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Article

Leaf Traits and Water-Use Characteristics of Impatiens hainanensis, a Limestone-Endemic Plant under Different Altitudes in Dry and Foggy Seasons

1
Key Laboratory of Genetics and Germplasm Innovation of Tropical Special Forest Trees and Ornamental Plants, Ministry of Education, Hainan University, Haikou 570228, China
2
College of Forestry, Hainan University, Haikou 570228, China
*
Authors to whom correspondence should be addressed.
Water 2022, 14(2), 139; https://doi.org/10.3390/w14020139
Submission received: 9 December 2021 / Revised: 27 December 2021 / Accepted: 4 January 2022 / Published: 6 January 2022
(This article belongs to the Section Ecohydrology)

Abstract

:
The southwestern mountains of Hainan Island are distributed in the southernmost tropical karst landscape of China, and the unique hydrological structure and frequent solifluction droughts lead to double water stress for local plants. Highly heterogeneous water environments affect the water–use characteristics of plants. Plants develop local adaptative mechanisms in response to changes in the external environment. In this paper, hydrogen–oxygen and carbon stable isotope technology, and physiological index measurements were applied to determine the leaf traits, water–use efficiency, and photosynthetic characteristics of Impatiens hainanensis leaves in dry and foggy seasons, hoping to expound the adaptation mechanism of I. hainanensis leaves to the water dynamics in dry and foggy seasons. In dry and foggy seasons (November 2018 to April 2019), the leaves of I. hainanensis at low and medium altitudes have the following combination of traits: larger leaf dry weights, leaf areas, and specific leaf areas; smaller leaf thicknesses and leaf dry matter contents; and higher chlorophyll contents. In comparison, the leaves of I. hainanensis at high altitudes have the following combination of traits: smaller leaf dry weights, leaf areas, and specific leaf areas; larger leaf thicknesses and leaf dry matter contents; and lower chlorophyll contents. The leaves of I. hainanensis can absorb fog water through their leaves. When the leaves are sprayed with distilled water, the water potential is low, the water potential value gradually increases, and the leaves have a higher rate of water absorption. The leaves of I. hainanensis at low and medium altitudes have the following water–use characteristics: high photosynthesis, high transpiration, and low water–use efficiency. At high altitudes, the Pn of I. hainanensis decreases by 8.43% relative to at low altitudes and by 7.84% relative to at middle altitudes; the Tr decreased by 4.21% relative to at low altitudes and by 3.38% relative to at middle altitude; the WUE increased by 16.61% relative to at low altitudes and increased by 40.79% relative to at middle altitudes. The leaves of I. hainanensis at high altitudes have the following water–use characteristics: low photosynthesis, low transpiration, and high water–use efficiency. I. hainanensis develop different physiological mechanisms of water adaptation by weighing the traits of the leaves and their use of light and water to obtain resources during dry and foggy seasons.

