A healthy stock of Egeria densa was collected from the Moto-Arakawa River in southern Saitama, Japan. The collected plants were cleaned with water to remove debris, and the attached algae were carefully separated by tweezers. Then, the plants were cultured in several glass tanks under laboratory conditions (25 ± 2°C, 12/12 h. photoperiod, PAR intensity 100–150 μmol m^–2 s^–1 using fluorescent lighting) for several months. Commercial sand (D₅₀ < 0.2 mm) was used as a substrate, and a 5% Hoagland solution was provided as the nutrient media. Algae-free stocks were selected for the experiments.

The experiments were conducted by growing E. densa cuttings (7 cm long) in 500-mL narrow glass beakers (13.6 cm height × 7.5 cm outside diameter) without a substrate. Each beaker was wrapped with a reflective sheet so every part of plant tissue was homogeneously exposed to the same intensity of light. Two cuttings were firmly attached to a sponge and fixed to the bottom of each beaker. A Hoagland solution (5%) was provided as the nutrient source. Three light intensities (30, 100, and 200 μmol m^–2 s^–1 PAR intensity) and six concentrations of Fe (0, 0.5, 3, 5, 7, and 10 mg L^–1) were chosen in order for the experiment to range from natural to extreme conditions. The light was provided by LED straight lights (Model LT-NLD85L-HN; OHM Electric Inc., Japan) with a 12/12 h photoperiod. The Fe concentration in the media was adjusted by adding the required FeCl₃ amount to the tank. The control condition was maintained by keeping the plants in a 5% Hoagland solution (0.13 mg L^–1 Fe) without any further treatment. Stress assays were performed after three or seven days of exposure.

Several sets of additional conditions were added to obtain the different patterns of solar radiation.

With 5% Hoagland media at 25 ± 2 or 20 ± 2°C, E. densa was grown in 30 × 18 × 20 cm reflective sheet-wrapped glass tanks under four PAR densities of 50, 100, 200, and 300 μmol m^–2 s^–1. In this set of experiments, analyses of the samples were conducted every 5 days for 30 days in order to observe the transition from the start of the experiment.

In another set of experiments, the E. densa-grown tanks were located outdoors and exposed to solar radiation for three consecutive clear days. Three tanks were prepared for each of either 20 ± 2 or 30 ± 2°C water temperature for the replicates. On the third day, every 3 h., from 6 am (just after sunrise) to 6 pm (slightly before sunset), samples were taken from the three tanks of each temperature and were subjected to analyses. The solar radiation intensity was measured at each sampling time.

Field sampling of E. densa was conducted in western Japan’s Saba River, midstream. Sampling was conducted on clear days with less than 20% cloud cover in August 2018. Plant conditions at river reaches were surveyed beforehand. Five to ten representative sites of healthy mono species communities of E. densa were selected from nearly stagnant water (less than 5 cm s^–1 mean velocity) upstream of weirs.

Light intensity was measured from the surface to the bottom of the river at 10cm intervals.

Then, the canopy top shoots were carefully sampled, tightly sealed in plastic bags, and stocked in a frozen storage box with dry ice until they were brought to the laboratory for chemical analysis (H₂O₂, Chl-a, Chl-b, and CAR). The comparison with non-frozen samples indicated that the freezing process did not have any effect on the chemical composition. The water depth of the sites ranged from 0.25 to 1.0 m. The water quality parameters were within the common range for the area: temperature, 20–25°C; pH, 6.8–7.0; dissolved oxygen, 9.0 mg L⁻¹; salinity, 0 ppt; turbidity, 0–35 NTU; and electrical conductivity, 5–11 ms m^–1.

Plant lengths were measured using a millimeter scale at 5–7-day intervals. The SGR was calculated as the difference in the shoot length between two observations. The SGR was obtained by dividing the length by the duration and was expressed in cm day^–1. At the end of the experiment, the plants were oven-dried at 70°C for 72 h. The dry weight (DW) of the shoots was measured to confirm the reliability of the shoot length as a reference parameter of the growth rate. The weight length⁻¹ ratio was 4.0 ± 1.0 mg DW cm^–1, regardless of conditions, except for the dying samples; thus, SGR values were used as the reference growth rate (Ellawala et al., 2011).

