Plaga BNE, Ponette Q, Skrzyszewski J, Sterba H, Svoboda M, Zlatanov TM, Pretzsch H (2018) Effects of crown architecture and stand structure on light Received: 15 May 2020 Accepted: 17 March 2021 absorption in mixed and monospecific Fagus sylvatica and Pinus sylvestris forests along a productivity and climate gradient through Europe. 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Effects of local neighbourhood diversity on crown structure and productivity of individual trees in mature mixed-species forests

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Abstract

Background: Species-specific genotypic features, local neighbourhood interactions and resource supply strongly influence the tree stature and growth rate. In mixed-species forests, diversity-mediated biomass allocation has been suggested to be a fundamental mechanism underlying the positive biodiversity-productivity relationships. Empirical evidence, however, is rare about the impact of local neighbourhood diversity on tree characteristics analysed at a very high level of detail. To address this issue we analysed these effects on the individual-tree crown architecture and tree productivity in a mature mixed forest in northern Germany. Methods: Our analysis considers multiple target tree species across a local neighbourhood species richness gradient ranging from 1 to 4. We applied terrestrial laser scanning to quantify a large number of individual mature trees (N = 920) at very high accuracy. We evaluated two different neighbour inclusion approaches by analysing both a fixed radius selection procedure and a selection based on overlapping crowns. Results and conclusions: We show that local neighbourhood species diversity significantly increases crown dimension and wood volume of target trees. Moreover, we found a size-dependency of diversity effects on tree productivity (basal area and wood volume increment) with positive effects for large-sized trees (diameter at breast height (DBH) > 40 cm) and negative effects for small-sized (DBH < 40 cm) trees. In our analysis, the neighbour inclusion approach has a significant impact on the outcome. For scientific studies and the validation of growth models we recommend a neighbour selection by overlapping crowns, because this seems to be the relevant scale at which local neighbourhood interactions occur. Because local neighbourhood diversity promotes individual-tree productivity in mature European mixed-species forests, we conclude that a small-scale species mixture should be considered in management plans. Keywords: Biodiversity, Tree growth, Crown architecture, Quantitative structure models, Terrestrial laser scanning, Neighbour classification * Correspondence: louis.georgi@tu-dresden.de Technische Universität Dresden, Institute of General Ecology and Environmental Protection, Pienner Straße 7, 01737 Tharandt, Germany Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Georgi et al. Forest Ecosystems (2021) 8:26 Page 2 of 12 Background crown volumes (CV) for beech and Norway spruce Forest canopies play a decisive role in shaping the local (Picea abies (L.) H. Karst.) when growing in mixture. and global climatic conditions due to evaporation and They also found species specific tree crown adaptions: in carbon fixation (Li et al. 2015; Bastin et al. 2019), and mixtures beech had flatter branch angles, whereas constitute an important habitat for a multitude of spe- spruce showed longer branches. Metz et al. (2013) cies (Ozanne et al. 2003). Canopies are formed by showed that neighbourhood diversity significantly influ- crowns of individual trees, which strive for the optimisa- enced beech growth and that intraspecific competition tion of their own light access in order to maximize the from beech is stronger than interspecific competition photosynthesis potential. The crown architecture is of from other, more translucent species. These patterns particular importance here, because of its direct link to a were more pronounced when crown dimensions and tree’s light absorption (Ishii and Asano 2010; Sapijanskas shapes were derived from TLS data compared to the use et al. 2014; Forrester et al. 2018). While the fundamental of conventional geometric crown shapes. Moreover, architecture of the crown is embedded in the species- Juchheim et al. (2017) detected that beech trees in mix- specific genotype (Costes and Gion 2015), the actual tures were associated with longer branches with flatter stature and allometry is strongly influenced by the local angles, a lower height-to-diameter ratio and a lower tree species composition and resource supply (De Kroon height of the maximal lateral crown extension. Corres- et al. 2005; Bayer et al. 2013; del Río et al. 2019). Besides pondingly, Barbeito et al. (2017) showed that beech trees abiotic factors, e.g. slope inclination (Lang et al. 2010), in mixed stands with Scots pine (Pinus sylvestris L.) had biotic interactions