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How hydrological connectivity regulates the plant recovery process in salt marshes

Citation

Wang, Qing et al. (2021), How hydrological connectivity regulates the plant recovery process in salt marshes, Dryad, Dataset, https://doi.org/10.5061/dryad.1g1jwstvm

Abstract

1. Designing effective restoration strategies is a priority in recovering salt marsh plants. As a main driver underpinning the success of plant recovery process, hydrological connectivity can regulate life history process-based restoration strategies, but the relations are not clear.

2. Plant recovering needs to go through a whole life history process, from seed to adult. Common restoration strategies are seed addition (SA) or seedling transplantation (ST), which start from seed germination and seedling growth stage. Besides these two strategies, another strategy starting from seed retention stage, microtopographic adjustment (MA), were designed to study the relationship with hydrological connectivity. And a framework was construct to assess a gradient of hydrological connectivity between marsh plain and sea and conducted several field experiments to test their relationships.

3. The composite measurement of hydrological connectivity with five geomorphic variables can well represent the variation of environmental factors. Soil moisture, inundation frequency and sediment deposition were positive correlated, while soil salinity and hardness were negative correlated with hydrological connectivity.

4. The success of different restoration strategies varied with hydrological connectivity. MA showed a monotone decreasing trend, while SA and ST showed unimodal trend with the increasing of hydrological connectivity. The important is, each strategy occupies a non-overlapping optimum range along hydrological connectivity gradient, they are low hydrological connectivity for MA (0 – 0.28), middle hydrological connectivity for SA (0.28 – 0.55) and high hydrological connectivity for ST (0.55 – 1).

5. Synthesis and applications. Our findings expand the quantification of the hydrological environment beyond elevation or distance or other single index to include a range of elements of hydrological connectivity, and illustrate the underlying mechanisms of hydrological connectivity regulating restoration strategies based on different life stages. The results not only provide a reliable framework to assess hydrological connectivity, but also the guidance to select optimum restoration strategy under different hydrological connectivities, or to regulate the hydrological connectivity variables (topography on marsh plain and morphology of tidal creeks) to relief stresses. These findings will benefit ecological restoration and coastal management a lot.

Methods

Hydrological connectivity

To conveniently describe the relationships between hydrological connectivity and restoration strategies, we followed the method developed by Paillex (2009) to compute an index of structural hydrological connectivity for each sampling site with five geomorphic parameters based on the movement of tidal waters on the marsh surface. The five parameters are: 1) creek order, using reversed Strahler order, the entry channel as order 1 and end channels as the highest order (Chirol et al., 2018); 2) creek cross-sectional area, calculated by the width and the maximal depth; 3) creek length, calculated by the distance along a creek segment from the mouth of the entry channel to the cross-section perpendicular to the site; 4) the lateral distance from the site to the nearest tidal creek; and 5) site elevation. Most of these variables were measured with Google Earth, while the creek cross-section area was measured in the field with a telemeter rod. The elevations were measured by a Zhonghaida GPS (V9, China) in October 2015. These parameters indicate the potential water-mediated flux and inundation intensity of a site on the marsh surface; this includes both the longitudinal and lateral hydrological connectivity. Except for the creek cross-section area, the other four variables are negatively correlated with hydrological connectivity. The five connectivity variables were integrated with a principal component analysis (PCA) to obtain synthetic variables (factorial axes) used as surrogates for the level of hydrological connectivity between the mash plain sites and the sea. The synthesis score is used as a surrogate for hydrological connectivity:

(1) The first PCA axis score: Y1 = a1X1+b1X2+c1X3+d1X4+e1X5

(2) The second PCA axis score: Y2 = a2X1+b2X2+c2X3+d2X4+e2X5

(3) Synthesis score: Y = (uY1+vY2)/ (u+v)

Where X1 is creek order, X2 is creek length, X3 is lateral distance, X4 is creek cross-sectional area, and X5 is site elevation; a1, b1, c1, d1, e1 and a2, b2, c2, d2, e2 are component coefficients of the first and second PCA axis, respectively; u and v are rates of contribution of the first and second PCA axis, respectively. Variables were appropriately (square-rooted) transformed to ensure normality. And the synthesis scores were normalized using a maximum-minimum method. PCA analysis was computed in SPSS 22.0.

Restoration strategies

We conducted the three manipulation experiments across a gradient of hydrological connectivity from tidal creek to upland in two bare salt marsh areas (A and B in Fig.1 a, b, and f). Six transects perpendicular to the tidal creek were set along the main and secondary tidal creeks in each area (twelve transects in total). Each transect in A (Fig. 1a) consisted of eight plots, with the lateral distance of 15, 30, 45, 65, 90, 115, 140, and 165 m, and each transect in B (Fig. 1b) consisted of six plots, with the lateral distance of 1, 5, 15, 25, 45, and 65 m. Each plot had three replicates with an interval of a 1.5 m distance.

