Many important processes for Seagrass ecology depend on leaf age. Through biweekly census, from April to November 2015, seasonal variation in leaf age structure of the Eelgrass Zostera marina L. was studied in Swan Lake of Shandong Peninsula, China by examining density, dimensions and biomass of shoots relative to leaf ages. In addition, we examined if variability in leaf age structure was related to water temperature and/or underwater irradiance. The leaf density, number of leaves per shoot, leaf area index, total leaf area per shoot and leaf biomass of young and old Z. marina leaves were far less than those of the mature leaves with percentages of >50% in all leaf ages. The leaf age structure of mature Z. marina leaves exhibited a clear seasonal variation with significant peaks in early July, which corresponded with the seasonal changes in shoot density and biomass of Z. marina. The results demonstrated that mature leaves would be a leading component in leaf age structure of Z. marina. Curve Estimation revealed that the seasonal variation in leaf age structure of Eelgrass was closely positively related to water temperature. The results provided data that could prove helpful in quantitative studies of leaf-age dependent aspects of Seagrass ecology.
Seagrass meadows are among the world's most valuable ecosystems because they add structural complexity to shallow soft bottom systems worldwide and provide food, refuge, and living space for a variety of organisms (Costanza et al., 1997; Duarte, 2000; Heck et al., 2003; Joseph et al., 2006). Seagrass meadows also provide important ecosystem functions such as absorbing and enriching heavy metals from either the water column or the sediment, cycling nutrients, and providing attachment leaf media for epiphytes and animals and spawning grounds for fish and shellfish (Neckles et al., 1994; Grizzle et al., 1996; Bologna and Heck, 1999; Hoshikawa et al., 2004; Polte and Asmus, 2006; Prado et al., 2007; Holzer et al., 2011; Thangaradjou et al., 2013; Govers et al., 2014). However, these functions are significantly leaf age dependent (Coley, 1980; Heijs, 1985; Borum, 1987; Wasserman and Lavaax, 1991; Hemminga et al., 1999).
Zostera marina (Eelgrass) is one of the most important meadow-forming Seagrasses in temperate coastal environments in the Northern Hemisphere (Short et al., 2007; Jarvis et al., 2014). It dominates the north temperate Pacific, occurring around the Pacific Rim from Japan, Korea and China to the northern Bering Sea and down to the Gulf of California, with other Zostera species centred in East Asia (Short et al., 2007). Although seasonal variations of shoot growth, morphology and reproduction in Z. marina have been well described in the coasts of Japan, Korean, northern China and NW Mediterranean (Marbà et al., 1996; Lee et al., 2005; Watanabe et al., 2005; Hasegawa et al., 2007; Morita et al., 2007; Zhang et al., 2016), data on the seasonal variation in leaf age structure of Z. marina are not yet known.
Swan Lake (37°21′N, 122°34′E) is a tidal lagoon with an area of 4.94 km2 located on the eastern coast of Shandong Peninsula, China (Figure 1). The lake is separated from the open sea (i.e. Rongcheng Bay and the Yellow Sea) by a 2.5 km-long sand spit, which lies to the east of the lagoon. The environment of Swan Lake is considered to remain relatively healthy, with extensive Seagrass meadows (Z. marina and Zostera japonica) developed in Swan Lake. Z. marina is currently the dominant Seagrass species and it is estimated to occupy approximately 2.0 km2, with most plants being distributed in the middle of the lagoon (Zhang et al., 2016).
We investigated density, dimensions and biomass of shoots of relative leaf age in Swan Lake biweekly, from April 2015 to November 2015, to study seasonal variation in leaf age structure. This study aims to gain a better understanding of the leaf age structure in Z. marina meadows, which has never been examined previously. In addition, the study aims to examine if variability in leaf age structure is related to water temperature and/or irradiance, which have been considered the key environmental factors inducing the strong seasonality of temperate Seagrass growth (Marbà et al., 1996; Lee et al., 2007).
Materials and methods
Description of the study area
The mean water depth in Swan Lake was about 1.0 m relative to the mean sea level. The tidal range is 1.15 m on springs and 0.64 m on neaps when measured at the entrance to the lagoon. The floor of the lagoon is generally dominated by fine-grained material, with mud and sandy mud covering approximately 40% of the lagoon area (Jia et al., 2003). Detailed information on climate and environmental conditions can be found in Zhang et al. (2016).