at the local level, e.g. crowding and larger crowns, especially in the lower canopy. However, species composition, are most crucial for the realized the site productivity had a strong impact on this mixing crown shape in closed-canopy stands (Pretzsch and effect. In a biodiversity-ecosystem functioning (BEF) ex- Schütze 2009; Fichtner et al. 2013; Forrester et al. 2017). periment with young subtropical trees in China, Kunz Photomorphogenetic responses of individual trees result et al. (2019) observed significant diversity effects on the in considerable crown plasticity, i.e. the environmentally crown architecture along a broad gradient of local neigh- driven intraspecific variability in crown architecture bourhood species richness. (Schröter et al. 2012; Pretzsch 2014). These light-related To fill the knowledge gap for mature European forests tree interactions for physical niche partitioning in can- we extended previous studies by analysing further decidu- opy space have been found to be severely impacted by ous tree species that might play an important role (besides species mixing and are thought to be an important beech we also included Common oak (Quercus robur L.), process in explaining the positive biodiversity – product- Common hornbeam (Carpinus betulus L.), sycamore ivity relationships (BPRs) in forests (Morin et al. 2011; (Acer pseudoplatanus L.), Common ash (Fraxinus excel- Huang et al. 2018; Kunz et al. 2019). sior L.) and European larch (Larix decidua Mill.) and con- The diversity-driven modifications in the individual- sidered a longer tree species richness gradient of up to tree crowns are based on variations in crown size and four in the local neighbourhood. Furthermore, most of the shape (Pretzsch 2014; Williams et al. 2017; Kunz et al. previous studies incorporated a relatively low number of 2019). The underlying mechanisms operate at multiple target trees (mainly because traditional crown measure- hierarchical levels, ranging from shifts in branch morph- ments in mature forest are highly time-consuming and ology and ramification to modifications in the biomass modern high-resolution inventory tools such as TLS are allocation ratio between trunk and branches (Kunz et al. analytically demanding). In this study we extended sub- 2019; Guillemot et al. 2020). However, empirical evi- stantially the number of trees analysed to obtain more dence is rare about the impact of local neighbourhood valid results. For analysing effects occurring on the local species richness on tree crown architecture analysed at a tree-to-tree scale it is of great advantage when the spatial very high level of detail. resolution of the analysis is very high. Airborne laser scan- Such analyses, with a very high spatial resolution, can ning (ALS) and TLS have been successfully applied to cap- be carried out effectively making use of terrestrial laser ture crown characteristics (for an overview see Vosselman scanning (TLS) (Liang et al. 2016). The few studies cited and Maas 2010). The earlier generations of laser scanners, below which have been conducted with high-resolution however, mostly lack a high-resolution acquisition of the TLS in mature forests of Central Europe mainly com- complex tree crowns in dense mature forests. In this study pared the effects between intra- and interspecific tree in- we make use of state-of-the-art technology of full- teractions in pure and mixed stands and/or focused on waveform TLS with online waveform processing to meas- only one tree species, namely European beech (Fagus ure a large number of individual trees in a highly accurate sylvatica L.). In addition, the gradient in the number of manner (Bienert et al. 2018;Georgiet al. 2018). neighbouring tree species was often short. In compari- Of particular importance in examining a tree’s local son to pure stands, Bayer et al. (2013) observed larger neighbourhood interactions is the identification of Georgi et al. Forest Ecosystems (2021) 8:26 Page 3 of 12 potential competitors and facilitators and hence, the rele- investigated trees growing inside permanent circular in- vant scale the local neighbourhood interactions in situ. Dif- ventory plots, each with a size of 500 m (radius = 12.62 ferent distance-dependent approaches exist for neighbour m). These plots were established in 1992, and inventory inclusion (Biging and Dobbertin 1992; Rivas et al. 2005). In data were recorded in 1992, 2003 and 2013. Based on contrast to tree plantations and experiments, the stem and the inventory data of 2013, 11 plots with two or more size distribution in natural forests is much more heteroge- tree species and a minimum age of 60 years were se- neous, resulting in potentially large differences when using lected. In order to capture all possible neighbouring different neighbour inclusion approaches (Rivas et al. 2005). trees for the analysis, all trees in a circular plot area of Hence, Metz et