The role of soil as a carbon sink in coastal salt-marsh and agropastoral systems at La Pletera, NE Spain

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The role of soil as a carbon sink in coastal salt-marsh and agropastoral systems at La Pletera, NE Spain ⁎

Maria Gisperta, , Chantha Phangb, Lorena Carrasco-Bareac a

Soil Science Unit, Department of Chemical Engineering, Agriculture, and Food Technology, University of Girona, C/ Maria Aurelia Capmany 61, 17003 Girona, Spain Agro-Industry Faculty, Royal University of Agriculture, Dongkor District, P.O. Box 2696, Phnom Penh, Cambodia c Plant Physiology Unit, Department of Environmental Sciences, University of Girona, C/ Maria Aurelia Capmany 69, 17003 Girona, Spain b

A R T I C LE I N FO

A B S T R A C T

Keywords: Salt-marsh soil Organic carbon Carbon dioxide Glomalin Structure Ecosystem service

To evaluate the potential of natural and modified salt-marsh soils to store organic carbon and their soil properties, we investigated six soil environments located at La Pletera salt-marsh area, NE Spain. Namely, Ruderal (RU), rubbles over marsh for construction purpose, ELY covered by Elymus elymoides (Raf.) meadows, ART under Arthrocnemum fruticosum L., SAL under Salicornia patula Duval Jouve, AGR under Zea mays L., and AME under Medicago sativa L. as artificial meadow. Soils were sampled at three depths (0–5, 5–20 and 20–40 cm). At 0–5 cm depth, soil organic carbon (SOC) was higher in ART soil (40.08 g kg−1) with respect to ELY, AME, AGR, SAL and RU (23.63, 11.45, 5.77, 4.40 and 3.18 g kg−1 respectively). Glomalin (TGRSP) in ART had the same trend, with 8.88 g kg−1 decreased by 51%, 77%, 89%, 92% and 94% in ELY, AME, AGR, SAL and RU soil respectively, indicating that in ART recalcitrant organic carbon may prevail. ART and ELY soils had higher SOC and GRSP than AGR and AME soils at 0–5 and 5–20 cm (on average + 70% and 57%) but SOC values were similar at 20–40 cm depth and glomalin was even higher in AGR and AME soils at this depth suggesting migration of stable organic compounds in cultivated soils. The water stable aggregates (WSA) analysed in the 0.25–2 mm and 2–5.6 mm fractions was also higher in ART and ELY soils (≈90%) at 0–5 and 5–20 cm with respect to the other investigated soils. Higher WSA (fraction 0.25–5 mm) was found in AGR and AME soils at 20–40 cm corroborating that at higher GRSP corresponds higher aggregation. Potential carbon loss as C-CO2 (Mg ha−1) was evaluated at 0–5 cm depth and was much lower in ART soil. Accordingly, C-CO2/SOC ratio assigned to ART soil 1.85% of SOC loss against 8.26%, 11.64%, 18.90%, 20.37% and 22.72% of ELY, AME, RU, SAL and AGR soils respectively, indicating that only ART and ELY soils may exert clear carbon sequestration ability. The soil under annual Salicornia patula Duval Jouve (SAL) showed very low SOC (4.40 g kg−1) and the highest carbon loss potential (22.72%) due to shortage of organic decaying debris at surface. Also, C-TGRSP resulted higher in ELY and ART soils (2.51 and 1.31 Mg ha-1respectively) and C-TGRSP/SOC ratio demonstrated glomalin carbon enrichment in this order: ART > AME > ELY > AGR > SAL > RU, suggesting that carbon sequestration capacity may be assigned to ART and ELY soils, major carbon sinks in the Pletera salt-marsh area. Conversely, RU, AGR and AME soils, identified as ancient salt-marsh converted into agropastoral systems or altered for tourism purposes showed worse soil properties and higher sensitivity to carbon destabilization. Statistical treatment of data by factor analysis corroborated the obtained results outlining the importance of ART and ELY soils in maintaining best soil properties and the highest carbon storage capacity.

1. Introduction Salt-marshes around the world are in danger due to activities such as urbanization, agriculture and recreational use, and even though they have been thoroughly studied from an hydrological and plant physiology point of view, more researches about the function of their soils as well as their role in this ecosystems must be done (Čížková et al.,

⁎

2011). Their value as highly effective sinks for atmospheric carbon dioxide into recalcitrant soil organic carbon in a global context should be taken into account (Chmura, 2013). Carbon budgets at a global scale have mainly focused over large agricultural and forest land and discarded small scattered salt-marshes with high carbon storing capacity (Chmura et al., 2003). The research on this topic is rather scanty and results vary according to physiographical, phenological and pedological

Corresponding author. E-mail addresses: [email protected] (M. Gispert), [email protected] (C. Phang), [email protected] (L. Carrasco-Barea).

https://doi.org/10.1016/j.catena.2019.104331 Received 14 March 2019; Received in revised form 14 October 2019; Accepted 17 October 2019 0341-8162/ © 2019 Elsevier B.V. All rights reserved.

Please cite this article as: Maria Gispert, Chantha Phang and Lorena Carrasco-Barea, Catena, https://doi.org/10.1016/j.catena.2019.104331

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Fig. 1. Geographical setting of the Pletera area (a, b, c). Orthophoto of La Pletera location with the sampling areas and constructions to be removed (d).

environments had much higher carbon amounts and lesser rates of decrease with respect to soil carbon percentages in converted lands because of heightened microbial activity, aerobic conditions and lower salinity (Burden and Garbutt, 2013). Likewise, afforestation largely implemented as a way to take carbon from the atmosphere has also resulted to be less efficient at removing carbon per unit area than marshes, strengthening the importance of salt-marsh restoration (Hussein et al., 2004). Indeed, the contribution of vegetated coastal habitats to long-term carbon sequestration is much greater than terrestrial forests (Mcleod et al., 2011). Hence, their recognition as carbon sinks is a strong argument for their protection (Sarmiento and Gruber, 2002). In the province of Girona (NE of Iberian Peninsula) there are several salt-marshes associated to the deltaic progradation of the Ter river. Alternating with coastal waterbodies with larger or smaller freshwater influence, there are some brackish or even hyperhaline coastal lagoons, where inputs of surface freshwater are very scarce. The hydrology of these brackish ecosystems is strongly determined by the sea, although they are separated from the sea almost all the year. In this case, due to their isolation from surface freshwater and marine inputs, they have been defined as confined coastal lagoons, which hydrology is dominated by sudden inputs during sea storms or flooding events, followed

characteristics. There is also little understanding of how in coastal areas carbon accumulation rates will change along climate change and its potential feedback (Lal, 2004; Kirwan and Mudd 2012). Salt-marshes occupy only a small percentage of Earth's land surface but they have a relevant role in contributing to a wide range of ecosystem services, which have significant global environmental, economic and societal value (Spencer and Harvey, 2012). They hold high biodiversity levels, provide important habitats for a large number of species, and support important regulations of hydrology, the biogeochemical cycles of nutrients and trace elements (Menció et al., 2017; Lefeuvre et al., 2003; Otero et al., 2005). Nonetheless, these areas have been often dismantled for other land uses, especially urbanization, causing noticeable alteration of the whole ecosystem (Spencer and Harvey, 2012). Restorations to its original conditions have been carried out in these environments, because recent research has shown that restoring salt-marshes is one of the most effective measures for sequestering carbon into soil (Howe et al., 2009). Salt-marshes may be extremely productive environments that capture significant amounts of carbon from the atmosphere, large amounts of which are stored in marsh soils. The need to restore salt-marshes has therefore been considered paramount as even the conversion to agriculture or pasture resulted worse in terms of carbon storage capacity. Existing salt-marsh soil 2

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2. Materials and methods

ART, under Arthrocnemum fruticosum L. community; the SAL, under Salicornia patula Duval Jouve community for comparative study of soil properties and carbon sequestration capacity of the selected soil environments. Moreover, representative soil samples from adjacent agricultural soil (AGR), after corn (Zea mays L.) harvesting, and soil under Medicago sativa L. as artificial meadow (AME) for periodical pasture were collected. The World Reference Base for Soil Resources (W.R.B., 2015) was used to classify the soils (Table 1). Soil sampling has been carried out by establishing five plots of 1 square meter in each selected environment as reported in Fig. 1d. Sampling was performed in AugustSeptember 2015. At each site soil samples were collected by using soil layers at fixed depth increments of 0–5, 5–20 and 20–40 cm with the objective to give special emphasis to the organic horizon of ART soil corresponding to 0–5 cm layer (Francaviglia et al., 2017). A total of 162 samples (54 disturbed samples at each depth, i.e. 9 samples per environment/depth) were finally obtained from the selected soil environments. After sampling, soil samples were took to the laboratory of Soil Science of the University of Girona, air dried, gently crushed and a part sifted in a sieve with mesh opening 2 mm to obtain three composited samples of the fine earth fraction (0–2 mm) of each environment/depth for physical, chemical and biological analyses. Moreover, soil aggregates in 0.25–2 mm and 2–5.6 mm size fractions were separated from three composited samples of each environment/depth from the dried bulk soil samples through sifting in sieves with mesh opening 0.25–2 mm and 2–5.6 mm at the three depths for structural stability of aggregates analysis. To determine the soil respiration potential, a representative amount of fresh undisturbed soil was collected at each site and only at 0–5 cm depth, then stored at the laboratory at 4 °C to maintain field moisture conditions. All analyses were carried out in three replicates.

