Shifts in characteristics of the plant-soil system associated with flooding and revegetation in the riparian zone of Three Gorges Reservoir, China

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Shifts in characteristics of the plant-soil system associated with flooding and revegetation in the riparian zone of Three Gorges Reservoir, China Chen Yea,b, Orpheus M. Butlerc, Chengrong Chenc, Wenzhi Liua,b, Ming Dua,b, Quanfa Zhanga,b,

⁎

a

Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China Center of Plant Ecology, Core Botanical Gardens, Chinese Academy of Sciences, Wuhan 430074, China c Australian Rivers Institute and Griffith School of Environment and Science, Griffith University, Nathan, QLD 4111, Australia b

A R T I C LE I N FO

A B S T R A C T

Keywords: Biogeochemistry Microbial community Recovery Revegetation Flooding regime

The operation of the Three Gorges Reservoir (TGR), the largest hydropower dam in the world, has triggered a dramatic shift in the flooding regimes of sites upstream of the reservoir. Little is known about how disrupted flooding regimes and consequent management approaches might affect the ecological and biogeochemical characteristics of riparian ecosystems. In this study, we evaluated the effects of disruptions to natural flooding regime on basic soil properties, soil nutrient and heavy metal levels, and key characteristics of riparian plant and soil microbial communities. To do this, we used an elevational gradient that encompassed four flooding duration zones (0 (i.e., control), 169, 237, 286 days of flooding per year on average). The disrupted flooding regimes were associated with levels of soil total N and P that were on average 17% and 24% lower, respectively, than those in the non-flooded areas. On the other hand, the concentrations of heavy metals (Hg, Pb, Cu, Zn and Mn) were higher in flood-affected areas than in the non-flooded areas. Increased flooding frequency was also associated with lower plant diversity and species richness relative to non-flooded areas. Thus, disruption of the natural flooding regime had strong and often negative consequences for the ecological and biogeochemical properties of the riparian ecosystems in our study. There was some evidence that riparian plant communities were able to partially recover from prior flooding during a single growing season, even after nine years of repeated flooding, and these recovery trajectories were associated with shifts in soil chemical properties during the same period. However, revegetation efforts had few effects on ecosystem properties or their recovery trajectories following flooding events, suggesting that natural regeneration could be a useful option for the management of these sites. We conclude that the unnatural flooding regimes associated with large scale reservoir development are likely to have profound impacts on the structure and functioning of riparian ecosystems, and these will pose a considerable challenge for environmental management and biodiversity conservation.

1. Introduction Human activities can severely disrupt the natural patterns and processes of flooding in riparian zones (Peralta et al., 2013), but the implications of disrupted flooding regimes for ecological structure and function are not well understood (Kayranli et al., 2010; Ruiz-Sinoga et al., 2012; Saint-Laurent et al., 2014). The effects of flooding on vegetation include plant mortality through physical, chemical, or biological processes, such as uprooting, soil loss through erosion, anoxic conditions, inhibited photosynthesis, and enhanced susceptibility to pathogens (Aerts et al., 2003; Sun et al., 2017; Xiao et al., 2017). These effects could lead to declines in species richness and diversity after floods, particularly when coupled with the rapid post-flood regrowth

exhibited by some plant taxa (Smith et al., 1998; Bagstad et al., 2005). Moreover, changes in flooding regime can transform the biogeochemical characteristics of the plant-soil system (Tian et al., 2010), and these changes may further affect or regulate the effects of flooding on vegetation, soil microbes, and the feedbacks between above- and belowground biological communities (Rokosh et al., 2009; Ye et al., 2018). Plant and microbial communities have developed various strategies to respond to or recover after flooding (Schreiber et al., 2011; Ye et al., 2018), and the nature of these responses could influence ecological properties and processes in flood-affected environments. For instance, Jackson and Armstrong (2008) showed that plants formed aerenchyma with large air spaces, allowing greater gas diffusion to better cope with submergence. Similarly, soil microbes exhibit a high degree of

⁎ Corresponding author at: Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan 430074, China. E-mail address: [email protected] (Q. Zhang).

https://doi.org/10.1016/j.geoderma.2019.114015 Received 27 March 2019; Received in revised form 8 October 2019; Accepted 15 October 2019 0016-7061/ © 2019 Elsevier B.V. All rights reserved.

Please cite this article as: Chen Ye, et al., Geoderma, https://doi.org/10.1016/j.geoderma.2019.114015

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Fig. 1. The study area (A) and water level from September 2016 to September 2017 (B) in the water-level-fluctuation zone of Thre Gorges Reservoir, China.

metabolic flexibility and physiological tolerance to withstand fluctuating environmental conditions (Meyer et al., 2004). Some authors have also argued that the recovery of plant and microbial communities following floods could be directly linked to biogeochemical processes (e.g., Kulmatiski et al., 2008). For instance, feedback relationships between soil properties and flooding might contribute to evolutionary processes in riparian zones, potentially resulting in a high proportion of flood-tolerant or flood-dependent vegetation and microbes (Sun et al., 2017; Ye et al., 2018). At the same time, the duration and depth of flooding have been shown to be important factors influencing the characteristics of riparian plant communities, soil microbes, and the physical and chemical properties of riparian soils (Aerts et al., 2003). Thus, the extent to which plant and microbial communities can recover from flooding likely depends on the strength and duration of the disturbance (Griffiths and Philippot, 2013; Karakoç et al., 2017). The response to flooding and subsequent recovery of riparian ecosystems is also heavily influenced by human management. The two main forms of management for ecosystem restoration are natural recovery, wherein ecosystems are essentially ‘left alone’ to recover over time, and active revegetation (Chazdon, 2008). The choice of management approach is influenced by the particular ecosystem and its