The Chl-a, Chl-b, and total CAR contents were spectrophotometrically (UV Mini 1210; Shimadzu, Japan) determined by extracting pigments of N, N-dimethylformamide after keeping dark for 24 h. The results were expressed in fresh weight (FW) (Porra et al., 1989). The chlorophyll fluorescence parameters were measured by fluorescence imaging (FC 1000-H; Photon Systems Instruments, Czech Republic) with auto image segmentation. Initially, the plants were dark-adapted for 20 min, and the maximum quantum efficiency of PSII (F_v F_m^–1) was obtained.

Apart from IAA, the stress assay compounds H₂O₂, CAT, APX, and POD were extracted by grinding the freeze-dried (with liquid nitrogen) fresh plant sample (∼500 mg) with an ice-cold, pH 6.0, 50 mM phosphate buffer. Polyvinylpyrrolidone (PVP) was added to the extraction to mask the effect of phenolic compounds in the plant materials. The sample extraction for endogenous IAA was performed by following a similar procedure, but distilled water was used as the extraction media. Then, the extractions were centrifuged at 5,000 × g and 4°C for 15 min, and the supernatant was separated and incubated at −80°C for further analysis. In each treatment, the extractions were performed in triplicate. All the results were expressed in FW.

The H₂O₂ contents were determined colorimetrically following the TiSO₄ method (Satterfield and Bonnell, 1955), with modifications. The reaction mixture contained 750 μL of enzyme extract and 2.5 mL of 1% TiSO₄ in 20% H₂SO₄ (v/v), which was centrifuged at 5,000 × g and 20°C for 15 min. The optical absorption of the developed yellow color was measured spectrophotometrically at a wavelength of 410 nm. The H₂O₂ concentrations in the samples were determined using the prepared standard curve for known concentration series. The H₂O₂ contents were expressed in μmol g^–1 FW.

The absorption at 410 nm includes the effect of other soluble compounds (Cheeseman, 2006; Queval et al., 2008). Thus, the H₂O₂ concentration was calculated from the slope of the standard curve obtained from the known H₂O₂ concentration, which was offset, derived by the intercept absorption rate with zero H₂O₂ concentration samples (Cheeseman, 2006). The results were compared with those of the e-FOX method (Queval et al., 2008), and a suitable correlation (R² = 0.98) was obtained. The results were presented as μmol g^–1 FW.

The CAT activity was measured as follows: 100 μL of 10 mM H₂O₂ and 2.0 mL of 100 mM potassium phosphate buffer (PH 7.0) were added to the cuvette before 500 μL of enzyme extract was added to initiate the reaction. The optical absorbance reduction at 240 nm was recorded every 10 s for 3 min. Finally, the CAT activity was obtained using an extinction coefficient of 40 mM^–1 cm^–1 (Aebi, 1984). The APX activity was determined as follows: the reaction mixture contained 100 μL of enzyme extract, 200 μL of 0.5 mM ascorbic acid in 50 mM potassium phosphate buffer (PH 7.0), and 2 mL of 50 mM potassium phosphate buffer (PH 7.0). The reaction was initiated by adding 60 μL of 1 mM H₂O₂. The decrease in absorbance at 290 nm was recorded every 10 s. The APX activity was calculated using an extinction coefficient of 2.8 mM^–1 cm^–1 (Nakano and Asada, 1981). The POD activity was spectrophotometrically measured based on the oxidation of guaiacol with the presence of H₂O₂. The reaction mixture contained 3.0 mL of pH 6.5 potassium phosphate buffer, 40 μL of 30 mM H₂O₂, and 50 μL of 0.2 M guaiacol. The reaction was initiated by the addition of 100 μL of crude enzyme extract, and the increase in absorbance at 420 nm was recorded every 10 s for 3 min. Then, the absorbance change rate and POD activity were calculated using an extinction coefficient of 26.6 mM^–1 cm^–1 (Goel et al., 2003).

The concentration of endogenous IAA was also determined using a prepared standard curve for known concentration series. The reaction mixture contained an aliquot of enzyme extract (1.00 mL) and 2.00 mL of modified Salkowski’s reagent (1.00 mL of 0.5 M FeCl₃ in 50 mL of 35% perchloric acid) (Gordon and Weber, 1951). The resultant color intensity was measured as absorbance after a 1 h incubation period at 25°C at a wavelength of 530 nm, and the results were presented as μg g^–1 FW.