2.1. Study area

2.3. General soil characterization

La Pletera salt-marsh is located in Catalonia (Fig. 1a, b) inside the Montgrí, Medes Islands and Baix Ter Natural Park, Estartit city, Girona Province, NE Spain (42° 01′ 03″N, 3° 11′ 29″E). This Natural Park is a Site of Community Importance (SCI) as established by the Low 15/2010 of May 28 of the Catalan Government, following the Council Directive 92/43/EEC (CEC, 1992) on the Conservation of natural habitats, identified as ES51 (Catalonia) and 20016 (Montgrí, Medes Islands and Baix Ter) zonation, and is included in Natura 2000 Network (Fig. 1c). According to the updated Köppen-Geiger classification (Kotteket al., 2006), the climate is warm temperate with dry and hot summers (Csa). It has an altitude of 2 m asl. The annual average temperature is 16 °C with an average maximum of 25 °C in summer and minimum of 10 °C in winter. Average rainfall is about 590 mm year−1 with higher rainfall (140 and 200 mm) recorded in spring and autumn respectively and annual evapotranspiration is 529 mm (Menció et al., 2017). La Pletera salt-marshes are considered brackish and hyperhaline coastal lagoons, with a well-preserved halophilic and psammophilic plant community. The area has been described as confined Mediterranean coastal ecosystem due to its isolation from the sea and from continental freshwaters (Badosa et al., 2006). In 1987 La Pletera salt-marsh has been affected by an incomplete construction of an urban development which filled its Northern part with rubble and sidewalks, and part of soils was also turned into agricultural activities and pasture (Fig. 1d). The building was interrupted in the early 1990 s letting an environmentally damaged residual area called Ruderal (RU).

2.3.1. Physical analysis Bulk density (BD) was determined by the cylinder method at sampling at 0–5, 5–20 and 20–40 cm depth by using 5 × 5 cm steel cylinders containing undisturbed soil samples according to Forster (1995). Particle size analysis was determined by the pipette method and aggregate stability was determined according to Kemper and Rosenau (1986) by using the previously separated aggregates tested with the Wet Sieving Apparatus of Eijkelkamp Agriresearch Equipment, The Netherlands. Measurements were carried out as follows: aliquots of both 0.25–2 mm and 2–5.6 mm aggregate fractions were moistened with distilled water by capillary action, placed in 0.25 mm and 2 mm sieves respectively and then subjected to vertical oscillatory sieving during 3 min in cups of distilled water. Each immersion–emersion cycle lasted 3 s, with a total of 60 cycles during 3 min, in which the aggregates were subjected to the dispersive forces of water. Soil aggregates surviving disruption and detachment were dried at 105 °C and weighed. The stability of aggregates to water (WSA) was calculated for each fraction and depth from the following equation, taking into account the sand content:

by long periods of confinement, when lagoons tend to dry out and increase their salinity (Quintana, 2002). Nowadays, confined coastal lagoons in Girona province are scarce and restricted to the two main nuclei (La Pletera and Baix Ter), both included in the Nature 2000 network. However, it is highly probable that this type of ecosystems were much more abundant in the past, not only in Girona, but in other floodplain areas around the Mediterranean coast. Their location (immediately behind the coastal sand bar) and shallow depth are probably the reason why they were drained and substituted by urbanized structures for tourism or converted in agriculture and pasture land. The drained lagoons were filled with rubbles and seaside sidewalks built before house constructions. The remaining confined coastal lagoons still conserve the natural hydrological characteristics based on a flooding–confinement pattern, which determine nutrient dynamics and plant species composition in these environments and the importance of conserving these areas is in their capacity of organic carbon fixation into their soils, thus contributing to reduce CO₂ emissions into the atmosphere. The man-made disturbance and the conversion to agriculture and pasture land of the salt-marsh areas have caused a reduction of almost 70% in terms of land use change, producing discontinuity in the ecosystem services, especially in carbon sequestration capacity. The aim of this work is to evaluate the organic carbon storing capacity of La Pletera salt-marsh soils and demonstrate the ability of these soils as valuable carbon sink with respect to those drained (for buildings), or converted to agriculture and pasture, in order to strengthen the importance of marshes in organic carbon sequestration against carbon loss. Produced data will provide generalizable results for an international audience.

WSA(%) =

(M(a + s) − Ms ) 100 (Mt − Ms )

where, M(a+s) is the mass of the resistant aggregates plus sand (g), Ms is the mass of the sand fraction alone (g), and Mt is the total mass of the soil sample (g).

2.2. Sampling and sample preparation 2.3.2. Chemical analysis Measurements of pH were carried out on 1:2.5 (w/v) soil water suspensions by means of a Dyson pH-meter of Dyson-Eutech Instruments, Spain (Forster, 1995). The soil electrical conductivity (EC) was carried out with a CON 510 conductivity meter of Eutech Instruments, The Netherlands and values were expressed as dS m−1 at 25 °C

Therefore, 6 sites were chosen for this study in 2015 (Table 1) according with the vegetation cover and soil type as follows: The Ruderal (RU) which is rubble cover almost 1.5 m thick mainly colonized by Phoeniculum vulgare Mill. and Brachipodium retusum (Pers.); the ELY coastal prairie which is colonized mainly by Elymus elymoides (Raf.); the 3

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Table 1 Physiographical and pedological characteristics of the studied soils at La Pletera (NE Spain). Soil

Parent material

Soil use

Plant cover species

Horizons

WRB

RU

Calcareous conglomerates

Rubbles

Brachipodium retusum (Pers.) Foeniculum vulgare Mill.

A/C

Gleyic Arenosol (Technic)

ELY

Coastal dune

Meadow

Elymus elymoides (Raf.)

A/C

Gleyic Arenosol (Eutric)

ART

Coastal dune

Salt-marsh

Arthrocnemum fruticosum L.

A/C

Gleyic Solonchak (Loamic)

SAL

Coastal dune

Salt-marsh

Salicornia patula Duval Jouve

A/C

Gleyic Solonchak (Arenic)

AGR

Calcareous sandstone

Cultivation

Zea mays L.

A/C

Calcaric Arenosol (Ochric)

AME

Calcareous sandstone

Artificial meadows

Medicago sativa L.

A/C

Calcaric Arenosol (Ochric)

RU: Ruderal soil environment; ELY: Elymus Elymoides (Raf.) soil environment; ART: Arthrocnemum fruticosum L. soil environment; SAL: Salicornia patula Duval Jouve soil environment; AGR: Corn (Zea mays L.) cultivated soil environment; AME: Artificial meadow (Medicago sativa L.) soil environment. WRB: World Reference Base for Soil Resources.

concentration was then calculated by:

(Forster, 1995). Soil organic carbon (SOC) analysis was performed by the dichromate oxidation method (Walkley and Black 1934). Total soil nitrogen (NT) was determined according to the Kjeldhal method (Bremner and Mulvaney, 1987).

C − TGRSP =

(H − S)(A × E × 1000) (C × M × D) × 1000

where: C-TGRSP is expressed in mg mL−1, H is the volume of titration solution for hot blank (mL), C is the volume of titration solution for cold blank (mL), S is the volume of titration solution for each sample (mL), M is the normality of K2Cr2O7 (eq L–1), D is the volume of K2Cr2O7 (mL), A is the volume of the sample (mL), E is the conversion factor in the oxidation process that occurs in the Cr6+ to Cr3+, the value is equal to 3. The respiration of the soil was determined by using a laboratory adaptation of the Keith and Wong method (Keith and Wong, 2006) and following the Grogan method (Grogan, 1998) for the appropriate correction for water formed during CO2 adsorption on soda lime. 150 g of fresh undisturbed soil samples collected at 0–5 cm depth were placed in 500 cm3 glass jar containing porcelain cups with 15 g of soda lime, previously oven dried at 105 °C and weighed with the accuracy of 0.01 mg. Samples were then incubated during seven days at 25 °C at dark. After incubation soda lime was dried overnight at 105 °C, cooled in a desiccator and weighed with the accuracy of 0.01 mg. The amount of CO2 absorbed by soda lime after incubation was calculated by using the correction factor proposed by Grogan (1998), taking into account the water obtained when soda lime reacts with CO2. Each mole of CO2 is bound with soda lime together with a mole of water, successively lost by oven drying. Dry mass increase before and after exposure would therefore underestimate the CO2 absorbed. The correction factor takes into account that 44 g of CO2 reacts with 74 g of Ca(OH)2 forming 100 g of CaCO3 and 18 g of water. The weight increase in soda lime is then 26 (i.e. 100–74), which gives the correction factor of 44/26 = 1.69 to be applied to the mass difference in order to obtain the true value of CO2 absorbed. Values were then expressed as g CO2 kg−1 day−1 soil (Keith and Wong, 2006; Rillig et al., 2003). Carbon of carbon dioxide (C-CO2) may be then calculated as follows:

