Tree Characteristics Research Articles

Evaluation of Dynamic Properties of Trees Subjected to Induced Vibrations

The preservation of trees in urban and archeological areas is a theme of particular relevance. Modern systems of monitoring, together with approaches for deriving the main characteristics of trees influencing their response toward extreme events, are nowadays at the basis of a growing number of studies. The aim of the present paper is the dynamic identification of trees carried out by employing an approach which combines a simple data-acquisition system, direct and ambient sources of excitation, and different data-processing methods. In particular, using a single accelerometer placed at different sections of the trunk and considering excitations induced by either pulling tests or ambient vibrations, the derivation of the main frequencies and levels of modal damping characterizing the dynamic response of a sour cherry tree (Prunus cerasus) is carried out. A finite element model of the tree is also carried out to support the validation of the proposed approach and further analyze the derived outcomes. The obtained results underline the feasibility of the proposed approach in deriving information useful for assessing the behavior of trees toward dynamic actions and, consequently, of particular relevance for the identification of possible damages induced by variations in terms of dynamic characteristics (frequencies) and damping.

Young Generations’ Perception of the Role of Deadwood in Forests: Comparison between Italy and Türkiye

The recreational value of a forest is related to the degree of naturalness that can be measured by considering qualitative and quantitative characteristics of deadwood and habitat trees. Forest user groups’ knowledge and opinions towards forest naturalness can support decision-makers in defining strategies. Among user groups, the literature shows a knowledge gap regarding the new generations’ perceptions and opinions related to biodiversity conservation. The aim of this study is to investigate young generations’ perception and preferences towards deadwood in forests. A questionnaire was developed and administrated online—in Italy and Türkiye—to a sample of university students under 25 years old. A total of 407 questionnaires (187 in Italy and 220 in Türkiye) were collected and processed. The results show that students from both countries have a high level of knowledge of deadwood and its role in forests. Most respondents perceive standing dead trees in forests to be aesthetically negative, while large lying deadwood is perceived as aesthetically positive. The attention of young generations towards issues related to biodiversity conservation is confirmed by the significance given in both countries to the management strategy that closely aligns with natural processes of mortality in undisturbed forests, where deadwood is allowed to remain without removal.

Understanding the effects of tree-crop intercropping systems on crop production in China by combining field experiments with a meta-analysis

CONTEXTTree-crop intercropping (TCI) systems have many environmental benefits in addition to providing direct economic benefits from trees and crops. An increasing number of field experiments have provided rich basic data on crop production in TCI systems in China. However, there are fewer quantitative analysis studies on a national scale. OBJECTIVEThe purpose of this study was to investigate the effects of TCI systems on crop production in China by combining field experiments with a meta-analysis, and to understand whether the results of the field experiments and the national scale meta-analysis are consistent. METHODSThis study consists of field experiments and a national-scale meta-analysis. In the field experiments, three TCI systems were designed with different tree species configurations in Dafeng District, Yancheng city, Jiangsu Province, China, to investigate their effects on the crop yield when compared with a sole cropping system. Furthermore, we conducted a meta-analysis of 36 studies with 94 comparisons in Chinese fields to examine the effects of TCI systems on crop yields and to explore how climatic conditions, crop species, tree species, and tree characteristics affect crop yields in TCI systems. RESULTS AND CONCLUSIONIn the field experiments, TCI systems had negative effects on crop yield, and understory crop yield was affected by the tree species in the TCI systems; the crop yield in the three TCI systems was 18.9–32.2% lower than that in the sole cropping system. The meta-analysis results were consistent with those of the field experiments. In the national scale meta-analysis, TCI systems had negative effects on crop yields in China (effect size = −0.488, 95% CIs = −0.576 to −0.401), and the TCI systems decreased crop yields by 38.6% overall when compared with sole cropping systems. Furthermore, the effects of TCI systems on crop yields were different among regions, climatic conditions, crop species, tree species, and tree characteristics. TCI systems should be designed carefully considering local climates, crop species, tree species, and tree characteristics to maximize agronomic and environmental benefits. SIGNIFICANCEThis study has the potential to enhance our understanding of TCI systems in China by integrating field experiments and meta-analysis. These results can inform the development of more effective and sustainable agricultural practices.

