Ecosystem Services Synergies and Trade-Offs from Tree Structural Perspectives: Implications for Effective Urban Green Space Management and Strategic Land Use Planning

Abstract

Urban green spaces (UGSs) are critical in providing essential ecosystem services (ESs) that enhance the quality of life of urban communities. This study investigated the synergies and trade-offs between structural characteristics of urban trees and their ecosystem services and their implications for urban park management within Yurim Park, Daejeon, South Korea, using the i-Tree Eco tool. The study specifically focused on regulating and supporting services, assessing diversity, air pollution removal, carbon sequestration, and avoiding runoff. A systematic review of urban park management practices complemented the empirical analysis to provide comprehensive management recommendations. The findings of a total of 305 trees from 23 species were assessed, revealing moderate species diversity and significant variations in structural attributes, such as diameter at breast height (DBH), leaf area index (LAI), and crown width (CW). These attributes were found to be strongly correlated with ES outcomes, indicating that healthier and larger trees with extensive canopies are more effective in providing benefits such as pollution removal, runoff reduction, and carbon sequestration. However, the study also identified trade-offs, particularly regarding volatile organic compound (VOC) emissions, which can contribute to ground-level ozone formation despite the trees’ pollution removal capabilities, sensitivity to water stress, requirements for shade and cooling effects, and impacts on water yield. The results highlight the importance of strategic management practices to balance these trade-offs, such as selecting low-emitting species and employing incremental pruning to enhance pollutant removal while minimizing VOC emissions. Additionally, the findings underscore the significance of tree placement and landscape patterns in optimizing year-round benefits, particularly in reducing urban heat island effects and enhancing energy efficiency in adjacent buildings. The study concludes that while urban parks like Yurim Park offer substantial ecological and environmental benefits, continuous monitoring and adaptive management are essential to maximize synergies and mitigate trade-offs. The insights provided on species selection, tree placement, and landscape design offer valuable guidance for urban planners and landscape architects aiming at enhancing the effectiveness of urban parks as nature-based solutions for sustainable urban development.

1. Introduction

Urban green spaces (UGSs) had attention drawn to them during COVID-19 because of vital ecosystem services (ESs) and the benefits they provide city dwellers [1]. During periods of restricted mobility and social distancing, the role of urban forests in enhancing mental and physical health, providing recreational spaces, and supporting biodiversity became more apparent [2]. Since then, people increased their visitation to urban forests and natural areas, valuing them for exercise, birding, and stress reduction [3]. ES, broadly categorized into provisioning, regulating, cultural, and supporting services, can reduce ecological footprints and enhance resilience, and quality of life in urban areas [4,5,6]. Specifically, the UGS structure regulates ecological functions in the urban environment as it influences both ESs and disservices of an urban ecosystem. These functions include air quality improvement, temperature regulation, stormwater management, and carbon sequestration, among other benefits [7,8,9,10,11]. Understanding the synergy and trade-offs in ecosystem services is crucial for effective urban planning and management. Synergies are situations in which two or more ecosystem services (ESs) are simultaneously enhanced [12], whereas a trade-off describes an antagonistic situation where the quality of one service is diminished in return for gaining another [13]. Recognizing these dynamics helps in optimizing the design and management of urban green spaces to achieve balanced outcomes that maximize overall ecological and societal benefits.

In the Republic of Korea, urban forestry discourse has seen increased attention from policymakers and decision-makers, emphasizing the need for the establishment and development of effective urban forest management strategies [14]. The FAO (Food and Agriculture Organization) and WHO (World Health Organization) have recommended a minimum urban forest area of 9 m² per capita. Since 2005, the Korean government has been making significant efforts to create urban forests near human settlements, resulting in a steady increase in the per capita area of urban forests [14,15,16]. According to the Korea Forest Service (KFS) report from 2013, as cited by Jang-Hwan, et al. [15], the average urban park size in South Korea is 7.95 m², showing promising progress toward the WHO’s recommended area of 9 m². The increased usage of UGSs also highlighted the need for strategic urban park management to ensure the sustainability and enhancement of these benefits. As urban forestry gains importance in South Korea, it is crucial to develop and implement comprehensive management strategies that balance growth with sustainability to fully realize the potential benefits of these green spaces.

Despite the growing research on urban forest structure and ecosystem services (ESs), there is still a significant gap in understanding how tree structure affects the balance of synergies and trade-offs within ecosystems, and in integrating this knowledge into urban park management and land use planning. Integrating structural characteristics of urban trees and the delivery of ecosystem services in park management can guide planning and maintenance to optimize the benefits of green spaces [17,18,19,20]. Effective management practices that consider tree species selection and diversity, diameter and age distribution, crown size and conditions, and health status are essential for sustaining these ESs over time [21]. Understanding the efficiency of delivering ESs could justify investments in urban forestry policies and programs and contribute to more detailed and informed planning.

Ibes [22] highlighted some limitations in integrating ESs into urban park planning, including the lack of models that adequately address urban environmental concerns and the absence of comprehensive tools that balance geographic, contextual, and spatial considerations. The i-Tree Eco tool addresses these challenges by providing a robust framework for characterizing the urban tree structure and composition and evaluating the associated benefits and costs [23,24]. Based on the comparative analysis of existing tools for measuring the multiple benefits of green spaces in cities, as conducted by Alvarado [25], i-Tree Eco stands out for its comprehensive suite of functionalities based on a series of peer-reviewed scientific equations and algorithms [26,27], making it highly relevant to this study. The platform integrates with Geographic Information Systems (GIS) tools, facilitating the visualization and analysis of spatial data, including climate and land use, thereby ensuring that assessments are tailored to the local urban context. Notably, since 2019, it has been tailored to include regions like South Korea.