2.3.3. Biological analysis Total glomalin related soil protein (TGRSP) was determined according to Rillig (2004). Briefly, 1 g of the fine earth fraction and 8 mL of a 50 mM trisodium citrate dihydrate solution at pH 8.0 were put in centrifuge tubs and then autoclaved at 121 °C for 60 min. After extraction, samples were centrifuged at 5000 rpm for 15 min and the supernatant collected and stored at 4 °C. This procedure was repeated until the supernatant was pale-yellow-coloured (at least 4 times), which indicates the absence of glomalin in the samples (Nichols and Wright, 2005). All extracts were then joined and glomalin quantified by the Bradford protein assay (Sigma Aldrich) with bovine serum albumin (BSA) as the standard. Easily extractable glomalin related soil protein (EEGRSP) was extracted with 8 mL of a 20 mM citrate solution, pH 7.0, by autoclaving at 121 °C but with only one extraction cycle, and then determined with the Bradford method. Taking into account that glomalin is a glycoprotein produced by arbuscular mycorrhizal fungi in symbiosis with land plant and then dispersed into the soil during the fungi life-cycle, the glomalin quantification is based on the reaction of Coomassie Brilliant Blue (CBB) G250 acidic solution binding to the BSA protein thus altering the absorbance properties of the dye. A total of 0.04 mL of BSA standard solutions (0, 25, 50, 100, 200 μg mL−1) was added to a 2 mL of 1:4 (v/v) acidic solution. The addition of protein results in a shift of the dye’s absorption from 465 to 595 nm, causing a visible colour change detected by spectrophotometric measurements. Similarly, 0.04 mL of the glomalin-extracted solution (containing the glycoprotein) was used to measure the unknown glomalin concentration of the soil samples. The assay is useful because the extinction coefficient of the dye-albumin complex solution is constant over a suitable concentration range (Bradford, 1976). In order to determine the organic carbon content in the total glomalin extracts (C-TGRSP) the dissolved organic carbon method of Vance et al. (1987) was performed. Briefly, 2 mL of 66.7 mM K2Cr2O7 was added to 4 mL of the extracts in a digestion tube together with 7 mL of a 2:1 acid mixture (H2SO4: H3PO4). Samples were then heated at 60 °C during 30 min in a digestion block and after cooling the excess of potassium dichromate was titrated, previous dilution with 100 mL of distilled water, with 0.05 N solution of ferrous ammonium sulphate hexahydrate using Ferroin as indicator. A heated and a room temperature blank were also prepared titrated. The organic carbon

C − CO2 = CO2

12 44

where 12 and 44 are the molecular weight of carbon and carbon dioxide respectively. 2.3.4. Data analyses The results were submitted to statistical analysis by using the program Statistics (Version 7.1, 2007, Statsoft Inc., Tulsa, OK, USA). One way ANOVA and Tukey HSD (Honestly Significant Difference) post-hoc test was used to check significant data variability within and among 4

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Table 2 Relevant soil properties at different depths of the studied soils at La Pletera (NE Spain). Standard error of the mean is reported. Soil 0–5 cm

N

SA (%)

SI (%)

CL (%)

BD (g cm−3)

pH

Texture

RU ELY ART SAL AGR AME

3 3 3 3 3 3

81.33 92.27 44.01 78.67 66.67 68.66

± ± ± ± ± ±

3 3 3 3 3 3

83.94 92.26 67.33 92.00 68.67 68.00

3 3 3 3 3 3

84.00 94.66 79.33 68.86 72.67 71.59

EC (dS m−1)

SOC (g kg−1)

NT (g kg−1)

8.32 12.33 12.94 9.87 9.67 12.06

10.67 ± 2.31 5.33 ± 1.51 27.32 ± 6.11 6.00 ± 4.00 17.33 ± 1.15 17.34 ± 1.15

8.00 ± 4.00 2.40 ± 1.06 28.67 ± 9.45 15.33 ± 2.31 16.00 ± 2.00 14.00 ± 2.00

LS S SCL LS SL SL

1.30 1.25 1.34 1.30 1.31 1.32

± ± ± ± ± ±

0.12 0.15 0.19 0.09 0.21 0.17

8.26 8.02 7.35 8.72 8.25 7.71

± ± ± ± ± ±

1.33 0.34 0.24 0.13 0.08 0.31

0.15 ± 0.05 0.25 ± 0.10 12.23 ± 2.03 5.87 ± 3.43 0.16 ± 0.02 1.06 ± 0.78

3.15 ± 1.21 23.63 ± 7.40 40.08 ± 2.52 4.40 ± 0.99 5.77 ± 0.83 11.45 ± 0.61

0.11 0.74 1.88 0.22 0.29 0.59

± ± ± ± ± ±

0.03 0.13 0.08 0.05 0.03 0.02

± ± ± ± ± ±

5.45 19.42 7.53 15.86 10.67 13.09

9.30 ± 4.88 4.41 ± 4.11 20.00 ± 9.17 2.67 ± 1.15 15.33 ± 6.11 22.00 ± 3.18

6.76 ± 3.61 3.33 ± 1.80 12.67 ± 6.11 5.33 ± 1.15 16.00 ± 4.00 10.00 ± 2.00

LS S SL S SL SL

1.38 1.33 1.25 1.34 1.52 1.44

± ± ± ± ± ±

0.15 0.18 0.20 0.17 0.17 0.22

8.36 8.40 8.41 8.71 8.19 7.73

± ± ± ± ± ±

0.25 0.18 0.16 0.27 0.12 0.20

0.12 0.31 4.26 3.14 0.18 1.21

± ± ± ± ± ±

0.03 0.14 0.48 0.99 0.04 0.77

3.29 ± 0.77 18.58 ± 3.63 14.94 ± 0.73 3.69 ± 2.81 5.17 ± 1.03 9.57 ± 1.69

0.10 0.39 0.46 0.17 0.25 0.37

± ± ± ± ± ±

0.01 0.03 0.02 0.02 0.03 0.03

± ± ± ± ± ±

14.19 21.54 19.21 23.73 14.57 7.59

9.33 ± 1.15 2.93 ± 0.46 6.67 ± 4.62 20.67 ± 14.46 14.00 ± 5.15 16.00 ± 4.00

6.67 ± 2.31 2.41 ± 1.06 14.00 ± 7.21 10.47 ± 6.43 13.33 ± 1.15 12.41 ± 2.56

LS S LS SL SL SL

1.40 1.35 1.37 1.40 1.54 1.49

± ± ± ± ± ±

0.12 0.08 0.14 0.11 0.21 0.19

8.50 8.71 8.51 8.72 8.26 7.93

± ± ± ± ± ±

0.09 0.31 0.10 0.19 0.06 0.11

0.05 0.44 2.87 2.28 0.18 0.85

± ± ± ± ± ±

0.02 0.32 0.48 0.69 0.02 0.34

2.52 7.04 6.02 1.96 4.22 6.59

0.07 0.13 0.24 0.11 0.36 0.27

± ± ± ± ± ±

0.01 0.02 0.04 0.03 0.02 0.02

5–20 cm RU ELY ART SAL AGR AME 20–40 cm RU ELY ART SAL AGR AME

± ± ± ± ± ±

1.05 0.44 1.62 1.44 0.62 2.91

RU: Ruderal soil environment; ELY: Elymus Elymoides (Raf.) soil environment; ART: Arthrocnemum fruticosum L. soil environment; SAL: Salicornia patula Duval Jouve soil environment; AGR: Corn (Zea mays L.) cultivated soil environment; AME: Artificial meadow (Medicago sativa L.) soil environment; N: Number of replications; SA: Sand; SI: Silt; CL: Clay; LS: Loamy sand; S: Sand; SCL: Sandy clay loam; SL: Sandy loam; BD: Bulk density; EC: Electrical conductivity; SOC: Soil organic carbon; NT: Total nitrogen.

(2010) inferred that increased water content and salinity in soil may inhibit the microbial activities, thereby reducing the decomposition of the organic matter and enhancing carbon sequestration. Values of EC decreased by 65% and 76% in ART soil and by 46% and 61% in SAL soil at 5–20 and 20–40 cm respectively (Table 2). Chengji Shen et al. (2015) suggested that upward salt-marsh salinity may be often affected by the combined influence of tidal inundation, precipitation, evapotranspiration, and inland freshwater input. It is therefore reasonable to assume that ART and SAL soil environments can be periodically washed throughout the profile justifying their EC decrease with depth. Soil RU, ELY, AGR and AME showed low to very low EC values in agreement with their current use (Table 2). Results of soil organic carbon (SOC) were highly different among the investigated soils. The highest SOC value was found in ART soil at 0–5 cm depth (40.08 g kg−1) mainly attributed to litter production capacity of perennial Arthrocnemum fruticosum L. and subsequent organic matter incorporation, and the lowest in RU soil (3.15 g kg−1) being the Ruderal landfill scarcely colonized by plants with poor organic debris deposition, thus low organic matter content. SOC in ART soil increased by 1,160% that in RU and by 70%, 811%, 595% and 250% that in ELY, SAL, AGR and AME respectively (Table 2). The difference with AGR and AME soils may be justified by current land use and related anthropic pressure, which may flatten SOC content with respect to natural environments (Lai et al., 2014). The same authors referred that plant canopy and litter cover are paramount for long-term carbon enrichment in soil and found comparatively higher C inputs in soils under than out the main vegetation. Moreover, they postulated that the aboveground decomposing litter might enhance soil biological activity regulating carbon dynamics and soil respiration rather than soil temperature and moisture. The high SOC difference between ART and SAL (811%) may be effectively attributed to the plant community of the two soils. Arthrocnemum fruticosum L. (Fig. 2a) is a perennial species extended over a large part of Pletera area whilst Salicornia patula Duval Jouve (Fig. 2b) is an annual species and its presence is rather less extended. This may have an effect on soil organic matter due to denser vegetation in ART (Fig. 2c) than SAL (Fig. 2d). ART soil would therefore have larger

each soil environments along the three depths (0–5, 5–20, 20–40 cm). A multivariate factor analysis with principal component method was also carried out by the Statistica 7.1 software to create a factor structure with variables responsible for most of the global data variance. In addition, scoring each factor including variables and matching them with the selected soil environments provided information about the relationships between treatments (soil environments) and variables to emphasize trends of soil properties and carbon storage in the studied area.

