Ecological Engineering Evaluating the ecological performance of ...

Ecological Engineering 35 (2009) 1090–1103

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Evaluating the ecological performance of wetland restoration in the Yellow River Delta, China Baoshan Cui a,∗ , Qichun Yang a , Zhifeng Yang a , Kejiang Zhang b a b

School of Environment, Beijing Normal University, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Beijing 100875, China The Centre of Environmental Engineering Research and Education (CEERE), University of Calgary, Alberta, Canada T2N 1N4

a r t i c l e

i n f o

Article history: Received 17 July 2008 Received in revised form 24 March 2009 Accepted 27 March 2009 Keywords: Ecological restoration Monitoring program Wetlands Change Yellow River Delta

a b s t r a c t Long-term monitoring is essential to evaluate the effects of wetland restoration projects. A monitoring program before and after restoration has been carried out in the study area located in the Yellow River Delta since 2001. Water quality, soil salinity, soil organic matter, plant community, and bird species were chosen as indicators in this program. During the past seven years, the restored wetland showed increasing efficiency in reducing water pollution levels. Soil quality was constantly improved through salinity reduction and soil organic matter accumulation. The vegetation community quickly re-established after the restoration was initiated in 2002. The restored vegetation communities provide favorable habitat conditions for birds and thirty-seven bird species were observed in October 2007. Based on Canonical Correspondence Analysis (CCA), plant species and vegetation community are mainly influenced by soil salinity and water depth. These indicate that conducting freshwater to the project area is an efficient measure for vegetation restoration. While monitoring results show that the restoration project had positive effects on the wetland ecosystem over the past seven years, two issues remain for future study: (1) the contribution of harvesting vegetation to stabilizing nutrient removal rate and the accumulation of soil organic matter in the soil; and (2) the effects of excessive propagation of Phragmites australis on spatial heterogeneity and plant diversity. © 2009 Elsevier B.V. All rights reserved.

1. Introduction It is estimated that more than half of the original wetlands in the world have been lost due to drainage projects and human development projects (Mitsch, 2005; Mitsch and Day, 2006). Fundamental changes in riverine inputs associated with local landscape alterations have led to an undermining of historical ecosystem functions (Teal and Weisha, 2005; Simenstad et al., 2006). Wetland protection and function remediation, restoration of wetland supporting aquatic environments have become vital areas for further study (Mitsch, 2005). Effective restoration of damaged and degraded wetlands through adaptive management is urgent, because of intensifying anthropogenic pressures on natural ecosystems (Zedler, 2001; Bruland and Richardson, 2005; Hopfensperger et al., 2006; Orr et al., 2007). In the last decades, wetland restoration activities have been undertaken in many inner and coastal regions (Gray et al., 2002; Gilbert et al., 2004; Konisky et al., 2006). Typically, wetland restoration focuses on restoring three key components—hydrology,

∗ Corresponding author. Tel.: +86 010 58802079; fax: +86 010 58802079. E-mail addresses: [email protected], [email protected] (B. Cui). 0925-8574/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.ecoleng.2009.03.022

biology and soil—of wetlands. Detailed investigation of these components of a target ecosystem and how they change during ecosystem development is required. These changes include hydroperiods and water chemistry (Bossio et al., 2006; Wilcox et al., 2006; Niedermeier and Robinson, 2007), wildlife habitats (Zedler and Kercher, 2005), vegetation composition and structure, percent cover, biomass, plant diversity associated with re-establishment of species (Phinn et al., 1999; Walker et al., 2004; Jin, 2008), soil microbial communities, and functioning soil propagule bank (Grandin, 2001; Smith et al., 2002; Ghorbani et al., 2003; Robertson and James, 2007). The objective of wetland restorations is to re-establish the ecological functions and the links between the biotic and abiotic components (Loomis et al., 2000; Zedler, 2000; Ruiz-Jaen and Aide, 2005; Gallego Fernandez and Garcia Novo, 2007), and to promote local biodiversity at all levels by considering the entire ecosystem and not just some parts or certain species group. Restoration implies restating prevailing ecological interactions, rebuilding morphology through self-organizing systems, and waiting for species dispersion to form adequate habitats (Gallego Fernandez and Garcia Novo, 2007). Wetland restoration is a systematic process (Kirk et al., 2004). Measurements of vegetation combined with measurements of soils

B. Cui et al. / Ecological Engineering 35 (2009) 1090–1103

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Fig. 1. Location of the Yellow River Delta and wetland restoration project area. The Delta is located at the coast of Bohai Sea, with an area of 1530 km2 . The project area lies on the south bank of the Yellow River. Twenty sampling sites were selected to test change of soil and plant characteristics after the restoration project.

