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Research ArticleArticles

Using the CSR Theory when Selecting Woody Plants for Urban Forests: Evaluation of 342 Trees and Shrubs

Henrik Sjöman, Andrew Hirons and Harry Watkins
Arboriculture & Urban Forestry (AUF) July 2025, 51 (4) 329-354; DOI: https://doi.org/10.48044/jauf.2025.014
Henrik Sjöman
Swedish University of Agricultural Science, Department of Landscape Architecture, 8 Planning and Management, Alnarp, Sweden, Gothenburg Botanical Garden, Carl Skottsbergsgata 22A, Gothenburg Global Biodiversity Centre, Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden, Royal Botanic Gardens, Kew, Richmond, United Kingdom
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Andrew Hirons
University Centre Myerscough, Bilsborrow, Preston, Lancashire, United Kingdom
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Harry Watkins
St. Andrews Botanic Garden, Canongate, St Andrews, Fife, Bartlett School of Architecture, Queen Elizabeth Olympic Park, London, United Kingdom
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  • Figure 1.
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    Figure 1.

    The hypothetical trait-based scheme for urban foresters, as presented by Watkins et al. (2021), builds upon the competitorstress tolerator-ruderal (CSR) theory. It demonstrates the diversity of viable plant strategies, which are characterised by a trade-off between fast growth and high tolerance of stress. This allows for the identification of tree species that are well-suited to urban forestry sites. (A) Positions A and C represent the 2 extremes of the trade-off between competitive and stress-tolerant strategies, with position B representing a generalist strategy. In disturbed environments, a greater investment in reproduction and faster growth is required, resulting in more ruderal strategies (Position D). In more stressful situations, delayed sexual maturity allows for greater investment in dense structural and photosynthetic tissues (Position E). It should be noted that, in contrast to other similar graphs, the trait trade-off is fitted by a quadratic rather than a linear line of best fit. (B) Overlays environments found in urban forests upon this model, resulting in a method for identifying the most suitable tree species for urban forestry sites.

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    Figure 2.

    Ordination of trees and shrubs growing in Alnarp, showing the different evolutionary strategies of each life form classifying plants according to 3 principal strategies (Competitors [C], Stress tolerators [S], Ruderal [R]), which represent a spectrum of plant forms and functions arising under conditions of competition, abiotic restriction to growth, or periodic disturbance, respectively. In this assessment, the study taxa of trees and shrubs were distributed along the Competitor-Stress tolerator (CS) axis of the ternary plots. It indicates that long-lived organisms such as trees have a limited tolerance to recurrent disturbances with extensive biomass losses, while this tolerance is somewhat higher in shrubs concerning disturbance, showing that shrubs have a more general approach to disturbance as well as competition and stress (CSR) compared with trees.

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    Figure 3.

    Ordination of trees growing in Alnarp, with examples of species within the different sections of the model according to 3 principal strategies (Competitors [C], Stress tolerators [S], Ruderal [R]) which represent a spectrum of plant forms and functions arising under conditions of competition, abiotic restriction to growth, or periodic disturbance, respectively. This shows a clear concentration of CS strategists with a relatively high tolerance to stress (resource constrained conditions) with a relatively good growth rate. Among the species that are more pronounced C-strategists, there are several pioneer species from resource-rich habitats, while pronounced S-strategists originate from resource-limited habitats such as warm and dry environments to shade late successional phases in forest environments.

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    Figure 4.

    Ordination of shrubs, growing in Alnarp, classifying them according to 3 principal strategies (Competitors [C], Stress tolerators [S], Ruderal [R]), which represent a spectrum of plant forms and functions arising under conditions of competition, abiotic restriction to growth, or periodic disturbance, respectively. This shows a broader spectrum of strategies with the exception of pronounced C-strategies compared to trees. Due to the limited ability of shrubs to compete with trees for sunlight, many species have developed characteristics to cope with more extreme conditions such as hot and dry sites or as undergrowth in mature forest environments, resulting in a large proportion of specialists and thus a large proportion of S-strategists.

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    Figure 5.

    The S-C axis in variation, overlaid with hypothesised fitness in urban environments, where position A relates to situations with high resource availability and low disturbance (e.g., swale bottoms or parks); position B relates to plants with generalist that have a relatively wide range of adaptive capacity; position C relates to plants that are well fitted to high stress environments such as paved areas or sites prone to drought; and position D relates to plants with a higher degree of adaptation to disturbed sites, making them more suitable for pioneer roles within new plant assemblages (S = logC2 + logC – 76.13 [1]; S = logC2 + logC – 104.65 [2]).

