Abstract
Urban trees are important, green features of cities. However, knowledge of the size development of frequently planted tree species, which is the basis for modeling environmental benefits of urban trees, is mostly limited. Within this study, allometric relationships for tree structures like tree height, crown parameters, and leaf area were developed for 4 common urban tree species in South Germany (horse chestnut [Aesculus hippocastanum], small-leaved lime [Tilia cordata], black locust [Robinia pseudoacacia], and plane tree [Platanus × hispanica]). Growth and size differences between different tree species, cities, and planting sites (street, park, square) were analyzed. Moreover, the above- and belowground growing conditions were compared and their influences on growth analyzed. Marked differences in the structural development between species were found, mostly due to their species characteristics. Fast growing species (e.g., R. pseudoacacia) also showed fastest development of the tree structures compared to other species. Differences between cities were minor, especially for trees younger than 100 years, whereas the variation of growing conditions within cities strongly influenced their growth. Park trees mostly had greater tree structures compared to trees at other growing sites, though this was also species-dependent. Above- and belowground conditions varied between species, cities, and sites (street, park, square), with obstacles (trees, buildings) south of the trees having a negative influence on crown growth. These patterns can be helpful for better planning of green features in cities. They provide a basis for urban tree management based on the growing space requirements of tree species and their ecosystem service provision.
INTRODUCTION
The city landscape is a very unique growing environment for urban trees, diverging drastically from forest stands (Grabosky and Bassuk 1995; Bühler et al. 2006). Compared to typical forest trees, urban trees grow mostly in small planting pits with highly compacted and sealed soils (Day et al. 1995; Bühler et al. 2006). These planting pits are often characterized by reduced water supply, less oxygen input, poor soil qualities, and less mycorrhiza, as well as an overall small rooting space for trees (Morgenroth and Buchan 2009; Rahman et al. 2013). Besides a reduced belowground growing environment, the aboveground space can also be limited by power supply lines, close buildings, or pruning measures due to traffic security. Other influences affecting urban tree growth and vitality are inputs of dog urine, de-icing salts in winter, higher nitrogen and pollution loads, as well as a higher occurrence of pests and diseases (Whitlow and Bassuk 1986; Petersen and Eckstein 1988; Cekstere et al. 2008).
In addition to site conditions, the city environment itself is often warmer than the rural surroundings due to the urban heat island (UHI) effect (Oke 1982; Akbari et al. 2001; Day et al. 2010). Climate change is expected to aggravate the UHI effect and related environmental issues, such as a change of local precipitation, spread of diseases from warmer climates, and air pollution (Oliveira et al. 2011). Several studies have described a severe UHI effect, e.g., Zhou et al. (2014) showed a UHI effect of around 2 °C for China’s megacities, while Tran et al. (2006) found a UHI effect of 5 to 8 °C in Asian cities, with a maximum of 12 °C in Tokyo, Japan, and Peng et al. (2012) found a UHI effect of around 6.5 °C for global big cities. Even for a small European city at the coast of Crete, Greece, a UHI effect of 8 °C in summer was observed (Kolokotsa et al. 2009). Another study on the UHI effect in Europe during the severe heat wave of 2006 found that, interestingly, cities of cooler climates seem to be more vulnerable to heat waves, whereas southern European cities appear to be better adapted (Ward et al. 2016).
All this influences tree growth and vitality, leading to a higher mortality and reduced maximum age of urban trees compared to trees in rural surroundings or forest stands (Roman and Scatena 2011). For several species, the pool of planted trees in cities is mostly younger than 50 years (Vaz Monteiro et al. 2017). As Sanders et al. (2013) stated, expectations on tree performance over time is often only expressed as establishment success. However, good vitality and high growth rates for older trees also are important criteria for the urban tree stock of a city.
Besides these performance criteria regarding vitality and growth, climate mitigation effects of trees are often named as important features of urban trees, especially in view of the UHI effect and climate change (Millennium Ecosystem Assessment 2005). These benefits for humans provided by urban trees are called ecosystem services. Ecosystem services that are especially important for human thermal comfort in cities and city climate regulation include carbon storage and sequestration (Davies et al. 2011; Liu and Li 2012), cooling by shading and evapotranspiration (Konarska et al. 2016; Rahman et al. 2020b), regulation of water flow (Villarreal and Bengtsson 2005), air pollutant filtration (Sæbø et al. 2012), noise buffering (Roy et al. 2012), as well as promotion of human recreation and health (Gómez-Baggethun and Barton 2013). In contrast, several disservices of urban trees exist as well, e.g., allergenicity to pollen, litter fall, and damage to streets and pavement (Escobedo et al. 2011; Moser et al. 2018).
