Physiological Response of Trees to Seasonal Variation Reveals Native Species Are Suitable for Urban Parks That Resemble Natural Sites

  • Arboriculture & Urban Forestry (AUF)
  • August 2026,
  • jauf.2026.024;
  • DOI: https://doi.org/10.48044/jauf.2026.024

Abstract

Background Cities are hotter and have poor soil compared to surrounding natural areas, necessitating identification of stress-tolerant species suitable for urban plantings. Species selection based on physiology is highly informative, but also time-consuming, so quick-to-measure proxies are needed. Further, parks may represent relatively less stressful locations where native trees could be included to increase urban biodiversity.

Methods We examined seasonal physiological responses of leaf hydraulic conductance, turgor loss point (ΨTLP), and gas exchange for 3 Northeastern Ohio species (Acer rubrum, Acer saccharum, and Nyssa sylvatica), one Southeastern United States (US) species (Liquidambar styraciflua), and one East Asian species (Pyrus calleryana) growing at 2 parks in Northeast Ohio. We compared these with published growth, leaf dry matter content (LDMC), and carbon:nitrogen ratio (CN) data for the same trees in our study.

Results Lakeview soil was most similar to surrounding natural areas, but both parks had higher soil bulk density and sand percentage compared to a nearby forest. At both parks, physiology was related to soil properties. Our seasonal analysis showed that water stress was mitigated via seasonal physiological adjustments at both parks. Pyrus callyerana was not distinguished from Liquidambar styraciflua and Nyssa sylvatica. Principal component analysis showed positive correlations of LDMC with growth and ΨTLP, and CN with carbon sequestration.

Conclusions Our study demonstrates suitability of Ohio and Southeastern US species for Northeastern Ohio parks, despite the presence of some compacted soil. In addition, we suggest LDMC and CN could be useful physiological proxies for broadscale analysis of tree suitability for urban environments.

Keywords

Introduction

Urban trees may suffer water stress due to urban heat island effects, and this problem is expected to increase with climate change (Chapman et al. 2017; Burley et al. 2019). Urban heat island effects could become particularly acute when overlain with late-summer water stress, which may be one factor leading to the decline in the urban canopy (Nowak and Greenfield 2018). Urban foresters thus face the daunting task of choosing tree species that can tolerate the stress of urban environments while maintaining aesthetic value and presenting limited maintenance issues. The choice of urban tree species has been subjective, however, the result of heuristic decision-making, nursery availability, and neighborhood resident preferences (Avolio et al. 2018). In the past decade, there has been growing interest in using plant physiology to define species suitability for urban plantings. Intensive, comparative studies of tree physiology can accurately quantify stress tolerance, but most previous research on urban tree physiology focuses on a narrow set of drought tolerance traits for a few commonly planted species or cultivars (Gillner et al. 2015; Gillner et al. 2017; Sjöman et al. 2018). In addition, physiology is difficult and time-consuming to measure, so studies that relate dynamic physiological responses to quick-to-measure traits are needed to speed the discovery of suitable species for use in urban forestry.

Comparing spring versus summer water relations can provide insight into how trees manage water stress, because drought stress increases predictably over summer as temperatures increase. Maximum leaf hydraulic conductance (Kleaf), or the rate of leaf laminar water flow at a given water potential gradient, determines the capacity for leaf water loss and thereby sets limits on stomatal conductance (Sack and Scoffoni 2012; Scoffoni et al. 2016). Similarly, the water potential at leaf turgor loss point (ΨTLP) sets limits on cellular function and predicts stomatal closure and wilting (Rodriguez-Dominguez et al. 2016; Maréchaux et al. 2018). If Kleaf declines from spring to summer, growth limitations arise due to increased resistance in the leaf hydraulic pathway (Scoffoni et al. 2016), which reduces the capacity of the leaf to replace water lost due to evaporation, leading to stomatal closure (Brodribb and Holbrook 2003). On the other hand, when ΨTLP declines from spring to summer, increased cell solute concentration can allow stomata to remain open as leaf water potential declines (Maréchaux et al. 2018). Thus, changes in ΨTLP could mitigate risk of Kleaf decline, allowing photosynthesis to continue even as drought stress increases over summer.

Potentially exacerbating heat and drought stress in urban areas, urban soil is prone to compaction due to human activities such as increased foot traffic and heavy machinery use, leading to reduced porosity and water-holding capacity. Urban street trees and those in planters are likely to experience more intense drought effects than urban park trees due to small soil volumes (Kjelgren and Clark 1993). Urban park trees are an interesting context in which to explore the performance of trees, because even with larger soil volumes compared to street trees, urban park soil can also be extremely compacted, which should increase the probability of seasonal water stress. The extent of soil compaction in urban parks, however, is likely to vary substantially based on park history (Scharenbroch et al. 2005). Species also vary in their ability to tolerate poor quality or compacted soil; for example, tree species that have wide geographic distributions, those which can tolerate flooding, or those which tend to grow in disturbed soils may have a stronger ability to acclimate and thereby maintain their performance across seasons and different soil types (Sheth and Angert 2014; Puglielli et al. 2023).

Soil is an important component that interacts with precipitation to determine physiological outcomes. Trees experiencing lower precipitation and more heavily compacted soil may exhibit the largest Kleaf decline over the summer, because compact soil prevents water infiltration and limits root growth (Scharenbroch et al. 2005). Faster growing species should show the largest Kleaf decline due to their need to maintain higher stomatal conductance to support higher photosynthetic capacity, unless they can respond to stressful conditions with larger seasonal changes in ΨTLP (Bartlett et al. 2012). Pyrus calleryana is commonly used in urban settings in part because it is viewed as fast-growing (Rahman et al. 2015), but fast growth is likely one reason this species has escaped cultivation and demonstrated potential to be invasive (Culley and Hardiman 2007). In addition, underlying physiological trade-offs may result in lower mechanical strength of fast-growing species (Reich 2014), so this might be one reason why P. calleryana is prone to breakage (Dirr 1990). Slower-growing species should allocate more to carbon-rich structural tissues (Wright et al. 2004), making their leaves and wood more suitable to provide ecosystem services like carbon sequestration over the long term. While fast growth might provide an advantage in some urban settings, we lack information about the extent of stress tolerance required for long-term survival of urban trees in different types of growing conditions.