Field procedure and data collection
Twelve permanent sampling stations were established at the maximum continuous Eelgrass bed with an area of 0.383 km2 located on the eastern coast of Swan Lake (Figure 1). A permanent buoy was fixed to the sea bed using steel stakes to mark each station.
Shoot density, morphology and biomass were monitored biweekly for 8 months from 11 April 2015 to 8 November 2015. In each sampling time, one 0.25×0.25 m quadrat was haphazardly placed within 20 m of each sampling station, but one 0.5×0.5 m quadrat was used in sampling months from April to May. Shoots were carefully collected from the quadrats and then rinsed thoroughly in seawater to remove sediments. These shoots were placed in sealed polythene bags, stored on ice, transported to the laboratory, and stored at 4°C before sorting for analysis.
Leaves were divided into three age categories, old, mature and young leaves. Identifying the age structure of different leaves was accomplished by observing the following characteristics of leaf growth: (1) Leaves may be assigned a direction relative to the youngest, central leaf and (2) the stage of leaf decay and the degree of epiphytic growth is an indication of relative leaf age (Hamburg and Homann, 1986). The young leaves of a shoot bundle are fresh green and are in the central position of the shoot without epiphyte cover; the mature leaves are dark green and are in the intermediate position of the shoot with a low epiphyte cover; and the old leaves are usually brown and are in the outermost position of the shoot with a high epiphyte cover (Ott, 1980; Thayer et al., 1984; Mazzella and Alberte, 1986; Rueda et al., 2009).
Samples were gently cleansed with gauze to remove epiphytes, and washed with tap water in the laboratory. First, the number of shoots per quadrat was counted to calculate the shoot density (shoots m−2). Shoot height (cm) was measured. Second, leaves were sorted by leaf age and cut with a razor blade for morphometrics and weight analysis. The number of leaves per shoot/per quadrat with leaf age was counted to calculate the number of leaves per shoot (leaves shoot−1) and the leaf density (leaves m−2). Third, morphometrics of leaves was analyzed by measuring leaf length and leaf width (cm). The leaf area was calculated by multiplying the leaf length by the leaf width. This area was roughly approximated because the leaves are more elliptical in shape. Total leaf area per shoot (cm2 shoot−1) with leaf age was determined as the sum of all the leaf areas of each plant, and the measurements were converted to total leaf area per unit area values (leaf area index, LAI, cm2 m−2). Lastly, subsamples were rinsed in deionized water and dried at 60°C for 48 h to obtain the leaf and rhizome dry weight. Shoot biomass and leaf biomass with leaf age (g dry wt. m−2) were calculated. The percentage of the density, morphology and biomass of the total leaves that were categorized into old, mature or young leaves were also calculated.
Water temperature (°C) and underwater photosynthetic photon flux density (PPFD) were recorded continuously every 30 min throughout the study period by using HOBO pendant temperature/light data loggers (Onset Computer Corp.), which were placed underwater 20 cm from the seabed. The measured water temperature was averaged daily. Light intensity (lux) measured using the HOBO data logger was converted to PPFD (µmol photons m−2 s−1) through concurrent quantum measurements by using LI-250A data logger and LI-193SA spherical quantum sensor (Li-Cor, Inc.). Daily PPFD (mol photons m−2 d−1) was calculated as the sum of the quantum flux over each 24 h period.
All values are reported as mean ±95% confidence interval (CI). Data were tested with one-way analysis of variance (ANOVA). Data were tested for normality and homogeneity of variance to meet the assumptions of parametric statistical analysis. Tukey HSD multiple range test was used to establish the significance of differences among treatments when the ANOVA result was significant at α = 0.05. The relationships between water temperature/irradiance and leaf age structure were estimated using Curve Estimation and the significances of these regressions were tested using ANOVA. For this purpose, measured water temperature and PPFD were averaged biweekly. Statistical analyses were performed using SPSS Windows Program (Release 18.0, SPSS, Inc.).
Water temperature and photosynthetic photon flux density
Water temperature showed a typical seasonal variation pattern during the sampling period from 11 April 2015 to 8 November 2015 (Figure 2a), with the highest value of 26.8°C in August and the lowest value of 6.8°C in April 2015. Underwater irradiance also exhibited a clear seasonal variation (Figure 2b). PPFD was highest during late spring and summer and lowest in the middle of fall.