Several studies have analyzed the ecosystem service provisions of urban trees. Rahman et al. (2020a) for example studied the cooling effects of Robinia pseudoacacia and Tilia cordata, two common urban tree species in Germany, and found clear species differences. Nowak et al. (2013) assessed citywide carbon sequestration of urban trees in US cities, and Berland et al. (2017) dealt with the water regulation capacity of urban trees. Moreover, simulation studies based on growth models such as i-Tree (2019) or CityTree (Rötzer et al. 2019) give insight into the ecosystem service provisions of different tree species of various ages.
However, the magnitude of provided ecosystem services by urban trees depends on various aspects. Tree species, age, and structures like crown height need to be considered when modeling services of single trees, tree stands, or on a citywide scale (Xiao et al. 2000; Bayer et al. 2018; Rötzer et al. 2019; Rahman et al. 2020b). Therefore, allometric studies on the structural development of urban tree species over time, as published by McPherson et al. (2016) for several US cities, Stoffberg et al. (2008) for South African tree species, Semenzato et al. (2011) for urban trees in Italy, or Dahlhausen et al. (2016) for several tree species worldwide, provide the basis for accurate ecosystem service modeling. Regarding the vast numbers of available urban tree species and different climate conditions worldwide, great knowledge gaps for many species, growing sites within cities, and climate regions are obvious. As McHale et al. (2009) state, growth equations of urban trees of a certain city and climate region cannot simply be transferred to other growth conditions. More region-, site-, and species-specific research on tree development over time is necessary to provide an adequate basis for ecosystem service modeling.
In summary, the lack of regional and site-specific data on urban tree development is a major restriction in applying accurate modeling approaches to quantify urban tree growth and service provision. Here we present allometric relationships for 4 common urban tree species in central Europe (small-leaved lime [Tilia cordata], horse chestnut [Aesculus hippocastanum], black locust [Robinia pseudoacacia], and London plane tree [Platanus × hispanica]), which differ in their ecological and morphological character. Differences in tree growth between species, cities, and growing sites within the city were analyzed. With this study, we try to close existing knowledge gaps in the growth relationships of urban trees for a South German city, making growth predictions for future space planning possible and providing a basis for ecosystem service calculation of urban tree species. In detail, we pose the following research questions:
What are the growth characteristics of T. cordata, R. pseudoacacia, A. hippocastanum, and P. × hispanica in South German cities?
What are the specific allometric relationships and differences of these species?
Are there differences in the growth relationships between the analyzed tree species, cities, and growing site categories (street, square, park) within the city?
How do above- and belowground obstacles, such as planting pit size, close-growing trees, or present buildings, influence tree growth?
MATERIALS AND METHODS
Site Description
The study was conducted in 6 South German cities, Munich (48°09′N, 11°35′E), Würzburg (49°48′N, 9°56′E), Nuremberg (49°27′N, 11°4′E), Bayreuth (49°56′N, 11°34′E), Hof (50°18′N, 11°54′E), and Kempten (47°43′N, 10°18′E), from 2014 to 2017. Figure 1 provides an overview of the geographical location of the cities as well as the sites of the measured trees across the cities. The cities were chosen due to their different climatic characteristics (Table 1).
Selected cities and the measured individual trees across the cities. The background map of Bavaria, Germany shows the location and the climate (average precipitation in July) of the selected cities (Rötzer et al. 1997). The maps of the cities provide the sampling sites of the measured tree species: A. hippocastanum (brown), R. pseudoacacia (red), T. cordata (green), and P. × hispanica (blue)(ESRI 2019).
Climate characteristics of the long-term mean (1965–2015) of the selected cities derived from DWD (2018).
Of all 6 cities, Hof and Kempten are the coldest, with an average yearly temperature of 7.5 °C and 7.4 °C, respectively. Kempten is also characterized by the highest amount of yearly precipitation (1,257 mm). Würzburg is the warmest city together with Munich, both having a yearly temperature average of 9.6 °C, though Würzburg is the driest city of all chosen cities, with a yearly precipitation of 599 mm. Kempten is located at highest altitude of 674 m above sea level (ASL), while Würzburg is located at 177 m ASL.
