Diversity and structure in California’s urban forest: What over six million data points tell us about one of the world's largest urban forests

Urban street trees provide many benefits to surrounding communities, but our ability to assess such benefits relies on the availability of high-quality urban tree data. While these data are numerous, they are not available in an easily accessible, centralized place. To fill this gap, we aggregated public and private data into a single, comprehensive inventory of urban trees in California called the California Urban Forest (CUF) Inventory. These data are offered to the public (aggregated to ZIP code) via an online data portal, which at the time of publication contained over 6.6 million urban tree records. In this study, we first describe the assembly and utility of the inventory. Then, we conduct the most comprehensive assessment of the diversity and structure of California’s urban forest to date at statewide, regional, and local spatial scales. These analyses demonstrate that California’s urban forests are highly diverse and among the most diverse urban forests in the world. We present a new and intuitive metric of species diversity, the top diversity or TD-50 index, which represents the cumulative number of species accounting for the top 50 % abundance of trees in an urban forest. We used species abundance data from 81 well-inventoried cities to demonstrate that the TD-50 index was a robust metric of diversity and a good predictor of comprehensive metrics like the Shannon Index. We also found that small-statured trees, such as crape myrtles (Lagerstroemia cv.) dominate California’s urban forests. This aggregated inventory of one of the world's largest urban forests provides the data necessary to assess the structure, diversity, and value of California’s urban forests at multiple spatial scales. The inventory’s presentation to the public and the information that can be gained from its analysis can be a model for urban forest management worldwide.     

Diversification of the urban forest—Can we afford to exclude exotic tree species?

Introduced tree species represent a substantial component of urban forests in cities all over the world. Yet there is controversy about the further use of introduced tree species. Many practice orientated publications,research papers and governmental websites in the fields of urban planning, urban forestry, and urban ecology argue for planting native species and avoiding introduced species. Such arguments for native-only species selection are also touted by environmental groups and the media. Consequently the debate has sometimes spiralled away from a sensible and rational platform where invasion risks and biodiversity loss are discussed, to a groundless and unreasonable argument where exotic species are generally considered incapable of providing ecosystem services. From a European perspective, we here aim to curate a set of necessary considerations for current and future discussions on native and non-native plant material in sustainable urban development. Using examples from Northern and Central Europe we illustrate that in some regions the catalogue of native tree species may be too limited to fulfil ecosystem services and resilience in harsh urban environments. A main message from our line of arguments is that we cannot afford to generally exclude non-native tree species from urban greening. If “native-only” approaches become incorporated in regional, national or international policy documents or legislation there is a risk that urban ecosystem resilience will be compromised, particularly in regions with extreme environmental conditions. Since both invasion risks and sizes of native species pools vary conspicuously at regional to continental scales we also argue to adapt urban policies on using non-native trees to regional contexts.     

Defect-disorder and risk assessment of heritage trees in urban Hong Kong

Heritage trees in a city, echoing factors conducive to outstanding performance, deserve special care and conservation. To understand their structural and health conditions in urban Hong Kong, 30 defect-disorder (DD) symptoms (physical and physiological) subsumed under four tree-position groups (soil-root, trunk, branching, and crown-foliage) and tree hazard rating were evaluated. The surveyed 352 trees included 70 species; 14 species with 233 trees were native. More trees had medium height (10–15 m), medium DBH (1–1.5 m) and large crown (>15 m). In ten habitats, public park and garden (PPG) accommodated the most trees, and roadside traffic island (RTI) and public housing estate (PH) had the least. Tree dimensions and tree habitats were significantly associated. The associations between the 2831 DD and tree-position groups, tree habitats and tree hazard rating were analyzed. Fourteen trees from Ficus microcarpa, Ficus virens and Gleditsia fera had high hazard rating, 179 trees from 22 species moderate rating, and 159 trees from 55 species low rating. RTI, roadside tree strip (RTS), roadside tree pit (RTP), roadside planter (RP) and stone wall (SW) had more moderate hazard rating, and PPG, roadside slope (RS) and government, institutional and community land (GIC) more low rating. Redundancy analysis showed that DD were positively correlated with RTS, RTP, RP and SW, but negatively correlated with PPG, RS and GIC (p < 0.05). The DD significantly increased tree hazard rating and failure potential. Future management implications for heritage-tree conservation and enhancement focusing squarely on critical tree defect-disorder in urban Hong Kong were explored, with application to other compact cities.     