Shoot density and height
The shoot density of Z. marina showed a clear seasonal variation (P < 0.05) with high values in sampling months from May to early August (Figure 3a). The shoot density was low with an average of 301 shoots m−2 in April 2015. The maximum value of 1063 shoots m−2 was recorded in the early July 2015. Shoot height also exhibited a significant seasonal variation (P < 0.05) with the maximum value of 70.6 cm in late August and the minimum value of 11.0 cm in early April 2015 (Figure 3b).
Random samples obtained each semi-month showed that the above ground, below ground and total biomass of Z. marina plants increased rapidly from April to early July, when it levelled off, and a significant decrease was observed from late August to November 2015 (Figure 4). The below ground biomass was far less than that of above ground tissues.
Leaf density and number of leaves per shoot
The mature leaf density and total leaf density showed a similar and clear seasonal variation (P < 0.05) with the highest values of 3134 mature leaves m−2 and 5411 leaves m−2 in early July and the lowest values in April. The young leaf density and old leaf density were far less than the mature leaf density, ranging from 167 young leaves m−2 in early April to 1126 young leaves m−2 in early November and 147 old leaves m−2 in early October to 1217 old leaves m−2 in early July (Figure 5a). The mature leaf percentage was higher than 50% in all leaf ages in each sampling time. No marked differences in leaf percentage were found between young and old leaves in the same sampling time except for sampling months from early October to early November with averages of 20.4% and 17.4%, respectively (Figure 5b).
The number of leaves per shoot ranged from 4 leaves per shoot in early April and months from early August to late September to 6 leaves per shoot in early May. The number of mature leaves per shoot ranged from 2 leaves per shoot to 4 leaves per shoot. No marked differences in number of leaves per shoot were found between young and old leaves in the same sampling time except for sampling months from early October to early November with averages of 1 leaf per shoot and 0.8 leaf per shoot, respectively (Figure 6a). The mature leaf percentage was higher than 50% in all leaf ages in each sampling time. The young leaf percentage did not exhibit clear seasonal variation with an average of 20%. The old leaf percentage showed the higher values in sampling months from late May to late August except for early August with an average of 16.7% (Figure 6b).
Leaf area index and total leaf area per shoot
The mature leaf area index and total leaf area index exhibited significant seasonal variations (P < 0.05) with the highest values of 69,719 cm2 m−2 and 99,040 cm2 m−2 in early July and the lowest values in April. The old leaf area index also showed a clear seasonal variation with the high values in early July and late August. The young leaf area index was far less than the mature leaf area index, ranging from 368 cm2 m−2 in early April to 4711 cm2 m−2 in late August (Figure 7a). The mature leaf percentage was higher than 60% in all leaf ages in each sampling time except for late August. The young leaf percentage was lower than 10% in all leaf ages in each sampling time except for early April. The old leaf percentage showed a significant seasonal variation with the highest value of 42% in late August and the low values (<10%) in October (Figure 7b).
The total leaf area per shoot in all leaf ages and their percentages exhibited a similar trend to the leaf area index in all ages and their percentages (Figure 8). The total mature leaf area per shoot showed a clear seasonal variation with significant peak in sampling months from early July to early August. The mature leaf percentage was higher than 60% in all leaf ages in each sampling time except for late August, whereas the young leaf percentage was lower than 10% in all leaf ages in each sampling time except for early April.
The leaf biomass in all leaf ages and their percentages showed a similar pattern of variation to the leaf area index in all ages and their percentages (Figure 9). The mature leaf biomass and total leaf biomass exhibited a clear seasonal variation with significant peaks in early July. The young leaf biomass was far less than the mature leaf biomass, ranging from 1.6 g DW m−2 in early April to 14.2 g DW m−2 in late August. The mature leaf percentage was higher than 60% in all leaf ages in each sampling time except for late August, whereas the young leaf percentage was lower than 10% in all leaf ages.
Relationships among leaf age structure of Eelgrass and water temperature/irradiance
Curve Estimation revealed that water temperature was significantly positively correlated with leaf age structure of Eelgrass (Table 1). However, there were not significant relationships (P > 0.05) between underwater irradiance and leaf age structure of Eelgrass.
