Effects of water level fluctuation on the growth of submerged macrophyte communities

Flora 223 (2016) 83–89

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Effects of water level fluctuation on the growth of submerged macrophyte communities Pu Wang 1 , Qian Zhang 1,2 , Ying-Shou Xu, Fei-Hai Yu ∗ School of Nature Conservation, Beijing Forestry University, Beijing 100083, China

a r t i c l e

i n f o

Article history: Received 4 December 2015 Received in revised form 12 April 2016 Accepted 8 May 2016 Edited by Hermann Heilmeier Available online 12 May 2016 Keywords: Aquatic plants Clonal plants Diversity index Water regime Frequency Morphological adaptation

a b s t r a c t Aquatic plant communities are frequently subjected to water level fluctuation. While many experimental studies have examined effects of water level fluctuation on the growth of individual aquatic plant species, very few have tested those on aquatic plant communities. We constructed aquatic communities consisting of four submerged macrophytes (Potamogeton perfoliatus, Myriophyllum spicatum, Chara fragilis and Ceratophyllum demersum), and subjected them to three static water depths (30, 90 and 150 cm) and three water level fluctuations with low, medium and high frequency (two, four and eight cycles of water depth change between 30 cm to 150 cm). Water depth in each of the three fluctuation treatments was on average 90 cm, which was comparable to the static water depth of 90 cm. Increasing water depth significantly decreased the growth of the communities in terms of biomass, number of shoot nodes and shoot length because it decreased the growth of most species (P. perfoliatus, M. spicatum and C. fragilis). Compared to the static water depth of 90 cm, water level fluctuation increased number of shoot nodes and shoot length of the communities, whereas fluctuation frequency had little impact. We conclude that water level fluctuation may potentially increase the vegetative spread of submerged macrophyte communities and managing water level fluctuation may be helpful for the restoration of submerged macrophyte communities in degraded wetlands. © 2016 Elsevier GmbH. All rights reserved.

1. Introduction Disturbance is a common event in nature (Klimeˇsová and Klimeˇs, 2003). Both theoretical and empirical studies have shown that a certain level of disturbance is beneficial to maintaining species diversity, plant growth and community productivity (e.g. ‘Intermediate Disturbance Hypothesis’; Bornette et al., 1994; Connell, 1978; Higgins and Cain, 2002; Lenssen and de Kroon, 2005; Peintinger et al., 2007). This may be because colonizing species can occupy gaps created by disturbance events when some individuals die (Higgins and Cain, 2002). However, strong disturbance will impose great stress that will ultimately cause negative impacts on plant communities (Belote et al., 2012; Connell, 1978; Franklin et al., 2016).

∗ Corresponding author. E-mail address: [email protected] (F.-H. Yu). 1 These authors contributed equally. 2 Current address: Department of Experimental Plant Ecology, Institute for Water and Wetland Research, Radboud University Nijmegen, 6525 AJ Nijmegen, The Netherlands. http://dx.doi.org/10.1016/j.flora.2016.05.005 0367-2530/© 2016 Elsevier GmbH. All rights reserved.

Flooding caused by heavy precipitation and extreme drought due to little precipitation are predicted to occur in higher frequency and severity over the coming years due to climate change (IPCC, 2013). These unusually strong disturbance events will inevitably impose strong stress on both terrestrial and aquatic plant communities (Brock et al., 2003; Wright et al., 2015). While numerous studies have examined effects of these disturbance factors on the performance of plant individuals and communities in terrestrial ecosystems (e.g. Engelbrecht et al., 2007; Jaleel et al., 2009; Vervuren et al., 2003; Wright et al., 2015), relatively little attention has been paid on aquatic ecosystems (Froend and McComb, 1994; Thomaz et al., 2006). Aquatic plants, especially submerged macrophytes that grow only under the water, seem less likely to experience flooding and drought directly, but the dynamics of water regime caused by these disturbances may reconstruct aquatic plant communities (Deegan et al., 2007; Wilcox and Nichols, 2008). Therefore, empirical studies about effects of water regime on the productivity and structure of aquatic plant communities are of great value for better prediction of aquatic community dynamics and for management of aquatic ecosystems in the context of climate change. Water regime or hydraulic regime, defined as water depth and its seasonal variability (fluctuation), is strongly altered by changes