state of deterioration, along with government policy and economic concerns (Zhang et al., 2010). However, while numerous studies have compared these two management options (Langer et al., 2008; Zhang et al., 2011; Lennon et al., 2012), it is still unclear which is more likely to succeed under a given set of conditions. For instance, some work indicates that revegetation significantly alters soil properties and microbial community composition (Demoling and Baath, 2008; Zhang et al., 2011), while other studies found that revegetation contributed little to the recovery of plant and microbial communities after flooding (Bapiri et al., 2010; Lennon et al., 2012). Understanding how riparian vegetation and microbial communities respond to the altered flooding regimes associated with human development activities, along with the consequent management approaches, will prove essential to conservation of riparian ecosystems. One of the prime examples of development-driven shifts in flooding regime globally is the Three Gorges Reservoir (TGR) project in central China, which occupies a 600 km segment of the Yangtze River and with an area of 1080 km2 represents the largest hydroelectric project on Earth (Fu et al., 2010). The commencement of operation of the TGR in 2008 triggered a dramatic shift in flooding regime that has had important and ongoing implications for the ecology and biogeochemical functioning of 2

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riparian ecosystems along the Yangtze. For instance, the characteristics of the terrestrial vegetation community have been altered substantially since inundation, with annual plants such as Echinochloa crusgalli and Bidens tripartita and perennials including Cynodon dactylon now dominating many areas that were previously dominated by Setaria viridis, Leptochloa Chinensis, Digitaria ciliaris, Ficus tikoua, Cynodon dactylon, Pterocarya stenoptera, and Vitex negundo (Ye et al., 2013). To restore and protect riparian ecosystems throughout the TGR watershed, active revegetation has been carried out for at least 10 years. Flooding resistant plants like C. dactylon, Hemathria sibirica, Hibiscus syriacus, Morus alba, Salix variegate, Salix chaenomeloides, and Taxodium distichum were selected for this revegetation. The TGR catchment provides a unique scenario to investigate the effects of a disrupted flooding regime and consequent management approaches on the ecological and biogeochemical characteristics of riparian ecosystems across a 600 km stream gradient in a globally-significant river system. We hypothesized that: (1) the disrupted flooding regimes affect soil properties and the characteristics of plant and soil microbial communities; (2) the associated changes in environmental factors would influence the responses of plant and microbial communities to altered flooding regimes; and (3) different management approaches (active revegetation versus natural regeneration) in flood-affected riparian areas would have differing effects on ecological and biogeochemical properties. This work will help to develop ecological restoration strategies for the TCR region and elsewhere.

gradient, from 145 m a.s.l to 185 m a.s.l. Because flooding regime varies based on elevation, these transects allowed us to investigate the effects of flooding on ecosystem properties. Meanwhile, the soil properties were similar among elevations before the operation of TGR (Ye et al., 2015). Thus, we collected samples from four plots along the transects, representing the following elevation range and flooding regimes: (1) 145–155 m a.s.l., which is flooded 286 days per year on average (hereafter referred to as the ‘Extreme Flooding Zone’; ‘EFZ’); (2) 155–165 m a.s.l., which is flooded 237 days per year (Severe Flooding Zone; ‘SFZ’); (3) 165–175 m a.s.l., which is flooded 169 days per year on average (Moderate Flooding Zone; ‘MFZ’); and (4) 175–185 m, which has not been flooded since the establishment of the TGR (Non-Flooding Zone; NFZ). In June and September of 2017 when the reservoir’s water level was 145 m and the WLFZ was exposed to the air after submergence, we collected soil samples from each flooding zone at every site. Surface soil samples (0–20 cm) were collected to analyze soil physical and chemical properties and 0–10 cm and 10–20 cm layers of soil were sampled to investigate soil microbial community characteristics. We collected five topsoil samples from a 1 m2 plot at each flooding zone, and these were combined to give a single composite sample. At Banan, soils were collected from the MFZ and NFZ only, because the SFZ and EFZ were inundated during the sampling period (Ye et al., 2019a,b). Therefore, a total of 140 composite samples were collected and these were stored at 4 °C before chemical analysis.

2. Materials and methods

2.3. Field measurements and laboratory analysis

2.1. Site description

The vegetation attributes for each plot were quantified in June and September of 2017 and the detailed investigation method was described in Ye et al. (2019a,b). We identified the plants within the quadrats (5 m × 5 m) to species level according to Van der Meijden (2005) and then calculated species diversity based on the ShannonWiener heterogeneity index (H) (Shannon and Weaver, 1949). We used the Braun-Blanquet method to quantify species coverage (BraunBlanquet, 1932), and finally harvested all plants at soil level to measure the above ground biomass of vegetation in the plots. Analytical methods for soil nutrients and heavy metals were described in detail by Ye et al. (2012). Soil organic matter (SOM) was determined by potassium dichromate titrimetric solution with a method detection limit (MDL) of 0.5 mg kg−1. Total N was analyzed by the Kjeldahl method. Total and available P were measured by molybdenum-antimony anti-spectrophotometric method with a MDL of 0.01 mg L−1. The available P was extracted by 0.5 mol L−1 NaHCO3, which included soluble P, partly Ca-associated P, partly Al associated P and partly Fe associated P. Total K and available K were determined by flame photometric method with a MDL of 0.01 mg L−1. The available K was extracted by 1.0 mol L−1 CH3COONH4, which was the sum of exchangeable K and soluble K. To determine the contents of ammonium (NH4+-N) and nitrate (NO3−-N), 20 g fresh soil was extracted with 100 ml extractant (i.e., 0.4 M KCl) for 1 h, then the filtered solution was analyzed for NH4+-N and NO3−-N on the Skalar’s San++ continuous flow auto analyzer (Breda, Netherlands) (Keeney and Nelson, 1982) with a MDL of 0.05 mg L−1. Soil moisture and bulk density were determined gravimetrically by weighing fresh soils, oven-drying intact soil cores at 105 °C for 24 h, and re-weighing. Soil pH was measured at a soil-to-water ratio of 2:1 (by weight) with a Fisher Scientific AR15 (Waltham, MA) pH probe, and distilled water (pH value = 7) was used to leach soil samples in the measurement of soil pH. Soil particle-size was determined by the pipette sampling technique (sand: 2–0.05 mm; silt: 0.05–0.002 mm; clay: < 0.002 mm) (Saint-Laurent et al., 2014). To analyze As and heavy metals including Hg, Cr, Pb, Cu, Zn, Fe and Mn, total soil digestion was performed in Teflon vessels following the classical open digestion procedures with a mixture of concentrated HFHClO4-HNO3 (i.e., 10 ml HNO3, 5 ml HF and 5 ml HClO4) (Li et al., 2010). Content of As was determined by diethyl disulfide and