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and hydrologic characteristics are widely used for wetland assessment (White and Walker, 1997; McCoy and Mushinsky, 2002; Neckles et al., 2002; Wilkins et al., 2003; Breauxa et al., 2005). However, post-restoration monitoring is usually limited to cost, time, and lack of experienced investigators. The collected data are rarely published (Zedler, 2000). Furthermore, estimating some attributes often requires detailed long-term studies, but the monitoring phase for most restoration projects was less than 5 years (Ruiz-Jaen and Aide, 2005). Therefore, there is a need to further develop, refine, and disseminate site and landscape-level monitoring methods (Simenstad et al., 2006; Tuxen et al., 2007) and trail restoration processes. The Yellow River Delta Nature Reserve (N37◦ 35 –38◦ 12 , E118◦ 33 –119◦ 20 ) is located in the estuary of the Yellow River in Dongying City, Shandong Province, China (see Fig. 1). It has warm temperate continental monsoon climate with distinctive seasons and rainy summer. The annual average temperature is 12.1 ◦ C, the frost-free period lasts 196 days, annual average rainfall is 551.6 mm, evaporation is 1962 mm, and the drought index is up to 3.56. The area of perennial waterlogged wetlands including rivers, lakes, estuary waters, pits and ponds, reservoirs, channels, salt lakes, shrimp and crab pools, and tidal flats is 964.8 km2 , accounting for 63.06% of total area of the Yellow River Delta. The area of seasonal waterlogged wetlands (i.e. heavily saline-alkalized wetlands in supratidal zones, Phragmites australis swamps, other swamps, woodlands, shrub wetlands, wet meadows, and rice fields) is 565.2 km2 , accounting for 36.94% of total area. Every year, approximately 1.05 × 107 tons of sand and soil are carried by the river from upstream and deposited in the delta where the flow rate slows down resulting in vast area of floodplain and special wetland landscape (Xu et al., 2002; Wang et al., 2004a,b). The wetland hydrological characteristics are affected by the interactions between freshwater and seawater and between groundwater and surface water due to the low elevation (generally below 10 m except for roads and dikes) and being near the sea. Environmental attributes are characterized as significant spatial variation of habitats which therefore can be occupied by different species. Wetlands in the Yellow River Delta support a wide variety of flora and fauna. Two hundred and twenty different kinds of plant species including national priority protection species, wild soybean (Glycine soja Siebold & Zucc.), are found in this area. There are more than 800 animal species, consisting of 199 kinds of birds: 7 of them are first-class protection bird species defined by the government such as red-crowned crane (Grus japonensis) and oriental white stork (Ciconia boyciana), as well as 31 second-class protection bird species. The Yellow River Delta has become an important over-wintering and breeding site for migrating birds in Northeast Asian Inland and Western Pacific Rim. In recent years, low flows of the Yellow River have led to a decrease in water supply to the wetlands. As the second largest river in China, annual runoff of the Yellow River showed great interannual changes since 1980s (see Fig. 2). In 1983, runoff of this river reached its maximum value of 49.1 billion during this period. After that, it decreased and fluctuated at 20.0 billion m3 in following several years. This trend continues till 1997, when runoff reached its lowest level of 18.8 billion m3 of this period. From 1997 to 2002, annual runoff of this river was mainly below 10.0 billion m3 except for that in 1998. The Yellow River Delta is also a famous oil production base in China. Significant roads were constructed between the river and wetlands in recent years. After that, water supply to the wetland was stopped due to these road constructions. As a result, natural hydrological relationships between the river and its floodplain were seriously destroyed. These two stressors led to substantial salinization in this region, which in turn induced the degradation of both wetlands and bird habitats (Fig. 3).

Fig. 2. Annual runoff of the Yellow River from 1980 to 2007 (Lijin hydrographic station) and amount of freshwater diverted to the wetland from 2001 to 2007. Runoff of the Yellow River decreased severely from 1997 to 2002 and led to serious wetland degradation in the Yellow River Delta. After the restoration project, freshwater was pumped annually to degraded wetlands.

Fig. 3. Channel and sluices used to induct water from Yellow River to project area.

After 2002, due to scientific management strategies of the Yellow River, its runoff stopped decreasing and increased to 18.0 and 19.0 billion m3 in 2003 and 2004, respectively. In the following years, runoff of the river stabilized at 20.0 billion m3 , making it possible to provide sufficient water for wetland restoration from this river. In order to improve the wetland functions and protect the natural habitat for rare birds, a restoration project was implemented for the region governed by Dawenliu Management Station in the Yellow River Delta Nature Reserve in July 2002. The position of this project is 4 km south of the current channel of the Yellow River, and 15 km west of the estuary. Its central geographic coordinates are N37◦ 45 48 and E119◦ 03 07 . The restoration region is selected as the study site of this research. A monitoring study was implemented along with the restoration project. In our study, the data associated with water quality, soil, vegetation, and associated bird development were collected in the past 7 years following wetland restoration. These data were used to (1) identify the changes of ecological attributes before and after restoration by comparing the datasets; (2) track the responses of some attributes to determine whether the annual changes of ecological performances are positive. These results benefit further refinements and improvements for management of wetland restoration in the future. 2. Restoration project design The main process of the restoration project was initially designed to bring freshwater to the wetland and resist saltwater intrusion, thus increasing the self-regulatory capacity of wetland


ecosystem. The general objective is that with the implementation of the project, the hydrological process will be improved and soil conditions, where salinization had constituted the primary threat to the freshwater wetlands, will provide suitable habitats for freshwater vegetation and birds. Specific objectives are set as given below. The region of wetland restoration project, covering an area of 50.24 km2 , was separated from the Yellow River by a road, which partly accounted for ecosystem degradation (see Fig. 1). The main restoration activities included the construction of dikes and bridges. Four reservoirs and one channel were dug to restore the wetland hydrological conditions. The dike, with the length 9 km, width 3.5 m, and 1.5 m in height, were constructed along the south side of project area. It was designed to prevent seawater from invading the study area. In the Yellow River Delta, high tidal level generally varies between 2.7 and 2.9 m, the dikes were then built at 3 m contours. A channel with the length of 2.5 km was dug between the river (Yellow River) and the wetlands in the western side of the study area (Fig. 1). Freshwater was directed to the wetlands through this channel. The restored wetlands were then connected with the river by the channel, thus establishing hydrological relations between the river and project area. In consideration of ecological water requirement, evaporation as well as precipitation in the project area, this project planned to divert 3 million m3 freshwater to the wetland. In 2002, 1.41 million m3 water was pumped to the wetland. In following 5 years, 3.10, 2.88, 3.32, 3.07, 3.16 million m3 water was pumped to the wetlands separately. During this study, discharge flow at the inflow sluice varied between 8000 and 12,000 m3 /d, and 1000–4000 m3 /d at the outflow sluice. Four newly constructed reservoirs located in the west of restoration area were constructed and offered proper breeding habitats for waterfowls. Hydrological conditions in the project area were completely changed after 2002. Sufficient water supply led to large areas of surface water. Due to the variation of diverted freshwater amount as well as the elevation of this area, water depth is different in all 20 sampling sites. In 2007, water depth in the project area varied from 0.00 to 1.02 m (see Fig. 4). As the study area is located at the junction of land and sea, the natural conditions varied significantly over time. Engineering methods alone cannot provide adequate protection to the wetlands. Management as an essential part of the project provides a reliable guarantee to maintain relative stability of hydrological conditions as well as reduces human disturbances. The freshwater replenishment for the restoration area mainly depends on precipitation and river water. The flow rate of the Yellow River significantly changes over time during one year and the corresponding water management measures have to be adapted. The quantity of runoff during the summer (from June to August) often represents about 58.8% of annual total flow rate of the Yellow River. Thus, sufficient water is available for replenishment to restore the wetlands in the summer. Comparatively, in dry seasons, i.e. autumn (September to November) and spring (March to May), less water flows into restoration area automatically and significant evapotranspiration also occurs in these periods. These two factors result in a vast area of saline soil in the study area. Therefore, management measures have to be adapted based on the variation of water body. When the water level in the river channel was low in the dry seasons, water was pumped from the river to the restored area through the channels. This work continued till the beginning of the rainy season when the water level was high enough to flow into the restored area automatically. Management measures can also reduce the disturbances of human activities to the restoration area. Agricultural cultivation activities, oilfield development, and road construction near the restoring wetlands had negative effects on the wetland restoration.

