Research ArticleArticles

Plant and Wood Area Index of Solitary Trees for Urban Contexts in Nordic Cities

Johanna Deak Sjöman, Andrew Hirons, Nina Bassuk and Henrik Sjöman
Arboriculture & Urban Forestry (AUF) November 2021, 47 (6) 252-266; DOI: https://doi.org/10.48044/jauf.2021.022

Abstract

Background: We present the plant area index (PAI) measurements taken for 63 deciduous broadleaved tree species and 1 deciduous conifer tree species suitable for urban areas in Nordic cities. The aim was to evaluate PAI and wood area index (WAI) of solitary-grown broadleaved tree species and cultivars of the same age in order to present a data resource of individual tree characteristics viewed in summer (PAI) and in winter (WAI). Methods: All trees were planted as individuals in 2001 at the Hørsholm Arboretum in Denmark. The field method included a Digital Plant Canopy Imager where each scan and contrast values were set to consistent values. Results: The results illustrate that solitary trees differ widely in their WAI and PAI and reflect the integrated effects of leaf material and the woody component of tree crowns. The indications also show highly significant (P < 0.001) differences between species and genotypes. The WAI had an overall mean of 0.91 (± 0.03), ranging from Tilia platyphyllos ‘Orebro’ with a WAI of 0.32 (± 0.04) to Carpinus betulus ‘Fastigiata’ with a WAI of 1.94 (± 0.09). The lowest mean PAI in the data set was Fraxinus angustifolia ‘Raywood’ with a PAI of 1.93 (± 0.05), whereas Acer campestre ‘Kuglennar’ represents the cultivar with the largest PAI of 8.15 (± 0.14). Conclusions: Understanding how this variation in crown architectural structure changes over the year can be applied to climate responsive design and microclimate modeling where plant and wood area index of solitary-grown trees in urban contexts are of interest.

Keywords

INTRODUCTION

In the urban landscape, vegetation is paramount to the mitigation of rising temperatures, where trees in particular are fundamental to lowering the urban heat island effect (Masson et al. 2020). Trees play a central role in cities’ green infrastructure and often provide multiple services and benefits to the community (Pauleit et al. 2017). The capacity of ecosystem services, such as the amount of carbon stored and sequestered, volume of rainfall intercepted, and amount of pollution removed, relies on the size and vitality of trees, and crown structure and the amount of leaf area is critical in determining expected services (Nowak et al. 2008). On a tree population level, species diversity is central to sustaining a green resource throughout the urban forest and providing resilience to outbreaks of pests and diseases (Vander Vecht and Conway 2015; Sjöman and Östberg 2019). Devastating scenarios featuring a lack of species diversity have been observed throughout the world, with the most notable examples being Dutch elm disease (Ophiostoma novo-ulmi) and emerald ash borer (Agrilus planipennis), both driving the mortality of millions of trees throughout towns and cities worldwide (Bukowski 2018). Research concludes that a greater species diversity will ease future biotic threats and should be incorporated into urban forest and green space management (Smith et al. 2017).

With increasing impacts of climate change on urban landscapes, species will also vary in their response to drought and higher temperatures (Teskey et al. 2014; Choat et al. 2018). Even within the same species, differences in drought tolerance differs between cultivars and tree provenance (Sjöman et al. 2015; Hannus et al. 2020; Hirons et al. 2021). Similarly, the amelioration of urban microclimates can be affected by different species as a result of crown structure and overall tree architecture, as they influence wind speed and wind dispersal in different ways (Konarska et al. 2014; Sjöman et al. 2016). In summer, shading aids the cooling effect by reducing the heat stored and emitted by built structures (Hardin and Jensen 2007); evapotranspiration contributes further to the cooling effect of trees (Rahman et al. 2020; Winbourne et al. 2020). As such, trees help reduce urban temperatures and create microclimates that improve thermal comfort and human health during hot summer days and reduce wind chill effects in winter (Erell et al. 2010; Sawka et al. 2013; Sjöman et al. 2016).

