Response of soil properties and microbial indicators to land use change in an acid soil under Mediterranean conditions

Catena 189 (2020) 104486

Contents lists available at ScienceDirect

Catena journal homepage: www.elsevier.com/locate/catena

Response of soil properties and microbial indicators to land use change in an acid soil under Mediterranean conditions Eduardo Vázqueza,

⁎,1

, Marta Benitoa, Rafael Espejoa, Nikola Teutscherovaa,b,

T

⁎

a

Departamento de Producción Agraria, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Avda. Puerta de Hierro, E-28040 Madrid, Spain b Department of Crop Sciences and Agroforestry, Faculty of Tropical AgriSciences, Czech University of Life Sciences Prague, Kamýcka 129, Prague 6-Suchdol 16500, Czech Republic

A R T I C LE I N FO

A B S T R A C T

Keywords: Raña soil No-tillage Land abandonment Cork oak Soil enzymes Microbial biomass Land use change

Land use change (LUC) can alter the soil quality and lead to soil degradation or soil conservation depending on the management practices. In the Mediterranean region, the impact of LUC on soil quality has been well described on neutral or alkaline soils, which are the most common in the area. However, some areas in the west of the Iberian Peninsula are covered by Raña surfaces, a continental detritic formation associated with quartzitic ranges and characterized by very acid and weathered soil. Seven following land uses were selected for this study: cork oak climax vegetation (Cork Oak), pine afforestation (Pine), natural revegetated shrubland (Shrub) and grassland (Grassland) after land abandonment, tilled olive grove (Olive), tilled annual cropland for animal forage (Tillage) and the same annual cropland managed by no-tillage (No-Tillage). The two tree-based uses, Pine and Cork oak, accumulated the highest contents of carbon (C) and nitrogen (N) fractions. However, the further acidification and the C accumulation in labile forms of Pine could hinder the feasibility of Pine plantations to restore acid and degraded soils. Instead, the natural revegetation succession after land abandonment (first Grassland and then Shrub) were found as a suitable alternative able to increase the C content and restore the microbial activity in comparison with Tillage and Olive, the two land uses which showed the lowest C and N content and reduced microbial activity. Furthermore, the improved aggregate stability in Shrub, probably caused by root exudates of dominant plant species, could play a key role in soil restoration. Microbial biomass C and N, C decomposability and enzymatic activities were the most sensible microbial indicators to discriminate among the studied land uses. A clear pattern of lower microbial biomass and enzymatic activity was found with increasing human intervention and soil disturbance. In this respect, soil managed by no-tillage contained higher soil C and N contents when compared to Tillage and the microbial indicators were comparable with those obtained under Cork Oak. Our results demonstrate that soil tillage reduction is an essential step to mitigate soil degradation in Raña soils and highlighted the suitability of No-tillage as an alternative to traditional tillage, which can increase crop productivity while building soil organic matter content. In addition, the natural soil revegetation, including natural grasslands, shrublands and climax cork oak vegetation are more preferable for degraded soil improvement when compared to pine plantations.

1. Introduction The land use change (LUC) and the implementation of unsuitable agronomic practices is one of the main drives of soil degradation and

the loss of soil organic carbon (SOC) and thereby, an increase of soil CO2 emissions (Tan and Lal, 2005). The LUC during the last centuries in the European Mediterranean region, where natural forest or shrublands were converted to vineyards, olive groves or to agricultural lands, has

Abbreviations: LUC, land uses change; SOC, soil organic carbon; TN, total nitrogen; POM, particulate organic matter; POxC, permanganate oxidizable carbon; BD, bulk density; MBC, microbial biomass C; MBN, microbial biomass N; EOC, extractable organic carbon; EN, extractable N; BR, Basal respiration; CUM, the cumulative C-CO2 emissions; SIR, substrate induced respiration; Gluc, β-glucosidase enzymatic activity; NAG, β-glucosaminidase activity; BAA, N-benzoyl-L-argininamide protease activity; RDA, redundancy analysis ⁎ Corresponding authors at: Departamento de Producción Agraria, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Avda. Puerta de Hierro, E-28040 Madrid, Spain (N. Teutscherova). E-mail addresses: [email protected] (E. Vázquez), [email protected] (N. Teutscherova). 1 Present Address: Department of Soil Biogeochemistry and Soil Ecology, University of Bayreuth, Dr. Hans-Frisch-Straße 1-3, 95448, Bayreuth, Germany. https://doi.org/10.1016/j.catena.2020.104486 Received 9 May 2019; Received in revised form 26 August 2019; Accepted 21 January 2020 0341-8162/ © 2020 Elsevier B.V. All rights reserved.

Catena 189 (2020) 104486

E. Vázquez, et al.

generally considered to enhance soil quality after land abandonment, has been observed to generate N depletion in the acid soils of Western Spain (Rolo et al., 2012). Furthermore, studies evaluating the LUC in other Acrisols, mainly distributed in humid and subhumid tropical areas, are not comparable with Raña’s Acrisols, due to the peculiarity of the Mediterranean climate. Therefore, this study aims to fill the gap in our understanding of the effects of the LUC on these particular Mediterranean acid soils, which cover a considerable area in the west of the Iberian Peninsula. The objectives of the present study were: (i) to assess the differences in the chemical, physical and biological properties caused by the common land uses in the acid soils of SW Spain; and (ii) to evaluate the utility of microbial parameters as indicators of soil quality, which will contribute to the optimization of land management strategies in the study area in order to reduce soil degradation.

caused a dramatic reduction of SOC stocks (García-Ruiz, 2010; MuñozRojas et al., 2015) and significantly contributed to rapid degradation of soil quality (García-Ruiz, 2010; Mariscal et al., 2007; Parras-Alcántara et al., 2013). Analogically, SOC and soil quality can be recovered by natural revegetation after agricultural land abandonment (Romero-Díaz et al., 2017). Along with changing soil properties driven by the LUC, soil microbial activity and abundance evolve which can have strong implications for nutrient cycling (Eleftheriadis and Turrión, 2014; Garcia-Orenes et al., 2013; Zornoza et al., 2009). Therefore, several attempts have been made to detect the suitable biological indicators of soil quality (Francaviglia et al., 2017; Lagomarsino et al., 2011; Marzaioli et al., 2010) due to the sensitivity of microbial communities to LUC in relatively short period of time when compared to soil physical and chemical properties. The rañas are flat detritic formations from middle-Pliocene formed near the quartzitic ranges in the west of the Iberian Peninsula which cover more than 106 ha (Espejo, 1987; Espejo Serrano, 1985; Peregrina et al., 2008). Rañas are characterized by highly weathered soils with low pH and the exchange complex saturated by Al3+, are classified as Ultisol or Acrisol (according to USDA or FAO taxonomy, respectively) (Espejo, 1987; Espejo Serrano, 1985). The soils of Cañamero’s raña (Cáceres, SW Spain) have been rapidly degrading since the beginning of the XX century when the natural vegetation was substituted by rainfed cereal crops or olive groves (Peregrina et al., 2008). The initial low quality of these soils further exacerbated by excessive tillage caused a rapid reduction of the SOC content, increase of soil acidity and degradation of soil physical properties (Mariscal-Sancho et al., 2009; Mariscal et al., 2007; Peregrina et al., 2008), which consecutively led to a dramatic reduction of productivity. The traditional rainfed agriculture was then substituted by unmanaged grasslands for hunting and grazing purposes, pine plantations for timber, more intensively managed olive orchards or reforestation with cork oak (Quercus suber L.), the climax vegetation. Furthermore, the encroachment of basel-leaved rock rose (Halimium ocymoides (Lam.) Willk.) and heath (Erica umbellata L.) within grasslands forms the Halimio-Ericetum umbellatae associations, which became emblematic for raña formations. On the continuously decreasing agricultural areas, no-tillage agriculture has been proposed and successfully tested as an alternative to traditional tillage, with a potential to enhance crop yields and restore exhausted SOC stocks (Hontoria et al., 2018). The LUC and its impact on soil properties and biogeochemical processes have been evaluated in Southern Spain (Parras-Alcántara et al., 2013), Southeastern Spain (Almagro et al., 2013; Romero-Díaz et al., 2017; Zornoza et al., 2009), Northeastern Spain (Dunjó et al., 2003; Gispert et al., 2013), Sardinia (Francaviglia et al., 2017, 2014; Lagomarsino et al., 2011), Central and Southern Italy (Marzaioli et al., 2010; Moscatelli et al., 2007; Papini et al., 2011), in subhumid Mediterranean area in Slovenia (van Hall et al., 2017), in Northern Greece (Eleftheriadis et al., 2018; Eleftheriadis and Turrión, 2014) and in Turkey (Celik, 2005). However, with the exception of the slightly acidic Sardinian soils, all the studies focused on neutral or alkaline soils with limestone or marls as parent materials, which may considerably influence the LUC impact on soil properties. The low soil pH in the study area (pH(H2O) ≤ 5), together with low buffer capacity and high Altoxicity, play a key role in the plant production and SOC accumulation (Gómez-Paccard et al., 2013; Hontoria et al., 2018). In addition, the absence of calcium carbonate, very common in other Mediterranean soils, reduces the Ca-mediated soil aggregation leading to a lower SOC stabilization and higher risk of C depletion (Romanyà and Rovira, 2011). This suggests greater differences in the SOC after LUC in acidic soils than in alkaline ones (Romanyà and Rovira, 2011). For instance, the pine afforestation in Mediterranean region leads to soil acidification (Iovieno et al., 2010) which in our case could exacerbate the already acid soil pH and considerably influence soil microbial communities and affect the C and N cycling (Díaz-Pinés et al., 2014; Iovieno et al., 2010). Moreover, the shrub encroachment,