The TGR region (29°16′—31°25′ N, 106°—111°50′ E) lies in the main channel of the Yangtze River from Yichang to upstream Chongqing (Fig. 1). The climate in this region is classed as humid subtropical monsoonal. The average annual temperature ranges from 16 to 19 °C and total annual precipitation varies from 817 to 1361 mm. Around 80% of precipitation occurs between April and October (MEP, 2014). Soils in the region are classified as Entisols (Regosols in FAO taxonomy; purple soil, yellow soil and mountain yellow soil in the Chinese soil taxonomy; Ye et al., 2014). Detailed geomorphological characteristics of the TGR watershed have been described by Ye et al. (2013) and Bao et al. (2015). Following the completion of the TGR project in 2008, the water levels upstream of the reservoir fluctuate from 145 m a.s.l. in summer (May to September) to 175 m a.s.l. in winter (October to April). This ‘water level fluctuation zone’ (WLFZ) has an area of 1080 km2. Due to the inversion of flooding timing (from flooding in summer to flooding in winter) and the prolonged inundation duration since 2008, the number of plant species has declined sharply and the plant community is presently dominated by annual plants such as Echinochloa crusgalli and Bidens tripartita, with perennials such as C. dactylon and a few invasive species such as Eupatorium adenophorum and Alternanthera philoxeroides also present (Zhong and Qi, 2008). 2.2. Sample collection We established eighteen sampling sites along a 600 km gradient of the TGR catchment. This area encompassed fourteen counties, from upstream at Banan to the dam area at Zigui (Fig. 1). There were fifteen sampling sites situated in areas where no active efforts have been made to revegetate or rehabilitate the riparian ecosystems (referred to hereafter as ‘natural regeneration’ areas). At Zhongxian, Wanzhou and Lanlingxi we also established sampling sites in areas where active revegetation efforts have occurred to enable a comparison between natural regeneration and active revegetation approaches. Thus, there were eighteen sampling sites in total. At each sampling site we established a transect along an elevational 3

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(Butler et al., 2018). Where means were significantly greater than zero, the flood-affected zone was significantly more similar to the NFZ in September than in June, suggesting ‘positive’ recovery. Where means were significantly less than zero, the difference between the flood-affected zone and the NFZ was greater in September than in June, suggesting ‘negative’ recovery. Where means did not differ significantly from zero there was no recovery.

carbamate silver colorimetric method (DDC-Ag) with a MDL of 0.025 mg L−1, as recommended by the State Environmental Protection Administration of China (GB15618-2008) (SEPA, 2008). Concentrations of metals in solutions were determined using flame atomic absorption spectrometry (FAAS) (AAs vario6, Analytik Jena AG, Germany) for Pb, Zn and Fe with a MDL of 0.1 mg L−1 and the FAAS was also used for determining the contents of Cu and Mn with a MDL of 0.01 mg L−1 and for Cd with the MDL of 0.001 mg L−1, and cold vapor AAS for Hg with the MDL of 0.002 mg L−1 (Zhang et al., 2009). The abundances of fungi, actinomycetes, and culturable heterotrophic bacteria, were determined via plate counting. Plate counts of colony-forming units (cfu) of fungi were made on rose Bengal agar (Oxoid) amended with 30 mg L−1 streptomycin sulfate. Plate counts of colony-forming units (cfu) of actinomycetes were made on glycerol casein agar amended with 0.05 g L−1 cyclohexamide (Ye et al., 2014). Plate counts of culturable heterotrophic bacteria were made on tryptone soya agar (Oxoid, Basingstone, Hampshire, England) amended with 0.1 g L−1 cyclohexamide. Plates were inoculated with 100 μL of soil suspension and incubated at 25 °C for seven days, after which visible colonies of the micro-organisms were present. Control plates, containing the respective media but without any soil suspension, were also incubated to test for potential contamination effects. Concentrations of microbial biomass C (MBC) and N (MBN) in soil samples were determined using the chloroform fumigation-extraction method (Vance et al., 1987). In brief, three 5.0 g sub-samples of each soil sample were fumigated with ethanol-free chloroform at 25 °C for 24 h in an evacuated extractor. The fumigated soil samples, along with an equal number of corresponding sub-samples that had not been fumigated (i.e. controls), were then extracted with 20 ml 0.5-M K2SO4 by horizontal shaking for 1 h. Sample extracts were then filtered with Whatman 42 filter paper and stored at −15 °C before chemical analysis. The total organic carbon and total nitrogen concentrations in these extracts were measured using a Multi N/C 3100 analyzer (Analytik Jena AG, Analysensysteme GmbH). The concentrations of MBC and MBN in soil were calculated based on conversion factors 0.45 for MBC and 0.54 for MBN (Wu et al., 1990; Brookes et al., 1985).