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    Figure 6.

    Species originating naturally from resource-rich habitats have developed unique traits with a rapid turnover in growth to create a competitive advantage (C-strategy), traits that they retain in cultivation as they establish and grow rapidly in resource-rich environments such as parks and gardens. Species originating from resource-limited habitats have a slower turnover in growth due to limited resources (S-strategy), a characteristic they also have in cultivation, even on resource-rich habitats, resulting in significantly slower establishment and growth. Figure developed with inspiration from Chapin (1980) and Laughlin (2023).

Tables

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    Table S1.

    Compilation of the CSR classification of the studied shrubs, where the calculated percentage for each category is presented in % (using one decimal), with a subsequent final classification using the StrateFy tool (Pierce et al. 2017).

    Species (Shrubs)C (%)S (%)R (%)Strategy
    Acer pensylvanicum56.528.814.7C/CSR
    Actinidia deliciosa67.532.50.0C/CS
    Aesculus parviflora47.625.127.3C/CSR
    Amelanchier alnifolia21.868.110.1S/CS
    Amelanchier laevis23.161.715.2S/CSR
    Amelanchier × lamarckii27.464.48.2S/CS
    Amelanchier × spicata21.461.517.1S/CSR
    Aristolochia macrophylla68.413.717.9C/CR
    Aronia melanocarpa30.669.40.0S/CS
    Berberis julianae11.388.70.0S
    Berberis thunbergii11.688.40.0S
    Berberis verruculosa5.694.40.0S
    Berberis × frikartii6.393.70.0S
    Buddleja davidii42.929.727.4CSR
    Buxus sempervirens16.483.60.0S/CS
    Caragana arborescens8.155.336.6SR
    Chaenomeles japonica13.386.70.0S
    Cornus alba33.243.423.3CS/CSR
    Cornus mas30.150.719.1S/CSR
    Cornus racemosa24.958.117.0S/CSR
    Cornus racemosa ‘Green Carpet’24.575.50.0S/CS
    Cornus sanguinea31.940.227.8CSR
    Cornus sericea28.571.20.4S/CS
    Cornus sericea ‘Bailadeline’ Firedance™19.373.37.4S/CS
    Cornus sericea ‘Baileyi’29.664.85.6S/CS
    Corylus avellana37.245.317.5CS/CSR
    Corylus maxima ‘Cosford’41.037.021.9CS/CSR
    Corylus maxima ‘Nottingham’42.727.529.8CSR
    Corylus maxima ‘Purpurea’45.727.127.2C/CSR
    Cotinus coggygria33.152.214.7S/CSR
    Cotinus coggygria26.366.86.9S/CS
    Cotoneaster apiculatus9.575.814.6S/SR
    Cotoneaster dammeri11.988.10.0S
    Cotoneaster dielsianus9.784.65.7S
    Cotoneaster divaricatus8.191.90.0S
    Cotoneaster lucidus21.358.120.6S/CSR
    Cotoneaster multiflorus17.572.210.2S/CS
    Cotoneaster splendens7.187.35.6S
    Cotoneaster × suecicus8.282.39.4S
    Crataegus laevigata19.760.819.5S/CSR
    Crataegus monogyna20.873.06.2S/CS