2. Materials and methods 2.1. Study site The study was located near Cañamero (Cáceres, SW Spain) within the Raña flat surface (slope gradient in average is less than 0.5%) (Espejo, 1987). The rañas are continental detritic formations located in the western of the Iberian Peninsula associated with quartzitic ranges and were formed in the middle Pliocene (Espejo, 1987; Espejo Serrano, 1985). The soils were developed under subtropical pre-Quaternary climate (i.e. hot and wet summers) and retained their typical features until present: highly weathered soils with kaolinite as the main clay component, very low pH and the exchange complex dominated by Al3+ (Espejo, 1987). The soils are classified as Panthoskeletic Endoplinthic Acrisol (IUSS Working Group WRB, 2015), equivalent to Plinthic Palexerults (Soil Taxonomy, 2014). Until the beginning of the XX century, the soils were maintained with the natural vegetation because of their low fertility, but the scarcity of food after the Spanish civil war (1936–39) caused the clearance of the natural vegetation and initiation of agricultural activity (Espejo, 1987). The previous climax vegetation was formed by scattered cork oak (Quercus suber L.) trees surrounded by strawberry trees (Arbutus unedo L.) and false olive (Phillyrea angustifolia L.) shrubs of the Phillyreo-Arbutetum tipicum association (Rivas-Goday, 1964). After vegetation clearance, the continuous tillage and use of fertilizers led to dramatic decrease of the SOC, increase of the Al3+ toxicity and degradation of soil physical properties, causing the cropland abandonment (Mariscal et al., 2007; Peregrina et al., 2008). The recent climate in the study area is temperate with dry and hot summer (Csa, Hot-summer Mediterranean climate). During the period between 2007 and 2019, the mean annual temperature was 15.4 °C, the rainfall 952 mm and the annual evapotranspiration (Penman-Monteith) was 1359 mm (Data from the meteorological station of Guadalupe, 12 km away). The sampling points were located within 39°21′and 39°19′ N and 5°21′and 5°19′W, with an elevation between 600 and 660 m a.s.L (Fig. 1). We selected six most common land uses in the region and, in addition, we included no-tillage and traditional tillage experimental plots described in (Hontoria et al., 2018). No-tillage agricultural plots were included because of the observed positive impact on crop yields and simultaneous potential to restore the exhausted SOC stocks (Hontoria et al., 2018). Although the land uses are common in the region (with the exception of No-tillage) we have selected a single monitoring area, representative of each land use, in which the management and the time since land use establishment are homogenous (Fig. 1). Single monitoring area of large size (instead of several spatially separated repetitions) has been previously used in similar studies (Francaviglia et al., 2017, 2014; Gispert et al., 2013; Lagomarsino et al., 2011; Moghimian et al., 2017; Qi et al., 2018; Soleimani et al., 2019). Furthermore, by selecting a single monitoring area of large size we tried to reduce the impact of slight differences within replications in the agronomic/silvocultural management or time since establishment which could hinder the interpretation of results. 2

Catena 189 (2020) 104486

E. Vázquez, et al.

Fig 1. Location of the representative monitoring areas selected for each land use and experimental plot where Tillage and No-tillage were assayed in the study area (Raña flat surface, Cáceres, Spain).

Olive (Olea europea L.): Increasing areas are covered with olive orchards. The selected rainfed olive grove (7.5 ha) is 65 years old and it is heavily tilled several times per year for weed control. The olives were planted at a spacing of 10 × 10 m and the productive is very low (5–12 kg of olives per tree). In the last five years the olive orchard was not fertilized and the pruned biomass is not applied to the soil. Tillage: Traditionally, the area was used for extensive rainfed winter cereal (oat or ray) to produce fodder for sheep. To represent this use, we sampled a 10-years old experimental plot where Tillage and Notillage were compared (Hontoria et al., 2018). The Tillage treatment is tilled once per year prior sowing of a mix of Avena sativa L., Triticosecale Wit., and Vicia sativa L. Inorganic fertilizers are applied once a year after sowing (36 kg N ha−1, 72 kg P ha−1, 72 kg k ha−1). No-tillage: The No-tillage have been proposed recently as an alternative to traditional tillage in order to recover the previous SOC contents and to improve soil physical properties (Hontoria et al., 2018; León et al., 2017). The samples were collected from the same experimental plot as the Tillage samples (Hontoria et al., 2018) after ten years of no-tillage management. The weed control is achieved by the use of herbicides and the fertilization rate is the same than in the Tillage treatment.

The main characteristics of the monitoring areas selected as representative for each land use are: Cork oak (Quercus suber L.): Cork oak forest is considered the climax vegetation in the area (Rivas Goday, 1964), which was, however, extensively removed during the agricultural development after 1940s. In the last decades, new plantations have been established for cork production. To assess the potential development of soil under cork oak, the samples were collected from the small patches of relict cork oaks which were more than 100 years old with diameter at breast height of approximately 40–65 cm. Although relict cork oaks patches are present in several locations within Raña formation, the four patches selected for the sampling were located within a cork oak plantation for cork production (17 ha of total surface planted at a spacing of 5 × 5 m) to reduce the edge effect. Pine (Pinus pinea L.): Pine plantations for timber were established on large areas to substitute the low profitable cereals during the 1970s and 1980s. A plantation of approximately of 12 ha, established 40 years ago and with low intensity management was selected as the most representative of the studied land use. For the establishment, the trees were planted in lines after soil subsoiling. The present plantation density is 800 trees ha−1 with a diameter at breast height of 30 cm. No fertilizer are applied and the understory vegetations is periodically removed. Shrub (Halimio-Ericetum umbellatae): The shrublands of HalimioEricetum umbellatae association are the first shrub formations which colonize the abandoned grasslands (RivasGoday, 1964). The most important plants are Erica umbellate L. (Ericaceae) and Halimium ocymoides (Lam.) Wilk (Cistaceae). A marginal agricultural lands (5.5 ha) which were abandoned few decades ago and which are now a shrubland were selected as the transition between agricultural use and climax vegetation (Rivas Goday 1964). Grassland: Extensive areas of former cropland tilled during decades for winter cereals, abandoned in the last 10–15 years and now only occasionally tilled in order to avoid shrub encroachment, are now covered by natural grasslands. For the present study, an area of 7 ha which was abandoned more than ten years ago was selected.

