Comparative Gas Exchange of Ulmus crassifolia (Cedar Elm, Ulmaceae) and Ungnadia speciosa (Mexican Buckey, Sapindaceae) at Ambient and Elevated Levels of Light, CO₂ and Temperature

Matthew B. Grunstra, Oscar W. Van Auken

Department of Integrative Biology, University of Texas at San Antonio, San Antonio, TX, USA.

DOI: 10.4236/ajps.2023.146047                

Abstract

Ulmus crassifolia Nutt. (Cedar elm, Ulmaceae) is a tree found in central and east Texas, northern Mexico, east to Florida, and north to southern Missouri and Oklahoma. Ungnadia speciosa Endl. (Mexican-buckeye, Sapindaceae) is a shrub or small tree found in woodlands and savannas of central and western Texas, southern New Mexico and northern Mexico. In central Texas, both species are found in Juniperus ashei/Quercus virginiana woodlands or savannas or also at low density in inter-canopy grassland gaps or patches. Environmental conditions in this area are stressful because of shallow soils, high summer temperatures, and inconsistent low rainfall. Currently, both species have a low density in these areas, and Ulmus crassifolia is usually a tree, while Ungnadia speciosa is a woody understory shrub. This study suggests U. crassifolia and U. speciosa are tolerant or intermediate species, with juveniles starting in shade. Maximum photosynthetic rate (A_max), dark respiration (R_d), intercellular CO₂, light saturation (L_sp) and water use efficiency significantly increased when light levels and CO₂ concentrations were elevated for both species, but not when temperatures were elevated. Stomatal conductance decreased when the CO₂ concentration doubled, but there were few effects from elevated temperature. These findings suggest that U. speciosa and U. crassifolia should be more common and imply that they will have a higher density in a future high CO₂ environment.

Keywords

Light Response, Gas Exchange, Photosynthesis, Respiration, Water Use Efficiency

1. Introduction

Plant communities around the world have changed many times historically and will continue changing in the future [1] [2] . Woodlands and savannas in central Texas are composed of communities with various densities of Juniperus ashei Buch. and Quercus virginiana Mill. (Ashe juniper and hill country live oak) [3] [4] [5] [6] [7] . These central Texas Juniperus woodlands are an example of Juniperus woodlands from all over the world (7) but contain specific species and sometimes species with very limited distributions (4). The structure of these communities in a future high-CO₂ and high-temperature world is unknown. There are various understory woody species in these communities that may become canopy species in the future, including Garrya ovata Benth. (Lindheimer’s silktassle), Diospyros texana Scheele (Texas persimmon), Rhus virens Gray (evergreen sumac), Sophora secundiflora (Ort.) DC (Texas mountain laurel), several species of Quercus (L., oaks) and a few other Leguminosae (Juss., legumes) [3] [5] [6] [7] [8] . Most of the understory species have received little ecological or environmental study.

We have not found anything in the literature regarding the current level of atmospheric CO₂ if it is in limited supply or excess in these central Texas Juniperus woodlands. In some plant communities, CO₂ concentration has been shown to be limiting and increasing levels promoted higher photosynthetic uptake and growth in the species present (8). However, we have not seen any work showing the effects of elevated CO₂, temperature and light levels in any Juniperus woodland communities, which is the focus of the present study and work presented.

Woodlands with various Juniperus species are found in many parts of North America, with elevation, climate and species composition varying [6] - [18] . In North America, these woodlands are found from the Atlantic to the Pacific coasts through the Great Plains to the low and mid-elevations of the mountains of the western United States, Canada and Mexico [14] [19] [20] [21] [22] [23] . In past times, in central and western North America, they were more commonly along canyon walls or steep slopes protected from fire or where there was not enough fuel for a fire [24] [25] [26] .

Juniperus communities today are widespread and have been treated by many as stable communities [6] [11] [13] [14] [17] [18] [21] [22] [23] [24] . However, various studies of encroachment have suggested they are pioneer successional communities leading to various forests [6] [27] [28] . Over time, the area covered and species composition of these communities will continue to transform, but their future composition and structure are unknown [29] [30] [31] [32] .

In the past 15,000 - 20,000 years, changes in the composition and distribution of plant communities have been mainly due to climate warming and glacial retreat [33] . More recently, in the past 200 - 500 years, changes in many North American plant communities were caused by the introduction of large populations of domestic ungulates, with constant grass herbivory and decreased fire frequency [34] [35] [36] [37] . Conditions resulted in the formation of Juniperus/Quercus savannas and woodlands in many places. Other environmental conditions appeared secondary [7] [38] - [44] . Future community composition will most likely be influenced by elevated atmospheric CO₂ and temperature [33] .

Canopy density can be highly variable in Juniperus communities, with a canopy cover of 40% to 90% [3] [6] [45] . Most of these communities have open patches with shallow soils populated by juvenile woody species, some grasses and other herbaceous species [46] - [51] . There are many low-density woody species in these communities, but it is unknown if some could become part of the canopy in the future.

In the future, these woodlands may remain dominated by a few species or the Juniperus species may be replaced by other species from below the canopy, changing to another community type. The pattern is controlled by the interaction of species, surface light, soil resources, herbivory, and fire [6] [27] [28] [31] [52] [53] . Due to modifications of climactic variables, the structure of many of these woodlands will change, and the composition of the future communities is unknown. These changing factors include atmospheric CO₂ and temperature, which are expected to continue increasing into the foreseeable future [33] . These central Texas Juniperus woodlands are an example of Juniperus woodlands that are present across the globe, but species here are different and some are quite rare [5] . Ecological success or competitive success of the low-density species found in these woodlands has never been examined [7] .

We hypothesize that the central Texas Juniperus/Quercus plant communities are changing. In addition, we theorize that certain understory species will become future canopy species. We envision that atmospheric CO₂ and temperature will be the driving forces. In the present study, we tested the short-term gas exchange response of Ungnadia speciosa and Ulmus crassifolia, two low-density and low-biomass understory species, to ambient and increased levels of light, CO₂, and temperature to project their future community composition.

2. Materials and Methods

The study site is in central Texas and is part of the University of Texas at San Antonio campus. Topography is rolling with slopes between 4.5˚ and 13.5˚ [54] and soils are clayey-skeletal, smectitic, thermic lithic calciustolls [55] in the Tarrant association with surface horizons between 0 and 25 cm thick [54] . The subsurface is heavily fractured limestone over limestone bedrock. Climate is subtropical-subhumid [56] with a mean annual temperature of 20˚C and ranges between 9.6˚C in January and 29.4˚C in July [57] . Precipitation is 78.7 cm/yr and bimodal, with peaks in May (10.7 cm) and September (8.7 cm) [57] . Precipitation is highly variable with very little reported in June and July with peaks in May and September. No domestic livestock were present in the study area for the past 75 years. There are large areas of Juniperus ashei/Quercus virginiana woodlands or savannas on former grassland sites which is considered representative of similar communities found in this region [3] .