Argan tree cultivation in Algerian desert Sahara (case of Adrar Province)

ABSTRACT The morphological characteristics of the Argan tree Argania spinosa (L.) Skeels planted in the Adrar province (Sahara Desert, Algeria) in 2010 on 0.7 hectares at the Forest Experiment Station show good domestication ability. After 12 years, the recorded success rate was 20.56%. Principal Correspondence Analysis of morphological variables demonstrated five groups of 23 subjects of Argan trees. Two more sites were planted in 2016 and 2018. Success rates of 80% and 42%, respectively, have been recorded in 2021. The oil production from almonds of Argan seeds is good, showing oil recovery efficiencies of 38.27% for mechanical pressing and 59.27% for Soxhlet-assisted hexane extraction.

Longer-term mixed nut consumption improves brain vascular function and memory: A randomized, controlled crossover trial in older adults

Nut consumption may reduce age-related cognitive decline, but underlying mechanisms are unclear. To investigate in older adults longer-term effects of mixed nut consumption on brain vascular function, which may underlie improvements in cognitive performance. Twenty-eight healthy individuals (age [mean±SD]: 65±3 years; BMI: 27.9±2.3kg/m2) were included in a randomized, single-blinded, cross-over trial with a 16-week intervention (60g/d mixed nuts: walnuts, pistachio, cashew, and hazelnuts) and control period (no nuts), separated by 8 weeks of washout. Participants followed the Dutch food-based dietary guidelines. At the end of each period, cerebral blood flow (CBF), a marker of brain vascular function, was quantified using arterial spin labeling magnetic resonance imaging. Effects on endothelial function, arterial stiffness, and the retinal microvasculature were also assessed. Cognitive performance was measured using the Cambridge Neuropsychological Test Automated Battery. Body weight remained stable during the study. As compared to the control period, the mixed nut intervention resulted in a higher regional CBF in the right frontal and parietal lobes (treatment effect: 5.0±6.5mL/100g/min; P<0.001), left frontal lobe (5.4±7.1mL/100g/min; P<0.001), and bilateral prefrontal cortex (5.6±6.6mL/100g/min; P<0.001). Carotid artery reactivity (0.7PP; 95%CI: 0.2 to 1.2; P=0.007), brachial flow-mediated vasodilation (1.6PP; 95%CI: 1.0 to 2.2; P<0.001) and retinal arteriolar calibers were higher (2μm; 95%CI: 0 to 3; P=0.037), and carotid-to-femoral pulse wave velocity lower (-0.6m/s; 95%CI:-1.1 to-0.1; P=0.032). Further, visuospatial memory (-4 errors [16%]; 95%CI:-8 to 0; P=0.045) and verbal memory (+1 correct [16%]; 0 to 2; P=0.035) improved, but executive function and psychomotor speed did not change. Longer-term mixed nut consumption as part of a healthy diet beneficially affected brain vascular function, which may relate to the observed beneficial effects on memory in older adults. Moreover, different characteristics of the peripheral vascular tree also improved.

Detection of susceptible Norway spruce to bark beetle attack using PlanetScope multispectral imagery

Climate change-related acute or long-term drought stress can weaken forest ecosystems and result in widespread bark beetle infestations. Eurasian spruce bark beetle (Ips typographus L.) infestations have been occurring in Norway spruce [Picea abies (L.) Karst.]-dominated forests in central Europe including the Czechia. These infestations appear regularly, especially in homogeneous spruce stands, and the impact varies with the climate-induced water stress conditions. The removal of infected trees before the beetles leave the bark is an important step in forest pest management. Early identification of susceptible trees to infestations is also very important but quite challenging since stressed tree-tops show no sign of discolouration in the visible spectrum. We investigated if individual spectral bandwidths or developed spectral vegetation indices (SVIs), can be used to differentiate non-attacked trees, assumed to be healthy, from trees susceptible to attacks in the later stages of a growing season. And, how the temporal-scale patterns of individual bands and developed SVIs of susceptible trees to attacks, driven by changes in spectral characteristics of trees, behave differently than those patterns observed for healthy trees. The multispectral imagery from the PlanetScope satellite coupled with field data were used to statistically test the competency of the individual band and/or developed SVIs to differentiate two designated classes of healthy and susceptible trees. We found significant differences between SVIs of the susceptible and healthy spruce forests using the Enhanced Vegetation Index (EVI) and Visible Atmospherically Resistant Index (VARI). The accuracy for both indices ranged from 0.7 to 0.78; the highest among all examined indices. The results indicated that the spectral differences between the healthy and susceptible trees were present at the beginning of the growing season before the attacks. The existing spectral differences, likely caused by water-stress stimuli such as droughts, may be a key to detecting forests susceptible to early infestations. Our introduced methodology can also be applied in future research, using new generations of the PlanetScope imagery, to assess forests susceptibility to bark beetle infestations early in the growing season.

