Advertisement

Vulnerability of ten major Nordic cities to potential tree losses caused by longhorned beetles

  • Henrik SjömanEmail author
  • Johan Östberg
Open Access
Article

Abstract

Urban forest and urban trees are currently facing several challenges arising from a changing climate, complex inner-city environments and severe threats of pathogen and insect attacks. The latter have already had serious consequences for many cities, with outbreaks of diseases and pests causing large-scale tree losses that will take a long time to resolve. The pest species Asian longhorned beetle (Anoplophora glabripennis) and citrus longhorned beetle (A. chinensis) have large numbers of host species and genera and can hence be classified as one of the most serious future threats to the urban (and natural) tree landscape. The question is not whether these new threats will arrive in northern Europe, but rather when an infestation will occur and how well prepared are cities to deal with it. This study presents an up-to-date compilation of the urban tree population in 10 major Nordic cities, based on recent tree inventories, and investigates and discusses the effects of an outbreak of the two longhorned beetle species, based on information taken from a review of 35 papers presenting host-related data on these species. Evaluation of the data on host susceptibility to the two longhorned beetles revealed clear differences in tree losses between scenarios, with predicted tree losses of 15–98% in the different cities.

Keywords

Urban trees Urban forest Diversity, tree loss scenario Asian longhorned beetles 

Introduction

Recent research clearly shows the importance of urban trees for sustainable urban development through their capacity for delivering numerous important ecosystem services. These include provisioning services (e.g. fuel and food), regulating services (e.g. stormwater management, urban heat island mitigation, air pollution regulation), cultural services (e.g. recreation, physical and mental health benefits) and supporting services (e.g. wildlife habitats) (Costanza et al. 1997; Akbari et al. 2001; Grahn and Stigsdotter 2003; Tyrväinen et al. 2005; Gill et al. 2007; Morgenroth et al. 2016). Since large healthy trees have the greatest capacity to deliver these services (Xiao and McPherson 2002; Gratani and Varone 2006; Gómez-Muñoz et al. 2010), maintenance of existing trees and planning for future tree plantings are critically important in order to utilise the full scope of potential ecosystem services.

However, urban forest and urban trees are currently facing a number of challenges arising from a changing climate, complex inner-city environments with locally tough site situations and severe threats of pathogen and insect attacks (Sjöman et al. 2012). The latter have already had serious consequences for many cities, with outbreaks of pathogens and pests causing large-scale tree losses that will take a long time to resolve. For example, in Europe and North America, the elm (Ulmus spp.) was one of the most common urban trees until Dutch elm disease, caused by Ophiostoma novo-ulmi, was introduced to the two continents and killed millions of trees in urban environments and in natural habitats (Sinclair and Lyon 2005). This has resulted in cities losing a large proportion of their tree canopy, which will take a long time to recover to the point it was at before the outbreak of Dutch elm disease. Today, Europe is experiencing a similar scenario with Ceratocystis platani on plane trees (Platanus spp.), where infected trees are reported to die within 3–7 years (Forestry Commission 2017). With this in mind and considering the fact that London plane (Platanus x hispanica) is one of the most common urban trees in southern and central Europe (Saebo et al., 2005), another devastating scenario of large tree losses in many cities is possible in coming years. However, these two examples of pathogens are at least limited to a specific tree genus, while insect pests such as Asian longhorned beetle (Anoplophora glabripennis, ALB) and citrus longhorned beetle (A. chinensis, CLB) have large numbers of host species and genera and can hence be classified as one of the most serious future threats to the urban (and natural) tree landscape (Sjöman et al. 2014).

Well-known hosts of ALB in China include species of Acer, Alnus, Betula, Eleagnus, Fraxinus, Malus, Platanus, Populus, Pyrus, Salix, Styphnolobium and Ulmus (Haack et al. 2010; Sjöman et al. 2014). In the United States, ALB has been reported to complete its development on species within the genera Acer, Betula, Fraxinus, Pyrus, Salix and Ulmus, and also in species of Robinia (Haack et al. 2010). Thus, this beetle is expanding its host range as it invades new territories and encounters new potential host species, with devastating biological and economic consequences. For example, Nowak et al. (2001) used tree inventories to estimate potential monetary losses resulting from ALB in nine cities in the United States and reported an estimated loss of approximately 1.2 billion trees, at a compensatory value of USD $669 billion.

With intense global trading, the spread of new pathogens and pests, such as longhorned beetle, is very fast. Therefore, the question now is not whether these new threats will arrive in northern Europe, but rather when an infestation will occur and how well prepared cities are to deal with it. To fight pests such as the longhorned beetle, providing a large diversity of tree species and genera is argued to be one of the most important solutions (Nitoslawski et al. 2016). However, tree diversity data from across the northern hemisphere indicate that species diversity is very limited, with few species comprising the majority of the tree population, particularly in paved and street environments (e.g. Raupp et al. 2006; Yang et al. 2012; Cowett and Bassuk 2014; McPherson et al. 2016). Therefore, in long-term planning of the urban treescape it is important to evaluate possible losses of existing trees and to consider which future tree species and genera run the lowest risk of being attacked by these two wood-boring pests.

The objective of the present study was to prepare an up-to-date compilation of the urban tree population in 10 major Nordic cities, based on recent tree inventories, and to investigate the potential impact of large-scale outbreaks of ALB and CLB in those cities, based on published host tree information. A second objective was to identify future research directions in the field of urban tree diversity that could reduce the effects of an outbreak of ALB or CLB in urban environments.