2.5. Statistical analysis We used one-way ANOVA as a complementary method for assessing the effects of flooding frequency on the properties of soils and on the characteristics of plant and microbial communities. Further, redundancy analysis (RDA) was used to identify the factors that likely influenced the FRRs of plant and microbial communities. Monte Carlo permutation tests were used to determine the statistical significance of the relationships between the ordination and explanatory variables in the RDAs (Ye et al., 2019a,b). The effects of environmental factors on FRRs of plant and microbial communities were tested using the Forward Selection method. Moreover, in the RDAs, we used a principal component analysis (PCA) of the flood response ratios of soil metals to reduce the number of variables while preserving the variation. The first two principal components (PCs) accounted for almost 60% of the variation in the flood response ratios of soil metals. Thus, the site scores of the first two PCs, hereafter referred to as ‘metals-1’ and ‘metals-2’, were used to replace the flood response ratios of soil metals (Schipper et al., 2011). Pearson’s correlation was used to correlate the FRRs of plant and microbial community properties with the FRRs of soil properties, and was also used to assess the relationships between the recovery of plant community properties and the recovery of soil properties. To investigate the effects of revegetation, paired t-tests were used to compare soil properties, plant and microbial communities between the revegetation areas and the natural regeneration areas within the EFZ, SFZ and MFZ (statistical significance at P < 0.05). All the analyses were performed using SPSS 19.0 (IBM SPSS Inc., Chicago, IL, USA) except the RDA which was performed using Canoco 5.0 (Ye et al., 2017). 3. Results

2.4. Calculation of flooding response ratios (FRRs) and recovery response ratios (RRRs)

3.1. Effects of flooding on soil properties and plant and microbial communities

To evaluate the consistency of the size of the effects of flooding on soil properties, plant and microbial communities across sites, we calculated flood response ratios (FRRs) on a percentage basis at each site and for each flood zone (FZ), i.e., EFZ, SFZ and MFZ and no flood zone (NFZ). FRRs for June and September were calculated separately. The FRRs were estimated using the formula: −

Statistically significant, positive effects of flooding were observed on soil moisture, pH, Pb, Cu and Zn at each of the three levels of flooding duration (Fig. 2). Moreover, the C:N ratio was significantly increased, and total P and total K were decreased in the EFZ and MFZ after flooding (with 95% confidence intervals) (Fig. 2). Mean values of soil pH, moisture, C:N, Hg, Pb, Cu, Zn, and Mn were higher in floodaffected riparian zones than in the NFZ, while the mean values of bulk density, total N, and total P were lower in the flood-affected zones, with total N 17% lower and total P 24% lower in the flooding zones, relative to NFZ levels (Figs. S2 and S3). There were no significant differences in soil properties among the EFZ, SFZ and MFZ (Figs. S2 and S3). Plant coverage and aboveground biomass were significantly higher in the SFZ and MFZ relative to the NFZ, but the effect of increased flooding duration on plant diversity and species richness were significantly negative with respect to the NFZ (Figs. 3 and S4). In general, soil microbial community properties were not significantly affected by the different flooding regimes (Figs. 4 and S5).

−

⎛X − X ⎞ FRR% = ⎜ Fz − NFz ⎟ × 100% XNFz ⎠ ⎝

(1)

The mean FFR for each flood zone was calculated for each parameter, along with 95% confidence intervals. Where confidence intervals did not overlap zero, the effect of flooding was considered consistent and significant for that particular flood zone. Then, we used the FRRs to calculate the ‘recovery’ of plant and microbial communities from June to September after the annual flooding event at each site and for each flood zone (FZ), i.e., EFZ, SFZ and MFZ. Mean recovery response ratios (RRR) was evaluated by the equation: −

−

⎛ |FRRJun| − |FRRSep| ⎞ RRR% = ⎜ − ⎟ × 100% |FRRJun| ⎝ ⎠

3.2. Drivers of variation in the responses of plant and microbial communities to altered flooding regime

(2)

This value quantifies to what extent the value of a given parameter in a flooded-affected zone has become more or less similar to the value in the NFZ from June to September. Again, results were considered significant when the confidence intervals (95%) did not overlap zero

The responses of plant diversity and richness to variation in flooding regime were positively correlated with the FRRs of soil NO3-N, and the FRRs of plant coverage were positively correlated with the FRRs of soil 4

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Fig. 2. Effects of flooding on soil parameters in the Extreme Flooding Zone (EFZ, n = 14), Severe Flooding Zone (SFZ, n = 14) and Moderate Flooding Zone (MFZ, n = 15) in the natural regeneration areas, expressed as mean flooding response ratios (%) ( ± 95% bootstrapped confidence intervals). Flooding effects were considered significant where confidence intervals did not overlap zero (Only the significant flooding effects on soil parameters were presented in this figure, the rest variables were showed in Fig. S1).

Hg (Table S1). Approximately 54.7% of the variability in the FRRs of plant community was explained by RDA axis 1 (51.9%) and axis 2 (2.8%), where the distance to the dam, silt, metals-1, available P and total P were closely correlated with the first axis, and NO3-N contributed significantly to the second axis. In total, the FRRs of available P (8.4%), total N (8.1%), clay (7.6%) and distance from the reservoir (7.4%) explained 31.5% of variation in the FRRs of plant community (Table 1). However, there were little significant relationships among the FRRs of microbial community properties and the FRRs of soil properties in this study. According to the RDA, only 26.2% of the variability in the flooding responses of microbial community was explained by RDA axis 1 (18.4%) and axis 2 (7.8%) (Table1). In particular, the flooding response of soil clay accounted for 9.5% of variation in the responses of microbial community to flood (Table 1).

was negative (mean = −265% ± 115%), indicating that aboveground biomass was more different between flooded and unflooded areas in September than it was in June and suggesting an absence of any positive post-flooding recovery as per our definition. In contrast, the recovery of plant diversity and species richness after flooding in the EFZ and SFZ, together with the recovery ratio of plant coverage in the EFZ, were significantly positive (Fig. 5). As shown by Pearson’s correlation, the recovery of plant coverage was strongly positively correlated with the recovery of soil bulk density and Zn (Table 2). Meanwhile, the recovery of aboveground biomass was positively related to the recovery of total P and K, NH4+-N, As, Cr and Mn, but negatively correlated with the recovery of Pb and Cu (Table 2).