Analiza izbranih drevesnih modelov razvoja gozdov, primernih za modeliranje na velikoprostorski ravni, in možnosti njihove uporabe v Sloveniji

This article discusses single-tree growth models, which have become an important tool for decision-making, management and strategic decisions in the field of forest management. In Slovenia, we have only recently begun systematic development in the field of forest modelling, which includes the development of a matrix population model, testing selected models from abroad and the development of individual model components. The goal of our work is to introduce the field of empirical single-tree models for modelling forest development on a larger scale. We provide a detailed overview of established methods for modelling individual components of tree models, such as radial and height growth, crown recession, mortality, and recruitment and regeneration. We evaluated the suitability of the selected models from the perspective of their applicability in Slovenia. We conclude that the SILVA, WEHAM, MASSIMO and CALDIS models have the greatest potential for use in Slovenia, as they are all suitable for the different forest types and mixed forests with different structure that prevail in Slovenia. In addition to testing the existing models, we propose the development of new models adapted to the heterogeneous and mixed stands in Slovenia. We also propose expanding the set of indicators in forest inventories and measuring additional tree characteristics, such as canopy characteristics, which would expand forest modelling opportunities in Slovenia. In the conclusions, we also discuss the potential use of machine learning in forest development modelling, as this type of model could represent the next generation of forest models.

Sap flow as a function of variables within nested scales: ordinary least squares vs. spatial regression models

Understanding scale-dependent influential drivers of sap flow variability can help managers and policymakers to allocate resources within a particular scale to improve forest health and resiliency against water-stress stimuli such as drought and insects, e.g. bark beetle infestations. We defined a daily measure of sap flow as a function of variables within nested scales of landscape, stand, and tree, using ordinary least squares (OLS), spatial lag and error regression models. Model covariates were elevation, latitude (Y-coordinate), longitude (X-coordinate), neighborhood tree density, tree diameter at breast height, and bark temperature for 40-surveyed Norway spruce (Picea abies) in the Czech Republic, Central Europe. Trees were spatially distributed within 19-established subplots across five plots, with distances ranging 2–9 km, at which variations in soil water potential and temperature were limited. The daily measure of sap flow within the regional scale allowed us to avoid the temporal and spatial variability of climate effects on sap flow. A relatively flat terrain across subplots also allowed us to control the effects of slope, aspect, and topography-related solar incidence angle on sap flow. Sap flow was strongly spatially autocorrelated, so OLS models failed to take spatial autocorrelation into account unless to some extent, depending on the spatial distribution of samples, by including latitude and/or longitude in the models. Among spatial regression models, spatial error models performed better than lag models, allowing to capture the effects of unmeasured independent variables. Sap flow variability for the most part (∼70%) was explained by the landscape-level variable of elevation followed by the stand-level variable of tree density, and the remaining part by variables related to tree characteristics; a nested down-scaling function, defined and visualized for the first time. Therefore, thinning forest stands and future plantations with optimum distances, based on the elevation gradients, may be required to counterbalance the allocation of resources, e.g. water, nutrients, and light, among trees, leading to enhance forest health and resiliency against water-stress stimuli.

Simulation of English part-of-speech classification based on artificial intelligence and additive logistic regression

English part-of-speech classification technology is a technology that can process text data, can effectively solve the problem of messy data in text information categories, make data structured and organized, and facilitate people to obtain effective information implicit in the text. This article transforms the original polynomial distribution into a generalized linear model and uses logistic regression algorithm for specific implementation. Moreover, the model proposed in this paper inherits the good explanatory characteristics of the decision tree, and it locally uses logistic regression to fit the data, which greatly improves the function space that logistic regression can fit. In addition, due to changes in the decision theory of logistic regression leaf nodes, the corresponding tree branch theory also needs to be changed accordingly. Finally, this paper designs experiments to study the performance of the model constructed in this paper. The research results show that the model constructed in this paper has high accuracy in the extraction and classification of English part-of-speech features.