1. Introduction

Changes in climate extremes and precipitation patterns resulting from global climate change have important implications for the growth, development, and distribution of plants [1]. In rock–deserted areas, frequent changes in hydrothermal conditions may lead to a diversification of plant water-use patterns [2]. The ability of plants to coordinate carbon assimilation and water dissipation governs their adaptation to drought conditions [2]. The carbon and water changes in plants are adequate indicators of plant physiological and ecological processes in the vegetation–soil–atmosphere system and information on plant gas exchange in arid environments [3,4]. The ability of plants to synergize carbon assimilation and water dissipation, i.e., water-use efficiency (WUE), is an essential physiological indicator of plant adaptation to habitats [5,6]. Therefore, WUE is a key factor for plant growth in arid rocky deserts, and an essential link in the carbon and water cycle of terrestrial ecosystems [7,8,9]. The leaf is the main site of carbon and water balance in plants, and the traits characteristics of their leaves are closely related to the plant’s access to resources [10]. The δ13C and photosynthetic properties of leaves are also correlated with WUE [11]. The δ13C of leaves can indicate plants’ long–term WUE and water use [12], revealing the coupling between carbon and water changes in plant leaves and habitat [13].
Island karst habitats are characterized by seasonal influences and local spatial heterogeneity. Rainwater run–offs leach limestone mineral nutrients, which results in calcium-rich alkaline soils and the formation of “heterogeneous environmental sieves” such as stone gaps and crevices. Local microhabitats have increased the amount of natural shade intensity and reduced plant water transpiration [14,15]. The “heterogeneous environmental sieves” are relatively more habitat–friendly, and the ecological stress in the karst landscape is weakened. The highly heterogeneous and diverse shallow karst fissure habitats reduce the stress–limiting effects of the karst “heterogeneous environmental sieve” and maintain the relative stability of microhabitat species [16,17], creating a favorable environment for plant survival. The local adaptation processes of endemic plants to hydrothermal changes in tropical karst fissure locations [18], in particular, the ecological response of karst–specific plants to heterogeneous environmental sieves, suggest that karst–specific plants have adapted to living in rocky fissure habitats and to dealing with water stressors. Have karst–specific plants that grow in shallow rocky fissure habitats for long periods of time developed unique adaptation mechanisms to deal with water stressors here?
Hainan Island is located in the southernmost part of China and is the largest tropical island in China [19]. Located at the northern edge of the tropics, Hainan Island is a typical tropical monsoon climate zone with a maximum interval of 47.6 ± 16.1 d between typhoons; dry and wet seasons are obvious. The dry season here is from November to April each year, and the average temperature for the coldest month is 18 °C [20]. The tropical karst landscapes of Hainan are located in the southernmost part of central and western Hainan Island, with a total area of 400 km2 consisting of exposed carbonate rocks [21], exposed bedrock, shallow soils, strong lithification, severe soil erosion, and highly heterogeneous habitats; microenvironmental changes can also occur over a range of altitudes [22,23]. The tropical karst landscape of Hainan Island is characterized by a combination of homogeneous background areas and heterogeneous microhabitats [24]. These seasonal drought and infertile soils are the main stressors to plant growth and development in tropical karst habitats [25,26].
Compared with subtropical karst landscapes, the ‘karst aridity’ and ‘frequently water variability’ of tropical rainforest karsts result in a high abundance and heterogeneity of vegetation, with a series of functional trait combinations that are conducive to reducing transpiration and storing nutrients, different traits adapted to the karst water environment [26,27,28]. Studies have shown that the traits of the leaves adopt different adaptation strategies in response to environmental gradients and that the traits of plant leaves are influenced by altitude-induced hydrothermal changes, with changes in leaf area, fresh weight, dry weight, and specific leaf area with increasing altitude [29]. Frequent hydrothermal changes at the horizontal scale also affect the WUE and δ13C of local plants, with most plant leaves showing increases in δ13C during the dry season, when water conditions are poor, and only a few plants show no change or signs of decreases in δ13C [30,31,32]. In some karst areas, it has been found that, as water availability decreases, WUE increases significantly, as does δ13C [33,34].
Impatiens hainanensis Y.L. Chen is a perennial herb endemic to Hainan Island’s limestone regions and is only distributed in the karst tropical mountain rainforests at altitudes of 190–1300 m, in karst fissures [35] (Figure 1). I. hainanensis communities are dominated by low scrub and sparsely distributed with few species, often forming dense rocky microhabitats and limiting their own regeneration and settlement due to rocky microhabitats [36]. Stone gap microhabitats indirectly affect vegetation growth by influencing soil water and nutrients [37]. I. hainanensis has a well–developed and dense root system that climbs rocks, penetrates fissures, and obtains water replenishment in fissured soils and karst crevices [38]. The combination of water heterogeneity and habitat heterogeneity affects the growth and distribution of I. hainanensis. The leaves of I. hainanensis show morphological plasticity in response to changes in distribution habitat type. We hypothesized that, in addition to soil water and karst fissure water, horizontal precipitation may be an important source of water replenishment for I. hainanensis during the dry season: the plant canopy traps fog water, which drips and percolates into the karst fissure soil and is absorbed by the plant roots and leaves [39,40]. The functional traits of I. hainanensis leaves in response to changes in environmental factors along the altitude gradient can be considered a “water adaptation metamorphosis” under changes in the dominant water factor. Here, we investigate the water-use strategies of I. hainanensis leaves in dry and foggy seasons based on the functional traits of their leaves and on isotope techniques and ask the following questions: (1) What are the traits of I. hainanensis leaves at different altitudes in dry and foggy seasons? (2) What are the changes in the photosynthetic characteristics and WUE of I. hainanensis leaves at different altitudes during dry and foggy seasons? (3) What are the water-use characteristics of I. hainanensis leaves at different altitudes during dry and foggy seasons?

2. Materials and Methods

2.1. Study Area and Locations

Our study area was located in the southwestern mountainous region of Hainan Island (in the southernmost part of mainland China): the Bawangling Emperor Cave of Changjiang County (18°57′–19°11′ N, 109°03′–109°17′ E) (Sample Plot A), altitude 198–257 m; Exianling of Wangxia Township (18°56′–19°03′ N, 109°00′–109°09′ E) (Sample Plot B), altitude 850–1110 m; and Mihouling of Dongfang City (18°90′–19°13′ N, 108°88′–109°11′ E) (Sample Plot C), altitude 422–456 m. They are typical tropical rainforest karst landscapes and have a tropical monsoon climate (Figure 2). As altitude increases, rainfall gradually increases and relative humidity increases (mist and dew are often seen on the mountain). The geology of the study area primarily consists of limestone, with intervals of metamorphic and sedimentary rocks [38]. Soil is mainly black or brown limestone. Soil cover is unevenly distributed, with the bedrock extensively exposed, steep slopes (63% of the slopes at ≥28°), thin soil layers, severe vegetation degradation, and low forest cover [38]. There was continuous outcrop of rocky habitat, including stone faces, caves, ditches, and crevices in each sample plot. The vegetation was mostly tropical evergreen monsoon rainforest, deciduous monsoon rainforest, and hilltop scrub. The understory was rich in dead branches, while shrubs and groundcovers were growing vigorously.

2.2. Indicators and Methods for Determining Leaf Traits

There were three I. hainanensis sample plots at the study site (Sample Plot A: Bawangling of Emperor’s Cave, Sample Plot B: Exianling, and Sample Plot C: Mihouling), and each sample plot was set up with nine repeated samples (5 m × 5 m). We collected mature leaves (no less than nine per plant) that were fully expanded and free from disease and pests each month from 6 November 2018 to 6 April 2019. The leaf indicators measured were leaf dry weight (LDW), leaf fresh weight (LFW), leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf thickness (LT), and relative chlorophyll content (RCC).

2.2.1. Specific Leaf Area Determination

Leaf area was scanned using a CI–203 handheld leaf area meter (CID Bio–Science, Inc., Camas, WA, USA) and specific leaf area was calculated. SLA (cm2/g) = LA/LDW.

2.2.2. Determination of Leaf Dry Matter Content

The fresh weight of each leaf was weighed using an analytical balance (AR2140, accuracy: 0.0001 g, Ohaus International Trade (Shanghai) Co., Ltd., Shanghai, China). The weighed leaves were dried in an oven at 80 °C to a constant weight, and the dry weight of each leaf was weighed on an analytical balance (accuracy: 0.0001 g). LDMC (g/cm2) = LDW/LFW.