    Crataegus rhipidophylla19.968.511.6S/CS
    Daphne mezerum25.426.248.3R/CSR
    Decaisnea fargesii28.526.245.3R/CSR
    Deutzia gracilis15.085.00.0S
    Deutzia scabra32.551.116.5S/CSR
    Diervilla lonicera23.976.10.0S/CS
    Diervilla lonicera ‘Dilon’52.137.210.6CS
    Diervilla sessilifolia36.363.70.0S/CS
    Enkianthus companulatus18.736.045.2SR/CSR
    Euonymus alatus14.385.70.0S
    Euonymus europaeus27.755.017.3S/CSR
    Euonymus fortunei ‘Emerald Gaiety’28.458.713.0S/CSR
    Euonymus fortunei ‘Emerald ‘n’ Gold’26.669.43.9S/CS
    Euonymus fortunei ‘Silver Queen’22.277.80.0S/CS
    Euonymus fortunei var. radicans25.872.81.5S/CS
    Euonymus fortunei var. vegetus52.213.034.7CR/CSR
    Euonymus planipes37.945.316.8CS/CSR
    Forsythia ‘Lowe Tide’18.681.40.0S/CS
    Forsythia mandshurica49.639.311.1CS/CSR
    Forsythia ‘Maree d’Or’™17.778.34.0S/CS
    Forsythia intermedia24.675.40.0S/CS
    Forsythia × intermedia ‘Goldzauber’41.834.224.0CS/CSR
    Fothergilla major40.847.911.4CS/CSR
    Hamamelis virginiana40.441.218.3CS/CSR
    Hamamelis × intermedia39.045.715.4CS/CSR
    Hedera colchica55.045.00.0CS
    Hedera helix44.045.510.5CS
    Hippophaë rhamnoides19.578.52.0S/CS
    Hydrangea arborescens46.946.66.5CS
    Hydrangea macrophylla65.125.29.6C/CS
    Hydrangea petiolaris48.650.31.1CS
    Hydrangea serrata52.244.23.6CS
    Hypericum kalmianum ‘Ames’11.676.911.5S/CS
    Hypericum kalmianum ‘Gemo’8.779.511.8S
    Ilex aquifolium ‘Alaska’25.174.90.0S/CS
    Ilex aquifolium ‘J.C. van Tol’32.267.80.0S/CS
    Ilex crenata ‘Blondie’15.484.60.0S
    Ilex crenata ‘Dark Green’4.295.80.0S
    Ilex verticillata31.961.36.7S/CS
    Kolkwitzia amabilis25.852.122.2S/CSR
    Laburnum alpinum25.337.537.3CSR
    Laburnum anagyroides23.954.721.5S/CSR
    Ligustrum vulgare14.379.66.0S/CS
    Lonicera caerulea24.057.518.5S/CSR
    Lonicera caerulea var. kamtschatica20.879.20.0S/CS
    Lonicera involucrata34.150.115.9CS/CSR
    Lonicera maackii25.762.611.7S/CS
    Lonicera nitida9.887.13.1S
    Lonicera periclymenum35.932.631.5CSR
    Lonicera tatarica28.054.817.2S/CSR
    Lonicera xylosteum26.254.019.7S/CSR
    Lonicera xylosteum ‘Compacta’23.665.710.7S/CS
    Magnolia ‘Wada’s Memory’32.945.122.0CS/CSR
    Magnolia × soulangeana53.834.212.0CS/CSR
    Mahonia aquilifolium28.563.28.2S/CS
    Malus toringo var. sargentii34.265.80.0S/CS
    Philadelphus coronarius30.146.223.7S/CSR
    Physocarpus opulifolius28.452.818.8S/CSR
    Pieris floribunda20.273.76.1S/CS
    Pieris japonica19.280.80.0S/CS
    Pinus mugo var. pumilio3.196.90.0S
    Potentilla fruticosa5.983.210.9S
    Prunus cerasifera23.060.616.4S/CSR
    Prunus laurocerasus ‘Mano’48.049.62.4CS