al. (2013) points out the importance of un- 1600 m (radius = 22.62 m) were sampled. Additionally, standardized approaches to consider the crown size vari- for exceptionally large individuals growing near the plot ation among equally thick and tall trees. boundary, we manually selected also even more remote Given the technical progress of surveying instruments, neighbours in order to meet the requirements of the the options for more precise and accurate neighbour in- neighbour inclusion approach based on realised crown clusion approaches are improving. In the past this pro- overlap (see below). gress led to a selection by overlapping tree crowns with TLS data were recorded in March 2017, using a the help of crown mirrors instead of being confined to RIEGL VZ-400i full-waveform terrestrial laser scanner the use of circular plots with fixed radii around a target (RIEGL Laser Measurement Systems GmbH, Horn, tree. Using this approach, von Oheimb et al. (2011) Austria). Each plot was scanned in a multiple scan found no significant impact of neighbourhood diversity mode from five scanner positions (Liang et al. 2016), on tree growth. However, they only used the average with one scanning position in the centre of the plot crown radius of the horizontal projection of each tree, and the other four distributed in the cardinal direc- disregarding the actual overlap. In this study, we proceed tions at a distance of 23 to 25 m from the centre a step further by using full-waveform TLS to detect (slightly variable distances were used to select posi- every single branch with full extend and with the precise tions that most effectively reduced occlusions). The location in three-dimensional space to identify poten- angular resolution was 0.04 deg (corresponding to a tially interacting neighbours. resolution of 7 mm at 10 m). At the centre positions, The aim of this study is to address two questions: the scanner was also tilted by 90° to overcome the limitation of the panoramic field of view. The instru- (1) How does local neighbourhood tree species ment was mounted on a tripod and operated at a diversity influence the tree morphology in mature height of 1.30 m. All scans were performed under European forests? clear skies and nearly windless conditions. (2) How does local neighbourhood tree species TLS point clouds were co-registered using the registra- diversity impact individual-tree productivity? tion tools “Automatic Registration 2” and “Multi Station Adjustment” of Riegl RiSCAN Pro 2.6.1, resultant in a Methods registration accuracy between 2.2 and 2.7 mm (Fig. 1a). Study area To achieve a higher quality point cloud, stray and noise This study was performed in the Lauerholz Forest, located points with a so-called surface reflectance less than − 25 in south-eastern Schleswig-Holstein, Northern Germany, dB or a pulse shape deviation greater than 15, both at a mean altitude of 20 m above sea level (53°88′ N, terms defined by the scanner manufacturer Riegl, were 10°74′ E). The study area is dominated by mixed-species removed (Pfennigbauer and Ullrich 2010). The reflect- deciduous forest, with a large number of different tree ance value in dB ranges from − 25 up to 5. The project species (in particular F. sylvatica, Q. robur, C. betulus, F. coordinate system was defined by the plot centre point excelsior, A. pseudoplatanus, Acer platanoides L., Prunus cloud and the other scanning positions were registered avium L., Betula pendula Roth, L. decidua). With a mean to this point cloud. annual temperature of 8.3 °C and an annual precipitation of about 800 mm, the study area is characterised by a sub- TLS data post-processing oceanic climate (Deutscher Wetterdienst 2017). The dom- All trees of the 11 plots with a diameter at breast height inant soil texture is till with the associated soil types luvi- (DBH) ≥ 7cm (n = 920) were segmented in a stepwise sols and pseudogleyic luvisols. The geological substrate procedure. First, the TLS point clouds were automatic- originates from the last (Weichselian) glaciation. ally segmented in trees with the SimpleTree (4.33.06) software, a plugin of Computree (5.0.054b) (Hackenberg TLS data acquisition and registration et al. 2015). Second, the automatically extracted trees For some of the analyses the growth data of the last de- were visually checked, and falsely classified tree seg- cades were required (see below). Therefore, we ments were manually corrected using RiSCAN PRO Georgi et al. Forest Ecosystems (2021) 8:26 Page 4 of 12 Fig. 1 a) Registered point cloud with multiple trees and ground; b) single segmented tree in red; c) crown volume in blue and crown projection area in yellow Table 1 Morphologic traits measured for each sample tree Measure Abbreviation Origin Reference/Calculation 2 2 Basal area (cm ) BA Point cloud/Inventory DBH × π/4 Diameter at breast height (cm) DBH QSM Raumonen et al. (2013) Crown volume (m ) CV Point cloud See methods