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Article

Leaf Angle as a Criterion for Optimizing Irrigation in Forest Nurseries: Impacts on Physiological Seedling Quality and Performance after Planting in Pots

by
Richardson Barbosa Gomes da Silva
1,*,
Danilo Simões
1,
Ivar Wendling
2,
Débora Zanoni do Prado
3,
Maria Márcia Pereira Sartori
1,
Angelo Albano da Silva Bertholdi
1 and
Magali Ribeiro da Silva
1
1
School of Agriculture, São Paulo State University (Unesp), Botucatu 18610-034, Brazil
2
Brazilian Agricultural Research Corporation (Embrapa Forestry), Colombo 83411-000, Brazil
3
Institute of Biosciences, São Paulo State University (Unesp), Botucatu 18618-689, Brazil
*
Author to whom correspondence should be addressed.
Forests 2023, 14(5), 1042; https://doi.org/10.3390/f14051042
Submission received: 12 March 2023 / Revised: 15 May 2023 / Accepted: 16 May 2023 / Published: 18 May 2023
(This article belongs to the Section Forest Ecophysiology and Biology)

Abstract

:
Seedling species with different architectures, e.g., mean leaf angles, are often subjected to the same irrigation management in forest nurseries, resulting in wasted water and fertilizer and reduced seedling quality. We aimed to evaluate whether irrigation volumes applied to tree seedling species with different leaf angles affect the physiological quality in forest nurseries and, consequently, performance after potting. We submitted nine seedling species with different mean leaf angles to four daily water regimes (8, 10, 12, and 14 mm). In the nursery, the following physiological attributes were considered to assess seedling quality: leaf water potential, daily transpiration rate, SPAD value, chlorophyll a and b, anthocyanins, carotenoids, and total nutrient content. After potting, we evaluated height and stem diameter over 120 days. Leaf angle can be used as a criterion for optimizing irrigation in forest nurseries, avoiding water and fertilizer wastage, and increasing physiological seedling quality. Leaf angle measurements combined with concurrent assessments of leaf traits are helpful in further understanding the effects of leaf angle variation and water regime on seedling quality. For positive leaf angles, an irrigation volume of 8 mm is sufficient to increase physiological seedling quality. Conversely, seedlings with negative leaf angles show the opposite response, requiring the largest irrigation volume (14 mm) to increase physiological seedling quality, except when the mean leaf area is small and concentrated in the upper half of the stem, which facilitates the access of irrigation water to the substrate and thus satisfies seedling water requirements. For all species, up to 120 days after planting in pots, the effect of the irrigation volume that provides greater growth and physiological quality at the end of the nursery phase is not overcome by other irrigation volumes applied.

Graphical Abstract

1. Introduction

To combat the global warming crisis, the United Nations has declared 2021–2030 as the “International Decade on Ecosystem Restoration” to accelerate the restoration of degraded ecosystems, including tropical forests. As such, active management techniques, such as planting seedlings, play an important role in forest restoration. Seedling production requires specialized knowledge to produce morphologically and physiologically high-quality plants to meet forest restoration goals.
High quality seedlings are often a critical requirement for implementing forest and landscape restoration programs [1]. Nursery cultural practices directly affect the physiological functioning and subsequent morphological development of seedlings [2].
A broad seedling quality evaluation program provides useful information to support grower decisions and to understand the effects of management [3]. Successful establishment depends on the use of seedlings whose morphological and physiological characteristics achieved at the end of nursery production support growth and survival under an expected range of site conditions [4].
Physiological attributes commonly measured during seedling development include nutrient status and plant water status. The use of physiological quality at the end of nursery production as a criterion for selecting species for ecological restoration is advantageous. The resistance of species to the effects of seasonality results in reduced mortality and restoration costs [5].
In nurseries, the main factors that affect the quality of seedlings are the quality of genetic material, irrigation, nutrition, container type, and substrate composition. In irrigation, overhead microsprinklers are the most commonly used system for tree seedlings and tend to grow several species with different architectures under the same water management [6,7].
Species with larger crown canopies may largely contribute to leaf water interception. This canopy effect, which depends on canopy characteristics, container size, and spacing, is not considered by many growers. As a result, many growers typically apply more water than needed when scheduling irrigation, preferring the risk of increased leaching losses to the consequences of seedling water deficits [8,9].
Plant species can vary widely in architecture, i.e., the disposition of their components in space [10], such as the leaf angles. Leaf angle is an important plant structural trait that affects light interception, as well as carbon and water fluxes [11]. Steeper leaf angles can help reduce exposure to excess radiation and consequent water stress during the middle of the day, thereby increasing water use efficiency and hence carbon gain [12,13].
On the other hand, lower leaf angles increase light interception when the sun is at a high angle. The large interception of radiation by lower leaf angles can result in a significant increase in leaf temperature to levels above those optimal for photosynthesis. High leaf temperatures also increase the vapor pressure difference with the atmosphere, which increases transpiration rate and decreases water use efficiency [14,15].
The authors [16] measured and compiled an extensive dataset of leaf angles for 138 deciduous broadleaf species commonly found in temperate and boreal ecoclimatic regions. Similarly, [17] provide a dataset of leaf angles for 71 different Eucalyptus species native to Australia. More recently, data on leaf angle distributions for 50 widespread forest broadleaf tree species in Europe were also reported [18].
Rather than focusing on seedlings and their physiological attributes in response to water management, most studies of leaf angles have been concerned with the study of forests and their effects on radiation [19,20,21,22,23,24,25], remote sensing of the environment [26,27,28,29], leaf wettability and rainfall distribution in forests [30,31], and genotypic and phenotypic plasticity [32,33].
Overcoming this knowledge gap will help growers improve seedling quality and avoid wasting inputs such as water and fertilizer. We aimed to evaluate whether irrigation volumes applied to tree species with different leaf angles affect the physiological seedling quality in forest nurseries and, consequently, the performance after planting in pots.

2. Materials and Methods

2.1. Site Description

We conducted this study during the summer months in a sectored forest nursery located in the São Paulo State, Brazil, at coordinates 22°51′ S 48°26′ W. The climate is classified as Cfa (Köppen classification) and the original phytophysiognomies in this region are tropical semi-deciduous forest and Cerrado, which are considered biodiversity hotspots [34].

2.2. Leaf Angle Measurement and Experimental Treatments

We measured the mean leaf angle of nine tree seedling species from tropical semi-deciduous forests and the Cerrado, typically used for implementing active forest restoration programs: Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°) using a 180-degree transparent protractor on the youngest fully expanded pair of leaves. According to [7,13], we measured the leaf angle from the horizontal plane (0°∼flat; 90°∼upward leaf; −90°~downward leaf). For each species, we considered the mean value of 30 seedlings between 25 and 35 cm tall.
We tested water regimes typically used for seedling production (8, 10, 12, and 14 mm/day−1), divided twice a day, and applied by an overhead microsprinkler system. To accurately measure the amount of water applied by the irrigation system, we placed 36 plastic containers equidistantly under the microsprinklers in each covered bed prior to the irrigation pulse. The test duration was 1.0 h. Irrigation volumes were measured using a 1.0 L graduated cylinder.
Thus, the irrigation volumes were applied by the irrigation system at an average rate of 32.4 mm h−1, with an operating pressure of 300 kPa. From this reference, we programmed the control panel of the irrigation system to apply the specified irrigation volume of each treatment.
The experiment was conducted using a split-plot design. The main plots were assigned to four irrigation volumes: 8, 10, 12, and 14 mm/day−1. Subplots were assigned to nine tree seedling species: Croton floribundus, Heliocarpus popayanensis, Guazuma ulmifolia, Esenbeckia leiocarpa, Lafoensia pacari, Moquiniastrum polymorphum, Psidium cattleyanum, Magnolia ovata, and Genipa americana. Four replicates were set up for each treatment, giving a total of 144 subplots. The experimental unit (each subplot) included a total of 20 seedlings.