Rapid urbanization, combined with the unprecedented impacts of climate change in South Korea, has placed significant pressure on urban forest management, challenging the survival and growth of urban trees (Kim et al. [28]). The study assessed the synergies and trade-off relationships between the structural characteristics of urban trees and ESs using i-Tree Eco in Yurim Park, Daejeon, South Korea. By optimizing tree structure and service delivery, the study could enhance the overall environmental stability and resilience of urban parks, thereby improving their capacity to withstand and adapt to ongoing pressures. While there are a number of studies that have investigated the synergies and trade-offs, the novelty of the case study lies in its explicit analysis of the role of tree structural attributes in delivering these ecosystem services, an aspect that has often been overlooked in previous research. The study focused only on the regulating and supporting services, which are very essential to the environmental stability of the park [29]. The analysis framework employed a mixed-method strategy, where the assessed structure and ecosystem services (ESs) were translated into urban park management options through a comprehensive literature review. To fulfill the objectives of this study, three research questions were formulated: (1) How do different structural characteristics of urban trees influence the provision of regulating and supporting ecosystem services in urban parks? (2) What are the synergies and trade-offs between different ecosystem services (e.g., air quality improvement vs. stormwater management) associated with varying urban tree structures in Yurim Park, Daejeon, South Korea? (3) What management strategies can be recommended to optimize the balance between synergies and trade-offs of ecosystem services in urban parks, based on tree structure and environmental conditions? Since trade-offs and synergies occur with management options, findings from this research could inform urban park managers and landscape architects in optimizing the benefits of urban parks as nature-based solutions (NbSs). This approach can enhance the sustainability and effectiveness of urban park management efforts.

2. Materials and Methods

2.1. Site Description

The study was conducted at Yurim Park, an urban park located at 27, Eoun-ro, Yuseong-gu, Daejeon Metropolitan City (Figure 1). As described in the study of Kim, et al. [30], the park covers a total area of 5.74 hectares, with 36,583 square meters, or about 63.7%, allocated to green spaces. The built area spans 20,817 square meters, constituting approximately 26.3% of the total park area, and features a distinctive peninsula of over 2600 m². The park is home to a rich variety of flora, including 64,082 seasonal trees and 135,450 perennial plants. Based on the nearest weather station in Oncheon 1-dong, Yuseong-gu, Daejeon, the mean annual precipitation of Yurim Park is 161.3 cm.

2.2. Research Design and Structural Measurements

The urban park structure was assessed using the i-Tree Eco Field Guide Manual ver. 6.0. Field data collection was conducted from 15 to 19 May 2024, during the latter part of the spring and almost the start of the summer season in South Korea. By the latter part of spring, most trees have fully expanded their leaves, providing a near-complete view of the canopy. This allows for detailed measurements of leaf area, canopy density, and overall structure, which is essential for evaluating photosynthetic activity, leaf density, and overall canopy structure. This season is crucial for assessing tree health in terms of its full functionality and resilience. A total of 33 circular sample plots were established, each plot having an 11.3 m radius covering a total of 1.323 ha, which corresponds to about 20% of the total area. The sampling intensity and plot size were guided by the study of Nowak, et al. [31]. While i-Tree Eco uses a measurement standard where diameter at breast height (DBH) is measured at a height of 1.3 m and includes trees with a diameter of 5 cm or more, this study utilized the measurement protocol from South Korea’s National Forest Inventory (NFI). The NFI protocol involves measuring DBH at 1.2 m above ground using a laser rangefinder and includes trees with a minimum diameter of 6 cm. For crown volume calculations, tree height (TH), crown base height (CBH), and crown width (CW) were recorded. CBH represents the vertical distance from the ground to the lowest branch of the crown, essentially capturing the length of the trunk devoid of branches. Crown width, or crown spread, was measured in two orthogonal directions—North–South (N/S) and East–West (E/W)—by recording the distances to the outermost points of the crown in each direction. Percent crown missing (%CM) quantifies the proportion of the crown’s total area that is devoid of branches and leaves, thus reflecting the effective crown volume occupied by branches. Crown health was visually assessed and represented as the percentage of dead branches relative to the total number of branches within the crown.

2.3. Diversity Index

Shannon [32], Menhinick [33], and Simpson [34] diversity indices were assessed. The Shannon–Wiener Index quantifies community diversity by considering both species richness (the number of species) and evenness (how evenly the individuals are distributed among these species) [35]. Menhinick’s Index is a measure of species richness relative to the total number of individuals in the sample, providing a straightforward ratio of the number of species to the square root of the total number of individuals [36]. Simpson’s Index is designed to measure the probability that two individuals randomly selected from a sample will belong to the same species, focusing on dominance or concentration [37]. This index is particularly sensitive to changes in the abundance of the most common species, thus emphasizing species evenness [38].

2.4. Ecosystem Services Estimation by i-Tree Eco

Ecosystem services using tree structural attributes were estimated using the i-Tree Eco v6.0.35 software. It is a peer-reviewed software that operates through a systematic process involving field data collection, analysis, and reporting to assess the structure, function, and value of urban green spaces (UGSs) [39]. The selection of ecosystem services in this study was guided by the capabilities of the i-Tree Eco tool, which includes carbon stock and sequestration, air pollution removal, and avoided runoff. These services are interrelated and collectively contribute to the overall ecological and environmental benefits of urban green spaces.

2.4.1. Air Pollution Removal

Hourly weather data and pollution data were obtained from the Daejeon Metropolitan City Yuseong-gu Meteorological Observatory (KOR-133), with boundary layer data sourced from the nearest monitoring station. The i-Tree utilizes localized data (such as temperature, humidity, and wind speed) that helps ensure that the estimates of air quality improvement and other benefits provided by trees are accurate and relevant to the specific community. It provides data that reflect these specific conditions, which can be quite different from those recorded at a national station. However, potential limitations like local weather and pollution data can be influenced by short-term events or anomalies, such as unusual weather patterns or temporary pollution sources. These short-term fluctuations might affect the accuracy of assessments if not properly accounted for. This can make it harder to generalize findings or apply them to broader contexts without additional calibration. Data included hourly pollution concentration measurements for ozone (O₃), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), particulate matter with diameters between 2.5 and 10 µm (PM₁₀), and particulate matter less than 2.5 µm (PM₂.₅). Air pollution removal by urban trees was estimated exclusively on the dry deposition (air pollution removal) during non-precipitation periods throughout the year [40]. The dry deposition model of i-Tree Eco employs tree data, hourly weather information, and pollution concentration levels to quantify the hourly amount of pollution removal and the corresponding percent improvement in air quality.

