Urban Forest Management Research Articles

Impacts of Leaf Surface Micromorphology Variation on the Ability to Capture Particulate Matter

As the most important carrier of atmospheric particles captured by plants, the differences in micromorphology characteristics and leaf roughness are important determinants of particle capture capacity. Leaf micromorphology usually changes with growth (internal factor), and with environmental pollution intensity (external factor). The existing dust-spray simulation was always short; however, the leaf micromorphology changes had a clear delayed response, and therefore its results could not reflect the micromorphology changes caused by internal and external factors that influence the particulate capture capacity of leaves. In the present study, new and old leaves were used to study leaf growth, and different pollution source conditions were selected to study pollution intensity under natural conditions, to analyze the changes in leaf surface micromorphology and their impacts on particulate capture capacity. It was found that the amounts of TSP, PM10, PM2.5, and PM1 on the old leaves of three evergreen trees (Taxus cuspidata var., Platycladus orientalis, and Pinus tabuliformis) were higher than those of the new leaves, and the amounts of the particles with respect to the old leaves increased with leaf growth. Moreover, there were significant differences between the new and old leaves regarding the captured amount of different-sized particles. The increase in needle roughness (Rq) of the three evergreen trees, caused by growth, was the main factor that led to an increase in particle capture capacity for old leaves. The TSP and PM10 captured amounts of P. orientalis, P. tabuliformis, Sophora japonica, Populus tomentosa, and Ginkgo biloba were higher in the heavily polluted area than in the clean area. The amounts of PM2.5 and PM1 captured by P. tabuliformis, G. biloba, and P. orientalis in the heavily polluted area were higher than those in the clean area; however, the amounts of PM2.5 and PM1 captured by S. japonica and P. tomentosa in the clean area were higher than those in the heavily polluted area. Pollution intensity very significantly affected the capture capacity of TSP, PM10, and PM2.5 by leaves, as well as significantly affecting the capture capacity of PM1. This was mainly caused by the leaf micromorphology changes found in the heavily polluted area, such as stomatal index decrease, waxy layer degradation, more irregular surface texture and boundaries of the epidermal cells, and longer and hardened trichomes. These changes caused the Rq values to be generally higher in the heavily polluted area than in the clean area, and the roughness of the abaxial surface increased more notably than that of the adaxial surface. These results will provide data support for further revealing the driving factors of particulate matter capture capacity of leaves and proposing more scientific urban forest management measures to improve their particulate matter removal function.

Hot routes in urban forests: The impact of multiple landscape features on recreational use intensity

It is well known that both built and natural landscape features contribute to recreational values of forests. Insights on visual preferences and visitor behaviour are used to meet societal demands for outdoor recreation in forests. However, there is a lack of knowledge on the hierarchy of importance of landscape features that characterise the surroundings of recreational routes for explaining activity-specific use intensity. Furthermore, urban forest managers lack reliable spatial information on which areas are most intensively used for recreation. Therefore, using Public Participation GIS (PPGIS), we invited residents of three densely populated regions in Germany’s Southwest to map their recreational routes in urban forests and report the respective type of activity. Overall, 1136 respondents participated in our study and mapped 2468 routes. We identified two main user groups – cyclists and pedestrians – and created maps that visualise their use intensity. We found recreational use intensity patterns differ for both the three study areas and type of activity. We used linear mixed effects models to identify the contribution of landscape features to overall, cyclists’, and pedestrians’ use intensity. Therefore, we measured area sizes of forest structural attributes, natural area features, and human-made infrastructure for each surrounding area of mapped routes (defined by a 50 m radius). For each mapped route, we calculated the total length of other routes that were within its surrounding area to operationalise recreational use intensity. Results showed that water bodies, broadleaved dominated stands, and unique structural compositions (represented by protected habitats) were among the most important landscape features that explained overall, cyclists’, and pedestrians’ use intensity. We found differences in the importance of landscape features for use intensities between cyclists and pedestrians. Our findings add to previous research since we present a hierarchy of importance of 14 landscape features for explaining residents’ self-mapped recreational behaviour in urban forests. Urban forest managers can use these results to promote outdoor recreation. Furthermore, our hot route maps may help integrating economic, ecological, and social objectives into management plans.