2.2. Soil sampling design Soil sampling was performed in October 2015 before the soil preparation for the next sowing in Tillage and No-tillage experimental plots. Therefore, the last tillage event in Tillage plots and fertilization was done one year before sampling. Soil samples from all land uses were collected from the top soil layer (10 cm) after the removal of litter (if present). In the case of the Tillage and No-tillage treatments, the experimental plot had four field repetitions (4 m × 16 m) and we collected a composite sample from eight randomly distributed spots at each field repetition. In the case of Cork Oak, four relict patches were selected within the above mentioned cork oak plantation. At each patch, eight subsamples were collected bellow the tree canopy to a minimum distance from the trunk of 2 m. In the other four land uses, 3

Catena 189 (2020) 104486

E. Vázquez, et al.

proposed by Parham and Deng (2000) using p-nitrophenyl-N-acetyl-βD-glucosaminide as substrate. In order to evaluate the microbial respiration activity, the cumulative C-CO2 emissions (CUM) were determined by aerobic incubation (47 days) of 20 g of fresh soil. Soil aliquots at 60% field capacity were placed in 0.5 L plastic jars for aerobic incubation (25 °C) using an alkaline NaOH trap followed by titration with HCl after carbonates precipitation with BaCl2 (Iannotti et al., 1993). The soil moisture was periodically adjusted adding distilled water. Soil basal respiration (BR) was calculated as the CO2 emission rate during the initial three days of incubation. Substrate-induced respiration (SIR) was determined using a similar setup by incubation of 20 g of fresh soil adjusted to 60% field capacity with talco:glucose mixture (3:1) for four hours at 25 °C (Anderson and Domsch, 1978). The SOC decomposability was calculated after normalize the CUM emissions by the SOC content of each sample (Díaz-Pinés et al., 2014).

four representative pseudoplots of 10 × 10 m were selected and a composite sample from eight randomly distributed spots was collected from each pseudoplot. In the case of Shurb, the four pseudoplots were at least 25 m far apart and the subsamples were collected at least 30 cm from the shrubs within each pseudoplot. In Pine and Olive, the pseudoplots were at least 100 m far apart and the samples were collected at least two meters from the tree trunks. Finally, the grassland pseudoplots were 100 m far apart and the eight subsamples were collected randomly within each pseudoplot. Therefore, four composited samples of each land use were collected. The soil samples were sieved (< 2 mm) and the amount of coarse elements weighted. An aliquot of the sample was airdried for determination of soil chemical properties. Other aliquot was refrigerated (4 °C) until the analysis of soil biological properties. Additionally, an intact soil core was collected at each sampling point to determine the bulk density. The samples had all sandy loam texture. 2.3. Analytical methods

2.4. Statistical analysis

Soil pH(H2O) and pH(KCl) were determined in distilled H2O and KCl (1 M), respectively (1:2.5 soil/extract ratio). The SOC was quantified by dichromate oxidation method (Walkley and Black, 1934), the total N (TN) by Kjeldahl digestion (Bremner and Mulvaney, 1982) and the C to N ratio (CN) was calculated. The Permanganate oxidizable C (POxC) was determined colorimetrically (UV-1203, Shimadzu, Kyoto, Japan) following the method of Weil et al. (2003). The particulate organic matter (POM) was isolated according to Cambardella and Elliott (1992). Briefly, we dispersed 10 g of soil in 30 mL of 5 g l−1 sodium hexametaphosphate by shaking overnight. The dispersed samples were then passed through a 53 µm-mesh sieve and the retained fraction was collected and dried at 60 °C. Finally, the POM content was determined by loss on ignition (450 °C, 16 h). The NH4+-N was extracted with 1 M KCl (1:10) and was determined colorimetrically using the sodium salicylate method (Forster 1995). The intact soil cores were used to determine the bulk density of fine earth (BD) and the gravimetric and volumetric rock fragments (considering a density of 2.65 g cm−3 for quartzite). The BD was calculated assuming the volumen occupied by fine earth = total core volumen − rock fragments volumen. The SOC stocks (Mg ha−1) were calculated based of SOC concentration, BD of fine earth, the content of rock fragments and the depth of the soil layer (10 cm). The content of water-stable aggregates (WSA) were determined by wet-sieving of air-dried 1–2 mm aggregates through a 250 mm sieve (Kemper and Rosenau, 1986) and calculated as the weight of stable aggregates divided by the sum of stable and unstable aggregates. Finally, the aggregates were expressed in grams of WSA per kg of soil. Microbial biomass C and N (MBC and MBN, respectively) were quantified using the fumigation-extraction method (Vance et al., 1987). Briefly, 8 g of soil were fumigated during 24 h with ethanol-free chloroform and extracted by 0.5 M K2SO4 (1:4 soil:extractant ratio). The concentration of organic C in the extract was determined colorimetrically by measuring Cr3+ produced by reduction of Cr6+ (578 nm) after microwave digestion (Speedwave four, Berghof, Eningen, Germany) at 135 °C for 30 min. The concentration of N in the extracts was determined as N-NO3- (Robarge et al., 2008) after alkaline persulfate oxidation (Cabrera and Beare, 2010) by colorimetry. Finally, MBC and MBN were calculated as the difference between the C and N content in fumigated and non-fumigated samples, divided by 0.38 (Joergensen, 1996) and 0.54 (Brookes et al., 1985), respectively. In addition, the contents of C and N obtained in the no-fumigated samples were considered as extractable organic C (EOC) and extractable N (EN). The β-glucosidase enzymatic activity (Gluc) was assessed using βglucoso-saligenin (salicin) as a substrate following the method of Hoffmann and Dedeken (1965) modified by Strobl and Traunmueller (1996). The activity of N-benzoyl-L-argininamide protease (BAA) was performed according to Nannipieri et al. (1980). Finally, The β-glucosaminidase activity (NAG) was determined following the method

Data were checked for normality of distribution (Shapiro-Wilk test) and homogeneity of variance (Levene’s test) prior to statistical analyses and log-transformed when necessary. The differences among the land use systems were analyzed by analysis of variance (ANOVA) and posthoc Tukey’s test (p < 0.05) using SPSS 22 software (IBM SPSS, Inc., Chicago, USA). In addition, we performed a redundancy analysis (RDA) using the Vegan package of R (Oksanen et al., 2011) aiming to elucidate the relationships between soil chemical and physical properties and the measured microbial indicators. We considered the microbial indicators as dependent variable and the soil chemical and physical parameters as explanatory variables. The most significative explanatory variables were selected using the ordistep function of the Vegan package. In addition, the sampling points of each land use were projected in the RDA biplot using the ordiellipse (p < 0.05) function of the Vegan package. 3. Results 3.1. Soil physical and chemical properties The highest contents of rock fragments in the top soil (0–10 cm) were found in Olive and Pine, while the lowest was detected in Cork Oak and Shrub (Table 1). The BD of fine earth of Olive and No-Tillage was the highest while the lowest BD was observed in Cork Oak and Pine (Table 1). The content of WSA (weight kg−1 soil) was the highest in Shrub and the lowest under Olive (Fig. 2). The pH(H2O) ranged from 4.86 to 4.06 with the lowest values detected in Pine and the highest in Grassland and No-tillage (Table 1). Similarly, the lowest values of pH(KCl) were found in Pine and Cork Oak (3.02 and 3.51, respectively). Table 1 Selected soil properties in the 0–10 cm soil layer.

Cork oak Pine Shrub Grassland Olive Tillage No-tillage

Rock fragments %

BD of fine earth kg m−3

pH (H2O)

41 73 36 51 75 60 58

673 (40) cd 509 (35) d 759 (35) bc 804 (66) bc 1022 (14) a 817 (36) bc 885 (28) ab

4.39 4.06 4.50 4.86 4.45 4.64 4.82

(6) (8) (3) (5) (7) (4) (4)

b a b ab a ab ab

(0.11) (0.05) (0.06) (0.08) (0.08) (0.04) (0.02)

pH (KCl)

b c b a b ab a

3.51 3.02 3.59 3.91 3.92 3.68 3.89

(0.16) (0.15) (0.08) (0.01) (0.05) (0.08) (0.06)

cd d bc a a abc ab

Standard errors (n = 4) are reported in brackets. The differences among the land use systems were analyzed by analysis of variance (ANOVA) and post-hoc Tukey’s test (p < 0.05). Different letters indicate differences at p < 0.05. BD, bulk density. 4

Catena 189 (2020) 104486

E. Vázquez, et al.

200

weight of WSA kg-1 soil

significantly higher than the CUM detected in the other five land uses, while emissions in Olive were the lowest (128 ± 8 mg C-CO2 kg−1) (Table 4. Fig. S1). The SOC decomposability was higher in Pine, Cork Oak and Tillage while the lowest were Olive and Grassland (Table 4)

a

180 160 140 120 100

20

bc

bc

60 40

3.3. Correlation among variables

b

80

The full model RDA performed with soil physical and chemical variables as explanatory variables of the soil microbial indicators (Fig. 3). It accounted for 83.35% of the variance, with the two first RDA axis explaining 72.84% and 8.61%, respectively. The explanatory variables retained (p < 0.1) were SOC, TN, C:N, NH4+-N and pH (H2O). The pH(H2O) was loaded in the positive side of the RDA1 while all the other explanatory variables were loaded in the negative side, showing their negative relationship. All the microbial indicators were loaded on the negative side of the RDA1 showing a high relationship with the most of the chemical variables. The three enzymatic activities, MBN and C decomposability were grouped in the positive side of RDA2 and were related with the NH4+-N. However, the CUM and BR were grouped on the negative side of RDA2 and seemed to be associated with the CN and SOC. The sampling points were distributed in a clear pattern along the RDA biplot showing the suitability of the selected soil parameters to identify the differences between the seven land uses. Pine, Cork Oak and No-tillage plotted in the negative side of the RDA1 (as all the microbial indicators) while Tillage, Grassland, Shrub and Olive along the positive side of RDA1. The Cork Oak and Olive were plotted orthogonally which showed them as the most contrasting land uses. Additionally, the ellipses of No-tillage and Tillage clustered separately showing the differences between both managements.

c d e

0 Cork oak

Pine

Shrub

Grassland

Olive

Tillage

No-tillage

Fig. 2. The content of water stable aggregates (WSA). Bars indicate standard error of the mean (n = 4). Different letters indicate differences at p < 0.05.