this publication Tree height (m) TH Point cloud Z – Z max min Total wood volume (m ) V QSM Raumonen et al. (2013) tot Merchantable wood volume (m ) V QSM See methods this publication mw Volume of fine woody material (m ) V QSM See methods this publication fwm Crown base height (m) CBH Point cloud See methods this publication Crown projection area (m ) CPA Point cloud See methods this publication Crown surface area (m ) CSA Point cloud See methods this publication 2 −1 Basal area increment (cm ∙year ) BAI Point cloud/Inventory ΔBA/Δyears Branch length sum (m) QSM Raumonen et al. (2013) Mean branch angle 1st order (°) QSM See methods this publication Mean branch angle 2nd order (°) QSM See methods this publication Formula wood volume (m ) V Inventory Bergel (1973, 1974) 3 −1 Formula wood volume increment (m ∙year)V I Inventory ΔV I/Δyears f f Georgi et al. Forest Ecosystems (2021) 8:26 Page 5 of 12 (Fig. 1b). The original point density was not reduced with a concave hull (alpha-shape with α-value = 0.3) during the whole procedure to get the most accurate using the Point Cloud Library (Rusu and Cousins 2011) results. and the Computational Geometry Algorithms Library Several tree characteristics (Table 1) and the above- (Kai et al. 2019) (Fig. 1c). ground wood volumes were derived for each seg- mented tree individual using quantitative structure Target and neighbour tree selection models (QSMs). QSMs are a state-of-the-art approach The primary aim of this study was to analyse the neigh- (Raumonen et al. 2013) to quantify the 3D structure bourhood diversity effect on an individual-tree level. In of atreeand itsbranching topology.QSMsdeliver addition to the selection of the affected trees (in the fol- estimates of the aboveground wood volume with a lowing “target tree”), the determination of influencing high accuracy (Calders et al. 2015; Bienert et al. neighbours is of central importance. 2018). These models are a description of the tree as a To focus on vigorous trees as target trees, we included hierarchical collection of geometric primitives (here: only trees taller than two-thirds of the highest tree grow- cylinders). They are embedded into the point cloud ing in the plot for all analyses. Tree species with rare oc- from which geometric and topological tree character- currence (N ≤ 2) were excluded as target trees and one istics can be derived. To create the QSMs, we applied tree which was the only one having five neighbour tree the TREEQSM (2.30) software developed by Raumo- species. A total of 920 trees was extracted from the TLS nen et al. (2013), which runs within Matlab® (Math- point clouds of which 148 were dedicated as target trees Works, Natick, MA, USA) version R2018b on the (61% F. sylvatica, 20% Q. robur, 12% C. betulus,3% F. Taurus high-performance cluster (HPC) of the TU excelsior,2% A. pseudoplatanus and 2% L. decidua). For Dresden. The method categorizes the point cloud in 47 target trees a full set of DBH measurements from the the stem and single branches and captures the tree’s past three inventories was available. topology. Afterwards a volume model is compiled by Two approaches to identify the local neighbours were fitting cylinders in the point cloud segments (Raumo- used. The first approach was a fixed radial distance of nen et al. 2015;Kunzetal. 2017). Due to the param- 10 m from the target tree. Parameters which have been eter sensitivity of the modelling process, we calculated with these trees are subscripted with “ ”. radius conducted a parameter optimisation test with a subset In the second approach, we used the highly accurate of trees. This led to the following parameter values: point cloud to classify all trees as neighbours which first minimum patch size: 5 cm; second minimum crowns were overlapping with that of the target tree patch size: 1 cm; second maximum patch size: 2 cm; (with alpha-shape; α-value = 1). Examples for the differ- relative cylinder length: 4 cm; relative radius for out- ent outcomes resulting from the two neighbour selection lier removal: 5 cm. approaches are shown in Fig. 2. We extracted the basal area (BA), tree height (TH), A total of 238 trees were determined as neighbour- total wood volume (V ) and branch length of the TREE only trees (63% F. sylvatica, 17% Q. robur, 15% C. betu- tot QSM output. We also computed the merchantable wood lus,3% F. excelsior,1% P. avium and 1% L. decidua). volume (V ), defined as all aboveground woody struc- mw tures with a diameter > 7 cm (i.e. the trunk and the lar- Data analysis ger branches). The volume of fine woody material (V ; We applied two different approaches to quantify tree di- fwm diameter < 7 cm) was calculated as the difference of V versity in the local neighbourhood of a target tree (Table tot and V . 