IntroductionTop

The Raña of Cañamero is one of the typical digitiform or fan-like uplands in the Iberian Peninsula, dated in a Middle-posterior Pliocene with a subtropical climate. Ancient raña-surfaces are formed by alluvial sediments from quartzite massifs located between river basins, the Villuercas Mountains (Espejo-Serrano, 1978). Currently and into the proper xeric regime of the Mediterranean subregion, the raña-environment is relatively humid by its Atlantic influence (annual rainfall about 900 mm). The soil is classified into ultisols as Typical Palexerult (Soil Survey Staff, 2014), with plinthic segregation of the horizon Bt (Peregrina, 2005), and the soil epipedon is fragile with high content in gravel, and acid (pH ≈ 5) with high soluble aluminium content (González-Fernández et al., 2008).

In the middle of the twentieth century, the dominant raña-forest of cork oak’s Quercus suber L. was primary converted into silvopastoral systems of Quercus silex L., pastures and cereal lands of Secale cereale (L). Traditional agriculture in the raña-land was determinant into the soil impoverishment, the posterior abandonment of the land use and its natural reconversion into prairies steppe/savannah-type. The raña-prairie is an unproductive agrosystem with a low forage production -about 1.6 t/ha (Pedro González-Fernández; unpublished data)- of xerophytic grasses (Fig. 1A). Liming, or pH-amendment practices, promote fertility and productivity of acid soils (Manoj-Kumar et al., 2012), and reduce its erodibility (Rhoton, 2000). For raña-soils, phosphogypsum, red gypsum and sugar foam are alternatives to lime and mine gypsum to alleviate soil acidity and related aluminium phytotoxicity (González-Fernández et al., 2003; García Navarro et al., 2009).

Agrosystems need a model of productivity that ensures its sustainability (Marshall, 1993; Convention on Biological Diversity, 2010; De Vries et al., 2013). For our knowledge, there are no references about the diversity of soil animals in raña-environment and the effect of the agriculture practices in the local populations of soil animals.

Figure 1. Natural field in late March-2008 (A); experimental field in late April-2008 (B). FP, fertilized prairie; IP, improved prairie; FC, forage crop.

Within the soil biotic-net and its inhabiting mesofauna (invertebrates with a breadth<2 mm), mites belonging to Oribatida Duges, 1834 or oribatids are common residents and dominants in the upper layers of soils and organic horizons (Wallwork, 1976; Coleman, 2001). Oribatids are detritivorous and microphytophagous, primary and secondary decomposers in the soil’s food web (Woolley, 1960; Schneider et al., 2004) and therefore, are involved in the cycle and mineralisation of organic matter and in the formation and stability of fertile soils (Butcher et al., 1971; Petersen & Luxton, 1982; Seastedt, 1984; Osler & Sommerkorn, 2007). By their demographic behaviour, are k-strategists with a low growth rate of population and a poor dispersal capacity (Luxton, 1981; Beckmann, 1988). For the last reasons, the oribatids diversity, based on the species abundance data, constitute a direct and feasible parameter to biodiversity in soils (Linden et al., 1994; Behan-Pelletier, 1999; André et al., 2002; Gergócs & Hufnagel, 2009), and are useful to analyse the biological response to a soil disturbance, at local and medium or long-term levels (Beckmann, 1988).

In 2002, a project was started about the promotion of the fertility and consequent productivity of the raña-prairie. The selected model of agriculture was defined as plant-conservative, because herbicidal treatments were excluded to preserve the grass diversity of the prairie, and in contraposition to largely applied soil-conservative models where chemical herbicides are required (e.g. no-till and direct seeding). This paper aims to evaluate the effect of selected agricultural practices (conventional tillage, liming and cropping) on the diversity of soil animals of the prairie, estimated by the oribatid mites demography, and to obtain a model of agricultural practices that integrates a more efficient plant productivity and preservation of the soil biodiversity of the raña-prairie.

Material and methodsTop

ResultsTop

Table 1 shows the descriptive statistics for agricultural responses and estimated GLM coefficients associated to plot-treatments. Field factor (EF treatment) affects pH, bulk density and herbaceous biomass (p<0.001), and there is no evidence of effect on C:N ratio (p>0.05). The pH increase was associated exclusively with lime, and the reduction of bulk density and increase of vegetal biomass with crop. Into EF, there were no plot differences in all responses related to crop and lime interaction (p>0.05).