2.2.3. Leaf Thickness

The thickness of each point was measured using a vernier caliper (accuracy 0.01 mm), and the average of the 6 points was taken as the thickness of the blade (mm).

2.2.4. Relative Chlorophyll Content Determination

A CCM–200 portable chlorophyll meter (OPTI–Sciences Inc., Hudson, NH, USA) was used to calculate the chlorophyll content from the different absorption rates of the plant leaves at 940 and 660 nm. Three points were evenly selected along one side of the main veins, and the average of the three points was used as the relative chlorophyll content of the leaves (%).

2.3. Isotope Sample Collection and Determination

2.3.1. Sample Collection

There were three I. hainanensis sample plots at the study site (Sample Plot A: Bawangling of Emperor’s Cave, Sample Plot B: Exianling, and Sample Plot C: Mihouling), and each sample plot was set up with nine repeated samples (5 m × 5 m). We collected samples from these sites, three times per month between 6 November 2018 and 6 April 2019. We collected stem bases from three mature I. hainanensis plants from each sample square (three replicates). We collected stem bases from three mature I. hainanensis plants from each sample square (three replicates). We collected leaf samples, with mature plants were selected from each sample plot in the dry season and 9 replicate samples collected from each plant. The leaf samples were taken back to the laboratory, killed at 105 °C for 1 h, and baked at 80 °C for 24 h; the leaves were ground, sieved through an 80 mesh, and stored at room temperature. Fog water was collected in the morning between 07:00 and 11:00 when the fog was thickest using collection tanks in the dry season. The precipitation samples, stem water samples, and fog water collected in the field were quickly packed into sampling bottles, sealed with a sealing film to prevent evaporation, and stored in an incubator at −4 °C to be taken back to the laboratory.

2.3.2. Stable Isotope Measurement

Stem water was extracted using evaporative cooling through a moisture vacuum extraction system (LI–2000). We used a Finnigan Delta V Advantage Isotope Ratio Mass Spectrometer (Thermo Fisher Scientific Inc., Waltham, MA, USA) and Flash 2000 HT elemental analyzer (Thermo Fisher Scientific Inc., Waltham, MA, USA) measurements (±<1‰ for δD, ±<0.2‰ for δ18O, and ±<1‰ for δ13C) at the Flash, Stable Isotope Laboratory, Tsinghua University, to measure all water samples including atmospheric precipitation, the stem water, the fog water, and the leaf samples. Hydrogen isotope ratios can be expressed in terms of the difference in thousands (‰) relative to the Vienna Standard Mean Ocean Water (V–SMOW) [41,42] as follows:
δ = ( R sample / R standard 1 )   ×   1000
Rsample and Rstandard are the D/1H and 18O/16O stable isotope compositions of the sample and V–SMOW.
δ13C = [(RP/Rs − 1)] × 1000
RP is the ratio of heavy hydrogen isotopic abundance of carbon in the leaf sample (13CP/12CP); RS represents the ratio of heavy hydrogen isotopic abundance of international common standard substances (13CS/12CS) [43].

2.4. Water Absorption and Utilization of Leaves

2.4.1. Measurement of Leaf Water Potential, Relative Water Content, and Water Absorption

Measurement of leaf water potential in the wild: the water potential of the leaves was measured every 2 h from 09:00 to 17:00 using the PMS pressure water potential meter (PMS Inc., Las Cruces, NM, USA). Measurement of leaf water potential, relative water content, and water absorption of indoors: the leaves were collected, immersed in distilled water, and brought back to the laboratory. After the leaves had absorbed water to saturation, saturation weight was weighed and water potential was measured using a PMS pressure water potential meter. The leaves were allowed to lose water, and fresh weight and water potential (Ψw) were measured every 1 h until the leaf water potential dropped to −1.2 Mpa. Distilled water was sprayed on the leaves at room temperature to simulate fog water. The leaf Ψw was measured every 1 h, and the leaf absorbed the water until saturation, was weighed at saturation, was dried to a constant weight at 70 °C, and was weighed dry. Relative water content (RWC) = (fresh weight – dry weight)/(saturated weight – dry weight). The RWC–Ψw data were used to establish the RWC–Ψw regression equation, to obtain the RWC of the leaves at different times of spraying and Ψw, and to calculate the fresh weight of the leaves based on their dry weight and saturated weight.

2.4.2. Measurement of Photosynthetic Properties

The photosynthetic physiological parameters were measured on mature leaves in the sunny central part of mature plants in the I. hainanensis sample plots. The gas exchange characteristics of the leaves were measured every 2 h from 09:00 to 17:00 using a LI–6800XT (Li Cor Inc., Lincoln, NE, USA). After the gas exchange measurements, physiological parameters such as photosynthetic rate (Pn, μmoL·m2·s1), transpiration rate (Tr, mmoL·m2·s1), stomatal conductance (GS, moL·m2·s1), and intercellular CO2 concentration (Ci, μmoL·moL1) were obtained. Nine plants from each sample plot of I. hainanensis were used as replicates.