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Some measures were needed to minimize these human disturbances. First, strict regulation was established to prevent human and livestock from entering the study area. Secondly, the quantity of vehicles on the main road was limited to an acceptable number to reduce negative impacts. Hunting of birds and other wetland animals were forbidden to protect biodiversity of the restored wetlands. 3. Methods A monitoring program was carried out before and after the project in order to test the effects of restoration. This program started in 2001 and continued to track the restoration processes. Elements including water quality, plant communities, soil salinity, soil organic matter, as well as bird communities were chosen to reflect the effects of the restoration. These included both abiotic and biotic factors. A sample collecting plan for each element was also set. Water, soil, and plant samples are collected from March to November the following year. Plants grow well in this period. From December to next February, no samples are collected as the low temperature, while bird observation is conducted all round the year. Annual runoff data from 1980 to 2007 were obtained from LIJIN hydrological station. 3.1. Water sampling and testing River water entered the wetlands through a long channel, and then flowed into the southeast of the wetlands. Inflow sluice was constructed at the end of the channel, through which freshwater was inducted to the wetlands. Outflow sluice was constructed at the east side of the area. After passing through the study area, pollutants in the water would be degraded to a certain level by plants. Removal rate of the pollutants was influenced by flow rate, plant density, and contaminant concentration. Samples were collected separately at the inflow sluice and outflow sluice constantly every monitoring month since 2002. Pollutant concentrations in the inflow and outflow water were then compared. As the elevation in the project area is a little higher in northwest part (1–1.2 m) than that in southeast part (0.4–0.6 m), water automatically flows from west to east after being pumped into this area through the inflow sluice. Due to lower gradient of this area, water moved slowly. It was estimated that it would take 5–7 days for water to pass through the study area. So water samples were collected once a week simultaneously both at the inflow sluice and the outflow sluice and tested for water quality. In each sluice site, three samples were collected at a time using LIMNOS water sampler and the mean was used to represent the result. Twenty-four water samples (3 × 4 × 2) were collected each month. Three indicators, i.e. pH, total nitrogen (TN), and total phosphorus (TP), were selected to describe water quality of samples. The pH was analyzed with compatible pH meter in site, while TN and TP were analyzed in the laboratory. Samples were preserved in icebox to restrain microbial activities before experiment. TN and TP were tested using standard laboratory method (Nydahl, 1978; Gachter, 1992) and their respective average was used to represent the water quality. 3.2. Soil sampling and testing Soil samples were collected at fixed sampling sites each with the size of 10 m × 10 m (Fig. 1) every August. Twenty sample sites distributed uniformly over the study area were set to determine the vertical and horizontal salinity patterns. All these sites were marked with bamboo poles to record their locations. Five sampling spots (four corner parts and one center part) were chosen

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Fig. 4. Water depth of 20 sampling sites from 2001 to 2007. These data were collected together with plant sample collection in August every year. In each sampling site, five data were collected and averaged to represent hydrologic condition of that site.

11.4 7.2 6.4 13.3 11.5 13.1 ± ± ± ± ± ± 25.2 13.6 23.1 34.7 29.7 30.2 8.2 11.1 7.4 9.2 14.3 12.1 ± ± ± ± ± ± 22.3 28.5 18.7 21.1 25.9 26.5 1.79 1.34 0.47 1.56 2.11 1.76 ± ± ± ± ± ± 5.89 5.27 5.62 5.83 7.15 6.84 2.11 1.22 2.03 1.39 1.23 1.89 ± ± ± ± ± ± 5.32 4.89 6.04 5.54 5.77 6.16 0.5 0.6 1.0 0.6 0.6 0.8 ± ± ± ± ± ±

Outflow COD (mg l−1 ) (n = 24) Inflow COD (mg l−1 ) (n = 24) Outflow DO (mg l−1 ) (n = 24) Inflow DO (mg l−1 ) (n = 24) Outflow TN (mg l−1 ) (n = 24)

1.6 1.1 1.7 1.4 1.0 1.5 0.5 0.4 1.2 1.4 0.7 0.4 ± ± ± ± ± ± 2.6 2.9 3.2 2.3 1.8 2.1 0.09 0.02 0.05 0.66 0.11 0.08 ± ± ± ± ± ± 0.14 0.04 0.08 0.13 0.15 0.14 0.12 0.08 0.15 0.05 0.17 0.17 ± ± ± ± ± ± 0.21 0.17 0.23 0.35 0.31 0.28 1.13 1.54 1.22 0.76 1.77 1.14 ± ± ± ± ± ± 8.53 8.72 8.91 8.17 8.35 8.38 0.73 0.65 1.32 0.69 1.12 0.73 ± ± ± ± ± ±

The results showed an increase in pH, while TN and TP showed a noticeable reduction after water flowed through the wetlands (see Table 1). Compared with inflow water, pH of outflow water increased uniformly in the past several years, except for 2005. Moreover, the increased pH value exceeded 1 in the first three years after restoration. Both TN and TP concentrations in inflow water were reduced during the monitoring years. TP removal rate remained above 40% between 2002 and 2007, and reached its highest removal level of 76% in 2003. TN removal rate also maintained above 40% before 2007, with the maximum in 2003 when about 62% of TN was removed (see Fig. 5).