Information on urban tree structures, such as tree cover, leaf area index (LAI), and the percent evergreen trees, was incorporated into the model along with local weather and pollution data. Boundary layer height data were incorporated to estimate the percentage improvement in air quality due to pollution removal by trees. The pollutant flux (F; in g m⁻²s⁻¹) is calculated as the product of the deposition velocity (Vd; in m s⁻¹), which is set to zero in the precipitation period, and pollutant concentration (C; in g m⁻³) using this formula:

F = V_d C

(1)

For CO, NO₂, SO₂, and O₃, deposition velocities were calculated as the inverse of the sum of aerodynamic resistance (R_a), quasi-laminar boundary layer resistance (R_b), and canopy resistance (R_c): Vd = (R_a + R_b + R_c) − 1. The aerodynamic resistance is independent of the air pollutant type, which is calculated using meteorological data while the quasi-laminar resistance and canopy resistance is calculated for each air pollutant. Hourly canopy resistance was estimated using the following equation:

1/R_c = 1/(r_s + r_m) + 1/r_soil + 1/r_t:

(2)

where r_s is the stomatal resistance; r_m is the mesophyll resistance; r_soil is the soil resistance, and r_t is the cuticular resistance.

2.4.2. Carbon Stock and Sequestration

The i-Tree Eco estimates urban forest carbon storage (C_s) and gross carbon sequestration (C_seq) using a peer-reviewed tree growth model and a set of biomass equations [27]. Tree species, DBH, crown coverage, and tree health were the variables incorporated for this study to estimate C_s and C_seq. The model employs 150 allometric equations for different tree species. A genus-level aggregate equation was used when a specific species equation is unavailable, and family-level aggregate equations if a genus-level is also unavailable. Based on the recommendation of Nowak [41], on average, urban trees have an average of 20% less biomass than allometric equations predicted for upland forest trees. Hence, the biomass estimate is adjusted by multiplying 0.8 to reduce error.

2.4.3. Avoided Runoff

It refers to the volume of water captured by tree canopies and subsequently re-evaporated after a rainfall, rather than entering the water treatment system [42]. In i-Tree modeling, precipitation data are essential for calculating avoided runoff. For this study, meteorological information from the 2018 records of the Daejeon Yuseong-gu Meteorological Observatory (KOR-133) was utilized, noting a total annual precipitation of 154.1 cm at the study location. Based on the methodology developed by Hirabayashi [43], the i-Tree Eco model evaluates annual surface runoff by comparing two scenarios: one with vegetation and one without. The first scenario includes both vegetated and non-vegetated areas, while the second scenario only considers non-vegetated areas. Runoff is calculated on an hourly basis for each scenario and then adjusted for the area of impermeable surfaces. Typically, scenarios with vegetation show reduced runoff since plants capture, store, and evaporate some of the rainfall. The difference between the two scenarios indicates the volume of water vegetation helps to prevent surface runoff. The i-Tree Eco model calculates annual avoided runoff (AvRa in m³) using the following formula:

AvRa = ∑Ri_t × IA₂ − (∑Rvt × IAv₁ + ∑Rgt × IAg₁)

(3)

where Ri_t represents the surface runoff from impervious areas in scenario 2 at time t (m hr⁻¹); IA₂ denotes the impervious area in scenario 2 (m²); IAv₁ is the impervious cover under the canopy in scenario 1 (m²); and IAg₁ is the impervious cover outside the canopy in scenario 1 (m²).

2.4.4. Oxygen Production

The tool calculated net oxygen production by trees as the difference between the amount of oxygen produced during photosynthesis and the amount consumed during plant respiration as described by Mokashi, et al. [44] and Nowak, et al. [45].

2.4.5. Energy Savings

The estimated energy effects of trees in Yurim Park by i-Tree Eco calculate the amount of energy saved in terms of MBTU (million British thermal units) and MWH (megawatt-hours), as well as the carbon emissions avoided as a result of reduced energy consumption. The i-Tree Eco model calculates the energy-saving benefits of urban forests by determining the amount of electricity and natural gas consumption needed to achieve the same temperature reduction or increase. This consumption is then converted into economic value based on current electricity and natural gas prices. The economic values of these savings are derived based on current market prices: KRW 76,390.00 per MWH (USD 55.07), KRW 8.58 per MBTU (USD 0.0062), and KRW 228,185.00 (USD 164.50) per metric ton of avoided carbon [46].

2.5. Systematic Literature Review on Urban Park Management

A systematic review was conducted to consolidate and synthesize existing research on urban park management. The review focused on the contextual application of urban park management practices, ensuring that the structural characteristics of urban trees and their ecosystem services were considered holistically. To ensure the relevance and quality of the studies included in the review, specific inclusion and exclusion criteria such as studies published in peer-reviewed journals, explicit usage of urban forest structure and ES terminologies, and research focusing on urban park management.

2.6. Statistical Analysis

Analysis was performed using SPSS 26. Prior to conducting the correlation analysis, the normality of the data for all variables (ecosystem services) was assessed using the Shapiro–Wilk test. Additionally, Levene’s test for homogeneity of variances was conducted to assess equal variances across groups. Given the non-normal distribution of the data, Spearman’s rank correlation was employed to evaluate the relationship between tree structural attributes and their influence on environmental effects. An Independent-Samples Kruskal–Wallis Test was conducted to assess the differences in C_seq across different levels of Crown Light Exposure (CLE). This non-parametric test was selected due to its resilience to violations of normality and homogeneity of variance assumptions observed in the data. It provided a robust method for comparing C_seq across multiple groups without relying on the assumptions of normal distribution or equal variances.