Materials and methods

Tree inventories

The analysis of tree diversity was based on urban tree databases obtained from 10 Nordic cities. Many cities in the Nordic region outsource the maintenance of public greenery to contractors (Randrup and Persson 2009) and this is also the case for Sweden (Randrup et al. 2017). In order to outsource this service, it is crucial for city authorities to know the amount of green spaces and trees that might need maintenance, which has led to the creation of extensive tree inventories in many cities. There are no conclusive data on the total number of cities in the Nordic countries that have an inventory, but in Sweden 52.8% of all cities and towns have a full or partial urban tree inventory, with the data generally collected by contractors, urban authority staff or a combination of these (Östberg et al. 2018). For the purposes of the present study, a request was sent out to all cities in the Nordic region with more than 200,000 inhabitants, which meant a total of 10 cities (Danmarks statistik 2018; SCB 2018; SSB 2018; STAT 2018). These cities were: Aarhus and Copenhagen in Denmark; Espoo, Helsinki and Tampere in Finland; Gothenburg, Malmö and Stockholm in Sweden; and Bergen and Oslo in Norway (Fig. 1). However, Bergen did not have a developed urban tree database and was therefore excluded from the study. It was replaced by Turku (189,669 inhabitants) in Finland, in order to include 10 major Nordic cities with rather well-developed urban tree databases in the study. These 10 cities have a combined population of 4,802,929, which represents 17.9% of the total Nordic population (Denmark has 5,806,015 inhabitance, Finland 5,513,000, Norway 5,323,933 and Sweden 10,120,242) (Danmarks statistik 2018; SCB 2018; SSB 2018; STAT 2018).
Fig. 1

Map of the 10 Nordic cities studied (illustration by Björn Wiström) and the area covered by the northern continental, southern maritime and southern continental climate zones in the region (Sabo et al. 2003)

Five of the selected cities are located in the southern maritime zone of the Nordic region (Aarhus, Copenhagen, Gothenburg, Malmö and Oslo) and five in the southern continental zone (Espoo, Helsinki, Stockholm, Tampere and Turku) (Sabo et al. 2003) (Fig. 1). In the request sent out to the cities, the departments responsible for urban trees in the different cities were asked to provide their complete tree database. However, the amount and type of data differed between the cities and only information on species diversity and distribution between park environments and street environments was available from all cities included in the study. A distinction is made in the data between park trees and street trees, where the latter are defined as trees placed in or close to streets or roads and needing special management in order to meet the demands of the street environment. The Malmö database covers all trees in parkland and in street environments, while cities such as Aarhus, Copenhagen, Gothenburg, Helsinki and Tampere include about 95% of all street trees in their databases, but the proportion of park trees varies. The databases of the remaining cities are still under development, but had sufficient data at the time of the present study to allow analysis (Table 1).
Table 1

Total number of trees in tree databases maintained by the 10 Nordic cities included in the study and the degree of coverage of the overall population that this number represents

City

Total number of trees

Degree of coverage

Aarhus

18,753

Almost all street trees and 10–15% of park trees have been inventoried

Copenhagen

26,032

Almost all street trees have been inventoried.

Espoo

18,067

30% of street trees have been inventoried

Gothenburg

24,818

Almost all street trees have been inventoried

Helsinki

27,252

Almost all street trees and 10–15% of park trees have been inventoried.

Malmö

54,901

The inventory is complete for all trees that are maintained by the city’s parks department

Oslo

11,756

The central area of the city has been inventoried

Stockholm

13,857

All street trees in the central area of the city have been inventoried, plus 30% of the trees outside the city centre.

Tampere

20,991

All street trees have been inventoried.

Turku

34,180

25–30% of the whole urban tree population has been inventoried.

Total

250,607

 

Biology and distribution of the longhorned beetle

In order to understand the different scenarios analysed in this study, it is necessary to have some knowledge of the biology and distribution of the two longhorned beetle species. The native range of ALB includes China and Korea, while that of CLB covers these two countries and also includes Japan, with occasional records from Indonesia, Malaysia, the Philippines, Taiwan and Vietnam (Lingafelter and Hoebeke 2002). The life cycle of ALB and CLB is similar and well described (Haack et al. 2010).

The main pathway to date for introduction of ALB into new regions has been through wood packaging material, while CLB has mainly been introduced through living plants (Haack et al. 2010). The first discovery of an established population outside its native range was reported for ALB in North America in 1996 (Haack et al. 1997) and for CLB in Europe in 2000 (Hérard et al. 2006). In summer 2011, CLB was found for the first time in Denmark, in an Acer palmatum believed to originate from a Dutch nursery in 2009 (NOBANIS 2018). In October 2015, two living specimens of ALB where found in Vanda, north-east of Helsinki, Finland (Tilli 2016). Before these findings, it was believed that these two exotic woodborers could not survive in the cold Nordic climate. However, using a CLIMEX map, a programme based on phenology and climate conditions within a pest’s natural distribution that can estimate its potential geographical distribution and relative abundance in a given region, MacLeod et al. (2002) demonstrated that ALB has the biological potential to develop populations in Denmark, southern Sweden and southern and south-western Norway. Moreover, their calculation did not include future climate scenarios, where the Nordic region is predicted to develop a 2-5 °C milder climate compared with the present (IPCC 2007). Therefore, the region can clearly support a greater distribution of ALB in the future, with large-scale economic, social and biological effects. If a region becomes infested with ALB, the dispersal range can be 2.0–2.6 km from the original host tree if wind conditions are favourable (e.g. Smith et al. 2001; Smith et al. 2004; Li et al. 2010; Hull-Sanders et al. 2017). This undoubtedly complicates the work of limiting the spread and distribution of ALB.

Tree loss scenarios

The host tree information used in this study was taken from Sjöman et al. (2014), who reviewed 35 papers reporting host-related data on the two longhorned beetle species. Based on the information in the review, tree species were ranked into four different categories based on their host grade, ranging from Very good host through Good host and Host to Resistant/rarely affected (Table 2).
Table 2

Division of beetle host susceptibility into: Very good host, Good host, Host and Resistant/rarely affected

Host grade

ALB and CLB feeding and life cycle features

Impact on tree growth

Included in scenario:

Very good host

Attracts longhorned beetles. Extensive feeding. Complete life cycle with population or entire tree infestation increases.

Dieback of tree crown and whole tree.

ES, WCS

Good host

Moderate feeding. Can complete life cycle.

Dieback of some branches. Dieback of whole tree crown or entire tree if stressed.