3. Results and discussion 3.1. Soil physical and chemical characteristics All soil samples presented abundant sand in agreement with their parent material and littoral location (Tables 1 and 2). Only the ART soil showed a sandy clay loam texture for its higher amount of clay especially at 0–5 cm depth, which was 117% higher with respect to the mean of clay content of the other soil environments (Table 2). At 0–5 cm depth the textural class varied from sandy in the ELY soil, loamy sand in RU and SAL soils and sandy loam in AGR and AME soils. At 5–20 cm and 20–40 cm depth the textural class changed slightly though in general the sand amount was the highest fraction (Table 2). Bulk density (BD) values were rather similar among the soil and at any depth. A small BD increase at 5–20 and 20–40 cm in AGR and AME soil environments may be attributed to agricultural management consisting in crop-fallow rotation and periodical grazing respectively, which may cause some compaction of beneath soil layers (Table 2). Soil pH was slightly to strong alkaline and showed an increasing trend along depths (Table 2). Electrical conductivity (EC) was high both in SAL (5.87 dS m−1) and ART (12.23 dS m−1) soils (Table 2). According to USDANRCS (2017) a soil is considered saline with pH values < 8.5 and EC values > 4 dS m−1. SAL soil was classified as slightly saline (4–8 dS m−1) and ART soil as moderately saline (8–16 dS/m−1). Slight and moderate salinity conditions have been reported to positively influence the rate of carbon sequestration (Connor et al., 2001), whilst li et al. 5

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Fig. 2. Fotographs of ART (a, c, e) and SAL (b, d, f) salt-marsh soils morphological characteristics.

very high SOC content (up to 160 g kg−1) in the upper shallow organic horizon with sharp decrease of SOC along depth suggesting a larger carbon storage capacity in the upward layers. Similar trend was found in ART soil. Other soils showed a much lesser and heavenly distributed SOC content along depth (Table 2). As expected SOC and NT were significantly correlated at 0–5 cm (NT = 0.04SOC-0.01, r = 0.97, P < 0.01) and 5–20 cm (NT = 0.02SOC + 0.11, r = 0.88, P < 0.05) while no correlation was found at 20–40 cm depth.

surface organic decaying debris enrichment (Fig. 2e), suggesting larger soil microbial activity and positive trend for carbon stock potential (Lai et al., 2014) with respect to SAL soil (Fig. 2f). SOC data in ART soil decreased by 62% at 5–20 cm and by 84% at 20–40 cm, whilst ELY soil showed a relatively higher amount of SOC at 5–20 (+24%) and 20–40 cm (+32%) with respect to ART soil. According to Duchaufour (1982), isohumic characteristics are likely to occur in prairie. Grass species like Elymus elymoides (Raf.) may produce larger amounts of organic matter at lower depth due to dead dense roots contributing to subsurface organic compounds enrichment and a probable 2A horizon formation. Fourqurean et al. (2012) reported that coastal grass ecosystems may store large amounts of carbon at lower depths. Besides that, the capacity of SOC accumulation in ART soil resulted in a range of 22–26% higher than ELY soil along the investigated depths. Van de Broek et al. (2016) reported the ability of brackish soils to accumulate

3.2. Aggregate stability, organic carbon and glomalin Water stable aggregates (WSA), is a measurement of soil structure resistance against disruptive forces caused by rapid wetting. Soil structure, defined as the combination of soil mineral and organic 6

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(WSA(0.25-2) = 0.97WSA(2-5.6)-0.96, r = 0.94, P < 0.01). Caravaca et al. (2005) reported that the substances responsible for aggregate stability are prevalently organic hence of biological origin and usually develop in the rhizosphere, and Gregory (2006) remarked that root/ rhizosphere soil interactions are more sensitive and abundant in topsoil layers. Thus, release of organic compounds promoting aggregation is more likely to occur in surface soil. In general, Arthrocnemum fruticosum L. and Elymus elymoides (Raf.) communities showed the higher root density and SOC content was 3.3 and 5.6 times, respectively, that of the average of soil under Medicago sativa L., Zea mays L. and Salicornia patula Duval Jouve (Table 3) which also showed lower root density. Structural stability of aggregates increased with increasing SOC content and clearly suggested the differential aggregation ability of organic carbon (SOC) in the upward layer for the studied soil environments but RU (Fig. 3). As no significant Pearson correlation was found between SOC and WSA at 0–5 cm depth a logarithmic regression was tried and fitted well SOC data in both fractions: WSA(0.25-2) = 19.87ln (SOC) + 28.91, r = 0.81; WSA(2-5.6) = 23.145ln(SOC) + 9.29, r = 0.92. The guidelines for interpreting correlation coefficient r in logarithmic regressions consider a strong correlation between the analysed terms of the equation when 0.7 < |r| ≤ 1 (Fig. 4a, b). At other depths no correlation was found between SOC and WSA suggesting that the 0–5 cm layer has a relevant importance in maintaining soil organic carbon stock and structure (Schmidt et al., 2011; Bai et al., 2016). At this depth ART and ELY soils showed the highest WSA in both fractions, also corresponding to higher glomalin values (Table 3), which implicitly may indicate the role of mycorrhizal fungi in WSA as reported by Caravaca et al. (2005). WSA values followed in decreasing order in AME, AGR, SAL and RU soils for both WSA(0.25-2) and WSA(25.6) aggregate fractions (Table 3) in agreement with their lower SOC and glomalin content. Our results may suggest that soil microbial activity and soil properties related to microbial activity, such as SOC and aggregate stability, may be determined by the type of the halophytic species, as also pointed out by Caravaca et al. (2005). Consistent decrease of WSA (−36%) was observed in the 2–5.6 mm fraction with respect to the 0.25–2 mm fraction in SAL soil. It was postulated that the largest aggregate fraction might be more easily disaggregated due to

Table 3 Structural stability of aggregates and glomalin related soil protein at different depths at La Pletera (NE Spain). Standard error of the mean is reported. Soil 0–5 cm

N

WSA (%)

WSA(2-5.6) (%)

EEGRSP (g kg−1)

TGRSP (g kg−1)

RU ELY ART SAL AGR AME

3 3 3 3 3 3

27.21 87.63 88.78 73.75 77.81 79.92

± ± ± ± ± ±

10.44 9.01 2.84 9.02 1.59 12.17

20.25 86.87 86.94 47.04 63.26 68.81

± ± ± ± ± ±

9.18 8.52 1.15 16.11 25.84 38.14

0.22 1.02 1.14 0.26 0.43 0.80

± ± ± ± ± ±

0.08 0.12 0.19 0.05 0.06 0.20

0.56 5.31 8.88 0.46 1.17 2.47

± ± ± ± ± ±

0.11 2.09 2.93 0.18 0.11 0.55

3 3 3 3 3 3

21.20 83.20 86.04 34.50 66.67 66.97

± ± ± ± ± ±

7.67 8.49 1.15 11.85 2.94 1.67

19.56 81.72 82.70 39.26 30.53 25.18

± ± ± ± ± ±

9.33 2.73 13.06 34.96 6.95 13.61

0.22 0.42 0.69 0.17 0.48 0.65

± ± ± ± ± ±

0.04 0.13 0.15 0.12 0.05 0.11

0.70 2.02 2.89 0.82 2.29 3.01

± ± ± ± ± ±

0.10 0.58 0.79 0.09 0.12 0.29

3 3 3 3 3 3

20.12 14.78 33.06 28.30 52.99 40.56

± ± ± ± ± ±

5.78 12.36 17.71 17.99 12.54 8.50

18.68 ± 6.22 15.34 ± 16.62 8.35 ± 6.63 2.92 ± 1.22 9.62 ± 6.50 18.04 ± 11.64

0.20 0.15 0.25 0.30 0.57 0.53

± ± ± ± ± ±

0.10 0.09 0.06 0.25 0.07 0.04

0.53 0.89 1.03 0.74 1.63 1.69

± ± ± ± ± ±

0.24 0.37 0.51 0.24 0.38 0.28

(0.25-2)

5–20 cm RU ELY ART SAL AGR AME 20–40 cm RU ELY ART SAL AGR AME

RU: Ruderal soil environment; ELY: Elymus Elymoides (Raf.) soil environment; ART: Arthrocnemum fruticosum L. soil environment; SAL: Salicornia patula Duval Jouve soil environment; AGR: Corn (Zea mays L.) cultivated soil environment; AME: Artificial meadow (Medicago sativa L.) soil environment; N: Number of replications; WSA (0.25-2): Water stability of aggregates in the 0.25–2 mm fraction; WSA (2-5.6): Water stability of aggregates in the 2–5.6 mm fracgtion; EEGRSP: Easily extractable glomalin related soil protein; TGRSP: Total glomalin related soil protein.

particles may be influenced by many physical, chemical, and biological factors also including the soil use history (Oades, 1984). Data of WSA (Table 3) in the two analysed aggregate fractions (0.25–2 mm and 2–5.6 mm) were significantly correlated only at 0–5 cm depth

100 ELY

90

ART

80 AME AGR

WSA(2-5.6 mm) (%)

70 60

SAL

50 40 30 RU

20

r = 0.94

10 0

0

10

20

30

40

50

60

70

80

90

100

WSA(0.25-2 mm) (%) Fig. 3. Linear regression between WSA(0.25-2 Pearson correlation refers to P < 0.01.

mm)

and WSA(2-5.6

mm)

representing the aggregate stability of the investigated soil environments at 0–5 cm depth.