3. Results

3.1. Species Composition, Abundance, and Diversity

Sampling revealed a total of 305 trees belonging to 23 species. The entire park has an estimated 1527 trees with a tree cover of 61.4% and an overall tree density of 230 trees/ha. The three most common species are Chionanthus retusus (15.4%), Pinus densiflora (14.4%), and Pinus strobus (13.4%). In terms of DBH class, C. retusus is highly concentrated in the 7.6–15.2 cm DBH class, representing 76.6% of the population. There is a smaller proportion (19.1%) in the 15.2–30.5 cm DBH class, with negligible representation in other DBH classes. P. densiflora shows a broader distribution across multiple DBH classes with a notable representation (47.7%) in the 15.2–30.5 cm class, and substantial proportions in the 30.5–45.7 cm (34.1%) and 45.7–61.0 cm (18.2%) classes. On the other hand, P. strobus is heavily skewed towards the 15.2–30.5 cm DBH class (70.7%), with decreasing representation in larger DBH classes. Among species, Platanus orientalis recorded the highest DBH class representing 8.3% of the total population. Species diversity in the study area, as measured by the Shannon–Wiener Index (H’), is 2.6, indicating a moderate diversity. Menhinick’s Index is calculated at 1.3, indicating a moderate level of species richness relative to the total number of individuals. A very high Simpson’s Diversity Index of 11.3 suggests a very low probability that two randomly selected individuals belong to the same species, which implies high diversity. The Evenness Index value is 0.8, indicating a fairly even distribution of individuals among species. Detailed information can be seen in Appendix 1 from https://drive.google.com/drive/folders/19363u9qJxHsgwSR9R2j7U97pJqQScQGA?usp=sharing, accessed on 5 August 2024.

3.2. Tree Structure and the Estimated ES

3.2.1. Pollution Removal

Trees in Yurim Park are estimated to remove a total of 252.62 kg of air pollutants annually. Ozone accounts for the largest share at 148.18 kg/yr (58.66%) followed by PM₁₀ at 48.75 kg/yr (19.30%) (Figure 2). Higher pollution removal rates were observed during the growing season (spring and summer) when trees are in full leaf. During these months, trees removed substantially more PM₁₀, PM_2.5, and gaseous pollutants compared to the dormant season (fall and winter). For instance, ozone removal was highest during the summer months, peaking in July and August while the lowest was observed in the winter months, particularly in December and January, when many trees are dormant and have shed their leaves (Appendix 2 from https://drive.google.com/drive/folders/19363u9qJxHsgwSR9R2j7U97pJqQScQGA?usp=sharing). Spearman’s rank test showed a strong positive correlation with crown width (CW) (r_s = 0.823, p < 0.001), total height (TH) (r_s = 0.805, p < 0.001), and crown base height (CBH) (r_s = 0.803, p < 0.001). Meanwhile, a very weak and non-significant correlation was observed with the percent crown missing (r_s = −0.059, p < 0.789). A synergy effect was observed with tree attributes as explained by the highest significant inter-correlations between TH and CBH (r_s = −0.949, p < 0.001).

Meanwhile, trees in Yurim Park emitted an estimated 68.9 kg of volatile organic compounds (VOCs) comprising 22.53 kg/yr of isoprene and 46.37 kg/yr of monoterpenes. Emissions varied among species, as influenced primarily by leaf biomass (r_s = −0.785, p < 0.001), LAI (r_s = −0.764, p < 0.001), CBH (r_s = −0.683, p < 0.001), CW (r_s = −0.651, p < 0.001), and TH (r_s = −0.663, p < 0.001). Particularly noteworthy were P. orientalis and P. strobus, with total annual VOC emissions of 18.0 kg and 10.5 kg, respectively.

3.2.2. Carbon Stock (C_stock) and Sequestration (C_seq)

The estimated carbon stock of Yurim Park is 33.45 MgC ha⁻¹ with a gross sequestration of about 9.021 MgC ha⁻¹ (Figure 3). The net carbon sequestration is calculated at 8.269 MgC ha⁻¹. The Spearman’s Rank test revealed significant relationships between tree structural attributes and C_seq. Specifically, DBH, LAI, CW, basal area, TH, and CBH showed a very strong positive correlation with carbon sequestration (p < 0.001). However, a very weak and non-significant correlation was observed with %CM (r_s = 0.019, p < 0.931). Meanwhile, the Kruskal–Wallis test revealed that variations in CLE do not significantly influence C_seq (p = 0.205).

3.2.3. Avoided Runoff

Avoided runoff or the intercepted precipitation by trees, infiltration by roots, and storage in the soil (hereafter, AvR), revealed an estimated 420 m³ per year. The relative benefit in terms of precipitation offsetting by the intercepted rainfall for the park is approximately 0.454%. The Spearman’s Rank test revealed that LAI and species abundance have a very strong positive correlation with AvR with rs = 0.973 (p < 0.001) and rs = 0.810 (p < 0.001), respectively. However, other tree structural attributes such as TH, CBH, CW, %CM, DBH, and basal area were found to have very weak correlations and non-significant values (see Appendix 3 from https://drive.google.com/drive/folders/19363u9qJxHsgwSR9R2j7U97pJqQScQGA?usp=sharing).

3.2.4. Oxygen Production

Yurim Park annually produces an estimated 22.05 Mg of oxygen. Among the observed species, P. densiflora, P. strobus, and Prunus serrulata Lindl. were identified as the top three oxygen-producing species. The amount of oxygen produced shows a strong positive and significant correlation with LAI (rs = 0.888, p < 0.001) and abundance (rs = 0.879, p < 0.001). Meanwhile, a very weak and non-significant correlation was observed with C_seq (rs = −0.081, p = 0.713).