7.74 7.66 7.86 8.27 8.05 8.18

4.1. Water quality

2002 2003 2004 2005 2006 2007

4. Results

Inflow TN (mg l−1 ) (n = 24)

Analysis of water characteristics, soil salinity, soil organic matter, vegetation patterns, as well as bird species were performed using SPSS statistical software. Repeated Measures ANOVA method was employed to analyze the variation of surface soil salinity after restoration. In order to illustrate horizontal soil salinity pattern, inverse distance weight (IDW) interpolate method was used to describe spatial characteristics of soil salinity in different years. Salinity at each sampling site was calculated using ARCGIS Desktops Software 9.0. Canonical Correspondence Analysis (CCA) was conducted with CANOCO Windows 4.5 (Ter and Smilauer, 2002) to illustrate the correlations between environmental variables and species. pH, TN, TP, Cl− , K+ Ca2+ , Mg2+ , Na+ , SOM, and water depth (WD) were selected as environmental variables in this analysis.

Outflow TP (mg l−1 ) (n = 24)

3.5. Data analysis

Inflow TP (mg l−1 ) (n = 24)

Birds were observed every month from 2001 to 2007. Three sites located in the south and east of the study area were selected. In each site, bird behavior was observed for approximately 3 h per day, after sunrise. Each observation lasted for 15 min with a 10 min interval. The birds presented at each site were counted and recorded using both sight and telescope. All the records of three sites for the same month were put together and averaged to represent birds’ appearance in the whole study area.

Outflow pH (n = 24)

3.4. Bird observation

Indexes

Vegetation samples were also collected in August every year because plants grow well and can be easily identified in this period. Similar to soil sampling, vegetation samples were obtained at 20 fixed sampling sites. At each site, five 1 m × 1 m spots were set where soil samples were collected to get plant information. As a result, 100 spots (5× 20) were selected every time. Several parameters such as type and quantity of constructive species, plant cover and height were recorded to reflect the vegetation characteristics. The mean of the data in five spots were used to represent the information in each site and the annual information was represented by averaging the mean in 20 sites.

Inflow pH (n = 24)

3.3. Vegetation sampling

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Years

in each site. Soil samples from three different depths, i.e. 0–20, 20–40, and 40–60 cm, were collected at each sampling spot. As a result, 300 samples (3 × 5 × 20) were obtained every year. All samples were air dried and sieved to obtain the ≤2 mm fraction. The measured soil features included soil salinity, soil organic matter (SOM) (Westerman, 1990), Cl− , K+ Ca2+ , Mg2+ , and Na+ (Soltanpour and Schwab, 1977).

Table 1 Inflow and outflow water features from 2002 to 2007. Three water samples were collected using LIMNOS water sampler were collected once a week simultaneously both at the inflow sluice and the outflow sluice from March to November. Samples in each year were averaged to demonstrate change of water features. Normally, flow rate of the inflow sluice was about 8000–12,000 m3 /d, and about 1000–4000 m3 /d at the outflow sluice.


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Fig. 5. TN and TP removal in the study area from 2002 to 2007. Water samples were collected from both inflow sluice and outflow sluice to calculate nutrients removal.

4.2. Soil salinity and organic matter Soil samples collected at the depth of 0–20 cm where soil conditions significantly influence the plant growth were used to illustrate soil improvement (see Table 2). Soil salinity level reached a maximum in 2001 before restoration. In the following years, it decreased constantly with a rate more than 70% of that in 2001 and there is a slight fluctuation in the last three years. In addition, the anions and cations associated with soil salinity also indicated a similar reduction trend which provided a favorable condition for freshwater vegetation (Table 3). In order to illustrate the improvement in top soil over the whole area, the data from 2001 to 2007 were selected to represent horizontal soil salinity distributing patterns by using IDW inter-plot method. The results showed that top soil salinity in most of the area continued to decrease in the past several years (see Fig. 6). In 2001, the soil salinity for most part of this area was above 10 g/kg, with the highest level up to 21 g/kg in northwest part. In 2005, soil salinity in most of the study area fell below 6 g/kg, and this trend continued till 2007. Generally, soil salinities in western and eastern part of the study area were higher than that in the central part (see Fig. 6). Surface soil patterns in different years after restoration were compared with that in 2001 to describe the change of soil salinity. Results of Repeated ANOVA method showed significant difference of soil salinity after the project. However, desalinization process in this area was not continuous. Mean difference between 2006 and 2001 decreased to 10.970 compared with that between 2005 and 2001. This result revealed salinity accumulation in 2006 (Fig. 7). Soil salinity changes in different depths over time were shown in Fig. 5. Fig. 5 shows that soil salinity tends to increase along soil depth, and the level in the third layer (i.e. between 40 and 60 cm) was much greater than that in the first layer (i.e. between 0 and 20 cm) and middle layer (i.e. between 20 and 40 cm). Soil salinity was reduced constantly in the first and middle layers in the last seven years, with a slight fluctuation in the third layer. The reduced rate of soil salinity was above 70% in the first layer from 2001 to 2007, and about 45% in the middle layer in the same period. According to statistical analysis (see Table 4), standard deviation (SD) of the first layer was 4.4 and the middle layer was 6.2 which showed the significant difference in this layer. While in the third layer, the SD was 1.8 indicating a slight variance of soil salinity. It is clear that soil salinity at the depth from 0 to 40 cm (first and middle layers) was significantly altered than that in the third layer during restoration.

Fig. 6. Spatial distributions of surface soil salinity from 2001 to 2007. Samples of each sampling site were used to forecast spatial characteristics of soil salinity in the whole area. Inverse distance weight interpolate method was used in this study.