From tree-related microhabitats to ecosystem management: A tree-scale investigation in productive forests in Estonia

A diversity of microhabitats has been suggested to play a key role in mediating the co-occurrence of trees with specific tree-inhabiting biodiversity, which may further influence ecosystem functioning. However, this triple relationship between tree characteristics, tree-related microhabitats (TreMs), and biodiversity has not been described explicitly enough to set quantitative targets of ecosystem management. The two major approaches directly targeting TreMs in ecosystem management are tree-scale field assessment of TreMs and precautionary management, which both require insights into the predictability and magnitude of specific biodiversity-TreM relationships. To obtain such insights, we analysed tree-scale relationships between the diversity of TreM development processes (four classes: peculiarity; pathology; injury; emergent epiphyte cover) and selected biodiversity variables based on 241 live trees (age range 20–188 years) of two species (Picea abies, Populus tremula) in hemiboreal forests in Estonia. We addressed the diversity and abundance of epiphytes, arthropods, and gastropods; their specific response to TreMs was disentangled from tree age and tree size effects. We found that a relatively small improvement in the biodiversity responses studied was attributable solely to TreMs, and that such contribution was more frequently observed in young trees. Unexpectedly, several age- or size-independent effects of TreMs were negative, suggesting trade-offs with other factors of biodiversity relevance (such as tree foliage suppression due to injuries that created TreMs). We conclude that tree-scale microhabitat inventories have only limited potential to resolve the general problem of providing diverse habitats for biodiversity in managed forests. The basic sources of uncertainty are that microhabitat management is mostly indirect (managing TreM-bearing trees and stands rather than TreMs themselves) and that snapshot surveys cannot address various time perspectives. We outline a set of basic principles and constraints for spatially heterogeneous and precautionary forest management that includes TreM diversity considerations. These principles can be further elaborated through multi-scale research on functional biodiversity links of TreMs.

Incremental Bag of Words with Gradient Orientation Histogram for Appearance-Based Loop Closure Detection

This paper proposes a novel approach for appearance-based loop closure detection using incremental Bag of Words (BoW) with gradient orientation histograms. The presented approach involves dividing and clustering image blocks into local region features and representing them using gradient orientation histograms. To improve the efficiency of the loop closure detection process, the vocabulary Clustering Feature (CF) tree is generated and updated in real time using the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm, which is combined with an inverted index for the efficient selection of candidates and calculation of similarity. Moreover, temporally close and highly similar images are grouped to generate islands, which enhances the accuracy and efficiency of the loop closure detection process. The proposed approach is evaluated on publicly available datasets, and the results demonstrate high recall and precision.

Multivariate mixed-effects models for stand characteristics of hybrid aspen plantations in southern Finland and southern Sweden

Hybrid aspen, a hybrid between the European aspen and North American trembling aspen (Populus tremula L. × P. tremuloides Michx.), is a promising species because of its fast-growth and its suitability for multi-purpose use. However, models for predicting the age-dependent development of stand characteristics are still missing. The main objectives of this study were therefore to develop the models for predicting stand characteristics of hybrid aspen plantations and to validate the model applicability. The target response variables were stand basal area (BA), basal area-weighted mean diameter (DG) and basal area-weighted mean height (HG). Data were obtained from clonal hybrid aspen trials in southern Finland and southern Sweden. Multivariate mixed-effects modelling was used to estimate the parameters of seemingly unrelated regression for BA, DG, and HG. Model fit provided the following predictor variables: stand age (AGE), the number of trees per hectare (TPH), site index (SI), growing degree-days (GDD5), soil and site type, and thinning treatment. The chosen predictors differed slightly by response variable, but all parameters were highly significant (P < 0.0001), and model goodness-of-fit statistics presented high accuracy: RMSE of 2.59 m2 ha−1 for BA, 1.21 cm for DG, 1.05 m for HG in arithmetic scale. The applied simulations illustrated clear differences in the predicted development of stand characteristics when input variables SI, TPH or GDD5 changed. The developed models were assessed to be easily applicable and useful for predicting the stand and tree characteristics of clonal hybrid aspen plantations, especially for the stands with AGE ≤ 30 years and TPH ≤ 2000 trees ha−1.