A total of 13698 oribatids belonging to 34 species were collected (Table 2). In NF, 22/34 of the species were detected, Cosmochthonius reticulatus and Minunthozetes sp.were unique species and Oribatula (Zygoribatula) exarata is the dominant species with nearly 2/3 of the oribatids population.

Contrary to NF findings, in EF we identified 32/34 of the species detected and two primitive oribatids (Haplochthonius sanctaeluciae and Acrotritia ardua) appeared as unique species. Adittionally, O. (Z) exarata numbers were reduced to nearly 1/3 of the abundance and less abundant species in NF increased their numbers, as is in the extreme case of Microppia minus that multiplies in 208 the NF values, reaching nearly a fifth of the total individuals.

The analysis of field MCFs of richness indicates that there was a significant increment of S_o in relation to soil sample size (Fig. 2A, Laplace test, p<0.001) and the lack of significance for field factor (shape ± scale, EF: 2.05 ± 64.15, NF: 2, 30 ± 154.92; Chi-square, p>0.05). Additionally, the increment of S_e is due to oribatids abundance (Fig. 2B, Laplace test, p<0.001) and there was no difference between fields (EF: 1.20 ± 2, 13, NF: 1.21 ± 2.32; Chi-square, p>0.05).

Figure 2. Species richness in raña-fields, mean cumulative functions (MCFs) and 95% confidence levels. Observed richness versus soil sample size (A). Expected richness versus oribatids cumulative abundance obtained by the rarefaction method (B). EF: experimental field, NF: natural field.

For the field factor, the α-responses S_j, H_j and D_j fit adequately to normal distribution and N_j to log-normal one (Table 3, Fig. 3). GLM analyses indicates that all α-parameters are influenced by field factor (p<0.001) and a lack of significance of crop, lime or crop and lime interaction into EF-field (Table 3).

Figure 3. Fits of α-parameters and 95% confidence levels for field factor. A, C and D: normal distributions. B: log-normal distribution. EF: experimental field, NF: natural field.

Sample richness was positively correlated with herbaceous biomass (r=0.463, p<0.01) and negatively with bulk density (r=-0.472); sample abundance with biomass (r=0.462, p<0.01); and equity and dominance with pH, bulk density and biomass (pH: H_j, r=0.420 and D_j r=-0439, p<0.01; ρ_s, H_j, r =-0.589 and D_j r=0.583, p<0.01; t/ha, r=0.386 and D_j r=0.495, p<0.001). The optimal regression equations (F and t-tests p<0.05, normality of standarized residuals, p>0.05) are:

Sj=6.86 – 3.04 ρ_s + 0.145 t/ha (F, p<0.001; t, constant p<0.001, ρ_s and t/ha, p<0.05; s= 1.31, R²=27.0%),

Ln N_j=3.25 + 0.0670 t/ha (F-test, p<0.01; t-tests, constant, p<0.001, t/ha, p<0.01; s= 0.50, R²=14.7%),

H_j=1.70 – 0.817 ρ_s (F-test, p<0.001; t-tests, constant, p<0.001, ρs, p<0.001; s= 0.19, R²=33.2%), and

D_j=0.196 + 0.350 ρ_s (F-test, p<0.001; t-tests, constant, p<0.001, ρ_sp<0.001; s= 0.08, R²=32.4%).

Agricultural variables and α-statistics by separate do not securely discriminate fields (discriminant analysis; agricultural: 95.6% accuracy, D²=17.72; α-statistics: 93.3% accuracy, D²=7.20), and combined data discriminate securely fields (D²=26.48). A greater discriminative value is offered by the species abundance matrix (D²=343.55). Figure 4 shows the combined influence of α-diversity, agricultural variables and species abundance on the plots dispersion in the two principal components analysis.

Figure 4. First two principal components graph of the combined matrix of species abundance (in black), agricultural variables (in red) and α-parameters (in green). A: scatter graph, B: eigenvectors. EF: experimental field, NF: natural field. Species abbreviations in B follow Table 2.

DiscussionTop

Oribatids from the Raña-prairie of Cañamero are commonly reported in the Iberian Peninsule living in a wide variety of soils in xeric habitats (Pérez-Íñigo, 1993; Pérez-Íñigo, 1997; Subías & Arillo, 2001). Fifteen species are previously cited in the related Villuercas Mountains (Subías & Shtanchaeva, 2012) and 12 are new location records (Subías et al., 2014).