Soil organic matter (SOM) showed a descent trend along with soil depth (Fig. 8). In general, SOM in all three layers increased continuously during the past seven years, especially in surface soil layer. In 2007, SOM accumulated to high level of 17 g/kg in the first layer, with an increase of 38% compared with that of in 2001. While SOM in the second layer increased by 47% from 6.7 to 9.85 g/kg.

Fig. 7. Soil salinity (with standard deviation) of different depths from 2001 to 2007. Soil samples were obtained from three layers of five sampling points in each sampling sites. Average value was used to demonstrate change of soil salinity after restoration.


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Table 2 The salinity change of top soil for project area in monitoring years. Averaged values with standard deviation were used to show soil salinity characteristics in each year. Cl− (g/kg) 2001 2002 2003 2004 2005 2006 2007

1.74 1.52 1.03 0.86 0.57 0.62 0.49

± ± ± ± ± ± ±

0.33 0.21 0.07 0.25 0.14 0.11 0.17

Mg2+ (g/kg) 1.80 1.70 1.31 0.99 0.67 0.58 0.52

± ± ± ± ± ± ±

Ca2+ (g/kg)

0.12 0.37 0.19 0.18 0.14 0.05 0.21

2.28 2.33 1.77 0.85 0.60 0.44 0.57

± ± ± ± ± ± ±

K+ (g/kg)

0.76 0.43 0.56 0.31 0.26 0.12 0.22

0.055 0.080 0.050 0.040 0.030 0.020 0.020

± ± ± ± ± ± ±

Na+ (g/kg) 0.023 0.017 0.006 0.011 0.015 0.011 0.015

1.21 0.99 0.90 0.59 0.42 0.51 0.35

± ± ± ± ± ± ±

0.12 0.23 0.29 0.14 0.19 0.22 0.18

Total salinity (g/kg) 15.3 11.0 7.2 5.5 3.6 4.4 3.9

± ± ± ± ± ± ±

3.3 4.3 2.5 4.2 1.2 2.4 1.7

Table 3 Results of repeated measures ANOVA of surface soil salinity from 2001 to 2007. Degree of freedom of this study is 19. Features

Years

Mean difference S.E. p Value a

2001 vs 2002

2001 vs 2003

2001 vs 2004

2001 vs 2005

2001 vs 2006

2001 vs 2007

4.3015a 1.109 0.001a

8.020a 0.680 0.000a

9.615a 0.839 0.000a

11.515a 0.699 0.000a

10.970 0.754 0.000a

12.986a 0.746 0.000a

This means difference is significant at the 0.05 level.

Table 4 Statistical analysis of average soil salinity (g/kg) and average soil organic matter in different layers over past seven years.

Although the middle layer showed the highest increase by 48% in 2007 compared with that of in 2001, its SD was moderate.

Depth

4.3. Plant communities

Features Soil salinity

0–20 cm 20–40 cm 40–60 cm

Soil organic matter

Mean

SD

Mean

SD

7.45 25.36 30.97

4.4 6.2 1.8

14.62 7.77 6.21

2.52 1.34 0.33

Compared with above two layers, SOM in the third layer increased at relatively lower speed. From 2001 to 2007, SOM of this layer increased from 5.1 to 5.8 g/kg. SOM at different depths showed various responses to the restoration. This can also be indicated by statistical analysis in Table 4. SD of SOM decreased constantly along soil depth. In the first layer, SD reached 2.52 indicating an obvious spatial variance of SOM in the study area. According to statistical analysis, SOM in the first layer was significantly changed than in other two layers. On the contrary, the third layer shows the least change occurred in the past seven years with SD equal to 0.33.

Significant changes of macrophyte community represent the improvement of biodiversity and plant cover in the past several years (Fig. 9). In 2001, only eight terrestrial species and few aquatic species were found in the project area. Due to the high soil salinity and lack of freshwater, plant communities were characterized as lower biodiversity. Even though, several habitats exist in the study area, there are no plants. Comparatively, saline vegetation, such as Tamarix chinensis Lour was found to distribute wildly with high density and plant cover. Other saline vegetation, for example, Imperata cylindrica var. major, Suaeda heteroptera, and I. cylindrica var. major, were typical species before restoration. However, some typical aquatic species such as P. australis (L.) Trin distributed fragmentarily with low density and cover in the project area. There is a significantly different landscape with various species in the plant communities after restoration (Fig. 10). P. australis (L.) Trin and abounding Typhacattail silvergrass become the dominant species in aquatic plant communities. New species such as G. soja Siebold & Zucc., Polygonum hydropiper, Echinachloa crusgallii were identified. The appearance of new species indicates an improvement of biodiversity. S. heteroptera Kitag and Tamarisk chinensis were also found in many sampling sites indicating a community succession from saline vegetation to aquatic community. Biodiversity was continuously enhanced as a result of improved environmental conditions. For example, 14 and 18 species were identified in 2003 and 2007, respectively. 4.4. Bird species

Fig. 8. Soil organic matter (with standard deviation) of different depths from 2001 to 2007. Soil samples were obtained from three layers of five sampling points in each sampling sites. Average value was used to demonstrate change of soil organic matter after restoration.

In the past seven years, birds were observed based on the frequency of appearance in the sampling sites. Bird species was used as an indicator to represent habitat improvement after restoration. As described in Fig. 9, about 10 types of bird species were observed in different months in 2001, and the highest level was recorded in July. At the first four years after restoration, the amount of bird species fluctuated slightly around that in every month of 2001. However, the observed bird species were quite high in 2006 and 2007 and with the maximum observed in October (see Fig. 11).

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Fig. 9. Change of plant community of the project area after restoration. Before the project was carried out (2002), wetlands degraded seriously with large areas of barren land (a). After restoration (b, 2006), hydrologic links was rebuilt between the Yellow River and wetlands. Plant community shifted from halophytic vegetation to hygrophilous vegetation.