Topological and spatial analysis of within-tree fruiting characteristics for walnut trees

Shoot morphology and canopy position usually have a significant impact on fruiting potential, but these effects have not been fully quantified, especially at the whole tree level. This study addressed the fruit number variation as affected by shoot length and within-tree position for mature walnut trees cv. Chandler, which is a lateral bearing variety. A positive relationship was observed between parent shoot (previous-year) length and the number and length of current-year floral shoots, as well as between the length of current-year floral shoots and fruit number per floral shoot. Fruit number and spatial position in defoliated trees were manually identified based on LiDAR data, but tree architecture, including shoot length and topology, was not accurate to be reconstructed by the available software (TreeQSM). About half of fruits were located in the outer canopy, while the reminder, especially at the mid-canopy height, were equally distributed inside the canopy to a depth of about 90 cm. The topological fruit location at the whole tree level were manually quantified in relation to the length and relative node rank of parent shoots. Even though long parent shoots exhibited more lateral bearing, the majority of fruits at the whole tree level were on current-year floral shoots that developed from the terminal buds of relatively short (<=10 cm) parent shoots because these represented the vast majority (over 90%) of parent shoots on mature trees.

Characterization of key sweet taste compounds in Camellia nanchuanica black tea

Camellia nanchuanica gained attention for having original tea tree characteristics and producing black tea with appealing sweetness. To better study the sweet taste of Camellia nanchuanica black tea, 30 kinds of Camellia nanchuanica black tea (NCBT) samples were classified into three types (high, middle and low sweetness) according to the differences in sweetness. A total of 844 metabolites were detected in NCBT; among them, there were 155 differential metabolites. Four differential metabolites (phloridzin, dulcitol, l-alanine, and sucrose) positively correlated with sweetness and showed higher VIP (variable importance for the projection) values (>1), which made main contributions to the sweetness of NCBT. Phloridzin and l-alanine might be the key sweet compounds of NCBT due to higher DoT (dose-over-threshold) values. Addition experiments further verified that phloridzin was the key sweet taste compound because phloridzin significantly increased the sweet taste of low sweetness samples. Notably, although NCBT24, 26, and 28 belonged to high sweetness samples, phloridzin content was lower. Based on the interactions of binary mixture, hyper-addition effects of phloridzin, dulcitol, l-alanine, and sucrose existed in NCBT24, 26 and 28.

Nut, Kernel and Tree Characteristics of Selected Seed Propagated Almonds (Amygdalus communis L.) in Datca Peninsula

Nut, Kernel and Tree Characteristics of Selected Seed Propagated Almonds (Amygdalus communis L.) in Datca Peninsula

Flowering in ‘Honeycrisp’ Apple Shows That Spurs Are Semiautonomous Organs

Irregular flowering and biennial bearing are challenging in many apple (Malus ×domestica) cultivars such as Honeycrisp. Apple flowering is influenced by many factors including crop load, fruit weight, seed number, and bourse shoot length. However, it is unclear how these factors exert their control. We investigated flowering in ‘Honeycrisp’ and whether flower formation is regulated locally within the spur or if it is under the control of the whole tree system. Treatments consisting of 30 to 240 fruit per tree with one or two fruit per spur were applied, and seed number, fruit weight, bourse shoot length, bourse number, and resulting flower formation measured. In 2013, flowering was affected by fruit number per tree, fruit number per spur and their interaction, and with lower total tree crop loads, spurs bearing two fruit had fewer flowers than those with a single fruit. In 2014, few spurs formed flowers regardless of treatment. In 2013, flowering was unaffected by seed number on single-fruited spurs but flowering inhibition was correlated with fruit weight. In spurs bearing two fruit, flowering was inhibited by higher seed numbers but fruit weight per spur had no effect on flowering. Our data suggest that both whole tree and within-spur characteristics contribute to local flower formation. Therefore, ‘Honeycrisp’ spurs can be considered semiautonomous organs because inhibition of flower formation appears to be related to the depletion of resources both locally within the spurs, and systematically within the whole tree. The main factors associated with flower formation were fruit number per tree, fruit number per spur, bourse shoot length, and bourse number per spur. In contrast to previous reports, our data show that seeds do not play a direct role in regulating flower formation.