2). The number of tree species (neighbourhood species mw The trees mean branch angle was derived from all richness, NSR) and the exponential Shannon index (eH ) single branches and was calculated with the same based on the abundance of neighbouring trees (Shannon method for the first- and second-order branches, re- 1948; Jost 2006). B is the sum of BA of all neighbouring spectively. To measure the branch’s vertical orienta- trees of a given species i and B is the BA of all neigh- tion in space, we focused on the branch’sexit angle bours. Based on BA, this index has been used in former by considering the first ten cylinders after the branch studies to describe forest diversity (Liang et al. 2007; base, derived from theQSM.Fromthose,the angle Ratcliffe et al. 2015). between the Z-axes of the coordinate system and the B B mean branch axes was computed. i i eH ¼ exp − ln Moreover, we extracted numerous crown morpho- B B i¼1 logical traits. The crown base height (CBH), defined as the height of the lowest living branch, was measured in RiSCAN Pro. The crown projection area (CPA), CV and The partitioning of canopy space was analysed using crown surface area (CSA) for each tree were calculated the crown complementarity index (CCI) according to Georgi et al. Forest Ecosystems (2021) 8:26 Page 6 of 12 Fig. 2 Examples for the variable outcomes resulting from different tree neighbour selection approaches: left: overlapping tree crowns; right: fixed radius of 10 m. A: C. betulus, DBH = 19.4 cm, height = 23.6 m; B: Q. robur, DBH = 81.0 cm, height = 31.0 m. Solid circle radius = 12.62 m; dashed circle radius = 22.62 m. NN = Number of neighbours; NSR = Neighbourhood species richness (Williams et al. 2017). Crown complementarity (CC) was sylvatica, C. betulus, L. decidua) and Bergel (1974; Q. calculated for two trees as the difference in crown vol- robur, F. excelsior, A. platanoides). ume (V) between the two individuals (i and j) in each We applied linear mixed-effects models to assess the ef- stratum (k) summed across all strata. The CCI of a tree fects of tree diversity and space occupation on growth of is the mean of all its neighbour CCs. We calculated the target trees at the local neighbourhood scale. Explanatory CCI with a strata height of 0.5 m. variables were NSR, eH or CCI (either based on the fixed radius or crown overlap neighbour selection approach) and V −V the current BA or, for the increment models, the BA . ik jk init CC ¼ ij Target tree species identity and study plot were used as V −V i j crossed random effects. The following response variables were used: CV, CPA, CSA, branch length sum, mean first CC ij CCI ¼ order branch angel, mean second order branch angel, V , tot V , V ,BAI andV I. To improve the linear model fit mw fwm f 2 − 1 Basal area increment (BAI, cm ∙year ) and the mer- and reduce the residual variance, we log-transformed the chantable formula wood volume increment (V I, response variables and the BA. The model assumptions 3 − 1 m ∙year ) was calculated using DBH (by caliper) and were tested and validated according to Zuur et al. (2009). height measurements (with vertex) from inventories in Due to co-linearity of the competition (according to Hegyi 1992 and 2013. Calculations for merchantable wood vol- 1974;Martinand Ak 1984; Biging and Dobbertin 1992) ume were based on volume functions by Bergel (1973; F. with the BA, we excluded these from the models. Georgi et al. Forest Ecosystems (2021) 8:26 Page 7 of 12 Table 2 Biodiversity and space partitioning indices measured for each target tree Measure Abbreviation Origin Reference/Calculation Neighbour species richness NSR Inventory See methods this publication Exponential Shannon-Index eH Point cloud/Inventory Shannon (1948) Crown complementarity index CCI Point cloud Williams et al. (2017) All statistical data analysis was performed with R was found for the NN of large-crowned trees (see ex- (3.6.1; R Core Team 2019) using the packages nlme (Pin- ample in Fig. 2). heiro et al. 2019), lmerTest (Kuznetsova et al. 2019), MuMIn (Bartoń 2019) and effects (Fox et al. 2019). Neighbourhood diversity effects on crown architecture and wood volume Results Besides the strong positive effect of the BA, NSR and Neighbourhood definition effect eH significantly positively influenced the tree crown di- The two neighbour selection approaches yielded highly mensions (CV, CPA, CSA), branch length sum and the variable results regarding the number of neighbours wood volumes based on the neighbour selection ap- (NN) and NSR: the median ΔNN was 3, spanning a proach “crown overlap” (Table 3 and Fig. 3). In contrast, range from min = 0 to max = 18 and the median ΔNSR no significant influence of NSR and eH on the response was 0, with a range of min = 0 and max = 2. An import- variables was found when using the fixed radius selec- ant factor to explain the differences between the two ap- tion approach (with the only exception of a positive NSR proaches is the tree dimension, especially the CPA. For effect on CV, Table 2). With both selection approaches, trees with relatively