Plants in the understory of mature relatively undisturbed J. ashei/Q. virginiana woodland communities were randomly selected for study. Mean structure of the communities was determined but limited information about structure is presented here (see [8] [58] ). All trees were identified, counted and measured. Concise but succinct information about community structure is presented below. Gas exchange measurements were made in the summer of 2007. Three plants were randomly selected for gas exchange responses at both ambient and elevated levels of CO₂ and temperature. Mature, non-damaged leaves were selected at breast height (approximately 137 cm above the soil surface) on each plant. Steady state photosynthetic light response curves (A_net vs. PAR) were completed [60] . Photosynthetic response curves were measured on fully expanded leaves at mid-day (1000 - 1400 hrs) when relative humidity had stabilized [60] . Replicates were one fully expanded leaf per plant that was placed into the cuvette of a portable photosynthetic meter (LICOR^® LI-6400). A leaf covered the entire chamber (2 × 3 cm) and was attached to the plant. Measurements made and recorded were: A_net (net photosynthesis = µmol CO₂·m⁻²·s⁻¹), C_i (intercellular [CO₂] = µmol CO₂·mol∙air⁻¹), T_leaf (chamber leaf temperature = ˚C), T_air (air temperature outside the chamber = ˚C), PAR (photosynthetic active radiation = µmol·m⁻²·s⁻¹), g (stomatal conductance = mol·H₂O·m⁻²·s⁻¹) and E (transpiration = mmol·H₂O·m⁻²s⁻¹).

The chamber was used to mimic varying degrees of environmental modifications. The light level, CO₂ concentration, and temperature were manipulated. Relative humidity was kept at 30% - 40% and the gas flow rate was set at 400 µmol/s. Coefficient of variation stabilized (<1%) before recording and moving to the next setting. Light levels started at 1800 µmol·m⁻²·s⁻¹ and decreased to 1600, 1400, 1200, 1000, 800, 600, 400, 200, 100, 75, 50, 25, 10, 5 and finally 0 µmol·m⁻²·s⁻¹. Light curves and CO₂ response curves were measured for different combinations of the leaf chamber CO₂ and temperature environments.

The leaf chamber was set at 2007 CO₂ levels (390 µL·L⁻¹) and a temperature of 35˚C. This temperature was chosen based on the mean high temperatures for San Antonio during the summer months of June, July and August. Light curves were repeated holding the ambient CO₂ constant while raising the chamber temperature to 40˚C and then to 45˚C. Next, the leaf chamber CO₂ was raised to 1.5 times the 2007 CO₂ levels to 585 µL·L⁻¹. Light curves were completed at a temperature of 35˚C, 40˚C and 45˚C. This process was then repeated with the leaf chamber CO₂ level set at twice the ambient level at 780 µL·L⁻¹. Lastly, CO₂ response curves were measured at a canopy shade light level (700 µmol·m⁻²·s⁻¹). Measurements were made at 35˚C, 40˚C and 45˚C.

Microsoft Excel^© and JMP^© IN 5.1 were used for data organization and analysis. The JMP^© IN 5.1 software measured significant differences using a repeated measures MANOVA on the photosynthetic rate curves, intercellular CO₂ concentrations, stomatal conductance and transpiration using the light level, PAR, as the repeat variable [61] . Water use efficiency was calculated by dividing the photosynthetic rate by the transpiration rate and also analyzed using a repeated measures MANOVA. Significance levels for all tests were P ≤ 0.05. Normality was checked with the Shapiro-Wilk W test and homogeneity of variance with Bartlett’s test and log transformed as necessary. A standard least squared ANOVA was used to detect significant differences in each curve at each CO₂ concentration and temperature combination. However, this is a curve to curve comparison and individual CO₂ uptake was not compared at individual light levels on each plant and each replication.

Other measurements were derived from Excel^® plots of the LICOR^® LI-6400 measurements. These included photosynthetic rate (A_max which was the highest A_net measured for each replicate or a mean of the highest A_net values that were not significantly different). The dark respiration rate (R_d) was the gas exchange rate at PAR = 0 µmol·m⁻²·s⁻¹. The quantum yield (Φ) was the linear initial slope relationship calculated using the dark values and A_net at increasing PAR until the regression coefficient of the slope decreased. The light compensation point (L_cp) was calculated as the PAR when A_net = 0 µmol CO₂·m⁻²·s⁻¹ using the linear regression of the initial response. The light saturation point (L_sp) was the light level when the initial slope reached A_max. A standard least squared ANOVA was used to determine significant differences for the CO₂ concentration and temperature effects. Tukey-Kramer HSD multiple comparison tests were used to determine differences between pair wise comparisons [61] .

3. Results

Before gas exchange measurements were started, structure of the communities was examined [8] . Communities were simple with two major overstory species, but all the trees were identified, counted and measured. Juniperus ashei and Quercus virginiana were present in every community examined (Relative Occurrence = 100%). Relative J. ashei canopy density of was 61% ± 12% (mean ± standard deviation). Relative Q. virginiana canopy density of was 36% ± 6%. Low density community species included Diospyros texana (Texas persimmon), Celtis laevigata (sugarberry or hackberry), Ulmus crassifolia (cedar elm), Prosopis glandulosa (mesquite), Sophora secundiflora (Texas mountain laurel) and Ungnadia speciosa (Mexican buckeye) with relative densities of 0.06% - 1.8%. The two species examined in this study had low relative occurrence, low density and low relative density. Ulmus crassifolia relative occurrence was 38% with density and relative density at 175 plants/ha and 0.5% respectively. Relative occurrence of U. speciosa was 25% with density and relative density at 15 plants/ha and 0.06%, respectively.

Comparisons of light curve results examining the main effects of CO₂ concentration and temperature were made for both species. Interactions were not significant and removed from the models (Table 1). For Ulmus crassifolia, there were no significant temperature effects on photosynthetic rates, conduction or internal [CO₂] concentrations (Table 1 upper). Temperature only had a significant effect on the transpiration rate and water use efficiency (WUE). For CO₂ there were significant effects on response variables including photosynthetic rate, stomatal conductance, intercellular CO₂ concentration, and WUE. Transpiration rate was not significantly affected by CO₂ (Table 1 upper). For Ungnadia speciosa, there were no significant temperature effects (repeated measures MANOVAs Table 1 lower). However, CO₂ had significant effects on photosynthetic rates, conduction, internal [CO₂] levels, and WUE (Table 1 lower). The CO₂ had no significant effect on the transpiration rate.