    Prunus laurocerasus ‘Otto Luyken’39.560.50.0CS
    Prunus laurocerasus ‘Piri’35.364.70.0S/CS
    Prunus pumila var. depressa21.278.80.0S/CS
    Prunus spinosa16.971.012.1S/CS
    Pyracantha ‘Anatolia’10.789.30.0S
    Pyracantha coccinea ‘Red Cushion’10.889.20.0S
    Rhamnus catharticus29.339.531.2CSR
    Rhododendron brachycarpum38.761.30.0CS
    Rhododendron ‘Catawbiense Album’38.062.00.0CS
    Rhododendron catawbiense ‘Boursalt’41.652.06.3CS
    Rhododendron ‘Catawbiense Grandiflora’37.862.20.0CS
    Rhododendron luteum35.646.617.8CS/CSR
    Rhododendron mucronulatum22.958.218.9S/CSR
    Rhododendron ‘Rosa Wolke’33.666.40.0S/CS
    Rhododendron ‘Roseum Elegans’42.446.411.2CS/CSR
    Rhus aromatica19.180.90.0S/CS
    Rhus typhina26.853.819.4S/CSR
    Ribes alpinum18.261.620.2S/CSR
    Ribes alpinum ‘Compacta’11.588.50.0S
    Ribes glandulosum23.276.80.0S/CS
    Rosa dumalis14.172.013.8S/CS
    Rosa majalis17.265.217.6S/CSR
    Rosa pimpinellifolia20.765.314.0S/CS
    Rosa rubiginosa10.672.017.4S/SR
    Rosa rugosa18.881.20.0S/CS
    Salix caprea41.648.110.3CS
    Salix lanata ‘Hjeltnes’38.161.90.0CS
    Salix lanata ‘Nitida’6.888.54.7S
    Salix repens6.785.67.7S
    Salix × purpurea9.081.29.8S
    Sambucus nigra38.213.648.2CR/CSR
    Sorbaria sorbifolia17.148.834.1SR/CSR
    Spiraea betulifolia22.474.82.8S/CS
    Spiraea fritschiana21.178.80.1S/CS
    Spiraea japonica24.155.620.3S/CSR
    Spiraea miyabei23.276.80.0S/CS
    Spiraea nipponica8.472.519.2S/SR
    Spiraea trilobata14.378.77.0S/CS
    Spiraea × cinerea5.975.618.5S/SR
    Spiraea × cinerea ‘Grefsheim’6.271.822.0S/SR
    Stephanandra incisa16.849.733.5SR/CSR
    Stephanandra tanake28.462.78.9S/CS
    Symphoricarpos ‘Arvid’ E.18.969.911.2S/CS
    Symphoricarpos ‘Magical Galaxy’9.883.07.2S
    Symphoricarpos orbiculatus10.289.80.0S
    Syringa josikaea46.433.420.3CS/CSR
    Syringa meyeri ‘Palibin’20.950.928.2S/CSR
    Syringa microphylla ‘Superba’27.863.98.3S/CS
    Syringa patula30.158.911.0S/CSR
    Syringa reflexa43.640.915.5CS/CSR
    Syringa reticulata47.640.911.5CS/CSR
    Syringa vulgaris43.449.07.6CS
    Syringa × chinensis32.345.322.4CS/CSR
    Taxus baccata3.496.60.0S
    Taxus cuspidata2.897.20.0S
    Viburnum carlesii33.266.80.0S/CS
    Viburnum ferreri35.549.015.5CS/CSR
    Viburnum lantana36.254.89.0CS
    Viburnum opulus39.840.120.1CS/CSR
    Viburnum plicatum f. tomentosum38.055.76.3CS
    Viburnum rhytidophyllum52.847.20.0CS
    Viburnum sargentii33.350.416.3CS/CSR
    Viburnum × bodnantense46.035.718.4CS/CSR
    Viburnum × burkwoodii38.961.10.0CS
    Vinca minor12.287.80.0S
    Weigela × hybrida39.960.10.0CS
    Wisteria sinensis19.561.818.7S/CSR
    • View popup
    Table S2.