Ecosystem Service-Based Sensitivity Analyses of i-Tree Eco

"Trees are known to provide various ecosystem services and disservices to urban communities, which can be quantified using models based on field and environmental data. It is often uncertain how tree structure and environmental variables impact model output. Here we perform a sensitivity analysis (SA) of i-Tree Eco, a common urban forest model, to analyze the relative impact of different model inputs on three module outputs: biogenic volatile organic compound (BVOC)(isoprene and monoterpenes) emissions, carbon storage and sequestration, and dry deposition of nitrogen dioxide, sulfur dioxide, and ozone. The SA methods included novel applications of the Morris one-at-a-time method and a variance-based decomposition method, which integrates Monte Carlo simulation with Latin hypercube sampling and Iman Conover analysis. A case study was performed in New York City, New York, USA, with field plot data collected in 2013. Genus has the largest influence on BVOC emissions by determining base emission rates and its high interactions with other input factors, and BVOC emissions are sensitive to leaf biomass in a concave manner and temperature in a convex manner, while isoprene emissions show a strong linear relationship with photosynthetically active radiation (PAR). Diameter at breast height plays the most important role for both carbon storage and sequestration estimators; crown light exposure and tree condition are also important for carbon sequestration. Dry deposition velocity is sensitive to leaf area index and relative humidity in a nearly linear way, while sensitive to temperature and PAR in a concave manner. The results provide guidance to facilitate future field plot campaigns and model development. The knowledge revealed by the SA is also beneficial for model uncertainty reduction, which in turn facilitates more effective urban forest management and decision-making.

Visiting the Forest with Kindergarten Children: Forest Suitability

By providing ecosystem services, urban forests contribute significantly to the well-being of urban populations. Urban forests, along with other urban green spaces, are often the closest natural environment in the city where a child can play. The majority of pre-school children spend a large part of the day in kindergarten, which means that forest visits should have a prominent place in the kindergarten curriculum. Therefore, this study focuses on making the forest more suitable and thus more accessible for visits with children. The first goal of the research is to identify teachers’ preferences for the forest environment they visit with a group of pre-school children. The second goal is to present a forest suitability model for a visit with kindergarten children based on the teachers’ preferences. Based on the research survey conducted among the teachers in Slovenian public kindergartens, we formed and evaluated the criteria for the construction of a model of forest suitability for a visit with children. As the most important requirement for visiting a forest, the teachers note its proximity. They prefer a mature, mixed forest, with a bit of undergrowth, dead wood, and a presence of water and a meadow. Based on the identified criteria, we used the multi-criteria evaluation method in the GIS-environment in order to build a model of urban forest suitability for a visit with kindergarten groups of children in the study area of the City of Ljubljana, Slovenia. The results are useful in urban forest planning and management to ensure better forest suitability and accessibility for visits by children. Suitability maps can be used as one of the spatial foundations necessary for an integrated urban forest planning with emphasis on social functions. The model can be adapted beyond Slovenia to different spatial and social requirements and contexts.

Factors affecting the planning and management of urban forests: A case study of Istanbul