WCS

Host

Limited feeding by adult beetles. Small number of adults. Slight damaged eggs laid. Can escape attack if nearby trees are more susceptible.

Normal growth with recovery wounds.

WCS

Resistant or rarely affected

No feeding activity by adult beetles; no eggs laid.

Normal growth.

 

In an expected scenario (ES), only Very good hosts were included. In a worst-case scenario (WCS), the tree host categories Very good host, Good host and Host were all included. ALB = Asian longhorned beetle, CLB = citrus longhorned beetle

For the 10 Nordic cities included in the study, two different tree loss scenarios were developed: 1) an expected scenario and 2) a worst-case scenario. The expected scenario was based on trees described in the literature as a Very good host, where the longhorned beetle reaches full development, resulting in dieback of the whole tree crown or the entire tree (Yin and Lu 2005; Sjöman et al. 2014). The worst-case scenario considered all trees described in the literature as a Very good host, Good host or Host, where beetle development varies from full development to feeding on host trees, affecting the trees with a range of damage from complete dieback to slight damage with recovery wounds (Yin and Lu 2005). The reason for including tree species classified as Host, where the beetle has a limited impact on tree condition, in the worst-case scenario was that if the beetles are introduced to less favourable species in the absence of more susceptible species, they can start feeding and reach full development on these less susceptible species and have severe impacts on growth.

In comparing the host tree information contained in the tree inventories from the 10 Nordic cities, separate analyses of ALB and CLB were first performed for the two different scenarios (expected and worst-case), followed by combined analysis of both beetle species in an expected and worst-case scenario. When a whole genus was found to be described as Host in the literature, all species within that genus mentioned in the inventories were included.

Results

Composition and distribution of urban trees in the 10 major Nordic cities studied

For all 10 cities in the study, Tilia (lime) was the most common genus, representing 21.09% of the tree population, followed by Acer (12.34%), Sorbus (10.41%) and Betula (10.22%). These four genera together made up 54.06% of the total tree stock analysed (Table 3). On analysing the genus diversity among the individual cities, Tilia was found to be the most common genus in Copenhagen, Espoo, Gothenburg, Helsinki, Oslo and Stockholm, while Sorbus was the dominant genus in Malmö and Aarhus and Betula was the dominant genus in Tampere and Turku (Table 3). The dominance of Tilia was particularly pronounced in Helsinki, where it accounted for almost 44% of the total tree population (Table 3).
Table 3

Proportion (% of total) of city trees from different genera in the 10 Nordic cities studied

 

All cities (as a percentage of the total number of trees in all cities)

Aarhus

Copenhagen

Espoo

Gothenburg

Helsinki

Malmö

Oslo

Stockholm

Tampere

Turku

Abies

          

12.16%

Acer

12.34%

12.13%

8.34%

21.10%

8.24%

11.96%

10.03%

23.27%

18.82%

10.16%

12.79%

Aesculus

2.44%

2.87%

3.56%

 

4.06%

 

4.14%

5.04%

3.25%

  

Alnus

     

2.12%

   

3.94%

3.54%

Betula

10.22%

4.81%

2.65%

10.77%

9.93%

10.88%

2.58%

11.49%

8.41%

38.79%

13.37%

Carpinus

  

2.29%

        

Crataegus

2.00%

2.56%

2.23%

  

2.52%

4.20%

 

2.01%

  

Fagus

    

2.10%

 

3.45%

    

Fraxinus

3.22%

8.03%

6.73%

 

4.04%

 

3.25%

2.36%

4.84%

 

2.91%

Malus

2.19%

2.32%

2.13%

 

3.11%

 

2.81%

   

3.84%

Picea

          

6.59%

Pinus

3.08%

  

3.61%

    

6.14%

3.51%

9.99%

Platanus

 

2.48%

9.10%

   

2.91%

    

Populus

3.05%

3.77%

2.85%

2.58%

2.82%

2.42%

4.78%

 

2.05%

 

2.54%

Prunus

4.83%

3.27%

6.60%

 

7.64%

 

8.35%

4.72%

3.15%

 

4.27%

Quercus

4.88%

10.41%

5.93%

4.61%

6.67%

2.96%

5.52%

3.12%

6.29%

 

3.31%

Robinia

  

4.51%

        

Salix

3.62%

3.18%

    

10.34%

 

2.42%

 

2.97%

Sorbus

10.41%

18.91%

6.71%

16.49%

8.05%

7.57%

13.10%

3.05%

5.74%

12.57%

8.13%

Taxus

    

4.87%

      

Tilia

21.09%

15.90%

25.78%

22.29%

21.97%

43.98%

12.05%

27.14%

23.79%

23.54%

10.71%

Ulmus

3.29%

  

10.33%

5.37%

8.10%

 

8.68%

6.80%

  

Less than 2%

13.34%

9.35%

10.59%

8.21%

11.13%

7.48%

12.48%

11.13%

6.29%

7.48%

2.88%

Analysis of species diversity in all cities studied revealed that Tilia × europaea L. was the most common species, comprising 14.54% of the total tree population analysed. This was followed by Acer platanoides L. (8.9%), Betula pendula Roth. (7.69%) and Sorbus × intermedia (Ehrh.) Pers. (4.31%) (Table 4). These four most common species accounted for 35.44% of the combined tree population in the 10 cities studied. As regards species diversity in the individual cities, Tilia × europaea was the most common species in four of the 10 cities (Copenhagen 18.10%, Espoo 19.26%, Gothenburg 10.51% and Helsinki 39.78%). In Oslo, Tilia spp. was the dominant species, comprising 39.57% of the total stock (Table 4). In analysis of the diversity distribution on species level, only Malmö and Aarhus had sufficient diversity so that no species accounted for more than 10% of the total tree population. In further analysis of the number of species representing less than 2% of the total, Malmö differed from the other cities studied in that over 45% of its total tree population consisted of species with an occurrence of less than 2% (Table 4).
Table 4

Proportion (% of total) of species found in the 10 Nordic cities studied

 

All cities (as a percentage of the total number of trees in all cities)