    Compilation of the CSR classification of the studied trees, where the calculated percentage for each category is presented in % (using one decimal), with a subsequent final classification using the StrateFy tool (Pierce et al. 2017).

    Species (Trees)C (%)S (%)R (%)Strategy
    Abies alba1.998.10.0S
    Abies homolepis1.498.60.0S
    Abies nordmanniana2.098.00.0S
    Abies pinsapo1.198.90.0S
    Acer campestre36.554.78.8CS
    Acer davidii43.549.96.7CS
    Acer miyabei35.362.12.6S/CS
    Acer monspessulanum22.469.58.1S/CS
    Acer negundo51.243.25.6CS
    Acer nigrum51.944.14.0CS
    Acer palmatum38.228.733.1CSR
    Acer platanoides56.640.23.2CS
    Acer pseudoplatanus66.831.12.2C/CS
    Acer pseudosieboldianum36.252.811.1CS/CSR
    Acer rubrum43.550.75.8CS
    Acer saccharinum41.152.96.0CS
    Acer saccharum50.245.93.9CS
    Acer spicatum50.137.412.4CS/CSR
    Acer tataricum32.163.44.5S/CS
    Acer × zoeschense38.062.00.0CS
    Alnus glutinosa42.848.88.4CS
    Alnus incana38.753.87.5CS
    Alnus rubra44.652.82.7CS
    Alnus sinuata41.255.63.1CS
    Alnus subcordata53.239.96.8CS
    Alnus × spaethii45.550.93.6CS
    Amelanchier lamarckii25.268.06.8S/CS
    Betula albosinensis36.452.411.2CS/CSR
    Betula alleghaniensis38.353.28.5CS
    Betula pendula27.761.710.6S/CS
    Betula populifolia30.367.52.2S/CS
    Broussonetia papyrifera59.737.13.2CS
    Buxus sempervirens ‘Rotundifolia’17.282.80.0S/CS
    Carpinus betulus33.952.713.4CS/CSR
    Carpinus caroliniana30.063.66.4S/CS
    Carpinus fargesii29.161.89.1S/CS
    Carpinus orientalis13.976.110.0S/CS
    Carpinus turczaninowii19.977.52.7S/CS
    Carya cordiformis66.333.40.3C/CS
    Carya ovata71.428.60.0C/CS
    Carya tomentosa71.128.90.0C/CS
    Castanea sativa49.043.87.2CS
    Catalpa speciosa71.724.63.7C/CS
    Celtis occidentalis36.156.27.7CS
    Cercidiphyllum japonicum36.047.116.9CS/CSR
    Cladrastis kentukea63.127.49.5C/CS
    Cornus florida41.144.414.5CS/CSR
    Cornus kousa40.153.06.9CS
    Cornus mas34.856.19.1CS
    Corylus avellana44.044.411.7CS/CSR
    Corylus chinense48.646.55.0CS
    Corylus colurna50.145.54.4CS
    Corylus ferox43.049.97.1CS
    Cotinus coggygria30.468.51.1S/CS
    Crataegus monogyna30.269.80.0S/CS
    Davidia involucrata57.734.18.2CS
    Elaeagnus angustifolia22.673.44.0S/CS
    Eucommia ulmoides49.045.15.8CS
    Fagus orientalis37.044.618.4CS/CSR
    Fagus sylvatica35.457.37.3CS
    Fraxinus americana ‘Autumn Purple’64.629.65.8C/CS
    Fraxinus excelsior67.229.13.7C/CS
    Fraxinus fallax69.028.92.1C/CS
    Ginkgo biloba47.136.316.6CS/CSR
    Gleditsia triacanthos45.354.50.3CS
    Gymnocladus dioicus76.117.46.5C/CS
    Hippophae rhamnoides14.285.80.0S
    Ilex aquifolium29.870.20.0S/CS
    Juglans cinerea73.224.72.2C/CS
    Juglans nigra72.023.54.5C/CS
    Juglans regia75.624.40.0C/CS
    Koelreuteria paniculata62.035.82.2C/CS
    Laburnum angyroides42.442.415.2CS/CSR
    Larix × eurolepis0.0100.00.0S
    Liquidambar styraciflua45.750.43.9CS
    Liriodendron tulipifera64.425.89.8C/CS
    Magnolia biondii48.746.74.6CS
    Magnolia kobus44.446.49.1CS
    Magnolia obovata73.919.56.6C/CS
    Magnolia sprengeri56.343.20.5CS
    Magnolia × loebneri41.049.59.5CS
    Malus domestica46.052.31.7CS
    Malus sylvestris39.559.31.2CS
    Metasequoia glyptostroboides37.662.40.0CS
    Morus alba60.634.15.3C/CS
    Morus nigra61.728.49.9C/CS
    Nothofagus antarctica10.781.87.4S
    Nyssa sylvatica32.858.88.4S/CS
    Ostrya carpinifolia31.858.39.9S/CSR
    Ostrya virginiana35.153.511.4CS/CSR
    Picea abies0.0100.00.0S
    Picea omorika0.0100.00.0S
    Picea orientalis0.0100.00.0S
    Picea peuce3.396.70.0S
    Picea sitchensis0.0100.00.0S