Leaf and Plant Area Index

Leaf area index (LAI) is a measure of plant foliage and often explained as the total area of one side of the leaf tissue (or projected leaf area m2) per unit ground surface area (m2)(Turner et al. 1999). It represents an important attribute of vegetation structure and is regularly used in research concerning photosynthetic activity, energy exchange, carbon sequestration, and water and nutrient use (Bréda 2008). LAI thus applies to ecological monitoring at various scales—from mapping terrestrial biomes and crop yields, to more detailed modeling of how LAI influences rainfall interception and microclimates in urban settings (Gower et al. 1999; Xiao and McPherson 2002; Hardin and Jensen 2007; Venkatraman et al. 2016; Klingberg et al. 2017). As a key variable of terrestrial ecosystem processes, research in climate change designates LAI as an indicator of fluctuation in temperatures and humidity in relation to global warming, land cover change, and human activity (as in Buermann et al. 2001; Jiapaer et al. 2015).

Retrieving LAI with direct methods is an elaborate and destructive task and often involves harvesting the leaves of individual plants (Bréda 2008). Indirect methods include allometric equations by litter collection and canopy spread and indirect non-contact methods of gap-fraction measurement and photosynthetic active radiation (PAR)(Bréda 2008; Vyas et al. 2010; Olivas et al. 2013). In-situ methods for the indirect non-contact approach involve digital imaging technology and hemispheric projections, where the presence of trunks and branches, as well as clustered foliage (clumping), usually display in a captured image (Peper and McPherson 2003; Bréda 2008). The gap-fraction approach does not differentiate photosynthetically active leaf tissue from stem, branches, or flowers, and although the PAR approach targets leaf tissue, post-processing to separate wood structure is generally needed for a true LAI (Jonckheere et al. 2004; Fang et al. 2019; CID Bio-Science, e-mail correspondence, 2021 January 6). Suggestions for alternative terms admitting the presence of stems and trunks have been investigated (as in Jonckheere et al. 2004), and in this article we will refer to plant area index (PAI) when measurements include leaves and woody structure. Attribution to PAI correlates to studies modeling eco-physiological processes and may include evapotranspiration estimations and temporal variation in CO2 exchange of forest stands (Kumagai et al. 2014; Takahashi et al. 2015) or studies concerned with solitary (isolated) trees in urban contexts, where PAI helps influence rainfall interception (Xiao and McPherson 2002) and microclimatic modification (Konarska et al. 2014).

Whilst LAI and PAI measurements for trees are typically appraised for forest stands, orchards, and crop production, estimations of solitary (or isolated) trees in urban landscapes are less studied (Chianucci et al. 2015). Recognized challenges are proximity to nearby built infrastructure, as well as instruments sensitive to reflectance from foliage and changeable light conditions that provide inaccurate rendering (Chianucci et al. 2015; Klingberg et al. 2017). Several studies have investigated the technical challenges of capturing LAI (PAI) and wood area index (WAI) values in urban settings and as such deal with only a handful of tree species (as described in Nowak 1996; Peper and McPherson 2003; Chianucci et al. 2015; Wei et al. 2020).

Wood and Branch Area Index

In contrast to PAI, wood area index (WAI), also referred to as branch area index (BAI), relates to seasons when leaf cover for deciduous trees is absent. Thus, WAI values include branches and trunk only and are relevant to studies concerned with deciduous urban tree cover during wintertime (Kumakura et al. 2011). However, studies of WAI estimation predominantly involve boreal forest architecture (Kucharik et al. 1998), and few studies have been conducted using this index on solitary trees in urban environments (Breuer et al. 2003; Wang et al. 2008). For deciduous trees, WAI becomes an attribute to LAI and PAI with influence on regulating ecosystem services on a yearly basis—for example, shading, wind regulation, and storm water interception (Xiao and McPherson 2002; Gill et al. 2007; Coutts et al. 2016). In urban contexts, where trees often are planted as solitary elements along streets, in courtyards, and in residential areas, contrasting tree species also interact with the surrounding environment in different ways. For example, during winter, wind speed regulation and the interception of solar radiation will vary depending on architectural makeup of trunks and branches (Sjöman et al. 2016). Therefore, structural differences across tree species (and cultivars) can either enhance or detract from thermal comfort in urban microclimates (Nikoofard et al. 2011; Sawka et al. 2013).

In this study, we present the PAI of 63 deciduous broadleaved tree species and 1 deciduous coniferous tree, with a complement of WAI from the broadleaved tree species. The aim was to provide a data resource of PAI and WAI of a large share of solitary-grown broadleaved tree species and cultivars of the same age and in the same growing conditions in order to delineate characteristics and attributes of each individual tree, viewed both in summer (with leaves) and in winter (without leaves), that may be useful for eco-physiological modeling of trees in urban contexts.