5. Discussion Wetland restoration has been developed in many countries as people come to realize the important functions of wetland ecosystems (Klotzi and Gootjans, 2001; Morgan and Short, 2002; Shuman and Ambrose, 2003; Khan et al., 2004; Aldous et al., 2005). As shown in the aforementioned results, both biotic and abiotic aspects of the degraded wetlands were constantly improved by a natural process under human management. Aquatic vegetation communities colonized quickly after soil salinity was reduced by freshwater, thereby providing good shelter conditions and food resources for birds. Besides the improvement of ecosystem structure, the wetlands also contribute to the potentiality of nutrient retention which implies the enhancement of wetland functions. It has been proved by many wetland restoration practices, re-establishment of water regime and then relying on natural colonization is an effective way for wetland restoration (NRC, 1992; Galatowitsch and van der Valk, 1996). Useful experiences from this wetland restoration project can

Fig. 10. Plant species in the project area from 2001 to 2007. Plant samples were collected in every August. Every year, plant cover of each species was averaged among twenty sampling sites to demonstrate plant community style of that year.

be employed to guide other similar restoration projects such as floodplain and estuary wetlands. 5.1. Nutrient retention One important objective of wetland restoration is set to control water nutrients in many practices (Zedler, 2000; Arheimer and Wittgren, 2002; Green and Galatowitsch, 2002; Aldous et al., 2005; Orr et al., 2007). Nutrient concentration in water can be increased by human activities. Major sources of nutrients include runoff from agricultural areas (e.g. fertilizers), urban stormwater, municipal and industrial wastewater, eroded soils, and aquaculture. Nutrient concentration is a crucial indicator of water quality. The process of a water body becoming rich in dissolved nutrients is referred to as eutrophication (Richardson, 2006). In this research, restored wetlands exhibited an effective function in reducing TN and TP concentrations which are two primary contributors to eutrophication. Nutrient retention was influenced by a variety of factors such as plant density which vary from one place to another (Woltemade and Woodward, 2008). As a result, the removal rate is significantly different from various kinds of wetlands (Hansson et al., 2005). Christopher and Jinnieth (2008) showed that the inflow concentration, age of wetland, and plant were closely related to removal

Fig. 11. Birds species observed in the project area from 2001 to 2007. We collected bird data in three different sites in the project area. Averaged data of the three sites were used to demonstrate bird community of every month.

B. Cui et al. / Ecological Engineering 35 (2009) 1090–1103 Table 5 Results of correlation analysis between nutrient content removal and inflow concentration, age of wetland, cover of Phragmites australis. Factors

TN removal

TP removal

Correlation

p Value

Correlation

p Value

Inflow concentration Age Phragmites communis cover

−0.527 −0.586 0.532

0.283 0.221 0.277

0.022 −0.29 −0.14

0.966 0.957 0.791

potency of nutrients. However, as indicated by Hansson et al. (2005), the contributions of these factors to pollutant removal are still not clear. No obvious correlation was found on the basis of the statistical analysis shown in Table 5. Factors that influence the nutrient retention require further investigation in the future. In this research, nutrients were effectively reduced by restored wetlands. After re-establishment of hydrological connection between the river and wetlands, water was directed to the project area. The restored wetlands play an important role in reducing pollutants. The removal rates of TN and TP showed similar trend. In the first year after restoration, TN and TP were reduced by more than 60%, which is very efficient compared with the results from the literature (Seabloom and van der Valk, 2003; Hansson et al., 2005; Hoffmann and Pedersen, 2007). In the following years, the removal rate fell slowly and became stable. This phenomenon has also been observed in other practices of wetland restoration (Koottatep and Polprasert, 1997; Fink and Mitsch, 2004). This can be explained by the fact that the newly colonized macrophyte communities significantly absorbed the nutrients from the water and induced higher reduction rate of nutrients in the beginning. The dynamics of vegetation community then became stable and the decomposition of dead plants led to another source of nutrients in the last several years. The removal rate of TN and TP tended to be more stable during monitoring years than that of other studies (Arheimer and Wittgren, 2002; Hansson et al., 2005). Another important reason is that the vegetation in the project area is reaped every year, thus maintaining a constant need of nutrients for plants (Koottatep and Polprasert, 1997). The results show that it is necessary to remove plants away from the wetlands in order to obtain higher efficiency of nutrient retention (Table 6). The pH of inflow water showed a trend of basification as the water passed through wetlands. It can be explained that salinity was continuously dissolved into the inflow freshwater and then was taken out of the soil (Bruelheide and Udelhoven, 2005). In the last three years, pH of water increased less than that in the first three years. This indicated a balance between salinity dissolution and accumulation. This result was also proved by other soil salinity analysis (Huckle et al., 2000; Jafaria et al., 2004; Wang et al., 2007). Table 6 Eigenvalues, species–environment correlations and cumulative percentage variance for the first two axes of CCA. Axes

Eigenvalues Speciesa –environment correlations Cumulative percentage variance of species–environment relation

1

2

3

4

0.665 0.931 44.1

0.401 0.874 70.7

0.200 0.897 83.9

0.108 0.930 93.1

a Species: Phragmites australis (L.) Trin (PCT), Suaeda heteroptera (SH), Tamarix chinensis Lour (TCL), Cyperus L. (CL), Miscanthus sacchari florus (MSF), Imperata cylindrica var. major (ICV), Limoninum bicolor Bunge (LBB), Herba Artemisiaee annuae (HAA), Glycine soja Siebold & Zucc. (GS), Cynanchunmchinenss R.Br (CRB), Aeluropus Litoralis Parl (ALP), Lepiironia rticulata (LR), Echinachloa crusgallii (ER), Polygonum hydropiper (PGH).