Leaf growth would be an important component in net primary production of Seagrasses (Hosokawa, 2011). The leaf growth strategy of Z. marina is a mono-meristematic leaf-replacing form that continually produces strap-like leaf tissue at a combined basal leaf/rhizome meristem area. Leaves are produced in the center of a leaf bundle, held together by the protective sheath portion of older leaves, which are shed and replaced by the new leaves (Short and Duarte, 2001). Therefore, relative age of individual leaves in a leaf bundle increases with the production of new leaves (Hosokawa, 2011). The present study showed that leaf density, number of leaves per shoot, leaf area index, total leaf area per shoot, and leaf biomass of young and old Z. marina leaves were far less than those of the mature leaves with percentages of >50% in all leaf ages in each sampling time except for leaf area index in late August. The results revealed that mature leaves would be a leading component in leaf age structure of Z. marina and developed the maximum leaf area index and biomass.
Many Seagrasses are known to evolve a rapid growth strategy to counteract epiphytic loading (Orth and Montfrans, 1984). For example, the Seagrass Enhalus acoroides developed a rapid leaf growth with an average of 1.22 cm per day to enhance overall photosynthetic activity in this species (Johnstone, 1979). For Z. marina, the average leaf plastochrone interval (PL; time period between production of consecutive new leaf parts) was 15.3 days (Short and Duarte, 2001). At the same time, the life-span of the Seagrass leaves are usually much longer than the PL with an average of 88.4 days, but is highly variable, ranging from 345 days in Posidonia oceanica to only a few days in Halophila ovalis (Hemminga et al., 1999). For Z. marina, values rarely exceeded 50 days (average 37.6 days) (Ibarra-Obando et al., 1997; Alcoverro et al., 1998). However, older leaves are fragile and excessively fouled, easily resulting in obvious losses in the life-time (Orth and Montfrans, 1984; Hosokawa, 2011). These results may contribute to the explanation of the maximum percentage of mature leaves in all leaf ages found in the present study.
Our results indicated that leaf density, leaf area index and leaf biomass of mature Z. marina leaves exhibited a clear seasonal variation, with significant peaks in early July and distinctly less during early spring. These temporal patterns corresponded with the seasonal changes in shoot growth and dimensions of Z. marina found in Swan Lake (Qin et al., 2016; Zhang et al., 2016; this study), Sango Bay of northern China (Liu, 2011; Tang, 2013), and Qingdao Bay of northern China (Liu, 2011; Chen, 2013). In our research site, a rapid decline in shoot biomass from early July to early August and in leaf density, leaf area index and leaf biomass of mature Z. marina leaves from early August to late August may occur because of development and bloom of reproductive shoot and drift macroalgae (Hasegawa et al., 2007; Zhang et al., 2016).
Seasonal variation in productivity of Seagrasses has been attributed to changes in various biotic and abiotic factors that influence plant metabolism (Lee et al., 2007). Previous studies have demonstrated that temperature and underwater irradiance affect biochemical processes of organisms, and are considered as major factors controlling Seagrass growth (Koch and Beer, 1996; Moore et al., 1997; Lee et al., 2007; Zhang et al., 2016). In our study, Curve Estimation revealed that the seasonal variation in leaf age structure of Eelgrass was closely positively related to the water temperature. These results are consistent with the findings of previous studies in relationships between temporal changes in shoot growth of Eelgrass and water temperature. For example, Watanabe et al. (2005) found that temporal variation in production of Z. marina was correlated with that of water temperature in Akkeshi Bay, northern Japan. Lee et al. (2005) indicated that seasonal variations in Eelgrass shoot density, biomass, and leaf productivities in two bay systems (Koje Bay and Kosung Bay) on the south coast of the Korean peninsula were strongly correlated with water temperature. Also, Qin et al. (2016) and Zhang et al. (2016) revealed that water temperature and Eelgrass shoot density, biomass and above-ground tissue dimensions displayed positive linear relationships.
In conclusion, many important processes for Seagrass ecology depend on leaf age, such as photosynthesis, leaf growth, chemical composition, and grazing loss (Cebrián et al., 1994). Our results demonstrated that the mature leaves of Z. marina in Swan Lake, China developed the maximum percentage in all leaf ages and exhibited strong seasonal variations with significant peaks in early July. Also, seasonality of leaf age structure of Z. marina in Swan Lake was closely positively correlated with water temperature. The results obtained from this study provide data that could clarify the complex leaf age structure and prove helpful in quantitative studies of leaf-age dependent aspects of Seagrass ecology and ecosystem functions.
We thank Runlong Sun, Feng Jiang and Youzhi Wang for their assistance during sample collection and calculations.
This research was supported by the National Natural Science Foundation of China (41576112), National Basic Research Priorities Program of China (2015FY110600) and National Marine Public Welfare Research Project (201405010).