7

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a 100 ART

ELY AGR SAL

WSA(0.25-2 mm) (%)

80

AME

60

40 RU r=0.81

20

0

0

10

20

30

40

50

-1

SOC (g kg )

b 100 ELY

ART

80

WSA(2-5.6 mm) (%)

AME AGR 60 SAL 40

RU

20

0

0

r=0.92

10

20

30

40

50

-1

SOC (g kg ) Fig. 4. Logarithmic regressions fitting values of WSA(0.25-2

mm)

the very low SOC content (4.40 g kg−1) in SAL soil at 0–5 cm depth. Six et al., (2000) observed that aggregate disruption is likely to occur in larger macroaggregates because microaggregates may store more SOC in microsites, thus increasing their resistance to water. The low WSA value in RU soil at any depth (Table 3) clearly indicated that the allochthonous material used to replenish the disturbed area had a very poor structure and warns on its negative impact by changing the natural ecosystems dynamics. Irrespective to SOC drop at 5–20 cm depth

and WSA(2-5.6

mm)

against SOC values at 0–5 cm depth.

(Table 2), WSA values in ELY and ART soils were only slightly affected in both WSA(0.25-2) and WSA(2-5.6) aggregate fractions, suggesting a considerable aggregating role of SOC even at this depth. By contrast, WSA values decreased substantially in all soils in the two fractions at 20–40 cm depth (Table 3) which was attributed to further SOC decrease. This trend may indicate that WSA is primarily controlled by SOC and that aggregation in these soils is more related to SOC than clay (Tisdall and Oades, 1982; Celik, 2005). Significant correlation was 8

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a

found neither between clay and SOC nor between Clay and the two aggregate fractions at any depth. The determination of easily extractable glomalin (EEGRSP) and total glomalin (TGRSP) produced results in agreement with the content of soil organic carbon (SOC) in each soil environment (Table 3). Glomalin has been described as a glycoprotein produced by arbuscular mycorrhizal fungi (AMF) and its concentrations may range from 2 to 15 g kg−1 in temperate Mediterranean type of climate (Lovelock et al., 2004). Besides the fact that glomalin is yet to be a biochemically defined protein, Driver et al. (2005) reported that it is firmly incorporated into the hyphal wall and can accumulate in soils via hyphal turnover and release of glomalin from dead hyphae, and Francaviglia et al. (2017) suggested that early glomalin formation may enhance natural biological fertility and nutrient cycling, highlighting the role of soil microbial diversity and arbuscular mycorrhizal fungi communities in soil quality. Its positive effects on soil aggregation have been early demonstrated by Rillig (2004). Emran et al. (2012), investigating the organic matter recovery in abandoned land under renaturalization suggested positive contributions of glomalin to both the recalcitrant carbon pool and soil structure and postulated a fast or slow glomalin turnover, probably depending on the chemical characteristics of this organic compound. The presence of recalcitrant carbon components in glomalin has been assessed by Jing Zhang et al. (2017). According to Lutgen et al. (2003) soils presenting higher EEGRSP/TGRSP ratio may indicate faster glomalin turnover associated with carbon loss by enhanced microbial activity, while lower ratios may represent soils with more conservative carbon dynamics. Gispert et al. (2018) reported that soils with considerable SOC content may renew labile organic compounds stocking stable SOC fractions contemporarily. Older soils would therefore enrich the soil surface layers with more active organic fractions (useful for nutrient cycling) while storing recalcitrant organic fractions, glomalin included (useful for aggregate stability). In our soils we found the following EEGRSP/TGRSP ratios: 0.33 ± 0.14, 0.19 ± 0.09, 0.10 ± 0.04, 0.30 ± 0.11, 0.36 ± 0.12 and 0.32 ± 0.11 for soil RU, ELY, ART, SAL, AGR and AME respectively at 0–5 cm depth. If we assume that low EEGRSP/TGRSP ratios may indicate more conservative carbon dynamics and i) that EEGRSP is formed by more labile organic compounds released via hyphal turnover (Driver et al., 2005) or, ii) that EEGRSP is an easily mineralizable fraction of TGRSP along its lifecycle, we can thus postulate: iii) that EEGRSP may be quickly incorporated into TGRSP or, iv) that TGRSP might lose low amounts of carbon as EEGRSP. This trend was hypothesized when plotting EEGRSP against TGRSP with data of 0–5 cm depth. The strong correlation (r = 0.98) found in the logarithmic regression (EEGRSP = 0.35ln(TGRSP) + 0.38) showed in Fig. 5a may suggest that TGRSP turnover may have a threshold, at least in ART soil, balanced by mineralization process. By using the logarithmic model we tried a theoretical TGRSP value of 21.76 g kg−1 for ART soil (i.e. a 100% increase with respect to the current TGRSP value of 10.88 g kg−1) and we obtained an EEGRSP value of 1.46 g kg−1, that is, by increasing 100% the current TGRSP content in ART soil at 0–5 cm depth, the EEGRSP content increased only by 28% (from 1.14 g kg−1 to 1.46 g kg−1), which may support the previous assumptions of low EEGRSP turnover. At 5–20 cm depth EEGRSP plotted against TGRSP fitted a linear regression equation (EEGRSP = 0.05 + 0.24TGRSP) with significant correlation (r = 0.89, P < 0.05) probably indicating that at lower depth absolute glomalin values decrease considerably even though there still is increasing reciprocity between EEGRSP and TGRSP (Fig. 5b). At 20–40 cm the scatter of points was not significant (Fig. 5c) probably due to uneven distribution of glomalin along the soil profile. Independently of glomalin values, natural soils (ELY, ART and SAL) showed a logical decreasing pattern if compared with RU, AGR and AME soils where glomalin trend was fluctuating. Wenjie Wang et al. (2017) stated that glomalin may migrate along the profile in farmland soils and Wright et al. (1999) reported that soil in grass cover contained 45% more glomalin than tillage soil. Effectively, the highest values of

1.4 ART

1.2

EEGRSP (g kg-1)

ELY 1.0 AM E

0.8 0.6 AGR 0.4

SAL RU

r=0.98

0.2 0.0 0

2

4

6

8

10

12

-1

TGRSP (g kg )

b 0.8 0.7

ART

AM E

EEGRSP (g kg-1)

0.6 AGR

0.5

ELY

0.4 0.3 RU SAL

0.2 0.1

r=0.89

0.0 0.0

0.5

1.0

1.5

2.0

2.5

3.0

-1

TGRSP (g kg )

c 0.6 AM E

EEGRSP (g kg-1)

0.5 AGR

0.4 SAL

0.3

RU

0.2

ART ELY

0.1 0.0 0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

-1

TGRSP (g kg ) Fig. 5. Logarithmic and linear regression equations between EEGRSP and TGRSP (a: 0-5 cm; b: 5–20 cm; c: 20–40 cm). High correlation coefficients suggest low turnover of EEGRSP into TGRSP, thus corroborating stable organic carbon conservation ability of ART > ELY > AME > AGR > SAL > RU. Pearson correlation significant at P < 0.01. Significance is lost at 20–40 cm depth.

both EEGRSP and TGRSP cm were found at 20–40 depth in AGR and AME soil (Table 3). SOC and TGRSP data at 0–5 cm depth fitted a linear regression equation (TGRSP = 0.48 + 0.72SOC) highly significant at p < 0.01 (Fig. 6a), while correlation was weaker (P < 0.05) at 5–20 cm depth (Fig. 6b) or not significant at 20–40 cm depth (Fig. 6c). The results seem 9