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in precipitation (Froend and McComb, 1994). Water depth has a significant effect on the growth, reproduction and distribution of aquatic vegetation (Froend and McComb, 1994; van der Valk, 1987). In aquatic ecosystems, water depth is often not maintained constantly, but shows fluctuations with different frequencies and amplitudes depending on e.g. patterns of precipitation and human activities (Deegan et al., 2007; Rea and Ganf, 1994). Such water level fluctuation can directly modify light availability in the water and oxygen availability in the sediment (Casanova and Brock, 2000; Raulings et al., 2010), and strongly influence pathways of nutrient cycling (Coops and Hosper, 2002; Pinay et al., 2002). These processes may further impact the growth of aquatic vegetation (van der Valk, 2005). Many studies have addressed how water level fluctuation affected the growth of individual aquatic plant species (Deegan et al., 2007; Thomaz et al., 2006; Vretare et al., 2001). For instance, water level drawdown negatively affected biomass of Egeria najas, and water level recovery helped the floating species Eichhornia crassipes to grow fast (Thomaz et al., 2006). Strong water level fluctuation decreased the performance of Phragmites australis compared to constant water level (Vretare et al., 2001), but slight water level fluctuation might promote the growth of this species (Deegan et al., 2007). In addition, water level fluctuation also influenced sexual reproduction of an amphibious macrophyte, Schoenoplectus lineolatusthe (Ishii and Kadono, 2004). So far, however, few experimental studies have been conducted to test the effect of water level fluctuation on the growth of aquatic plant communities, especially submerged macrophyte communities. Fluctuation frequency, i.e. number of cycles of water depth changes over time, is one of the most important components of water level fluctuation (De Jager, 2012; Gerard et al., 2008). High fluctuation frequency means quick changes in water level, which may limit the time for plastic responses of morphological and/or physiological traits in aquatic macrophytes (Zhang et al., 2013). For species with slow morphological and physiological responses, they may not survive under high frequency fluctuations (Zhang et al., 2013; Luo et al., 2015). For species with an intermediate rate of responses, they could benefit from lowered water level because of increased light availability (Coops and Hosper, 2002) and not be inhibited too much by recovered water level. Therefore, they can adapt well under fluctuations with high or medium frequency. For species with quick responses and high plasticity, they may suffer more than slow-response or non-plastic species under high frequency fluctuations (Osmond, 1994). This is because sudden re-exposure of submerged plants to higher light intensity under lowered water level may bring damage to plant photosynthetic apparatus which is adapted to low light underwater conditions (Osmond, 1994). Additionally, high fluctuation frequency means high level of disturbance and may cause physical damages to the plants (e.g., stolon breakage, uprooting, or other damages; Luo et al., 2015), which eventually bring adverse impacts on plant growth (Hudon et al., 2000; Zhu et al., 2012). High fluctuation frequency can also lead to resuspension of sediment, which is an important determinant of turbidity, preventing clear conditions in the water body and thus inhibiting the establishment of aquatic macrophytes (Coops and Hosper, 2002). Therefore, species with higher tolerance can well establish under high frequency fluctuations, while those with lower tolerance may not survive. In this way fluctuation frequency may change the structure of a community. However, few experimental studies have examined impacts of water level fluctuation frequency on the growth of submerged macrophyte communities. We constructed submerged macrophyte communities and subjected them to three static water depth treatments and three water lever fluctuation treatments differing in frequency. Specifically, we addressed the following questions: (1) Does different static water depth affect the growth of the submerged macrophyte