3.3. Recovery of plant communities after flooding

The contents of soil Cd, Pb, Cu and Zn were significantly higher in the natural regeneration areas than in the revegetation areas. In contrast, there were no significant differences in plant coverage, diversity,

3.4. Effects of revegetation on soil properties and plant and microbial communities

The mean recovery response ratio (RRR) of aboveground biomass

Fig. 3. Effects of flooding on plant community characteristics in the Extreme Flooding Zone (EFZ, n = 14), Severe Flooding Zone (SFZ, n = 14) and Moderate Flooding Zone (MFZ, n = 15) in the natural regeneration areas, expressed as mean flooding response ratios (%) ( ± 95% bootstrapped confidence intervals). Flooding effects were considered significant where confidence intervals did not overlap zero.

5

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Fig. 4. Effects of flooding on soil microbial community characteristics in the Extreme Flooding Zone (EFZ, n = 14), Severe Flooding Zone (SFZ, n = 14) and Moderate Flooding Zone (MFZ, n = 15) in the natural regeneration areas, expressed as mean flooding response ratios (%) ( ± 95% bootstrapped confidence intervals). Flooding effects were considered significant where confidence intervals did not overlap zero.

The mean post-flooding recoveries of plant coverage, diversity, and species richness were small but significantly positive (5%) in both the revegetation areas and natural regeneration areas. However, the recoveries of aboveground biomass were not consistent between the two management areas, being negative in the revegetation area but nonsignificant in the natural regeneration areas (Fig. 6).

Table 1 RDA results showing the proportion of variances of the flooding responses of plant and microbial communities explained by single key explanatory variables. Explanatory variables Plant community Available P Total N Clay Distance Total P Metals-1a Soil moisture pH Soil organic matter Bulk density Microbial community Clay NH4-N Soil moisture C:N ratio Distance Factor 1 Total N Sand Available P Silt Metals-2a Total P

% variance explained

P value

F ratiob

8.4 8.1 7.6 7.4 6.7 5.0 4.3 2.0 1.9 1.0

0.03 0.03 0.04 0.03 0.08 0.14 0.08 0.23 0.29 0.44

4.9 4.3 3.5 4.7 2.9 2.4 2.9 1.4 1.2 0.6

9.5 3.9 3.0 3.0 2.7 2.5 2.2 1.9 1.6 1.5 1.3 1.1

0.03 0.16 0.23 0.23 0.24 0.29 0.28 0.36 0.43 0.51 0.57 0.63

4.3 1.8 1.4 1.4 1.3 1.2 1.0 0.9 0.8 0.7 0.6 0.5

4. Discussion 4.1. Effects of flooding on soil properties The lower concentrations of total N and P in soils exposed to unnatural flooding regimes, coupled with the lower soil total K and available P in the MFZ, support the assertion that unnaturally frequent flooding can disrupt biogeochemical processes and lead to gradual soil nutrient depletion. We suggest that this is due, at least in part, to the removal and transportation downstream of plant litter (and its constituent organic C and nutrients) by flood waters (Hamdan et al., 2010; Saint-Laurent et al., 2014). Our results also suggest that the effects of flooding on soil are strongly influenced by the associated vegetation community. For instance, the ability of riparian ecosystems to retain mobile nutrients (e.g., P and K) could be lowered when plants and soil micro-organisms die as a result of flooding events (Xiao et al., 2017). On the other hand, rapid uptake of nutrients (e.g., P) by live plants and microbes after flooding, particularly in the growing season, might quickly reduce soil available P concentrations, particularly if P levels are already low (Ye et al., 2015). Changes in plant diversity can also influence plant biomass decomposition and thus affect soil C and nutrient levels (Fraser et al., 2004). Thus, the low levels of plant diversity and species richness in the EFZ and SFZ might have contributed to the altered nutrient levels in these flooding zones compared to those in the NFZ (Figs. S2 and S4). The higher contents of most soil heavy meals (i.e., Hg, Pb, Cu, Zn and Mn) in flooded zones (Figs. 2 and S3) suggest that changes in flooding regimes can have profound consequences for the distribution and accumulation of heavy metals in riparian soils. Such effects are thought to be influenced by changes in other basic soil properties (Ye et al., 2019a,b). For example, the positive effects of flooding on soil pH and moisture might have increased the mobility and bioavailability of some heavy metals, which might have, in turn, promoted the enrichment of heavy metals in the riparian soils partly via plant uptake following inundation events (Fig. 2; Bing et al., 2016). This mechanism is

a A principal component analysis was executed on the flooding response ratios (FRRs) of soil heavy metals to reduce the amount of variables while preserving the variation. The first and second principal component accounted for ca.60% of the variation in the FRRs of heavy metals. Thus, the remaining components were discarded, and for each sampling sites, the FRRs of heavy metals were replaced by the site scores on the first component (Metals-1) and the second component (Metals-2) (Schipper et al., 2011; Ye et al., 2013). b F-ratio represents the analysis of variance, which was proposed by R.A.Fisher. The higher value of F-ratio means the more significant effects.

above-ground biomass, or species richness between the revegetation areas and the natural regeneration areas (Paired t-test p-values > 0.05) (Table 3). Similarly, soil microbial community characteristics did not differ between the active revegetation and natural regeneration areas, with the exception of soil microbial biomass C concentrations in the 10–20 cm soil layer, which were significantly higher in the revegetation areas than in the natural regeneration areas (Table 3). 6

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Fig. 5. Recovery response ratios of microbial and plant community characteristics in the Extreme Flooding Zone (EFZ, white bars, n = 14), Severe Flooding Zone (SFZ, light grey bars, n = 14) and Moderate Flooding Zone (MFZ, dark grey bars, n = 15) in the natural regeneration areas after flooding, expressed as mean recovery response ratios ( ± 95% bootstrapped confidence intervals) across natural regeneration areas. Recovery effects were considered significant where confidence intervals did not overlap zero.

supported by the positive association of certain heavy metals with soil pH and soil moisture in this study. Although soil nutrients and heavy metals were strongly affected by periodic flooding compared to the non-flooded zones, they were little influenced by the flooding depth and duration when comparing the three different flooding zones (EFZ, SFZ and MFZ) (Figs. S2, S3 and 2). This suggests that periods of alternating flooding and drought with frequent erosion and sedimentation processes could promote spatial homogeneity in soil characteristics (e.g., soil particle size) and disrupt soil development processes (Diodato et al., 2012; Wang et al., 2012).