2.3. Nursery Management

We filled polyethylene trays with peat moss-based substrates, carbonized rice hull, and perlite (2:1:1; by volume) and sowed in a shade house (50% shade), where the seedlings received 8 mm daily irrigation volume. After one month, we transferred the emerged seedlings to polyethylene containers (92 cm³). The occupancy of each polyethylene tray was one polyethylene container per 86.8 cm².
Subsequently, we standardized the subplots of each species, measuring their heights: Croton floribundus (5.0 cm ± 0.8), Heliocarpus popayanensis (11.7 cm ± 1.6), Guazuma ulmifolia (9.6 cm ± 1.0), Esenbeckia leiocarpa (7.9 cm ± 1.0), Lafoensia pacari (13.3 cm ± 1.3), Moquiniastrum polymorphum (4.8 cm ± 1.2), Psidium cattleianum (8.8 cm ± 1.2), Magnolia ovata (4.5 cm ± 0.5), and Genipa americana (3.4 cm ± 0.9).
Thus, we randomly assigned the trays in suspended and covered beds with diffuse-light film and programmed the overhead sprinkler system to apply the irrigation volumes corresponding to the treatments. The classification of Christiansen’s uniformity coefficient was high (90%) [35], and that of the uniform distribution coefficient was good (86%) [36].
At the beginning of the irrigation treatments, we started seedling fertilization by applying 8 mm of nutrient solution per week. This volume was applied equally to all treatments and was deducted from the irrigation volume. The macronutrient solution was composed of Ca(NO3)2, urea (CH4N2O), MAP (NH4H2PO4), KNO3, and MgSO4 at concentrations (milligrams per liter) of 295 (N), 84 (P), 200 (K), 38 (Mg), 160 (Ca), and 52 (S), and micronutrient solution of H3BO3, Na2MoO4, MnSO₄, ZnSO₄, CuSO4, and FeSO4 at concentrations (milligrams per liter) of 25 (Fe), 4.6 (B), 3.9 (Mn), 1.2 (Zn), 0.6 (Cu), and 0.3 (Mo). We also applied 8 mm per week of hardening fertilization solution composed of KCl at 700 mg L−1 for one month.
The nursery period of each species was different due to their different growth rhythms: Heliocarpus popayanensis, Lafoensia pacari, Moquiniastrum polymorphum, and Psidium cattleianum was 90 days; Croton floribundus, Esenbeckia leiocarpa, and Magnolia ovata was 150 days; and Guazuma ulmifolia and Genipa americana was 120 days.
To determine the effects of irrigation volume on seedling species with different leaf angles, we evaluated the physiological attributes at the end of the nursery phase. To determine the growth performance of the seedlings after potting, we evaluated the attributes’ height and stem diameter over 120 days.

2.4. Physiological Analysis

2.4.1. Leaf Water Potential and Daily Transpiration Rate

For each mean leaf angle, we evaluated leaf water potential ( Ψ l e a f ) in four seedlings of each irrigation volume with a dew point potentiometer (model WP4-T, Washington, USA), collecting two fully expanded leaves at midday.
For each mean leaf angle, we evaluated the gravimetrically daily transpiration rate (milligram of water per square meter of leaf per second) [37] in sixteen seedlings of each irrigation volume. At 06:00 p.m., we completely saturated the substrate with water and then allowed it to drain. We attached a plastic bag to the polyethylene container and sealed it completely around the seedling with masking tape to prevent the evaporation of substrate water.
On a subsequent day (07:00 a.m.), we weighed the initial mass of the set (plastic bag, masking tape, and seedling) on a high-precision balance and kept it in full sunlight. After one day, we weighed the final mass of the set and then we detached leaves to determine the leaf area using a LI-3100 (Li-Cor, Lincoln, NE, USA). Thus, we calculated transpiration using Equation (1):
Im Fm LA t
where T is the daily transpiration rate, Im (mg) is the initial mass of set, Fm (mg) is the final mass of set, LA (m2) is the leaf area, and t is the time (s).

2.4.2. Leaf Pigment Contents Analysis and SPAD Value

For each mean leaf angle, we measured leaf pigment contents (chlorophyll a and b, anthocyanins, and carotenoids) in sixteen seedlings of each irrigation volume, collecting two fully expanded leaves, according to [38]. We homogenized leaves (0.100 g) in liquid nitrogen, and we performed all measurements in triplicate. We extracted pigments with 3 mL acetone/Tris pH 7.8 buffer solution (80/20, volume/volume). After the centrifugation of the extracts at 6000 rpm for five minutes, we read the absorbance at 663, 647, 537, and 470 nm. We calculated the pigment contents (mg g of fresh weight−1) according to Equations (2)–(5), as follows:
Chl a = 0.01373 × A 663 0.000897 × A 537 0.003046 × A 647
Chl b = 0.02405 × A 647 0.004305 × A 537 0.005507 × A 663  
Anthocyanins   = 0.08173 × A 537 0.00697 × A 647 0.002228 × A 663
Carotenoids = ( A 470 ( 17.1 × ( Chl a + Chl b ) 9.479 × Anthocyanins ) ) 119.26
where Chla is the chlorophyll a content, Chlb is the chlorophyll b content, and A is the sample absorbance at wavelength x in a 1 cm path length cuvette.
For each mean leaf angle, we considered the two fully expanded leaves and measured SPAD values in sixteen seedlings of each irrigation volume, using a chlorophyll concentration estimator (SPAD-502, Konica Minolta, Osaka, Japan).

2.4.3. Total Nutrient Content Analysis

For each mean leaf angle, we evaluated the total nutrient content in four seedlings of each irrigation volume, according to [39,40,41]. Seedlings were separated into roots and shoots and the substrate was washed from the roots. Both the shoot and root parts were dried in an air circulation oven at 70 °C until they reached a constant mass and then they were weighed for dry mass determination on a high-precision balance. The dried samples were separately ground in a Wiley mill (Arthur H. Thomas Company, Philadelphia, PA, USA) and used for determination of tissue macronutrient (g kg−1) and micronutrient (mg kg−1) concentrations for P, K, Mg, Ca, S, Zn, Fe, Cu, and Mn by nitroperchloric digestion, N by sulfuric perchloric digestion, and B by dry-ashing.
Tissue concentrations were multiplied by the oven-dried weight of the corresponding part to calculate nutrient content. Total macronutrient and micronutrient content were determined by summing the nutrient content of each seedling part.

2.5. Seedling Growth Performance after Planting in Pot

After finishing the nursery phase, we planted six seedling representatives of each species and irrigation volume in 7 L pots containing Oxisol medium texture with sand (3:1; by volume). In the soil, we added fertilizer with the N-P-K formulation (4:14:8) at a dosage of 2 kg m−3 soil. We randomized pots of seedlings in a covered greenhouse with diffuse-light film and irrigated them with 500 mL of water every five days. Immediately after planting and at 30, 60, 90, and 120 days after planting, we measured the growth characteristics: height (cm) and stem diameter (mm).

2.6. Data Analysis

The physiological data (leaf water potential, daily transpiration rate, SPAD value, chlorophyll a and b, anthocyanins, and carotenoids content) were submitted to the Shapiro–Wilk test [42] to verify the normality. Analysis of Variance (ANOVA) [43] was performed on these data (p < 0.05). The Scott–Knott test [44] was used for multiple comparisons (p < 0.05).
The relationship between each total nutrient content and irrigation volume at each leaf angle was evaluated using the Pearson correlation coefficient (p < 0.05 and p < 0.01).
To analyze the effect of the treatments applied during the nursery phase on seedling growth performance after potting, the ANOVA was performed on the growth data every 30 days (p < 0.05). Before the analysis, the normality of the data was verified with the Shapiro–Wilk test. The Scott–Knott test was used for multiple comparisons (p < 0.05). All statistical analyses were performed with the STATISTICA software package [45].

3. Results

3.1. Physiological Quality of Seedlings

In the ANOVA (Tables S1–S7 available in Supplementary Materials), the significant interaction between irrigation volume and mean leaf angle influenced the leaf water potential, daily transpiration rate, SPAD value, chlorophyll a and b, anthocyanins, and carotenoids content (p < 0.05).
Increasing irrigation volume did not significantly increase daily transpiration rate at 58°, 55°, 42°, and 38° leaf angles. For leaf angles of −54°, 31°, and 57°, the application of a 10 mm irrigation volume increased the daily transpiration rate, which was not significantly different from the larger irrigation volumes. On the other hand, for leaf angles of −14° and −56°, the largest irrigation volume (14 mm) was required to provide a greater daily transpiration rate (Figure 1).
In addition, species with negative leaf angles showed less negative leaf water potential at 14 mm irrigation volume, except for Heliocarpus popayanensis (−54°), for which this attribute did not significantly differ between irrigation volumes (Figure 2). It is important to highlight that Heliocarpus popayanensis had the smallest mean leaf area of the species tested (45.73 cm2; Table S8 available in Supplementary Materials). For species with mean leaf angles of 58°, 57°, 55°, 42°, 38°, and 31°, increasing irrigation volume did not significantly change leaf water potential.
Pigment contents and SPAD values were reduced in varying proportions with increasing irrigation volume when the leaf angle of the species was positive and −54°, except for leaf angle 38° where irrigation volume did not significantly change chlorophyll a and b or anthocyanins content. For the leaf angles of −14° and −56°, the larger irrigation volumes were required to produce higher carotenoids, chlorophyll a and b, and anthocyanins content (Figure 3, Figure 4, Figure 5 and Figure 6) and a higher SPAD value (Figure 7).
For each mean leaf angle, the Pearson’s correlation coefficient between each total nutrient content and irrigation volume was significant for most nutrients. When significant, for leaf angles of −14° and −56°, the correlation coefficient was positive, i.e., an increase in irrigation volume increased the total nutrient content. For leaf angles of 58°, 57°, 55°, 42°, 38°, 31°, and −54°, the correlation coefficient was negative, i.e., total nutrient content decreased as irrigation volume increased (Figure 8).