Chlorophyll fluorescence was measured using a chlorophyll fluorescence imaging technique (FC 1000-H; Photon Systems Instruments, Czech Republic) with auto image segmentation. The Fv Fm^–1 value became highest 20–30 min. after darkening (20 min. is sufficient; Hubbart et al., 2012). Thus, plant segments were dark-adapted for 20 min. before measurement. The maximum quantum efficiency of PSII photochemistry (Fv Fm^–1) was calculated using the equation Fv Fm^–1 = (Fm - Fo) Fm^–1, where Fv, Fm, and Fo are the variable, maximum, and minimum fluorescence in the dark-adapted state, respectively.

The initial and final lengths of apical tips were measured using a ruler. The relative SGR was calculated with the formula SGR = (FL - IL) days^–1, where FL is the final length and IL is the initial length.

The collected data were tested for normality with the Shapiro–Wilk test before the statistical analyses were performed. All results were presented as the mean ± SD of three replicates. The data were subjected to a one-way analysis of variance (ANOVA) with Tukey’s post hoc test for mean separation. The t-test was performed where necessary. Bivariate analysis was used and followed by Pearson’s correlation method to evaluate the relationship between parameters. Statistical analyses were performed with IBM SPSS V25.

The H₂O₂ concentration variation from the beginning of the experiment to 30 days after its commencement shown in Figures 9, 10 with different light intensities. Regardless of temperature, the H₂O₂ concentration was higher with low PAR for 50–200 μmol m^–2s^–1 of PAR (Table 3). Although the H₂O₂ concentration rose after the experiments began, it declined afterward until the 15th day with 50–100 μmol m^–2s^–1 of PAR and then became stable; there was no significant correlation with time (p > 0.7 for 50–100 μmol m^–2s^–1 of PAR). However, the H₂O₂ concentration continued to decline slightly with 200 μmol m^–2s^–1, and the H₂O₂ concentration for 15–30 days had a significant negative correlation with PAR in 50–200 μmol m^–2 s^–1 [Table 3; empirically given by H₂O₂ (μmol g^–1FW) = 0.025*PAR (μmol m^–2s^–1) + 14.9 for 20°C, and H₂O₂ (μmol g^–1FW) = 0.025*PAR (μmol m^–2s^–1) + 11.1 for 25°C].

In contrast, with 300 μmol m^–2s^–1, the H₂O₂ concentration tended to increase after 10 days until reaching 17 μmol g^–1FW then, it significantly declined (Table 4).

The pigment concentration steadily declined after the beginning of the experiment, with 300 μmol m^–2s^–1 of PAR Shown in Table 4. However, with other PAR intensities, the pigment concentration did not indicate significant change. As the days progressed from 1 to 30, increasing PAR affected the pigment concentration, which in turn, gradually decreased the Chl-a, Chl-b, and CAR levels.

The diurnal variation is shown in Figure 10. Following the variation of PAR, the H₂O₂ concentration and Chlorophyll concentrations varied, increasing in the morning and decreasing in the afternoon. The H₂O₂ concentration varied in a single day at different temperatures. A similar trend is also observed in the Chlorophyll concentrations. However, compared with the symmetrical change in Chlorophyll, the H₂O₂ concentration was higher in the afternoon, compared with the morning changes (Figure 11 and Table 4).

The activities of CAT and POD are also shown in Figure 11. POD showed high fluctuation day time experiment compared with CAT. Although the POD activity followed the PAR and H₂O₂ variations, the CAT activity delayed approximately 3 h of the variational patterns of the PAR and H₂O₂ concentrations because CAT got the optimal concentration of H₂O₂ to react and give a maximum yield (Scandalios et al., 1997).

In the natural environment, an E. densa colony can be formed in lower light intensity, having a low level of H₂O₂ concentration within a few days. The threshold value for E. densa is 16 μmol g⁻¹FW in the daytime (Asaeda et al., 2020), which is observed in high solar radiation and indicates plant tissue damage due to oxidative stress. It was observed that E. densa prefers a light intensity < 200 μmol m^–2 s^–1. When the light intensity is over 200 μmol m^–2 s^–1, plant tissues tend to show signs of H₂O₂ accumulation. High solar radiation disrupts plant metabolism, creating hypoxic conditions. As a result, E. densa plants deteriorate (Asaeda et al., 2020).