In 2023, the Ohio Department of Natural Resources banned the planting of Pyrus calleryana, meaning that now alternatives which can perform under similar urban conditions are urgently needed. Tree species selection for urban plantings has long involved debate over the relative value of native versus non-native species. Although native species are thought to be better adapted to regional conditions, this assumption may not hold in highly modified urban environments where abiotic stressors can differ substantially from those in surrounding natural areas (Kendle and Rose 2000). Consequently, trait-based and physiological assessment may provide a more mechanistic framework for informing site-specific urban forestry decisions. Thus, providing more information on the suitability of native species for urban plantings is critical. For instances when locally native species’ suitability is limited, consideration of southern species may be appropriate. Under climate change models, suitable habitats are projected to shift northward, potentially shifting species distributions more northward (Prasad et al. 2025). Species that are currently distributed farther south of a particular urban area may therefore be useful candidates for urban plantings. This hypothesis is based on the idea that plants occurring at warmer or drier locations within a species range may have greater heat or drought tolerance; however, this idea should be evaluated physiologically and at the site scale because tree responses to climate change are strongly trait-dependent (Fei et al. 2017).

To investigate the suitability of deciduous hardwood species native to the Northeastern United States for urban park plantings in Northeast Ohio, we conducted a study of urban park trees growing at Lakeview Cemetery, located in the heart of Cleveland, Ohio, and Secrest Arboretum, located in Wooster, Ohio, a small city situated approximately 40 km away from the Akron-Canton metropolitan area. For both locations, Mixed Oak Forest was the native plant community prior to urbanization. These are nonirrigated parks characterized by planted, open-grown trees surrounded by turf grass with some paved utility and walking paths. We compared 3 tree species native to Ohio (Acer rubrum, Acer saccharum, and Nyssa sylvatica) with a Southeastern United States native species, Liquidambar styraciflua, and East Asian Pyrus calleryana. We measured seasonal changes in Kleaf and ΨTLP to characterize tree responses to late-summer water stress, along with photosynthetic capacity (maximum electron transport rate [Jmax] and maximum carboxylation rate [Vcmax]), and gas exchange rates (net photosynthesis [A], stomatal conductance [gs], and instantaneous water use efficiency [WUE]). We compared these physiological rates across parks and to previously published data on soil texture and bulk density of samples collected from each tree planting location. Lastly, to understand potential growth-stress trade-offs and identify quick-to-measure physiological proxies, we asked how these dynamic physiological rates measured in our study compared to previously published data on relative growth rate and carbon allocation (aboveground carbon sequestration, diameter at breast height, specific leaf area, leaf dry matter content [LDMC], and leaf carbon:nitrogen ratio [CN]) collected in the same parks on the same plants examined in our study by Simovic et al. (2024).

Specifically, we asked the following:

  1. Do tree physiological rates differ across parks with different weather patterns or according to soil properties of the planting location?

  2. Do tree species native to Northeast Ohio exhibit physiological rates consistent with late-summer water stress, including a larger change in Kleaf and a smaller seasonal change in ΨTLP, compared with the Southeastern US native Liquidambar styraciflua and East Asian Pyrus calleryana?

  3. Are faster physiological rates and greater seasonal change in water relations associated with quick-to-measure traits reflecting faster relative growth rates and/or lower carbon allocation to leaves and wood?

Materials and Methods

Experimental Design

We conducted our study in two parks, Lakeview Cemetery (41.514, −81.598), located 8 km south of Lake Erie, and Secrest Arboretum (40.778, −81.918), located 88 km south of Lake Erie. Trees at the two parks are not irrigated or fertilized. We determined seasonal changes in Kleaf and ΨTLP as well as late-summer gas exchange rates (A and gs) and photosynthetic capacity (maximum electron transport rate [Jmax] and maximum carboxylation rate [Vcmax]) calculated from A/Ci (photosynthetic CO2 response) curves to characterize tree responses to summer growing conditions. We sampled 3 individuals of each species at each park. We measured Kleaf and water potential at turgor loss point (ΨTLP) at both parks in early summer (2018 June 8–2018 July 12) and late summer (2018 August 1–2018 August 31). We investigated how these dynamic physiological rates differed across 2 parks and 5 species.

We compared physiological data collected in our study to data on planting-site soil properties measured for the same trees examined in this study and previously published in Simovic et al. (2024). For soil properties, 3 soil cores were extracted at 40-cm depth at the bole of each tree and averaged. We also compared our physiological data to data published in Simovic et al. (2024) on relative growth rate and carbon allocation (aboveground carbon sequestration, diameter at breast height in 2019, specific leaf area, leaf dry matter content [LDMC], and leaf carbon:nitrogen ratio [CN]) measured for the same individuals in this study. In this previous publication it was noted that most trees in the study had at least 90% healthy crown, and none of the trees examined here had canopy dieback or discoloration greater than 25% (Simovic et al. 2024).

Weather During the Study Period

We obtained data from nearby weather stations for each park from 2018 May 1–2018 August 31 (i.e., one month prior to and during the physiological sampling period). Data for Secrest Arboretum was obtained from the Ohio Agricultural Research and Development Center (OARDC) weather station located approximately 2 km west of Secrest, and data for Lakeview Cemetery was obtained from Cleveland Hopkins International Airport, located approximately 24 km southeast of Lakeview. We also obtained long-term climate means from the National Oceanic and Atmospheric Administration (NOAA).