This study aims to focus on a case study of Istanbul province in order to reveal the most important factors affecting the planning and management of urban forests by means of a multidimensional approach. First of all, 67 variables, which affected the planning and management of urban forests, were developed by taking the literature review and expert opinions into consideration. These variables were grouped under five main headings, and questionnaire forms were prepared accordingly. The questionnaire forms were applied to 201 people from three different stakeholder groups through face-to-face interviews. In the study, a factor analysis was conducted with 67 variables, and approximately 71 % of the respondents' opinions on the planning and management of urban forests were explained with 8 factors by taking 32 variables as basis, as a result of the reliability analysis. According to their level of significance, these factors are as follows: (1) spatial functions, activities and main objective, (2) use of space, (3) problems caused by management, (4) budget and staff shortages, (5) garden types, (6) R&D activities, (7) education, knowledge and experience deficiencies and (8) provision of environmental and social benefits. In addition, whether there was a statistically significant difference between the various socio-economic variable groups specified within the scope of the questionnaire in terms of the dimensions (factors) perceived by the respondents was explored using non-parametric tests, Kruskal-Wallis H test and Mann-Whitney U test Linear regression analysis was also conducted in order to determine how and to what extent the most important factors affecting the planning and management of urban forests affected the basic purpose of urban forests. Accordingly, this study puts forward the main aim of urban forests in terms of their functions as 'providing environmental and social benefits', 'providing an environment for scientific researches and nature education' and ‘meeting the recreational and social needs of urban people’.

Detecting Long-Term Urban Forest Cover Change and Impacts of Natural Disasters Using High-Resolution Aerial Images and LiDAR Data

Urban forests provide ecosystem services; tree canopy cover is the basic quantification of ecosystem services. Ground assessment of the urban forest is limited; with continued refinement, remote sensing can become an essential tool for analyzing the urban forest. This study addresses three research questions that are essential for urban forest management using remote sensing: (1) Can object-based image analysis (OBIA) and non-image classification methods (such as random point-based evaluation) accurately determine urban canopy coverage using high-spatial-resolution aerial images? (2) Is it possible to assess the impact of natural disturbances in addition to other factors (such as urban development) on urban canopy changes in the classification map created by OBIA? (3) How can we use Light Detection and Ranging (LiDAR) data and technology to extract urban canopy metrics accurately and effectively? The urban forest canopy area and location within the City of St Peter, Minnesota (MN) boundary between 1938 and 2019 were defined using both OBIA and random-point-based methods with high-spatial-resolution aerial images. Impacts of natural disasters, such as the 1998 tornado and tree diseases, on the urban canopy cover area, were examined. Finally, LiDAR data was used to determine the height, density, crown area, diameter, and volume of the urban forest canopy. Both OBIA and random-point methods gave accurate results of canopy coverages. The OBIA is relatively more time-consuming and requires specialist knowledge, whereas the random-point-based method only shows the total coverage of the classes without locational information. Canopy change caused by tornado was discernible in the canopy OBIA-based classification maps while the change due to diseases was undetectable. To accurately exact urban canopy metrics besides tree locations, dense LiDAR point cloud data collected at the leaf-on season as well as algorithms or software developed specifically for urban forest analysis using LiDAR data are needed.

Urban Trees and Human Health: A Scoping Review.

The urban forest is a green infrastructure system that delivers multiple environmental, economic, social and health services, and functions in cities. Environmental benefits of urban trees are well understood, but no review to date has examined how urban trees affect human health. This review provides a comprehensive summary of existing literature on the health impacts of urban trees that can inform future research, policy, and nature-based public health interventions. A systematic search used keywords representing human health, environmental health, and urban forestry. Following screening and appraisal of several thousand articles, 201 studies were conceptually sorted into a three-part framework. Reducing Harm, representing 41% of studies, includes topics such as air pollution, ultraviolet radiation, heat exposure, and pollen. Restoring Capacities, at 31%, includes attention restoration, mental health, stress reduction, and clinical outcomes. Building Capacities, at 28%, includes topics such as birth outcomes, active living, and weight status. The studies that were reviewed show substantial heterogeneity in purpose and method yet indicate important health outcomes associated with people’s exposure to trees. This review will help inform future research and practice, and demonstrates why urban forest planning and management should strategically promote trees as a social determinant of public health.