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a 12

20–40 cm (85% less). In the same soil TGRSP is 10.88 g kg−1 in the upper layer (0–5 cm) and decreases by 73% at 5–20 cm and by 90% at 20–40 cm. This trend strengthened previous statements that glomalin may be part of soil organic matter (Rillig et al., 2003; Gispert et al., 2013). The highest value of EEGRSP (1.14 mg g−1) and TGRSP (10.88 g kg−1) was found in the ART soil and the lowest was always in RU (0.22 g kg−1 and 0.66 g kg−1 respectively). Glomalin values in SAL soil were also low (0.26 g kg−1 and 0.86 g kg−1 respectively) reflecting the low SOC values (Table 3). In the 0–5 cm layer glomalin decreased in this order: ART > ELY > AME > AGR > SAL > RU in both EEGRSP and TGRSP. Glomalin has also a beneficial effect on soil aggregation (Rillig, 2004). Also, Hammer and Rillig (2011) proven that soil salinity conditions may increase glomalin production. Findings of this work demonstrated that higher glomalin values corresponded to high aggregate stability in the studied aggregate fractions of salt-marsh soils. As for SOC, TGRSP and WSA((0.25-2 mm) and WSA(2-5.6 mm) data at 0–5 cm depth fitted a logarithmic model (y = 14.48ln(x) + 65.11 and y = 17.82ln(x) + 50.88) showing a strong correlation (Fig. 7a and b). Likewise, a linear regression equation (y = 28.11x + 14.17, P < 0.01) was successfully tried at 5–20 cm depth for WSA((0.25-2 mm) and TGRSP (Fig. 7c). By contrast, data in Fig. 7d, e and f did not show any significance. This pattern may further suggest that glomalin is strictly associated to SOC and this is especially magnified in the 0–5 cm layer where slow or recalcitrant glomalin carbon may exist ensuring high particle aggregation (Rillig, 2004). SOC and glomalin decline along depth affect structural stability of aggregates especially in the largest aggregate fraction of natural soils, whilst recalcitrant glomalin may persist in the lowest aggregate fraction of cultivated soils at lower depth (Koide and Peoples, 2013). It seems therefore reasonable to assume that the 0–5 cm depth (especially of ELY and ART soils) is responsible of the large part of the SOC, TGRSP and WSA dynamics outlining the importance of this shallow layer in maintaining ecosystems functionality.

ART

TGRSP (g kg-1)

10 8 6

ELY

4

AME

2 0

r=0.99

AGR SAL RU 0

10

20

30

40

50

-1

SOC (g kg )

b 3.0

ART

TGRSP (g kg-1)

2.5 ELY

AME

2.0 1.5

AGR

1.0

SAL RU

0.5 0.0

r=0.84 0

5

10

15

20

3.3. Potential soil respiration, organic carbon loss and storage

-1

SOC (g kg )

Carbon dioxide (CO2) emission from soil was determined in laboratory by potential soil respiration trials using fresh soil of the 0–5 cm depth, as this was the most active layer in terms of soil carbon dynamics (Table 4). In addition, and at the same depth, we determined the carbon content of TGRSP, namely C-TGRSP. The values of C-TGRSP showed the same decreasing order of TGRSP: ART > ELY > AME > AGR > SAL > RU and the highest value (3.75 g kg−1) such that of TGRSP (8.88 g kg−1) was found in ART soil (Table 4). Carbon dioxide emission potential of RU soil (2.23 g kg-1day−1) was similar to that of ART soil (2.73 g kg-1day−1) but RU had very low organic carbon as this material corresponds to the quasi-inert rubble cover used to replenish the ancient salt-marsh soil, so that its carbon loss potential would be much higher. Even though C-CO2 values may be considered theoretical (Table 4), SAL, AGR and AME soils showed potential carbon loss of 22.72%, 20.45% and 11.62% with respect to their SOC content (Table 5). These findings may suggest that conversion of salt-marsh soils into agropastoral systems may incur in relevant decrease of soil organic carbon, and proper organic supply should be managed. The soil colonized by Salicornia patula Duval Jouve (SAL) may deserve also special attention to secure a surface organic mantle at 0–5 cm depth. Without strongly altering the Salicornia patula Duval Jouve ecosystem, plants of Arthrocnemum fruticosum L. should be randomly grown in order to increase litter production and consequent incorporation of organic decaying debris. Independently of absolute CO2 values, the lowest C-CO2 loss percentage with respect to SOC was found in ELY (8.63%) and ART (1.80%) soils. The mineralization coefficient q values calculated as the ratio C-CO2/SOC (Table 4) were considerably lower in ELY and ART soils (0.09 and 0.02 respectively) than RU (0.19), SAL (0.22), AGR (0.20) and AME (0.12), and indicated additional evidence of their low potentially-mineralizable carbon. In fact, q values of

c 1.8

AME

AGR

1.6 TGRSP (g kg-1)

1.4 1.2

ART

1.0

ELY

0.8 0.6

SAL

0.4

RU

0.2 0.0

0

1

2

3

4

5

6

7

8

SOC (g kg-1) Fig. 6. Linear regression equations between TGRSP and SOC at any investigated depth strengthening the relationship between these two soil components and confirming that TGRSP is part of SOC. a) 0–5 cm depth, P < 0.01; b) 5–20 cm depth, P < 0.05; c) 20–40 cm depth, no significant.

reasonable when referring to organic carbon compounds along the investigated soils and depths. Especially in ART soil the organic carbon (SOC) is mainly concentrated in the 0–5 cm layer (40.08 g kg1) and drops to 14.94 g kg−1 at 5–20 cm (63% less) and 6.02 g kg−1 at 10

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a

b

AGRAME 80 SAL

100

ART

ELY

60 40

RU r=0.75

20 0

0

2

ELY

80 WSA(2-5.6 mm) (%)

WSA(0.25-2 mm) (%)

100

4

6

8

10

AME AGR

60

SAL

40 RU

20 0

12

0

r=0.88

2

4

-1

ART

AME

AGR

60 SAL

40

RU

0.5

r=0.90

1.0

1.5

2.0

ELY

80 WSA(2-5.6 mm) (%)

WSA(0.25-2 mm) (%)

ELY

2.5

60

20 0 0.0

3.0

ART

SAL

40

TGRSP (g kg-1)

AGR

AME

RU

0.5

1.0

1.5

2.0

2.5

3.0

TGRSP (g kg-1)

e

f

100

100

80

80

60

WSA(2-5.6 mm) (%)

WSA(0.25-2 mm) (%)

12

100

80

20

10

d

100

40

8

TGRSP (g kg )

c

0 0.0

6

-1

TGRSP (g kg )

20

ART

AGR SAL RU

ART

AME

ELY

ELY

60 40 20

RU ART

AME AGR

0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

SAL 0 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

TGRSP (g kg-1)

TGRSP (g kg-1)

Fig. 7. Logarithmic and linear regression equations of WSA(0.25-2 mm) and WSA(2-5.6 mm) against TGRSP (a, b 0.5 cm); (c, d 5–20 cm); (e, f 20–40 cm). Further evidence that aggregate stability depends largely on glomalin and that glomalin is part of SOC is given. Pearson correlation significant at P < 0.01.

11

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3.4. Carbon budget

Table 4 Carbon dioxide emission potential, organic carbon from CO2, organic carbon from glomalin related soil protein and mineralization coefficient of the studied soils at 0–5 cm depth at La Pletera. Standard error of the mean is reported. Soil 0–5 cm

CO2 (g kg-1day−1)

C-CO2 (g kg-1day−1)

C-TGRSP (g kg−1)

q

N

RU ELY ART SAL AGR AME

3 3 3 3 3 3

2.23 7.36 2.73 3.68 4.33 4.89

0.61 2.01 0.74 1.00 1.18 1.33

0.16 2.04 3.75 0.32 0.46 1.00

0.19 0.09 0.02 0.22 0.20 0.12

± ± ± ± ± ±

0.33 0.44 0.29 0.87 0.73 0.79

± ± ± ± ± ±

0.12 0.12 0.08 0.24 0.20 0.22

± ± ± ± ± ±

0.07 0.62 1.11 0.08 0.11 0.12

± ± ± ± ± ±

Carbon sequestration capacity and/or loss among the selected soil environments at 0–5 cm depth was scaled by using SOC, C-TGRSP and C-CO2 expressed as Mg ha−1 (Table 5). As expected, ART soil showed higher SOC stock (27.47 ± 4.25 Mg ha−1). SOC was 44%, 72%, 86% 89%, and 92% lower in ELY, PAS, AGR, SAL and RU than ART soil. Likewise, the highest C-TGRSP value (2.51 Mg ha−1) was obtained for ART soil (Table 5) and other soils followed the same decreasing pattern (-47%, −73%, −88%, −91%, −96%). The higher C-CO2 value (1.26 Mg ha−1) was found in ELY soil and was associated to its lowest bulk density (1.25 g cm−3). The organic carbon loss susceptibility was explored by the C-CO2/ SOC ratio which provided, though theoretically, an indication of how the studied soils are sensitive to this process (Table 5). ART soil under Arthrocnemum fruticosum L. with only 1.83% of carbon loss susceptibility with respect to its SOC content resulted the most appropriate towards a carbon conservation perspective. Natural meadows soil (ELY) under Elymus elymoides (Raf.) and artificial meadows soil (AME) under Medicago sativa L. had intermediate C-CO2/SOC values (8.26% and 11.64% respectively) but AME increased by 41% with respect to ELY, indicating that conversion from natural to man-made ecosystems may negatively affect organic carbon balance (Pendleton et al., 2012). This assumption was even further supported by the C-CO2/SOC value of 20.37% for the agricultural soil (AGR). Moreover, while natural meadow may presumably improve its carbon storage ability along time thereby reducing its C-CO2/SOC ratio, AGR and AME soils may be subjected to SOC decline if not properly managed. The highest carbon emission potential (22.72%) was recorded in SAL soil under annual Salicornia patula Duval Jouve and attributed to scarceness of litter accumulation producing very low SOC. Similarly, C-TGRSP/SOC ratio may represent the stable carbon fraction to total SOC, and again ART soil produced the best value (9.34%) whilst the lowest was found in RU soil with 4.83%. The sequence of stable carbon enrichment followed this order ART > AME > ELY > AGR > SAL > RU (Table 5). On average, ART soil resulted 26% more enriched of stable organic carbon and was 38% less sensitive to carbon dioxide production with respect to the other investigated soils, strengthening the aptitude of this soil to carbon sequestration against carbon loss. In a comparative study of coastal sediments, Adame et al. (2012) found that fungal activity and glomalin production was higher in coastal salt-marsh covered by Chenopodiaceae and Arthrocnemum fruticosum belongs to this family of plants. Moreover, salt marsh plants, including chenopods, have been early observed to have AM fungal symbionts (Hoefnagels et al. 1993). Effectively, mycorrhizal fungi can contribute to soil carbon sequestration by immobilizing carbon in living fungal tissues and by producing recalcitrant compounds that remain in the soil following fungal senescence (Treseder et al., 2007).