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5.2. Soil salinity and soil organic matter Soil was characterized with high salinity as many other estuaries (Funk et al., 2004; Hsieh, 2004; Yao and Yang, 2007). The surface soil salinity on average reached 1.05% in this study area. Shallow ground water, seawater intrusion, and strong evaporation significantly contribute to soil salinization (Hsieh, 2004; Fang et al., 2005; Silvestri et al., 2005). Water regime is the crucial factor influencing the spatial characteristics of soil salinity. There is higher salinity near the coast. In the highland and floodplain where the freshwater dominates the water regime, soils are characterized by low salinity (Wang et al., 2004a,b; Traut, 2005). In the perpendicular direction, soil salinity varied after water flow. In the dry season from November to May of next year, soluble salts in groundwater are carried to the surface in the form of capillary water, then water evaporates and salinity is left in the top soil. Without rainfall or surface flow, this process will continue and result in salinization. During the summer, top soil salinity will be washed away by rainfall or flood (Mahal and Park, 1976; Guan et al., 2001; Li, 2001; Wang et al., 2007), thus leading to desalinization in the surface soil. During restoration, freshwater was conducted to the wetlands and provided a continuous surface flow. Soil salinity distributions in the whole area and in perpendicular direction were all significantly altered (Figs. 4 and 5). Soil salinity had been decreasing in the past seven years. Soil can be categorized in five levels considering its salinity (g/kg), based on China coastal saline soil classification standards (Wang et al., 1993), i.e. un-salinized soil (soil salinity < 1 g/kg), slightly salinized soil (1 g/kg < soil salinity < 2 g/kg), moderately salinized soil (2 g/kg < soil salinity < 4 g/kg), severely salinized soil (4 g/kg < soil salinity 6 g/kg). According to this standard, top soil was classified into moderately salinized level in 2005 and 2007. Soil salinity below 20 cm fell into the level of completely salinized soil. For soil under 40 cm, soil salinity is about 30 g/kg and keeps almost constant. Soil salinity in the top soil was significantly improved, while soil salinity in the other two layers was still high. This indicated that freshwater flow mainly influenced the salinity in the top soil (above 20 cm) by washing them away from the project area, while salinity migration to the ground water was relatively limited due to the high ground water level which prevented surface flow moving downward (Redfield, 1972; Pennings et al., 2004). Although the salinity in the top soil was reduced after freshwater was directed into the wetlands, this area was still threatened by salinization. Soil salinity was not stable even in the top soil, for example, the average salinity in the top soil raised slightly in 2006 than that of in 2005. Salinization and desalinization keep a dynamic equilibrium which varies according to water regime. Once the freshwater replenishment is not sufficient, soil salinity will rise again. SOM refers to all organic substances within the soil from biologic components of the ecosystem without living roots and animals. It provides nutrients and feasible environmental conditions for plants and micro-organisms (Eswaran et al., 1993). SOM is often used as an important indicator to reflect soil fertility (Cowie and Hedges, 1994; Rasmussen et al., 2006). Few studies have been implemented to investigate the SOM in the Yellow River Delta so far. SOM increased steadily in all three layers after restoration and its change in the top soil was obvious. Large amounts of freshwater provided to the wetland after restoration led to significant areas of surface water (see Fig. 4). After 2002, most of the sampling sites were found to be inundated. This may be the reason for organic matter accumulation. In continuous inundation condition organic matter decomposition rates are slower than those in aerobic soils. As a result, organic matter in soils or sites that remain flooded accumu-

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late quickly (Sahrawat, 2003). SOM showed little difference below 40 cm because the surface SOM mainly comes from the decomposition of dead vegetation. Organic matter in deeper layers came from the decomposition of plant root while the roots of most plants in this area mainly exist above 40 cm (Shen et al., 2005; Trumbore et al., 2006). Although SOM was significantly improved, it was still at a low level (Eswaran et al., 1993; Chen et al., 2007a,b). With the introduction of water from the Yellow River, most parts of the project area are covered by thick infertile sediment which may account for the low content of SOM. Deficiency of SOM was another major characteristic in the Yellow River Delta due to shortage of new soil and scantiness of plantation accumulation. Reeds are reaped every year in order to move the nutrients from this area which results in low SOM. A balance between nutrient removal and organic substance accumulation needs to be considered when choosing the restoration measures. 5.3. Vegetation Water regime is a crucial factor that influences the dynamics of vegetation community (Merendino and Smith, 1991; Kindscher et al., 2004). Vegetation started to colonize quickly after restoration. This process is noticeable in the first three years (Budelsky and Galatowitsch, 2000) and will reach stability after a long time (Warren et al., 2002). In the past seven years, an obvious vegetation transformation was observed. P. australis became the constructive species instead of T. chinensis. In order to identify the factors that influence vegetation colonization, Canonical Correspondence Analysis (CCA) was used to illustrate species and community characteristics subject to different environmental variables in 2007. As shown in Table 3, the first two axes represent 70.7% of the correlation between species and environment which indicates that CCA is a reasonable method in this research. Biplots of species and environmental factors and samples and environmental factors were drawn to illustrate their relations. In biplots of CCA analysis, environmental factors like water depth (WD) and pH and other factors are exhibited by lines with arrow. Length of each line indicates the relationship between environmental variables and species (Fig. 11a), or between environmental factors and samples (Fig. 11b). Characteristics of correlations between those environmental factors and each ordination axes were indicated by quadrants where each arrow was placed. For example, line of pH was placed in the second quadrant, indicating a positive correlation with the vertical axis and a negative correlation with the horizontal axis. Angles between lines and axes indicate degree of correlations; with small angles indicating higher degree of correlations. According to CCA analysis, the vertical axis shows salinity gradient, while the horizontal axis shows water depth gradient. Water depth (WD) and ions (represent soil salinity) were the most important factors that influenced both species and samples. These two factors both showed a gradient from low salinity to high soil salinity. Species fall into two major groups along the salinity gradient (Fig. 12a), the first group contains Aeluropus litoralis Parl (ALP), Phragmites communis (L.) Trin (PCT), I. cylindrica var. major (ICV), Cynanchunmchinenss R.Br (CRB), Miscanthus sacchari florus (MSF), and G. soja Siebold & Zucc. (GS) which are the typical aquatic species favoring low salinity. Another group suited to vegetate in the high salinity soils includes T. chinensis Lour (TCL), Limoninum bicolor Bunge (LBB), Herba Artemisiae Annuae (HAA), S. heteroptera (SH), Cyperus L. These plants can adapt to high soil salinity and are appropriate for growing in the soils with lower water level. Samples can also be divided into two groups (Fig. 11b). Sites of 5, 15, 16, 17, and 19 are characterized with low soil salinity and