Discriminating tree species at different taxonomic levels using multi-temporal WorldView-3 imagery in Washington D.C., USA

With the promise of transformative changes for the management of rural and urban forests, the discrimination of tree species from satellite imagery has been a long-standing goal of remote sensing. For the species-rich urban setting of Washington, D.C. USA, we evaluate current prospects toward this goal by combining a Random Forest (RF) object-based tree species classification method with two large datasets 1) A suite of 12 very high resolution (VHR) WorldView-3 images (WV-3), whose image acquisition date cover each pheno-phase of the growing season from April to November; and 2) the 16,496 street trees from Washington D.C. Department of Transportation's (DDOT) field inventory. We classify the 19 most abundant tree species with an overall accuracy of 61.3% and classify the ten most abundant genera with an overall accuracy of 73.7%. We observe that (1) there are larger declines in accuracy when attempting to classify species in the same genus, and (2) the most valuable phenological period is fall senescence for classification at different taxonomic levels. Especially if satellite data can be matched to the key pheno-phases, our study highlights that current VHR satellite sensors now have the radiometric, spectral, and spatial resolution to potentially help manage species-rich urban forests.

The use of information and infocommunication technologies in the management of urban forests of St. Petersburg using geographic information systems

The article considers the possibility of using infocommunication technologies in the management of urban forests. There are schemes and models of integration the Internet of things into geoinformation systems for making managerial decisions that contribute to the care of green spaces in the city of St. Petersburg.

Assessment of skills needed in entry-level urban foresters in the USA

Urban forestry is an interdisciplinary field of science and a profession that directly manages green infrastructure. There are many significant benefits to a properly managed urban forest resource, managers need to be appropriately prepared to successfully manage their resources. We conducted a mixed-mode survey that asked employers what skills they were looking for when they hired entry-level urban foresters and if recent hires possessed these skills. The survey was mailed to municipal urban forest managers at the top 200 most populous cities in the United States and was available online as a snowball survey. Most of the skill ratings for entry-level urban foresters in this study were positive. It appears that academic programs are meeting much of the needs for entry-level urban foresters as important-performance analysis found that employers felt most of the urban forestry, arboriculture, & forestry skills were being adequately met. Yet there was room for improvement in skills such as site plan review, project management, conflict resolution and community outreach. Interestingly, accredited degree programs were not valued in this survey, while some professional certifications and licenses were valued.

Urban Forestry in Brazilian Amazonia

Urban forests provide multiple benefits in improving people’s lives and can be an important tool for achieving the goal of carbon neutral cities. In this study, we analyzed the diversity of plant species from urban forests in cities in the Brazilian Amazonia, based on data from scientific articles, through a systematic literature review. Our analysis revealed that 530 taxa, of which 479 were identified at the species level and 51 at the genus level, covering 38,882 individuals were distributed in 29 cities. The three most frequent species were Ficus benjamina, Mangifera indica, and Licania tomentosa. Exotic species were more frequent than native. The three most frequent species had almost 42% of the inventoried individuals. The choice of species has been made mainly by the local population, without monitoring by the public authorities. Recommendations for sustainable management of urban forests in Amazonia include investing in training of management bodies, periodic inventories, and awareness actions about the benefits of urban green infrastructure and on the advantages of native species. Policies for the sustainable management of urban green areas are necessary. The municipal governments must continuously monitor indicators of urban ecosystem services and provide financial resources for maintaining and increasing those area rates per person.

Analyzing Potential Tree-Planting Sites and Tree Coverage in Mexico City Using Satellite Imagery

Locating potential tree-planting sites and analyzing tree canopy cover is important in the planning and management of urban forests. This paper reports the quantification of potential planting sites as well as tree canopy cover in the urban area of Mexico City, estimated by means of SPOT (Satellite Pour l’Observation de la Terre) 6 satellite images and a supervised pixel-based classification approach. Results showed an estimated area of 3100.7 ha of potentially useful sites, including places with bare soil and grass-covered areas such as median strips, roundabouts and parks. An average tree canopy cover of 10.6% and an average impervious surface of 79.2% for the 15 boroughs were also analyzed. The area of potential planting sites would represent a 5% gain for the current tree canopy cover if it were to be planted. With an overall accuracy of 92.4%, the use of both images from the SPOT 6 sensor and the classification approach proved to be appropriate for obtaining thematic covers in the urban environment of Mexico City.