High carbon losses from established growing sites delay the carbon sequestration benefits of street tree plantings – A case study in Helsinki,Finland

We assessed the net carbon (C) sequestration dynamics of street tree plantings based on 10 years of measurements at two case study sites each with different tree species in Helsinki, Finland. We assessed C loss from tree soils and tree C accumulation, tested the applicability of pre-existing growth and biomass equations against observations, and estimated the time point for the beginning of net C sequestration for the studied street tree plantings. The tree woody biomass C accumulation in the first 10 years after planting was 18–32 kg per tree. At the same time the C loss from the growth media was at least 170 kg per growth media volume (25 m³) per tree. If this soil C loss was accounted for, the net C sequestration would begin, at best, approximately 30 years after planting. Biomass equations developed for traditional forests predicted more stem biomass and less leaf and branch biomass than measured for the species examined, but total aboveground biomass was generally well predicted.     

Willing partners? Residential support for municipal urban forestry policies

Cities across North America are adopting ambitious goals to grow their urban forests. As existing trees and new planting opportunities are often located on private property, residents’ support and participation is needed in order to meet these goals. However, little research has examined support for municipal urban forestry efforts, including policies specifically targeting residential areas. The objectives of this research are to (1) assess resident’ level of support for common urban forestry policies and (2) determine if there are specific household characteristics associated with different levels of policy support. The objectives are addressed through a statistical analysis of survey responses and a qualitative examination of follow-up interviews with residents in four neighborhoods located in Mississauga (Ontario, Canada). The survey participants and their properties vary in their socioeconomic characteristics, age of development, and urban forest conditions. Our results found that the majority of residents had neutral to very positive attitudes toward common municipal policies encouraging planting and restricting removal of trees, but support levels were lower for the policies than for general statements about desired presence and size of urban trees. Several characteristics are significantly related to level of policy support, including age of household members, education-level, property-level tree density, recent tree planting activity and age of house. Interviews also highlighted residents’ apprehensions about living among tall trees and older resident's concerns with tree maintenance. The results suggest that most residents would be willing partners in urban forestry efforts, with many of these residents already actively planting and maintain trees. However, to increase support and participation rates, different types of trees – including those smaller in stature and ones that require relatively little maintenance – should be part of any planting program to meet the varying needs of households.     

Application of artificial intelligence for tree risk assessment optimization in Itanhaém – São Paulo,Brazil

Tree risk assessment consists of the identification of a set of defects that may affect the stability of the tree, leading to a possible collapse or failure, either of the whole plant or a part of it; and also, the identification of the targets to be reached and the side effects caused by any eventual failure. Although this is a necessary practice, the large number of variables involved in this evaluation makes the analysis time-consuming. Thus, this research aimed to optimize the tree risk assessment by creating a new protocol with the three visual assessment methods common variables and generating a new protocol applied to trees of species frequently used in urban afforestation worldwide: Terminalia catappa, Ficus Benjamin and Delonix regia. Altogether 36 variables were used for tree risk visual assessment applied in the evaluation of 230 trees located in the urban forest in Itanhaém - São Paulo - Brazil. The data collection was carried out using a smartphone and a data spreadsheet created in ODK collect app, facilitating data storage and processing. To identify the variables with the greatest possibility to determine the risk of falling, artificial intelligence was used through the Decision Tree algorithm (C4.5) in the WEKA software. The results showed that, from the 36 variables evaluated, 14 were enough to determine the risk of tree falling, with 73% hit rate in the tree risk classification. It is concluded that the use of artificial intelligence was essential in detecting tree problems in order to redirect management practices.     