In the laboratory studies, it was confirmed that E. densa has a preferred PAR intensity ranging from 30 to 200 μmol m^–2 s^–1. This indicates the light tolerance of E. densa and its preferred environmental conditions.

The H₂O₂ concentration slightly declined and then stabilized when exposed to less than 200 μmol m^–2s^–1 of PAR intensity. However, with 300 μmol m^–2s^–1, H₂O₂ gradually increased to ∼14 μmolg^–1FW of H₂O₂ concentration and then suddenly declined to the lower level. On the other hand, the Chl-a concentration steadily declined with 200 μmol m^–2s^–1 of PAR after the experiment began, although there was almost no effect with lower light intensity. Therefore, slightly less than 200 μmol m^–2s^–1 of PAR seems to be the optimal light intensity for this species.

In diurnal changes of solar radiation, H₂O₂ is higher in the afternoon compared with the morning for the same light intensity. Elevated detoxifying ROS activity is one of the prime strategies plants often possess in response to abiotic stress. Though the POD antioxidant activity nearly follows the variation of H₂O₂, the CAT and APX activities are delayed nearly 3 h (Tables 5, 6). The delay of scavenging activity seems to allow the high H₂O₂ in the afternoon.

E. densa also exhibited a highly negative responsive to Fe exposure. Fe is an essential nutrient for plants and is the major metal involved in electron transfer chains, both accepting and donating electrons of photosynthesis and respiration, respectively (Michalak, 2006). However, Fe is toxic when it accumulates to high levels (Michalak, 2006). An excess amount of Fe in a plant leads to an increased formation of ROS (Hell and Stephan, 2003). The antioxidation process, mainly prominent in the tolerant genotype, is achieved by controlling antioxidant enzymes (de Pinto and de Gara, 2004; Halliwell, 2006; Kumar et al., 2014). At higher concentrations, Fe can replace essential metals in pigments and enzymes, disrupting their function; high iron concentrations also reduce the activities of CAT, APX, and other antioxidants (Bielawski and Joy, 1986). In addition to the enzymatic defense, certain amino acids and sulfur metabolites also possess antioxidant properties that reduce ROS damage in Fe-toxic plants, which may reduce the antioxidant enzyme activity (Freeman et al., 2004; Kumar et al., 2014).

In the present study, the Fe toxicity is clearly exhibited. With an increasing Fe concentration in the substrate, the CAT and APX antioxidant levels decreased, which led to an increase in H₂O₂ accumulation in the plant tissues. On the other hand, the increased POD activity was proportionate to H₂O₂ accumulation, suggesting the low-Fe independent nature of POD. CAT protects cell walls from the destruction caused by H₂O₂ production due to iron stress. CAT also plays an important role in the co-degradation of H₂O₂ in association with POD (Khan et al., 2018; Figure 8). Due to the inhibiting effect of excess ROS production and damage caused by a massive concentration of free Fe ions, significant decreasing results were observed in CAT, POD, and APX (Khan et al., 2018).

The influence of high Fe content on plants is enhanced with increased light intensity. The plants survived a 10 mg L^–1 Fe exposure under 30 and 100 μmol m^–2 s^–1 PAR intensities, but deteriorated under a 200 μmol m^–2 s^–1 PAR intensity, confirming the strong influence of light intensity on the condition of plants.

There is an enhanced correlation between H₂O₂ and Fe when controlling the PAR intensity effect, and there are significantly enhanced correlation between H₂O₂ and PAR when controlling the Fe effect. This suggests that the accumulation of H₂O₂ is caused by both Fe content and high light intensity, independently of the other stressor, in the present experimental range.

The highest accumulation of H₂O₂ in the tissues under Fe toxicity and high PAR exposure might exceed the tolerance level—although it is likely species-specific and causes extensive damage to cells (Cheeseman, 2007; Quan et al., 2008; Asaeda et al., 2021).