Fig. 12. Biplots of species and environmental variables (a) and samples and environmental variables (b). In CCA analysis, characteristics of the relationships between those environmental factors and each ordination axes were indicated by quadrants where each arrow was placed. Angles between lines and axes indicate significance of co-relationship, with small angles indicating higher significance of co-relationship. Hollow circle and number in (a) represent sampling sites. In (b), for abbreviations: ALP, Aeluropus litoralis Parl; PCT, Phragmites communis (L.) Trin; ICV, Imperata cylindrica var. major; CR, Cynanchunmchinenss R.Br; MSF, Miscanthus sacchari florus; GS, Glycine soja Siebold & Zucc.; TCL, Tamarix chinensis Lour; LBB, Limoninum bicolor Bunge; HAA, Herba Artemisiae Annuae; SH, Suaeda heteroptera; CL, Cyperus L; EC, Echinachloa crusgallii; PGH, Polygonum hydropiper; LR, Lepiironia rticulata.

located at the south part of the project area where the elevation is low and can be easily reached by freshwater. In sites 6–8, 10, 12, and 13, the environmental conditions are suitable for halophytes. It is clear that species distribution is mainly controlled by soil salinity and water depth based on the analysis of CCA (Wu et al., 1994). WD and concentration of Cl− are significantly correlated (r = −0.91, p < 0.01) which indicates conducting freshwater to the project area is an effective measure for wetland restoration (Guan et al., 2001; Wang et al., 2007) (Fig. 13). In the past seven years, P. australis increased constantly in this area as soil salinity was reduced. Other species will suffer from intensified competition exerted by this species (Budelsky and Galatowitsch, 2000). It can be foreseen that P. australis will continue to increase in the project area. Green and Galatowitsch (2002) reported that an aggressive plant can impair the spatial heterogeneity and biodiversity of vegetation. The effects of the increasing P. australis on vegetation patterns and other wetland functions require further investigation.


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2006). Before restoration, there were only a few plant species in the study area and T. chinensis was the constructive species which provided poor habitats for birds (Ellis, 1995; Pallisson et al., 2006). After restoration, the improvement of ecological conditions provided favorable habitats for a variety of birds. More and more migrating and breeding birds including some rare species such as G. japonensis and C. boyciana appeared and bred in the study area. Birds are sensitive to environmental conditions (Burton et al., 2002; Steen et al., 2006; Antos et al., 2007; Cardoni et al., 2008). Based on the analysis results shown in Fig. 11, bird diversity shows positive correlation with wetland ages (R2 = 0.6406) and the cover of constructive plant, e.g. P. australis (R2 = 0.8843). However, no significant correlation was observed between bird species and plant species. In 2001, typical plant community was T. chinensis which was not suitable for birds to breed. Plant coverage was much lower in the study area due to the high soil salinity. Lower plant coverage failed to provide sufficient refuge for birds till 2 or 3 years after the restoration. After that, birds species steadily increased resulting from the improvement of inhabit conditions (Maurer and Heywood, 1993; Coppedge et al., 2006; Armitage et al., 2007). The components of bird species are subject to the process of wetland restoration. 6. Conclusions The restoration of hydrologic links between the Yellow River and the floodplain wetlands is an effective way to re-establish both ecosystem structure and functions in the study area. In the past seven years after the implementation of restoration project, an obvious improvement in soil chemical and physical conditions was observed in the study degraded wetland ecosystem. This facilitates the re-colonization of plants in this area. Restoration of ecosystem function was reflected by nutrient retention and increased flora and fauna species. Variation of ecological elements included in the monitoring program was analyzed in order to investigate their correlations. Soil salinity decreased constantly after the restoration, while soil organic matter maintained an increasing trend. Plant diversity was significantly influenced by water depth and soil salinity, and bird diversity positively correlated with P. australis cover. These results confirmed the necessity to re-establish the hydrological conditions and provided useful experiences for other wetland restoration projects in estuary areas. The effects of harvesting vegetation and excessive propagation of P. australis on spatial heterogeneity and plant diversity still require further investigation. Acknowledgements

Fig. 13. Correlation analysis between bird species and restoration years (a), Phragmites australis cover (b), and plant species (c). Total bird species of every year was used to identify possible influence factors.

5.4. Birds The improvement of water regime affected the breeding birds in the project area due to the changed breeding habitats resulting from vegetation development and transformation (Wan et al., 2001; Armitage et al., 2007; Forcey et al., 2007). Wetlands with more vegetation species and shallow water tend to attract more birds (Lindegarth and Chapman, 2001; Hoover, 2006; Riffell et al.,

The authors would like to acknowledge Juanzhang Lu, Yueliang Liu from the Yellow River Delta Management Bureau, Feng Lu and Lidong Wang from the Dawenliu Management station for their help in field work and the financial supports of the State Key Basic Research Development Program of China (973) (2006CB403303), National Natural Science Foundation (U0833002; 40571149). References Aldous, A., McCormick, P., Ferguson, C., Graham, S., Craft, C., 2005. Hydrologic regime controls soil phosphorus fluxes in restoration and undisturbed wetlands. Restor. Ecol. 2, 341–347. Antos, M.J., Ehmke, G.C., Tzaros, C.L., Weston, M.A., 2007. Unauthorized human use of an urban coastal wetland sanctuary: current and future patterns. Landscape Urban Plann. 80, 173–183. Armitage, A.R., Jensen, S.M., Yoon, J.E., Ambrose, R.F., 2007. Wintering shorebird assemblages and behavior in restored tidal wetlands in Southern California. Restor. Ecol. 1, 139–148. Arheimer, B., Wittgren, H.B., 2002. Modelling nitrogen removal in potential wetlands at the catchment scale. Ecol. Eng. 19, 63–80.

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