Factors influencing long-term street tree survival in Milwaukee,WI, USA

Street trees are exposed to a variety of site conditions, environmental factors, and physical disturbances which influence their survival in urban areas. This study draws on 25 years of urban forest monitoring data from the city of Milwaukee, WI (United States) to model the impacts of these factors on tree survival for a single cohort of trees. Tree condition, tree size, tree species, and site attributes were measured initially in 1979. These factors were measured again in 1989 and 2005 and compared to construction data for the same area during the study period. Multivariate logistic regression was used to identify factors associated with tree survival. Cross-validation show the final model could successfully predict tree survival nearly 85% of the time. Results indicate that tree survival varied by species. Additionally, trees were more likely to die as trunk diameter increased, planting space width decreased in the tree lawn, and tree condition decreased. Finally, trees adjacent to construction were nearly twice as likely to die as those not exposed to development and redevelopment activities.     

Stress-resistant trees are more common in urban than rural forests: A case study of Cleveland,Ohio’s natural parks

Natural parks are comprised of preserved forested natural areas that are undergoing natural ecological processes. These areas can offer a refuge for local biodiversity and contribute substantially to ecosystem services in both rural areas with relatively low population densities, as well as high-density urban areas. Forested natural parks located in urban areas should experience more stressful environmental conditions than nearby rural areas, yet we know relatively little about how urbanization impacts tree communities within these important natural habitats. To better understand the impact of urbanization on forests, we investigated the species composition, abundance, and diversity of midstory and canopy trees as well as tree seedlings in urban and rural natural parks in and around Cleveland, Ohio. We found that both urban and rural natural parks have similar tree abundance, but midstory and canopy trees as well as tree seedling communities in the urban natural parks included higher abundances of stress-tolerant species compared to rural parks. In addition, this pattern was driven by changes in native tree species, as we observed low abundance of invasive species. More stress-resistant native species in urban areas include Quercus rubra and Prunus serotina, in contrast to rural natural parks which are dominated by Acer spp. and Fagus grandifolia. Lastly, we show that urban and rural natural parks have similar species diversity within plots, but we found higher variation in community composition among urban natural parks compared to among rural parks. Furthermore, Q. rubra and P. serotina were significantly larger in rural natural parks, indicating that both environmental stress and successional stage could drive compositional differences. Thus, we show that urbanization can have unexpected effects on plant community composition and diversity. Our study refutes the idea that these are degraded habitats, highlights the need to conserve them, and suggests that characterization of local variation in self-assembled urban tree communities will provide the most accurate picture of their management needs and potential ecosystem services.     

Can canopy temperature acquired from an airborne level be a tree health indicator in an urban environment?

Nowadays, gathering information about tree health conditions in cities is necessary. Trees are essential in regulating urban microclimate and mitigating the urban heat island effect. Therefore, their health status should be crucial in urban vegetation monitoring. The growing number of new cameras, sensors and research methods allows for a broader application of thermal data in remote sensing vegetation studies. This research aimed to evaluate whether it is possible to use thermal infrared data to assess the health condition of selected species of deciduous trees in an urban environment. More specifically, the data must have a 3.6–4.9 µm spectral range, obtained during the day and the night. For this purpose, research was carried out in the city center of Warsaw (Poland) in 2020. During the airborne data acquisition, thermal data, laser scanning and RGB images were collected. Synchronously with airborne data, 617 ground references were obtained in different health condition classes (healthy, slightly poor condition, poor condition and dying) for five tree species: Acer platanoides, Acer pseudoplatanus, Aesculus hippocastanum, Tilia cordata and Tilia × euchlora. The results were as follows: (i) healthy trees were cooler than trees in poor condition and dying both during the daytime and nighttime; (ii) the difference in the canopy temperatures between healthy and dying trees was 1.06 °C of mean value on the nighttime data and 3.28 °C of mean value on the daytime data; (iii) all condition classes significantly differ from each other on daytime thermal data. The aerial thermal data can be considered a new alternative to hyperspectral data. Thermal sensing represents another method of assessing the health condition of trees in an urban environment – especially data obtained during the day, which can differentiate condition classes better than data obtained at night. The method based on thermal infrared and laser scanning data fusion could be a quick and efficient solution for identifying trees in poor health.