3.2. Seedling Growth Performance after Planting in Pot

The height and stem diameter of the species at the end of the nursery phase followed a pattern similar to that of the physiological attributes in response to the irrigation volumes applied, i.e., the 8 mm irrigation volume produced higher growth seedlings when the leaf angles were 58°, 57°, 55°, 42°, 38°, 31°, and −54°, while a 14 mm irrigation volume was necessary for the mean leaf angles of −14° and −56°.
After planting, the effect of the treatments applied during the nursery phase influenced the performance of the potted seedlings to different extents. Regarding height, the effect of irrigation volumes remained significant up to 120 days after planting at leaf angles of 57° and 58°; 42° (90 days); 38°, 31°, and −14° (60 days); and −54° and −56° (30 days). The 55° mean leaf angle was the only one where irrigation volumes differed only at the time of planting (Figure 9).
For stem diameter, there was a difference between the irrigation volumes applied during the nursery phase until 120 days after planting for the species with an angle of 42°; −14° and 57° (60 days); and −54° and 55° (30 days). For leaf angles of 58° and 31°, irrigation volumes did not differ between 30 and 90 days after planting; however, they differed again at 120 days. The species with angles of −56° and 38° were the only species in which the irrigation volumes applied during the nursery phase differed only at the time of planting (Figure 10).

4. Discussion

4.1. Physiological Quality of Seedlings

Irrigation water capture and its direction to the substrate is hindered by seedling species with negative mean leaf angles (−14° and −56°), their leaf area, and the spatial distribution of leaves (extended their leaves downwards of the stem) (Figure 11a,b); therefore, to achieve less negative leaf water potential and to increase the daily transpiration rate, a 14 mm irrigation volume is required to compensate for the uncaptured water.
These results are in accordance with the study of [46], i.e., for species with negative mean leaf angles of −1° and −64°, the smallest irrigation volume (6 mm) reduced the leaf water potential, stomatal conductance, and daily transpiration rate. According to [47], the leaf water potential indicates whether the physiological status of seedlings has deteriorated. In their review, leaf water potential had a 100% positive correlation with growth, highlighting the importance of this attribute in assessing seedling quality. Furthermore, leaf water potential shows interactions between water supply and plant water demand. Even moderate stress, as caused by some of the treatments in this study, can cause stomatal closure, reducing transpiration rates and photosynthesis [48,49,50].
Seedlings of Heliocarpus popayanensis (−54°) showed different behavior from other negative leaf angles, i.e., it was not necessary to apply a 14 mm irrigation volume to provide less negative leaf water potential and increase the daily transpiration rate. This was due to the fact that this species had the smaller mean leaf area of all species tested here (45.73 cm²; Table S8 available in Supplementary Materials) and concentrated their leaf area in the upper half of the stem (Figure 11c), which facilitated the access of irrigation water to the substrate and thus fully satisfied the water requirements of the seedlings with the smaller irrigation volumes. These results are in accordance with [51], who recommended that leaf angle measurements be combined with concurrent assessments of leaf traits (e.g., leaf area and spatial distribution of leaves). These combinations would be helpful in further understanding the effects of leaf angle variation and water regime on seedling quality.
For mean leaf angles of 57° and 31°, the daily transpiration rate increased as the irrigation volume increased from 8 mm to 10 mm, which did not differ significantly from the other irrigation volumes. For mean leaf angles of 58°, 55°, 42°, and 38°, the 8 mm irrigation volume was sufficient to maintain an adequate volume of water in the container, so that daily transpiration rate and leaf water potential were not significantly different from the larger irrigation volumes. Among these species, Moquiniastrum polymorphum (42°) had the higher midday leaf water potential values (ranging from −3.28 to −3.55 MPa). Moquiniastrum polymorphum is a common species in dry forests and Cerrado, occurring both in the more open and in the more closed vegetation types of typical or forested savanna and riparian forests [52] with fire resistance [53]. Drought-tolerant species function at low plant water potentials by maintaining low osmotic potentials or by accumulating solutes in response to stress [54]. They have the ability to maintain turgor, growth, and gas exchange in very dry environments [55].
For mean leaf angles of −56° and −14°, greater irrigation volumes were necessary to achieve higher pigment contents and SPAD values. This indicates that the application of smaller irrigation volumes could not fully meet the water and nutrient requirements of these seedlings (Figure 11a,b). During the stress period, carotenoids are associated with several important physiological functions, including light harvesting and photoprotection [56,57]. In Erythrina velutina and Poincianella pyramidalis seedlings, the full recovery of photosynthesis after rewatering was associated with enhanced photoprotection by carotenoids, ensuring the resilience of these species in the face of periodic drought [58].
The effect of irrigation on chlorophyll and carotenoids content is controversial. In seedlings of Picea abies [59], Pistacia lentiscus [60], Pachira aquatica [61], Prunus sargentii [62], Populus nigra and Quercus brantii [63], drought stress caused a decrease in the concentrations of chlorophylls and carotenoids, which may have a protective role in protecting the photosynthetic apparatus against drought-induced damage. In seedlings of Acacia arabica [64] and Larix kaempferi [62], with higher water content, carotenoids and leaf chlorophyll were not affected. Thus, pigment response to irrigation and water stress may vary among species.
For seedlings with leaf angles of 58°, 57°, 55°, 42°, 38°, 31°, and −54°, the smallest irrigation volume (8 mm) was sufficient to produce higher pigment contents and SPAD values. The increase in irrigation volume at these leaf angles resulted in a loss of ions and probably affected the biosynthesis of chlorophyll, carotenoids, and anthocyanins. Mineral nutrition can affect the synthesis of these pigments. It also significantly affects the dynamics of leaf surface formation and its extent, which is reflected in the photosynthetic potential and net photosynthetic productivity. The only exception was the seedlings of Lafoensia pacari (38°), which did not produce any anthocyanins content in any of the irrigation volumes. This result is in accordance with the studies of [65,66], where no anthocyanins and anthocyanidins (non-glycosylated form of anthocyanins) were found in the phytochemical profile of the hydroalcoholic extract of the leaves of Lafoensia pacari.
Of all the macronutrients, nitrogen has the greatest influence on plant development in general [67]. Furthermore, in tree species, the nitrogen concentration has been correlated with the chlorophyll content and the SPAD value [68,69,70,71,72,73,74], allowing the use of SPAD as a rapid and reliable diagnostic tool to predict nitrogen status in forest nurseries [75].
To develop large-scale nursery production practices that improve seedling quality at reduced cost, more knowledge is needed on irrigation and nutrient management in container seedlings [76,77,78,79]. For mean leaf angles of −14° and −56°, an increase in irrigation volume increased all the total macronutrient and micronutrient contents, except B and Fe, which were not significantly correlated. This indicates that the application of smaller irrigation volumes at these angles has difficulty reaching the substrate surface, which likely causes a reduction in ion contact with the roots (Figure 11a,b).
According to [80], it is necessary to apply greater irrigation volumes (e.g., 10, 12, and 14 mm) in Eucalyptus grandis seedlings to achieve higher nutrient contents. Optimal nutrient reserves can increase shoot growth during the field establishment phase. Seedlings with optimum nutrient reserves before planting had a positive relationship with shoot growth in 78% of the studies reviewed by [47]. In addition, high nutrient content in pine seedlings developed larger root systems by maintaining a greater number of growing roots rather than by increasing the elongation rate of individual roots, which can be interpreted as a strategy to maximize foraging efficiency [81].
At mean leaf angles of 58°, 57°, 55°, 42°, 38°, 31°, and −54°, all total macronutrient contents, except Ca and Mg in Psidium cattleyanum (55°), were reduced with greater irrigation volumes. In these species, 75.6% of the micronutrients were also reduced with increased irrigation volumes. It is not easy to perform efficient fertilization practices that deliver nutrients at the right time; however, new irrigation and fertilization strategies are being sought by commercial forest nurseries and researchers to improve fertilizer application and minimize negative adverse effects [82].