Soil under Pine contained the highest amount of SOC content (154 ± 21.8 g kg−1) followed by Cork Oak (72.5 ± 10.3 g kg−1), Shurb (43.0 ± 2.1 g kg−1) and No-tillage (36.1 ± 1.7 g kg−1) (Table 2) while the lowest SOC contents were found in Tillage (25.7 ± 1.2 g kg−1) and Olive (22.8 ± 1.6 g kg−1). When the SOC content was expressed as SOC stock, the greatest C stock in the top soil layer (0–10 cm) was found in Pine and Cork Oak, while the lowest were found in Olive, Tillage and Grassland (Table 2). The top layer of Pine accumulated 54.8 ± 6.4 Mg C ha−1 and the Cork Oak 39.9 ± 3.5 Mg C ha−1 while the SOC stock in Tillage and Olive were virtually identical (16.1 ± 1.3 and 16.3 ± 1.0 Mg C ha−1). Pine and Cork Oak also contained the highest amount of TN, while the lowest content was detected in Grassland, Shrub, Olive and Tillage (Table 2). The C:N of Pine was significantly higher than in the rest of the land uses. The greatest POxC was found in Pine and Cork Oak while the lowest was in Olive and Tillage (Table 2). Similarly, Pine and Cork oak contained the highest amount of POM (Table 2). The EOC in Olive was significantly lower than in Pine and Cork Oak (Table 3). The EN of Cork Oak, Tillage and No-tillage was higher than in Shrub, Grassland and Olive (Table 3). The NH4+-N of Olive and Shrub were lower than in Cork Oak, Tillage and No-tillage (Table 3).

4. Discussion 4.1. Impact of different land uses in soil properties The accumulation of SOC is controlled by the balance between the C inputs via litter or root deposition and the output through C decomposition by soil heterotrophs. Therefore, the two tree-based land uses, Pine and Cork Oak, presented the highest content of all the studied C and N soil fractions because of the larger organic inputs. On the other hand, the lowest C and N contents were observed under Tillage and Olive, which could be explained by high soil disturbance by tillage, thus higher organic matter decomposition, and scarce C inputs. Our results confirm previous studies from the Mediterranean region (Francaviglia et al., 2017; Lagomarsino et al., 2011) and highlight the high impact of vegetation, land use and soil disturbance on the accumulation of soil C and N. The high SOC accumulation under Pine after few decades of afforestation revealed a quick SOC recovery capacity of the Mediterranean acid soils after LUC, which is faster than the SOC increase generally reported for alkaline soils (Romanyà and Rovira, 2011).

3.2. Soil biological parameters The MBC of Tillage and Olive were significantly lower than in Pine and Cork Oak (Table 3). Similarly, the MBN of Pine and Cork Oak were significantly higher than in Tillage, Olive, Grassland and Shrub (Table 3). The SIR of Shrub, Olive and Tillage was significantly lower than in Pine, Cork Oak and No-Tillage (Table 4). The highest BR was measured in Pine and Cork Oak and the lowest in Olive. The highest activities of the three enzymes were measured in Cork Oak, No-Tillage and Pine while the lowest was found in Olive. The CUM after 47 days of incubation in Pine (2,584 ± 313 mg CCO2 kg−1) and in Cork Oak (1,279 ± 281 mg C-CO2 kg−1) were Table 2 Soil carbon and nitrogen contents and stocks in the 0–10 cm soil layer.

Cork oak Pine Shrub Grassland Olive Tillage No-tillage

SOC g kg−1

TN g kg−1

72.5 (10.3) b 154 (21.8) a 43.0 (2.1) c 33.0 (1.3) cd 22.8 (1.6) e 25.7 (1.2) de 36.1 (1.7) c

3.50 3.75 1.98 1.51 1.08 1.58 2.02

(0.51) (0.52) (0.25) (0.20) (0.15) (0.13) (0.27)

C:N

ab a bc c c c bc

21.1 43.5 22.7 23.1 21.8 16.4 18.4

POxC mg kg−1 (1.8) (9.6) (2.9) (3.3) (1.9) (0.8) (1.4)

b a b b b b b

3.34 4.32 1.08 0.86 0.59 0.80 1.09

(0.74) (1.68) (0.04) (0.05) (0.06) (0.07) (0.11)

POM % a a b b c bc b

7.76 17.3 2.10 1.35 0.89 1.49 2.33

SOC stock Mg C ha−1 (1.13) (2.71) (0.34) (0.11) (0.07) (0.12) (0.26)

a a bc cb cb bc b

39.9 54.8 28.0 21.3 16.3 16.1 24.6

(3.5) (6.4) (1.3) (2.1) (1.0) (1.3) (1.0)

ab a bc cd d d c

Standard errors (n = 4) are reported in brackets. The differences among the land use systems were analyzed by analysis of variance (ANOVA) and post-hoc Tukey’s test (p < 0.05). Different letters indicate differences at p < 0.05. SOC, soil organic carbon; TN, total nitrogen; POxC, permanganate oxidizable carbon; POM, particulate organic matter. 5

Catena 189 (2020) 104486

E. Vázquez, et al.

Table 3 The content of microbial biomass and extractable carbon and nitrogen pools in the 0–10 cm soil layer. MBC

NH4+-N

MBN

EOC

EN

98.1 (18.2) a 107.8 (14.2) a 48.5 (4.0) bc 50.6 (4.9) bc 14.1 (3.2) c 39.8 (8.9) bc 72.5 (7.4) ab

158 (22.1) ab 182 (22.5) a 114 (18.8) abc 102 (9.3) bc 80 (3.8) c 104 (13.1) bc 130 (6.6) abc

68.2 43.6 20.1 35.8 29.6 67.1 81.9

mg kg−1 Cork oak Pine Shrub Grassland Olive Tillage No-tillage

837 (1 2 4) ab 1149 (90) a 553 (65) bc 466 (24) c 103 (10) d 329 (35) cd 563 (62) bc

(3.5) (2.6) (3.9) (3.0) (2.1) (7.0) (7.3)

a b c bc bc a a

12.4 9.05 0.97 4.65 1.51 13.0 13.6

(0.90) (1.03) (0.58) (1.07) (0.34) (2.08) (1.52)

a ab c bc c a a

Standard errors (n = 4) are reported in brackets. The differences among the land use systems were analyzed by analysis of variance (ANOVA) and post-hoc Tukey’s test (p < 0.05). Different letters indicate differences at p < 0.05. MBC, microbial biomass C; MBN, microbial biomass N; EOC, extractable organic carbon, EN, extractable N.

activity (León et al., 2017). The environmental implication of slower organic matter stabilization and soil acidification could increase the SOC stock under Pine plantations, which, however, does not necessarily need to be stable in the long term because of the accumulation in form of POM (partly decomposed organic matter) and lower mineral-association, which is considered more stable in the long run (Rovira et al., 2010) and easily lost after LUC (Eleftheriadis et al., 2018). However, in order to assess the capacity of each land use system to store SOC, deeper soil layers need to be included as well as in situ CO2 emissions measurements. Further acidification of already acid soil could preclude a future use of such areas for agricultural or pastoral purposes (Mariscal-Sancho et al., 2009). The land abandonment and the natural revegetation by grasslands and the subsequent shrub encroachment (the typical vegetation recovery in the Mediterranean ecosystems) promoted an increase of the SOC content and the top soil C stocks respect to Olive or Tillage, which confirms findings of other authors (Gispert et al., 2013; Romero-Díaz et al., 2017). All the measured C pools were slightly higher in Shrub than in Grassland which showed the trend of C accumulation after land abandonment and natural vegetation recovery during secondary succession (Dunjó et al., 2003; Romero-Díaz et al., 2017; van Hall et al., 2017). The absence of soil disturbance by tillage and the higher C inputs via root exudation or plant biomass production has caused an increase in SOC (Francaviglia et al., 2014; Lagomarsino et al., 2011; Moscatelli et al., 2007; Parras-Alcántara et al., 2013) and promoted an enhancement of the soil aggregation respect to Olive, which could reduce the C availability for mineralization. Higher soil aggregation