Leaf Hydraulic Conductance Measurements

For our measurements of Kleaf we collected branches approximately 20 cm long the day prior to measurement. We sampled branches from the outer crown on the south side of the tree at approximately 5 m high. Shoots were immediately placed in a dark cooler filled with wet paper towels. The samples were trimmed by at least 3 nodes under water and allowed to rehydrate overnight (Sack and Scoffoni 2012). Leaf-hydraulic and turgor-loss measurements were taken in both early and late summer. All branches remained in water in a dark cooler until just prior to taking leaf-hydraulic measurements.

On the day following branch collection, Kleaf was measured in the laboratory using the evaporative flux method (Sack and Scoffoni 2012). Leaves were cut from the branches under deionized water and attached to the hydraulic manifold. The flow solution was deionized water that was partially degassed and filtered to remove particles larger than 0.2 mm. Leaves were placed under approximately 1,200 µmol PAR (photosynthetically active radiation). Once leaves reached a steady state of flow, we averaged the final 10 flow measurements. Leaf and air temperature were recorded to account for the temperature effect on water viscosity. Leaves were immediately removed from the manifold, the petiole was dried, and the leaf was placed in a plastic bag filled with exhaled air and allowed to equilibrate for at least 20 minutes. Water potential was recorded using a pressure chamber (Model #600, PMS Instruments, Albany, OR, USA). Kleaf was corrected for the temperature sensitivity of water viscosity with equation 2 reported in Sack and Scoffoni (2012). Finally, we measured leaf lamina area with a leaf area meter (LI-3100, LI-COR, Inc., Lincoln, NE, USA) to standardize leaf hydraulic conductance by leaf area. To understand seasonal progression of Kleaf, we calculated ΔKleaf, or the difference in values from early to late summer.

Gas Exchange Rates

Gas exchange was measured in the late summer. Because we wanted to measure leaves taken from a comparable place in the tree canopy as those sampled for hydraulics, and because it was not possible to bring our gas exchange system up into the canopy, we used excised branches. Although branch excision may initially decrease gas exchange, our protocol used the same branches collected for summer Kleaf and thus included overnight rehydration time. This allows branches to acclimate to their new environmental conditions, which enables photosynthetic rates to adequately adjust (Verryckt et al. 2020). Gas-exchange measurements took place in the lab from 8:00–13:00. We used a portable photosynthesis system (LI-6400, LI-COR, Inc., Lincoln, NE, USA) to measure A/Ci curves. Sample chamber conditions were set to 25 °C; relative humidity was kept between 40% to 60%; and Photosynthetic Photon Flux Density = 1,500 µmol m−2 s−1, with the following progression of CO2 levels: 400, 2,000, 1,500, 1,000, 400, 100 and 50 ppm. Following stabilization at each CO2 level (typically about 15 minutes), we collected 6 measurements over a 1-minute period to calculate mean gas exchange rates for each plant at each CO2 level. We calculated Jmax and Vcmax using the equations of Ethier and Livingston (2004). Lastly, we calculated net assimilation rate (Anet), transpiration rate (E), and stomatal conductance (gs) from the CO2 response measurements taken at ambient CO2 levels (400 ppm) and we calculated instantaneous water use efficiency (WUE) at 400 ppm by dividing Anet by E.

Estimation of Water Potential at Turgor Loss Point

We used a protocol described in Bartlett et al. (2012) to estimate water potential at turgor loss point (ΨTLP). In both early and late summer, a small leaf punch of 8 mm was taken from the center of the leaf lamina of one leaf on one of the branches collected to measure Kleaf, avoiding the midrib and large veins. Briefly, leaf discs were wrapped in tin foil and frozen in liquid nitrogen, then punctured with a needle followed by placement into a vapor pressure osmometer (Vapro Model #5600, Wescor, Inc., South Logan, UT, USA) to obtain osmotic potential at full turgor. We calculated ΨTLP from osmotic potential at full turgor using an equation reported by Sjöman et al. (2015). This equation was developed from the original dataset from Bartlett et al. (2012) but specified for only the species from temperate biomes and is therefore the most appropriate for the species included in this study. To better understand the seasonal progression of ΨTLP, we calculated ΔΨTLP, or the difference in values from early to late summer.

Data Analysis

We used ANOVA to investigate variation in weather, physiological rates, planting-site soil, relative growth rate, and carbon allocation across parks and species. We used principal component analysis (PCA) to (1) create a combined metric of soil properties for analysis, and (2) determine the relationships between tree physiological rates to relative growth rate and carbon allocation. Several factors differed across the parks, including weather, soils, and the mean height and diameter at breast height (DBH), which were both larger for trees at Secrest compared to Lakeview (Table 1). For these reasons, and to account for other potential variation between parks that we did not measure, we included park as a predictor in our statistical models.

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Table 1.

Mean and standard deviation of plant height and diameter at breast height (DBH) for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeast Ohio parks, Lakeview and Secrest. These represent a subset of data published in Simovic et al. (2024).

First, we tested for the effect of park on weather collected at nearby weather stations (daily maximum temperature, daily minimum temperature, and daily precipitation) using a linear mixed effects model using the lme function in the package ‘nlme’. We set park and date as the predictors, with date as a random factor, and method = “REML”. Following, we passed this model to the Anova function in the package ‘car’ to generate test statistics.

Second, we tested the effects of park, species, and their interaction on tree physiological rates (Kleaf, ΨTLP, and gas exchange), planting-site soil properties (percent sand, silt, and clay and bulk density), relative growth rate and carbon allocation (carbon sequestration, DBH, specific leaf area, leaf dry matter content [LDMC], and leaf carbon:nitrogen ratio [CN]). We generated linear models using the lm function which we then passed to the Anova function in the package ‘car’ to generate test statistics. In cases where species was found to have a significant effect, we generated pairwise comparisons using the TukeyHSD function.