2.5. Data Analyses

2.5.1. Water–Use Efficiency

A quantitative relationship was calculated between WUE, atmospheric CO2 concentration (Ca), and plant intercellular CO2 concentration (Ci) [44]:
WUE = ( Ca Ci ) / 1.6   Δ W
Ca is the atmospheric CO2 concentration, ∆W is the gradient between leaf and air water vapor concentration, and 1.6 is the conversion factor (conversion of stomatal conductivity to water vapor to conductivity to CO2).
The quantitative relationship between stable carbon isotope resolution (Δ13C) and intercellular CO2 concentration (Ci) was calculated:
Δ13C = a + (b − a)/(Ci/Ca)
Δ = (δ13Ca − δ13Cp)/(1+ δ13Cp)
δ13Cp and δ13Ca are the CO2 stable carbon isotope ratios in plants and the atmosphere, respectively. The δ13Ca value is −6.7‰ in the northern hemisphere; a value of 4.4‰ is the diffusive fractionation of CO2 as it passes through stomata, and a b value of 27.0‰ is the fractionation of CO2 during shuttling by Rubisco.
The combination of the two equations gives the plant water-use efficiency, which is calculated as follows:
WUE = Ca [ 1 δ Ca 13 δ Cp 13 a ( b a ) ] / 1.6 Δ W
With an average atmospheric CO2 concentration of 321 μL and a ∆W of 12.0 MPa·Pa1, the plant water-use efficiency is calculated as follows:
WUE = 13.712 + 0.354 δ13C

2.5.2. Statistical Analysis

We used the statistical analysis software SPSS 26.0 for all data analyses. We used ANOVA to assess the leaf traits, water–use characteristics, and photosynthetic properties. Pearson’s test was used for a correlation analysis between leaf traits. Duncan Multiplex comparison was used for leaf traits at different altitudes. We conducted generalized linear model analyses to test the relationship between δD and δ18O of precipitation, plant stem water, and fog water. We used a mean comparison and ANOVA to compare the differences in δD and δ18O between precipitation, plant stem water, and fog water. All statistically significant differences were tested at the 0.05 level.

3. Results

3.1. Leaf Traits of I. hainanensis

3.1.1. Interrelationships between Leaf Traits at Different Altitudes

The coefficients of variation for leaf traits in Sample Plot A and Sample Plot C were ranked as follows: SLA > LDW > LFW > LDMC > LT > LA > RCC, indicating that the specific leaf area was highly variable and that the relative chlorophyll content was not very variable. The coefficients of variation of the leaf traits in Sample Plot B were ranked as follows: SLA > LDMC > LDW > LFW > LA > LT > RCC, indicating that the specific leaf area varied greatly and that the relative chlorophyll content did not vary much (Table 1). The results of the Pearson correlation analysis (Table 2) showed that leaf dry weight was significantly and positively correlated with leaf fresh weight, leaf area, and leaf thickness (p < 0.05); highly significant positive correlation with leaf dry matter content (p < 0.01); and highly significant negative correlation with specific leaf area (p < 0.01), i.e., leaves with larger areas had relatively heavier dry and fresh weights and relatively more leaf dry matter content. Leaf dry weight was highly significantly negatively correlated with specific leaf area (p < 0.01), and leaf fresh weight was significantly negatively correlated with specific leaf area (p < 0.05); both leaf dry weight and leaf fresh weight were significantly positively correlated with leaf thickness (p < 0.05), and leaf dry matter content was significantly positively correlated with leaf thickness (p < 0.05), leaf dry weight, and leaf fresh; and the leaf dry matter content increased with increasing leaf thickness. Specific leaf area was significantly negatively correlated with leaf dry matter content (p < 0.05), and relative chlorophyll content was not significantly correlated with other leaf traits.

3.1.2. Correlation of Leaf Traits with Altitude

The leaf area and leaf thickness of I. hainanensis at different altitudes varied significantly (Table 3). The results of the multiple comparisons showed that the leaf area of the plants in the lower elevation Sample Plot A and the middle elevation Sample Plot C were significantly higher than that in Sample Plot B and that the leaf area decreased with increasing elevation. Leaf thickness was significantly higher in the high–elevation Sample Plot B than in the low–elevation Sample Plot A and in the mid–elevation Sample Plot C. Leaf thickness increased with elevation. The specific leaf area and leaf dry matter content were significantly higher in the high altitude Sample Plot B than in the other altitude samples. The differences in leaf dry weight, leaf fresh weight, and relative chlorophyll content between I. hainanensis leaves at different altitudes was insignificant. Altitude significantly affects the leaf area and leaf thickness of I. hainanensis. At higher altitude sample sites, I. hainanensis increases the ability to retain resources such as water through increases in leaf thickness and decreases in leaf area.

3.2. Dynamics of δD (δ18O) and δ13C

3.2.1. δD(δ18O) Characteristics of Fog Water

A linear regression analysis of fog water δD and δ18O in I. hainanensis showed that the linear correlation between soil water δD and δ18O was highly significant (Figure 3). This indicates that I. hainanensis was able to utilize both atmospheric precipitation and other water sources (e.g., fog water) in the area. During the dry season, fog water δD and plant water δD are closely related (Figure 4), indicating that I. hainanensis takes up and uses fog water. Fog water has a partial water recharge effect on I. hainanensis in the dry season.

3.2.2. δ13C and WUE Characteristics of Leaf

As can be seen from Figure 5, in the dry season, the variation in δ13C values of plant leaves in Sample Plot A ranged from −32.21‰ to −31.12‰, that in Sample Plot B ranged from −30.91‰ to −28.35‰, and that in Sample Plot C ranged from −34.11‰ to −32.61‰. The leaf δ13C values fluctuated with moisture changes in the dry season. The leaf δ13C values in Exianling (Sample Plot B) were significantly higher than those in the Emperor’s Cave (Sample Plot A) and in Mihouling (Sample Plot C). In the dry season, the leaf WUE values in Sample Plot A ranged from 2.31–2.71 mmol CO2·mol1 H2O, that in Sample Plot B ranged from 2.77–3.68 mmol CO2·mol1 H2O, and that in Sample Plot C ranged from 1.64–2.17 mmol CO2·mol1 H2O. The leaf WUE values in Exianling (Sample Plot B) were higher than those in the Emperor’s Cave (Sample Plot A) and in Mihouling (Sample Plot C), with the highest water-use efficiency. The water-use efficiency of plants in the three sample plots were ranked B > A> C.