The mean curves of the photosynthetic rates for U. crassifolia are shown by temperature and CO₂ effects (Figure 1(a) and Figure 1(c)). Photosynthetic rates compared by temperature were not significantly different (MANOVA, P = 0.1873) (Figure 1(a)). However, photosynthetic rates increased to a plateau of approximately 7.4 - 8.9 µmol CO₂·m⁻²·s⁻¹ as light levels increased. The comparisons by CO₂ concentration were statistically significant between the curves (repeated measures MANOVA, P = 0.0002) (Figure 1(c)). The curves increased as the light levels increased and as the CO₂ concentration increased. The ambient (390 µL·L⁻¹) or low CO₂ concentration was significantly different from both the middle (585 µL·L⁻¹) and the high (780 µL·L⁻¹) CO₂ concentration (P = 0.0033 and P = 0.0009). Between the ambient CO₂ concentration (390 µL·L⁻¹) and the middle CO₂ concentration the plateau photosynthetic rate increased approximately 27% from 5.9 µmol CO₂·m⁻²·s⁻¹ to 8.1 µmol CO₂·m⁻²·s⁻¹ while between the low and the high CO₂ concentration the plateau rate increased approximately 45% to 10.8 µmol CO₂·m⁻²·s⁻¹ (Figure 1(c)).

The mean curves of the photosynthetic rates for U. speciosa are shown by temperature and CO₂ effects (Figure 1(b) and Figure 1(d)). Photosynthetic rates compared by temperature were not significantly different (MANOVA, P = 0.8856) (Figure 1(b)). Rates reached a plateau of approximately 8.5 µmol

Table 1. Table includes P-values for repeated measures MANOVAs of gas exchange measurements for Ulmus crassifolia (upper) and Ungnadia speciosa (lower) comparing the main effects of temperature and CO₂ at 16 light levels (interactions were not significant and removed from the models). Data is from three replicates at three CO₂ concentrations (390, 585 and 780 µL·L⁻¹) and three temperatures (35˚C, 40˚C and 45˚C). Bold entries are significant.

Figure 1. Presented are repeated measures MANOVA curves for treatments of main effects on photosynthetic rates for Ulmus crassifolia displayed by temperature (a) and CO₂ concentration (c) and Ungnadia speciosa displayed by temperature (b) and CO₂ concentration (d). P-values are shown from the repeated measures MANOVAs. No letters or like letters at the end of the curves indicate no significant difference. There were three concentrations of CO₂ (390, 585 and 780 µL∙L⁻¹) and three temperatures (35˚C, 40˚C and 45˚C). Error bars are shown indicating standard deviation with the open end (|) for the upper most curve and the bar end (┬) for the lower curve.

CO₂·m⁻²·s⁻¹. The comparisons by CO₂ concentration were statistically significant between the curves (repeated measures MANOVA, P < 0.0001) (Figure 1(d)). The curves increased as the light levels increased and as the CO₂ concentration increased. Each level of CO₂ concentration was significantly different from the other. The approximate photosynthetic rate at the plateau and lower CO₂ concentration was 6.2 µmol CO₂·m⁻²·s⁻¹ and then increased to 8.7% or 29% and 10.4 or 40% µmol CO₂·m⁻²·s⁻¹ at the highest level of CO₂ used.

The mean curves of the water use efficiency (WUE) for U. crassifolia are shown by temperature and CO₂ effects (Figure 2(a) and Figure 2(c)). Water use efficiency was significantly different when compared by temperature (MANOVA, P = 0.0004) (Figure 2(a)). Water use efficiency values decreased from a plateau of approximately 4.0 mmol·mol⁻¹ to approximately 2.4 mmol·mol⁻¹ as temperature increased or by a total of 40%. The comparisons by CO₂ concentration were also statistically significant between the curves (repeated measures MANOVA, P < 0.0001) (Figure 2(c)). The curves generally increased as the light levels increased and as the CO₂ concentration increased. At the ambient (390 µL·L⁻¹) or low CO₂ concentration the WUE value was lowest at approximately 1.9 mmol·mol⁻¹ (Figure 2(c)). At the highest CO₂ concentration, the WUE value increased approximately 57% to a value of approximately 4.4 mmol·mol⁻¹.

Figure 2. Presented are repeated measures MANOVA curves of main effects on water use efficiency for Ulmus crassifolia displayed by temperature (a) and CO₂ concentration (c) and Ungnadia speciosa displayed by temperature (b) and CO₂ concentration (d). P-values are shown from the repeated measures MANOVAs. No letters or like letters at the end of the curves indicate no significant difference. There were three concentrations of CO₂ (390, 585 and 780 µL∙L⁻¹) and three temperatures (35˚C, 40˚C and 45˚C).

The mean curves of the water use efficiency (WUE) for U. speciosa are shown by temperature and CO₂ effects (Figure 2(b) and Figure 2(d)). Water use efficiency was not significantly different when compared by temperature (MANOVA, P = 0.1465) (Figure 2(b)). The water use efficiency value was approximately 4.2 - 5.1 mmol·mol⁻¹. There were statistically significant differences between CO₂ treatments (repeated measures MANOVA, P = 0.0002) (Figure 2(d)). The curves generally increased as the light levels increased and as the CO₂ concentration increased. At the ambient (390 µL·L⁻¹) or low CO₂ concentration the WUE value was the lowest around approximately 3.4 mmol·mol⁻¹ while increasing approximately 42% to a value of 5.9 mmol·mol⁻¹ at the highest CO₂ concentration (Figure 2(d)).

Measured light curve parameters including photosynthetic maximum (A_max), light saturation point (L_sp), light compensation point (L_cp), dark respiration (R_d) and quantum yield (Φ) were compared with the standard least squared ANOVA (Table 2). Temperature and CO₂ concentration were main effects for both species and each of the comparisons. The interactions were not significant and removed from the model.