The higher availability of C substrate in Cork oak and Pine promoted the increase of soil microbial biomass, enzymatic activities and C mineralization (represented by the BR and CUM) when compared to the lower SOC systems. However, clearly separated clusters in the RDA revealed several differences between the soils under Cork oak and Pine, which have important implications for long-term C storage. Firstly, we observed that the higher SOC content in Pine was caused by the larger POM pool while POxC content was comparable in both land use systems. A similar pattern was found in mountains of Central Spain under Scot pine and Pyrenean oak ecotone and it was interpreted as a slower organic matter stabilization under the conifer (Díaz-Pinés et al., 2011) related to the lower C:N of oak litter respect to conifer litter which increases the C decomposability (Díaz-Pinés et al., 2014, 2011). In the present study, the soil C:N ratio of Cork oak soil is considerably lower when compared to soil C:N under Pine plantation. This relative enrichment in labile N forms may explain higher decomposability of Cork oak litter inputs. The lower decomposability of Pine-derived organic matter could explain the higher or similar enzymatic activities and SIR in Cork Oak when compared to Pine despite the differences in SOC. Moreover, the lower soil pH of Pine confirms the capacity of coniferous needles to acidify the soil respect to alternative oak vegetation in the Mediterranean region (Díaz-Pinés et al., 2014; Iovieno et al., 2010; Sariyildiz et al., 2005). The acidification of the soil under coniferous vegetation has been found to alter the soil microbial populations (Díaz-Pinés et al., 2014; Iovieno et al., 2010), and in our case, the further reduction of already low soil pH can exacerbate the Al-toxicity of the soil, which could constrain the microbial activity and enzymatic Table 4 Enzymatic activities and biological indicators in the 0–10 cm soil layer.

Cork oak Pine Cistus Grassland Olive Tillage No-tillage

β-gluca

NAGb

BAAc

336 (27.5) a 285 (18.4) ab 85.9 (2.23) c 104 (4.82) c 29.8 (3.67) d 84.3 (1.87) c 251 (14.1) b

150 (3.13) a 85.2 (5.52) bc 63.2 (11.2) cd 64.8 (5.00) cd 12.8 (0.48) e 45.9 (4.17) d 11.0 (4.39) b

51.0 32.8 26.9 33.3 10.6 22.5 36.9

(2.66) (5.12) (3.42) (2.92) (1.25) (4.79) (7.64)

BRd a ab bc ab c bc ab

1.67 2.32 0.66 0.52 0.16 0.46 0.77

SIRe (0.22) a (0.230) a (0.12) bc (0.04) c (0.05) d (0.04) c (0.05) bc

7.77 7.87 2.62 2.78 2.51 2.54 3.54

CUMf (0.30) (0.37) (0.20) (0.07) (0.14) (0.18) (0.12)

a a c bc c c b

1.28 2.58 0.51 0.34 0.13 0.34 0.41

(0.28) (0.31) (0.04) (0.03) (0.01) (0.02) (0.04)

SOC decomposabilityg b a c c d c c

17.1 17.2 11.9 10.5 5.69 13.3 11.3

(1.49) (1.68) (0.82) (1.17) (0.38) (1.04) (0.70)

a a b bc c ab b

The differences among the land use systems were analyzed by analysis of variance (ANOVA) and post-hoc Tukey’s test (p < 0.05). Different letters indicate differences at p < 0.05. Β-gluc, β-glucosidase enzymatic activity; NAG, β-glucosaminidase activity; BAA, N-benzoyl-L-argininamide protease activity; BR, Basal respiration; SIR, substrateinduced respiration; CUM, the cumulative C-CO2 emissions, SOC, soil organic C. h mg C-CO2. a μg saligenin g−1 3 h−1. b μmoles p-nitrophenol g-1 h−1. c mg NH4-N kg−1 soil h−1. d µg C-CO2 g-1 h−1. e mg C g−1. f mg C-CO2 g−1. 6

Catena 189 (2020) 104486

E. Vázquez, et al.

Fig. 3. Redundancy analysis (RDA) plot of soil microbial indicators constrained by soil physicochemical properties (0–10 cm) at seven common land uses in an acid Raña soil under Mediterranean conditions. The retained set of explanatory variable was selected by ordistep function in Vegan package. Vectors represent the retained physicochemical variables while soil microbial indicators are plotted in blue. Ellipses were obtained using ordiellipse function in Vegan package and indicate 95% confidence of the standard error of sampling point scores. SOC, soil organic carbon; TN, total nitrogen; CN, carbon to nitrogen ratio, NH4, NH4+-N content, pHH2O, soil pH determined in H2O; MBC, microbial biomass carbon; MBN, microbial biomass nitrogen; BR, Basal respiration; CUM, the cumulative C-CO2 emissions; C decomp, C decomposability; SIR, substrate induced respiration; Gluc, β-glucosidase enzymatic activity; NAG, β-glucosaminidase activity; BAA, N-benzoyl-L-argininamide protease activity. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

et al., 2017). The N losses derived from this stimulated N cycle should require further studies in order to rank the different LUC according to their environmental impact. The similarity between No-tillage and Cork Oak confirmed the feasibility of No-tillage to restore degraded soils and enhance their biological activity, while maintaining the crop production (Eleftheriadis et al., 2018; Eleftheriadis and Turrión, 2014; Vazquez et al., 2017). On the other hand, the depletion of all the studied C and N pools and the low levels of microbial activity observed in Olive groves confirm the unsuitability of tilled perennial woody crops under Mediterranean conditions due to the immense impact of tillage on soil SOC storage (Lagomarsino et al., 2011; Parras-Alcántara et al., 2013). The substitution of tillage by cover crops (preferably legumes) and the application of pruning waste or manure in woody crops have been found to reduce the soil degradation, promote the C accumulation and the enhancement of soil biological activity (Vicente-Vicente et al., 2016). The local administration should encourage and help the farmers to shift their agronomic management towards more sustainable soil conservation practices.

under Cistus shrubs, belonging to the same family as the shrubs in the present study, has been previously described after the encroachment of abandoned agricultural land by Cistus (Ternan et al., 1996b). The authors related the high aggregate stability under Cistus shrubland with the sticky exudation of Cistus which increases the hydrophobicity of the soil aggregates. In addition, the high affinity of the plant from the genus Cistus with the mycorrhiza could suggest an increase of soil aggregation promoted by the mycorrhiza (Comandini et al., 2006; Gómez-Paccard et al., 2013). Furthermore, the native Cistus shrublands have been proposed as alternative to restore degraded Raña soils because of the low erosion rates of Cistus shrublands (Ternan et al., 1996a) when compared to pine afforestation. This reduction of soil erosion could be related with the low rock fragments content of Shrub while the high content of Pine may be still caused by site conditioning during the afforestation. Similar SOC contents were obtained in No-tillage, Grassland and Shrub, while Tillage and Olive showed lower C contents, clearly demonstrating the susceptibility of these soils to enhanced mineralization of SOM under tillage. Similar effect, although of lower magnitude have been described in other Mediterranean alkaline soils (Celik, 2005; Francaviglia et al., 2014; Papini et al., 2011; Parras-Alcántara et al., 2013). However, the absence of calcium carbonate in acid soils reduce the soil Ca2+-mediated aggregation and decrease the SOC stabilization (Romanyà and Rovira, 2011). Therefore, the magnitude of SOC pools changes are greater in acid soils than those reported for alkaline soils. No-tillage have been proposed to increase the SOC content and restore the soil properties (Hontoria et al., 2018). According to RDA, the No-tillage sampling points were plotted separately from the Grassland and Shrub despite of their similar contents of the different studied C pools. No-tillage was plotted in the upper side of RDA2 near to the Cork Oak ellipse, which was caused by the relative enrichment of the N pools and the higher microbial activity, similarly to Cork Oak vegetation. The enrichment in the N pools and enhancement of microbial parameters could be caused by the yearly application of N fertilizers and the inclusion of vetch as a N-fixing legume (Kooch et al., 2019; Moghimian

4.2. Suitability of soil microbial indicators to identify different land uses The use of microbial parameters such as MBC and MBN, enzymatic activities, SIR or soil respiration have been successfully used for the evaluation of LUC impact on soil quality under Mediterranean conditions (Eleftheriadis and Turrión, 2014; Francaviglia et al., 2017; Lagomarsino et al., 2011; Peregrina et al., 2014). In particular, several authors have described MBC to be a good indicator due to its quick response to LUC when compared to SOC pool (Lagomarsino et al., 2011; Moghimian et al., 2017). The MBC seems to be sensitive to deforestation, agricultural land abandonment and soil disturbance by tillage (Eleftheriadis and Turrión, 2014; Madejón et al., 2009; Vazquez et al., 2017; Zornoza et al., 2009). Our results indicate a decreasing trend of MBC with increasing human intervention and agricultural intensification. In addition, according to RDA, MBC was also related with TN and 7