Aarhus

Espoo

Gothenburg

Helsinki

Copenhagen

Malmö

Oslo

Stockholm

Tampere

Turku

Abies

          

11.13%

Acer

   

2.43%

       

Acer campestre

      

3.38%

    

Acer platanoides

8.90%

8.03%

20.52%

3.33%

10.69%

4.93%

2.93%

18.25%

16.87%

9.02%

11.96%

Acer pseudoplatanus

2.88%

    

2.40%

3.75%

   

Aesculus hippocastanum

2.26%

2.74%

 

3.60%

 

3.44%

3.66%

4.94%

3.19%

  

Alnus glutinosa

        

3.69%

3.50%

Betula

   

5.04%

   

5.31%

 

6.25%

 

Betula pendula

7.69%

4.10%

8.26%

4.23%

8.98%

  

3.76%

8.19%

31.94%

11.16%

Betula pubescens

      

2.40%

  

2.07%

Carpinus betulus

    

2.29%

     

Fagus sylvatica

     

3.40%

    

Fraxinus excelsior

2.60%

7.85%

 

2.80%

 

4.39%

2.50%

2.31%

4.81%

 

2.41%

Picea omorika

         

2.74%

Pinus sylvestris

2.12%

 

2.74%

     

5.75%

2.45%

8.85%

Platanus

     

9.10%

     

Platanus x hispanica

2.44%

    

2.79%

    

Populus tremula

 

2.31%

        

Prunus

   

2.33%

   

3.39%

   

Prunus avium

    

4.06%

4.38%

    

Quercus petraea

 

2.81%

         

Quercus robur

3.47%

7.28%

4.59%

3.80%

2.76%

2.85%

3.53%

 

6.21%

 

3.25%

Robinia pseudoacacia

     

4.25%

     

Salix alba

2.62%

3.02%

    

9.19%

    

Sorbus aucuparia

3.13%

2.19%

9.01%

 

3.09%

    

11.81%

3.94%

Sorbus hybrida

          

2.00%

Sorbus intermedia

4.31%

5.31%

5.61%

5.24%

2.39%

3.77%

8.41%

 

3.51%

  

Sorbus latifolia

3.20%

         

Sorbus mougeotii

6.76%

         

Taxus x media

  

4.84%

       

Tilia spp.

3.59%

  

8.16%

4.08%

  

24.45%

10.09%

  

Tilia cordata

5.64%

 

2.24%

 

2.79%

  

3.59%

  

Tilia platyphyllos

2.58%

   

2.74%

     

Tilia x europaea

14.54%

7.64%

19.26%

10.51%

39.78%

18.10%

7.97%

 

8.55%

21.18%

9.51%

Ulmus glabra

2.48%

 

9.26%

2.26%

7.19%

  

7.78%

5.25%

  

Less than 2%

43.16

25.53%

18.46%

39.19%

21.05%

37.28%

45.46%

23.66%

23.99%

13.67%

27.46%

Tree loss scenarios

Evaluation of the data on host susceptibility to the two longhorned beetles revealed clear differences in predicted tree losses between the expected scenario and worst-case scenario. Tampere differed from other cities in the study in that it risked losing over half of its inventoried tree population to ALB in the expected scenario and over 90% of its trees in the worst-case scenario (Table 5). The reason was a high proportion of Acer platanoides (9.02%) and Betula pendula (31.94%), which are considered a Good host or Very good host where the beetle can reach full development. Since maple (Acer spp.) is considered a Very good host for ALB, cities with high numbers of this genus can suffer serious tree losses. For example, Espoo has 20.52% Acer platanoides in its tree population and Stockholm and Oslo have 16.87% and 18.25%, respectively (Table 5). In the worst-case scenario for ALB, Oslo and Tampere were most affected, with predicted losses of 96% and 92%, respectively, due to their large proportions of Tilia spp. and Ulmus spp. (35.82% and 23.54%, respectively, of their tree population) (Table 4).
Table 5

Potential tree losses (% of total tree population), in the individual Nordic cities studied and in all 10 cities combined, caused by longhorned Asian longhorned beetle (ALB) and citrus longhorned beetle (CLB), separately or combined, in an expected scenario and a worst-case scenario

Scenario, beetle species

Percent of total population in all cities

Aarhus

Espoo

Gothen-burg

Helsinki

Copen-hagen

Malmö

Oslo

Stock-holm

Tampere

Turku

Expected scenario, ALB

33%

27%

29%

29%

32%

27%

33%

42%

41%

51%

30%

Worst-case scenario, ALB

77%

77%

41%

79%

88%

84%

81%

96%

81%

92%

60%

Expected scenario, CLB

21%

31%

21%

16%

20%

15%

23%

20%

25%

23%

21%

Worst-case scenario, CLB

62%

76%

30%

62%

45%

64%

72%

51%

65%

71%

66%

Expected scenario ALB+ CLB

45%

46%

59%

37%

40%

34%

47%

54%

47%

64%

38%

Worst-case scenario, ALB+ CLB

94%

96%

97%

92%

98%

96%

96%

97%

98%

97%

80%

In the expected scenario of an outbreak of CLB, large tree losses mainly occurred in cities with high numbers of maples (Acer spp.) and Sorbus spp., i.e. genera on which the beetle can reach full development. The main cities affected were Aarhus, Malmö and Stockholm, with estimated tree losses in the expected scenario of 31%, 23% and 25%, respectively (Table 5). In the worst-case scenario for CLB, the tree losses increased most in cities with large proportions of Betula spp., Fraxinus spp., Prunus spp. and Quercus spp. For example, adding Betula spp. as a susceptible genus in the worst-case scenario for CLB increased tree losses dramatically in Tampere and Turku, where Betula comprises 38.79% and 13.37%, respectively, of the total tree population (Table 5). In a combined outbreak of the two woodboring beetle species, Espoo, Oslo and Tampere risked losing over half their urban tree population, even in the expected scenario. In the worst-case scenario of a combined outbreak, the potential tree losses were very dramatic, with all cities in the study facing a risk of losing over 90% of their tree population.