Data Collection
Altogether, 553 T. cordata, 448 P. × hispanica, 412 R. pseudoacacia, and 590 A. hippocastanum were chosen for data collection in the 6 cities. Tilia cordata is a native, very common urban tree in central Europe. It is shade-tolerant, can grow up to 30 m tall, has a medium to high leaf area index (LAI)(Rauner 1976), and a diffuse-porous wood anatomy (Larsen and Kristoffersen 2002; Radoglou et al. 2009). Robinia pseudoacacia, on the other hand, was introduced from the northern US; however, it is now a very common urban tree in central Europe. It is light-demanding, grows up to 30 m, has a low LAI, and has a ring-porous wood anatomy (Moser et al. 2016). Platanus × hispanica is a crossing of P. orientalis with P. occidentalis and is also common in central Europe. It is light-demanding, can reach heights of 35 m, and has a diffuse-porous wood anatomy as well as a low LAI. Aesculus hippocastanum can be found commonly in central Europe, has a high LAI, can grow up to 30 m, and is diffuse-porous (Roloff 2013).
The sampled trees were selected to represent 3 types of open spaces with their different growth conditions: park trees, trees at public squares, or street trees. If possible, at least 30 individual trees were collected per species in each site category in each city. Park trees were growing in a green area without buildings, while street trees were trees planted in a street canyon. Only trees growing between the sidewalk and the street were selected; other trees, such as those on front lawns, were excluded. Hereby, public square trees are defined as freestanding trees with open, detached crowns growing in smaller, mostly paved spaces freely accessible to the public. Additionally, crowns of public square trees did not reach over streets. Damaged, pruned, or low-forking trees were excluded from data collection. For each tree, the following information was recorded: diameter at breast height (DBH), tree height (TH), crown base height (CS), crown length (CL), crown radii, tree pit, vitality, coordinates and altitude, and distance to adjacent buildings and trees (Figure 2).
Illustration of measured and calculated tree structural variables: diameter at breast height (DBH), tree height (TH), crown base height (CS), crown diameter (CD), crown length (CL), crown projection area (CPA), crown volume (CV), and tree pit.
DBH of all trees was measured with a diameter measurement tape at a height of 1.3 m. Tree height and crown length, defined as the distance from the top of the crown to the beginning of the trunk and to the lowest primary branch, respectively, were measured using a Forestor Vertex IV (Haglöf, Langsle, Sweden). Crown radii and tree pit were measured in 8 intercardinal directions (N, NE, etc.) along the ground surface with a measuring tape from the center of the trunk to the tip of the most remote downward-projecting shoot and to the last visible, open, non-asphalted surface of the soil. The distances to the neighboring trees and buildings were estimated in 8 intercardinal directions.
From the measured tree data, further tree variables were calculated (Figure 2). With the following equations, average crown radius (CR) and crown diameter (CD), crown volume (CV), crown projection area (CPA), and average tree pit were derived:
with RN as the widest measured crown extension in the northern direction, RNE the widest crown extension in the northeast direction, etc.
Moreover, the unsealed area of the tree pit in each intercardinal direction was calculated from the maximum influence area of the tree crown in each intercardinal direction:
With influencing areaX = ([1.5 × CRX]2 × π)/8 and DX as the longest distance of open surface in each direction (N, NE, etc.).
LAI was derived from hemispherical pictures taken during the fully foliated phase (July through August) with a Nikon Coolpix P5100 camera equipped with a fisheye lens. The resulting hemispherical photos were analyzed with the programs WinSCANOPY and XLSCanopy (Régent Instruments Inc., Quebec, Canada). The age of all sampled trees was computed with age formulas based on tree structures. For T. cordata and P. × hispanica, the formulas of Lukaszkiewicz and Kosmala (2008) were applied. To obtain the age of R. pseudoacacia, we used a species-dependent age factor of 0.996, which is based on the measurements of Dwyer (2009) for Gleditsia triacanthos. The age of A. hippocastanum was derived by dividing the DBH by 1.01 based on the measurements of Bühler et al. (2006). This approach, however, held some uncertainty and errors regarding the true age of the trees. Therefore, most further shown results are based on DBH. Figures related with age can be found in the appendix.