Catena 189 (2020) 104486

E. Vázquez, et al.

5. Conclusions

SIR. Similarly, MBN is another commonly used indicator of LUC, especially if emphasis is placed on N availability for plants and potential N losses from the system (Singh and Gupta, 2018). In our case, both MBC and MBN followed a decreasing pattern with higher human intervention as also observed previously (Kooch et al., 2019; Moghimian et al., 2017; Qi et al., 2018). In addition, the relatively higher MBN detected in No-tillage or Cork Oak was correlated with higher N availability (in form of NH4+-N) as shown in the RDA biplot. This confirms the potential of these two systems to accumulate SOC through SOC stabilization by the action of microbial activity promoted by higher N availability. In addition, Shrub was plotted together with Grassland or Tillage and separated of No-tillage despite their similar C contents. This was caused by the lower contents of EN, MBN and NH4+N in Shrub than in No-tillage which also reflects in the enzymatic activities. A study in the same region showed that Cistus shrubs caused a depletion of the N pools which reduced the N availability for the adjacent plants (Rolo et al., 2012). This fact should be considered carefully in the case of potential utilization of shrublands, which could be for example in the form of silvopastoral systems. Microbial activity could be quantified by the rate of CO2 release from the soil resulting from microbial decomposition of organic matter. Several studies have used BR, SIR, CUM and the calculated C decomposability to assess the LUC impacts because of their relationship with the SOC, soil C quality and microbial activity (Díaz-Pinés et al., 2011; Francaviglia et al., 2017; Moghimian et al., 2017; Moscatelli et al., 2007; Soleimani et al., 2019). All these variables followed the expected pattern of decreasing values with increasing soil disturbance. However, according to the RDA, C decomposability was more related to the differences in the N availability and enzymatic activity. This characteristic of C decomposability was observed in the similar values obtained in Cork Oak and Pine despite their differences in SOC (referred in the previous discussion Section 4.1) or the similar situation between Tillage and No-tillage, Shurb and Grassland. Tillage per se causes disruption of soil aggregates which enhances the C availability for the microorganisms (Kabiri et al., 2016). Additionally, we want to highlight than both SIR and CUM failed in separating some of the different land uses which were better discriminated by other microbial parameters, which decreases their usefulness as predictors of LUC on soil properties. Finally, the use of soil enzymatic activity as indicator of soil quality have been proposed (Gispert et al., 2013; Lagomarsino et al., 2011; Moghimian et al., 2017; Peregrina et al., 2014) and tested in the present study. In general terms, the three determined enzymes increased with increasing SOC and TN contents and decreasing soil disturbance as previously found in other areas (de Medeiros et al., 2017; Lagomarsino et al., 2011; Peregrina et al., 2014). However, the activity of the selected enzymes in Cork Oak and No-tillage were similar or higher than the activities determined under Pine despite the higher SOC. This result could be related with above mentioned lower decomposability of the derived Pine organic matter, to the further acidification of the soil, or to the relative scarcity of other nutrients as N which could affect the microbial stoichiometry suppressing the enzymatic activity (Sinsabaugh et al., 2009). This hypothesis is also supported by the tight relation between NH4+-N and the enzymatic activities found in RDA. In addition, the higher enzymatic activities observed in No-tillage respect to Tillage could be related to the drought and heat amelioration of Notillage under Mediterranean conditions as previously described by Vazquez et al. (2017). Finally, we want to highlight the absence of POxC and POM in RDA as both explanatory variables were removed during the ordistep selection. This was surprising as many previous studies found POM and POxC as the best indicators of LUC and tillage practices at least at European scale (Bongiorno et al., 2019). More studies are required to evaluate the potential and the suitability of these indicators under Mediterranean conditions.

Our study in the acid Raña soils in SW Spain identified the main changes caused by the most common land uses in the area. A general trend of higher C and N contents and higher microbial biomass and activity with decreasing agricultural intensity and soil disturbance was found. Both Cork Oak forest and Pine plantation accumulated the highest C and N contents, although the acidification and the C accumulation in labile forms of Pine could hinder the feasibility of Pine plantations to restore the acid and degraded Raña soils. In this respect, the natural revegetation after land abandonment was found to be a suitable strategy to recover degraded soils, emphasizing the high aggregate stability found in Shrub, probably derived from the sticky exudation of Halimium ocymoydes (Cistaceae). Among the three agricultural uses (No-tillage, Tillage and Olive), all the studied properties were degraded in Tillage and Olive respect to No-tillage, which confirms the negative impact of excessive tillage on already degraded Raña soils. Unlike chemical properties, the majority of the studied microbial parameters were suitable to discriminate among different land uses. Nevertheless, soil enzymatic activities, microbial biomass, basal respiration and C decomposability seemed to be the most useful indicators due to their capacity to account for the different levels of N availability among the land use systems. It is clear that the reduction of soil tillage is indispensable initial step in Raña soil quality restoration in order to maintain the agricultural production and reduce soil degradation. In addition, the natural revegetation seems to be more useful path for soil recovery when compared to pine afforestation for the restoration purposes of degraded Raña areas. Acknowledgements This work was supported by project AGRISOST-CM (S2013/ABI2717) from the Comunidad de Madrid and co-funded by the European Structural and Investment Funds. Eduardo Vázquez thanks the Spanish Ministry of Education for his FPU fellowship and Nikola Teutscherova thanks Cátedra Rafael Dal-Re/TRAGSA for their support. Financial support was also obtained from the Internal Grant Agency of Czech University of Life Sciences Prague (no. 20185004, and no. 20195005). Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.catena.2020.104486. References Almagro, M., Querejeta, J.I., Boix-Fayos, C., Martínez-Mena, M., 2013. Links between vegetation patterns, soil C and N pools and respiration rate under three different land uses in a dry Mediterranean ecosystem. J. Soils Sediments 13, 641–653. https://doi. org/10.1007/s11368-012-0643-5. Anderson, J.P.E., Domsch, K.H., 1978. A physiological method for the quantitative measurement of microbial biomass in soils. Soil Biol. Biochem. 10, 215–221. https:// doi.org/10.1016/0038-0717(78)90099-8. Bongiorno, G., Bünemann, E.K., Oguejiofor, C.U., Meier, J., Gort, G., Comans, R., Mäder, P., Brussaard, L., de Goede, R., 2019. Sensitivity of labile carbon fractions to tillage and organic matter management and their potential as comprehensive soil quality indicators across pedoclimatic conditions in Europe. Ecol. Indic. 99, 38–50. https:// doi.org/10.1016/j.ecolind.2018.12.008. Bremner, J.M., Mulvaney, C.S., 1982. Nitrogen-total. In: Page, A.L., Miller, R.H., D.R., K. (Eds.), Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties (Agronomy Series n 9) ASA. SSSA Madison, Wisconsin, pp. 595–624. Brookes, P.C., Landman, A., Pruden, G., Jenkinson, D.S., 1985. Chloroform fumigation and the release of soil nitrogen: A rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol. Biochem. 17, 837–842. https://doi.org/10. 1016/0038-0717(85)90144-0. Cabrera, M.L., Beare, M.H., 2010. Alkaline persulfate oxidation for determining total nitrogen in microbial biomass extracts. Soil Sci. Soc. Am. J. https://doi.org/10.2136/ sssaj1993.03615995005700040021x. Cambardella, C.A., Elliott, E.T., 1992. Particulate soil organic-matter changes across a grassland cultivation sequence. Soil Sci. Soc. Am. J. 56, 777. https://doi.org/10.