Discussion

Calculated tree loss

Outbreaks of serious pathogen and insect attacks are one of the most challenging threats to the future urban and natural treescape. In the scenarios analysed in this study, the results were catastrophic. In particular, in a combined outbreak of the two beetle species, almost half the tree population in all 10 cities could be lost in the expected scenario and up to 90% in the worst-case scenario. Similar tree losses have been estimated in earlier studies, e.g. Nowak et al. (2001) estimated losses of between 12 and 61% of the tree population following an ALB infestation in nine different cities in the US. Actual tree losses are reported by Andre (2018) for Worchester, Massachusetts, where 24,179 ALB-infested trees have been found and removed, with associated large-scale losses in ecosystem capital from removed trees and high costs of planting new trees. However, it is important to bear in mind that the results presented in this study, and in other studies estimating tree losses to ALB and CLB, should be regarded as rough theoretical indications rather than solid proof at this stage, as there are several weaknesses and limitations in the available information that prevent more detailed and solid conclusions being drawn. The main issue is a lack of clear evidence on the tree species that are susceptible to attack by the two longhorned beetle species and their degree of susceptibility. As stated in the review by Sjöman et al. (2014), there is great variation in the quality of the information currently available, which can lead to incorrect conclusions and recommendations on tree susceptibility or resistance. Some publications describe a particular genus or species as a host to some degree, while others describe it as resistant or rarely infested. In the papers reviewed by Sjöman et al. (ibid.), five describe Tilia spp. (lime trees) as a Host for ALB (Nowak et al. 2001; Ric et al. 2006; Hu et al. 2009; Jordbruksverket 2010; APHIS 2012), while two other publications state that the genus Tilia is Resistant/rarely affected (Haack et al. 1997; Raupp et al. 2006). Such inconsistent information leads to difficulties in assessing potential tree losses in a city. Furthermore, there have unfortunately been simplifications in some literature with the aim of providing guidance on the species and genera of trees that face attack by longhorned beetle. For example, Van der Gaag et al. (2008) present a list of hosts for CLB based on data taken from Lingafelter and Hoebeke (2002), most of which are in turn based on information reported in Chinese and Japanese studies (Sjöman et al. 2014). Lingafelter and Hoebeke (2002) categorise a large number of species as a Host for CLB, but in the compilation by Van der Gaag et al. (2008) much of this species information has been changed to whole genera, without further information. This simplification of host-related information can result in great confusion and misunderstanding when predicting potential tree losses, but also in future recommendations on risk-free trees for urban planting.

Increase species diversity

While the levels of tree losses estimated in this study can only be taken as general indications, the results still show the risks involved in having a limited diversity of species and genera in a city. In the literature, it is frequently recommended that no given species should account for more than 10% of the total tree population (e.g. Grey and Deneke 1986; Smiley et al. 1986; Santamour 1990; Miller and Miller 1991), while Barker (1975) and Moll (1989) argue that no species in a tree population should exceed 5%. In the present study, no city achieved the latter level, while only Aarhus and Malmö achieved the level of no species accounting for more than 10% of the total tree population (Table 4). In Helsinki, Tampere and Oslo, two species accounted for over half the tree population inventoried, and thus the risks of catastrophic tree losses are high if these overused tree species become infested by a pest such as longhorned beetle. However, a study by Berland and Hopton (2016) showed that generally high species diversity does not necessarily reduce vulnerability to a polyphagous pest such as ALB with its large range of potential host genera and species. Instead, it is important to analyse the particular species that contribute to the diversity. For example, if different species or genera that are susceptible to ALB each make up less than 10% of the tree population, but together represent the great majority of the total, the tree losses can be immense. Thus a city such as Malmö, with a rather rich diversity of species and genera, can risk losing a large proportion of its trees if longhorned beetle attacks species within tree genera classified in the literature as being less susceptible, but can suffer severe impacts on growth if more favourable species are absent. In the analysis presented in this study, Malmö went from a risk of losing 33% of its tree population in an expected scenario of an outbreak of ALB to losing up to 81% of its trees in a worst-case ALB scenario. The reason for this large increase in tree losses was that only four genera (Prunus, Quercus, Sorbus and Tilia) represent almost 40% of the total tree population in Malmö (Table 3). These genera are classified in the literature as Hosts and can escape attacks if nearby trees are more susceptible, but if future studies reveal them to be more susceptible than currently believed the scenarios can change dramatically, as shown in Table 3. This indicates a need to move from quantitative compilation of diversity data with the focus on different percentages of species and genus diversity and instead analyse more qualitatively what the species combination actually comprises and how vulnerable it is to different scenarios of pest attacks or pathogens. In theory, a city with a limited diversity of tree species, but with large proportions of Pyrus calleryana and Ginkgo biloba, two species resistant to longhorned beetles, could risk losing fewer trees than a city with a higher diversity but a larger proportion of species susceptible to ALB or/and CLB. Lacan and McBride (2008) present a Pest Vulnerability Matrix (PVM), which is a valuable tool for screening the pest vulnerability of an existing tree population and for evaluating future tree planting programmes.