Preferences for ecosystem services provided by urban forests in South Korea

The existence of tradeoffs and synergies between ecosystem services emphasize the need to understand the preferences of ecosystem service beneficiaries. In this paper, the preferences of ecosystem services provided by different types of urban forests in South Korea are analyzed to provide insights on the improved distribution and supply of ecosystem services. The Delphi technique was utilized to elicit expert opinions on the categorization of ecosystem services provided by urban forests. A choice experiment on 500 Seoul citizens was then conducted to analyze the preferences for 7 types of ecosystem services – food provision, water flow regulation, noise reduction, microclimate regulation & air quality improvement, moderation & prevention of landslides, biodiversity enhancement, recreation, and health services. An AHP analysis was carried out to investigate experts’ ranking of the relative importance of these ecosystem services. The results showed that except for microclimate regulation & air quality improvement, Seoul citizens’ preferences for different types of urban forests did not differ according to the attribute level of each ecosystem service. There were also no significant differences between the preferences for urban natural parks and urban neighborhood parks, possibly indicating that Seoul citizens perceive them to be similar. Secondly, the results indicate a higher preference for urban forests with certain features, such as a higher proportion of fruit trees and deciduous trees, higher leaf area, denser tree canopy cover, wider distances between trees, and higher levels of species richness. The enhancement of biodiversity was considered the most influential service for Seoul citizens in their choice of urban forests. Seoul citizens were willing to pay 12,176 KRW/year and 21,036 KRW/year to enhance the level of biodiversity from “poor” to “average” and from “average” to “rich,” respectively. Finally, preferences and relative importance for almost all ecosystem services were different for citizens and experts. As it is impossible to maximize the provision of all ecosystem services concurrently, policymakers and urban forest managers need to consider citizens’ preferences and opinions when designing and managing urban forests in order to increase user satisfaction and welfare.

Assessing spatio-temporal changes in forest cover and fragmentation under urban expansion in Nanjing, eastern China, from long-term Landsat observations (1987–2017)

Assessing changes in forest cover and fragmentation under urban expansion and the correlation analysis between these changes can provide decision support for urban forest managers. In this study, forest cover and morphological spatial patterns (cores, islets, perforations, edges, loops, bridges, and branches) were firstly mapped by the vegetation change tracker (VCT) algorithm and morphological spatial pattern analysis (MSPA) respectively in Nanjing from 1987 to 2017. Next, the visible red and near-infrared-based built-up index (VrNIR-BI) was derived to extract urban impervious surface (UIS) areas, and the neighbourhood-based urban expansion model was proposed to describe the expansion types (edge-expansion, infilling and outlying). Finally, the relationships among the forest cover, fragmentation changes and urban expansion were determined using the Pearson correlation coefficient (r). The results showed that the distribution of forest cover in Nanjing was relatively scattered and it decreased by 94 km2, while the UIS area increased by 893 km2 from 1987 to 2017, resulting in some forests being gradually surrounded or encroached upon by UIS areas. The main forest morphological spatial pattern was identified as cores, with many small-area cores. Moreover, islets exhibited a higher proportion of 0.18, and these suggested that the fragmentation of Nanjing's forests was severe. Forest net changes had the higher correlation with cores, edges and branches. In addition, there were strong correlations between edge-expansion and cores, edges, branches with the r values greater than 0.75, which meant that most of the urban areas extended to core regions from the forest edges or branches. The derived information will help forest managers monitor forest dynamics in response to urban expansion and achieve sustainable development.