For U. crassifolia, the maximum photosynthetic rate (A_max) did not change with temperature (P = 0.4399) while it did increase significantly with CO₂ concentration (P = 0.0006) (Table 2). Tukey comparisons of the CO₂ effect showed significant differences between the ambient CO₂, 5.93 µmol CO₂·m⁻²·s⁻¹, and

Table 2. Factors measured and P-values for Standard Least Squared ANOVAs for measured light curve parameters for Ulmus crassifolia and Ungnadia speciosa. Data is from three replicates at three CO₂ concentrations of (390, 585 and 780 µL·L⁻¹) and three temperatures (35˚C, 40˚C and 45˚C). Interactions were not significant and removed from the models. Bold entries are significant at 0.05 or less. Same upper-case or lower-case letters following measurements within a column for a species indicate treatment was not significantly different (TUKEY comparisons P > 0.05).

high CO₂ concentration, 10.05 µmol CO₂·m⁻²·s⁻¹ for an A_max increase of approximately 41%. A similar response was measured for U. speciosa, it’s maximum photosynthetic rate (A_max) did not change with temperature (P = 0.9812) while it did increase significantly with CO₂ concentration (P = 0.0001). Tukey comparisons of the CO₂ effect showed significant differences between the ambient CO₂, 6.22 µmol CO₂·m⁻²·s⁻¹, and high CO₂ concentration, 10.48 µmol CO₂·m⁻²·s⁻¹ for an A_max increase of approximately 41%.

For U. crassifolia, the light saturation point (L_sp) did not change significantly with temperature (P = 0.9569) (Table 2). A significant difference was found between the values for the ambient CO₂ L_sp at 205 µmol·m⁻²·s⁻¹ and high CO₂ L_sp at 286 µmol·m⁻²·s⁻¹ for a 28% increase. Ungnadia speciosa also showed a similar L_sp response. It showed no significantly different change with temperature (P = 0.9812) but was significantly different by CO₂ (Table 2). For U. speciosa a significant difference was found between the ambient CO₂ L_sp at 231 µmol·m⁻²·s⁻¹ and high CO₂ L_sp at 385 µmol·m⁻²·s⁻¹ for a 40% increase.

For U. crassifolia, the light compensation point (L_cp) showed a significant difference by temperature but not by CO₂ concentration (P = 0.0015 and P = 0.4380) (Table 2). The 35˚C L_cp (17.4 µmol·m⁻²·s⁻¹) was significantly different from the 45˚C L_cp (31.4 µmol·m⁻²·s⁻¹) for a 45% increase. For U. speciosa there were no significant differences in the light compensation point (L_cp) at any CO₂ concentration or as the temperature increased (P = 0.1539 and P = 0.5521).

For U. crassifolia, the dark respiration rate (R_d) showed a significant difference by temperature but not by CO₂ concentration (P = 0.0066 and P = 0.5431) (Table 2). The 35˚C R_d (0.65 µmol CO₂·m⁻²·s⁻¹) was significantly different from the 45˚C R_d (1.09 µmol CO₂·m⁻²·s⁻¹) for a 40% increase. For U. speciosa the dark respiration rate (R_d) did not show a significant different between CO₂ concentration or temperature level (P = 0.1539 and P = 0.5521).

For U. crassifolia, the quantum yield (Φ) showed a significant difference by CO₂ concentration (P = 0.0002) (Table 2). The high CO₂ Φ (0.041 µmol CO₂·m⁻²·s⁻¹/µmol·m⁻²·s⁻¹) was significantly different from both the ambient CO₂ Φ (0.033 µmol CO₂·m⁻²·s⁻¹/µmol·m⁻²·s⁻¹) and medium CO₂ Φ (0.037 µmol CO₂·m⁻²·s⁻¹/µmol·m⁻²·s⁻¹). For U. speciosa the quantum yield (Φ) did not differ significantly with temperature or CO₂ treatment (P = 0.8754 or P = 0.9823).

The CO₂ response curves for U. crassifolia were measured at light levels that were held constant at approximately 700 µmol∙m⁻²∙s⁻¹ as a function of the three temperature (35˚C, 40˚C and 45˚C) and were found to be not significantly different (P = 0.5777) (Figure 3(a)). At CO₂ concentration of about 800 µL·L⁻¹, the photosynthetic rates reached a plateau of approximately 10 µmol CO₂·m⁻²·s⁻¹. None of the repeated measures MANOVAs performed on the photosynthetic response, intercellular CO₂ concentration, stomatal conductance and transpiration were significantly different by temperature and are not presented (P > 0.05 for all). When the WUE by CO₂ was examined for U. crassifolia the repeated measures MANOVA of the response to temperature with increasing CO₂ levels was not significantly different (P = 0.5447) (Figure 3(c)). The curves plateaued around 800 - 1000 µL·L⁻¹ of CO₂ with approximate values of 2.8 - 3.6 mmol H₂O∙mol ${\text{CO}}_2^{-\text{1}}$ .

The U. speciosa CO₂ response curves measured at light levels that were held constant at approximate 700 µmol∙m⁻²∙s⁻¹ as a function of the three temperatures (35, 40 and 45˚C) and were found to be not significantly different (P = 0.7542) (Figure 3(b)). Photosynthetic rates increased as CO₂ increased up to a plateau starting at about 800 µL·L⁻¹ of approximately 8.5 - 9.5 µmol CO₂·m⁻²·s⁻¹. None of the repeated measures MANOVAs performed on the photosynthetic response, intercellular CO₂ concentration, stomatal conductance and transpiration were significantly different by temperature and are not presented (P > 0.05 for all).

Figure 3. Photosynthetic response curves for increasing CO₂ levels for Ulmus crassifolia and Ungnadia speciosa ((a) and (b), respectively) and water use efficiency curves ((c) and (d), respectively) at a light level of 700 µmol∙m⁻²∙s⁻¹ and three temperatures (35˚C, 40˚C and 45˚C). Each curve was plotted from a mean of three replicates. P-values are shown from the repeated measures MANOVAs. Error bars are shown indicating standard deviation with the open end (|) for the upper most curve and the bar end (┬) for the lower curve.

When the WUE by CO₂ was examined for U. speciosa the repeated measures MANOVA of the response to temperature and with increasing CO₂ levels was not significant (P = 0.7711). The curves started to plateau around 8000 µL·L⁻¹ at approximately 4.2 mmol H₂O∙mol ${\text{CO}}_2^{-\text{1}}$ at until a peak value of 6.2 mmol H₂O∙mol ${\text{CO}}_2^{-\text{1}}$ was reached at the 1200 µL·L⁻¹ of CO₂ (Figure 3(d)).