0.10 0.07 0.01 0.11 0.07 0.06

RU: Ruderal soil environment; ELY: Elymus Elymoides (Raf.) soil environment; ART: Arthrocnemum fruticosum L. soil environment; SAL: Salicornia patula Duval Jouve soil environment; AGR: Corn (Zea mays L.) cultivated soil environment; AME: Artificial meadow (Medicago sativa L.) soil environment; N: Number of replications; CO2: Potential carbon dioxide loss by soil respiration; C-CO2: Carbon of carbon dioxide; C-TGRSP: Carbon of total glomalin related soil protein; q: Mineralization coefficient.

ELY and ART soils resulted 102% and 812% lower respectively than the mean of the other investigated soils, corroborating that coastal halophites and prairie soils may be able to capture carbon and sequester it into the soil while maintaining high primary production in these soil environments (Jones et al., 2009). However, carbon sequestration capacity of ART soil may be much larger because its q and C-CO2 values decreased by 77% and 63% and C-TGRSP values increased by 84% with respect to ELY soil. Glomalin enrichment in ART soil might be associated to higher mycorrhizal activity which benefits plant nutrient uptake and soil properties (Ruiz-Lozano et al., 2012). ART soil had higher SOC, NT, glomalin, WSA and very low CO2 emission. Barea et al. (2005) reported that AMF symbiosis influences nutrient cycling in soil/ plant system and improves plant health through increased protection against biotic and abiotic stresses, and soil structure through aggregate formation. Rietz and Haynes (2003) reported that electrical conductivity (EC) has a negative impact on CO2 release in soils irrespective of climate and origin of salinity. Increasing salt concentration may inhibit microbial growth and activity due to osmotic stress, thus hindering enhanced mineralization. At this regard, a linear regression equation was tried between CO2 and EC. When data of all selected soils at 0–5 cm were used, the equation was CO2 = 4.77–0.17EC, r = 0.440, no significant; instead, when data of soil RU were discarded, the equation changed as CO2 = 5.62–0.26EC, r = 0.76, P < 0.05, indicating salinity conditions as limiting factor for CO2 emission, especially for ART soil (Fig. 8). Under field conditions Setia et al. (2010, 2011) found 50% reduction in CO2 emission from soils with EC of 5.10 dS m−1 compared to a non-saline soil.

Table 5 Amounts of SOC, TGRSP, TGRSP, C-TGRSP and C-CO2 (Mg ha−1) calculated by using BD values, and the proportion of TGRSP-C and C-CO2 to SOC at 0–5 cm depth of the studied soils at La Pletera (NE, Spain). Standard error of the mean is reported. Soil 0–5 cm

N

SOC Mg ha−1

C-TGRSP Mg ha−1

C-TGRSP/SOC (%)

C-CO2 Mg ha−1

C-CO2/SOC (%)

RU ELY ART SAL AGR AME

3 3 3 3 3 3

2.06 ± 0.89 15.12 ± 3.17 26.86 ± 4.25 2.86 ± 067 3.78 ± 1.12 7.56 ± 3.28

0.10 1.31 2.51 0.21 0.30 0.66

4.83 8.66 9.34 7.34 7.94 8.73

0.39 1.26 0.49 0.65 0.77 0.88

18.90 ± 7.70 8.26 ± 2.59 1.83 ± 0.42 22.72 ± 13.04 20.37 ± 18.22 11.64 ± 9.45

± ± ± ± ± ±

0.04 0.13 0.56 0.07 0.10 0.18

± ± ± ± ± ±

2.00 2.45 1.95 2.56 3.18 4.03

± ± ± ± ± ±

0.13 0.30 0.18 0.20 0.46 0.32

RU: Ruderal soil environment; ELY: Elymus Elymoides (Raf.) soil environment; ART: Arthrocnemum fruticosum L. soil environment; SAL: Salicornia patula Duval Jouve soil environment; AGR: Corn (Zea mays L.) cultivated soil environment; AME: Artificial meadow (Medicago sativa L.) soil environment; N: Number of replications; SOC: Soil organic carbon; TGRSP: Total glomalin related soil protein C-TGRSP: Organic carbon of total glomalin related soil protein; C-CO2: Carbon of carbon dioxide. 12

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8 ELY 7

CO2 (g kg-1day-1)

6 AME

5

AGR 4

SAL

3

ART

2 r=0.76 1 0

0

2

4

6

8

10

12

14

-1

EC (dS m ) Fig. 8. Linear regression between CO2 and EC after discarding allochthonous soil RU. Pattern indicates that EC may reduce microorganism activity thus reducing carbon dioxide emission. Pearson correlation significant at P < 0.05. Table 6 Analysis of variance (one way ANOVA) and Tukey's honestly significant difference (HSD) post hoc test for data variability within and among soil environments at La Pletera salt-marsh (NE Spain). Soil

Selected variables CL F

EC P

SOC

CO2

NT

WSA(0.25-2)

WSA(2-5.6)

EEGRSP

TGRSP

C-TGRSP

F

P

F

P

F

P

F

P

F

P

F

P

F

P

F

P

F

P

Within soil environments RU 0.15 0.86 ELY 0.47 0.23 ART 13.90 ** SAL 4.69 0.06 AGR 1.00 0.42 AME 2.51 0.16

0.24 0.64 50.1 1.61 0.50 0.22

0.18 0.56 ** 0.27 0.63 0.81

0.01 38.95 295.2 1.29 2.58 4.62

0.98 ** ** 0.34 0.16 *

1.91 99.82 849.0 7.18 12.68 141.88

0.23 ** ** * ** **

1.99 88.0 24.7 10.29 19.55 27.11

0.22 ** ** ** ** **

0.65 49.0 33.8 10.02 8.26 16.29

0.55 ** ** ** * **

0.03 1.16 63.2 3.36 8.74 3.83

0.97 0.38 ** 0.10 * 0.08

0.20 45.3 28.6 0.50 4.12 3.07

0.82 ** ** 0.63 0.07 0.12

0.89 9.80 26.3 4.93 3.00 2.97

0.46 ** ** * 0.12 0.13

0.04 9.19 17.8 5.01 5.18 5.58

0.96 ** ** * * *

Among soil environments 0–5 cm 7.2 ** 5–20 cm 4.02 * 20–40 cm 3.21 *

26.27 30.46 27.12

** ** **

58.67 27.94 4.92

** ** **

273.2 97.40 56.35

** ** **

26.6

**

25.42 43.91 3.30

** ** *

4.70 5.18 23.92

** ** **

27.43 12.79 6.12

** ** **

21.43 11.77 6.88

** ** **

20.90

**

RU: Ruderal soil environment; ELY: Elymus Elymoides (Raf.) soil environment; ART: Arthrocnemum fruticosum L. soil environment; SAL: Salicornia patula Duval Jouve soil environment; AGR: Corn (Zea mays L.) cultivated soil environment; AME: Artificial meadow (Medicago sativa L.) soil environment; CL: Clay; EC: Electrical conductivity; SOC: Soil organic carbon; NT: Total nitrogen; CO2: Carbon dioxide loss by soil respiration; WSA (0.25-2): Water stability of aggregates in the 0.25–2 mm fraction; WSA (2-5.6): Water stability of aggregates in the 2–5.6 mm fraction; EEGRSP: Easily extractable glomalin related soil protein; TGRSP: Total glomalin related soil protein; C-TGRSP: Carbon of total glomalin related soil protein. *P < 0.05, **P < 0.01

(P < 0.01) and among soil environments (P < 0.01) at any depth (Table 6) indicating that only ART soil environment may be sensitive to such changes. Significant variation was found within SOC data for ELY, ART and AME soil (P < 0.01 and P < 0.05 respectively) and among soil environments (p < 0.01) at any depth (Table 5). Except RU soil, NT data varied significantly within (P < 0.01, P < 0.05) and among (P < 0.01) soil environments. Similarly, except RU soil, CO2 values showed significant variation within and among soils at 0–5 cm depth (P < 0.01). Lack of significant data variability in RU soil indicates homogeneity of this allochthonous rubble, alien to the natural dynamics of the study area. Data of WSA(0.25-2 mm) varied significantly within soils (P < 0.01, P < 0.05) but RU and among soils at any depth

3.5. Statistical variability of data - Tukey's HSD post hoc test Collection of field data may be labour intensive and costing. Thus, numbers produced during these works may have relevance if significant variability is detected within and among the investigated soil environments. Among other things it may corroborate that sampling has been performed correctly. Significant data variability of the clay fraction was only detected within ART soil (P < 0.01) and among the soil environments at the three depths (P < 0.01, P < 0.05, P < 0.05), probably indicating that fine particle redistribution may occur along periodical floodingdrying events. Yet, EC data varied significantly only within ART soil 13

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significant (P < 0.01, P < 0.05) within each soil environment but RU and among soil environments (p < 0.01) at 0–5 cm depth.