8

Catena 189 (2020) 104486

E. Vázquez, et al.

in a Mediterranean agro-forest ecosystem. Biol. Fertil. Soils 47, 283–291. https://doi. org/10.1007/s00374-010-0530-4. León, P., Espejo, R., Gómez-Paccard, C., Hontoria, C., Mariscal, I., Renella, G., Benito, M., 2017. No tillage and sugar beet foam amendment enhanced microbial activity of degraded acidic soils in South West Spain. Appl. Soil Ecol. 109, 69–74. https://doi. org/10.1016/j.apsoil.2016.09.012. Madejón, E., Murillo, J.M., Moreno, F., López, M.V., Arrue, J.L., Alvaro-Fuentes, J., Cantero, C., 2009. Effect of long-term conservation tillage on soil biochemical properties in Mediterranean Spanish areas. Soil Tillage Res. 105, 55–62. https://doi. org/10.1016/j.still.2009.05.007. Mariscal-Sancho, I., Peregrina, F., Mendiola, M.A., Santano, J., Espejo, R., 2009. Exchange complex composition in mediterranean ultisols under various types of vegetation and soil uses. Soil Sci. https://doi.org/10.1097/SS.0b013e3181a974fe. Mariscal, I., Peregrina, F., Terefe, T., González, P., Espejo, R., 2007. Evolution of some physical properties related to soil quality in the degraded ecosystems of “raña” formations from SW Spain. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv. 2007.01.025. Marzaioli, R., D’Ascoli, R., De Pascale, R.A., Rutigliano, F.A., 2010. Soil quality in a Mediterranean area of Southern Italy as related to different land use types. Appl. Soil Ecol. 44, 205–212. https://doi.org/10.1016/j.apsoil.2009.12.007. Moghimian, N., Hosseini, S.M., Kooch, Y., Darki, B.Z., 2017. Impacts of changes in land use/cover on soil microbial and enzyme activities. Catena 157, 407–414. https://doi. org/10.1016/j.catena.2017.06.003. Moscatelli, M.C., Di Tizio, A., Marinari, S., Grego, S., 2007. Microbial indicators related to soil carbon in Mediterranean land use systems. Soil Tillage Res. 97, 51–59. https:// doi.org/10.1016/j.still.2007.08.007. Muñoz-Rojas, M., Jordán, A., Zavala, L.M., De la Rosa, D., Abd-Elmabod, S.K., AnayaRomero, M., 2015. Impact of land use and land cover changes on organic carbon stocks in Mediterranean soils (1956–2007). L. Degrad. Dev. https://doi.org/10.1002/ ldr.2194. Nannipieri, P., Ceccanti, B., Cervelli, S., Matarese, E., 1980. Extraction of phosphatase, urease, proteases, organic carbon, and nitrogen from soil. Soil Sci. Soc. Am. J. 44, 1011. https://doi.org/10.2136/sssaj1980.03615995004400050028x. Oksanen, J., Blanchet, F., Kindt, R., Legendre, P., O’Hara, R., Simpson, G., Solymos, P., Stevens, M., Wagner, H., 2011. Vegan: community ecology package. R package version 1.17-18. Papini, R., Valboa, G., Favilli, F., L’Abate, G., 2011. Influence of land use on organic carbon pool and chemical properties of Vertic Cambisols in central and southern Italy. Agric. Ecosyst. Environ. 140, 68–79. https://doi.org/10.1016/j.agee.2010.11. 013. Parham, J.A., Deng, S.P., 2000. Detection, quantification and characterization of B-glucosaminidase activity in soil. Soil Biol. Biochem. 32, 1183–1190. Parras-Alcántara, L., Martín-Carrillo, M., Lozano-García, B., 2013. Impacts of land use change in soil carbon and nitrogen in a Mediterranean agricultural area (Southern Spain). Solid Earth 4, 167–177. https://doi.org/10.5194/se-4-167-2013. Peregrina, F., Mariscal, I., Ordóñez, R., González, P., Terefe, T., Espejo, R., 2008. Agronomic implications of converter basic slag as a magnesium source on acid soils. Soil Sci. Soc. Am. J. https://doi.org/10.2136/sssaj2006.0197. Peregrina, F., Pilar Pérez-Álvarez, E., García-Escudero, E., 2014. Soil microbiological properties and its stratification ratios for soil quality assessment under different cover crop management systems in a semiarid vineyard. J. Plant. Nutr. Soil Sci. 177, 548–559. https://doi.org/10.1002/jpln.201300371. Qi, Y., Chen, T., Pu, J., Yang, F., Shukla, M.K., Chang, Q., 2018. Response of soil physical, chemical and microbial biomass properties to land use changes in fixed desertified land. Catena 160, 339–344. https://doi.org/10.1016/j.catena.2017.10.007. Weil, R.R., Islam, K.R., Stine, M.A., Gruver, J.B., Samson-Liebig, S.E., 2003. Estimating active carbon for soil quality assessment: A simplified method for laboratory and field use. Am. J. Altern. Agric. 18, 3–17. https://doi.org/10.1079/AJAA200228. Rivas-Goday, S., 1964. Vegetación y flórula de la cuenca extremeña del Guadiana: (vegetación y flórula de la provincia de Badajoz). Diputación Provincial de Badajoz. Robarge, W.P., Edwards, A., Johnson, B., 2008. Water and waste water analysis for nitrate via nitration of salicylic acid 1. Commun. Soil Sci. Plant Anal. 14, 1207–1215. https://doi.org/10.1080/00103628309367444. Rolo, V., López-Díaz, M.L., Moreno, G., 2012. Shrubs affect soil nutrients availability with contrasting consequences for pasture understory and tree overstory production and nutrient status in Mediterranean grazed open woodlands. Nutr. Cycl. Agroecosyst. 93, 89–102. https://doi.org/10.1007/s10705-012-9502-4. Romanyà, J., Rovira, P., 2011. An appraisal of soil organic C content in Mediterranean agricultural soils. Soil Use Manage. https://doi.org/10.1111/j.1475-2743.2011. 00346.x. Romero-Díaz, A., Ruiz-Sinoga, J.D., Robledano-Aymerich, F., Brevik, E.C., Cerdà, A., 2017. Ecosystem responses to land abandonment in Western Mediterranean Mountains. Catena. https://doi.org/10.1016/j.catena.2016.08.013. Rovira, P., Jorba, M., Romanyà, J., 2010. Active and passive organic matter fractions in Mediterranean forest soils. Biol. Fertil. Soils 46, 355–369. https://doi.org/10.1007/ s00374-009-0437-0. Sariyildiz, T., Anderson, J.M., Kucuk, M., 2005. Effects of tree species and topography on soil chemistry, litter quality, and decomposition in Northeast Turkey. Soil Biol. Biochem. 37, 1695–1706. https://doi.org/10.1016/j.soilbio.2005.02.004. Singh, J.S., Gupta, V.K., 2018. Soil microbial biomass: a key soil driver in management of ecosystem functioning. Sci. Total Environ. 634, 497–500. https://doi.org/10.1016/j. scitotenv.2018.03.373. Sinsabaugh, R.L., Hill, B.H., Follstad Shah, J.J., 2009. Ecoenzymatic stoichiometry of microbial organic nutrient acquisition in soil and sediment. Nature 462, 795–798. https://doi.org/10.1038/nature08632. Soleimani, A., Mohsen, S., Reza, A., Bavani, M., Jafari, M., Francaviglia, R., 2019. Catena