Statistical Analysis
The software package R version 3.6.1 (R Core Team 2020) was used for statistical analysis. With regression analysis, the associations between tree structures such as tree height, crown length, crown diameter, crown volume, crown projection area, LAI, and tree pit with DBH (Figure S1) as well as age (Figure S2) were determined. All regressions were performed using log transformation of the tree structures, following Pretzsch et al. (2012), Stoffberg et al. (2008), and Peper et al. (2001). Age-related growth was graphically analyzed with nonlinear least square (nls) functions. Using the R package lme4 (Bates et al. 2015), linear mixed models were developed to analyze the influence of obstacles (buildings, trees) on tree structural development. Analysis of variance (ANOVA) with Tukey’s HSD test was performed to identify differences between the measured tree dimensions in the abovementioned categories (park, public square, street). Assumptions for ANOVA (normal distribution, homogeneity of variances) were tested by the Shapiro-Wilk test, Levene-test, and with graphical display. The average tree pit size and distance of close obstacles was graphically illustrated with circle plots (Jiddu 2016).
RESULTS
In Table 2, the average tree structures of all measured trees in each city are given. Due to difficulties in finding tree individuals for each species in every city, the number of sampled trees per city varies. For example, in Hof, there were hardly any R. pseudoacacia trees available, therefore only 17 trees were sampled. Since trees of every age class were collected, the average age of the trees should be similar. However, due to species features, A. hippocastanum proved to be oldest on average (68 years), and P. × hispanica the youngest (37.5 years). Despite having the lowest average age, P. × hispanica provided the highest tree height (15.7 m) together with the largest crown diameter (11.2 m), CPA (113.7 m2), and crown volume (1,759.8 m3) on average (P < 0.001).
Mean values and standard deviation of age, diameter at breast height (DBH), tree height (TH), crown diameter (CD), crown length (CL), crown projection area (CPA), crown volume (CV), and tree pit, together with the sample size (n) of each species (A. hippocastanum, P. × hispanica, R. pseudoacacia, and T. cordata) in the chosen cities of Bayreuth, Hof, Kempten, Munich, Nuremberg, and Würzburg.
Between the cities, differences regarding mean tree structures were found (Table 2, P < 0.001). Despite being statistically significant, these were minor and mostly related with the tree species (P < 0.001) and site conditions within the cities (P < 0.001).
Allometric Relationships
Allometric relationships were established by regression analysis. Figure 3 shows the logarithmic relationships of tree structures with DBH for the 4 analyzed species. Related regression coefficients can be found in Table 3. When comparing the results of the regression analysis (intercept a and slope b) shown in Table 3 and Figure 3, a faster structural development (e.g., of tree height, crown diameter) for P. × hispanica is obvious compared to the other species. With a small DBH, R. pseudoacacia has similar tree structures, but with a DBH of 20 cm, the development of this species slows down. The only exception is LAI, where P. × hispanica shows an atypical development of a decreasing LAI over increasing DBH, while the LAI of the other species increases with an increase of DBH. The highest LAI was found for T. cordata, especially when the trees grow older. The allometric relationships can be used to estimate the necessary growing area and the space requirements of a species, with the development of different species for comparison. For instance, at a DBH of 20 cm, A. hippocastanum has a tree height of around 8 m, a crown diameter of 5.6 m, a crown volume of 150 m3, and a LAI of 2.2, while a P. × hispanica tree of the same DBH has a tree height of 11.5 m, a crown diameter of 7.1 m, a crown volume of 318 m3, and a LAI of 2.0. The values for R. pseudoacacia and T. cordata at a DBH of 20 cm are somewhere in between (R. pseudoacacia: tree height 10.6 m, crown diameter 6.1 m, crown volume 210 m3, LAI 1.2; T. cordata: tree height 10 m, crown diameter 5.7 m, crown volume 176.3 m3, LAI 2.2). Similar comparisons can be made for other DBH values for the 4 species (Figure 3 and Table 3).
Allometric relationships based on diameter at breast height (DBH) for the development of tree height, crown projection area (CPA), crown diameter, crown length, crown volume, and leaf area index (LAI) of A. hippocastanum, P. × hispanica, R. pseudoacacia, and T. cordata, pooled for the 6 South German cities by regression. Regression coefficients are given in Table 3.