Table 7 Varimax rotated data of physical, chemical and biological variables for factor multivariate analysis at 0–5 cm depth. Loadings below 0.6 omitted. Organic reserve and structural stability SA (%) SI (%) CL (%) BD (g cm−3) pH EC (dS m−1) SOC (g kg−1) NT (g kg−1) CO2 (g kg-1day−1) C-CO2 (g kg-1day−1) q WSA(0.25-2) (%) WSA(2-5.6) (%) EE-GRSP (g kg−1) TGRSP (g kg−1) TGRSP-C (g kg−1)

−0.96 0.63 0.77 0.93 0.96 0.97

Absolute variance Cumulative variance

58.25 58.25

Porosity and carbon loss

3.6. Factor analysis

−0.93 0.86 0.93 0.94

The principal component factor analysis was performed by using all data simultaneously to check relationships among the analysed variables and soil environments. Factor analysis may provide statistical evidence of factors (namely indices) associated with analysed variables. The use of indices to estimate soil dynamics has been proposed (Paniagua et al., 1999). A two factor structure explaining 84.93% of the total variance into variables was obtained (Table 7). The first factor explained 58.25% of variance and was named “Organic reserve and structural stability” with positive loadings related to carbon dynamics and structure stability such as SOC, NT, EEGRSP, TGRSP, C-TGRSP, WSA(0.25-2) and WSA(2-5.6). Negative loadings were found on mineralization coefficient (q) and pH (Table 7). The high positive loads in this factor emphasized the importance of organic compounds in the upper investigated layer and the supremacy of chemical and biological parameters in regulating organic matter mineralization and maintaining a stable soil structure. The pH position might suggest a negative effect on organic reserve. Factor 2 explained 26.68% of total variance and showed positive loads on CL, SI, BD and EC and negative loads on CO2, C-CO2, and sand (SA). The second factor was named “Porosity and carbon loss” (Table 7), suggested by the presence of fine particle size (CL and SI) and bulk density (BD), together with electrical conductivity (EC). The inverse trend between terms of porosity and EC and potential carbon loss and sand (SA), may indicate that organic carbon will probably be more protected under lower porosity conditions and high salinity. The position of each analyzed variable is shown in the ordination plot together with the factor score percentage for each selected soil environment (Fig. 9). Factor score emphasized the role of ELY and ART soils as carbon sinks attributing high positive scores for the factor “Organic reserve and structural stability” against negative scores of -for RU, SAL, AGR and AME soils respectively (Fig. 9). The same soils had

−0.77 0.61 0.98 0.90 −0.69 −0.69

26.68 84.93

SA: Sand; SI: Silt; CL: Clay; BD: Bulk density; EC: Electrical conductivity; SOC: Soil organic carbon; NT: Total nitrogen; CO2: Carbon dioxide emission potential; C-CO2: Carbon of carbon dioxide; q: Mineralization coefficient; WSA(0.25-2): Water stable aggregates in 0.25–2 mm fraction; WSA(2-5.6): Water stable aggregates in 2–5.6 mm fraction; EEGRSP: Easily extractable glomalin related soil protein; TGRSP: Total glomalin related soil protein; C-TGRSP: Carbon of total glomalin related soil protein.

(P < 0.01, P < 0.05). By contrast, significant data variability of WSA(2-5.6 mm) was only found within ART (P < 0.01) and AGR (P < 0.05) soils and among soils (P < 0.01) along depth (Table 6). Data variability was significant (P < 0.01) for both EEGRSP and TGRSP within ELY and ART soil environments and among soils (P < 0.01) along any depth (Table 6). Yet C-TGRSP data variation was

1.2 Factor score (%)

1.0

Porosity and carbon loss (26.68 %)

0.8

Organic reserve and structural stability RU ELY ART SAL AGR PAS -35+39 +61 -30 -27 -8

CL BD

SL EC

0.6 0.4 0.2 0.0

Fig. 9. Ordination plot from factor multivariate analysis where indices of soil functionality as organic reserve and structural stability (58.25%) of explained variance) and porosity and carbon loss (26.68% of explained variance) are reported. Also, factor score delineated ART and ELY soil as the major carbon sinks among the studied soils.

NT

Porosity and carbon loss RU ELY ART SAL AGR PAS -25+41 +60 -14 -35 -27

TGRSP WSA(0.25-2) C-TGRSP WSA(2-5.6) SOC

q

EEGRSP

-0.2 pH

-0.4 -0.6

C-CO2 CO2

-0.8

SA

-1.0 -1.2 -1.2

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

Organic reserve and structural stability (58.25 %) 14

0.8

1.0

1.2

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negative scores for “Porosity and carbon loss” factor against positive score for ELY and ART soils respectively. Scores identify ELY and ART soils as environments with less carbon loss and associated to EC and terms of porosity. Mavi et al. (2011) reported that fine textures may maintain salinity conditions in salt affected soils due to reduced matric potential. All other soils resulted more or less involved in mechanisms of carbon destabilization.

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4. Conclusions Experiments conducted at La Pletera salt-marsh demonstrated that changes in land use such as conversion into agriculture or urban structure for tourism produced alteration of physical, biological and chemical properties of the soils under study. Among the six selected soil environments, those affected by land use change such as RU, AGR and AME showed worse soil properties at the three investigated depths (0–5 cm, 5–20 cm and 20–40 cm). Poor soil properties were also found in the salt-marsh soil (SAL) colonized by Salicornia patula Duval Jouve. Therefore, soil RU, AGR, AME and SAL should be properly managed in order to secure appropriate edaphic conditions. By contrast, ELY and ART salt-marsh soils showed the best soil properties and a major ability for carbon sequestration. Glomalin, considered an important soil aggregating agent and a source of recalcitrant carbon pool steadily increased as follows: RU > SAL > AGR > AME > ELY > ART assigning to ART and ELY soils higher amount of stable organic compounds and a primary function in organic carbon storage. Potential carbon loss was very low or low in ART and ELY soils and progressively increased in AME, RU, AGR and SAL, warning on the impoverishment of organic carbon content in more sensitive soils. Factor analysis gave statistical evidence for ELY and ART soils as carbon sinks, suggesting that prairie and salt-marshes under undisturbed conditions may constitute valuable areas for ecosystem service. Declaration of Competing Interest Authors declare that they have no known competing financial interests of personal relationships that could have appeared to influence the reported in this paper. Acknowledgements This work has been developed under the Project LIFE 13 NAT/ES/ 001001. The Erasmus Training is also acknowledged for permitting mobility and participation in this research activity the student from the Royal University of Agriculture, Cambodia. References Adame, M.F., Wright, S.F., Grinham, A., Lobb, K., Reymond, C.E., Lovelock, C.E., 2012. Terrestrial-marine connectivity: Patterns of terrestrial soil carbon deposition in coastal sediments determined by analysis of glomalin related soil protein. Limnol. Oceanogr. 57, 1492–1502. Badosa, A., Boix, D., Brucet, S., López-Flores, R., Quintana, X.D., 2006. Nutrients and zooplankton composition and dynamics in relation to the hydrological pattern in a confined Mediterranean salt marsh (NE Iberian Peninsula). Estuar. Coast. Shelf Sci. 66, 513–522. Bai, Junghang, Zhang, Guangliang, Zhao, Qingping, Quiongpiong, Lu., Jia, Jia, Cui, Baoshan, Liu, Xinhui, 2016. Depth-distribution patterns and control of soil organic carbon in coastal salt marshes with different plant covers. Sci. Rep.-U.K. 6, 1–12. Barea, J.M., Pozo, M.J., Azcón, R., Azcón-Aguilar, C., 2005. Microbial co-operation in the rizhosphere. J. Experimental Botany 56, 1761–1768. Bradford, M.M., 1976. A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal. Biochem. 72, 248–254. Bremner, J.M., Mulvaney, C.S., 1986. Nitrogen total. In: Page, A.L., Miller, R.H., Keeney, D.R. (Eds.), Methods of Soil Analysis. American Society of Agronomy Inc., Soil Science Society of America Publisher, Madison, pp. 595–623. Burden, A., Garbutt, R.A., 2013. Carbon sequestration and biogeochemical cycling in a saltmarsh subject to coastal managed realignement. Estuar. Coast. Shelf S. 120, 12–20. Caravaca, F., Alguacil, M.M., Torres, P., Roldán, A., 2005. Plant type mediates

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