4. Discussion

Increasing atmospheric CO₂ concentration and temperature are expected to continue into the future [1] [2] and their potential effects on forests, woodlands and other plant communities are not well understood. This is not the first time the world has experienced high levels of atmospheric CO₂ and concomitant higher temperatures [1] [2] . At the end of the Cretaceous period, approximately 60 million years ago, there was a huge release of carbon into the Earth’s atmosphere [2] [62] . The atmospheric CO₂ level was approximately 1500 ppm and did not decline to lower levels for approximately 1000 years [2] . Before the last glaciation, about 125,000 years before the present, the atmospheric CO₂ level was about 280 ppm and the mean temperature was 2˚C above the present [63] . Then the CO₂ levels dropped to 230 ppm and the temperature dropped by 6˚C, with both rebounding to higher levels today [63] . These levels of CO₂ and associated higher temperatures resulted in changes in the plants and animals present and a change in the communities as well. Changes in plant communities will happen in the future as carbon dioxide levels and temperatures increase, but how the plants and animals will change is uncertain.

Considering our results and comparisons with values for other species [8] [9] [64] [65] , both U. crassifolia and U. speciosa appear to be shade-adapted or intermediate species [59] [66] [67] . Both U. crassifolia and U. speciosa have relatively lower A_max values when compared with other central Texas woodland species [8] . Ulmus crassifolia has a low relative A_max value under ambient CO₂ conditions, while it increased more than other species at the high CO₂ concentration. This would suggest that this species starts as a shade-tolerant species but would appear to become relatively less shade tolerant as the CO₂ concentration increases. This is similarly expressed by U. speciosa. Both U. crassifolia and U. speciosa had lower L_cp values, which would also reinforce their classification as relatively shade-tolerant species. Ulmus crassifolia did show an increase in L_cp with increased temperature, which may indicate an increase in future shade intolerance. Ungnadia speciosa had low Φ values, indicating it also has other shade-tolerant characteristics.

Ulmus crassifolia showed an increasing transpiration response to increasing temperature but did not respond to the elevated CO₂. This suggests that U. crassifolia may be more susceptible to the predicted increased temperatures. Ulmus crassifolia showed a decrease in water use efficiency from increasing temperature, but at the same time, an increase in water use efficiency from increasing CO₂ concentration. Ungnadia speciosa showed an increase in water use efficiency as the CO₂ concentration increased with no temperature response. This will most likely allow the species to be more drought resistant in the future climate.

Not only is the modification to the overall water use efficiency of note, but it may be important that for all species, the water use efficiency closely mimicked the light curves. As the light level decreased, the water use efficiency decreased. This is due to the photosynthetic responses decreasing in the low light environment while the transpiration rate only decreased slightly over the lower light levels. This shows that at lower light levels, these species can not properly regulate water loss. This may be the reason why understory seedlings suffer high mortalities [28] . Shade-tolerant species may be better able to moderate this disconnected water use efficiency at lower light levels, thereby increasing their survival. However, this does not explain the low density of these species in these woodland communities or the lack of them in the grassland gaps and patches.

Something else that has changed radically in these central Texas woodlands is the density of large native herbivores, which has increased dramatically [68] . These increases over the past hundred years have happened in many other areas of North America, causing plant community structure and composition changes [69] - [76] . Certain plant species in the study area are susceptible to herbivory and seem to require exclosures to maintain future populations [5] [77] [78] [79] [80] [81] . This is similar to what has been reported for various Quercus and other woody species in many North American forests [69] [74] [77] . Although the herbivory of U. crassifolia and U. speciosa was not examined directly in this current study, there is a high possibility that browsing may have a similar effect on the population structure and distribution of these species in the future.

The responses to light level suggest that U. crassifolia and U. speciosa are similar to other restricted eastern North American low-density shade-tolerant and herbivory susceptible plants [16] . The canopy position of these plants and their low relative density may be caused by the high density of other woody shrubs that could afford some protection from the herbivores (probably white-tailed deer), masking their presence and position [78] .

Juniperus woodlands seem to be successional communities [82] . In the eastern North American deciduous forests, Juniperus plants are often found in gaps, blow downs or on shallow soil in glades [6] . In western North America, Juniperus tends to occur above the desert communities and above the arid or semiarid grasslands, but usually below the higher-elevation pine, spruce, or fir forests [37] . In central Texas, Juniperus ashei establishes on hillsides and in former grasslands on shallow soil [49] . Juniperus woodlands in many parts of the world are probably caused by a number of factors, with constant high levels of grass herbivory and a reduction of grassland fire frequency being dominant [37] [82] .

Grasslands are favored when biomass and fire frequency are high, while woody plants, like various species of Juniperus, and many species of nitrogen-fixing legumes, are favored when fire frequency is low or nonexistent [83] [84] . The structure of many grasslands and savannas has changed and the direction of community succession has been altered because of new conditions controlling their structure and composition [32] [83] [84] [85] [86] .

The new higher atmospheric CO₂ and temperature conditions in the woodlands, plus browsing by native herbivores, are causing community change. Community changes in woodlands are hard to detect, but conditions will be modified in the future [33] . These new conditions will allow some species to expand their density, while other species will decline. The result will be changes in community composition and structure. The current study species, U. crassifolia and U. speciosa, found in these central Texas Juniperus/Quercus communities are expected to change in density and basal area. This study suggests that they will gain competitive advantages over other community species with increased atmospheric CO₂ levels and light levels. But there seems to be a factor or factors that we have not examined or accounted for, which is natural herbivory or browsing by white-tailed deer (Odocoileus virginianus). This species has been shown to cause establishment difficulties for species in many areas of central Texas [78] . This difficulty in the establishment has been shown for various woody species, possibly in conjunction with competition for water with C₄ southern grasses [65] [72] - [77] [87] . These complications mean predicting future plant community changes will be a demanding task.

Acknowledgments

We would like to thank Samantha Daywood and Jason Gagliardi for their help in the field, especially in data collection. Thanks to Drs. Janis Bush and Rob Wayne, who helped with various aspects of the work, reported here. Many helpful suggestions were made by Dr. Julie Foote and Jason Gagliardi, who read an earlier iteration of this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest regarding the publication of this paper.