small crowns, the NN is consider- no impact of the diversity measures on the mean first or ably higher using the fixed radius compared to the second order branch angel was observed. Moreover, the crown overlap approach. In contrast, an opposite pattern Fig. 3 Neighbourhood species richness (NSR) effect on trees crown architecture and wood volume, based on the neighbour selection approach “crown overlap”, with the shaded area representing the 95% confidence interval of the prediction. NSR levels jittered for better clarity Georgi et al. Forest Ecosystems (2021) 8:26 Page 8 of 12 Table 3 Results of mixed-effects models for the effects of neighbourhood tree species richness (NSR), exponential Shannon index (eH ), crown complementarity index (CCI) and target tree basal area (BA ) on crown dimensions, branch length and wood volume S log based on the two tree neighbour selection approaches fixed radius and “overlapping crowns” (n target trees = 148). In all models BA p =.: p < 0.1; *: p < 0.05; **: p < 0.01; ***: p < 0.001; n.s. = not significant log Response variable Fixed Fixed radius Overlapping crowns effects 2 2 Estimates pR Estimates pR c c Crown volume (log) NSR + BA 0.08 + 0.98 * 0.89 0.09 + 0.95 * 0.89 log eH +BA 0.01 + 0.95 n.s. 0.89 0.08 + 0.96 * 0.89 S log CCI + BA 0.04 + 0.95 n.s. 0.89 −0.10 + 0.93 ** 0.89 log Crown projection area (log) NSR + BA 0.04 + 0.70 n.s. 0.85 0.10 + 0.70 ** 0.86 log eH +BA −0.01 + 0.69 n.s. 0.85 0.08 + 0.71 * 0.86 S log CCI + BA 0.04 + 0.69 n.s. 0.85 −0.02 + 0.69 n.s. 0.84 log Crown surface area (log) NSR + BA 0.06 + 0.93 n.s. 0.89 0.10 + 0.92 ** 0.90 log eH +BA 0.00 + 0.91 n.s. 0.89 0.08 + 0.93 * 0.90 S log CCI + BA 0.01 + 0.91 n.s. 0.89 −0.05 + 0.89 n.s. 0.89 log Branch length sum (log) NSR + BA 0.09 + 0.70 n.s. 0.76 0.17 + 0.68 ** 0.77 log eH +BA 0.00 + 0.68 n.s. 0.75 0.13 + 0.69 * 0.77 S log CCI + BA 0.01 + 0.68 n.s. 0.76 −0.07 + 0.67 n.s. 0.74 log Total wood volume (log) NSR + BA 0.02 + 0.96 n.s. 0.97 0.06 + 0.96 ** 0.97 log eH +BA 0.00 + 0.96 n.s. 0.97 0.05 + 0.96 ** 0.97 S log CCI + BA −0.03 + 0.96 n.s. 0.97 −0.05 + 0.95 *** 0.97 log Fine woody material volume (log) NSR + BA 0.06 + 0.70 n.s. 0.81 0.14 + 0.69 ** 0.82 log eH +BA −0.01 + 0.69 n.s. 0.81 0.12 + 0.70 ** 0.82 S log CCI + BA −0.01 + 0.70 n.s. 0.81 −0.07 + 0.67 ** 0.80 log Merchantable wood volume (log) NSR + BA 0.01 + 1.07 n.s. 0.98 0.03 + 1.06 . 0.98 log eH +BA 0.02 + 1.07 n.s. 0.98 0.03 + 1.06 . 0.98 S log CCI + BA −0.04 + 1.08 ** 0.98 −0.04 + 1.07 ** 0.98 log CV and the wood volumes significantly increased with Discussion lower CCI. In the mature mixed-species forests examined in this study we observed significant impact of the local neighbourhood tree diversity on crown architecture Neighbourhood diversity effects on individual-tree as well as on wood volume and growth. These find- productivity ings were, however, very sensitive to the approach The effects of NSR on tree productivity (BAI and V I) used to select neighbouring trees. Whereas the fixed strongly depended on the initial size (i.e. BA) of a radial distance approach barely yielded significant re- target tree. For small-sized trees, BAI was higher in sults, this was always the case using the neighbour conspecific than in heterospecific neighbourhoods, selection based on overlapping crowns. Mature for- while large-sized trees benefitted from increasing NSR ests composed of late successional tree species dis- (Table 4 and Fig. 4). Interacting with the BA , play a wide range of tree sizes at small spatial scales. init.log NSR and eH had significant positive impacts on The large differences in the performance of the two both, BAI and V I, over the past 21 years. The local approaches points to an important role of above- CCI interacting with the BA also showed a ten- ground interactions, i.e. competition for physical init.log dency towards a positive influence on tree growth. space and light. Previous studies used various differ- Again, there is a high sensitivity of the results to- ent approaches to calculate a tree’s zone of influence wards the neighbour selection approach, because most or its competitors (Bachmann 1998). Earlier methods the investigated effects solely occurred or were stron- to determine the exact crown dimensions and neigh- ger with the neighbour selection approach “crown bours of a tree using a compass, hypsometer and overlap” than with “fixed radius” definition (data not crown mirror are error-prone and time-consuming. shown). Hence, an often-used simple neighbour selection is Georgi et al. Forest Ecosystems (2021) 8:26 Page 9 of 12 Table 4 Results of mixed-effects models for effects of target tree initial basal area (BA ), neighbourhood tree species richness init (NSR), exponential Shannon index (eH ) and crown complementarity index (CCI) on basal area increment and wood volume increment with the neighbour selection approach “crown overlap” (n = 47)..: p < 0.1; *: p < 0.05; **: p < 0.01 Fixed effects Basal area increment (log) Volume formula increment (log) 2 2 Estimate pR Estimate pR C C NSR × BA 0.161 . 