Third, we tested for relationships between plant physiological rates and soil characteristics of the planting sites. For soil, due to the colinearity of soil variables (% clay, % sand, % silt, and bulk density), we used principle component analysis (PCA) to create a combined soil properties metric, represented by the first 2 principal component scores (PC1 and PC2), which were subsequently used as the dependent variable. PCA was computed using the prcomp function, with center and scale = TRUE. For this PCA, we excluded one Acer rubrum individual from Lakeview with clay and sand percentages that were more than 2 standard deviations from the mean, and one Acer saccharum for which we did not have data on soil properties. We used a linear mixed effects model with each physiological rate as the dependent variable, and the first 2 soil principal components (PC1 and PC2) as fixed effects, and we accounted for autocorrelation between samples taken at the same park (i.e., within-park similarities in soil properties, as well as unmeasured factors such as tree diameter, tree age, and atmospheric composition) by using park as a random effect in this model. We used the lme function from the package ‘nlme’ and method = “REML”, followed by Anova to generate test statistics.

Fourth, we asked whether urban-park trees exhibit seasonal changes in Kleaf and/or ΨTLP. For this we used a linear mixed effects model, setting either Kleaf or ΨTLP as the dependent variable, with park, season, species, and all 2-way interactions as the independent fixed effects. We used individual plant as a random effect in this model to account for multiple measurements of the same individual at 2 time points. Model significance was determined in the same way as described above using the Anova function.

Lastly, to understand coordination of seasonal changes in Kleaf and ΨTLP with growth and carbon allocation, and to determine whether Pyrus calleryana has a more acquisitive life history strategy compared to Eastern US tree species, we again used the ‘prcomp’ function to conduct PCA. To avoid overspecification of the PCA, we excluded early-summer and late-summer values of Kleaf and ΨTLP, because these are used to calculate ΔKleaf and ΔΨTLP. In addition, we found strong significant correlations among gas exchange variables A, E, gs, Vcmax, and Jmax (correlation coefficient > 0.85), so we chose to represent this suite of variables using gs and WUE in our analysis. Thus, we included the following variables in the PCA: ΔKleaf, ΔΨTLP, Jmax, Vcmax, and WUE from our study, along with specific leaf area (SLA), CN, LDMC, relative growth rate, DBH, and carbon sequestration published in Simovic et al. (2024). We extracted PC1 and PC2 scores for all individuals to test for effects of park, species, and their interaction using the lm function followed by Anova, as described above. We also computed pairwise correlation coefficients between these same variables using the ‘cor’ function and generated P-values using the ‘rcorr’ function.

All data analyses were conducted in R (version 4.3.1)(R Core Team 2021).

Results

Long-Term Climate Means and Weather During the Study Period

Long-term average summer minimum temperature near Lakeview is 18.9 °C, maximum is 26.1 °C, and precipitation is 25.3 cm (NOAA 2025). Nearby Secrest, long-term average summer minimum temperature is 14.9 °C, maximum is 27.8 °C, and precipitation is 33.1 cm (NOAA 2025).

During the study period, daily maximum temperatures (MaxTemp) were similar at both parks in early summer, but during the month of August, MaxTemp was 1.7 °C ± 3.0 °C lower at Secrest compared to Lakeview (Figure 1a). Using a linear mixed effects model, we did not find a significant effect of park (Chi-square 1.26, P = 0.26), but we did detect significant effects of date (Chi-square 14.68, P = 0.0001) and a significant park × date interaction (Chi-square 15.58, P < 0.0001). Daily minimum temperature (MinTemp) was 2.1 °C ± 1.4 °C higher at Lakeview compared to Secrest, and this difference was consistent throughout the study period (Figure 1b), though the differences were smaller in early summer and increased throughout the summer, and we found significant effects of park (Chi-square 129.69, P < 0.0001), date (Chi-square 53.10, P < 0.0001), and a significant park × date interaction (Chi-square 7.99, P < 0.0047). For both parks, precipitation was above the long-term average for the site, and the total precipitation during the study period was higher at Lakeview compared to Secrest (55.3 cm versus 38.5 cm, respectively)(Figure 1c). We did not detect any significant effects of park (Chi-square 2.87, P = 0.09), date (Chi-square 0.19, P < 0.6595), or park × date interaction (Chi-square 0.01, P = 0.91).

Figure 1.

Weather at the two study parks before and during the physiological measurements, including (a) maximum temperature, (b) minimum temperature, and (c) precipitation. For a and b, dashed horizontal lines represent the mean maximum and minimum temperatures at each park during the study period, and solid lines represent the long-term mean maximum or minimum temperatures at each park.

Physiological Rates Across Parks and Species

Physiological rates varied across parks and species. All measured physiological rates were higher at Lakeview compared to Secrest, including higher late-summer Kleaf (Figure 2a), higher (i.e., less negative) early-summer ΨTLP (Figure 2b), a larger change in Kleaf (higher ΔKleaf)(Figure 2c), higher gas exchange rates (A [Figure 2d), gs [Figure 2e]), higher instantaneous water use efficiency (WUE)(Figure 2f), higher carboxylation rates (Vcmax)(Figure 2g), and higher electron transport rates (Jmax)(Figure 2h). For the most part, physiological rates that differed across parks did not differ according to species, and we did not find any significant park × species interactions (Table 2). Liquidambar styraciflua had significantly higher Kleaf values compared to all other species (Figure 3a). We also found significant effects of species on early summer and late-summer ΨTLP; in this case, Pyrus calleryana had lower values compared to all other species (Figure 3b, 3c).

Figure 2.