References

[1]	Berner, R.A. (2005) The Rise of Trees and How They Changed Paleozoic Atmospheric CO2, Climate and Geology. In: Ehleringer, J.R., Cerling, T.E. and Dearing, M.D., Eds., A History of Atmospheric CO2 and Its Effects on Plants, Animals, and Ecosystems, Springer Science + Business Media, New York, 1-7.
[2]	Kunzig, R. (2011) World without Ice. National Geographic, 220, 90-109.
[3]	Van Auken, O.W., Ford, A.L. and Allen, J.L. (1981) An Ecological Comparison of Upland Deciduous and Evergreen Forests of Central TEXAS. American Journal of Botany, 68, 1249-1256. https://doi.org/10.1002/j.1537-2197.1981.tb07832.x
[4]	Amos, B.B. and Gehlbach, F.R. (1988) Edwards Plateau Vegetation: Plant Ecological Studies in Central Texas. Baylor University Press, Waco.
[5]	Van Auken, O.W. (1988) Woody Vegetation of the Southeastern Escarpment and Plateau. In: Amos, B.B. and Gehlbach, F.R., Eds., Edwards Plateau Vegetation, Baylor University Press, Waco, 43-55.
[6]	Van Auken, O.W. and McKinley, D.C. (2008) Structure and Composition of Juniperus Communities and Factors that Control Them. In: Van Auken, O.W., Ed., Western North American Juniperus Communitities: A Dynamic Vegetation Type, Springer, New York, 19-47. https://doi.org/10.1007/978-0-387-34003-6_2
[7]	Van Auken, O.W. (2018) Ecology of Plant Communities of South-Central Texas. Scientific Research Publishing, Wuhan. http://www.scirp.org
[8]	Grunstra, M.B. (2008) Investigation of Juniperus Woodland Replacement Dynamics. Ph.D. Thesis, The University of Texas at San Antonio, San Antonio, 422.
[9]	Grunstra, M.B. and Van Auken, O.W. (2015) Photosynthetic Characteristics of Garrya ovata Benth. (Lindheimer’s silktassle, Garryaceae) at Ambient and Elevated Levels of Light, CO2 and Temperature. Phytologia, 97, 103-119.
[10]	Wells, P.V. (1965) Scarp Woodlands, Transported Grassland Soils, and Concept of Grassland Climate in the Great Plains Region. Science, 148, 246-249. https://doi.org/10.1126/science.148.3667.246
[11]	Gould, F.W. (1969) Texas Plants—A Checklist and Ecological Summary. Texas Agricultural Experiment Station Bulletin, MP-585. College Station.
[12]	Blackburn, W.H. and Tueller, P.T. (1970) Pinyon and Juniper Invasion in Black Sagebrush Communities in East-Central Nevada. Ecology, 51, 841-848. https://doi.org/10.2307/1933976
[13]	Correll, D.S. and Johnston, M.C. (1970) Manual of the Vascular Plants of Texas. Texas Research Foundation, San Antonio.
[14]	Little, E.L. (1971) Atlas of United States Trees: Volume 1: Conifers and Important Hardwoods. USDA Miscellaneous Publication 1146, Washington DC.
[15]	Baskin, J.M. and Baskin, C.C. (1986) Distribution and Geographical/Evolutionary Relationship of Cedar Glade Endemics in the Southeastern United States. Association of Southeastern Biologist Bulletin, 33, 138-154. https://doi.org/10.2307/2845343
[16]	Baskin, J.M. and Baskin, C.C. (1988) Endemism in Rock Outcrop Plant Communities of Unglaciated Eastern United States: An Evaluation of the Roles of the Edaphic, Genetic and Light Factors. Journal of Biogeography, 15, 829-840.
[17]	West, N.E. (1988) Intermountain Deserts, Shrub steppe and Woodlands. In: Barbour, M.G. and Billings, W.D., Eds., Terrestrial Vegetation of North America, Cambridge University Press, New York, 209-230.
[18]	Dick-Peddie, W.A. (1993) New Mexico, Vegetation: Past, Present and Future. University of New Mexico Press, Albuquerque.
[19]	Johnson, T.N. and Alexander, R.A. (1974) Juniperus L. In: Schopmeyer, C.S., Ed., Seeds of Woody Plants in the United States, Forest Service, US Department of Agriculture, Washington DC, 460-469.
[20]	Elias, T.S. (1980) The Complete Trees of North America. Van Nostrand Reinhold, New York.
[21]	Hora, B. (1981) The Oxford Encyclopedia of Trees of the World. Oxford University Press, New York.
[22]	Barbour, M.G. and Billings, W.D. (1988) North American Terrestrial Vegetation. Cambridge University Press, New York.
[23]	Barbour, M.G., Burk, J.H., Pitts, W.D., Gilliam, F.S. and Schwartz, M.W. (1999) Terrestrial Plant Ecology. Addiison Wesley Longman, Menlo Park.
[24]	Bray, W.L. (1904) The Timber of the Edwards Plateau of Texas: Its Relation to Climate, Water Supply and Soil. Bureau of Forestry Bulletin Number 49 USDA, Washington DC. https://doi.org/10.5962/bhl.title.66269
[25]	Foster, J.H. (1917) The Spread of Timbered Areas in Central Texas. Journal of Forestry, 15, 442-445.
[26]	Smeins, F.E. (1980) Natural Role of Fire of the Edwards Plateau. In: White, L.D., Ed., Prescribed Range Burning in the Edwards Plateau of Texas: Proceedings of a Symposium, Texas Agriculture Extension Service, College Station, 4-16.
[27]	Jackson, J.T. and Van Auken, O.W. (1997) Seedling Survival, Growth and Mortality of Juniperus ashei (Cupressaceae) in the Edwards Plateau Region of Central Texas. Texas Journal of Science, 49, 267-278.
[28]	Van Auken, O.W., Jackson, J.T. and Jurena, P.N. (2004) Survival and Growth of Juniperus Seedlings in Juniperus Woodlands. Plant Ecology, 175, 245-257. https://doi.org/10.1007/s11258-005-0022-z
[29]	Miller, R.F. and Wigand, P.E. (1994) Holocene Changes in Semiarid Pinyon-Juniper Woodlands: Response to Climate, Fire, and Human Activities in the US Great Basin. BioScience, 44, 465-474. https://doi.org/10.2307/1312298
[30]	Miller, R.F., Svejcar, T. and Rose, J. (2000) Impacts of Western Juniper on Plant Community Composition and Structure. Journal of Range Management, 53, 575-585. https://doi.org/10.2458/azu_jrm_v53i6_miller
[31]	McKinley, D.C. and Van Auken, O.W. (2005) Influence of Interacting Factors on the Growth and Mortality of Juniperus Seedlings. American Midland Naturalist, 154, 320-330. https://doi.org/10.1674/0003-0031(2005)154[0320:IOIFOT]2.0.CO;2