0.79 0.186 * 0.82 init.log eH ×BA 0.177 * 0.80 0.205 ** 0.83 S init.log CCI × BA 0.116 . 0.76 0.110 . 0.78 init.log the use of fixed radii, a worldwide uniform approach dimensions (D’Amato and Puettmann 2004). In het- which is also cost effective without the use of TLS. erogeneous forests the choice of one specific radius This method, however, has two disadvantages. First, will always remain a compromise. In our study, the it only considers the fixed stem base location. This minimum and maximum crown diameters were 3.48 is the position where the seed sprouted and the tree and 17.00 m or 4.59 and 23.45 m, derived from the individual has been able to prevail until today. How- CPA and from the maximal chord, respectively. As ever, the competition for light, water and nutrients an alternative to a single fixed radius, several studies at this spot changes in the course of decades. In our used either a variety of radii (Lin and Augspurger study area, water and nutrient supply are generally 2006; Antos et al. 2010; Ratcliffe et al. 2015)ortree not limiting tree growth. Rather, trees compete for size dependent radii (von Oheimb et al. 2011). How- light (Schwinning and Weiner 1998) and competition ever, the strong advantage of the crown overlap ap- effects occur on the crown distribution (Longuetaud proach is to focus on every individual tree and its et al. 2013). Therefore, it is reasonable to select actual surrounding structure in three dimensions neighbours based on the photosynthetically active (Zambrano et al. 2019). At this level of resolution, part of a tree, the crown. The actual shape of a the procedureisonlypossibledue to the application crown represents the accumulated competitive cir- of highly precise TLS for forest science and ecology. cumstances of the past. A second disadvantage of a Deploying this state-of-the-art technology enables fixed-radius approach is the neglection of tree size enhanced insights in the outcome of tree-tree inter- differences by using the same radius for a range of actions at the local scale, even in temperate mature different sizes. It has often been found that the opti- forests with canopy heights of up to 45 m. mal radial distances strongly depended on tree size Fig. 4 Size-dependency of neighbourhood species richness (NSR) effects on the annual basal area increment with the neighbour selection approach “crown overlap”, with the shaded area representing the 95% confidence interval of the prediction Georgi et al. Forest Ecosystems (2021) 8:26 Page 10 of 12 Our results confirm previous findings that an in- opportunity to shift crown growth to a less competing crease in neighbourhood tree species richness allows direction (Ali 2019). trees to enhance their crowns in size and shape Since different structural characteristics induce various (Bayer et al. 2013;Kunzetal. 2019). The diversity- reactions among species with different resource-use driven plasticity is gained by enhanced branch strategies, the mixing effect is species-specific (Fichtner lengths and an increased biomass allocation to fine et al. 2017; Forrester 2019). To analyse the species- woody material (V ), leading to larger CPA and specific neighbour effects in temperate European mixed fwm greater CSA and thus to larger crown volume. forests with precise laser scanning technology might be Pretzsch (2014) stated, the more species, the larger the next step, requiring even more trees to achieve sta- the sum of the crown area. A tree’s individual crown tistically solid results. growth is a modular reaction to micro- environmental light heterogeneity (Kawamura 2010) Conclusions and thus elementary in the compensatory feedback With our study, we provide evidence that neigh- loop between structure, environment and growth bourhood species mixing has a significant influence (Bayer et al. 2013; Pretzsch 2014). Through the com- on individual tree morphology and productivity in bination of species with different light ecology and mature European mixed-species forest. Moreover, crown morphology, the canopy is more diverse and weshowed theimportanceofa preciseneighbour- the individual trees can respond and therefore utilize hood definition and selection procedure to reveal the canopy space in a more complementary way diversity effects in mature natural and near-natural (Pretzsch 2014). Our results support the niche com- stands. plementarity hypothesis, postulating the more effi- For future studies in heterogeneous mixed forests, it cient use of resources, here the physical partitioning would be advantageous to include an even larger num- in canopy space, by coexisting species (Tilman 1999; ber of trees to facilitate analyses across extensive areas. Forrester and Bauhus 2016). Along with higher A possible approach to advance in this direction