Quantifying urban forest structure with open-access remote sensing data sets

Future cities are set to face ever increasing population and climate pressures, ecosystem services offered by urban forests have been recognised as providing significant mitigation for these pressures. Therefore, the ability to accurately quantify the extent and structure of urban forests, across large and highly dynamic cities, is vital for determining the value of services provided and to assess the effectiveness of policy to promote these important assets. Current inventory methods used in urban forestry are mostly reliant on plot networks measuring a range of structural and demographic metrics; however, limited sampling (spatially and temporally) cannot fully capture the dynamics and spatial heterogeneity of the urban matrix. The rapid increase in the availability of open-access remote sensing data and processing tools offers an opportunity for monitoring and assessment of urban forest structure that is synoptic and at high spatial and temporal resolutions. Here we present a framework to estimate urban forest structure that uses open-access data and software, is robust to differences in data sources, is reproducible and is transferable between cities. The workflow is demonstrated by estimating three metrics of 3D forest structure (canopy cover, canopy height and tree density) across the Greater London area (1577 km2). Random Forest was trained with open-access airborne LiDAR or iTree Eco inventory data, with predictor variables derived from Sentinel 2, climatic and topography data sets. Output were maps of forest structure at 100 m and 20 m resolution. Results indicate that forest structure can be accurately estimated across large urban areas; Greater London has a mean canopy cover of ∼16.5% (RMSE 11-17%), mean canopy height of 8.1–15.0 m (RMSE 4.9–6.2 m) m and is home to ∼4.6 M large trees (projected crown area >10 m2). Transferability to other cities is demonstrated using the UK city of Southampton, where estimates were generated from local and Greater London training data sets indicating application beyond geographic domains is feasible. The methods presented here can augment existing inventory practices and give city planners, urban forest managers and greenspace advocates across the globe tools to generate consistent and timely information to help assess and value urban forests.

Mapping aboveground biomass and carbon in Shanghai's urban forest using Landsat ETM+ and inventory data

Quantifying the spatiotemporal distribution of forest biomass carbon (FBC) is vital for the management of urban forests in accordance with the rapid urbanization. This paper presents a method for quantifying and estimating the urban FBC in Shanghai, China, between 2005 and 2015, using data from 93 sampling forest plots and Landsat ETM + data. Our study included an analysis of the choice of predicted factors to estimate FBC and the method of carbon density estimation employed in the estimation. The results showed that combining regression analysis and spatial analysis to map forest carbon stocks at city level make available FBC estimates for the urban forests of Shanghai, China. Based on the proposal method, there was a decreasing trend of carbon density from downtown areas to outer suburban areas. About 92 % of the overall FBC storage in Shanghai distributed in the suburban areas whereas the urban areas shared a fraction amounting to only 8 % in 2015. From 2011–2015, the total urban forest carbon storage gradually increased by 32.3 %, whereas the average carbon density gradually decreased by 8.21 % in the urban areas. The associated values both increased continuously from 2005–2011, from 2005 to 2011, but the average carbon storage density decreased in the suburban districts. The total carbon stocks in the estimated forest biomass across Shanghai were about 1.5 Tg in 2005 and 2008, and 1.7 Tg in 2011 and 2015, while the associated average FBC density remained at about 17.5 t/ha from 2005 to 2015. This study provides important information required to manage the urban forest stand for optimal carbon sequestration.

Restoration and Management of High-Use Urban Missouri Woodlands and Forests in St. Louis

St. Louis City’s urban woodland and forested natural areas were modified, degraded, and/or overly-mature habitats requiring management intervention for ecological health, species diversity, and public safety. To accomplish long-term success in Forest Park’s woodlands and forests, restorations and management strategies seeking to “treat the problem not the symptom” was implemented. The most important best management practices for Forest Park’s woodlands and forests included forest stand improvement, prescribed burns, invasive and non-native species management, creation of public stewards, and plant material supplementation.