2136/sssaj1992.03615995005600030017x. Celik, I., 2005. Land-use effects on organic matter and physical properties of soil in a southern Mediterranean highland of Turkey. Soil Tillage Res. 83, 270–277. https:// doi.org/10.1016/j.still.2004.08.001. Comandini, O., Contu, M., Rinaldi, A.C., 2006. An overview of Cistus ectomycorrhizal fungi. Mycorrhiza. https://doi.org/10.1007/s00572-006-0047-8. de Medeiros, E.V., Duda, G.P., Rodrigues dos Santos, L.A., de Sousa Lima, J.R., AlmeidaCortêz, J.S.D., Hammecker, C., Lardy, L., Cournac, L., 2017. Soil organic carbon, microbial biomass and enzyme activities responses to natural regeneration in a tropical dry region in Northeast Brazil. Catena 151, 137–146. https://doi.org/10.1016/ j.catena.2016.12.012. Díaz-Pinés, E., Rubio, A., Van Miegroet, H., Montes, F., Benito, M., 2011. Does tree species composition control soil organic carbon pools in Mediterranean mountain forests? For. Ecol. Manage. 262, 1895–1904. https://doi.org/10.1016/j.foreco.2011.02.004. Díaz-Pinés, E., Schindlbacher, A., Godino, M., Kitzler, B., Jandl, R., ZechmeisterBoltenstern, S., Rubio, A., 2014. Effects of tree species composition on the CO2 and N2O efflux of a Mediterranean mountain forest soil. Plant Soil 384, 243–257. https:// doi.org/10.1007/s11104-014-2200-z. Dunjó, G., Pardini, G., Gispert, M., 2003. Land use change effects on abandoned terraced soils in a Mediterranean catchment, NE Spain. Catena. https://doi.org/10.1016/ S0341-8162(02)00148-0. Eleftheriadis, A., Lafuente, F., Turrión, M., 2018. Soil & tillage research effect of land use, time since deforestation and management on organic C and N in soil textural fractions. 183, 1–7. https://doi.org/10.1016/j.still.2018.05.012. Eleftheriadis, A., Turrión, M.B., 2014. Soil microbiological properties affected by land use, management, and time since deforestations and crop establishment. Eur. J. Soil Biol. https://doi.org/10.1016/j.ejsobi.2014.03.001. Espejo, R., 1987. The soils and ages of the “raña” surfaces related to the Villuercas and Altamira mountain ranges (Western Spain). Catena 14, 399–418. https://doi.org/10. 1016/0341-8162(87)90012-9. Espejo Serrano, R., 1985. The ages and soils of two levels of “raña” surfaces in Central Spain. Geoderma. https://doi.org/10.1016/0016-7061(85)90039-4. Forster, J.C., 1995. Soil nitrogen. In: Alef, K., N.P. (Ed.), Methods in Applied Soil Microbiology and Biochemistry. pp. 79–87. Francaviglia, R., Benedetti, A., Doro, L., Madrau, S., Ledda, L., 2014. Influence of land use on soil quality and stratification ratios under agro-silvo-pastoral Mediterranean management systems. Agric. Ecosyst. Environ. https://doi.org/10.1016/j.agee.2013. 10.026. Francaviglia, R., Renzi, G., Ledda, L., Benedetti, A., 2017. Organic carbon pools and soil biological fertility are affected by land use intensity in Mediterranean ecosystems of Sardinia, Italy. Sci. Total Environ. 599–600, 789–796. https://doi.org/10.1016/j. scitotenv.2017.05.021. Garciá-Orenes, F., Morugań-Coronado, A., Zornoza, R., Scow, K., 2013. Changes in soil microbial community structure influenced by agricultural management practices in a Mediterranean agro-ecosystem. PLoS One 8, 1–9. https://doi.org/10.1371/journal. pone.0080522. García-Ruiz, J.M., 2010. The effects of land uses on soil erosion in Spain: A review. Catena 81, 1–11. https://doi.org/10.1016/j.catena.2010.01.001. Gispert, M., Emran, M., Pardini, G., Doni, S., Ceccanti, B., 2013. The impact of land management and abandonment on soil enzymatic activity, glomalin content and aggregate stability. Geoderma 202–203, 51–61. https://doi.org/10.1016/j. geoderma.2013.03.012. Gómez-Paccard, C., Mariscal-Sancho, I., León, P., Benito, M., González, P., Ordóñez, R., Espejo, R., Hontoria, C., 2013. Ca-amendment and tillage: Medium term synergies for improving key soil properties of acid soils. Soil Tillage Res. https://doi.org/10.1016/ j.still.2013.08.009. Hoffmann, G.G., Dedeken, M., 1965. Eine Methode zur colorimetrischen Bestimmung der β-Glucosidase-Aktivität in Böden. Zeitschrift für Pflanzenernährung, Düngung, Bodenkd. 108, 193–198. https://doi.org/10.1002/jpln.19651080302. Hontoria, C., Gómez-Paccard, C., Vazquez, E., Mariscal-Sancho, I., Ordoñez-Fernández, R., Carbonell-Bojollo, R., Espejo, R., 2018. Mid-long term effects of no tillage and Caamendment on degraded acid soils under contrasting weather conditions. Soil Tillage Res. 183, 83–92. https://doi.org/10.1016/j.still.2017.08.011. Iannotti, D.A., Pang, T., Toth, B.L., Elwell, D.L., Keener, H.M., Hoitink, H.A.J., 1993. A quantitative respirometric method for monitoring compost stability. Compost Sci. Util. 1, 52–65. https://doi.org/10.1080/1065657X.1993.10757890. Iovieno, P., Alfani, A., Bååth, E., 2010. Soil microbial community structure and biomass as affected by Pinus pinea plantation in two Mediterranean areas. Appl. Soil Ecol. 45, 56–63. https://doi.org/10.1016/j.apsoil.2010.02.001. IUSS Working Group WRB, 2015. World reference base for soil resources 2014, update 2015: International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106. FAO. Joergensen, R.G., 1996. The fumigation-extraction method to estimate soil microbial biomass: Calibration of the kEC value. Soil Biol. Biochem. 28, 25–31. https://doi.org/ 10.1016/0038-0717(95)00102-6. Kabiri, V., Raiesi, F., Ghazavi, M.A., 2016. Tillage effects on soil microbial biomass, SOM mineralization and enzyme activity in a semi-arid Calcixerepts. Agric. Ecosyst. Environ. 232, 73–84. https://doi.org/10.1016/j.agee.2016.07.022. Kemper, W.D., Rosenau, R.C., 1986. Aggregate stability and size distribution. Methods Soil Anal. Part 1. Phys. Mineral. Methods 9, 425–442. https://doi.org/10.2136/ sssabookser5.1.2ed.c17. Kooch, Y., Ehsani, S., Akbarinia, M., 2019. Stoichiometry of microbial indicators shows clearly more soil responses to land cover changes than absolute microbial activities. Ecol. Eng. 131, 99–106. https://doi.org/10.1016/j.ecoleng.2019.03.009. Lagomarsino, A., Benedetti, A., Marinari, S., Pompili, L., Moscatelli, M.C., Roggero, P.P., Lai, R., Ledda, L., Grego, S., 2011. Soil organic C variability and microbial functions

9

Catena 189 (2020) 104486

E. Vázquez, et al.

vegetation succession on soil quality in a humid Mediterranean landscape. Catena 149, 836–843. https://doi.org/10.1016/j.catena.2016.05.021. Vance, E.D., Brookes, P.C., Jenkinson, D.S., 1987. An extraction method for measuring soil microbial biomass C. Soil Biol. Biochem. 19, 703–707. https://doi.org/10.1016/ 0038-0717(87)90052-6. Vazquez, E., Teutscherova, N., Almorox, J., Navas, M., Espejo, R., Benito, M., 2017. Seasonal variation of microbial activity as affected by tillage practice and sugar beet foam amendment under Mediterranean climate. Appl. Soil Ecol. 117–118, 70–80. https://doi.org/10.1016/j.apsoil.2017.04.013. Vicente-Vicente, J.L., García-Ruiz, R., Francaviglia, R., Aguilera, E., Smith, P., 2016. Soil carbon sequestration rates under Mediterranean woody crops using recommended management practices: A meta-analysis. Agric. Ecosyst. Environ. https://doi.org/10. 1016/j.agee.2016.10.024. Walkley, A., Black, I.A., 1934. An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sci. 37, 29–38. Zornoza, R., Guerrero, C., Mataix-Solera, J., Scow, K.M., Arcenegui, V., Mataix-Beneyto, J., 2009. Changes in soil microbial community structure following the abandonment of agricultural terraces in mountainous areas of Eastern Spain. Appl. Soil Ecol. https://doi.org/10.1016/j.apsoil.2009.05.011.

Influence of land use and land cover change on soil organic carbon and microbial activity in the forests of northern Iran. 177, 227–237. https://doi.org/10.1016/j. catena.2019.02.018. Soil Taxonomy, 2014. Keys to Soil Taxonomy, 12th. USDA-Natural Resources Conservation Service, Washington, D.C. Strobl, W., Traunmueller, M., 1996. β-Glucosidase activity. In: Schinner, F., Öhlinger, R., Kandeler, E., Margesin, R. (Eds.), Methods in Soil Biology. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 198–200. https://doi.org/10.1007/978-3-64260966-4. Tan, Z., Lal, R., 2005. Carbon sequestration potential estimates with changes in land use and tillage practice in Ohio, USA. Agric. Ecosyst. Environ. 111, 140–152. https://doi. org/10.1016/j.agee.2005.05.012. Ternan, J.L., Williams, A.G., Elmes, A., Fitzjohn, C., 1996a. The effectiveness of benchterracing and afforestation for erosion control on Rana sediments in Central Spain. L. Degrad. Dev. https://doi.org/10.1002/(SICI)1099-145X(199612)7:4<337::AIDLDR238>3.0.CO;2-G. Ternan, J.L., Williams, A.G., Elmes, A., Hartley, R., 1996b. Aggregate stability of soils in central Spain and the role of land management. Earth Surf. Process. Landforms 21, 181–193. https://doi.org/10.1002/(SICI)1096-9837(199602)21:2<181::AIDESP622>3.0.CO;2-7. van Hall, R.L., Cammeraat, L.H., Keesstra, S.D., Zorn, M., 2017. Impact of secondary

10