3.3. Water Absorption and Utilization of Leaf

3.3.1. Diurnal Variation in Leaf Water Potential

In the dry season, the water potential (Ψw) of I. hainanensis leaves varies considerably from −0.67 to −0.18 bar per day. The water potential was higher in the morning and then decreased, reaching a minimum at 13:00 and then gradually rebounding. The differences were not very significant in the evening and early morning but were significant compared with midday. The water potential was ranked as Sample A > Sample C > Sample B (Figure 6).

3.3.2. Changes in Leaf Water Potential, Relative Water Content, and Water Absorption after Spraying

The water absorption of I. hainanensis leaves increased with distilled water spraying time, and Ψw and RWC also gradually increased is shown in Figure 7. After 5 h of spraying, the water absorption of I. hainanensis leaves increased to 0.85 in Sample Plot A, to 1.22 in Sample Plot B, and to 0.92 in Sample Plot C. The relative water content of leaves increased from 70% to 82% in Sample Plot A, from 75% to 87% in Sample Plot B, and from 72% to 84% in Sample Plot C. The relative water content of leaves increased from 70% to 82% in Sample Plot A, from 75% to 87% in Sample Plot B, and from 72% to 84% in Sample Plot C. The relative water content of leaves increased from 72% to 84% in Sample Plot A. The Ψw of the leaves increased from −1.0 Mpa to −0.4 Mpa in Sample Plot A, from −1.0 Mpa to −0.38 Mpa in Sample Plot B, and from −1.0 Mpa to −0.39 Mpa in Sample Plot C. The Ψw of the leaves increased from −1.0 Mpa to −0.39 Mpa in Sample Plot C. The Ψw of the leaves increased from −1.0 Mpa to −0.39 Mpa in Sample Plot B.

3.3.3. Linear Relationship between Leaf Water Potential and Relative Water Content

Based on the regression equations for leaf water potential and relative water content of plants in Bawangling (Sample Plot A), Exianling (Sample Plot B), and Mihouling (Sample Plot C) during dry and foggy seasons (Figure 8), it can be seen that leaf water potential and RWC are positively correlated.

3.3.4. Changes in Photosynthetic Properties of I. hainanensis

During the dry season, the humidity of the I. hainanensis sample plot decreases; evaporation is high; and the daily changes in net photosynthetic rate, transpiration rate, stomatal conductance, and intercellular CO2 concentration show bimodal changes. The photosynthetic “lunch break” phenomenon occurs at 10:00–11:00 am and 15:00 pm: the temperature rises, Tr becomes larger, stomata open, and leaf cell activity Pn rises to a maximum. The Pn of I. hainanensis was significantly higher in the morning than in the afternoon (Figure 9). The magnitudes of Pn, Tr, Gs, and Ci in the three sample plots were ranked A > C > B.

4. Discussion

4.1. Leaf Traits of I. hainanensis under Different Altitudes during Dry and Foggy Seasons

During dry and foggy seasons, plant distribution and structural–functional traits change gradually with temperatures and annual precipitation decrease in the karst areas [45,46]. In karst areas with shallow soils, strong lithification, nutrient–poor soils or parent material, and alternating prolonged water deprivation with short–term intense inputs, plants are frequently exposed to temporary droughts during dry and foggy seasons [47,48]. In this study, the coefficient of variation in leaf area and leaf thickness of I. hainanensis at high altitudes was the highest compared with other leaf trait indicators. The leaf area and leaf thickness of I. hainanensis at high altitudes is more susceptible to environmental influences. In the three I. hainanensis sample plots, the higher altitude populations had lower leaf area and specific leaf area, and higher leaf thickness and leaf dry matter content. Leaf dry matter content and leaf thickness increased with altitude, which is consistent with the findings of Pang et al. [49]. The average leaf areas of I. hainanensis at low and medium altitudes were 16.04 cm2 and 13.34 cm2. The average leaf area of I. hainanensis at high altitudes is 5.33 cm2, which is small compared with the leaf area of I. hainanensis in the other sample plots. The average specific leaf areas were 407.37 cm2/g and 237.42 cm2/g for low and medium altitude leaves and 168.21 cm2/g for high altitude leaves. The lower specific leaf area is more conducive to heat dissipation and water regulation by stomata and reduces energy consumption [50]. As the altitude rises, the degree in drought gradually increases, bare leakage increases, soil water content decreases, and plant habitat become more hostile. The smaller the specific leaf area of I. hainanensis, the greater the water–use efficiency and osmoregulation capacity, and the greater the dry matter content of the leaves, presenting a higher resource–use efficiency and thus more biomass to resist the drought habitat [51,52]. The higher leaf area, leaf thickness, and specific leaf area and the relatively low leaf dry matter content of I. hainanensis from low and mid altitude populations may result from competition for more light and water in the tropical rainforest, where I. hainanensis increases leaf area carbon investment by increasing leaf area and by reducing leaf thickness carbon build–up. Studies have shown that some lianas in karst areas have smaller leaf thickness, and larger leaf area and leaf dry matter content, which are similar to the leaf traits of I. hainanensis at low and medium altitudes but differs from those of I. hainanensis at higher altitudes because, compared with karst trees and herbs, some lianas tend to increase their leaf area and because some lianas tend to increase their leaf area and chlorophyll content compared with karst trees and herbs, expanding the range of light absorption and maintaining better photosynthetic capacity [53]. At high altitudes, in addition to precipitation and soil water, fog water supplements plant growth [40]. Although light and water resources are relatively more abundant at higher altitudes, the rate of water loss is accelerated. The increased thickness of I. hainanensis leaves can effectively enhance the plant’s resource retention capacity and reduce the water and energy consumption in the plant. This is consistent with Wang et al. [10] and Ou et al. [53], who concluded that plant leaf dry matter content, leaf area, and leaf thickness adapt to changes in light resources and water with local microhabitat changes.