4.2. Seedling Growth Performance after Planting in Pot

Seedling quality is the key to successful active forest restoration programs, and especially under climate change [83,84,85], it has an important function in plant survival and growth [86,87,88,89]. Seedling quality assessment has evolved to consider various morphological and physiological measurement protocols in the nursery to predict future planting performance [90,91]. Thus, intrinsic growth potential is related to physiological and morphological seedling attributes and their eco-physiological behavior toward site characteristics [92].
We show that the duration of treatment effects applied at the nursery phase on the seedling growth performance after potting was variable. On the other hand, it is important to emphasize that for all species, up to 120 days after planting in pots, the effect of the irrigation volume that provided greater growth and physiological quality at the end of the nursery phase was not overcome by the other irrigation volumes applied (p < 0.05).
A positive correlation between the initial seedling height and stem diameter and subsequent growth after planting was found in 70% and 91% of the studies reviewed by [47], respectively. The height advantage is relevant on soils without water and nutrient deficits because the competition for light between seedlings and the site vegetation is the main factor limiting seedling development [93,94]. As a result of limited sunlight and depleted upper-profile soil moisture in areas of high vegetative competition, reductions in seedling carbon gain corresponded to substantial increases in seedling mortality and establishment failure [95,96]. Researchers agree on the importance of considering stem diameter as the best morphological attribute to predict seedling growth [97,98,99,100,101], especially under dry soil conditions [102].
The height and stem diameter of each species at the end of the nursery phase followed a similar pattern to that of the physiological attributes in response to the irrigation volumes applied. This correspondence between the physiological and morphological attributes was a relevant finding because quantifying the benefits of physiological plant attributes is a very narrow window.
For most nursery management programs, rapid and non-destructive morphological measurements are still best suited [103]. This is because seedling survival and subsequent establishment after planting depend not only on their physiological status but also on their morphological characteristics, ability to root, and eco-physiological response [104]. With this understanding, growers can implement appropriate nursery practices to improve seedling physiological functioning and morphological development [105].

5. Conclusions

Leaf angle can be used as a criterion to optimize irrigation in forest nurseries, prevent water and fertilizer wastage, and increase physiological tree seedling quality. Leaf angle measurements combined with concurrent assessments of leaf traits (e.g., leaf area and spatial distribution of leaves) are helpful in further understanding the effects of leaf angle variation and water regime on seedling quality.
Water access to the substrate is facilitated by tree seedlings with positive mean leaf angles; thus, an irrigation volume of 8 mm is sufficient to increase physiological tree seedling quality. Conversely, negative mean leaf angles show the opposite response, requiring the largest irrigation volume (14 mm) to increase physiological tree seedling quality, except when the mean leaf area is small and concentrated in the upper half of the stem, which facilitates the access of irrigation water to the substrate and thus satisfies seedling water requirements.
For all species, up to 120 days after planting in pots, the effect of the irrigation volume that provides greater growth and physiological quality at the end of the nursery phase is not overcome by the other irrigation volumes applied, highlighting the benefits of applying the correct irrigation volume in tree seedlings. Furthermore, the height and stem diameter of tree seedling species at the end of the nursery phase in response to irrigation volume show a similar pattern to physiological attributes, facilitating the creation of operational procedures for active forest restoration.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14051042/s1: Table S1: Analysis of variance (ANOVA) for the daily transpiration rate of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase; Table S2: Analysis of variance (ANOVA) for the leaf water potential of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase; Table S3: Analysis of variance (ANOVA) for the carotenoids content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase; Table S4: Analysis of variance (ANOVA) for the chlorophyll a content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase; Table S5: Analysis of variance (ANOVA) for the chlorophyll b content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase; Table S6: Analysis of variance (ANOVA) for the anthocyanins content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase; Table S7: Analysis of variance (ANOVA) for the SPAD values of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase; Table S8: Mean leaf area (cm2) at the end of the nursery phase of nine tree seedling species with different mean leaf angles submitted to four daily irrigation volumes.

Author Contributions

Conceptualization, R.B.G.d.S. and M.R.d.S.; methodology, R.B.G.d.S., D.Z.d.P., M.M.P.S. and M.R.d.S.; software, R.B.G.d.S., M.M.P.S. and D.S.; formal analysis, R.B.G.d.S., D.Z.d.P., M.M.P.S., A.A.d.S.B., D.S. and M.R.d.S.; investigation, R.B.G.d.S.; writing—original draft preparation, R.B.G.d.S.; writing—review and editing, R.B.G.d.S., I.W., D.Z.d.P., D.S., M.M.P.S., A.A.d.S.B. and M.R.d.S.; visualization, R.B.G.d.S., D.S., I.W. and D.Z.d.P.; supervision, M.R.d.S.; project administration, M.R.d.S. and R.B.G.d.S. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by São Paulo Research Foundation (FAPESP)—Grant Number 2013/17447-8.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data are provided in the main manuscript. Contact the corresponding author if further explanation is needed.