MATERIALS AND METHODS

Plant Material

PAI and WAI data of 64 tree species/genotypes were collected at the Hørsholm Arboretum in Denmark (55°52′49″N, 12°30′29″E) in summer when trees were in full leaf and in winter with leaves absent (Figure 1; Table 1). All trees in the study were solitary-grown and non-pruned. Although the Hørsholm Arboretum presents trees subjected to different pruning techniques (Bühler and Kristoffersen 2009), non-pruned trees were chosen to provide an authentic example of different species’ crown architectural characteristics; the intervention from pruning can cause significant alteration to inherent tree characteristics. Only the initial lower branches were cut to allow for maintenance access (i.e., 1.5 m to 2 m clearance height for non-fastigiate trees).

Figure 1.
Figure 1.

Trees at the Hørsholm Arboretum in Denmark in 2019. All trees were planted in 2001.

View this table:
Table 1.

The attributes of all measured trees at the Hørsholm Arboretum in Denmark showing species, year of establishment, trunk diameter at breast height (DBH)(cm), total height of the tree (m), height of canopy (m), and canopy diameter (m).

Plant Area Index Data

For this study, the indirect method based on light attenuation by tree canopies was applied using a Digital Plant Canopy Imager (CI-110; CID Bio-Science, Camas, WA, USA) which captures wide-angle canopy images with a subsequent estimate of LAI (CID Bio-Science 2021). The CI-110 involves a fish-eye camera positioned at the end of a 0.8-m rod connected to a digital touch screen, where hemispheric images of digital projections beneath the tree canopy are processed and adjusted. The CI-110 does not automatically separate the woody portions of a plant from the leaves, and the more appropriate and accurate term for the captured projection is PAI.

The values were based on a one-sided projection of the tree crown within the crown projection area. All trees at the Hørsholm Arboretum were planted as solitary individuals, and no additional objects from adjacent trees, people, cars, etc. were visible in the captured images. All scans were taken on days with full cloud cover to ensure a diffuse light source and eliminate errors due to shifting light conditions. This was established using an exposure meter to provide consequent index values. Four scans of each tree species were taken at three separate field visits during the summer of 2015. At each field visit, each tree was scanned 4 times (south, west, north, and east) 0.5 m away from its trunk and 0.5 m above ground level. Scans were analyzed using the image processing tool provided with the Digital Plant Canopy Imager, and regions outside the crown projection (i.e., with no outer ring of the frame photo area) were excluded from analysis. Four points (north, south, east, and west) were measured on each tree at each field visit, and these values were used to calculate the mean species value. The standard error presented, therefore, represents the variation found within the crown of a single individual. Similar to Peper and McPherson (2003), we found it necessary to use a consistent contrast value for each scan; 100%, brightness to 45%, g at 50%, and an Otsu method threshold value ranging from 69.92% to 72.66% (Otsu 1979).

Wood Area Index Data

Wood area index was retrieved from the same trees in winter using the same method as described above. A complete description of the procedure is provided in Sjöman et al. (2016), where wood area index is referred to as branch area index. The results presented in the following section concerning the WAI data are also referred to in Sjöman et al. (2016) and are used to estimate the LAI results in this paper.

Statistical Analysis

All statistical analysis was conducted using R (R Core Team 2020) and the packages dplyr (Wickham et al. 2020) and ggfortify (Horikoshi and Tang 2018). Figures were produced in R using the package ggplot2 (Wickham 2016). Differences between species were determined using analysis of variance and a post-hoc Tukey’s honest significant difference method.

RESULTS

Plant Area Index

The WAI and PAI show highly significant (P < 0.001) differences between species and genotypes analyzed (Figure 2, Table S1). The WAI had an overall mean of 0.91 (± 0.03), ranging from Tilia platyphyllos ‘Orebro’ with a WAI of 0.32 (± 0.04) to Carpinus betulus ‘Fastigiata’ with a WAI of 1.94 (± 0.09). The lowest mean PAI in the data set is Fraxinus angustifolia ‘Raywood’ with a PAI of 1.93 (± 0.05), whereas Acer campestre ‘Kuglennar’ represents the cultivar with the largest PAI of 8.15 (± 0.14).