4.2. Changes in Water-Use Efficiency of I. hainanensis during Dry and Foggy Seasons

In the dry season, the trend in the photosynthetic characteristics of I. hainanensis under different altitude gradients is consistent, with the highest net photosynthetic rate (Pn) in Sample Plot A at low altitude, with a daily variation of 3.413 to −5.111 μmoL·m2·s1, followed by Sample Plots C and B, with daily variations of 3.391 to −5.282 μmoL·m2·s1 and 3.125 to −5.218 μmoL·m2·s1. The daily variation in the net photosynthetic rate of I. hainanensis was bimodal during the dry and foggy seasons. The first peak occurred between 9:00 and 11:00 am and was higher than the second peak. Studies have shown that the earlier the peak occurs, the more peaks there are, indicating a higher sensitivity of the plant to its environment [54,55]. As temperature increases, the intrinsic physiological systems begin to activate and photosynthesis gradually increases, with the formation of the first peak indicating that the plant can respond quickly to unfavorable conditions, accelerating water use and photosynthesis within a short period of time [56]. As temperature and light increase, transpiration intensifies and stomatal conductance is reduced or even closed to avoid damage to the photosynthetic system caused by excessive water loss, resulting in a decrease in the photosynthetic rate and a photosynthetic ‘siesta’. The variations in transpiration rate and net photosynthetic rate of I. hainanensis are the same, with a bimodal pattern.
The low annual precipitation in the dry and foggy seasons, combined with the low availability of soil and water resources in karst areas and the abundance of bedrock karst pipes, makes it easy for water to be lost through underground pipes, making plants more susceptible to drought stress than in the wet season [57,58,59]. To prevent excessive water loss, I. hainanensis gradually reduce their leaf area or stomatal density from low to high altitudes to reduce transpiration, resulting in less CO2 entering the leaves through the stomata, which leads to the highest δ13C values being between −34.11‰ and −32.61‰ for I. hainanensis in Sample Plot B. Studies by Ehleringer et al. [60,61] showed that plants in arid desert areas, with daily temperature changes, gradually intensify high-temperature drought stress, with some desert plants subsequently closing their stomata to reduce water consumption, reducing transpiration and increasing intercellular CO2 concentrations [62]. This is similar to the drought stress by I. hainanensis at high altitudes in karst areas. I. hainanensis constantly adjusts their photosynthetic and transpiration rates through bimodal changes under the dual stress of light and habitat temperature. When the ambient temperature rises slowly, I. hainanensis lowers their own temperature through transpiration, and when the high temperature comes, they lower their stomatal conductance to prevent themselves from becoming dehydrated due to excessive transpiration. The photosynthetic rate of I. hainanensis also dropped to a minimum during this time, and the plant is completely in a defensive state. When the high temperature gradually recedes, the stomatal conductance rises again slowly. Then, transpiration is used to regulate its temperature, thus ensuring that the plant does not die of water shortage in a dry environment and ensuring that water to replenish the transpiration after the highest temperature has passed, thus reducing the damage to itself from the high temperature and drought.
In this study, the mean transpiration rate of I. hainanensis in the high altitude sample plot ranged from 2.022 to 1.515 mmoL·m2·s1 and was lower than the other two plots. The daily trend of stomatal conductance was similar to that of the photosynthetic rate and the transpiration rate. The transpiration of plant leaves influence stomatal conductance, and its changes have adjusted feedback on the photosynthetic rate and the transpiration rate, which affects plant WUE [63,64]. Related studies have shown that WUE has a positive correlation with the δ13C of leaves, and WUE positively correlated with precipitation [65]. As precipitation decreases in the dry and foggy seasons in karst areas, the lower the plant water availability, the higher the δ13C values and WUE [66]. From low to high altitudes in karst areas, soil cover and thickness decrease, rock bareness and light increase, and topographic wetness index gradually decreases [67]. During dry and foggy seasons, I. hainanensis needs more extended periods of drought to continuously improve WUE by increasing its photosynthetic rate, allowing water–use patterns to become more conservative, thus maintaining a relatively strong water availability to avoid drought stress and adapting to local microhabitats.

4.3. Utilization of Fog Water by I. hainanensis

The dry season of I. hainanensis sample plots is foggy, and fog water can block some light to avoid photoinhibition from strong light and low night temperatures, to increase environmental humidity, and to reduce plant transpiration water loss. Fog water is a major water recharge pathway in arid regions and can meet the basic growth needs of plants under drought stress [68]. Plants can cope with the dry season when water is scarce through the uptake of fog water by the leaves and their own outstanding water retention capacity and can maintain normal functioning of the photosynthetic system through the uptake of fog water [69]. In the dry season, due to the influence of fog water, I. hainanensis uses atmospheric precipitation, soil water, and surface karst water in addition to fog water in part to increase water–use efficiency. In the dry season, when precipitation is low, the water potential Ψw of I. hainanensis leaves varies. As the temperature increases, the transpiration of I. hainanensis leaves is strong, the plant water demand increases, and the plant water potential changes from high to low. The photosynthetic lunch break occurs at around 13:00 pm, when the leaves are under local water stress and water content is reduced. At this time, the water potential of I. hainanensis also drops to the lowest during the day, with low photosynthesis, low transpiration, low water potential, and high water–use efficiency. Indoor experimental studies showed that, after 5 h of distillation spraying, the plant leaves started to absorb water. The leaf Ψw rose from −1.0 Mpa to about −0.4 Mpa, indicating that I. hainanensis can absorb fog water and can recover water quickly. Studies have shown that, compared with non–fog plants, fog plants can make better use of the physiological properties of leaves to increase light energy interception, to improve carbon accumulation, and to enhance the ability of plants to absorb fog water and nutrients [70].