communities? (2) Does water level fluctuation affect the growth of the submerged macrophyte communities? (3) If it does, is the effect of water level fluctuation affected by its frequency? 2. Materials and methods 2.1. Experimental communities and plant sampling The experimental communities were constructed with four submerged macrophytes all widely distributed in China, i.e., Potamogeton perfoliatus L. (Potamogetonaceae), Myriophyllum spicatum L. (Haloragidaceae), Chara fragilis Desv. (Characeae) and Ceratophyllum demersum L. (Ceratophyllaceae). These four species are all perennial and capable of clonal growth (Cronk and Fennessy, 2001; Nichols and Shaw, 1986; Zhang et al., 2014). The bud(s) within each shoot node can potentially develop into a new plant. The four species can co-occur in the wild (Talevska et al., 2009). Potamogeton perfoliatus occurs in fresh water to brackish water environments (Asaeda et al., 2004). Light is a key factor for its survival (Asaeda et al., 2004). Myriophyllum spicatum is native to Eurasia, and has leafy shoots and finely dissected whorls of leaves (Strand and Weisner, 2001). This species can grow in various sediment types and tolerate low-light environments (Smith and Barko, 1990). Chara fragilis is common in fresh water, attached to the muddy bottom. Ceratophyllum demersum occurs commonly in moderately to highly eutrophic lakes and ditches (Keskinkan et al., 2004). In May 2012, plants of these four species were collected in the lakes of Beijing Olympic Forestry Park. They were vegetatively propagated outdoors in the Cuihu wetland park in Beijing, China, for about four weeks to minimize the potential effect of local environments. On 4 June 2012, 108 shoots of each species were selected for the experiment described below. Each shoot was cut to 13 cm length with an apex but no lateral branches to minimize initial size variation. 2.2. Experimental design We constructed 36 submerged macrophyte communities in 36 plastic pots (18 cm in diameter and 12 cm in height) filled with 10-cm-deep river sediment collected in the Cuihu wetland park (organic matter: 14.01 ± 1.00 mg g−1 , total nitrogen content [TN]: 0.82 ± 0.07 mg g−1 , total phosphorus content [TP]: 6.71 ± 0.04 mg g−1 [mean ± SE, n = 3]). Each pot (community) was placed within a mesh container (19 cm in diameter and 56 cm in height) with an open top. Each experimental community initially consisted of three shoots of each of the four submerged macrophytes, planted randomly in three rows and four columns. After 7 days for recovery, the constructed wetland communities were subjected to six hydraulic treatments. The experiment was set up in a randomized-block design with six blocks, i.e., in six independent PVC tanks (1.0 m in diameter and 1.6 m in height). Each tank contained six constructed communities within six mesh containers. The mesh containers were used to physically separate the six communities and prevent them from direct interfering with one another, as we expected that at least some of the species would spread quickly by clonal growth. Because the meshes were coarse in size (6 mm), light could also get into the container through the mesh wall. The six communities in each tank were randomly assigned to six hydraulic treatments, i.e., three static water depth treatments (low, medium and high) and three water level fluctuation treatments differing in frequency (low, medium and high; Appendix A in Supplementary material). The static low, medium and high water depth treatments (coded as SL, SM and SH) were kept 30, 90 and 150 cm deep, respectively, from

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2.3. Harvest and measurements After 48 days, on 29 July, all plants were harvested and separated into individual species. Total shoot length and number of shoot nodes are measures of potential clonal growth and vegetative spread (Li et al., 2015; Zhang et al., 2014). At harvest, numerous shoots had been produced in each mesh container. During the harvest the shoots of the submerged clonal plants were easily broken, producing numerous shoot fragments. Thus it was too hard to count the number of shoot nodes and measure the shoot length for all shoot fragments. We thus randomly chose five shoot fragments of each species in each community to measure their shoot length and number of nodes as well as biomass (after oven-dried at 70 ◦ C for 72 h). The remaining parts of each species were also oven-dried at 70 ◦ C for 72 h and weighed to measure biomass. 2.4. Data analysis We calculated number of nodes and shoot length per unit biomass for each species in each community based on the data of the five shoot fragments (Zhang et al., 2014). Then by multiplying total biomass (i.e. biomass of the five shoots plus that of the remaining parts) with number of nodes per unit biomass (or shoot length per unit biomass), we obtained total number of shoot nodes (or total shoot length). To quantify species composition of the communities, we calculated Shannon-Wiener diversity index (Hill, (H) based on biomass of the four species in each community  1973; Zhang et al., 2014). It was calculated as H = − Pi ln (Pi ) (i = 1, 2. . .S), where S is number of macrophyte species in the community and Pi is biomass of species i divided by the sum of biomass of all the four species in the community. We used two-way ANOVAs to test effects of block and the hydraulic treatment (i.e. SL, SM, SH; FL, FM and FH) on the growth (biomass, shoot node number and shoot length) and diversity index of the submerged communities and the growth of each of the four submerged macrophyte species. To test the specific questions, we