Physiological rates for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeastern Ohio parks, Lakeview and Secrest, including (a) late-summer maximum leaf hydraulic conductance (Kleaf_late), (b) early summer turgor loss point (TLP_early), (c) the change in Kleaf from early to late summer (delta_Kleaf), (d) net assimilation rate (A), (e) stomatal conductance (gs), (f) water use efficiency (WUE), (g) maximum carboxylation rate (Vcmax), and (h) maximum electron transport rate (Jmax). Error bars represent standard error.

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Table 2.

F-values from ANOVA testing for the interactive effects of park and species on tree traits and soil properties in each tree planting location for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeast Ohio parks, Lakeview and Secrest.

Figure 3.

Physiological response to seasons for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeastern Ohio parks, Lakeview and Secrest, including (a) maximum leaf hydraulic conductance (Kleaf) across the two parks and water potential at turgor loss point (ΨTLP) at (b) Lakeview and (c) Secrest. Error bars represent standard error.

Seasonal Changes in Physiological Rates for Different Species at the Two Parks

Using linear mixed effects models, we found significant effects of park and species on Kleaf, but the differences among species depended on the park and season (significant species × park interaction and season × park)(Table 3). For most species, Kleaf was higher at Lakeview compared to Secrest, and Liquidambar styraciflua had the highest Kleaf values at both parks in both early and late summer (Figure 3a). The rank order of Kleaf values differed across parks, such that Acer saccharum had the lowest Kleaf values at Lakeview, while at Secrest the lowest values were observed for Pyrus calleryana and A. rubrum. We did not find a significant effect of season on Kleaf in this analysis.

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Table 3.

F-values for linear mixed effect model testing for interactive effects of season, species, and park on maximum leaf hydraulic conductance (Kleaf) and turgor loss point (ΨTLP) for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeast Ohio parks, Lakeview and Secrest.

For ΨTLP, we found significant main effects of season, park, and species, but no interactions. Early summer ΨTLP was higher than late summer, and values were higher at Lakeview (Figure 3b) compared to Secrest (Figure 3c). Lastly, the 3 Ohio native species and Southeastern US native L. styraciflua all had significantly higher ΨTLP compared to P. calleryana across both seasons and both sites.

Effects of Planting-Site Soil Properties on Physiological Rates

Planting-site soils at Lakeview had higher clay percentage while those at Secrest had higher silt percentage (Table 4), and there was a significant effect of park in our ANOVA model. The sand percentage and bulk density were not significantly different between the two parks (Table 2).

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Table 4.

Species mean and standard deviation of planting-soil properties, relative growth rate, and carbon allocation (carbon sequestration, diameter at breast height in 2019 at the end of the experiment, specific leaf area, leaf dry matter content, and leaf carbon:nitrogen ratio) for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeast Ohio parks, Lakeview and Secrest. Data are for the same plants examined in our study from a larger dataset published in Simovic et al. (2024).

The first 2 principal components of the soil PCA analysis explained 50% and 27% of the variance in soil properties, respectively, with PC1 being composed primarily by percent sand in opposition with percent silt, while PC2 was composed primarily by precent clay and to a lesser extent bulk density (Figure 4a). ANOVA indicated significant effects of park on PC1 and PC2 (Table 2). PC1 scores showed that planting-site soils at Secrest covered the full range of variation in PC1, from sandy to silty, but Lakeview soils were more like one another and consistently sandy for all planting sites. PC2 scores showed Lakeview had a higher clay percentage and higher bulk density compared to those at Secrest.

Figure 4.

Analysis of soil properties in the planting location versus physiological rates for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeastern Ohio parks, Lakeview and Secrest, including (a) principal component analysis for soil properties, as well as relationships of the second principal component (soilPC2) to (b) late-summer maximum leaf hydraulic conductance (Kleaf_late), (c) net assimilation rate (A), (d) water use efficiency (WUE), (e) maximum carboxylation rate (Vcmax), and (f) maximum electron transport rate (Jmax). Lakeview = circles and Secrest = triangles.

Using mixed effects ANOVA with park as a random covariate to account for unmeasured differences across parks, we found that tree physiological rates were related to soil PC2 (Table 5). Late-summer Kleaf (Figure 4b), net photosynthesis (A)(Figure 4c), water use efficiency (WUE)(Figure 4d), Vcmax (Figure 4e) and Jmax (Figure 4f) were all higher for plants with higher soil PC2. The relationships of late-summer Kleaf and WUE were weak (R2 < 0.15), though moderate correlations were found with A and Jmax (R2 = 0.36).

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Table 5.

F-values from ANOVA testing for the effects of planting-site soil characteristics (as represented by the first and second principal components (Soil PC1 and Soil PC2, respectively) on physiological rates for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeast Ohio parks, Lakeview and Secrest.

Relationship of Relative Growth Rate and Carbon Allocation to Physiological Rates

Relative growth rates were almost twice as high for trees at Lakeview compared to Secrest (Table 4), and this effect was significant in our linear model (Table 2). All Ohio native species and L. styraciflua had lower carbon sequestration at Lakeview compared to Secrest, though A. rubrum trees were much larger than other species at Secrest. In addition, P. calleryana showed the opposite pattern (Figure 5a), and we found a significant park × species interaction for carbon sequestration. Similarly, A. rubrum, A. saccharum, N. sylvatica, and L. styraciflua had smaller diameter at breast height (DBH) at Lakeview compared to Secrest. Compared to other species, the difference across parks was much smaller for A. saccharum and P. calleryana. These 2 species had the highest DBH at Lakeview and the lowest DBH at Secrest (Figure 5b), and we found a significant park × species interaction for DBH (Table 2). Leaf carbon:nitrogen ratio (CN) was lower at Lakeview compared to Secrest for A. saccharum, L. styraciflua, and N. sylvatica, but A. rubrum and P. calleryana had overall lower values and were the same at the two parks (Figure 5c), and we found a significant park × species interaction for this variable. Leaf dry matter content (LDMC) was significantly different across species (Table 2). Acer rubrum had the highest value, L. styraciflua had the lowest value, and A. saccharum, N. sylvatica, and P. calleryana were intermediate (Figure 5d).