Figure 2.
Figure 2.

The plant area index (PAI) and wood area index (WAI) of 64 species of trees. Bars represent the SE of the mean from 4 readings (N, E, S, W) from each crown. The vertical dotted line represents the mean of all the WAI, and the vertical dashed line represents the mean of all the PAI.

When comparing the PAI and WAI of the same trees, large differences in tree crown density between winter and summer can be observed. For example, Tilia platyphyllos ‘Fenris’ has one of the highest mean PAI in the data set (7.34), while it has one of the lowest mean WAI in the data set (0.35)(Figure 2). Notably, the genotypes with dense, rounded tree crowns, such as Acer platanoides ‘Globosum’ and Acer campestre ‘Kuglennar,’ have high mean WAI as well as high mean PAI.

Highly significant (P < 0.001) differences were also found across genotypes represented by 2 or more species in this study (Figure 3; Table S2). Tilia were found to have the most dense crowns, with a mean PAI of 5.85 (± 0.16), and Pyrus the least dense crowns, with a PAI of 2.74 (± 0.19). The results from the analysis of cultivars within a single species also indicate that significant differences (P < 0.05) occur between genotypes (Figure 4). For example, among the genotypes of the species Acer platanoides and Acer pseudoplatanus analyzed, the mean PAI ranged from 4.93 to 7.02 and 4.07 to 5.52, respectively.

Figure 3.
Figure 3.

The plant area index (PAI) and wood area index (WAI) of 8 genera that were represented by 2 or more species at the arboretum. Bars represent the SE of the mean. The vertical dotted line represents the mean of all the WAI, and the vertical dashed line represents the mean of all the PAI. Numbers in [x] indicate the number of species within this analysis represented in the genera. Uppercase letters indicate where significant differences (P < 0.05) occur between the WAI of genera. Lowercase letters indicate where significant differences occur between the PAI of genera.

Figure 4.
Figure 4.

The plant area index (PAI) and wood area index (WAI) of cultivars represented by Acer and Tilia, grouped by species. Bars represent the SE of the mean from 4 readings (N, E, S, W) from each crown. Uppercase letters indicate where significant differences (P < 0.05) occur between the WAI of the cultivars within the species panel. Lowercase letters indicate where significant differences occur between the PAI of the cultivars within the species panel.

DISCUSSION

The PAI and WAI results presented in this paper are obtained from 64 tree species/genotypes grown as solitary trees at the Hørsholm Arboretum, Denmark. As examined in several research papers, retrieving a true leaf area index of solitary trees is complicated due to the intrusion of woody material (occlusion), the effect of leaf clumping, leaf angle, and contours of leaves (Bréda 2008; Jensen et al. 2012; Wei et al. 2020). Subsequent post-processing subtraction of non-leaf obstacles may still not acknowledge leaf clumping (Wang and Fang 2020; Wei et al. 2020). In this respect, and due to the architectural structures of different tree species where woody material plays a role to climate adaptive design, we have chosen to measure the entire plant index, in summer and in winter.

The PAI and WAI captured from the trees at the Hørsholm Arboretum provide a snapshot of these attributes given the location and time of the study. The results should be viewed in respect of the context of (1) trees established and growing in favorable park conditions, i.e., not dry habitats of impermeable innercity environments (Sjöman et al. 2010); and (2) trees at a fairly young age, i.e., the presented estimations are likely to change with time, where leaf area index in particular will tend to decline with age (Nock et al. 2008). Further, the study only included one individual of each species and genotype, which in turn cannot render a full picture of consistent differences between species and/or genotypes. In most arboretums, such as the Hørsholm Arboretum or botanical collections, only one or two individuals of each species may exist, since the main interest is to display a variety of different tree species (Hirons et al. 2021). One possible route around this complexity is to study trees in nurseries, where more than one individual of the same species/genotype is available. However, trees in nurseries are most likely pruned to comply with production standards, which in turn affects the true characteristic of the tree species/genotype. For this study, we acknowledge the limitation of comparing species based on one individual but recognize the value in comparing a wide range of species that have been established in a consistent environment at the Hørsholm Arboretum. The application of statistical analysis provides an indication of the crown architectural differences between species.