3.2.5. Building Energy Savings

Trees in Yurim Park are estimated to reduce energy-related costs from residential buildings by KRW 193,000 (USD 139.83) annually. Trees also provide an additional KRW 521,000 (USD 377.47) valued from reduced the amount of carbon released by fossil-fuel-based power plants (a reduction of 2.28 metric tons of carbon emissions). The trees contribute to a heating energy savings of 85.620 MBTU and 0.643 MWH, resulting in a total heating energy savings of 88.113 MBTU and MWH combined. On the other hand, as to the cooling savings, the trees provide an energy savings of 1.872 MWH, contributing significantly to the reduction in cooling energy demand. The reduction in energy use translates to a significant amount of carbon emissions avoided: 1.998 MgC for heating; and 0.286 MgC for cooling (

Table 1. Annual energy savings by trees.

	Heating	Cooling	Total
MBTU a	85.62	N/A	85.620
MWH b	0.643	1.872	2.515
Carbon Avoided (Mg)	1.998	0.286	2.284

^a MBTU—Million British Thermal Units; ^b MWH—Megawatt-hour; Mg = million grams (or 1 metric ton).

and

Table 2. Annual monetary savings ^a (USD) from energy expenditure during heating and cooling.

	Heating	Cooling	Total
MBTU a	0.55	N/A	0.55
MWH b	36.71	106.94	143.64
Carbon Avoided (Mg)	340.91	48.82	389.73

^a Based on the prices of USD 57.12 per MWH and 8.58 per MBTU; Million British Thermal Units (MBTU) ^b MWH—Megawatt-hour; Mg = million grams (or 1 metric ton).

).

4. Discussion

4.1. Ecosystem Service Synergies and Trade-Offs from Tree Structural Perspectives

Trees in Yurim Park significantly contribute to air pollution removal, especially during the growing season, and include Platanus sp., Pinus densiflora Siebold & Zucc., Metasequoia glyptostroboides Hu and W.C.Cheng, and Gingko biloba L. However, their contribution to emitting VOCs necessitates the need for a nuanced consideration of their overall environmental impact [47]. The strong positive significant correlations of CW, TH, and CBH with air pollution removal indicate that healthy larger trees with more extensive canopies are more effective in removing pollutants, particularly during the spring (growing) season when leaf surface area is at its peak [8,41,48]. Trees with complex foliage structure, and with increasing tree canopy cover are more effective in removing airborne particulate matter [49,50,51]. However, while larger trees contribute significantly to pollution removal, they also emit VOCs, which can form ground-level ozone, a harmful pollutant [52,53,54,55]. It is important to note, though, that certain VOCs, such as phytoncides, can have beneficial effects on human health. Phytoncides possess antibacterial properties that help regulate and inhibit bacterial growth, and may influence physiological functions such as lowering blood pressure and enhancing mood [56,57,58]. These synergies and trade-offs are particularly notable in species like P. orientalis and P. strobus, which have high VOC emissions.

Structural attributes such as DBH, LAI, CW, basal area, and TH, show very strong positive significant correlations with both carbon stock and sequestration. Larger and denser trees in Yurim Park sequester more carbon, contributing significantly to carbon storage and offsetting atmospheric CO₂ [59,60,61]. However, these trees, with substantial carbon sequestration capabilities, may require more intensive management and maintenance [62], potentially involving higher costs and labor. Furthermore, while increasing tree density will enhance C_seq regardless of species [21], it may not be sufficient to improve habitat quality [19]. For instance, water yield can be adversely affected by increased stocking levels [63], a factor that varies depending on specific structural attributes [64]. While tree crown or canopy characteristics in a stand are influenced by CLE [65], the lack of significant influence of CLE on C_seq in this study needs further investigation. Studies explicitly examining CLE and C_seq are still limited.

Yurim Park effectively reduces surface runoff and promotes groundwater infiltration due to its dense tree canopy and species abundance. The high positive significant correlations of LAI and abundance with AvR indicate synergies in delivering ES. AvR results suggest that trees with dense foliage and higher species abundance are more effective in intercepting rainfall [66], reducing surface runoff, and promoting groundwater infiltration [67,68]. A higher density of trees is better at reducing runoff and enhancing infiltration [69]. Biomass accumulation enhances belowground root biomass, which in turn reduces erosion and landslide risks [70], improves ecosystem structure [71], and supports increased biodiversity [72], and the development of ecological niches [73]. Additionally, it boosts organic matter accumulation, thereby enhancing the soil’s moisture-holding capacity [74]. However, different species exhibit varying sensitivities to water stress, which can influence their long-term suitability for stormwater management [75]. Urban trees in the park, with their significant potential for stormwater management, warrant further research to explore how factors such as species type, age class, and influence of local soil, atmospheric, and landscape conditions impact their effectiveness [69].

Similar to AvR, existing trees in Yurim Park particularly those with larger leaf areas and greater abundance such as P. densiflora Siebold & Zucc., P. strobus L., and P. serrulata Lindl. are more effective in oxygen production [45,76,77]. Net oxygen production by a tree over the course of a year is directly related to the amount of carbon dioxide absorbed through photosynthesis, which in turn correlates with tree biomass accumulation [44,78]. Furthermore, the relationship between leaf surface area and photosynthesis highlights the connection between oxygen release and the overall health benefits provided by urban trees [79]. However, the overall benefit of tree-based oxygen production is relatively modest compared to the vast and stable amounts of oxygen present in the atmosphere compared to marine organisms like phytoplankton [80] and extensive upland forests [81].