Acknowledgments

We wish to thank Giuseppina Pace Pereira Lima, Luiz Fernando Rolim de Almeida, Angélica Lino Rodrigues, Cláudio Roberto Ribeiro da Silva, José Aparecido Benedito, João Marques Rodrigues, Rosangela Cristina Moreci, Ludmila Ribeiro Roder, Thaís Randazzo Enz, Leonardo Albiero Gomes, and Maurício Torloni Neto.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Haase, D.; Davis, A. Developing and Supporting Quality Nursery Facilities and Staff Are Necessary to Meet Global Forest and Landscape Restoration Needs. Reforesta 2017, 4, 69–93. [Google Scholar] [CrossRef]
  2. Grossnickle, S.C.; Kiiskila, S.B.; Haase, D.L. Seedling Ecophysiology—Five Questions To Explore in the Nursery for Optimizing Subsequent Field Success. Tree Plant. Notes 2020, 63, 112–127. [Google Scholar]
  3. Haase, D.L. Understanding Forest Seedling Quality: Measurements and Interpretation. Tree Plant. Notes 2008, 52, 24–30. [Google Scholar]
  4. Davis, A.S.; Jacobs, D.F. Quantifying Root System Quality of Nursery Seedlings and Relationship to Outplanting Performance. New For. 2005, 30, 295–311. [Google Scholar] [CrossRef]
  5. Rodrigues, A.L.; Bertholdi, A.A.S.; Mantoan, L.P.B.; Vasconcellos, G.M.; Almeida, L.F.R. Photochemistry and Hydric Responses of Congeneric Croton Species at Restoration Sites under Dry Season: Implications for Species Selection. Theor. Exp. Plant Physiol. 2019, 31, 329–339. [Google Scholar] [CrossRef]
  6. da Silva, R.B.G.; Simões, D.; da Silva, M.R. Qualidade de Mudas Clonais de Eucalyptus Urophylla x E. Grandis Em Função Do Substrato. Rev. Bras. Eng. Agrícola Ambient. 2012, 16, 297–302. [Google Scholar] [CrossRef]
  7. da Silva, R.B.G.; Gabira, M.M.; Prado, D.Z.D.; Uesugi, G.; Simões, D.; da Silva, M.R. Influence of Mean Leaf Angles and Irrigation Volumes on Water Capture, Leaching, and Growth of Tropical Tree Seedlings. Forests 2020, 11, 1198. [Google Scholar] [CrossRef]
  8. Beeson, R.C.; Yeager, T.H. Plant Canopy Affects Sprinkler Irrigation Application Efficiency of Container-Grown Ornamentals. HortScience 2003, 38, 1373–1377. [Google Scholar] [CrossRef]
  9. Yeager, T.; Million, J.; Larsen, C.; Stamps, B. Florida Nursery Best Management Practices: Past, Present, and Future. Horttechnology 2010, 20, 82–88. [Google Scholar] [CrossRef]
  10. Reinhardt, D.; Kuhlemeier, C. Plant Architecture. EMBO Rep. 2002, 3, 846–851. [Google Scholar] [CrossRef]
  11. Liu, J.; Skidmore, A.K.; Wang, T.; Zhu, X.; Premier, J.; Heurich, M.; Beudert, B.; Jones, S. Variation of Leaf Angle Distribution Quantified by Terrestrial LiDAR in Natural European Beech Forest. ISPRS J. Photogramm. Remote Sens. 2019, 148, 208–220. [Google Scholar] [CrossRef]
  12. King, D.A. The Functional Significance of Leaf Angle in Eucalyptus. Aust. J. Bot. 1997, 45, 619. [Google Scholar] [CrossRef]
  13. Falster, D.S.; Westoby, M. Leaf Size and Angle Vary Widely across Species: What Consequences for Light Interception? New Phytol. 2003, 158, 509–525. [Google Scholar] [CrossRef]
  14. van Zanten, M.; Pons, T.L.; Janssen, J.A.M.; Voesenek, L.A.C.J.; Peeters, A.J.M. On the Relevance and Control of Leaf Angle. Crit. Rev. Plant Sci. 2010, 29, 300–316. [Google Scholar] [CrossRef]
  15. Hagemeier, M.; Leuschner, C. Functional Crown Architecture of Five Temperate Broadleaf Tree Species: Vertical Gradients in Leaf Morphology, Leaf Angle, and Leaf Area Density. Forests 2019, 10, 265. [Google Scholar] [CrossRef]
  16. Chianucci, F.; Pisek, J.; Raabe, K.; Marchino, L.; Ferrara, C.; Corona, P. A Dataset of Leaf Inclination Angles for Temperate and Boreal Broadleaf Woody Species. Ann. For. Sci. 2018, 75, 50. [Google Scholar] [CrossRef]
  17. Pisek, J.; Adamson, K. Dataset of Leaf Inclination Angles for 71 Different Eucalyptus Species. Data Br. 2020, 33, 106391. [Google Scholar] [CrossRef]
  18. Pisek, J.; Diaz-Pines, E.; Matteucci, G.; Noe, S.; Rebmann, C. On the Leaf Inclination Angle Distribution as a Plant Trait for the Most Abundant Broadleaf Tree Species in Europe. Agric. For. Meteorol. 2022, 323, 109030. [Google Scholar] [CrossRef]
  19. Niinemets, Ü. A Review of Light Interception in Plant Stands from Leaf to Canopy in Different Plant Functional Types and in Species with Varying Shade Tolerance. Ecol. Res. 2010, 25, 693–714. [Google Scholar] [CrossRef]
  20. Zou, J.; Zhong, P.; Hou, W.; Zuo, Y.; Leng, P. Estimating Needle and Shoot Inclination Angle Distributions and Projection Functions in Five Larix Principis-Rupprechtii Plots via Leveled Digital Camera Photography. Forests 2020, 12, 30. [Google Scholar] [CrossRef]
  21. Deguchi, R.; Koyama, K. Photosynthetic and Morphological Acclimation to High and Low Light Environments in Petasites Japonicus Subsp. Giganteus. Forests 2020, 11, 1365. [Google Scholar] [CrossRef]
  22. de Mattos, E.M.; Binkley, D.; Campoe, O.C.; Alvares, C.A.; Stape, J.L. Variation in Canopy Structure, Leaf Area, Light Interception and Light Use Efficiency among Eucalyptus Clones. For. Ecol. Manag. 2020, 463, 118038. [Google Scholar] [CrossRef]
  23. Peguero-Pina, J.J.; Vilagrosa, A.; Alonso-Forn, D.; Ferrio, J.P.; Sancho-Knapik, D.; Gil-Pelegrín, E. Living in Drylands: Functional Adaptations of Trees and Shrubs to Cope with High Temperatures and Water Scarcity. Forests 2020, 11, 1028. [Google Scholar] [CrossRef]
  24. Wu, X.; Fan, W.; Du, H.; Ge, H.; Huang, F.; Xu, X. Estimating Crown Structure Parameters of Moso Bamboo: Leaf Area and Leaf Angle Distribution. Forests 2019, 10, 686. [Google Scholar] [CrossRef]
  25. Liu, Q.; Xie, L.; Li, F. Dynamic Simulation of the Crown Net Photosynthetic Rate for Young Larix Olgensis Henry Trees. Forests 2019, 10, 321. [Google Scholar] [CrossRef]
  26. Liu, Y.; Shan, Y.; Ying, H.; Wala, D.; Zhang, X.; Ruhan, A.; Rina, S.; Rina, S. Examining the Angular Effects of UAV-LS on Vegetation Metrics Using a Framework for Mediating Effects. Forests 2022, 13, 1221. [Google Scholar] [CrossRef]
  27. Wen, Y.; Zhuang, L.; Wang, H.; Hu, T.; Fan, W. An Automated Hemispherical Scanner for Monitoring the Leaf Area Index of Forest Canopies. Forests 2022, 13, 1355. [Google Scholar] [CrossRef]
  28. Zhang, B.; Wang, X.; Yuan, X.; An, F.; Zhang, H.; Zhou, L.; Shi, J.; Yun, T. Simulating Wind Disturbances over Rubber Trees with Phenotypic Trait Analysis Using Terrestrial Laser Scanning. Forests 2022, 13, 1298. [Google Scholar] [CrossRef]
  29. Qu, Y.; Wang, J.; Song, J.; Wang, J. Potential and Limits of Retrieving Conifer Leaf Area Index Using Smartphone-Based Method. Forests 2017, 8, 217. [Google Scholar] [CrossRef]
  30. Anna, K.-I.; Sylwia, Ł.; Marcin, Z.; Ewa, S.-O.; Wojtan, B. Variability of Leaf Wetting and Water Storage Capacity of Branches of 12 Deciduous Tree Species. Forests 2020, 11, 1158. [Google Scholar] [CrossRef]
  31. Dong, L.; Han, H.; Kang, F.; Cheng, X.; Zhao, J.; Song, X. Rainfall Partitioning in Chinese Pine (Pinus Tabuliformis Carr.) Stands at Three Different Ages. Forests 2020, 11, 243. [Google Scholar] [CrossRef]
  32. Fladung, M. Targeted CRISPR/Cas9-Based Knock-Out of the Rice Orthologs TILLER ANGLE CONTROL 1 (TAC1) in Poplar Induces Erect Leaf Habit and Shoot Growth. Forests 2021, 12, 1615. [Google Scholar] [CrossRef]
  33. Zhang, L.; Yang, J.; Huang, Y.; Jia, Z.; Fang, Y. Leaf Venation Variation and Phenotypic Plasticity in Response to Environmental Heterogeneity in Parrotia Subaequalis (H. T. Chang) R. M. Hao et H. T. Wei, An Endemic and Endangered Tree Species from China. Forests 2018, 9, 247. [Google Scholar] [CrossRef]
  34. Roder, L.R.; Guerrini, I.A.; Lozano Sivisaca, D.C.; Yaguana Puglla, C.A.; Góes de Moraes, F.; Pinheiro da Silva, J.; Batista Fonseca, R.C.; Umbelino, M.T.; James, J.N.; Capra, G.F.; et al. Atlantic Rainforest Natural Regeneration in Fragmented Formations Affected by Increasing Human Disturbance. J. Environ. Manag. 2023, 325, 116521. [Google Scholar] [CrossRef] [PubMed]
  35. Christiansen, J.E. Irrigation by Sprinkling; University of California: Berkeley, CA, USA, 1942. [Google Scholar]
  36. Merriam, J.L.; Keller, J. Farm Irrigation System Evaluation: A Guide for Management; Utah State University: Logan, UT, USA, 1978. [Google Scholar]
  37. Aroca, R.; Porcel, R.; Ruiz-Lozano, J.M. How Does Arbuscular Mycorrhizal Symbiosis Regulate Root Hydraulic Properties and Plasma Membrane Aquaporins in Phaseolus Vulgaris under Drought, Cold or Salinity Stresses? New Phytol. 2007, 173, 808–816. [Google Scholar] [CrossRef] [PubMed]
  38. Sims, D.A.; Gamon, J.A. Relationships between Leaf Pigment Content and Spectral Reflectance across a Wide Range of Species, Leaf Structures and Developmental Stages. Remote Sens. Environ. 2002, 81, 337–354. [Google Scholar] [CrossRef]
  39. Landis, T.D. Mineral Nutrition as an Index of Seedling Quality: Principles and Applications. In Evaluating Seedling Quality: Principles, Procedures, and Predictive Abilities of Major Tests; Duryea, M.L., Ed.; Forest Research Laboratory, Oregon State University: Corvallis, OR, USA, 1985; pp. 29–48. [Google Scholar]
  40. Oliet, J.A.; Tejada, M.; Salifu, K.F.; Collazos, A.; Jacobs, D.F. Performance and Nutrient Dynamics of Holm Oak (Quercus Ilex L.) Seedlings in Relation to Nursery Nutrient Loading and Post-Transplant Fertility. Eur. J. For. Res. 2009, 128, 253–263. [Google Scholar] [CrossRef]
  41. Xu, L.; Zhang, X.; Zhang, D.; Wei, H.; Guo, J. Using Morphological Attributes for the Fast Assessment of Nutritional Responses of Buddhist Pine (Podocarpus Macrophyllus [Thunb.] D. Don) Seedlings to Exponential Fertilization. PLoS ONE 2019, 14, e0225708. [Google Scholar] [CrossRef]
  42. Shapiro, S.S.; Wilk, M.B. An Analysis of Variance Test for Normality (Complete Samples). Biometrika 1965, 52, 591–611. [Google Scholar] [CrossRef]
  43. Fisher, R.A. Statistical Methods For Research Workers; Oliver and Boyd: London, UK, 1925. [Google Scholar]
  44. Scott, A.J.; Knott, M. A Cluster Analysis Method for Grouping Means in the Analysis of Variance. Biometrics 1974, 30, 507–512. [Google Scholar] [CrossRef]