The upper 10 cm of 0.18 m² of sampled soil of the prairie contains 22 species and 2123 individuals (S=22; converted N=11794 individuals/m²). Last data fall within the classic range for herbaceous biomes of Wallwork (Wallwork, 1980), close to desert grasslands (S=20, N=13000 individuals/m²) and lower than in temperate ones (S=44, N=32000). Comparing the data with other palearctic grasslands in Europe, the raña-prairie richness and/or abundance was: i) higher than dry and cold steppes of Northern Spain (Arroyo et al., 2005); ii) similar to those of humid regions of northern Spain (Corral-Hernández & Iturrondobeitia, 2012), heathlands in the Netherlands (Kardol et al., 2009), with acid soils in Scotland (Cole et al., 2005), loess soils in Germany (Hülsmann & Wolters, 1998), dry alpine meadows (Schatz, 1996) and with calcareous soils in Switzerland (Baur et al., 1996), and iii) less than dense prairies in wetlands of Europe (Weis-Fogh, 1948; Curry & Momen, 1988; Penttinen et al., 2008).

The raña-prairie can be identified as an infertile and unproductive ecosystem of Wardle et al. (2004), with an acid soil, low herbaceous biomass with xerophytic condition and consequent high soil C:N ratio (Fig. 2A; Table 1). The Oribatida community is adapted to agricultural land use, data supported by the presence of four passalozetids (Table 2), species that are common in Iberian agrosystems (Pérez-Íñigo, 1993). In the raña-prairie, O. (Z.) exarata is the dominant species. This oribatid has a southern Palearctic distribution (Subías et al., 2015), where is a common inhabitant of humid prairies (Pérez-Íñigo, 1993). This species possess a relatively thick cuticle with a striated cerotegumental layer that is distinctive of surface dwellers living in sunny habitats with poor vegetation. The strong influence of this species on the community demography is comparable to those of stony environments and mosses in steppes of Crimea (Ukraine) (Seniczak et al., 2012) and for this, the relative abundance of O. (Z.) exarata may be an indicator for soil compaction for raña-type or humid, sunny and stony prairies in the south of Europe where this species is present. Finally, species less adapted to higher soil density and low vegetation cover have smaller populations, are aggregated in more porous and/or protected locus and their finding depends statistically on the sample size (Fig. 2).

The plant-conservative model of the experimental field, preserves the natural development of the herbaceous community by avoiding herbicide treatment, improving soil structure and increasing herbaceous coverage estimated by it aerial biomass (Table 1). As consequence, EF treatments increased samples richness and abundance and structural equity of oribatids community (Fig. 3, Table 3). In relation to NF, EF samples contain 1.65 times more species, individuals are 1.16 times more abundant, the equity index is 1.42 times higher and decrease the dominance index 1.41 times. Our results agree with the postulate that the oribatid respond to changes in soil edaphic factors and dynamics of habitat resources (Butcher et al., 1971; Wardle, 2002) and their response is favourable to improving soil structure and revegetation (Dong-Hui et al., 2007; Minor & Norton, 2008). The prairie-community prefers this new habitat, where the oribatids population grows; the relative abundance of O. (Z) exarata decreases; new populations of small and/or delicate primitive oribatids are detected; and other oribatids less adapted to the original habitat increase their numbers, are more dispersed and establish more equitable demographic relationships.

By a first and strict point of view, traditional agriculture practices can decrease the heterogeneity, richness and abundance of oribatids (Edwards & Lofty, 1975; Siepel & Van de Bund, 1988; Hülsmann & Wolters, 1998; Pandit & Bhattacharya, 2000; Arroyo & Iturrondobeitia, 2006; Minor & Cianciolo, 2007). Contrasting with last assumption, the recuperation of degraded agrosystems is related to a positive and bi-directional relationship between plant biomass and soil animals (Osler & Beattie, 2001; De Deyn et al., 2003; Wardle et al., 2004; Gormsen, 2006; St John et al., 2006). This relationship follows a chronosequence model suggested by Maharning et al. (2009): in the early stage of recuperation increases the species richness and later, their abundance. Oribatids follow the model of Maharning et al. (2009), with an apparent effect at medium and long term (Zaitsev et al., 2006; Kardol et al., 2009). For the last reasons, an increase of the productivity of the raña-prairie, via soil fertilisation, pH correction and/or cropping more productive herbs, results in a positive effect in oribatids populations.