Although some genera, species, and genotypes demonstrate higher PAI in this data resource, this estimation may well decrease if such trees are particularly sensitive and susceptible to water stress and lose foliage (Sjöman et al. 2018). In this case, many of the Tilia and Acer species that have high PAI, with measures above the overall mean of 4.6 (± 0.20), are sensitive to water stress (i.e., Tilia cordata ‘Erecta,’ Acer pseudoplatanus ‘Negenia,’ Acer pseudoplatanus ‘Rotterdam,’ Acer pseudoplatanus, Tilia × europaea ‘Pallida,’ and Tilia cordata)(Sjöman et al. 2015, 2018). Although a high leaf area defines higher photosynthetic capacities, some specimen may well exhibit decreased leaf mass and leaf abscission when exposed to water stress. At the same time, species with a moderate to low PAI may well indicate greater resilience to water stress, with the likelihood of retaining leaf cover throughout the season (i.e., Acer campestre, Quercus palustris, Quercus frainetto, and Fraxinus ornus)(Sjöman et al. 2015, 2018). By including a wide range of species and genotypes in this study, we hope to support the continuing discussion around how increased species diversity can enhance the performance and resilience of urban tree populations. Furthermore, these data contribute to a critical discourse that quantitatively distinguishes between different genera, species, and genotypes.

The results show that when estimations of PAI and WAI were made for solitary trees at the Hørsholm Arboretum, the metrics differed widely at genus, species, and genotypic levels. Critically, the differences observed across species reflect the integrated effects of leaf material and the wood component of tree crowns. Understanding this variation gives planners, urban designers, and landscape architects opportunities to recognize how architectural structure and attributes of trees change over the year and how this variation may also occur at a genotypic level. On a local level and with place-specific attention to climate responsive design and ecosystem services, the interaction between trees and surrounding objects and materials plays a considerable role (Erell et al. 2010; Sawka et al. 2013). The positioning of trees in approximation to buildings, seating areas, playgrounds, etc. can provide different services and benefits regarding shading and wind attenuation (Sjöman et al. 2016). Similar interpretations can be made with regards to interception and to ground cover characteristics beneath and adjacent trees, appreciating a higher interception in trees with high PAI and WAI with potential to mitigate high runoff from impermeable surfaces (Xiao and McPherson 2002).

Acknowledging the entire structural characteristic of the tree and not only the leaf area helps develop a fuller picture of what can be expected from a particular tree species at a particular time of year in a particular spatial context. Species such as Tilia platyphyllos have sparse crowns (low WAI) during winter, yet dense crowns during summer. These characteristics make them favorable in cooler climates, as the crowns will intercept a relatively small proportion of solar radiation in winter—thus allowing additional microclimate warming—whilst in summer, the dense leaf material (LAIp) acts to provide substantial shade and thus microclimate cooling. Understanding the differences between the PAI, WAI, and the LAIp gives planners opportunities to specify trees that are most likely to improve thermal comfort, whether that be from cold winter winds (high WAI preferred), summer heat (high PAI preferred), or in situations where winter solar radiation is appreciated, but shade is required in summer (high LAIp preferred). To convert the two-dimensional measures of PAI and WAI into three-dimensional attributes of leaf area density (LAD) or wood area density (WAD), further investigations of individual trees are needed, as this varies with location in the crown (Wei et al. 2020). However, the results from this study can be used in microclimate studies and modeling where plant and wood area index of solitary-grown trees in urban contexts are of interest.

ACKNOWLEDGMENTS

The study presented in this paper was supported by the ISA Jack Kimmel International Grant and the Sweden-American Foundation. The authors would also like to thank Oliver Bühler at Copenhagen University in Denmark for access to the Hørsholm Urban Tree Arboretum, and Ann-Mari Fransson at the Swedish University of Agricultural Sciences for kindly lending the Digital Plant Canopy Imager (CI-110).

Appendix

View this table:
Table S1.

PAI and WAI for species and cultivars.

View this table:
Table S2.

PAI and WAI for genus.

Footnotes

  • Conflicts of Interest:

    The authors reported no conflicts of interest.

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Plant and Wood Area Index of Solitary Trees for Urban Contexts in Nordic Cities
Johanna Deak Sjöman, Andrew Hirons, Nina Bassuk, Henrik Sjöman
Arboriculture & Urban Forestry (AUF) Nov 2021, 47 (6) 252-266; DOI: 10.48044/jauf.2021.022
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