  45. StatSoft, Inc. STATISTICA (Data Analysis Software System), version 8; StatSoft, Inc.: Tulsa, OK, USA, 2007. [Google Scholar]
  46. Delgado, L.G.M.; da Silva, R.B.G.; Gabira, M.M.; Rodrigues, A.L.; Simões, D.; de Almeida, L.F.R.; da Silva, M.R. Mean Leaf Angles Affect Irrigation Efficiency and Physiological Responses of Tropical Species Seedling. Forests 2022, 13, 832. [Google Scholar] [CrossRef]
  47. Grossnickle, S.C.; MacDonald, J.E. Why Seedlings Grow: Influence of Plant Attributes. New For. 2018, 49, 1–34. [Google Scholar] [CrossRef]
  48. Taiz, L.; Zeiger, E. Plant Physiology; ArtMed: Porto Alegre, Brazil, 2017. [Google Scholar]
  49. Vishwakarma, K.; Upadhyay, N.; Kumar, N.; Yadav, G.; Singh, J.; Mishra, R.K.; Kumar, V.; Verma, R.; Upadhyay, R.G.; Pandey, M.; et al. Abscisic Acid Signaling and Abiotic Stress Tolerance in Plants: A Review on Current Knowledge and Future Prospects. Front. Plant Sci. 2017, 8, 161. [Google Scholar] [CrossRef]
  50. Yuan, Z.-S.; Liu, F.; Xie, B.-G.; Zhang, G.-F. The Growth-Promoting Effects of Endophytic Bacteria on Phyllostachys Edulis. Arch. Microbiol. 2018, 200, 921–927. [Google Scholar] [CrossRef]
  51. Yang, X.; Li, R.; Jablonski, A.; Stovall, A.; Kim, J.; Yi, K.; Ma, Y.; Beverly, D.; Phillips, R.; Novick, K.; et al. Leaf Angle as a Leaf and Canopy Trait: Rejuvenating Its Role in Ecology with New Technology. Ecol. Lett. 2023, 1–16. [Google Scholar] [CrossRef] [PubMed]
  52. Durigan, G.; Baitello, J.B.; Franco, G.A.D.C.; Siqueira, M.F. Plantas Do Cerrado Paulista: Imagens de Uma Paisagem Ameaçada; Páginas & Letras: São Paulo, Brazil, 2004; ISBN 85-86508-32-2. [Google Scholar]
  53. Brandes, A.F.D.N.; Sánchez-Tapia, A.; Sansevero, J.B.B.; Albuquerque, R.P.; Barros, C.F. Fire Records in Tree Rings of Moquiniastrum Polymorphum: Potential for Reconstructing Fire History in the Brazilian Atlantic Forest. Acta Bot. Bras. 2019, 33, 61–66. [Google Scholar] [CrossRef]
  54. Morgan, J.M. Osmoregulation and Water Stress in Higher Plants. Annu. Rev. Plant Physiol. 1984, 35, 299–319. [Google Scholar] [CrossRef]
  55. White, D.A.; Turner, N.C.; Galbraith, J.H. Leaf Water Relations and Stomatal Behavior of Four Allopatric Eucalyptus Species Planted in Mediterranean Southwestern Australia. Tree Physiol. 2000, 20, 1157–1165. [Google Scholar] [CrossRef]
  56. Lichtenthaler, H.K. Biosynthesis, Accumulation and Emission of Carotenoids, α-Tocopherol, Plastoquinone, and Isoprene in Leaves under High Photosynthetic Irradiance. Photosynth. Res. 2007, 92, 163–179. [Google Scholar] [CrossRef]
  57. Nisar, N.; Li, L.; Lu, S.; Khin, N.C.; Pogson, B.J. Carotenoid Metabolism in Plants. Mol. Plant 2015, 8, 68–82. [Google Scholar] [CrossRef]
  58. de Sousa Leite, T.; da Silva Dias, N.; Oliveira de Freitas, R.M.; Dallabona Dombroski, J.L.; de Sousa Leite, M.; Martins de Farias, R. Ecophysiological and Biochemical Responses of Two Tree Species from a Tropical Dry Forest to Drought Stress and Recovery. J. Arid Environ. 2022, 200, 104720. [Google Scholar] [CrossRef]
  59. Pukacki, P.M.; Kamińska-Rożek, E. Effect of Drought Stress on Chlorophyll a Fluorescence and Electrical Admittance of Shoots in Norway Spruce Seedlings. Trees 2005, 19, 539–544. [Google Scholar] [CrossRef]
  60. Vasques, A.R.; Pinto, G.; Dias, M.C.; Correia, C.M.; Moutinho-Pereira, J.M.; Vallejo, V.R.; Santos, C.; Keizer, J.J. Physiological Response to Drought in Seedlings of Pistacia Lentiscus (Mastic Tree). New For. 2016, 47, 119–130. [Google Scholar] [CrossRef]
  61. Frosi, G.; Harand, W.; de Oliveira, M.T.; Pereira, S.; Cabral, S.P.; Montenegro, A.A.D.A.; Santos, M.G. Different Physiological Responses under Drought Stress Result in Different Recovery Abilities of Two Tropical Woody Evergreen Species. Acta Bot. Bras. 2017, 31, 153–160. [Google Scholar] [CrossRef]
  62. Bhusal, N.; Lee, M.; Reum Han, A.; Han, A.; Kim, H.S. Responses to Drought Stress in Prunus Sargentii and Larix Kaempferi Seedlings Using Morphological and Physiological Parameters. For. Ecol. Manag. 2020, 465, 118099. [Google Scholar] [CrossRef]
  63. Karimi, A.; Tabari, M.; Javanmard, Z.; Bader, M.K.-F. Drought Effects on Morpho-Physiological and Biochemical Traits in Persian Oak and Black Poplar Seedlings. Forests 2022, 13, 399. [Google Scholar] [CrossRef]
  64. Lassouane, N.; Aïd, F.; Lutts, S. Water Stress Impact on Young Seedling Growth of Acacia Arabica. Acta Physiol. Plant. 2013, 35, 2157–2169. [Google Scholar] [CrossRef]
  65. Firmo, W.C.A.; Miranda, M.V.; Coutinho, G.S.L.; Silveira, L.M.S.; Olea, R.S.G. Estudo Fitoquímico e Avaliação Da Atividade Antibacteriana de Lafoensia Pacari (Lythraceae). Publ. UEPG Cienc. Biol. Saude 2014, 20, 7–12. [Google Scholar] [CrossRef]
  66. Lima, P.C.; Santos, M.G.; Calabrese, K.S.; Silva, A.L.A.; Almeida, F. Avaliação Da Capacidade Leishmanicida de Espécies Vegetais Do Cerrado. Rev. Patol. Trop. 2015, 44, 45–55. [Google Scholar] [CrossRef]
  67. Bojovic, B.; Stojanovic, J. Chlorophyll and Carotenoid Content in Wheat Cultivars as a Function of Mineral Nutrition. Arch. Biol. Sci. 2005, 57, 283–290. [Google Scholar] [CrossRef]
  68. Richardson, A.D.; Duigan, S.P.; Berlyn, G.P. An Evaluation of Noninvasive Methods to Estimate Foliar Chlorophyll Content. New Phytol. 2002, 153, 185–194. [Google Scholar] [CrossRef]
  69. Chenard, C.H.; Kopsell, D.A.; Kopsell, D.E. Nitrogen Concentration Affects Nutrient and Carotenoid Accumulation in Parsley. J. Plant Nutr. 2005, 28, 285–297. [Google Scholar] [CrossRef]
  70. Madeira, A.C.; Madeira, M.; Fabião, A.; Marques, P.; Carneiro, M. Avaliação Da Nutrição de Plantações Jovens de Eucalipto Por Análise Foliar e Métodos Não Destrutivos. Rev. Ciências Agrárias 2009, 32, 139–153. [Google Scholar] [CrossRef]
  71. Júnior, O.A.D.O.; Cairo, P.A.R.; De Novaes, A.B. Características Morfofisiológicas Associadas à Qualidade de Mudas de Eucalyptus Urophylla Produzidas Em Diferentes Substratos. Rev. Árvore 2011, 35, 1173–1180. [Google Scholar] [CrossRef]
  72. De Carvalho, R.P.; Davide, L.M.C.; Borges, F.L.G.; Davide, A.C.; Daniel, O. Respostas Morfofisiológicas Entre Procedências de Canafístula Submetidas a Diferentes Condições Hídricas e Nutricionais. Pesqui. Florest. Bras. 2015, 35, 179–188. [Google Scholar] [CrossRef]
  73. Uesugi, G.; Favan, J.R.; De Moraes, C.B.; Wanginiak, T.C.R.; da Silva, M.R. Utilização Do SPAD-502 Para a Predição Dos Teores de Nitrogênio Em Mudas de Croton Urucurana Baill. (Nota Científica). Rev. do Inst. Florest. 2015, 27, 177–181. [Google Scholar] [CrossRef]
  74. de Moura, A.R.; Nogueira, R.J.M.C.; da Silva, J.A.A.; de Lima, T.V. Relações Hídricas e Solutos Orgânicos Em Plantas Jovens de Jatropha Curcas L. Sob Diferentes Regimes Hídricos. Ciência Florest. 2016, 26, 345–354. [Google Scholar] [CrossRef]
  75. Acevedo, M.; Rubilar, R.; Dumroese, R.K.; Ovalle, J.F.; Sandoval, S.; Chassin-Trubert, R. Nitrogen Loading of Eucalyptus Globulus Seedlings: Nutritional Dynamics and Influence on Morphology and Root Growth Potential. New For. 2021, 52, 31–46. [Google Scholar] [CrossRef]
  76. Scagel, C.F.; Bi, G.; Fuchigami, L.H.; Regan, R.P. Irrigation Frequency Alters Nutrient Uptake in Container-Grown Rhododendron Plants Grown with Different Rates of Nitrogen. HortScience 2012, 47, 189–197. [Google Scholar] [CrossRef]
  77. Silva, D.; Stuepp, C.A.; Wenfling, I.; Helm, C.; Angelo, A.C. Influence of Seed Storage Conditions on Quality of Torresea Acreana Seedlings. Cerne 2019, 25, 60–67. [Google Scholar] [CrossRef]
  78. Mangueira, J.R.S.A.; Holl, K.D.; Rodrigues, R.R. Enrichment Planting to Restore Degraded Tropical Forest Fragments in Brazil. Ecosyst. People 2019, 15, 3–10. [Google Scholar] [CrossRef]
  79. Simões, D.; Gil, J.F.S.; da Silva, R.B.G.; Munis, R.A.; da Silva, M.R. Stochastic Economic Analysis of Investment Projects in Forest Restoration Involving Containerized Tree Seedlings in Brazil. Forests 2021, 12, 1381. [Google Scholar] [CrossRef]
  80. Lopes, J.L.W.; Guerrini, I.A.; Saad, J.C.C.; da Silva, M.R. Nutrição Mineral de Mudas de Eucalipto Produzidas Sob Diferentes Lâminas de Irrigação e Substratos. Rev. Bras. Ciência Do Solo 2007, 31, 713–722. [Google Scholar] [CrossRef]
  81. Toca, A.; Oliet, J.A.; Villar-Salvador, P.; Martínez Catalán, R.A.; Jacobs, D.F. Ecologically Distinct Pine Species Show Differential Root Development after Outplanting in Response to Nursery Nutrient Cultivation. For. Ecol. Manag. 2019, 451, 117562. [Google Scholar] [CrossRef]
  82. Oliet, J.A.; Salazar, J.M.; Villar, R.; Robredo, E.; Valladares, F. Fall Fertilization of Holm Oak Affects N and P Dynamics, Root Growth Potential, and Post-Planting Phenology and Growth. Ann. For. Sci. 2011, 68, 647–656. [Google Scholar] [CrossRef]
  83. del Campo, A.D.; Segura-Orenga, G.; Molina, A.J.; González-Sanchis, M.; Reyna, S.; Hermoso, J.; Ceacero, C.J. On the Need to Further Refine Stock Quality Specifications to Improve Reforestation under Climatic Extremes. Forests 2022, 13, 168. [Google Scholar] [CrossRef]
  84. Vieira, D.L.M.; Rodrigues, S.B.; Jakovac, C.C.; da Rocha, G.P.E.; Reis, F.; Borges, A. Active Restoration Initiates High Quality Forest Succession in a Deforested Landscape in Amazonia. Forests 2021, 12, 1022. [Google Scholar] [CrossRef]
  85. Fiore, N.V.; Ferreira, C.C.; Dzedzej, M.; Massi, K.G. Monitoring of a Seedling Planting Restoration in a Permanent Preservation Area of the Southeast Atlantic Forest Biome, Brazil. Forests 2019, 10, 768. [Google Scholar] [CrossRef]
  86. Stape, J.L.; Gonçalves, J.L.M.; Gonçalves, A.N. Relationships between Nursery Practices and Field Performance for Eucalyptus Plantations in Brazil. New For. 2001, 22, 19–41. [Google Scholar] [CrossRef]
  87. Campbell, K.A.; Hawkins, C.D.B. Effect of Seed Source and Nursery Culture on Paper Birch (Betula Papyrifera) Uprooting Resistance and Field Performance. For. Ecol. Manag. 2004, 196, 425–433. [Google Scholar] [CrossRef]
  88. Olivo, V.B.; Buduba, C.G. Influencia de Seis Sustratos En El Crecimiento de Pinus Ponderosa Producido En Contenedores Bajo Condiciones de Invernáculo. Bosque (Valdivia) 2006, 27, 267–271. [Google Scholar] [CrossRef]