Kardol et al. (2009) point out that the mesofaunistic restoration of degraded ecosystems depends primarily on the colonization of pioneer species from surrounding habitats. In our case of a moderately degraded agrosystem of the raña-prairie, we interpret an alternative model of in-site recolonization from the same habitat. This model, that is complementary or additive to the Kardol et al. (2009) model, is more consequent at short or medium-term scale with the k-strategy of population growth and low-scale capacity of dispersion in the space of the oribatids, and is supported by the statistical equality of expected and observed cumulative richness (Fig. 2). Additionally, previous authors indicated that the species richness is not determined by the identity or species composition of the herbaceous community (Osler & Beattie, 2001; Porazinska et al., 2003; St John et al., 2006). Our results agree with last premise: there are cumulative richness equality between fields and involving crop treatment (NF wild herbs=EF cultivated herbs; Fig. 2) and sample richness equality into EF (FP wild herbs = IP and FC wild herbs + forage crops; Table 3).

The oribatids have a specific pattern of vertical distribution in soil layers, that is related to soil depth, compaction (Price & Benham Jr, 1977; Perdue & Crossley Jr, 1990) and pore diameter (Vreeken-Buijs et al., 1998; Ducarme et al., 2004; Nielsen et al., 2008). Bulk density is a simple and reliable estimator of the soil physical condition, of its structure, texture and porosity (Chen et al., 1998; Carter & Ball, 1993) and additionally, of an available place into the soil to live for oribatids. The correlation and regression models show a direct correlation between ρ_s and α-diversity. In EF plots, increases the space for the ‘structure followers’ and among them, the oppiid M. minus. This species has great ecological plasticity and is common in open biotopes in Central and Northern Spain (Subías & Arillo, 2001; Arroyo et al., 2005). M. minus has tendency to vertical migration and occupies deeper organic layers (Moritz, 1963), is poli- and meso-hygrophilous and in relation to pH is oligo-mesophilic (Rajski, 1968), and as is in oppiids, with a relative great capacity of population increase (Maraun & Scheu, 2000). The relative abundance of M. minus can be used as indicative for a more porous and plant covered raña-microhabitat.

Mineralization increases the richness and abundance of mesoarthropods in low-input grasslands (Marshall, 1977; Cole et al., 2005). In our case of a seminatural and degraded raña-prairie, the low or minimum intervention model, that includes an initial tillage and annual fertilization (EF-FP-NL plots), enhances desirable α-parameters, which are positively related with herbaceous biomass. Bardgett & Cook (1998) indicate that grasslands with low human intervention are self-regulating ecosystems with an optimal biotic diversity. Additionally, in acid grasslands of Scotland, Cole et al. (2005) observed an independent and non-additive effect of fertilization and liming in oribatids demography. In our studied case, the minimum intervention model (plot EF-FP-NL with an unique and initial tillage and annual fertilisation) agrees with the optimum of Bardgett & Cook (1998) and, in line with Cole et al. (2005), suggests that above last optimal threshold of local diversity, if biomass is increased by effect of pH correction or crop, there is no apparent effect in population parameters (Table 3).

The soil pH amendment with sugar foam improves its productivity via correcting soil acidity and related phytotoxicity of the soluble aluminium, and adding new nutrients to soil. This treatment gradually increases the pH 0.7-0.9 points between 0-856 days post-treatment and is effective up to 8-9 years (González-Fernández et al., 2003, 2008). Oribatids exhibit a specific response to pH in natural (Moritz, 1963; Hågvar, 1990) and experimental conditions (Van Straalen & Verhoef, 1997). The raña-community shows adaptation to minor pH variations and its meso-acidophilic condition. Phosphogypsum was utilized as complement of sugar foam and source of phosphorus to the soil. However, this mineral contains 12.3 g/kg of fluorine, element that is phytotoxic in relation to its capacity to solubilize the soil aluminium (Mariscal-Sancho et al., 2009). Oribatids are sensitive to soil contamination with heavy metals and fluorine (Vasiliu et al., 1995; Ivan & Vasiliu, 2009) and in a natural grassland, a concentration of 10-15 ppm of fluorine in soil affects their abundance (Vasiliu et al., 1995). In our test, the application of an equivalent dose of 0.585 kg/ha of fluorine has not valuable signification on populations demography.

Finally, we conclude that, at local-scale and from the standpoint of the oribatids, the plant-conservative model applied is a feasible solution to improve both productivity and biodiversity of degraded and unproductive prairies for extensive agriculture and/or livestock use of pasture lands.