Table 2 Pearson correlation coefficients among the post-flooding recovery response ratios of plant characteristics and the recovery response ratios of soil parameter in natural regeneration areas (n = 43).

Distance Sand Silt Clay pH Moisture Bulk density SOM Total N Total P Total K Available P Available K NH4-N NO3-N C:N ratio Hg As Cr Cd Pb Cu Zn Fe Mn

Plant coverage

Aboveground biomass

Plant diversity

Species richness

0.01 −0.19 0.06 0.16 −0.02 −0.07 0.46a** −0.05 0.21 0.00 −0.18 0.21 −0.25 −0.17 0.07 −0.01 0.12 −0.26 −0.14 −0.09 0.22 −0.11 0.44** −0.12 −0.20

0.09 0.12 0.10 −0.15 −0.08 −0.04 −0.06 −0.13 −0.20 0.35* 0.34* −0.04 0.15 0.63*** −0.16 0.15 −0.02 0.37* 0.48** −0.02 −0.44** −0.34* −0.13 −0.02 0.55***

−0.02 −0.04 −0.08 −0.10 −0.10 −0.05 −0.02 −0.05 0.09 0.02 −0.08 −0.05 −0.07 −0.07 −0.14 0.01 −0.08 −0.14 −0.06 0.09 0.10 0.09 0.02 −0.06 −0.08

−0.23 −0.12 −0.11 −0.06 −0.08 −0.05 0.11 −0.03 0.15 0.06 −0.13 −0.09 −0.10 −0.12 −0.12 −0.09 −0.17 −0.14 −0.06 0.16 0.17 0.10 0.15 −0.13 −0.07

4.2. Effects of flooding on plant and microbial communities The lower plant coverage and aboveground biomass in the EFZ, together with the lower plant diversity and species richness in the EFZ and SFZ (Fig. 3), support the view that shifts in flooding regime can modify vegetation composition to a significant extent, often resulting in a high proportion of flood-resistant vegetation (Sun et al., 2017). In the EFZ, the water level was regulated not only by the TGR but also by occasional seasonal floods and waves generated by boats, such that it might have been difficult for ‘ordinary’ (i.e., non-flood resistant) taxa to achieve dispersal and rapid recovery (Sun et al., 2017). This might have contributed to the low plant diversity in this flood zone relative to other flood zones (Fig. 3). However, species like perennial herbs (e.g., C. dactylon) and annual herbs (e.g., Cyperus iria), with strong survivability and well-developed root systems, easily occupied the flooded areas (Ye et al., 2013). The effects of altered flooding regime on vegetation communities are also strongly regulated by the levels and availability of soil nutrients, and of N and P in particular (Nilsson et al., 1989). In the present study, the responses of plant community characteristics to flooding were significantly related to soil available P and total N concentrations (Table 1), which supports the view that flooding-altered soil nutrient availability is an important driver of flooding-induced changes in the

SOM: soil organic matter. a Bold-faced values represent significance at p < 0.05. * Represents significant correlation at p < 0.05. ** Represents significant correlation at p < 0.01. *** Represents significant correlation at p < 0.001.

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Table 3 Paired-t test results for plant community, soil properties and microbial community between revegetation areas and natural regeneration areas.

Soil properties pH Bulk density (g m−3) Soil moisture (%) Sand (%) Silt (%) Clay (%) Soil organic matter (g kg−1) Total N (g kg−1) C:N ratios Total P (g kg−1) Total K ((g kg−1)) Available P (mg kg−1) Available K (mg kg−1) NH4-N (mg kg−1) NO3-N (mg kg−1) Hg (mg kg−1) As (mg kg−1) Cr (mg kg−1) Cd (mg kg−1) Pb (mg kg−1) Cu (mg kg−1) Zn (mg kg−1) Fe (g kg−1) Mn (g kg−1) Plant characteristics Plant coverage (%) Above-ground biomass (g m−2) Plant diversity (H) Species richness (S) Microbial traits 0–10 cm Bacterial (108 cfu g−1) Fungi (106 cfu g−1) Actinomycetes (106 cfu g−1) Bacterial:Fungi ratio Fungi:Actinomycetes ratio Bacterial:Actinomycetes ratio Microbial biomass C (mg kg−1) Microbial biomass N (mg kg−1) Microbial C:N ratios 10–20 cm Bacterial (108 cfu g−1) Fungi (106 cfu g−1) Actinomycetes (106 cfu g−1) Bacterial:Fungi ratios Fungi:Actinomycetes ratio Bacterial:Actinomycetes ratio Microbial biomass C (mg kg−1) Microbial biomass N (mg kg−1) Microbial C:N ratio

Revegetation area (n = 12)

Natural regeneration area (n = 12)

t

P

7.56 ± 0.21 1.22 ± 0.07 28.9 ± 3.0 42.6 ± 7.3 33.3 ± 4.3 24.1 ± 3.6 13.6 ± 1.5 0.90 ± 0.07 9.52 ± 1.35 0.64 ± 0.05 13.6 ± 0.9 10.23 ± 1.36 61.4 ± 8.1 7.52 ± 0.53 8.80 ± 0.99 0.07 ± 0.01 12.9 ± 2.4 65.9 ± 1.0 0.17 ± 0.04 44.8 ± 6.6 32.4 ± 6.0 69.8 ± 8.4 20.3 ± 0.7 0.52 ± 0.09