Allometric relationships with intercept (a), slope (b), standard error (SE), residual standard error (RSE), R2, F-value, and P-value for A. hippocastanum, P. × hispanica, R. pseudoacacia, and T. cordata in South Germany to estimate tree height (TH), crown projection area (CPA), crown diameter (CD), crown length (CL), crown volume (CV), and leaf area index (LAI) over diameter at breast height (DBH)
Growth Differences Between Species and Cities
Figure 4 provides an overview of tree height growth over DBH of the 4 analyzed tree species in the 6 cities. It is obvious that P. × hispanica showed the fastest height increment in all cities (P < 0.001). Only in Bayreuth, R. pseudoacacia had a faster height development for bigger trees. R. pseudoacacia and T. cordata showed mostly an intermediate tree height increment, while A. hippocastanum had the lowest increment compared to the other species. This varied for some cities, e.g., in Nuremberg, older R. pseudoacacia showed a slower height development than the other species. On the other hand, in Hof, Kempten, Munich, and Würzburg, older T. cordata experienced a faster height growth than R. pseudoacacia and A. hippocastanum.
Development of tree height in m over diameter at breast height (DBH) in cm for the analyzed tree species A. hippocastanum, T. cordata, P. × hispanica, and R. pseudoacacia in Bayreuth, Kempten, Hof, Nuremberg, Munich, and Würzburg, generated with non-linear least square functions.
Further, the differences in tree growth between the cities were analyzed for each species (Figure 5). While especially the tree-height development of T. cordata was very similar in all cities, higher differences were found for R. pseudoacacia, P. × hispanica, and A. hippocastanum. All in all, the differences between the cities were smaller for the crown diameter development than for tree height. Similar figures about tree development of CPA and crown volume over DBH and for tree height, crown diameter, CPA, and crown volume over age for each city and species can be found in the appendix (Figures S1 and S2).
Development of tree height in m and crown diameter in m over diameter at breast height (DBH) in cm in Bayreuth, Kempten, Hof, Nuremberg, Munich, and Würzburg for the analyzed tree species A. hippocastanum, T. cordata, P. × hispanica, and R. pseudoacacia, generated with nonlinear least square functions.
Effect of the Planting Site on the Species-Specific Structure and Growth
Park trees of all species showed the highest average DBH compared to trees at squares and streets (Figure 6). However, while DBH of park trees differed significantly from trees at squares and streets for R. pseudoacacia, only streets trees were markedly different from park trees for the DBH of T. cordata, while trees at squares showed significant differences to park trees for A. hippocastanum and P. × hispanica. In total, trees of P. × hispanica showed a more uniform DBH growth regardless of growing site, while trees planted in squares showed the smallest DBH for A. hippocastanum, and street trees showed the smallest DBH for T. cordata.
Boxplots of diameter at breast height (DBH) distribution (upper row) and tree height distribution (lower row) of R. pseudoacacia, T. cordata, A. hippocastanum, and P. × hispanica grown at parks, squares, and streets for all cities pooled together. * : P < 0.05, ** : P < 0.01, *** : P < 0.001.
Similar results were found when looking at average tree height of all individuals of one species per type of growing site. For all species, park trees were the tallest, which were also significantly different from the street and square site categories. Only for P. × hispanica were park trees not significantly taller than street trees. For R. pseudoacacia, A. hippocastanum, and P. × hispanica, trees at squares were smallest regarding tree height, while street trees of T. cordata showed the smallest tree height.
Influence of Surrounding Trees and Buildings
The available above- and belowground space for tree development in cities of South Germany and its influences on tree structures were estimated. Figure 7 presents the average unsealed area around the tree stem (e.g., grass, soil) and distance from the tree stem to buildings and other trees for each intercardinal direction (N, NE, etc.) pooled for each city, species, and site, as well as the average crown radius of all measured trees. The center of each circular plot represents the individual tree location. Clear differences were found between cities regarding the unsealed area around a tree. Especially in Hof, urban trees are growing in significantly smaller tree pits (P < 0.001), similar in size to the average crown radius. In Würzburg, the tree pits have the greatest size. Overall, the unsealed area was in most cases distributed evenly around the trees, and no exceptions were found for a direction. Similar results regarding the uniformity of unsealed area around the tree trunk were found when looking at the unsealed area of each species and growing location. T. cordata and R. pseudoacacia had a significantly smaller tree pit than A. hippocastanum and P. × hispanica (P < 0.001). Moreover, as could be expected, park trees showed a far greater tree pit than trees growing in streets and public squares (P < 0.001).