15

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the water surface in the tank to the soil surface in the pot. In the low fluctuation frequency treatment (coded as FL), the water depth of the communities changed gradually from 30 cm to 150 cm and then from 150 cm to 30 cm for two times during the period of 48 days (24 days per time). In the medium frequency treatment (coded as FM), the water depth changed gradually in the same way for four times during the 48 days (12 days per time). In the high frequency treatment (coded as FH), the water depth changed gradually for eight times during the 48 days (6 days per time). In each tank, all mesh containers (with the communities) were suspended in the water by adjustable ropes connected to steel bars lying on the top of the tank. The water depth of each community was controlled by the length of the rope. For the static water depth treatments the lengths of the ropes were kept unchanged during the 48-day experiment, but for the fluctuation treatments the lengths of the ropes were adjusted (released more or pulled up) according to the changes in the water depth. The experiment was conducted outdoors in the Cuihu wetland park. During the experiment the highest and lowest daily mean air temperature was 31 ± 0.4 and 22 ± 0.3 ◦ C, respectively. On a sunny day, we measured light intensity immediately above and under the water surface, at 90 cm and 150 cm water depth, respectively, in six tanks using a Li-COR UWQ-4341 sensor. Light intensity immediately under the water surface, at 90 cm and 150 cm depth was 51.49 ± 0.88%, 14.54 ± 2.12% and 2.29 ± 0.58% (mean ± SE; n = 6) of that above the water surface. We kept the water level in the tanks constant by adding tap water into the tanks to compensate for water loss due to evaporation or removing surplus water caused by raining.

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(D)

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SL SM SH FL FM FH

SL SM SH FL FM FH

Fig. 1. Growth (A–C) and Shannon-Wiener diversity index (D) of the submerged macrophyte communities under the six hydraulic treatments. Bars and vertical lines are means ± SE (n = 6). Different lowercase letters show significant differences between water depth treatments; different capital letters show significant differences between fluctuation frequency treatments; symbols (ns p ≥ 0.05; * p < 0.05 and ** p < 0.01) show whether there was an overall effect of water level fluctuation. See Table 1 for statistics and treatment codes.

further conducted a series of linear contrasts following the twoway ANOVAs (Sokal and Rohlf, 1981). To test the effect of static water depth, we conducted three contrasts, i.e., SL vs. SM, SL vs. SH and SM vs. SH. To examine the overall effect of water level fluctuation, we conducted a contrast to compare the mean of SM with the pooled mean of the three water fluctuation treatments (FL, FM and FH). This was because the average water depth of each of the three fluctuation treatments was 90 cm, which was the same as that in SM. To investigate the effect of water level fluctuation frequency, we conducted three contrasts, i.e., FL vs. FM, FL vs. FH and FM vs. FH. The growth data of the submerged communities were log-transformed and those of the four species were transformed to square root before analysis. All analyses were conducted using SAS 9.2 with the contrast statement of the GLM procedure (SAS Institute Inc., 2009). 3. Results 3.1. Community-level effects of hydraulic treatments Overall, the hydraulic treatments had significant effects on the growth (biomass, number of nodes and shoot length) of the submerged macrophyte community, but not on the diversity index (Appendix B in Supplementary material). All three growth measures of the community were significantly greater at static low water depth (SL) than at static medium (SM) or high (SH) water depth, but they did not differ significantly between SM and SH (Table 1A, Fig. 1A–C). The diversity index of the community was not affected by static water depth (Table 1A, Fig. 1D). Water level fluctuation did not affect biomass or diversity index of the submerged macrophyte community (Table 1B, Fig. 1A and D), but significantly increased number of nodes and shoot length compared to SM (Table 1B, Fig. 1B and C). Neither growth nor the diversity index differed between the low (FL), medium (FM) and high fluctuation frequency (FH) treatments (Table 1C, Fig. 1A–D). 3.2. Species-level effects of hydraulic treatments In general, the hydraulic treatments had significant effects on the growth of the four species (Appendix C in Supplementary