Tree canopy cover and carbon density are different proxy indicators for assessing the relationship between forest structure and urban socio-ecological conditions

Abstract Forest canopy cover and carbon density are two pivotal biophysical parameters for assessing urban forest structure and its ecosystem services. While canopy cover (horizontal structure) has been extensively studied for understanding the relationship between socio-ecological dynamics and urban forests, carbon density (vertical structure) received little attention in the urban setting. The goal of this study was twofold: (i) exploring the differences between canopy cover and carbon density, and their relationships with socio-ecological factors across an urbanizing landscape, and (ii) assessing the effect of neighborhood category (i.e., low, medium and high development intensity) on the relationships at the neighborhood level. We used Mecklenburg County located in the Charlotte Metropolitan area of North Carolina, United States as a case study area, where rapid urban sprawl has fragmented the pine-oak-hickory dominated forests into a range of low to high housing density neighborhoods. We observed two major findings. First, canopy cover and carbon density demonstrated a generally weak correlation across various types of residential neighborhoods, although such relationship became relatively stronger in areas featuring a higher level of development intensity. Second, ecological factors (e.g., landscape spatial patterns) were found to dominate the statistical models explaining the variance in both canopy cover and carbon density compared to urban socioeconomic factors (e.g., income and age). However, the models and the explanatory factors were different for the two forest parameters, and they varied across neighborhoods of diverse development intensities. Based upon these findings, we argue that canopy cover and carbon density are different proxy indicators of forest functioning in the urban setting, and should be independently treated in urban forest management. The best management practices should be developed at the inner-city, neighborhood level, rather than the typical city level, owing to the significant, variable influence of socio-ecological conditions across neighborhood types.

Tree species identity and forest composition affect the number of oak processionary moth captured in pheromone traps and the intensity of larval defoliation

AbstractPure forests are often seen as being more prone to damage by specialist pest insects than mixed forests, and particularly mixed forests associating host and nonhost species. We addressed the effect of tree diversity on oak colonization and defoliation by a major specialist pest, the oak processionary moth (OPM) We quantified the number of male OPM moths captured and larval defoliation in pure stands of two oak host species (Quercus robur and Quercus petraea) and in mixed stands associating the two oak species or each oak species with another nonhost broadleaved species. We conducted two complementary studies to test the effect of host species and stand composition: (i) we used pheromone trapping to compare the number of males OPM captured throughout the distribution of oak hosts in France and (ii) we noted the presence of OPM nests and estimated defoliation in mature forests of north‐eastern France. Oak species and stand composition significantly influenced the number of male OPM captured and defoliation by OPM larvae. Quercus petraea was consistently more attractive to and more defoliated by OPM than Q. robur. Both oak trees were attacked more in pure stands than in mixed stands, in particular mixed stands associating oaks with another (nonhost) broadleaved species. The results of the present study support the view that mixed forests are more resistant to specialist pest insects than pure stands, and also indicate that this trend depends on forest composition. Our study provides new insights into OPM ecology and has potential implications for forest management, including the management of urban forests where OPM causes serious human health issues.

How Are Managers Making Tree Species Selection Decisions in the Pacific Northwest of the United States?

Trees provide an array of social, economic, and ecological benefits; furthermore, trees on public land are critical for providing those benefits to people who cannot afford their own trees. It is important to know how managers make trade-offs and prioritize different tree selection criteria in order to target educational campaigns at the state or regional level. Primary contacts for Tree City USA designated cities were surveyed across the Pacific Northwest. Of these municipalities, 79 out of 151 responded (52.3% response rate), with 6 municipalities providing responses from different departments for a total of 85 responses. Currently, there are primarily descriptive statistics in relation to tree species selection. This study provides a framework for future statistical analysis and greater exploration of how municipalities and managers are selecting tree species. Results were analyzed with a Mann-Whitney U test to compare International Society of Arboriculture (ISA) Certified Arborists® to those who are not certified across various tree species selection criteria. Another Mann-Whitney U test was used to compare small (≤ 50,000) and large (> 50,000) municipalities across the same criteria. ISA Certified Arborists® showed statistically significant differences from those who are not certified in a number of tree species selection criteria. ISA Certified Arborists® also differed in urban forest management on a city-wide scale, particularly in favoring greater tree species diversity. The differences in urban forest management between ISA Certified Arborists® and noncertified—and between municipality sizes—can help to influence future educational campaigns targeted toward increasing urban forest health and resiliency.