Circle plots of the average (a) unsealed area and (b) distance to a surrounding tree or building in 8 measured intercardinal directions in the categories city, species, and site, plotted with the average crown radius of all trees. The center of each circular plot refers to the tree location.
When looking at the average distances to the next building or tree in each direction, differences between cities were less obvious. Only in Würzburg (P < 0.01) and Nuremberg (P < 0.001), the surrounding environment was significantly smaller than in Bayreuth, where especially in directions E, SE, S, and SW, the greatest distances were found. The circular plots for the surrounding tree environment show clear differences for each species, however. R. pseudoacacia trees were on average planted closer to buildings and other trees (P < 0.001). A. hippocastanum and P. × hispanica, on the other hand, had the most space for growth, while for T. cordata, intermediate distances were recorded. Regarding the growing site, street trees had significantly less space for growth (P < 0.001). Trees at squares show a relatively great distance to buildings or other trees, which is only slightly smaller than for park trees. Availability of aboveground space was overall similar for all species. Only for P. × hispanica and A. hippocastanum was a smaller distance to buildings and other trees found in the southern direction, which could be negatively affecting tree growth due to light inhibition. The plotted average crown radius showed no differences for a particular direction.
Further mixed models on the influence of each intercardinal direction on crown radius development showed a positive influence of more below- and aboveground space on crown radius. We found differences regarding the direction, especially in southern directions (SE, S, SW): a larger tree pit and greater distance to growth hindrances were positive for crown radius formation (for mixed model results, see Tables S1 and S2).
DISCUSSION
This study presents a detailed analysis of the structural development of 4 selected urban tree species in South Germany. More than 2,000 individual trees were measured in 6 cities. To generate a broad picture of the structural development of urban trees, from planting to old age, our approach includes the measurement of trees of a broad range of DBH classes. With trees ranging in DBH from 10 cm up to 150 cm, we provide a large database for further studies, such as on the ecosystem services of urban trees, as has been illustrated by Rötzer et al. (2019).
The allometric relationships show, with some exceptions, high correlations between DBH and all other structural parameters (R2 > 0.7). Only the relationships of R. pseudoacacia for DBH with tree height and crown length are weaker, possibly due to the light-demanding character of this species, which leads to different tree structures depending on site conditions (Moser et al. 2015). All in all, the strong correlations demonstrate that the tree structures can be predicted rather well by DBH. Recently, many studies on the allometric relationships of urban trees have been published (e.g., Stoffberg et al. 2008; Semenzato et al. 2011; Rijal et al. 2012; Sanders and Grabosky 2014). They provide information on the structural development of different urban tree species over time. However, the vast number of urban tree species makes it hard to compare studies, since these studies also have been conducted in other climate regions (e.g., Acadian Region in North America, California in USA, Italy, and South Africa). An earlier study in Germany (Eastern, Western, and Central regions) also analyzed tree-height development over age and DBH for A. hippocastanum, T. cordata, and P. × hispanica (Rust 2014). In that study, a more similar tree height growth was found for all species, while in our study, a faster growth of P. × hispanica compared to the other studied species was obvious. Also, differences between the cities were marked, which was explained by the different influence of wind in the cities, leading to a varying slenderness of the crown (Rust 2014). On the other hand, another study on A. hippocastanum in Munich and T. cordata in Berlin, Germany, as well as P. × hispanica in Paris, France, found the lowest tree-height development for A. hippocastanum and fastest tree height growth for P. × hispanica (Dahlhausen et al. 2016), similar to our study. Likewise, the results showed the widest crown diameter development for P. × hispanica, with T. cordata being intermediate, and A. hippocastanum the smallest growing species (Dahlhausen et al. 2016).