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Table 1 Results of linear contrasts for effects of different levels of (A) static water depth, (B) water level fluctuation and (C) fluctuation frequency on the growth and diversity of the submerged macrophyte communities. Contrast

Biomass F1, 25

(A) Static water depth SL vs. SM SL vs. SH SM vs. SH

12.38 30.21 3.91

No. of nodes

Shoot length

Diversity

p

F1 , 25

p

F1 , 25

p

F1 , 25

p

0.002 <0.001 0.059

20.18 42.08 3.98

<0.001 <0.001 0.057

4.41 15.3 3.28

0.046 <0.001 0.082

0.03 0.55 0.86

0.854 0.464 0.362

(B) Water level fluctuation SM vs. (FL + FM + FH)

0.96

0.336

8.63

0.007

4.84

0.037

0.23

0.637

(C) Fluctuation frequency FL vs. FM FL vs. FH FM vs. FH

0.97 0.10 0.45

0.333 0.757 0.507

2.47 1.29 0.19

0.129 0.268 0.666

2.27 1.57 0.06

0.144 0.221 0.802

0.23 1.30 0.44

0.636 0.264 0.514

F, p and DF are given, and values of p < 0.05 are in bold. SL, SM and SH stand for static low, medium and high water depth, respectively; FL, FM and FH represent water level fluctuation of low, medium and high frequency, respectively.

Table 2 Results of linear contrasts for effects of different levels of static water depth, water level fluctuation and fluctuation frequency on the growth of each of the four submerged macrophytes. Species

Contrast

P. perfoliatus

(A) Static water depth SL vs. SM SL vs. SH SM vs. SH (B) Water level fluctuation SM vs. (FL + FM + FH) (C) Fluctuation frequency FL vs. FM FL vs. FH FM vs. FH

M. spicatum

C. fragilis

C. demersum

(D) Static water depth SL vs. SM SL vs. SH SM vs. SH (E) Water level fluctuation SM vs. (FL + FM + FH) (F) Fluctuation frequency FL vs. FM FL vs. FH FM vs. FH (G) Static water depth SL vs. SM SL vs. SH SM vs. SH (H) Water level fluctuation SM vs. (FL + FM + FH) (I) Fluctuation frequency FL vs. FM FL vs. FH FM vs. FH (J) Static water depth SL vs. SM SL vs. SH SM vs. SH (K) Water level fluctuation SM vs. (FL + FM + FH) (L) Fluctuation frequency FL vs. FM FL vs. FH FM vs. FH

Biomass

No. of nodes

Shoot length

F1,25

p

F1 ,25

p

F1 ,25

p

7.56 17.65 2.10

0.011 <0.001 0.159

8.60 20.94 2.70

0.007 <0.001 0.113

1.45 5.53 1.32

0.241 0.027 0.261

<0.01

0.990

1.66

0.210

0.68

0.418

0.21 0.11 0.01

0.650 0.738 0.905

0.16 0.04 0.35

0.695 0.851 0.562

0.37 0.00 0.31

0.546 0.955 0.584

29.09 76.25 11.14

<0.001 <0.001 0.003

23.81 73.23 13.53

<0.001 <0.001 0.001

4.48 22.90 7.12

0.044 <0.001 0.013

1.95

0.175

1.71

0.203

2.24

0.147

5.01 2.47 0.44

0.034 0.128 0.512

4.28 11.47 1.74

0.049 0.002 0.199

3.83 7.21 0.53

0.062 0.013 0.473

9.72 16.33 0.85

0.005 <0.001 0.365

9.23 18.07 1.47

0.006 <0.001 0.237

2.69 4.01 0.13

0.114 0.056 0.720

1.16

0.291

3.49

0.074

4.97

0.035

0.19 2.07 3.52

0.666 0.162 0.072

0.27 2.19 3.99

0.610 0.152 0.057

0.14 4.07 5.74

0.710 0.054 0.024

0.56 2.97 0.95

0.462 0.097 0.338

1.48 5.05 1.06

0.235 0.038 0.312

9.93 31.89 6.23

0.004 <0.001 0.020

0.98

0.331

3.97

0.057

6.97

0.014

0.45 0.01 0.61

0.510 0.910 0.441

0.55 0.04 0.29

0.466 0.843 0.594

0.04 0.13 0.31

0.846 0.724 0.585

F, p and DF are given, and values of p < 0.05 are in bold. Treatment codes are described as in Table 1.