The type of tree species in Yurim Park significantly influences energy consumption in buildings through several mechanisms such as shading, evaporative cooling, and wind blocking. Pandit and Laband [82] reported that growth rate and crown shape are important criteria in selecting trees in city parks. Large trees in Yurim Park such as Platanus sp., P. densiflora Siebold & Zucc., M. glyptostroboides Hu and W.C.Cheng, and G. biloba L. offer substantial shade and cooling benefits but require more space and time to reach maturity. In contrast, smaller trees or those with less dense foliage may provide less significant cooling effects [83]. Hence, strategic species selection and positioning are important [84]. Trees that provide extensive shade during the summer may also block sunlight in the winter, potentially leading to increased heating costs [85,86]. The economic benefits derived from energy savings highlight the value of urban trees in mitigating energy consumption and reducing carbon emissions [87].

High species diversity within Yurim Park, as indicated by diversity indices, enhances ecosystem stability and resilience, contributing to reduced soil erosion, increased biomass accumulation, and improved hydrological functions, thereby mitigating runoff and enhancing infiltration. Measured diversity indices suggest that Yurim Park is highly diverse, with a balanced representation of species and no single species dominating the ecosystem. Recent studies reported that high diversity is often correlated with ecosystem stability and resilience, providing a buffer against environmental fluctuations and perturbations [88,89]. Tree species diversity, combined with varying root depths contributes to reducing soil erosion. This diversity increases interception, decreases runoff (flash floods), and improves infiltration [90,91]. However, forests with high plant diversity might provide less carbon storage [92] (

Table 3. Summary of ES, Synergies, and Trade-offs.

Ecosystem Services	Synergies	Trade-Offs
Air pollution removal	Larger trees with extensive canopies effectively remove air pollution, especially during the growing season. VOC such as phytoncides that regulate the spread of bacteria, other compounds that regulate blood pressure, etc.	Large trees emit VOCs (isoprene and monoterpenes) that can form ground-level ozone, a harmful pollutant.
Carbon stock and sequestration	Larger and denser trees sequester more carbon, contributing to significant carbon storage and atmospheric CO2 offset.	Intensive management and maintenance may be required, potentially increasing costs and labor. Increasing tree density may adversely affect water yield, and the influence of specific structural attributes is variable.
Stormwater management (intercepting rainfall, reducing surface runoff, promoting groundwater infiltration)	Trees with dense foliage and higher species abundance are more effective in intercepting rainfall, reducing runoff, and enhancing infiltration.	Sensitivity to water stress varies by species, affecting their long-term suitability for stormwater management.
Erosion control and biomass accumulation	Biomass accumulation reduces erosion, improves ecosystem structure, and supports increased biodiversity.	Different species exhibit varying sensitivities to water stress, which can influence their long-term suitability for stormwater management
Oxygen production	Larger leaf areas and higher species abundance contribute to more effective oxygen production.	The benefit of tree-based oxygen production is relatively modest compared to atmospheric oxygen levels and marine organisms.
Energy savings from shading, evaporative cooling, and wind-blocking	Strategic selection and positioning of tree species can lead to significant energy savings and reduced carbon emissions.	Large trees provide more shade and cooling but also require more space and time to reach maturity. Smaller trees or those with less dense foliage may not provide as significant cooling benefits.
High Species Diversity	Enhances ecosystem stability and resilience and with varying root depths contributes to reducing soil erosion.	Forests with high plant diversity might provide less carbon storage.

).

4.2. Strategic Management Options and Land-Use Planning

The strong positive correlations between pollution removal and tree structural attributes imply that selecting and cultivating trees could enhance pollution removal capacities. While trees with extensive and healthy canopy cover contribute significantly to pollution removal, there are important management considerations for street trees in Yurim Park. Street trees along Hanbat Road, where there is slight-to-moderate traffic, can reduce ventilation [93], and PM deposition, thereby affecting the pollution removal capacity of trees. PM deposition has been found to accumulate on surfaces in areas with traffic density [94]. If the primary goal is to reduce the air pollutants such as those in heavy traffic areas, intensive pruning of street tree canopies with optimal density at 50–60% will minimize the negative trapping effect on particles (PM_2.5 and PM₁₀), thereby increasing ventilation [95]. While intensive pruning might improve PM removal efficiency on a per-unit area and reduce the amount of VOC emissions, it drastically reduces the overall volume of the tree’s crown [96]. To balance these effects, incremental pruning can be employed, allowing for the monitoring of both pollutant removal efficiency and VOC emissions over time, with a recommended pruning intensity of 25% [97].

In heavily trafficked areas, planting low-level canopy plants, such as shrubs, between single-row street trees is a more effective management strategy for pollution removal [98,99]. This approach helps prevent the negative trapping effects of particulate matter [95]. Studies by Sgrigna, et al. [100] and Linden, et al. [101] have shown that lower canopy plant types such as shrubs, herbaceous plants, and ground covers exhibit higher leaf surface PM deposition compared to upper canopy types. Additionally, the inclusion of green infrastructure (GI) elements, such as green roofs and walls in high-traffic density areas, is also very effective in removing air pollutants [102]. According to the study of Pugh, et al. [103], GI can reduce 43% NO₂ and up to 62% PM₁₀ without adversely affecting ventilation. Moreover, adequate irrigation can effectively reduce VOC emissions through reducing leaf temperature [81,104]. Setting environmental management priorities involves addressing trade-offs, such as water consumption and VOC reduction, which is deemed important. Park managers should carefully weigh these relationships in integrating them into their park management plans [81]. A practical approach to reduce VOC emissions involves selecting low-emitting tree species such as Prunus sargentii Rehder, Zelkova serrata (Thunb.) Makino, Ginkgo biloba L., and Taxus cuspidata Siebold & Zucc. [105].