As McHale et al. (2009) stated, due to the various growing conditions, the great number of urban tree species, and the different climate regions, the transfer of allometric studies to other cities may not be possible. Pretzsch et al. (2015) assigned tree species to allometric types in their study, which can be used as a first approach to generalize allometric studies for similar climate and growing conditions (Dahlhausen et al. 2016). These types were based on the growing size of the tree species and the growth speed (development of tree height over DBH) and are, for instance, medium-size trees with medium growth, like Fraxinus excelsior, or large-size trees with medium growth. The 4 species of this study, T. cordata, P. × hispanica, R. pseudoacacia, and A. hippocastanum, are categorized as large-size trees with medium growth (Pretzsch et al. 2015). The allometric equations in our study were derived from a large data set including a great range of growth conditions, making them robust enough for a transfer to similar urban situations at least within southern Germany, but likely also more widely for urban areas where climatic conditions and geology are not strongly different. In particular, if tree inventories or cadastres are missing, such a transfer of allometric relationships to similar species types or functional groups can generate important information on tree structural development and ecosystem service provision. However, the environmental conditions of urban ecosystems (e.g., climate, air pollution) or even the small-scale conditions of the site (e.g., soil characteristics, soil sealing, light reduction) can change tree growth, carbon allocation, and ecosystem service provision significantly. For example, substantial soil sealing and/or a low soil water-storage capacity might induce a stronger root growth and therefore change the root-shoot allometry (Rötzer et al. 2009). Such a behavior is of course species dependent and may alter the growth strategy of urban trees along with other species-specific physiological characteristics, such as the stomatal reaction to drought (aniso- or isohydric behavior; see e.g., Roman et al. 2015; Rötzer et al. 2017).
This assumption on the transferability of allometric relationships is also supported by the small differences in the growth patterns between the analyzed cities. Up to an age of 100 (with exception of the height development of R. pseudoacacia), trees showed a very uniform growth, regardless of the city. Differences found for the tree-height development in particular for old R. pseudoacacia and P. × hispanica can be explained by their high light demand, which leads to faster shoot development. These small differences are surprising though, since the chosen cities vary in their climate and provide different growing conditions for trees. Kempten, for example, receives double the amount of precipitation of Würzburg, but this does not result in markedly faster tree growth. The tree height and crown diameter growth of the studied tree species in the 6 cities was not uniform.
Small differences between cities seem to be highly influenced by species characteristics, as well as by different above- and belowground growing conditions. In detail, the results fit well with the different growth strategies of the analyzed tree species. Light-demanding, fast-growing species such as P. × hispanica and R. pseudoacacia showed in all cities and at all growing sites the highest growth rates, e.g., fastest tree height or crown diameter development. Slower growing species such as T. cordata and A. hippocastanum were, on the other hand, characterized by lower growth rates.
As was proven for several urban tree species (see e.g., Rhoades and Stipes 1999; Pretzsch et al. 2017; Vaz Monteiro et al. 2017), urban trees often experience higher growth rates due to growing more isolated, or experiencing warmer temperatures and longer growing periods. However, as our study could show, especially at street sites and public squares, the tree pit size can be tremendously reduced, which clearly resulted in reduced growth. Also, aboveground competition occurs at all growing sites. It could be expected that light-demanding species react with faster height growth to aboveground limitations. However, this was not found for P. × hispanica and R. pseudoacacia in the city of Nuremberg, where shortest distances to obstacles like buildings and other trees were observed. For example, at a DBH of 60 cm, P. × hispanica had in Nuremberg a 23% reduced tree height and 11% reduced crown diameter, while in Hof, tree height was reduced by 22% and crown diameter by 40% compared to the average tree height and crown diameter in all cities of 60 cm DBH. Similarly, R. pseudoacacia had at the same DBH a reduced crown diameter of 6% in Hof and a 12% reduced crown diameter in Nuremberg, while tree height was similar to the average tree height in all cities. So it seems that both species, and in particular P. × hispanica, are sensitive to belowground restrictions, as in the city of Hof, where the tree pit was smallest and high growth reductions of up to 40% were measured.
For R. pseudoacacia, these results might also be biased by a low number of sampled trees, since in Hof less than 20 individuals could be included in our study. Moreover, T. cordata and A. hippocastanum also showed in Hof (city with smallest tree pits) a slower crown diameter development than in other cities with bigger tree pits. At a DBH of 60 cm, crown diameter reductions of 5% compared to the average were found.