material). Specifically, biomass and number of nodes of P. perfoliatus were greater in SL than in SM or SH, but they did not differ between SM and SH (Table 2A, Fig. 2A and E). However, water level fluctuation or its frequency had no significant effect on the growth of P. perfoliatus (Table 2B and C, Fig. 2A, E and I).

Increasing water depth significantly decreased biomass, number of nodes and shoot length of M. spicatum (Table 2D, Fig. 2B, F and J). However, compared to SM, water level fluctuation did not affect any of the growth measures of M. spicatum (Table 2E, Fig. 2B, F and J). Compared to FL, FM significantly decreased biomass and number

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Chara fragilis 3

Biomass (g)

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Myriophyllum spicatum

Potamogeton perfoliatus 10

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Fig. 2. Biomass (A–D), number of nodes (E–H) and total shoot length (I–L) of each of the four submerged macrophytes under the six hydraulic treatments. Bars and vertical lines are means ± SE (n = 6). Different lowercase letters show significant differences between water depth treatments; different capital letters show significant differences between fluctuation frequency treatments; symbols (ns p ≥ 0.05; * p < 0.05 and ** p < 0.01) show whether there was an overall effect of water level fluctuation. See Table 2 for statistics. Treatment codes are described as in Table 1.

of nodes and FH decreased number of nodes and shoot length of M. spicatum (Table 2F, Fig. 2B, F and J). Biomass and number of nodes of C. fragilis were higher in SL than in SM or SH, but they did not differ between SM and SH (Table 2G, Fig. 2C and G). In contrast, shoot length of C. fragilis was not affected by static water depth (Table 2G, Fig. 2K). Water level fluctuation increased shoot length of C. fragilis, but had no significant impacts on biomass or number of nodes (Table 2H, Fig. 2C, G and K). Water level fluctuation frequency did not influence biomass or number of nodes of C. fragilis (Table 2I, Fig. 2C and G). Shoot length of C. fragilis was significantly greater under FH than FM, but did not differ between FL and FM or between FL and FH (Table 2I, Fig. 2K). Static water depth did not affect biomass of C. demersum, but significantly affected number of nodes and shoot length (Table 2J, Fig. 2D, H and L). Number of nodes of C. demersum was greater under SH than SL, but it did not differ significantly between SM and SL or between SM and SH (Table 2J, Fig. 2H). Increasing static water depth markedly increased shoot length of C. demersum (Table 2J, Fig. 2L). Water level fluctuation did not significantly affect biomass or number of nodes of C. demersum, but significantly increased its shoot length compared to SM (Table 2K, Fig. 2D, H and L). Fluctuation frequency did not significantly affect any of the growth measures of C. demersum (Table 2L, Fig. 2D, H and L). 4. Discussion Not surprisingly, relatively deep water significantly decreased the growth of submerged macrophyte communities. This is because most species (i.e. P. perfoliatus, M. spicatum and C. fragilis) that are also relative abundant responded negatively. Deeper water decreases light availability and thus inhibits plant growth (Strand and Weisner, 2001; Vretare et al., 2001; Zhu et al., 2012).