5. Conclusions

In this study, the traits, water–use efficiency, and photosynthetic characteristics of I. hainanensis leaves were analyzed using stable isotope tracing techniques combined with statistical analysis and physiological index measurements. In dry and foggy seasons (November 2018 to April 2019), the leaves of I. hainanensis at low and medium altitudes have the following combination of traits: larger leaf dry weight, leaf area, and specific leaf area; smaller leaf thickness and leaf dry matter content; and higher chlorophyll content. In comparison, the leaves of I. hainanensis at high altitudes have the following combination of traits: smaller leaf dry weight, leaf area, and specific leaf area; larger leaf thickness and leaf dry matter content; and lower chlorophyll content. With the change in water availability at different altitudes during dry and foggy seasons, the leaves of I. hainanensis at low and medium altitudes have the following water–use characteristics: of high photosynthesis, high transpiration, and low–water use efficiency. In contrast, the leaves of I. hainanensis at high altitudes have the following water–use characteristics of low photosynthesis, low transpiration, and high water–use efficiency. The foliage of I. hainanensis absorbs and uses fog water in the dry season. The partial water replenishment effect of fog water can better maintain the water balance in I. hainanensis, which is one of the important sources of water utilization for I. hainanensis to adapt to dry season water deficit in karst areas. In order to adapt to the ‘karst drought’ and ‘frequently changing water environment’ in the karst region, I. hainanensis develops different physiological mechanisms of water adaptation by weighing the traits of their leaves and by adjusting their use of light and water to obtain resources during dry and foggy seasons.

Author Contributions

Conceptualization, W.H. and X.S.; methodology, W.H. and X.S.; software, W.H.; validation, M.R. and Y.D.; formal analysis, W.H. and C.Z.; investigation, W.H. and C.Z.; resources, W.H. and X.S.; data curation, W.H. and C.Z.; writing—original draft preparation, W.H. and Y.Z.; writing—review and editing, X.S. and Y.D.; visualization, Y.Z.; supervision, M.R.; project administration, W.H. and X.S.; funding acquisition, X.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was jointly supported by (1) the Key R&D Project of Hainan Province (Grant No. ZDYF2020099); (2) the National Natural Science Foundation of China (Grant No. 31560229); and (3) Hainan University Research Project (Grant No. KYQD (ZR) 20055).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