Given the strong positive correlation of larger and denser trees with carbon stock and sequestration, management schemes that regulate key structural attributes (e.g., leaf area index, basal area) can help mitigate trade-offs with other ES. Tree species with compound leaves and larger leaf sizes, such as Aesculus turbinata Blume and Fraxinus rhynchophylla Roxb., contribute to significantly higher carbon assimilation efficiency, higher photosynthetic capacity, and enhanced hydraulic segmentation [106,107,108]. Additionally, these species exhibit low VOC emissions [109]. To mitigate the trade-off to water yield, studies have shown that native tree species (endemic, if any) showed conservative water use due to their high acclimatization rate and adaptations to local soil conditions [110,111,112]. In addition, species with glandular trichomes are reflective and can help deflect sunlight, reducing leaf temperature and thus lowering water loss through transpiration [113]. Further, it produces a sticky substance around the stomata, limiting air movement and water vapor exchange, which helps reduce water loss during transpiration [114]. Species with glandular trichomes include Quercus sp., Zelkova serrata (Thunb.) Makino, Acer sp., etc. Kauppi, et al. [115] indicate that land management has been a key driver in the carbon stock capacity of trees.

Landscape patterns and design significantly affect the provision of ESs [116,117]. The ground surface types in Yurim Park are composed of permeable surface, impermeable (non-porous bricks, asphalt, and cement), semi-permeable (urethane flooring materials mostly seen in playgrounds), and a water body (pond). Planting trees or vegetation with a dense crown diameter (like Quercus acutissima Carruth.) at proper spacing, to shade impervious surfaces, buildings, and water bodies can reduce the urban heat island effect (UHI) [118,119] and reduce building energy consumption [81].

Stormwater management is increasingly crucial as industrialization has significantly impacted the complexity of land-use patterns in urban areas. In this context, understanding the dynamics of tree structural attributes and ES is essential for effective green space management. While dense canopies are beneficial for runoff reduction, overly dense planting can lead to competition for resources, potentially reducing the overall health and growth rates of the trees [120]. Meanwhile, implementing stormwater management strategies that rely on ecosystem processes, such as tree canopy interception and rhizosphere biology, can be challenging in cities due to the high value of land and the poor suitability of urban soils for vegetation [121]. To address these challenges, several practical approaches can be employed. To prevent blockage of drainage canals, avoid planting deciduous trees, such as Acer palmatum Thunb., Quercus mongolica Fisch. ex Ledeb., and Z. serrata (Thunb.) Makino, in close proximity to these canals, whenever possible [122]. Additionally, selecting native tree species with deep and extensive root systems can improve soil structure and permeability, thereby promoting infiltration [123,124].

Strategic urban park planning and tree placement are crucial for optimizing year-round benefits, as trees significantly enhance urban cooling by shading buildings and reducing ambient temperatures. Trees provide significant cooling benefits in summer by shading buildings and reducing air temperatures beneath their canopy [125,126]. Balter, et al. [127] indicate that temperatures under tree cover can be 2.3 °C cooler, leading to a 42% decrease in cooling energy consumption compared to exposed areas. Moreover, the cooling effects and efficiency of urban parks on surrounding built-up landscapes are influenced by the size and arrangement of the park. Cheng, et al. [128] reveal nonlinear relationships between park sizes and their cooling effects on surrounding urbanized landscapes. Specifically, the proportion and dominance of urban land use types negatively affect the park’s cooling effect. However, increased shape complexity of urban land-use types can mitigate these adverse impacts. Meanwhile, Yurim Park is flanked by Gapcheon, a river that significantly influences the air temperature within the park. Teshnehdel, et al. [129] highlighted that while water body evaporation without trees may decrease air temperature, it also increases humidity, which can reduce the positive impact on thermal comfort and potentially affect energy consumption. On the other hand, in winter, strategically placed trees can mitigate heating costs by blocking cold winds and reducing heat loss from buildings [130]. For buildings that utilize solar power, the reductions in solar energy on south-facing walls by a deciduous tree may be greater in winter than in summer. However, dense tree cover may impede passive solar heating by shading buildings, potentially increasing energy consumption [131]. McPherson and Simpson [132] recommended specific planting distances and locations to optimize tree shading benefits. Trees or empty planting sites within 12.2 m of the east and west sides of buildings were classified as “positive sites” due to the significant shade benefits they provide. Trees located within 6.1 m of the south side of buildings were deemed “neutral sites” because the benefits of limited summer shade are likely offset by undesirable winter shade. Points located between 6.1 and 12.2 m on the south side of buildings were considered “negative sites” as most shade occurs during the heating season. Points located to the north or more than 12.2 m from buildings in other directions were also classified as “neutral sites” since their shade would not fall on buildings. Regardless of their location, all trees were assumed to produce energy benefits by reducing ambient temperatures and wind speeds (climate effect). Incorrect placement or selection of inappropriate species could lead to reduced benefits or even increased maintenance costs due to root interference with building foundations and utilities [133]. Meanwhile, the valuation of energy savings provided by trees could serve as the basis for future investments in urban park management. Effective management hinges on thoughtful urban park planning that considers seasonal variations, structural tree attributes, and surrounding landscape patterns. Balancing these factors can optimize energy efficiency year-round (

Table 4. Summary of Tree Structural Attributes, Impacts, and Management Options.