Furthermore, deeper water can also decrease oxygen concentration in below-ground parts (Weisner, 1988). This may decrease the nutrient uptake efficiency (Bradley and Morris, 1990) and thus reduce the growth of aquatic plants (Vretare et al., 2001). The only exception is C. demersum whose growth was not reduced by increasing water depth. Aquatic macrophytes can make morphological adaptation in response to increased water depth by elongating shoots or leaves (Wang et al., 2014). In the case of C. demersum, total shoot length increased markedly with increasing water depth, showing morphological adaptation. Also, this species normally does not produce roots but modified leaves to anchor it to the sediment, and can absorb all nutrients from the ambient water (Keskinkan et al., 2004). Because of this special life form, lower light intensity and oxygen concentration in below-ground parts in deeper water may not be a key factor limiting its growth. Thus, both morphological adaptation and the special life form may explain the unresponsiveness of this species to water depth. Water level fluctuation significantly increased number of nodes and shoot length of the submerged macrophyte community. This was because values of these two variables were higher in the fluctuation treatments than in the static medium water level treatment for all the four species, although in many cases they were statistically not different (Table 2). This result suggests that water level fluctuation may benefit the vegetative spread of submerged communities as both number of nodes and shoot length are important measures of clonal growth and each shoot node of these four species is potentially capable of developing into a new plant (Cronk and Fennessy, 2001; Li et al., 2015; Nichols and Shaw, 1986). However, total biomass or diversity of the community was not affected by water level fluctuation because biomass of the four species, especially that of the two most abundant species (P. perfoliatus and M. spicatum), was not affected by water level fluctuation. The growth

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measures of the submerged macrophyte community did not differ between any two of the three levels of fluctuation frequency, suggesting that frequency of fluctuation in water level did not impact the growth of the submerged community. Therefore, the significant effects of water level fluctuation did not depend on its frequency. This may be because the growth of most species in the community was not significantly affected by water level fluctuation frequency due to their adaptive capacities to tolerate fluctuation frequency. Another reason may be that factors other than fluctuation frequency also play important roles (Smith and Brock, 2007; Wang et al., 2014). In natural habitats, water level fluctuation is a dynamic process that may affect submerged macrophyte species both spatially and temporally (Cao et al., 2012; Yu and Yu, 2009). In most lakes, the water level is fluctuating throughout the time. The effects of water level fluctuation depends on many factors, including the duration of flooding or drought, frequency and amplitude of fluctuation (Smith and Brock, 2007; Wang et al., 2014). Some studies demonstrated that aquatic plants could produce greater biomass at fluctuating water levels than at static water levels over shorter time scales (Rea and Ganf, 1994; Smith and Brock, 1996, 2007). This is in accordance with our results in some way, i.e. water level fluctuation significantly increased shoot length and tended to significantly (P = 0.057–0.074) increase number of nodes of C. fragilis and C. demersum compared with the static medium water level treatment. Aquatic plants could perform best when an intermediate frequency of flooding events occurred (Bornette et al., 1994), consistent with the Intermediate Disturbance Hypothesis (Connell, 1978). However, we found that fluctuation frequency had little effect on the growth of P. perfoliatus, C. demersum or C. fragilis, and that M. spicatum grew the best in low fluctuation frequency. In another study, the growth of the submerged plant Ottlia alismoides also showed little response to fluctuation frequency (Yu and Yu, 2009). Thus, the ability to tolerate water level fluctuation frequency is species specific, which may be linked to the specific morphological and physiological adaptations of the species (Abernethy et al., 1996; Maberly, 1993). Of the four submerged species in the community, M. spicatum was the most responsive one to hydraulic treatments. This species was shown to have a high ability of morphological responses to increased water depth (Strand and Weisner, 2001), and produced longer shoots and greater aboveground biomass allocation in deeper water or under higher fluctuation frequency (Cao et al., 2012; Strand and Weisner, 2001; Thouvenot et al., 2013). However, total shoot length of this species did not show a plastic response to either deeper water level or higher fluctuation frequency in our study. This may be because other factors such as fluctuation amplitude (Zhang et al., 2013), sediment type or nutrients (Cao et al., 2012) played crucial roles in its morphological response to the hydraulic changes.

5. Conclusions We conclude that water level fluctuation may potentially increase the vegetative spread of submerged macrophyte communities as it can increase the production of shoot nodes and also enhance total shoot length. This suggests that managing water level fluctuation may be helpful for the restoration of submerged macrophyte communities in degraded wetlands. When disturbance is not strong, emergent macrophytes often become dominant in valuable, shallow, aquatic ecosystems because their shading excludes submerged macrophytes (Smith, 2014). There is evidence that fluctuating water levels could restrict the growth and spread of emergent macrophytes (Deegan et al., 2007). Thus, water

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