is the architectural plasticity of individual trees the whole application of mobile laser scanning (Bienert et al. 2018) canopy might be packed denser (Cianciaruso et al. in combination with largely automated individual-tree 2009). segmentation procedures. This can be used to clarify With the enlargement of the crown and an in- two important questions. On the one hand, it enables crease in leaf-bearing branches of higher orders, the mixture effects to be examined for species-specific there is an increase in photosynthetically active area. mixing effects. On the other hand, the diversity effect Under the significant impact of local neighbourhood can be studied on several spatial scales with the help of diversity, the 47 observed trees in this study show a much larger dataset. an ambivalent growth pattern over 21 years. Smaller Abbreviations trees with a DBH smaller than 40 cm are impeded in ALS: Airborne laser scanning; BA: Basal area; BAI: Basal area increment; their radial growth whereas larger trees benefitted BEF: Biodiversity-ecosystem functioning; CBH: Crown base height; CC: Crown complementarity; CCI: Crown complementarity index; CPA: Crown projection from increasing NSR. These results are similar to area; CSA: Crown surface area; CV: Crown volume; DBH: Diameter at breast those of Lasky et al. (2015) and Fichtner et al. height; eH : Exponential Shannon-Index; HPC: High-performance cluster; (2017) who observed that taller tree individuals N: Number; NN: Number of neighbours; NSR: Neighbour species richness; QSM: Quantitative structure model; TH: Tree height; TLS: Terrestrial laser benefiting more from a diverse neighbourhood. This scanning; V : Formula wood volume; V I: Formula wood volume increment; f f might be due to size-asymmetric competition V : Volume of fine woody material; V : Merchantable wood volume; fwm mw (Schwinning and Weiner 1998) of larger trees receiv- V : Total wood volume tot ing disproportionally more light in comparison to Acknowledgments smaller individuals and thus the ability to occupy We thank the Forestry Offices of the City of Lübeck County for permission to free niches earlier. Divers tree species mixtures could conduct this study in their forests. The QSM calculations were made on the Taurus HPC cluster of the ZIH of the TU Dresden. Moreover, we would like to further enhance this effect. thank the anonymous reviewers for their comments and suggestions on the In contrast to Williams et al. (2017) who studied manuscript. young and comparatively small trees, we observed a Authors’ contributions negative effect of the CCI on CV and wood volume. LG and GvO conceptualized the study; KFR and GvO recorded the data; LG, However, a reverse reasoning is also plausible. The big- MK, AF and KFR analysed the data; LG prepared the original draft and all ger the crowns, the more equal they are. Since we have authors reviewed and edited the manuscript. The author(s) read and approved the final manuscript. studied mature trees, close to their maximum height, we suspect an upper growth limit and rather the CBH as a Funding decisive influence on this parameter. Moreover, the aver- LG was funded by the German Research Foundation (DFG 320926971) aging effect of the CCI is notable, neglecting a trees through the project “Analysis of diversity effects on above-ground Georgi et al. Forest Ecosystems (2021) 8:26 Page 11 of 12 productivity in forests: advancing the mechanistic understanding of spatio- Cianciaruso MV, Batalha MA, Gaston KJ, Petchey OL (2009) Including intraspecific temporal dynamics in canopy space filling using mobile laser scanning”. variability in functional diversity. Ecology 90(1):81–89. https://doi.org/10.1890/ 07-1864.1 Costes E, Gion JM (2015) Genetics and genomics of tree architecture. In: Plomion Availability of data and materials C, Adam-Blondon A-F (eds) Advances in botanical research. Land Plants - Data are available from the corresponding author on reasonable request. Trees. 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The funders had no role in the diversity. Ecol Lett 20(7):892–900. https://doi.org/10.1111/ele.12786 design of the study; in the collection, analyses, or interpretation of data; in Fichtner A, Sturm K, Rickert C, von Oheimb G, Härdtle W (2013) Crown size- the writing of the manuscript, or in the decision to publish the results. growth relationships of European beech (Fagus sylvatica L.) are driven by the interplay of disturbance intensity and inter-specific competition. For Ecol Author details Manag 302:178–184. https://doi.org/10.1016/j.foreco.2013.03.027 Technische Universität Dresden, Institute of General Ecology and Forrester DI (2019) Linking forest growth with stand structure: tree size inequality, Environmental Protection, Pienner Straße 7, 01737 Tharandt, Germany. tree growth or resource partitioning and the asymmetry of competition. 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