Figure 5.

Growth and carbon allocation traits and principal component analysis showing relationship of tree physiological rates measured for the 5 study species (Acer rubrum = ACRU, A. saccharum = ACSA, Liquidambar styraciflua = LIST, Nyssa sylvatica = NYSA, and Pyrus calleryana = PYCA) growing at two Northeastern Ohio parks, Lakeview and Secrest, compared to growth and carbon investment measured in Simovic et al. (2024), including (a) carbon sequestration, (b) diameter at breast height, (c) leaf carbon:nitrogen ratio, (d) leaf dry matter content, and (e) principal component analysis. For panels a, b, c, and e, sites are denoted by different shapes, with Lakeview = circles and Secrest = triangles. Rel.growth (relative growth rate); Cabon.seq (carbon sequestration); LDMC (leaf dry matter content); (CN) leaf carbon:nitrogen ratio; DBH.19 (tree diameter at breast height at the end of the study in 2019).

The first 2 principal components of the plant traits PCA explained 35% and 15% of the variation, respectively. The first component, PC1, was composed of both physiological rates and carbon allocation traits, with relative growth rate being positively correlated with WUE and gs, in opposition to DBH (Figure 5e). SLA, CN, LDMC, and carbon sequestration contributed relatively equally to PC1 and PC2. The main components of PC2 included the seasonal change in Kleaf from early to late summer (ΔKleaf) and corresponding seasonal change in ΨTLP (ΔΨTLP). Higher ΔKleaf and concomitantly smaller ΔΨTLP were associated with higher carbon sequestration, lower CN, and higher LDMC. Lastly, ΔKleaf and ΔΨTLP were largely orthogonal to relative growth rate (RGR), DBH, WUE and gs. Based on ANOVA, PC1 scores were significantly higher at Secrest compared to Lakeview (Table 2).

Pairwise correlations showed that ΔKleaf was significantly positively correlated with WUE, Vcmax, and Jmax, but negatively correlated with CN (Table 6). Both Vcmax and Jmax were significantly positively correlated with relative growth rate and negatively correlated with carbon sequestration, while Jmax was significantly negatively correlated with DBH.

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Table 6.

Pairwise correlation coefficients for traits measured in this study compared to traits measured on the same trees and published in Simovic et al. (2024) for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeast Ohio parks, Lakeview and Secrest. ΨTLP (water potential at turgor loss point); WUE (instantaneous water use efficiency); Vcmax (maximum carboxylation rate); Jmax (maximum electron transport rate); DBH (diameter at breast height); CN (carbon:nitrogen ratio); Rel.growth (relative growth rate); Carb.seq (carbon sequestration); LDMC (leaf dry matter content); SLA (specific leaf area).

Discussion

We measured physiological responses to seasonal variation for 3 Ohio native tree species (Acer rubrum, Acer saccharum, and Nyssa sylvatica), along with the Southeastern US species Liquidambar styraciflua and East Asian Pyrus calleryana, at two urban parks in Northeast Ohio. We found that nearly all measured physiological rates were higher at Lakeview, indicating faster and more efficient growth, compared to Secrest. Physiological rates do not account for factors such as differences in tissue construction costs (Kruger and Volin 2006), which may be one reason why we did not see correspondingly higher carbon sequestration at Lakeview in our study. Trees at Lakeview did have a net-positive change in maximum leaf specific hydraulic conductance (ΔKleaf) from early to late summer, indicating that growth was not hindered by evaporative demand, which our data suggests did not exceed the ability of the plant to supply water to the leaf (Sack and Scoffoni 2012; Scoffoni et al. 2016). At Secrest, declines in Kleaf and ΨTLP over the season suggest that trees at this site did experience mild seasonal water stress (Brodribb and Holbrook 2003; Maréchaux et al. 2018). But overall, we saw physiological adjustments in Kleaf and ΨTLP from early to late summer at both parks, which should mitigate drought stress and contribute to the relatively robust photosynthetic rates we observed during late summer. Compared to P. calleryana, these seasonal adjustments were similar in magnitude for the other study species, demonstrating their ability to comfortably manage late-summer water stress in an urban setting.

Secrest was drier than Lakeview during the period of this study, and long-term climate records indicate that trees at Secrest experienced lower-than-average summer temperatures, whereas the summer was hotter than usual at Lakeview. These weather patterns are influenced by the proximity of Lakeview to Lake Erie, which results in higher cloud cover, precipitation, and humidity compared to Secrest. In addition, Lakeview is a larger and more densely planted park compared to Secrest, which could have large impacts on micro-scale climate experienced by individual trees. Our weather data should be viewed as characterizing only the prevailing weather conditions at each park, but in addition to the larger park size and higher planting density at Lakeview, the combined evidence suggests that trees at this park experienced conditions more similar to surrounding native forest compared to Secrest.

While our climate analysis does not capture climate variation at the scale of individual trees, our soil analysis does provide insight into tree-scale variation across the parks. Planting soils at Lakeview had a higher proportion of clay and lower silt compared to those at Secrest, suggesting they could have slower drainage, although there was substantial variation in soil texture within parks as well. We found that Kleaf in late summer as well as the efficiency of gas exchange (water use efficiency, maximum electron transport, and carboxylation rates) were all higher with increasing clay percentage and higher bulk density. While higher performance at higher bulk density may seem counterintuitive, the range of bulk densities at our study sites was on the lighter side for urban areas, though some planting-site soils approached what is considered the upper limit for unrestricted root growth (1.6 g cm−3)(Scharenbroch et al. 2005). If higher bulk density is driven by higher clay contents, rather than compaction, the higher clay percentage could improve soil water-holding capacity or cation-exchange capacity. Interestingly, planting-site soils at Lakeview and Secrest parks had bulk density values that were 3× to 4× higher and sand percentages that were 2× higher compared to soils in a nearby forested area which includes the Ohio native species we studied here (personal communication Katie Stuble). The percentage clay in nearby forested areas was similar to that measured at Lakeview, but approximately 2× higher than percentage clay measured at Secrest (personal communication Katie Stuble). This similarity between nearby forests and Lakeview soils could contribute to the higher physiological rates we observed at Lakeview.