7.70 ± 0.22 1.20 ± 0.05 30.5 ± 2.9 35.6 ± 6.4 36.5 ± 3.5 28.0 ± 3.6 15.3 ± 1.6 0.91 ± 0.07 10.06 ± 0.96 0.69 ± 0.04 15.2 ± 1.2 12.3 ± 1.2 67.4 ± 7.0 7.38 ± 0.52 7.97 ± 0.68 0.10 ± 0.03 10.47 ± 1.94 66.4 ± 1.2 0.24 ± 0.04 52.8 ± 6.8 34.2 ± 4.7 84.5 ± 8.9 21.3 ± 0.4 0.63 ± 0.07

0.611 −0.240 0.74 −1.464 0.819 1.415 1.112 0.174 0.429 0.689 1.92 1.196 1.515 −0.190 −0.940 0.979 −1.090 0.482 2.76 2.273 0.426 3.157 1.791 1.777

0.554 0.815 0.475 0.171 0.43 0.185 0.29 0.865 0.676 0.505 0.081 0.257 0.158 0.853 0.367 0.348 0.299 0.639 0.019* 0.044* 0.679 0.009** 0.101 0.103

85.8 ± 5.4 721 ± 150 1.66 ± 0.20 7.08 ± 1.22

77.08 ± 6.92 537.91 ± 129.12 1.56 ± 0.25 7.33 ± 1.74

−1.068 −1.398 −1.035 0.329

0.308 0.19 0.323 0.748

7.00 ± 3.75 8.93 ± 2.79 8.65 ± 2.83 121 ± 56 1.95 ± 0.48 388 ± 252 60.4 ± 16.8 16.1 ± 6.2 4.06 ± 1.48

11.16 ± 3.97 8.88 ± 4.35 14.67 ± 3.78 526 ± 248 1.02 ± 0.42 94.7 ± 35.6 54.4 ± 22.9 7.86 ± 2.41 4.74 ± 1.64

0.783 −0.009 1.077 1.536 −1.283 −1.134 −0.192 −1.094 0.313

0.45 0.993 0.304 0.153 0.226 0.281 0.852 0.297 0.761

6.75 ± 1.57 8.46 ± 1.85 14.9 ± 4.7 163 ± 99 1.52 ± 0.52 90.2 ± 25.8 86.5 ± 16.2 28.7 ± 12.3 5.87 ± 2.61

14.1 ± 6.7 14.2 ± 6.9 12.8 ± 2.5 382 ± 225 1.67 ± 0.67 150 ± 73 37.7 ± 10.0 10.2 ± 2.0 5.33 ± 2.72

1.09 0.786 −0.462 0.86 0.169 0.886 −3.677 −1.437 −0.141

0.299 0.449 0.653 0.408 0.869 0.394 0.004** 0.179 0.890

Results are given as mean ± SE. *P < 0.05; **P < 0.01.

to changes in flooding regime or have an ability to rapidly recover after inundation. These traits could arise from the high metabolic flexibility and physiological tolerance of many micro-organisms to changing environmental conditions (Meyer et al., 2004; Leininger et al., 2006). Indeed, Allison and Martiny (2008) suggested that, while soil microbial communities can be affected strongly by disturbance, they tend to recover rapidly, likely because of their potential for rapid post-disturbance re-growth and physiological adaptation. Our results regarding microbial community responses were generally consistent with this. On the other hand, plants, being generally longer-lived than micro-organisms, are unlikely to have similar mechanisms of resilience, and this could explain why plant communities were generally more strongly affected by changes in flooding regime than were microbial communities in our study. Ye et al. (2018) showed that ammonia-oxidizing archaea (AOA) have a strong capacity to recover and maintain their community

characteristics of vegetation communities (Kulmatiski et al., 2008). For instance, the reduced soil N and P levels could cause displacement of some plant species by N-fixing or high P-absorbing species (Gerard et al., 2008). Finally, the distance from the reservoir is also likely to be a key factor determining the responses of plant communities to altered flooding regime (Table 1). The different distances from the reservoir represent the combined effects of topography, flow speed, and soil properties, all of which affect the processes of vegetation development and the formation, distribution, transmission, and deposition of seeds, resulting in the different responses of plant community structure to the flooding (Chambers et al., 1991; Sun et al., 2017). In contrast to vegetation communities, soil microbial communities did not exhibit any obvious responses to the long-term changes in flooding regime in our study (Figs. 4 and S5). In our view, this indicates that the riparian soil microbial communities are either highly-resilient 8

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Fig. 6. Recovery response ratios of microbial and plant community characteristics after flooding in the revegetation areas (n = 9, grey bars) and the natural regeneration areas (n = 9, white bars), expressed as mean recovery response ratios ( ± 95% bootstrapped confidence intervals) across all the flooding zones. Recovery effects were considered significant where confidence intervals did not overlap zero.

Flooding frequency, soil N and P and, to a lesser extent, flood-N/P interactions have been hypothesized to regulate the occurrence, successional patterns and post-flooding recovery of riparian plant communities (Aerts et al., 2003). The significant positive relationship between the recovery of aboveground biomass and the recovery of soil total P and K, and NH4+-N in our study supports this idea (Table 2). Therefore, the lower soil N and P associated with prolonged, anti-seasonal flooding may contribute to the low degree of recovery of aboveground plant biomass (Figs. 5 and S2).

stability under the altered flooding regimes associated with the TGR. Thus, the flooding regime shift did not lead to an accumulation of nitrogen or disturbance of the AOA-driven aspects of the nitrogen cycle. This is further supported by our present results, which show that the concentrations of NH4+-N and NO3−-N are stable despite the long-term periodic flooding (Fig. S2). Therefore, the soil microbes that were seemingly resilient to the highly variable habitats associated with periodic flooding disturbances are possibly important for restoring and maintaining riparian ecosystems that have been affected by unnatural flooding regimes.