We thank Meng Xinya, from the college of Forestry, Hainan University, for her valuable comments on the writing of this paper. We also thank Zhao Moqiang, a ranger at the Bawangling National Nature Reserve, for his assistance in the field. We also thank Henry Camarillo at Yale University for his assistance with English language and grammatical editing.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Different I. hainanensis sample plots in a dry and foggy seasons: (A) the Bawangling of Emperor Cave, (B) Exianling, and (C) Mihouling.
Figure 1. Different I. hainanensis sample plots in a dry and foggy seasons: (A) the Bawangling of Emperor Cave, (B) Exianling, and (C) Mihouling.
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Figure 2. The location for our study site of I. hainanensis on Hainan Island. (A, B, and C are the sampling plots for different I. hainanensis populations. Each plot has nine repeated samples. Sample Plot A: Bawangling of Emperor Cave; Sample Plot B: Exianling; and Sample Plot C: Mihouling).
Figure 2. The location for our study site of I. hainanensis on Hainan Island. (A, B, and C are the sampling plots for different I. hainanensis populations. Each plot has nine repeated samples. Sample Plot A: Bawangling of Emperor Cave; Sample Plot B: Exianling; and Sample Plot C: Mihouling).
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Figure 3. The correlation between δD and δ18O of plant stem water and fog water (LMWL: the local meteoric water line).
Figure 3. The correlation between δD and δ18O of plant stem water and fog water (LMWL: the local meteoric water line).
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Figure 4. Changes in δD values of fog water, precipitation, and stem water with dry season precipitation in the three sample plots. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
Figure 4. Changes in δD values of fog water, precipitation, and stem water with dry season precipitation in the three sample plots. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
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Figure 5. Changes in the δ13C values and WUE of I. hainanensis leaf during the dry and foggy seasons in the three sample plots. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
Figure 5. Changes in the δ13C values and WUE of I. hainanensis leaf during the dry and foggy seasons in the three sample plots. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
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Figure 6. Diurnal variation in leaf water potential of I. hainanensis leaf in the three sample plots during the dry and foggy seasons. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons, with the dry and foggy seasons being from November 2018 to April 2019).
Figure 6. Diurnal variation in leaf water potential of I. hainanensis leaf in the three sample plots during the dry and foggy seasons. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons, with the dry and foggy seasons being from November 2018 to April 2019).
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Figure 7. Leaf water potential (Ψw), leaf relative water content (RWC), and water absorbed by the leaves after sprayed with distilled water. (a) Leaf water potential; (b) leaf relative water content; and (c) leaf water absorption. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
Figure 7. Leaf water potential (Ψw), leaf relative water content (RWC), and water absorbed by the leaves after sprayed with distilled water. (a) Leaf water potential; (b) leaf relative water content; and (c) leaf water absorption. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
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Figure 8. The regression equation between leaf water potential (Ψw) and leaf relative water content (RWC).
Figure 8. The regression equation between leaf water potential (Ψw) and leaf relative water content (RWC).
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Figure 9. Diurnal variation in photosynthetic properties of three I. hainanensis sample plots. (a) Dynamics of net photosynthetic rate; (b) dynamics of transpiration rate; (c) dynamics of stomatic conductance; and (d) dynamics of intercellular CO2 concentration. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
Figure 9. Diurnal variation in photosynthetic properties of three I. hainanensis sample plots. (a) Dynamics of net photosynthetic rate; (b) dynamics of transpiration rate; (c) dynamics of stomatic conductance; and (d) dynamics of intercellular CO2 concentration. (A) The Emperor Cave of Bawangling in the dry and foggy seasons; (B) Exianling in the dry and foggy seasons; and (C) Mihouling in the dry and foggy seasons.
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Table 1. Parameters of the leaf traits of I. hainanensis.
Table 1. Parameters of the leaf traits of I. hainanensis.
Sample PlotIndexMaximumMinimumMeanCoefficient Variation
A 1LDW(g)0.130.010.09 ± 0.010.50
LFW (g)0.810.020.20 ± 0.090.45
LA (cm2)22.2112.1116.04 ± 2.170.14
SLA (cm2/g)602.21389.67407.37 ± 117.930.79
LDMC (g/cm2)0.120.120.18 ± 0.030.36
LT (mm)0.120.060.09 ± 0.020.22
RCC (%)46.1335.5841.98 ± 2.790.04
B 2LDW (g)0.030.0010.02 ± 0.010.59
LFW (g)0.440.080.38 ± 0.100.51
LA (cm2)7.112.665.33 ± 1.400.81
SLA (cm2/g)252.8189.56168.21 ± 81.640.66
LDMC (g/cm2)0.610.120.09 ± 0.070.64
LT (mm)0.220.110.17 ± 0.040.23
RCC (%)38.6333.2335.88 ± 1.980.07
C 3LDW (g)0.050.0050.03 ± 0.010.52
LFW (g)0.680.060.56 ± 0.200.35
LA (cm2)16.1211.0613.34 ± 1.930.15
SLA (cm2/g)493.55156.33237.42 ± 171.690.55
LDMC (g/cm2)0.320.080.12 ± 0.150.20
LT (mm)0.130.080.10 ± 0.020.17
RCC (%)39.2135.5837.94 ± 1.630.06
1 Sample Plot A: Bawangling; 2 Sample Plot B: Exianling; and 3 Sample Plot C: Mihouling.
Table 2. Correlation analysis between the leaf traits of I. hainanensis.
Table 2. Correlation analysis between the leaf traits of I. hainanensis.
IndexLDWLFWLASLALDMCLTRCC
LDW1.000.24 *0.48 *−0.51 **0.61 **0.48 *0.41
LFW 1.000.83 **−0.79 *−0.130.83 *0.67
LA 1.000.76−0.020.470.56
SLA 1.00−0.88 *−0.760.43
LDMC 1.000.46 *−0.41
LT 1.00−0.56
RCC 1.00
* represents a significant difference (p < 0.05), ** represents an extremely significant difference (p < 0.01).
Table 3. Comparison of the leaf traits of I. hainanensis at different altitudes.
Table 3. Comparison of the leaf traits of I. hainanensis at different altitudes.
IndexA 1B 2C 3
LDW0.09 ± 0.010.02 ± 0.010.03 ± 0.01
LFW0.20 ± 0.090.38 ± 0.100.56 ± 0.20
LA *16.04 ± 2.17 a5.33 ± 1.40 b13.34 ± 1.93 a,b
SLA407.37 ± 117.93 b168.21 ± 81.64 a237.42 ± 171.69 a,b
LDMC0.18 ± 0.03 b0.09 ± 0.07 a0.12 ± 0.15 a,b
LT *0.09 ± 0.02 b0.17 ± 0.04 a0.10 ± 0.02 a,b
RCC41.98 ± 2.7935.88 ± 1.9837.94 ± 1.63
1 Sample Plot A: Bawangling; 2 Sample Plot B: Exianling; and 3 Sample Plot C: Mihouling. * represents a significant difference (p < 0.05). Different a, b letters in the same row represent significant differences (p < 0.05).
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Huang, W.; Zhong, Y.; Zhang, C.; Ren, M.; Du, Y.; Song, X. Leaf Traits and Water-Use Characteristics of Impatiens hainanensis, a Limestone-Endemic Plant under Different Altitudes in Dry and Foggy Seasons. Water 2022, 14, 139. https://doi.org/10.3390/w14020139

AMA Style

Huang W, Zhong Y, Zhang C, Ren M, Du Y, Song X. Leaf Traits and Water-Use Characteristics of Impatiens hainanensis, a Limestone-Endemic Plant under Different Altitudes in Dry and Foggy Seasons. Water. 2022; 14(2):139. https://doi.org/10.3390/w14020139

Chicago/Turabian Style

Huang, Weixia, Yunfang Zhong, Cuili Zhang, Mingxun Ren, Yanjun Du, and Xiqiang Song. 2022. "Leaf Traits and Water-Use Characteristics of Impatiens hainanensis, a Limestone-Endemic Plant under Different Altitudes in Dry and Foggy Seasons" Water 14, no. 2: 139. https://doi.org/10.3390/w14020139

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