Using Synthetic Tree Data in Deep Learning-Based Tree Segmentation Using LiDAR Point Clouds

Deep learning, neural networks and other data-driven processing techniques are increasingly used in the analysis of LiDAR point cloud data in forest environments due to the benefits offered in accuracy and adaptability to new environments. One of the downsides of these techniques in practical applications is the requirement for manually annotated data necessary for training neural networks, which can be time consuming and costly to attain. We develop an approach to training neural networks for forest tree stem segmentation from point clouds that uses synthetic data from a custom tree simulator, which can generate large quantities of training examples without manual human effort. Our tree simulator captures the geometric characteristics of tree stems and foliage, from which automatically-labelled synthetic point clouds can be generated for training a semantic segmentation algorithm based on the PointNet++ architecture. Using evaluations on real aerial and terrestrial LiDAR point clouds from a range of different forest sites, we demonstrate our synthetic data-trained models can out-perform, or provide comparable performance with models trained on real data from other sites or when available real training data is limited (increases in IoU from 1–7%). Our simulation code is open-source and made available to the research community.

Changes in Growth, Fruit Quality, and Leaf Characteristics of Apple Tree (Malus domestica Borkh. ‘Fuji’) Grown under Elevated CO2 and Temperature Conditions

Changes in Growth, Fruit Quality, and Leaf Characteristics of Apple Tree (Malus domestica Borkh. ‘Fuji’) Grown under Elevated CO2 and Temperature Conditions

Where to fish in the forest? Tree characteristics and contiguous seagrass features predict mangrove forest quality for fishes and crustaceans

Abstract Mangroves often support rich fish and crustacean communities, although faunal abundance and diversity show strong spatiotemporal variability. Consistent patterns in mangrove animal communities might be dictated by forest characteristics, by seascape context or by some combination of these factors. Predicting drivers of spatial heterogeneity in mangrove faunal communities can better support the zoning of forests for management purposes, for example by identifying sites important for fisheries nursery provision. We sampled 14 sites within a large (4000 ha) mangrove forest in Kenya, quarterly over a period of 2 years. There were clear and consistent differences in the quality of sites for fish and crustacean abundance and diversity. Forest characteristics (as summarised by the complexity index, CI) and seascape metrics (the presence, area and configuration of contiguous seagrass) were strong predictors of site differences. However, they showed opposite influences on dominant members of the fish and crustacean faunas, with CI correlated negatively with fishes and positively with crustaceans, and seagrass area correlated positively with fishes and negatively with crustaceans. Synthesis and applications. Sites within the same mangrove forest exhibit consistent differences in fish and crustacean abundance. However, the fish and crustacean communities (and particularly dominant species within them) act differently in response to forest and seascape characteristics. Old growth, mature forest, set in a seascape of seagrass patches with bare sediment, was associated with highest crustacean abundance. In contrast, denser smaller trees and seascapes with larger, continuous areas of seagrass correlated better with fish abundance. Zoning for management, as mandated in new Kenyan policy, will need to consider these differences in seascape use between fish and crustaceans.

Predictors of tropical cyclone-induced urban tree failure: an international scoping review

BackgroundTrees are critical components of rural and urban ecosystems throughout the world. While they have adapted to the historic conditions of their native environments, climate change, urbanization, and human-assisted range expansion may test the storm resiliency of many tree species.ObjectiveIn this global multilingual scoping review, we investigate a range of intrinsic (i.e., tree characteristics) and external (i.e., environmental and management) factors which have been used to predict tree failure during tropical cyclones.DesignWe searched online databases and journals in English, Chinese, French, Japanese, Portuguese, and Spanish to find peer-reviewed papers and dissertations. We retained papers that used ground-based methods to study tree damage following a tropical cyclone and conducted a statistical analysis of factors that influence tree resistance to damage. From each paper we extracted details of study methods, and the relationships between damage and predictors.ResultsOur efforts generated 65 peer-reviewed papers and dissertations that met our final criteria for inclusion (i.e., data on the relative proportion of trees failed/intact as assessed no more than a year after the storm event). Of these papers 37 independent variables were assessed to predict tree failure. Research in both urban and rural settings tends to be concentrated in regions frequently impacted by tropical cyclones. Characteristics of species such as wood density have been studied in rural environments and are also relevant predictors for tree failure in urban trees. Environmental characteristics unique to urban settings such as planting areas surrounded by pavement need further research. Several urban studies demonstrate that risk assessment methods can predict tree failure during a storm.ConclusionResults can be used by future storm researchers to identify both predictors may warrant inclusion in their models as well as predictors which have yet to be tested. Results can also inform planning and activities that can mitigate tropical cyclone damage to the urban forest.