4.4. The effects of revegetation on plant-soil system 4.3. Post-flooding recovery of vegetation communities The lack of differences in plant community characteristics between the revegetation and natural regeneration areas (Table 3) suggests that active revegetation made only a minor contribution to enhancement of biodiversity at our study sites. This result could be interpreted as evidence that natural regeneration is effective in our study system, possibly due to the formation of diverse, heterogeneous habitats associated with natural regeneration (Lamb et al., 2005). This heterogeneity could enable colonization by a large number of species or functional groups, and such an outcome is often difficult or impossible to achieve through deliberate planting efforts (Florgard, 2004; Ye et al., 2014). Indeed, the number of plant species present in the WLF of the TGR increased by 76.7% (from 73 to 129 species) during seven years of natural recovery (from 2011 to 2017). This certainly suggests that natural regeneration can contribute to the rehabilitation of riparian ecosystems throughout the TGR watershed. However, the potential utility of natural restoration approaches should always be evaluated with respect to site attributes, such as climate, soil properties, extent and severity of degradation, and the availability of propagules (i.e., seed bank, remnant vegetation, and dispersal agents; Zhang et al., 2010; Ye et al., 2014), along with the desired outcomes. Active vegetation will likely prove necessary, either to facilitate or complement natural regeneration, in situations where site conditions are severely degraded and propagules are few or absent (Ashton et al., 2001). Furthermore, the positive post-flooding recovery (as per our definition) of plant coverage, diversity, and species richness in both the

The effects of flooding on plant diversity and species richness in the high frequency flooding disturbance zones (EFZ and SFZ), together with the effects of EFZ on plant coverage, were smaller in September than they were in June (Fig. 5), suggesting some degree of post-flooding recovery, as per our definition, in the time between June and September. To some extent, our results support the view that the riparian vegetation communities are somewhat resilient to moderate flooding disturbance and can recover from floods within short timeframes (Bilkovic et al., 2012). As discussed above, high frequency flooding disturbance plays an important role in re-shaping of the riparian vegetation communities and can promote certain evolutionary ‘floodingtraits’ (Greet et al., 2012). The flood-resistant species like annual herbs with short life cycles and perennial plants that propagate by vegetative reproduction can grow rapidly and come to dominate the flooded areas during the growing season from June to September. This might have contributed to the positive recovery of plant diversity and species richness in the EFZ and SFZ between June and September (Fig. 5). However, in contrast to the recovery of plants in the EFZ and SFZ, the post-flooding recoveries of plant diversity and species richness in the MFZ were negative or negligible (Fig. 5), indicating that different flooding durations can lead to different pathways of plant community recovery following disturbance. The recovery of plant community characteristics was also strongly related to flooding-induced shifts in the levels of certain soil nutrients. 9

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revegetation and natural regeneration areas (Fig. 6) demonstrate that vegetation in these two areas was resilient to the disrupted flooding regime and can partially, if not fully, recover from the impacts of recent, repeated flooding. However, the recovery of aboveground biomass in the revegetation areas was negative (Fig. 6), suggesting the absence of post-flooding recovery. According to our discussion above, the results could be partly explained by the low contents of total P and K in the revegetation areas (Tables 2 and 3).

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5. Conclusion Our results reveal that anthropogenically-disrupted flooding regimes are associated with a significant shift in soil biogeochemical conditions, with soil total N and P concentrations 17% and 24% lower, respectively, in flood-affected soils, and with heavy metals concentrations (Hg, Pb, Cu, Zn and Mn) higher in flood-affected soils. Ten-year’s worth of periodic flooding was also associated with lower plant diversity and species richness relative to unflooded areas. However, soil microbial communities did not exhibit a similar response, suggesting that soil microbes are more resilient or have greater ability to recover from flooding than plants and might, therefore, contribute to the maintenance of riparian ecosystem stability. Plant diversity and species richness showed obvious post-flooding recovery in EFZ and SFZ, while plant aboveground biomass had little recovery after flooding. In general, active revegetation efforts did not have significant effects on soil or vegetation community properties or on their post-flooding recovery trajectories. Together, these results suggest that disrupted flooding regimes can trigger biogeochemical shifts in riparian ecosystems that can influence or regulate the effects of flooding on riparian plant communities. Given that these effects are little impacted by active revegetation efforts, natural regeneration is likely to be an efficient strategy for the management of the flood-affected environments associated with the Three Gorges Reservoir. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This research is supported by the National Natural Science Foundation of China (No. 31570521, 31300441), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (No. 2019334) and the Executive of the State Council Three Gorges Construction Committee (SX2017-022). We would like to thank Kai He, Ruyi Xu and Min Li for their assistance during fieldwork, Lu Yao for assistance with statistical analyses, and Pingcai Yan for assistance with laboratory analyses. Appendix A. Supplementary data Supplementary data to this article can be found online at https:// doi.org/10.1016/j.geoderma.2019.114015. References Aerts, R., DE Caluwe, H., Beleman, B., 2003. Is the relation between nutrient supply and biodiversity co-determined by the type of nutrient limitation? Oikos 101, 489–498. Allison, S.D., Martiny, J.B.H., 2008. Colloquium paper: resistance, resilience, and redundancy in microbial communities. PNAS 105, 11512–11519. Ashton, M.S., Gunatilleke, C.V.S., Singhakumara, B.M.P., Gunatilleke, I.A.U.N., 2001. Restoration pathways for rain forest in southwest Sri Lanka: a review of concepts and models. Forest Ecol. Manage. 154, 409–430. Bagstad, K.J., Stromberg, J.C., Lite, S.J., 2005. Response of herbaceous riparian plants to rain and flooding on the San Pedro River, Arizona, USA. Wetlands 25, 210–223. Bao, Y., Gao, P., He, X., 2015. The water-level fluctuation zone of Three Gorges Reservoir-

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