[32]	Keddy, P.A. (2017) Plant Ecology: Origins, Processes, Consequences. Cambridge University Press, Cambridge. https://doi.org/10.1017/9781316321270
[33]	NCA (National Climate Assessment) (2014) U.S. Global Change Research Program. http://nca2014.globalchange.gov/highlights/report-findings/our-changing-climate
[34]	Archer, S., Schimel, D.S. and Holland, E.A. (1995) Mechanisms of Shrubland Expansion: Land Use, Climate or CO2? Climate Change, 29, 91-99. https://doi.org/10.1007/BF01091640
[35]	Bush, J.K. and Van Auken, O.W. (1995) Woody Plant Growth Related to Planting Time and Clipping of a C4 Grass. Ecology, 76, 1603-1609. https://doi.org/10.2307/1938161
[36]	Van Auken, O.W. and Bush, J.K. (1997) Growth of Prosopis glandulosa in Response to Changes in Aboveground and Belowground Interference. Ecology, 78, 1222-1229. https://doi.org/10.2307/2265871
[37]	Van Auken, O.W. (2000) Shrub Invasion of North American Semiarid Grasslands. Annual Review of Ecology and Systematics, 31, 197-215. https://doi.org/10.1146/annurev.ecolsys.31.1.197
[38]	Breshears, D.D., Myers, O.B., Johnson, S.R., Meyers, C.W. and Martens, S.N. (1997) Differential Use of Spatially Heterogeneous Soil Moisture by Two Semiarid Woody Species: Pinus edulus and Juniperus monosperma. Journal of Ecology, 85, 289-299. https://doi.org/10.2307/2960502
[39]	Breshears, D.D., Nyhan, J.W., Heil, C.E. and Wilcox, B.P. (1998) Effects of Woody Plants on Microclimate in a Semi-Arid Woodland: Soil Temperature and Evaporation in Canopy and Intercanopy Patches. International Journal of Plant Science, 159, 1010-1017. https://doi.org/10.1086/314083
[40]	Martens, S.N., Breshears, D.D. and Meyer, C.W. (2000) Spatial Distributions of Understory Light along the Grassland/Forest Continuum: Effects of Cover, Height, and Spatial Pattern of Tree Canopies. Ecological Modeling, 126, 79-93. https://doi.org/10.1016/S0304-3800(99)00188-X
[41]	Martens, S.N., Breshears, D.D. and Barnes, F.J. (2001) Development of Species Dominance along an Elevational Gradient: Population Dynamics of Pinus edulis and Juniperus monosperma. International Journal of Plant Science, 162, 777-783. https://doi.org/10.1086/320772
[42]	Joy, D.A. and Young, D.R. (2002) Promotion of Mid-Successional Seedling Recruitment and Establishment by Juniperus virginia in a Coastal Environment. Plant Ecology, 160, 125-135. https://doi.org/10.1023/A:1015812923216
[43]	Wayne, E.R. and Van Auken, O.W. (2002) Spatial and Temporal Patterns of Juniperus ashei Seedling Xylem Water Potential. Southwestern Naturalist, 47, 153-161. https://doi.org/10.2307/3672901
[44]	Wayne, E.R. and Van Auken, O.W. (2004) Spatial and Temporal Abiotic Changes along a Canopy to Intercanopy Gradient in Central Texas Juniperus ashei Woodlands. Texas Journal of Science, 56, 35-54.
[45]	Smeins, F.E. and Merrill, L.B. (1988) Long-Term Change in a Semiarid Grassland. In: Amos, B.B. and Gehlbach, F.R., Eds., Edwards Plateau Vegetation, Baylor University Press, Waco, 209-230.
[46]	Quarterman, E. (1950) Major Plant Communities of Tennessee Cedar Glades. Ecology, 31, 234-254. https://doi.org/10.2307/1932389
[47]	Baskin, J.M. and Baskin, C.C. (1978) Plant Ecology of Cedar Glades in the Big Barrens Region of Kentucky. Rhodora, 80, 545-557.
[48]	Quarterman, E., Burbank, M.B. and Shure, D.J. (1993) Rock Outcrop Communities: Limestone, Sandstone and Granite. In: Martin, W.H. and Boyce, S.G., Eds., Biodiversity of the Southeastern United States: Upland Terrestrial Communities, John Wiley and Sons, New York, 35-86.
[49]	Terletsky, P.A. and Van Auken, O.W. (1996) Comparison of Cedar Glades and Associated Woodlands of the Southern Edwards Plateau. Texas Journal of Science, 48, 55-67.
[50]	Baskin, J.M. and Baskin, C.C. (2000) Vegetation of Limestone and Dolomite Glades in the Ozarks and Midwest Regions of the United States. Annuals of the Missouri Botanical Garden, 87, 286-294. https://doi.org/10.2307/2666165
[51]	Van Auken, O.W. (2000) Characteristics of Intercanopy Bare Patches in Juniperus Woodlands of the Southern Edwards Plateau, Texas. Southwestern Naturalist, 45, 95-110. https://doi.org/10.2307/3672449
[52]	Batchelor, M.E. and Fowler, N.L. (2004) Intraspecific Facilitation of Juniperus ashei in Texas Savannas. Bulletin of the Ecological Society of America, 89th Annual Meeting, Portland, 1-6 August 2004, 19.
[53]	McKinley, D.C. and Van Auken, O.W. (2004) Growth and Survival of Juniperus ashei (Cupressacae) Seedlings in the Presence of Juniperus ashei Litter. Texas Journal of Science, 56, 3-14.
[54]	Taylor, F.B., Hailey, R.B. and Richmond, D.L. (1966) Soil Survey of Bexar County, Texas. USDA, Soil Conservation Service, Washington DC.
[55]	United States Department of Agriculture (2000) Natural Resources Conservation Service. Soil Survey Division. Official Series Descriptions. https://soilseries.sc.egov.usda.gov/
[56]	Arbingast, S.A., Kennamer, L.G., Buchanan, J.R., Hezlep, W.L., Ellis, L.T., Jordan, T.G., Granger, C.T. and Zlatkovick, C.P. (1976) Atlas of Texas. 5th Edition, Bureau of Business Research, University of Texas Press, Austin.
[57]	National Oceanic and Atmospheric Administration (2001) National Climatic Data Center. Asheville, North Carolina. https://www.ncdc.noaa.gov/cdo-web/
[58]	Van Auken, O.W., Bush, J.K. and Elliott, S.A. (2005) Ecology Laboratory Manual. Pearson Custom Publishing, Boston.
[59]	Van Auken, O.W. and Bush, J.K. (2009) The Role of Photosynthesis in the Recruitment of Juvenile Quercus gambelii into Mature Q. gambelii Communities. Journal of the Torrey Botanical Society, 136, 465-478. https://doi.org/10.3159/09-RA-035.1