Strategy 1: Microtopographic adjustment (MA)

To overcome the limitation of seed retention, we simulated the natural hollowed microtopographic structures (Fig. 1c) to facilitate seed retention and monitor the life history within one year. The MA experiment was conducted in A (N=144) in October 2015 (at the beginning of the dispersal stage). To quantify the effect, we set hollowed microtopographic structures with uniform sizes of 50 × 50 cm2 at depths of 10 cm from the bare surface (Fig. 1 e). There was also a control treatment without microtopographic structure (the natural flat bare surface) near each plot, which was marked with four PVC pipes (50 × 50 cm2) (Fig. 1 d). Any emerged S. salsa seeds in the microtopographic structures and control plots were counted and recorded monthly between April and September 2016.

Strategy 2: Seed addition (SA

SA experiments were conducted with S. salsa seeds, which were sown with an optimum depth of 1 cm (Sun et al., 2014). This experiment was conducted in A and B (N=252). A hole with a diameter of 7.5 cm and depth of 10 cm was dug in each site. Then a soil core (diameter = 7.5 cm, depth = 6 cm) was used to collect a soil from the hole. The collected soil was placed in a flowerpot (diameter = 7.5 cm, depth = 7.5 cm, with small drainage holes in the bottom and on the lateral side) and 50 S. salsa seeds (collected from a nearby salt marsh) were sown in soil. Then, the seeds were covered by 1 cm soil, and the flowerpot was buried into the hole with its opening level with the bare surface. To prevent extraneous S. salsa seeds from entering the pot, a wire mesh cage (diameter =10 cm, height = 15 cm) with a fine mesh (pore < 0.01 cm) covering was placed over the flowerpot after seeds were sown in October 2015. The emerging S. salsa were counted monthly from April to September 2016.

Strategy 3: Seedling transplantation (ST)

The ST experiment used transplanted S. salsa seedlings with in situ soils, and the experiment was conducted in A and B (N=252). In April 2016, S. salsa seedlings were collected with the natural soil using a PVC cylinder (diameter = 10 cm, height = 10 cm) from nearby salt marshes. Seedlings that were 5 cm tall were selected; a total of 20 to 30 seedlings were kept in each PVC cylinder. Seedlings were then transplanted in the experimental sites. To mitigate transplanting stress, the experimental seedlings were watered using freshwater for 2 days in the week after transplanting (He, 2012). The monitoring of S. salsa number was conducted from April to September 2016.

Investigation of soil seed banks and soil characteristics

We investigated the soil seed bank in A and B. As there is a burial depth threshold (the optimum depth range is 1–2 cm and there is limited emergence down to 5 cm depth; Sun et al., 2014) for S. salsa emergence, only the surface soil layer (0–5 cm) was examined. The soil samples were dug up using a soil corer with a diameter of 5 cm. Two replicates were conducted in each site (N = 504). One replicate of the soil sample was used to examine the number of S. salsa seeds in a climatic chamber (ter Heerdt et al., 1996). The other replicate was used to measure soil salinity and moisture so that the basic abiotic characteristics of each microhabitat could be understood. Moreover, soil hardness was determined in each site with a sclerometer (N=252).

Investigation of dispersed seeds, sediment, and tidal floods

Seed traps were used to examine the dispersion of S. salsa seeds along the gradient of hydrological connectivity. A trap (a cylindrical transparent container with a length of 20 cm, radius of 3 cm, and drain holes at the bottom) was placed in a hole in each site with the opening of the container flush with the soil surface. In addition to trapping S. salsa seeds, seed traps can also capture sediment depositions. In April 2016, seedlings/seeds and sediment deposited in seed traps were removed and taken to the laboratory for counting and measurement (the dry weight of the sediment was measured). Two Odyssey Water Level Loggers (Z412, New Zealand) were used to record tidal level every 10 minutes (with the datum plane on the soil surface of each site) near the tidal creek edge in A and B from October 2015 to September 2016. The tidal characteristics were determined by analyzing the water level records using a Fortran 90 (ANSI standard, USA). An inundation frequency based on the number of days the tide arrived in a year was adopted (is calculated as %).

Data analysis

The number of established plants in the microtopographic structures during September 2016 was used to represent the effectiveness of the MA strategy (MA-final). For the SA and ST strategies, the effectiveness was calculated as the ratio of the final number (number of adult plants in September) to the initial number (the number of additional seeds or transplanted seedlings) (SA-final and ST-final, respectively). In addition, the maximum number recorded at each observation point during the experiment was also used to represent the re-establishing process (MA-max, SA-max and ST-max, respectively).

Usage Notes

The envrionmental data (except inundation data) and experimental data displayed as means of the three replicates of a plot, and each standard error was also given. n/a = values not available. Microtopographic adjustment (MA) experiments did not conduct in area B (displayed in grey).

Funding

National Natural Science Foundation of China-Guangdong Joint Fund, Award: U1901212

National Natural Science Foundation of China, Award: 51639001

China Postdoctoral Science Foundation, Award: 2019M660518