Another potential factor contributing to higher physiological rates at Lakeview is the fact that the trees were smaller compared to those at Secrest (Table 4), and water transport and photosynthetic capacity typically decline with tree size (Bond 2000). In support of this idea, our pairwise correlations did show that photosynthetic efficiency was positively correlated with relative growth rate but negatively correlated with tree size. Tree size has rarely been considered in studies of urban tree physiology (but see Simovic et al. 2024), and our work shows that this could be important to clarify the sources of physiological variation within urban spaces. It is also important to note here that we found variation in both tree size and soil properties across the two parks we investigated. Our use of park as a random factor in our soil analysis does provide confidence that soil does affect physiology independent of other factors that differ across parks, but the full extent to which soil versus size drives our results cannot be determined based on the current study. These findings highlight the complexity of the urban environment and the need for physiological proxy measures in urban tree selection, since the time-consuming nature of the seasonal physiological measurements limited the number of parks and trees we could include in our study.

Within this context, our investigation of seasonal responses at each site provides valuable insight because this analysis is independent of tree size. We hypothesized that the seasonal physiological response of trees could depend on whether the species is fast- or slow-growing (Wright et al. 2004), a trait which foresters may use to select suitable species (Rahman et al. 2015). We did find some support for this hypothesis, as our pairwise correlations did show a significant negative relationship of CN to ΔKleaf. Plants with lower CN are expected to have a more acquisitive physiology (Reich 2014), and our data show that these plants had a larger change in Kleaf across seasons. In addition, our principal component analysis showed that the change in water potential at turgor loss point from early to late summer (ΔΨTLP) was positively correlated with relative growth rate and negatively correlated with carbon sequestration. In this analysis, LDMC was also positively correlated with ΔΨTLP, with a larger change indicating higher resistance to loss of turgor pressure in late summer. Pairwise correlations showed no significant correlations between these variables however, suggesting that other traits moderate the relationship of LDMC to ΔΨTLP. A previous study of the same trees suggested that higher LDMC might alleviate water stress, if it was correlated with a higher resistance to loss of turgor pressure and/or xylem conductivity (Simovic et al. 2024). Our work supports this hypothesis and further suggests that LDMC and CN, which are both extremely quick-to-measure traits, should be further explored as proxies for determining the growth and stress responses of species. Interestingly, P. calleryana in our study had the highest growth rate at Lakeview and the lowest growth rate at Secrest, such that the mean across the two parks was intermediate, and this species was not statistically distinguishable from others in this analysis.

The two Acer species we examined were highly similar in their responses, although we observed key contrasts with relevance for urban plantings. Acer rubrum is a pioneer, bottomland species which is commonly found on disturbed soil and can tolerate a wide range of soil types (Burns et al. 1990). Acer rubrum has a strong ability to acclimate to stressful urban conditions (McDermot et al. 2020) such that its photosynthetic rates can be higher in urban compared to rural areas (Lahr et al. 2018). Our data show that this species had a high ΨTLP, which did not change across seasons, leading to the steepest seasonal decline in Kleaf and the lowest late-summer Kleaf compared to all other species. This is consistent with previous work showing a decline in gas exchange rates of A. rubrum from early to late summer (Lahr et al. 2018). Our principal component analysis adds to this by showing that A. rubrum trees are more different from one another than they are compared to trees of other species (widely dispersed along PC1 and PC2), perhaps reflecting their strong ability to acclimate to different growing conditions (McDermot et al. 2020) or higher intraspecific genetic variation for A. rubrum. Acclimation ability in particular may explain high variation in A. rubrum performance across different types of conditions (Burns et al. 1990), because acclimating to optimize growth under current site conditions can compromise future survival if conditions change (Medeiros 2025).

Our study sites are within the center of the native range of A. rubrum, but the other Acer species we examined, A. saccharum, has a more northerly distribution (Burns et al. 1990). This is a climax species which is restricted to cool, moist upland habitats, and it does best on well drained loam soil (Burns et al. 1990), suggesting that A. saccharum should have poor performance in urban sites. Instead, we found this species performed very similarly to A. rubrum, including having low Kleaf and high ΨTLP, which did not change appreciably across seasons. One reason for their similar performance may be the ability of A. saccharum to tolerate compacted soils (Leasia et al. 2012). Acer saccharum was shown to be the second most commonly planted urban tree in the Midwest United States, while A. rubrum was the sixth most common (Schoon 1993). Our study shows that A. saccharum trees had the lowest spring Kleaf at Lakeview but the highest ΨTLP at Secrest, and individual trees exhibited strong similarity to one another in our principal component analysis. This is consistent with the idea that this species has lower acclimation ability and implies that it may reach its turgor loss point earlier and more severely compared to A. rubrum but could also reflect lower within-species genetic variation for A. saccharum.

In terms of carbon allocation, the two Acer species had similarly high LDMC values compared to other species, but A. rubrum trees were the largest trees at both parks in terms of DBH and height. Compared to trees at Lakeview, all those at Secrest were larger and they grew more slowly, but A. rubrum showed the largest contrast in size across parks, again reflecting high variation across growing condition for this species. Simovic et al. (2024) also showed that trees at Secrest were older compared to those at Lakeview, and that younger age explains the smaller sizes at Lakeview rather than differences in park environmental conditions. Our physiology data provides additional support for this conclusion by showing that all measures of physiological performance were higher at Lakeview compared to Secrest, which is consistent with data on physiological variation between older and younger trees (Bond 2000).