  89. Devetaković, J.R.; Pavlović, S.; Krinulović, L.; Janković, I.K. Field Performance of Austrian Pine Bareroot Seedlings in Comparision to Seedlings Pattern and Density in the Nursery. Reforesta 2021, 11, 27–35. [Google Scholar]
  90. Jacobs, D.F.; Salifu, K.F.; Seifert, J.R. Relative Contribution of Initial Root and Shoot Morphology in Predicting Field Performance of Hardwood Seedlings. New For. 2005, 30, 235–251. [Google Scholar] [CrossRef]
  91. Jacobs, D.F.; Davis, A.S.; Dumroese, R.K.; Burney, O.T. Nursery Cultural Techniques Facilitate Restoration of Acacia Koa Competing with Invasive Grass in a Dry Tropical Forest. Forests 2020, 11, 1124. [Google Scholar] [CrossRef]
  92. Grossnickle, S. Restoration Silviculture: An Ecophysiological Perspective—Lessons Learned across 40 Years. Reforesta 2016, 1, 1–36. [Google Scholar] [CrossRef]
  93. Thiffault, N.; Jobidon, R.; Munson, A.D. Comparing Large Containerized and Bareroot Conifer Stock on Sites of Contrasting Vegetation Composition in a Non-Herbicide Scenario. New For. 2014, 45, 875–891. [Google Scholar] [CrossRef]
  94. Gardiner, R.; Shoo, L.P.; Dwyer, J.M. Look to Seedling Heights, Rather than Functional Traits, to Explain Survival during Extreme Heat Stress in the Early Stages of Subtropical Rainforest Restoration. J. Appl. Ecol. 2019, 56, 2687–2697. [Google Scholar] [CrossRef]
  95. Johnson, D.M.; Smith, W.K. Refugial Forests of the Southern Appalachians: Photosynthesis and Survival in Current-Year Abies Fraseri Seedlings. Tree Physiol. 2005, 25, 1379–1387. [Google Scholar] [CrossRef]
  96. Pinto, J.; McNassar, B.; Kildisheva, O.; Davis, A. Stocktype and Vegetative Competition Influences on Pseudotsuga Menziesii and Larix Occidentalis Seedling Establishment. Forests 2018, 9, 228. [Google Scholar] [CrossRef]
  97. Gomes, J.M.; Couto, L.; Leite, H.G.; Xavier, A.; Garcia, S.L.R. Parâmetros Morfológicos Na Avaliação de Qualidade de Mudas de Eucalyptus Grandis. Rev. Árvore 2002, 26, 655–664. [Google Scholar] [CrossRef]
  98. de Souza, C.A.M.; de Oliveira, R.B.; Filho, S.M.; Lima, J.S.D.S. Crescimento Em Campo de Espécies Florestais Em Diferentes Condições de Adubações. Ciência Florest. 2006, 16, 243–249. [Google Scholar] [CrossRef]
  99. Downes, G.M.; Drew, D.; Battaglia, M.; Schulze, D. Measuring and Modelling Stem Growth and Wood Formation: An Overview. Dendrochronologia 2009, 27, 147–157. [Google Scholar] [CrossRef]
  100. Binotto, A.F.; Lúcio, A.D.C.; Lopes, S.J. Correlations between Growth Variables and the Dickson Quality Index in Forest Seedlings. Cerne 2010, 16, 457–464. [Google Scholar] [CrossRef]
  101. Speck, T.; Burgert, I. Plant Stems: Functional Design and Mechanics. Annu. Rev. Mater. Res. 2011, 41, 169–193. [Google Scholar] [CrossRef]
  102. South, D.B.; Rakestraw, J.L.; Lowerts, G.A. Early Gains from Planting Large-Diameter Seedlings and Intensive Management Are Additive for Loblolly Pine. New For. 2001, 22, 97–110. [Google Scholar] [CrossRef]
  103. Ivetić, V.; Grossnickle, S.; Škorić, M. Forecasting the Field Performance of Austrian Pine Seedlings Using Morphological Attributes. iFor. Biogeosci. For. 2016, 10, 99. [Google Scholar] [CrossRef]
  104. Grossnickle, S.C. Why Seedlings Survive: Influence of Plant Attributes. New For. 2012, 43, 711–738. [Google Scholar] [CrossRef]
  105. Grossnickle, S. Seedling Establishment on a Forest Restoration Site—An Ecophysiological Perspective. Reforesta 2018, 6, 110–139. [Google Scholar] [CrossRef]
Figure 1. Daily transpiration rate of tree seedlings as influenced by mean leaf angles and irrigation volumes at end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
Figure 1. Daily transpiration rate of tree seedlings as influenced by mean leaf angles and irrigation volumes at end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
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Figure 2. Leaf water potential as influenced by mean leaf angles and irrigation volumes at end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
Figure 2. Leaf water potential as influenced by mean leaf angles and irrigation volumes at end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
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Figure 3. Carotenoids content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
Figure 3. Carotenoids content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
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Figure 4. Chlorophyll a content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
Figure 4. Chlorophyll a content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
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Figure 5. Chlorophyll b content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
Figure 5. Chlorophyll b content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
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Figure 6. Anthocyanins content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
Figure 6. Anthocyanins content of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
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Figure 7. SPAD values of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
Figure 7. SPAD values of tree seedlings as influenced by mean leaf angles and irrigation volumes at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). Different capital letters on the bars indicate significant differences between mean leaf angles at the same irrigation volume by the Scott–Knott test at 5% probability. Different small letters on the bars indicate significant differences between irrigation volumes for the same mean leaf angle by the Scott–Knott test at 5% probability. Error bars denote the standard error.
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Figure 8. Pearson’s correlation coefficient between irrigation volumes and content of nutrients in each mean leaf angle at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). ns = no significant correlation, * = significant correlation at 5% probability, and ** = significant correlation at 1% probability.
Figure 8. Pearson’s correlation coefficient between irrigation volumes and content of nutrients in each mean leaf angle at the end of the nursery phase. Croton floribundus (−56°), Heliocarpus popayanensis (−54°), Guazuma ulmifolia (−14°), Esenbeckia leiocarpa (31°), Lafoensia pacari (38°), Moquiniastrum polymorphum (42°), Psidium cattleyanum (55°), Magnolia ovata (57°), and Genipa americana (58°). ns = no significant correlation, * = significant correlation at 5% probability, and ** = significant correlation at 1% probability.
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Figure 9. Height (cm) of tree seedlings until 120 days after planting in pots as influenced by treatments applied during the nursery phase. (a) Genipa americana (58°), (b) Magnolia ovata (57°), (c) Psidium cattleyanum (55°), (d) Moquiniastrum polymorphum (42°), (e) Lafoensia pacari (38°), (f) Esenbeckia leiocarpa (31°), (g) Guazuma ulmifolia (−14°), (h) Heliocarpus popayanensis (−54°), and (i) Croton floribundus (−56°). Different letters on the lines indicate significant differences between irrigation volumes in the same month by the Scott–Knott test at 5% probability.
Figure 9. Height (cm) of tree seedlings until 120 days after planting in pots as influenced by treatments applied during the nursery phase. (a) Genipa americana (58°), (b) Magnolia ovata (57°), (c) Psidium cattleyanum (55°), (d) Moquiniastrum polymorphum (42°), (e) Lafoensia pacari (38°), (f) Esenbeckia leiocarpa (31°), (g) Guazuma ulmifolia (−14°), (h) Heliocarpus popayanensis (−54°), and (i) Croton floribundus (−56°). Different letters on the lines indicate significant differences between irrigation volumes in the same month by the Scott–Knott test at 5% probability.
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Figure 10. Stem diameter (mm) of tree seedlings until 120 days after planting in pots as influenced by treatments applied during the nursery phase. (a) Genipa americana (58°), (b) Magnolia ovata (57°), (c) Psidium cattleyanum (55°), (d) Moquiniastrum polymorphum (42°), (e) Lafoensia pacari (38°), (f) Esenbeckia leiocarpa (31°), (g) Guazuma ulmifolia (−14°), (h) Heliocarpus popayanensis (−54°), and (i) Croton floribundus (−56°). Different letters on the lines indicate significant differences between irrigation volumes in the same month by the Scott–Knott test at 5% probability.
Figure 10. Stem diameter (mm) of tree seedlings until 120 days after planting in pots as influenced by treatments applied during the nursery phase. (a) Genipa americana (58°), (b) Magnolia ovata (57°), (c) Psidium cattleyanum (55°), (d) Moquiniastrum polymorphum (42°), (e) Lafoensia pacari (38°), (f) Esenbeckia leiocarpa (31°), (g) Guazuma ulmifolia (−14°), (h) Heliocarpus popayanensis (−54°), and (i) Croton floribundus (−56°). Different letters on the lines indicate significant differences between irrigation volumes in the same month by the Scott–Knott test at 5% probability.
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Figure 11. Irrigation water capture by seedling species with negative mean leaf angles. (a) Leaf angle, leaf area, and spatial distribution of leaves in Guazuma ulmifolia (−14°) and (b) Croton floribundus (−56°) hinder the access of irrigation water to the substrate. (c) Leaf angle, small leaf area, and spatial distribution of leaves in Heliocarpus popayanensis (−54°) facilitate the access of irrigation water to the substrate.
Figure 11. Irrigation water capture by seedling species with negative mean leaf angles. (a) Leaf angle, leaf area, and spatial distribution of leaves in Guazuma ulmifolia (−14°) and (b) Croton floribundus (−56°) hinder the access of irrigation water to the substrate. (c) Leaf angle, small leaf area, and spatial distribution of leaves in Heliocarpus popayanensis (−54°) facilitate the access of irrigation water to the substrate.
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MDPI and ACS Style