[60]	Turner, C.L. and Knapp, A.K. (1996) Responses of a C4 Grass and Three C3 Forbs to Variation in Nitrogen and Light in Tallgrass Prairie. Ecology, 77, 1738-1749. https://doi.org/10.2307/2265779
[61]	Sall, J., Creighton, L. and Lehman, A. (2011) JMP Pro. SAS Institute, Inc., Cary.
[62]	Ehleringer, J.R., Cerling, T.E. and Dearing, M.D. (2005) A History of Atmospheric CO2 and Its Effects on Plants, Animal, and Ecosystems. Springer Science + Business Media, New York.
[63]	Petit, J.R., et al. (1999) Climate and Atmosphere History of the Past 420,000 Years from the Vostoc Ice Core, Antarctica. Nature, 399, 429-436. https://doi.org/10.1038/20859
[64]	Hull, J.C. (2002) Photosynthetic Induction Dynamics to Sunflecks of Four Deciduous Forest Understory Herbs with Different Phenologies. International Journal of Plant Sciences, 163, 913-924. https://doi.org/10.1086/342633
[65]	Wayne, E.R. and Van Auken, O.W. (2012) Comparisons of Gas Exchange of Several Sedges and C4 Grasses in Associated Savanna Communities. Phytologia, 94, 71-90.
[66]	Valladares, F. and Niinemets, U. (2008) Shade Tolerance, a Key Plant Feature of Complex Nature and Consequences. Annual Review Ecology and Systematics, 39, 237-257. https://doi.org/10.1146/annurev.ecolsys.39.110707.173506
[67]	Van Auken, O.W., Taylor, D., Bush, J.K. and Singhurst, J.R. (2022) Isolated Deciduous Woodlands in Central Texas. Phytologia, 104, 13-23.
[68]	Doughty, R.W. (1983) Wildlife and Man in Texas: Environmental Change and Conservation. Texas A & M University Press, College Station.
[69]	Anderson, R.C. and Loucks, O.L. (1979) White-Tail Deer (Odocoileus virginianus) Influence on Structure and Composition of Tsuga canadensis Forests. Journal of Applied Ecology, 16, 855-861. https://doi.org/10.2307/2402859
[70]	Augustine, D.J. and Frelich, L.E. (1998) Effects of White-Tailed Deer on Populations of an Understory Forb in Fragmented Deciduous Forests. Conservation Biology, 12, 995-1004. https://doi.org/10.1046/j.1523-1739.1998.97248.x
[71]	Russell, F.L., Zippin, D.B. and Fowler, N.L. (2001) Effects of White-Tailed Deer (Odocoileus virginianus) on Plants, Plant Populations and Communities. American Midland Naturalist, 146, 1-26. https://doi.org/10.1674/0003-0031(2001)146[0001:EOWTDO]2.0.CO;2
[72]	Cadenasso, M.L., Pickett, S.T.A. and Morin, P.J. (2002) Experimental Test of the Role of Mammalian Herbivores on Old Field Succession: Community Structure and Seedling Survival. Journal of the Torrey Botanical Society, 129, 228-237. https://doi.org/10.2307/3088773
[73]	Abrams, M.D. (2003) Where Has All the White Oak Gone? Bioscience, 53, 927-939. https://doi.org/10.1641/0006-3568(2003)053[0927:WHATWO]2.0.CO;2
[74]	Krueger, L.M., Peterson, C.J., Royo, A. and Carson, W.P. (2009) Evaluating Relationships among Tree Growth Rate, Shade Tolerance, and Browse Tolerance following Disturbance in an Eastern Deciduous Forest. Canadian Journal of Forest Research, 39, 2460-2469. https://doi.org/10.1139/X09-155
[75]	Kain, M., Battaglia, L., Royo, A. and Carson, W.P. (2011) Over-Browsing in Pennsylvania Creates a Depauperate Forest Dominated by an Understory Tree: Results from a 60-Year-Old Deer Exclosure. Journal of the Torrey Botanical Society, 138, 322-326. https://doi.org/10.3159/TORREY-D-11-00018.1
[76]	Abrams, M.D. and Johnson, S.E. (2012) Long-Term Impacts of Deer Exclosures and Land-Use History on Forest Composition at the Valley Forge National Historical Park, Pennsylvania. Journal of the Torrey Botanical Society, 139, 167-180. https://doi.org/10.3159/TORREY-D-11-00075.1
[77]	Van Auken, O.W. (1993) Size Distribution Patterns and Potential Population Change of Some Dominant Woody Species on the Edwards Plateau Region of Texas. Texas Journal of Science, 45, 199-210.
[78]	Leonard, W.J. and Van Auken, O.W. (2013) Light Levels and Herbivory Partially Explain the Survival, Growth and Niche Requirements of Streptanthus bracteatus A. Gray (Bracted Twistflower, Brassicaceae), a Rare Central Texas Endemic. Natural Areas Journal, 33, 276-285. https://doi.org/10.3375/043.033.0306
[79]	Nelson-Dickerson, T. and Van Auken, O.W. (2016) Survival, Growth and Recruitment of Bigtooth Maple (Acer grandidentatum) in Central Texas Relict Communities. Natural Areas Journal, 36, 174-180. https://doi.org/10.3375/043.036.0209
[80]	Van Auken, O.W., Taylor, D.L. and Shen, C. (2016) Diameter Growth of Acer grandidentatum (Bigtooth maple) in Isolated Central Texas Populations. Phytologia, 98, 142-144.
[81]	Van Auken, O.W. and Taylor, D. (2020) Survival of Juvenile Acer grandidentatum Nutt. (Bigtooth Maple, Aceraceae) in Central Texas Woodlands. American Journal of Plant Sciences, 11, 413-425. https://doi.org/10.4236/ajps.2020.113030
[82]	Van Auken, O.W. (2009) Causes and Consequences of Woody Plant Encroachment into Western North American Grasslands. Journal of Environmental Management, 90, 2931-2942. https://doi.org/10.1016/j.jenvman.2009.04.023
[83]	Bond, W.J. (2008) What Limits Trees in C4 Grasslands and Savannas? Annual Review of Ecology and Systematics, 39, 641-659. https://doi.org/10.1146/annurev.ecolsys.39.110707.173411
[84]	Van Auken, O.W. and Bush, J.K. (2013) Invasion of Woody Legumes. Springer, New York. https://doi.org/10.1007/978-1-4614-7199-8
[85]	Begon, M., Townsend, C.R. and Harper, J.L. (2006) Ecology: From Individuals to Ecosystems. Blackwell Publishing, Malden.
[86]	Smith, T.M. and Smith, R.L. (2012) Elements of Ecology. Pearson Benjamin Cummings, New York.
[87]	Van Auken, O.W., Taylor, D.L., Shen, C.C. and Bush, J.K. (2017) Structure of Isolated Acer grandidentatum (Bigtooth Maple) Communities and Potential Population Changes. American Journal of Plant Sciences, 8, 1368-1387.