    Pinus koraiensis4.395.70.0S
    Pinus leucodermis5.294.80.0S
    Pinus sylvestris3.796.30.0S
    Pinus × schwerinii5.494.60.0S
    Platanus × hispanica59.537.13.4CS
    Populus alba ‘Nivea’34.165.20.7S/CS
    Populus balsamifera51.541.67.0CS
    Populus lasiocarpa74.123.92.0C/CS
    Populus nigra ‘Italica’36.563.50.0S/CS
    Populus purdomii55.444.60.0CS
    Populus tremula35.654.89.6CS
    Populus × canadensis ‘Robusta’49.051.00.0CS
    Populus × wettsteinii38.955.55.7CS
    Prunus avium45.545.59.0CS
    Prunus cerasifera31.359.79.1S/CS
    Prunus laurocerasus36.064.00.0S/CS
    Prunus padus37.354.87.9CS
    Prunus sargentii45.247.47.4CS
    Prunus serotina33.258.48.4S/CS
    Prunus spinosa20.273.95.9S/CS
    Pterocarya fraxinifolia73.323.92.8C/CS
    Pterocarya insignis75.721.42.9C/CS
    Pterocarya rhoifolia71.422.75.9C/CS
    Pyrus communis32.064.04.1S/CS
    Pyrus ussuriensis31.657.111.3S/CSR
    Quercus coccinea48.251.80.0CS
    Quercus cerris36.955.87.3CS
    Quercus coccínea47.551.31.2CS
    Quercus dentata ‘Carl Ferris Miller’60.339.70.0CS
    Quercus frainetto41.954.14.0CS
    Quercus macrocarpa52.347.70.0CS
    Quercus petraea43.653.62.8CS
    Quercus prinus51.747.11.3CS
    Quercus robur44.355.10.6CS
    Quercus rubra55.040.74.3CS
    Rhododendron ‘Catawbiense Grandiflorum’43.156.90.0CS
    Rhododendron mucronulatum20.368.910.8S/CS
    Rhus typhina68.727.73.5C/CS
    Robinia pseudoacacia47.444.77.9CS
    Salix alba19.872.67.6S/CS
    Salix alba var. sericea26.272.11.6S/CS
    Salix caprea39.455.45.2CS
    Salix pentandra36.763.30.0S/CS
    Salix viminalis27.271.11.7S/CS
    Salix × fragilis29.957.812.3S/CSR
    Salix × sepulcralis ‘Chrysocoma’25.772.12.2S/CS
    Sambucus nigra66.617.416.0C/CS
    Sorbus aucuparia55.041.33.7CS
    Sorbus hupehensis50.949.10.0CS
    Sorbus intermedia41.258.80.0CS
    Sorbus torminalis44.155.90.0CS
    Sorbus ulleungensis64.036.00.0C/CS
    Styphnolobium japonicum56.533.69.9C/CSR
    Syringa reticulata40.859.20.0CS
    Syringa vulgaris51.848.20.0CS
    Taxodium distichum27.666.46.0S/CS
    Taxus baccata2.597.50.0S
    Taxus cuspidata3.097.00.0S
    Tetracentron sinense37.844.018.2CS/CSR
    Tetradium danielii69.530.50.0C/CS
    Tilia cordata45.046.58.5CS
    Tilia mongolica41.351.47.3CS
    Tilia platyphyllos44.748.76.6CS
    Tilia tomentosa52.042.25.8CS
    Tilia × europaea ‘Zwarte Linde’43.044.312.7CS/CSR
    Toona sinensis74.425.60.0C/CS
    Tsuga canadensis0.0100.00.0S
    Tsuga caroliniana0.499.60.0S
    Tsuga heterophylla0.399.70.0S
    Tsuga mertseniana0.299.80.0S
    Ulmus glabra51.442.85.9CS
    Ulmus glaucescens29.970.10.0S/CS
    Wisteria sinensis54.934.710.4CS
    Zelkova schneideriana30.669.40.0S/CS
    Zelkova serrata33.362.14.6S/CS
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Arboriculture & Urban Forestry: 51 (4)
Arboriculture & Urban Forestry (AUF)
Vol. 51, Issue 4
July 2025
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Using the CSR Theory when Selecting Woody Plants for Urban Forests: Evaluation of 342 Trees and Shrubs
Henrik Sjöman, Andrew Hirons, Harry Watkins
Arboriculture & Urban Forestry (AUF) Jul 2025, 51 (4) 329-354; DOI: 10.48044/jauf.2025.014

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Using the CSR Theory when Selecting Woody Plants for Urban Forests: Evaluation of 342 Trees and Shrubs
Henrik Sjöman, Andrew Hirons, Harry Watkins
Arboriculture & Urban Forestry (AUF) Jul 2025, 51 (4) 329-354; DOI: 10.48044/jauf.2025.014
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Keywords

  • Climate Change
  • Diversity
  • Plant Selection
  • Urban Environments

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