There are several factors that need to be considered when strategically planning more species-diverse urban forests. Simply ordering new tree species and genotypes that are untested for the region is not the best approach, as the adaptability and longevity of species in stressful urban habitats must be a dominant factor in the selection process (Raupp et al. 2006). Unsuitable choices may result in increased mortality, reduced lifespan of trees and, ultimately, greater costs when poorly performing trees must be removed or replaced (Richards 1983; Tello et al. 2005; Raupp et al. 2006). For this reason, it is important to develop local knowledge and experience of rare and/or non-traditional tree species. This emphasises the importance of evaluating plant material in local or regional botanic gardens and arboretums. By utilising these tree collections, it may be possible to find genetic material that is proven to be hardy for the region. Evaluation of species currently used in urban environments may also prove to be a valuable source of information on species suitability for local sites (Sjöman et al. 2012). For example, 45.46% of the total tree population in Malmö comprises species with less than 2% occurrence (Table 4). Many of these species may have demonstrated longstanding tolerance to the local site situation and their use could be extended to other sites in the city. By analysing this ‘2%-group’ and their susceptibility to ALB and CLB, it would be possible to devise local guidance on species and genetic material of the species to be further propagated and used. However, rare or non-traditional species and genotypes must also be evaluated, to assist in strategic diversification of future landscapes. Solely evaluating material from tree collections risks only providing guidance for high-quality sites, while evaluation of tree performance across a full range of sites would better inform guidance for challenging sites, such as warm and dry inner-city conditions. To establish urban tree populations that are resilient to ALB, it is likely to be necessary to accept the use of exotic tree species, especially from East Asia, providing these can be propagated using robust biosecurity standards. In a review by Yin and Lu (2005), a number of tree species native to China are classified as resistant or rarely affected by ALB. In fact, the majority of the species/genera classified in the literature as resistant or rarely affected by ALB (Sjöman et al. 2014) are native to China and Japan, where they have co-evolved for generations side-by-side with the beetle and have developed natural strategies to avoid attacks. Future selection of East Asian tree species in local arboreta and botanic gardens might be a fruitful approach in order to prepare for future outbreaks of Asian longhorned beetles.

Effects of tree loss

The loss of 15–98% of urban trees would not only represent a marked visible decrease in the overall tree population, but would also have major economic consequences for the affected city. Based on Östberg et al. (2015), replacing 21% of existing urban trees in Nordic cities with new trees with stem circumference 18–20 cm would cost SEK 204.9 million ($25.1 million), not including the cost of planting and aftercare. The cost of the worst-case scenario with a combined outbreak of ALB and CLB (94% tree losses) in this study would be SEK 912.7 million ($112.4 million) just for purchasing new replacement trees (Östberg et al. 2015). In addition, according to Gilioli et al. (2014) a European outbreak of CLB could reduce the amount of provisioning ecosystem services by 35% and the amount of regulating services by about 12%. As one example of this, a study in the US has found a relationship between large tree losses and increased human mortality related to cardiovascular and lower respiratory tract illness in counties infested with emerald ash borer (Donovan et al. 2011). However, emerald ash borer only affects ash trees (Fraxinus spp.) and the consequences of the multi-host ALB and CLB might be much more severe. For example, 17.9% of the Nordic population lives in the 10 cities included in the present study, so an outbreak of ALB and CLB in these 10 cities alone would affect a substantial proportion of the population in the Nordic countries, with risks of increased mortality and higher costs for the health service.

These three examples alone demonstrate that municipalities need to calculate not only the direct replacement costs of urban trees, but also the loss of ecosystem services and the negative impact on human health. Current management plans for potential outbreaks of ALB and CLB in Sweden only focus on practical tree removal and the reporting system (Huisman et al. 2011), and do not consider how an outbreak might affect ecosystem services and people’s health and the economic implications. With projected tree losses of 15–98%, there is an urgent need to develop comprehensive management plans to cope with potential attacks by longhorned beetles in the Nordic countries.

Conclusion

This study presents preliminary estimates of potential tree losses to longhorned beetle (Anoplophora glabripennis and A. chinensis) that can be used in early planning of future planting programmes. In order to obtain more accurate tree loss projections, extensive experimental activity with controlled evaluations of susceptible species and tolerant/resistant species is necessary. Such evaluations could also provide information about the extent to which different tree species/genera are susceptible, i.e. whether they support the complete life cycle of the beetles or just feeding by adult beetles. Another important requirement is to thoroughly evaluate host trees on species level and not include the whole genus, even if many species within the genus are susceptible, since this can exclude many potential trees from future planting. Furthermore, it is important to identify how the susceptibility of a species differs when it is growing together with other more receptive species, compared with standing alone, in order to produce trustworthy guidance on selection of planting material for the future urban forest. Until such information becomes available, we need to accept existing host information and focus on rare tree species and genera not mentioned in previous studies and their potential use in urban environments. Local arboreta and botanical gardens can be an important source of information and a gene bank of material for testing, where the focus should perhaps be on East Asian species. In order to further increase the range of suitable species for the Nordic region, targeted collection of hardier genotypes of species will be necessary, including species and genotypes from milder regions than Northern Europe, making botanical gardens an important resource in diversification of resilient urban forest.

The effects of future pest attacks on ecosystem services, human health and the overall budgets of urban park managers are currently being studied, but relevant recommendations for management plans are still lacking. Effective management plans are a key component in preparing urban areas for potential outbreaks of devastating pests such as ALB and CLB.