Many studies have been conducted on the inhibition effect of strong light intensity on photosynthesis (Öquist et al., 1992; Madsen and Sandjensen, 1994; Hanelt, 1998, 1996; Morrissey and Guerinot, 2009). Photoinhibition leads to a decrease in photosynthetic pigments (Chl-a and Chl-b), which is shown in the present results. The presence of H₂O₂ in plant tissues is negatively correlated with photosynthetic pigments. However, regardless of the stress source, the Chl-a concentration declines under lower stress intensities than with H₂O₂ in the plant tissues. Increasing H₂O₂ can lead to Chl-a and Chl-b declines after an 8-hr elevation of Arabidopsis thaliana (Rao et al., 1997). The optimum light-harvesting antenna for plants is a Chl a and b ratio of 5 (Wu et al., 2020). However, there was not clear difference in the ratio in the present experiment.

In the present study, the F_v F_m^–1, which explains the photosystem’s efficiency, proportionately decreased with H₂O₂ accumulation rather than Chl-a concentration.

Reduced photosynthesis efficiency negatively influences the prosperity and vigor of plants. This was reflected in the reduced SGR and IAA concentration, which regulated the shoot elongation (Yang et al., 1993; Zhou et al., 2006).

Chlorophyll fluorescence (F_v F_m^–1) indicates the efficiency of the photosynthesis rate at PSII, which is highly related to the environmental stress exerted on the plant body. Thus, it is often used to identify the condition of plants. The H₂O₂ concentration had a striking negative correlation with the F_v F_m^–1, regardless of stressor type, in the present study. The exception is the presence of a very high Fe (∼10 mg L^–1) concentration and high PAR intensity (∼200 μmol m^–2 s^–1), under which plants nearly died. There is a similar relationship between H₂O₂ and temperature rise in both laboratory and field experiments (Asaeda et al., 2020) in terms of different temperatures and light intensities (Riis et al., 2012). H₂O₂ values were slightly higher (∼10 μmol g^–1FW) with the experiments compared with the field samples, likely because the plants were exposed to radiation only at the tissue’s upper side in the field. Therefore, the difference is considered the result of a possible fluctuation in the field measurements.

The Chl-a and Chl-b concentrations also had a clear unique negative correlation with the H₂O₂ concentration in the plant tissue, regardless of stressor types. The type of growth rate parameter, shown by the extension rate, also indicates these unique negative trends. The oxidative stress intensity is based on the activities of H₂O₂, as well as other ROS, such as singlet oxygen and hydroxyl radicals, although superoxide is closely related to H₂O₂.

However, H₂O₂ is the major ROS generated in various organelles; thus, its concentration predominantly implies the level of environmental stress on the plants (Mittler, 2002; Miller and Mittler, 2006; Sharma et al., 2012; Czarnocka and Karpiński, 2018). The present study’s results indicate that H₂O₂ concentration has negative but unique correlations with plant growth, photosynthetic pigment content, IAA concentration, and F_v F_m^–1, regardless of the stressor type. Yet, the H₂O₂ response was slightly delayed compared with the photosynthetic pigment concentration.

Plants have opposite trends in their responses to some types of stressors, such as drought and salinity, drought and heat, and drought and high light (Rizhsky et al., 2002; Giraud et al., 2008; Ahmed et al., 2013; Suzuki et al., 2014; Choudhury et al., 2017). However, as for positively interacting stressors, the H₂O₂ concentration has the potential to be a good indicator of overall plant condition, at least at a practical management level (Asaeda et al., 2018).

The H₂O₂ concentration substantially increased in the natural river samples when exposed to high light intensities (Asaeda et al., 2020). Excessive light intensity overloaded electrons generated at PSII. These electrons are transported to PSI, where super oxides are produced from oxygen and then undergo dismutation to H₂O₂. They are toxic and damage the PSII protein D1, which otherwise repairs PSII (Leitsch et al., 1994). In this process, photoinhibition is activated more readily under higher light intensities and damages the plant. In the case of submerged plants, normal subjected light intensity is not high; it is several hundred μmol m^–2s^–1 PAR at most, which is low compared with that of terrestrial or emergent species (Asaeda and Barnuevo, 2019). At the present study’s sites, the light intensity was approximately 100–200 μmol m^–2s^–1 PAR at 0.5 m deep. E. densa grew mostly at 0.5–1.0 m deep, and plants grew at depressed sites on the river bottom. Canopy top shoots located less than 10 cm deep were often dying, although the deep shoots were healthy. These results indicate that this species seems to prefer the relatively low light intensity of 100–200 μmol m^–2s^–1 PAR to higher light intensities. Thus, exposure to high light intensity could be an efficient method of reducing the community.