Ecosystem Services (ESs)	Tree Structural Attributes	ESs Impacts (+,−)	Management Options	References
Pollution Removal	CW, TH, CBH	Positive Impacts: Larger and healthier trees are highly effective in removing pollutants from the air, particularly particulate matter (PM) and volatile organic compounds (VOCs). Trees with greater leaf surface area and dense canopies provide a larger area for pollutant capture. Negative Impacts: Dense canopies can reduce ventilation and exacerbate PM deposition, especially in areas with heavy traffic. This trapping effect can lead to higher accumulation of pollutants on tree surfaces.	Intensive Pruning (primary goal is to reduce pollution specially in heavy trafficked areas): optimal canopy density of 50–60% to minimize PM2.5 and PM10 trapping effects.	[95]
			Incremental pruning (monitoring of both pollutant removal efficiency and VOC emissions over time): general maintenance < 25% pruning intensity.	[97]
			Alternative Planting Strategies: in high-traffic areas, use low-level canopy plants like shrubs alongside single-row street trees.	[98,99,100,101,103]
			Adequate Irrigation and Tree Species Selection: low emitter tree species to reduce VOC emissions.	[81,104,134,135]
Cstock and Cseq	DBH, LAI, CW, Basal Area, TH, CBH	Positive Impacts: Larger trees with higher leaf area indices and compound leaves contribute significantly to carbon stock and sequestration. They exhibit higher photosynthetic capacity and enhanced hydraulic segmentation, leading to more effective carbon assimilation. Negative Impacts: Balancing carbon sequestration with other ecosystem services, such as water yield and pollutant removal, can be challenging. Dense tree canopies may compete for resources, potentially impacting tree health and growth rates, which indirectly affects carbon sequestration.	Native and Endemic Species Selection: high acclimatization rate; adapted to local soil conditions; and conservative water use.	[110]
			Species with Glandular Trichromes: reducing movement of air and water vapor exchange, help reduce water loss during transpiration.	[113,114]
			Species with high LAI, compound leaves, and larger leaf sizes: greater potential for carbon uptake through photosynthesis.	[112]
			Species diversity: Higher diversity enhances biomass accumulation.	[91]
Avoided runoff	CW, CBH, %CM	Positive Impacts: Dense tree canopies and strategic planting help reduce stormwater runoff by enhancing canopy interception and improving soil structure and permeability. Native species with deep root systems are particularly effective in promoting infiltration and soil health. Negative Impacts: very dense planting can lead to competition for resources, impacting tree health and growth. This competition can reduce the effectiveness of trees in stormwater management.	Avoid Planting Deciduous Trees in Close Proximity to Drainage Canals: prevent blockage of drainage due to litter deposition.	[122]
			Native Tree Species Selection: Deep and extensive root systems can improve soil structure and permeability, thereby promoting infiltration.	[123,124]
			Dense canopies: beneficial for runoff reduction with proper spacing.	[120]
			Species Diversity: higher diversity higher interception, decreases runoff, improves infiltration, decreases erosion.	[90]
Energy Savings	DBH, HT, CLE, %CM, CW, CBH	Positive Impacts: Trees significantly reduce the urban heat island effect by providing shade and lowering ambient temperatures. Properly placed trees can decrease cooling energy consumption in buildings by up to 42%, improving thermal comfort. Negative Impacts: Overly dense tree cover can impede passive solar heating in winter, potentially increasing energy consumption. Incorrect placement or choice of species may also result in reduced benefits or increased maintenance costs.	East and West Sides (≤12.2 m from Buildings): significant shade benefits. South Side (≤6.1 m from Buildings): limited summer shades; potential undesirable winter shade. South Side (6.1 to 12.2 m from Buildings): most shade occurs during the summer season. North Side or >12.2 m from Buildings: shade does not fall on buildings. Solar Power Buildings (Winter vs. Summer): deciduous trees reduce solar energy on south-facing walls more in winter than in summer.	[82,132]
			Dense Tree Cover: impedes passive solar heating; potential increase in energy consumption.	[131]

).

5. Conclusions

The concept of tree structural attributes and ESs offers a promising framework for more holistic and effective urban park management and planning. Understanding the synergies and trade-offs between tree structural attributes and ecosystem services can significantly enhance resource efficiency in urban environments. Assessing multiple ecosystem services (ESs) and identifying trade-offs and synergies among them enables the strategic management of ecosystems to optimize their benefits and promote long-term sustainability. Analyzing both the positive and negative impacts on ecosystem services provided by urban trees is crucial for effective and sustainable park management. This comprehensive evaluation allows for a nuanced understanding of how different tree attributes and management practices influence various ecosystem services, including pollution removal, carbon sequestration, urban cooling, and stormwater management. While this study has limitations with the assessed ES and measured tree structural attributes, it demonstrates that urban park management and planning can effectively utilize straightforward practical measures as nature-based solutions to enhance ecosystem functioning. It is crucial to continuously monitor these intricate relationships to identify further trade-offs and opportunities for synergistic outcomes, ultimately improving the effectiveness of urban parks and green spaces. Furthermore, the detailed insights on optimal tree placement and landscape patterns discussed therein offer a solid foundation for urban planners and landscape architects. These findings can guide the development of visual tools such as maps and plans by outlining the effective strategies for tree distribution and landscape patterns.

This study provides an exploratory assessment of the synergies and trade-offs associated with tree structural attributes in Yurim Park, South Korea. While the findings offer valuable insights, certain limitations impact the conclusions. Notably, constraints related to time and the software used restricted the study’s scope. Most importantly, the study did not measure or account for wind direction or speed, which are critical factors influencing air quality levels. Consequently, the study cannot definitively determine the extent to which observed improvements in air quality are attributable to the trees alone. Future research could address these limitations by incorporating comprehensive measurements of wind direction and speed to better isolate the impact of trees on air quality. Additionally, expanding the assessment to include the potential contributions of understory vegetation, such as shrubs and grasses, as well as green roofs, could provide a more holistic understanding of the ecosystem services provided by the park. This broader approach would not only enhance the accuracy of air quality improvement assessments but also offer a more integrated perspective on the various components of urban green spaces and their collective benefits. Also, future research should assess a comparative analysis of the overall impact of ESs, particularly the emission of VOCs, given their harmful and beneficial effects on human health. Integrating policy and institutional analysis in the future is recommended to assess how these factors influence ecological security and the integrity of park landscapes in South Korea. Ecosystem services mapping, along with land-cover and land-use change studies, should be conducted regularly to provide a basis for urban green space protection and management. This will help ensure compliance with the WHO’s recommendation of a minimum of 9 m² of urban green space per capita. This information aids urban landscape architects in designing more effective urban green spaces, such as parks, and provides guiding principles for maintaining or even expanding underutilized urban areas.