References

  1. Akbari H, Pomerantz M, Taha H (2001) Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Sol Energy 70(3):295–310CrossRefGoogle Scholar
  2. Andre F (2018) Ten years with the Asian longhorned beetle program in Massachusetts. The Citizen Forester No. 217. Massachusetts Department of Conservation and RecreationGoogle Scholar
  3. APHIS (2012) USDA-APHIS-PPQ, Center for Plant Health Science and Technology. Asian Longhorned beetle: annotated host list. Accessed 09/26/2012. www.uvm.edu/albeetle/hosts.htm
  4. Barker P (1975) Ordinance control of street trees. J Arboric 1:121–215Google Scholar
  5. Berland A, Hopton ME (2016) Asian longhorned beetle complicates the relationship between taxonomic diversity and pest vulnerability in street tree assemblages. Arboricultural Journal 38(1):28–40CrossRefGoogle Scholar
  6. Costanza R, D'Arge R, De Groot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O'Neill RV, Paruelo J, Raskin RG, Sutton P, Van Den Belt M (1997) The value of the world's ecosystem services and natural capital. Nature 387:253–260CrossRefGoogle Scholar
  7. Cowett FD and Bassuk NL (2014) State wide assessment of street trees in New York State, USA. Urban Forestry and Urban Greening 13:213–220Google Scholar
  8. Danmarks statistik (2018) Danish Office for National Statistics. Retrieved November 22, 2018 from http://statistikbanken.dk/statbank5a/SelectVarVal/saveselections.asp
  9. Donovan G, Butry D, Michael Y, Prestemon J, Liebhold A, Gatziolis D, Mao M (2011) The relationship between trees and human health - evidence from the spread of the emerald ash borer. Am J Prev Med 2013 44(2):139–145CrossRefGoogle Scholar
  10. Forestry Commission (2017) http://www.forestry.gov.uk/forestry/beeh-9ruekf#ceratocystis. Accessed 23 Sept 2017
  11. Gilioli G, Schrader G, Baker RHA, Ceglarska E, Kertész VK, Lövei G, Navajas M, Rossi V, Tramontini S, van Lenterenh JC (2014) Environmental risk assessment for plant pests: a procedure to evaluate their impacts on ecosystem services. Sci Total Environ 468–469(2014):475–486CrossRefGoogle Scholar
  12. Gill SE, Handley JF, Ennos AR, Pauleit S (2007) Adapting cities for climate change: the role of the green infrastructure. Built Environ 33(1):115–133CrossRefGoogle Scholar
  13. Gómez-Muñoz VM, Porta-Gándara MA, Fernández JL (2010) Effect of tree shades in urban planning in hot-arid climatic regions. Landsc Urban Plan 94(3–4):149–157CrossRefGoogle Scholar
  14. Grahn P, Stigsdotter AU (2003) Landscape planning and stress. Urban For Urban Green 2:1–18CrossRefGoogle Scholar
  15. Gratani L, Varone L (2006) Carbon sequestration by Quercus ilex L. and Quercus pubescens Willd. And their contribution to decreasing air temperature in Rome. Urban Ecosystems 9(1):27–37CrossRefGoogle Scholar
  16. Grey GW, Deneke FJ (1986) Urban Forestry, 2nd edn. Wiley, New YorkGoogle Scholar
  17. Haack RA, Law KR, Mastro VC, Ossenbruggen HS, Raimo BJ (1997) New York’s battle with the Asian long-horned beetle. J For 95(12):11–15Google Scholar
  18. Haack RA, Turgeon JJ, Herard F, Sun J (2010) Managing invasive populations of Asian longhorned beetle and citrus longhorned beetle: a worldwide perspective. Annu Rev Entomol 55:521–546CrossRefGoogle Scholar
  19. Hérard F, Ciampitti M, Maspero M, Krehan H, Benker U, Boegel C, Schrage R, Bouhot-Delduc L, Bialooki P (2006) Anoplophora species in Europe: infestations and management processes. EPPO Bull 36(3):470–474CrossRefGoogle Scholar
  20. Hu J, Angeli S, Schuetz S, Luo Y, Hajek AE (2009) Ecology and management of exotic and endemic Asian longhorned beetle Anoplophora glabripennis. Agric For Entomol 11:359–375CrossRefGoogle Scholar
  21. Huisman M, Åkesson I, Östberg J (2011)Environmental goals and quarantine pests. In Swedish: (Miljömål och karantänsskadegörare). Swedish University of Agricultural Science Report 2011:17Google Scholar
  22. Hull-Sanders H, Pepper E, Davis K, Trotter RT (2017) Description of an establishment event by the invasive Asian longhorned beetle (Anoplophora glabripennis) in a suburban landscape in the northeastern United States. PLoS One 12(7):e0181655.  https://doi.org/10.1371/journal.pone.0181655 CrossRefPubMedPubMedCentralGoogle Scholar
  23. IPCC Intergovermental Panel of Climate Change (2007) IPCC Fourth Assessment Report (AR 4)Google Scholar
  24. Lacan I, McBride JR (2008) Pest vulnerability matrix (PVM): a graphic model for assessing the interaction between tree species diversity and urban forest susceptibility to insects and diseases. Urban For Urban Green 7:291–300CrossRefGoogle Scholar
  25. Li G-H, Gao R-T, Smith MT, Kong L-C (2010) Study on dispersal of Anoplophora glabripennis (Motsch.) (Coleoptera: Cerambycidae) population. For Res, Beijing 25:678–684Google Scholar
  26. Lingafelter SW, Hoebeke ER (2002) Revision of Anoplophora (Coleoptera: Cerambycidae). Entomological Society of Washington, Washington, D.C. 236 ppGoogle Scholar
  27. MacLeod A, Evans HF, Baker RHA (2002) An analysis of pest risk from an Asian longhorn beetle (Anoplophora glabripennis) to hardwood trees in the European. Crop Prot 21:635–645CrossRefGoogle Scholar
  28. McPherson GE, van Doorn N, de Goede J (2016) Structure, function and value of street trees in California, USA. Urban Forestry and Urban Greening 17:104–115Google Scholar
  29. Miller RH, Miller RW (1991) Planting survival of selected street tree taxa. J Arboric 17:185–191Google Scholar
  30. Moll G (1989) Improving the health of the urban forest. In: Moll G, Ebenreck S (eds) A resource guide for urban and community forests. Island Press, Washington, pp 119–130Google Scholar
  31. Morgenroth J, Östberg J, Konijnendijk van den Bosch C, Nielsen AB, Hauer R, Sjöman H, Chen W, Jansson M (2016) Urban tree diversity – taking stock and looking ahead. Urban For Urban Green 15:1–5CrossRefGoogle Scholar