da Silva, R.B.G.; Simões, D.; Wendling, I.; do Prado, D.Z.; Sartori, M.M.P.; Bertholdi, A.A.d.S.; da Silva, M.R. Leaf Angle as a Criterion for Optimizing Irrigation in Forest Nurseries: Impacts on Physiological Seedling Quality and Performance after Planting in Pots. Forests 2023, 14, 1042. https://doi.org/10.3390/f14051042

AMA Style

da Silva RBG, Simões D, Wendling I, do Prado DZ, Sartori MMP, Bertholdi AAdS, da Silva MR. Leaf Angle as a Criterion for Optimizing Irrigation in Forest Nurseries: Impacts on Physiological Seedling Quality and Performance after Planting in Pots. Forests. 2023; 14(5):1042. https://doi.org/10.3390/f14051042

Chicago/Turabian Style

da Silva, Richardson Barbosa Gomes, Danilo Simões, Ivar Wendling, Débora Zanoni do Prado, Maria Márcia Pereira Sartori, Angelo Albano da Silva Bertholdi, and Magali Ribeiro da Silva. 2023. "Leaf Angle as a Criterion for Optimizing Irrigation in Forest Nurseries: Impacts on Physiological Seedling Quality and Performance after Planting in Pots" Forests 14, no. 5: 1042. https://doi.org/10.3390/f14051042

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