In parks, tree pits were significantly larger than tree pits of streets and squares. However, due to close plantings with other trees, aboveground space was also found to be markedly reduced in parks. This was reflected by the average tree height of the analyzed tree species, where park trees had greater DBH and tree height on average. However, as has been found before by Moser et al. (2015), trees in parks are also often older than trees in streets and on squares, which could bias the results. The light-demanding species P. × hispanica showed at streets a fast tree-height development, which may have been influenced by limited aboveground space. Trees at streets and public squares often showed smaller DBH and tree height, especially for R. pseudoacacia and A. hippocastanum, while tree structures were more similar for T. cordata and P. × hispanica. In a similar study on the growth of urban trees in street canyons, squares, and parks, a likewise better tree growth of park trees compared to trees in streets and at squares was found (Kjelgren and Clark 1992). Moreover, highest shoot growth was found for street trees, possibly due to light obstructions, as has been found for P. × hispanica as well in our study. Neal and Whitlow (1997) also found in a study on urban tree growth of Quercus phellos in Washington, DC (USA) a higher growth of trees growing in semi-natural, park-like settings. In their conclusions, the authors stated that when urban trees experience proper design and installation, high growth rates can be achieved in unfavorable settings, like at streets or squares (Neal and Whitlow 1997).
CONCLUSION
The study described the structural development of 4 urban tree species in detail, providing a database for the space requirements of common tree species over time, as well as for further modeling of ecosystem services such as carbon storage, cooling, or shading. Differences found in structural development were mostly related to different species characteristics and growing conditions within the city, while the city itself and its climate seemed to have minor influence. With certain limitations, a transfer of the provided growth equations to species of similar allometric types growing in comparable climate regions may be achieved, especially in cities without available tree inventories. Such information can be applied to better estimating the likely growth of urban trees in different growing sites and the ecosystem services derived from them. In that, it may help to make provision for suitable above- and belowground growing space for urban trees and address conflicts with the placement of buildings from the beginning. In the long term, the measurement of urban tree functions, structure, and growth in other climate regions and for other species is strongly recommended for accurate modeling of ecosystem services or for a realistic calculation of space requirements. Further research needs to provide allometric relationships also for additional species in this climate zone and other urban tree species in different climate zones, as well as for other planting types, such as private gardens, to have an accurate estimation of the urban tree stock in cities. Also, dendrochronological studies are necessary to derive the true age of urban tree species, which avoids the application of age-equations inducing a certain error. Only with a correct estimation of the tree stock can modeling studies provide an adequate overview of the ecosystem service provision of urban trees, which can be used to plan for sustainable cities.
ACKNOWLEDGMENTS
The authors thank the Bavarian State Ministry of the Environment and Consumer Protection for funding the projects TUF01UF-64971 “Urban trees under climate change: Growth, functions and services, and perspectives” and TKP01KPB-71924 “Climate experience Würzburg: Influence of trees on the micro climate of the city of Würzburg” of the Centre for Urban Ecology and Climate Adaptation (ZSK). We also would like to thank the responsible municipal authorities of Munich, Würzburg, Hof, Kempten, Bayreuth, and Nuremberg, who supported the study and permitted tree sampling. We further would like to express our gratitude to many student helpers for their help in data collection.
Appendix 1.
Linear mixed model of the crown radius in m of all analyzed trees (response variable), with the individual tree code as random effect and fixed effects area of the tree pit related to the intercardinal direction factor.
Linear mixed model of the crown radius in m of all analyzed trees (response variable), with the individual tree code as random effect and fixed effects distance to next obstacle (trees and buildings) related to the intercardinal direction factor.
Development of crown projection area (CPA) in m2 and crown volume (CV) in m3 over diameter at breast height (DBH) in cm for the analyzed tree species A. hippocastanum, T. cordata, P. × hispanica, and R. pseudoacacia in Bayreuth, Kempten, Hof, Nuremberg, Munich, and Würzburg, generated with nonlinear least square functions.
Figure S2. Development of tree height in m, crown diameter in m, crown projection area (CPA) in m2, and crown volume in m3 over age in years for the analyzed tree species A. hippocastanum, T. cordata, P. × hispanica, and R. pseudoacacia in Bayreuth, Kempten, Hof, Nuremberg, Munich, and Würzburg, generated with nonlinear least square functions.
Footnotes
Conflicts of Interest:
The authors reported no conflicts of interest.
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