  32. Nitoslawski SA, Duinker PN, Bush PG (2016) A review of drivers of tree diversity in suburban areas: research needs for north American cities. Environ Rev 24(4):471–483CrossRefGoogle Scholar
  33. Nowak DJ, Pasek JE, Sequeira RA, Crane DE, Mastro VC (2001) Potential effect of Anoplophora glabripennis (Coleoptera: Cerambycidae) on urban trees in the United States. J Econ Entomol 94(1):116–122CrossRefGoogle Scholar
  34. NOBANIS (2018) European Network on Invasive Alien Species. Retrieved October 2018 from https://www.nobanis.org/species-alerts/anoplophora-chinensis/
  35. Östberg J, Sjögren J, Kristoffersson A (2015) Financial valuation of replacement cost of urban trees-Alnarp model 2.0. (In Swedish: Ekonomisk värdering av återanskaffningskostnaden för träd-Alnarpsmodellen 2.0). Report 2015:24, Swedish University of Agricultural ScienceGoogle Scholar
  36. Östberg J, Wiström B, Randrup TB (2018) The state and use of municipal tree inventories in Swedish municipalities - results from a national survey. Urban Ecosystems 21(3):467–477Google Scholar
  37. Randrup TB, Persson B (2009) Public green spaces in the Nordic countries: development of a new strategic management regime. Urban For Urban Green 8(1):31–40.  https://doi.org/10.1016/j.ufug.2008.08.004 CrossRefGoogle Scholar
  38. Randrup TB, Östberg J, Wiström B (2017) Swedish green space management – the managers perspective. Urban For Urban Green 28:103–109.  https://doi.org/10.1016/j.ufug.2017.10.001 CrossRefGoogle Scholar
  39. Raupp MJ, Buckelew-Cumming A, Raupp EC (2006) Street tree diversity in eastern North America and its potential for tree loss to exotic borers. Arboricult Urban For 32(6):297–304Google Scholar
  40. Ric, J., P. de Groot, B. Gasman, M. Orr, J. Doyle, M.T. Smith, L. Dumouchel, T. Scarr, and J.J. Turgeon. (2006) Detecting signs and symptoms of Asian longhorned beetle injury. Natural Resources Canada, Canadian Forest Service, and Canadian Food Inspection Agency. 121 pp.Google Scholar
  41. Richards NA (1983) Diversity and stability in a street tree population. Urban Ecology 7:159–171CrossRefGoogle Scholar
  42. Sabo A, Benedikz T, Randrup TB (2003) Selection of trees for urban forestry in the Nordic countries. Urban For Urban Green 2:101–114CrossRefGoogle Scholar
  43. Santamour FS (1990) Trees for urban planting: diversity, uniformity and common sense. In: Proceedings of the 7th conference of the metropolitan tree improvement Alliance, vol 7, pp 57–65Google Scholar
  44. SCB (2018) Swedish Office for National Statistics. Retrieved November 22, 2018 from https://www.scb.se/hitta-statistik/sverige-i-siffror/manniskorna-i-sverige/
  45. Sinclair WA, Lyon HH (2005) Diseases of trees and shrubs, 2nd edn. Cornell University Press, IthacaGoogle Scholar
  46. Sjöman H, Östberg J, Bühler O (2012) Diversity and distribution of the urban tree population in ten major Nordic cities. Urban For Urban Green 11:31–39CrossRefGoogle Scholar
  47. Sjöman H, Östberg J, Nilsson J (2014) Review of host trees for the wood-boring pests Anoplophora glabripennis and Anoplophora chinensis: an urban Forest perspective. Arboricult Urban For 40(3):143–164Google Scholar
  48. Smiley ET, Kielbaso JJ, Proffer TJ (1986) Maple disease epidemic in southeastern Michigan. J Arboric 12(5):126–128Google Scholar
  49. Smith MT, Bancroft J, Li G, Gao R, Teale S (2001) Dispersal of Anoplophora glabripennis (Cerambycidae). Environ Entomol 30:1036–1040CrossRefGoogle Scholar
  50. Smith MT, Tobin PC, Bancroft J, Li G, Gao R (2004) Dispersal and spatiotemporal dynamics of Asian longhorned beetle (Coleoptera: Cerambycidae) in China. Environ Entomol 33:435–442CrossRefGoogle Scholar
  51. SSB (2018) Norwegian Office for National Statistics. Retrieved November 22, 2018 from https://www.ssb.no/befolkning/faktaside/befolkningen
  52. STAT (2018) Finish Office for National Statistics. Retrieved November 22, 2018 from http://www.stat.fi/tup/suoluk/suoluk_vaesto_sv.html
  53. Tello M-L, Tomalak M, Siwecki R, Gaper J, Motta E, Mateo-Sagasta E (2005) Biotic urban growing condition – threats, pests and diseases. In: Konijnendijk CC, Nilsson K, Randrup TB, Schipperijn J (eds) Urban forests and trees. Springer, Berlin, pp 325–365CrossRefGoogle Scholar
  54. Tilli K (2016) The hunt of asian longhorned beetles in Finland (Jakten på asiatiska longhorningar i Finland) in Swedish, Swedish University of Agricultural Science. Movium Direkt 8:7–11Google Scholar
  55. Tyrväinen L, Mäkinen L, Schipperijn J (2005) Tools for mapping social values for urban woodlands and of other green spaces. Landsc Urban Plan 79(1):5–19CrossRefGoogle Scholar
  56. Van der Gaag DJ, Ciampitti M, Cavagna B, Maspero M, Hérard F (2008) Pest risk analysis: Anoplophora chinensis. Plant protection service. Wageningen, The Netherlands, p 49Google Scholar
  57. Xiao Q, McPherson EG (2002) Rainfall interception by Santa Monica’s municipalurban forest. Urban Ecosystems 6:291–302CrossRefGoogle Scholar
  58. Yang J, Zhou J, Ke Y, Xiao J (2012) Assessing the structure and stability of street trees in Lhasa, China. Urban Forestry & Urban Greening 11:432–438Google Scholar
  59. Yin W, Lu W (2005) Review of Tree Selection and Afforestation for Control of Asian Longhorned Beetle in North China. Food & Agriculture Organization, Forestry Department. FAO Rome. Accessed 09/26/2012. www.fao.org/forestry/9599- 058fddfef27dd6c45f4665cedfcb9648f.pdf

Copyright information

© The Author(s) 2019

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Faculty of Landscape Planning, Horticulture and Agricultural Science, Department of Landscape Architecture, Planning and ManagementSwedish University of Agricultural SciencesAlnarpSweden
  2. 2.Gothenburg Botanical GardenGothenburgSweden
  3. 3.Gothenburg Global Biodiversity CentreGothenburgSweden

Personalised recommendations