We also investigated East Asian Pyrus calleryana because this species has been considered better suited to urban conditions compared to other tree species (Rahman et al. 2015). Further, the 2023 ban on planting this species in Northeast Ohio necessitates identification of other species which can be successful in sites where P. calleryana is currently planted. In our study, P. calleryana had a slightly larger ΔΨTLP from early to late summer compared to other species, but we did not see discrepancies in ΔΨTLP among species, seasons, or parks. This may be in part because the lowest ΨTLP values we measured were less negative compared to those measured in previous studies of forest trees (Table 7), suggesting that trees at our study parks did not experience water stress outside what they would experience in their native habitats. This is perhaps surprising given that urban trees are often expected to be more drought-stressed compared to nonurban counterparts (Sjöman et al. 2015; Sjöman et al. 2018) and it highlights that our assumption of higher drought stress for urban trees will not be universally true, especially in urban parks. Carbon allocation of P. calleryana was strikingly different from all other study species, with lower carbon sequestration rates in aboveground woody biomass and low CN at both parks. Low CN indicates faster growth rate (Wright et al. 2004), which is commonly associated with low wood strength (Poorter et al. 2010), providing support for the idea that this species is less structurally sound than native tree species (Dirr 1990).

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Table 7.

Comparison of ΨTLP and ΔΨTLP for the 5 study species (Acer rubrum, A. saccharum, Liquidambar styraciflua, Nyssa sylvatica, and Pyrus calleryana) growing at two Northeast Ohio parks, Lakeview and Secrest and measured in this study with values measured in forest trees reported in (a) Sjöman et al. (2015) and (b) Sjöman et al. (2018). ΨTLP (water potential at leaf turgor loss); ΔΨTLP (the difference in values from early to late summer).

Interestingly, ΨTLP values for Liquidambar styraciflua and Nyssa sylvatica were not significantly different from Pyrus calleryana at Lakeview and they were lower compared to the two Acer species. We also found that L. styraciflua and N. sylvatica, along with P. calleryana, had the highest values of Kleaf across both sites and seasons. Liquidambar styraciflua, native to the Southeastern United States and the southern part of Ohio, has previously been shown to acclimate to drought and salt stress (Baraldi et al. 2019) and different types of urban planting conditions (Kjelgren and Clark 1993). We found that L. styraciflua had carbon sequestration that was statistically indistinguishable from P. calleryana at Secrest, our more stressful site, and the DBH of these two species was not statistically distinguishable at either site. Lastly, L. styraciflua has the lowest LDMC value of any species, and combined with the growth patterns, our data suggest this species would perform similarly to P. calleryana in Northeastern Ohio park plantings. Yet, L. styraciflua was ranked 22nd in terms of presence in urban areas (Schoon 1993), indicating this species is underutilized.

In contrast, virtually nothing was previously known about the physiology of Nyssa sylvatica in urban settings, which was ranked 97th in terms of commonality in urban spaces (Schoon 1993). This species prefers well-drained light-textured soils found in creek bottoms, and trees growing on dry upland sites tend to be smaller (Burns et al. 1990), which may be one reason why they seem to be passed over in choosing urban trees. Our study parks are at the northern edge of N. sylvatica range (Burns et al. 1990), so the shorter growing season could explain the fact that trees of this species were the smallest in our study. Nyssa sylvatica also has higher growth rates in the presence of deep, periodic flooding (Keeland and Sharitz 1995), but our study suggests that they are highly suitable trees for urban parks in Northeast Ohio, potentially due to their ability to tolerate swings from drought to waterlogging that can occur in compacted urban soil (Scharenbroch et al. 2005).

Given the high heat and water stress reportedly experienced by urban street trees, it makes sense that urban foresters have sought to determine drought-tolerant species suitable for these extreme conditions (McCarthy et al. 2011; Cregg et al. 2023). Our study highlights the fact that not all urban environments are characterized by drought, and parks may be particularly good choices to increase the diversity of urban tree species. For example, L. styraciflua trees planted in urban parks experience less water and nutrient stress compared to those planted in areas with a greater amount of adjacent impervious surface (Kjelgren and Clark 1993). Isolated trees in parks should have minimal light limitation, potentially increasing the negative impacts of water limitation (Simovic et al. 2024), but this may be counteracted by relatively larger soil volumes and minimal competition, allowing for better root growth and water relations compared to plaza or street trees.

Here, we have presented perhaps the most detailed seasonal comparison to date of native and non-native tree physiology in urban parks. By combining leaf hydraulic conductance, turgor loss point, and photosynthetic CO2 response curves and harnessing the interpretive power of 2 seasonal time points, we offer unique insight into how park trees manage environmental conditions. Importantly, our study shows that species native to Ohio or the Eastern United States performed comparably to East Asian P. calleryana and thus might make good alternatives in Northeastern Ohio parks that previously included P. calleryana. The assessment of tree species for Northeastern Ohio parks is far from complete, however, as the Ohio Department of Natural Resources includes 99 species native to the state, and each urban area has its own nearby local populations of native species for consideration. Thus, our results should be considered exploratory, opening the door for new hypothesis testing, rather than an exhaustive assessment of species suitability. These findings do provide a foundation for city planning and future research, particularly in Northeast Ohio. Specifically, our identification of LDMC and leaf C:N ratio as potential quick-to-measure proxies for physiology has practical implications, and future work should consider these traits for a larger number of individual plants, for more species, and across sites with different urban land-use types to better assess the suitability of diverse tree species for use in urban forestry settings.

Conflicts of Interest

The authors reported no conflicts of interest.

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