Spatial distribution of biological soil crusts along an aridity gradient in the central-west of Argentina

Journal of Arid Environments 176 (2020) 104099

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Spatial distribution of biological soil crusts along an aridity gradient in the central-west of Argentina

T

Ana L. Navas Romeroa,∗, Mario A. Herrera Morattac, Eduardo Martinez Carreterob, Rosa Ana Rodrigueza, Bárbara Ventod a

Instituto de Ingeniería Química, Facultad de Ingeniería (UNSJ), Grupo Vinculado al PROBIEN (CONICET-UNCo), San Juan, Argentina Instituto Argentino de Investigaciones en Zonas Áridas, Consejo Nacional de Investigaciones Científicas y Tecnológicas, Mendoza, CP 5500, Argentina c Instituto de Biotecnología, Facultad de Ingeniería (UNSJ), Argentina d Instituto Argentino de Nivología y Glaciología-CONICET-Mendoza, Argentina b

A R T I C LE I N FO

A B S T R A C T

Keywords: Biocrusts Interaction Aridity gradient SADIE Impact

Biocrusts presented their highest expression in the inter-patches. However, an increase in the level of aridity along the landscape could lead to vascular plants to make a notable influence on the spatial distribution of biocrusts. Our objective was to determine the spatial variation of the vascular plant interactions with biocrusts, and the individual variations of biocrusts and each of its components along a gradient of aridity in Argentina. We worked on three sites following a semiarid-arid-hyperarid environmental aridity gradient. We established 15 plots along the stress gradient. In each plot, we evaluated the spatial distribution of cyanobacteria, mosses, and lichens and the interaction with the dominant shrubs using a distance index analysis. The hyperarid site showed an aggregate distribution pattern for each biological group (biocrusts, mosses, lichens, and cyanobacteria). The semiarid site showed an aggregate distribution for mosses and cyanobacteria. Respect to the interaction with the shrubs, only the hyperarid site showed a positive interaction between shrubs and the components of biocrusts. We found positive interactions of lichens on the semiarid site, but the arid studied site did not show interactions. Reductions in vegetation cover could directly influence in the biocrust coverage, generating impacts on ecosystems.

1. Introduction During the last decade, significant research efforts have been devoted to predict how the facilitation and competition interactions change along abiotic stress gradients influenced by precipitation and temperature (Maestre and Cortina, 2004; Brooker et al., 2008). This interest is not surprising, due to the importance of these stress situations to accurately predict the impacts of global change on plant communities and ecosystems. The relationship between the result of plantplant interactions and the degree of abiotic stress has been formalized in a conceptual model known as the stress gradient hypothesis (SGH) postulated by Bertness and Callaway (1994). This hypothesis predicts that the relative importance of facilitation and competition varies inversely in gradients with abiotic stress, being the facilitation the dominant process when the stress of the system increases. Thus, SGH predicts that the net balance of interactions is positive during facilitation, when the stress is high, due to environmental variables or even by the pressure of herbivores. On the other hand, negative interactions can

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occur in situations of intermediate stress levels (Maestre et al., 2009). The increase in facilitation processes is fundamental for the ecosystem functions because they have the capacity to expand the fundamental ecological niches and to change its distribution patterns (Graff and Aguiar, 2011). Additionally, it could increase the richness, the recruitment success of populations, and even affect the evolution of species (Kikvidze and Callaway, 2009). There are many studies to prove this prediction (Callaway, 2007) and many of them have shown that changes in the degree of abiotic stress have significant impacts on plantplant interactions (Lortie and Callaway, 2006; Maestre et al., 2009). However, a few studies have evaluated how these interactions vary along non-manipulated abiotic stress gradients (Dullinger et al., 2007). In addition, researches about the interactions among organisms other than vascular plants are still scarce. Biological soil crusts (biocrusts) are present in most of the arid systems in the world and they influence many functional ecosystem processes. They affect the cycle, stability and availability of soil nutrients and modulate the establishment and performance of vascular

Corresponding author. E-mail address: [email protected] (A.L. Navas Romero).

https://doi.org/10.1016/j.jaridenv.2020.104099 Received 16 May 2019; Received in revised form 8 January 2020; Accepted 9 January 2020 0140-1963/ © 2020 Elsevier Ltd. All rights reserved.

Journal of Arid Environments 176 (2020) 104099

A.L. Navas Romero, et al.

Fig. 1. Map showing the area of study with the location of the three studied sites: arid, semiarid and hyperarid.

specific components of the biological soil crusts (Zhang et al., 2016). Vascular plants seem to have influence in biological crusts, providing shade through the canopy, generating a thermal layer with the fallen litter or even modifying the edaphic properties through the activity of their roots (Zhang et al., 2016). Even though the organisms in biocrust are adapted to high intensities of light, they often obtain benefits from the shade of the vegetation reducing the damage by light and drought (Harel et al., 2004; Belnap et al., 2016). However, it is possible that this adaptation would be related to competition. Many studies indicate that the increased in intensity of UV-B solar radiation causes a significant reduction of the photosynthetic functions, the destruction of the chloroplast ultrastructure and the disorder of the antioxidant enzyme systems (Hui et al., 2013). A few methodologies have been developed to evaluate the interactions plant-plant or plant-biocrust. Currently, a more reliable and simple way to do it is to analyze their distribution patterns and their relationships (Martens et al., 1997; Miriti et al., 1998). The knowledge of the individual distribution patterns of a species together with the environment that surrounds it helps to predict the factors that influence its spatial distribution. Distribution patterns are fundamental to conserve the structure of communities and their diversity, as well as the ecosystems processes (Bolker et al., 2003). However, few studies have evaluated these distribution patterns empirically (Maestre and Cortina, 2002; Maestre, 2003). In order to advance in the knowledge about the interactions between the biocrust components and the vascular vegetation through a stress gradient, we formulated the hypothesis that the spatial distribution of biocrusts and the interaction with the vegetation patches are

plants, producing habitats for a large number of arthropods and microorganisms (Belnap et al., 2016). Their coexistence together with vascular vegetation is of special interest to study the interactions between their components and this kind of plants (Maestre et al., 2010; Belnap et al., 2016). Biocrusts have been demonstrated to be sensitive to intense changes in land use and climate changes (Memmott et al., 1998). The biological activity in arid and semiarid ecosystems is mainly determined by the frequency and time of precipitation (Noy-Meir, 1973). Due to this fact, biocrusts are metabolically active under humid conditions and their physiological functions are highly sensitive to the light and temperatures (Lange, 2003). Any change in the precipitation pattern for climate change, would have serious consequences in physiological functions of biocruts (Kidron et al., 2012; Johnson et al., 2012; Ferrenberg et al., 2015). In fact, annual rainfall has an effect in the succession stages of biocrusts and even the species within show different responses to climate change. This situation can produce the alterations of biocrusts and even in the function process of them in the ecosystem. A recent study about future climate conditions in southern South America postulates changes in the regional characteristics of droughts and serious changes in precipitation patterns for the central west of Argentina (Penalba and Rivera, 2016). Increases in dry stress levels along a landscape could lead to the vascular plants a notable influence on the spatial distribution of biocrusts (Maestre, 2003). Tewksbury and Lloyd (2001) worked on an abiotic stress gradient in arid zones and highlighted the importance of direct facilitation under unfavorable environmental conditions. Several studies suggest that vascular vegetation promotes microclimatic and edaphic changes that may help to the development of 2

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Table 1 Frequency values of the sampled squares showing a non-random spatial pattern (Ia ≠ 1, p < 0.005) and summary of the SADIE analysis for the components of the evaluated biological soil crust. The data represent the mean and the standard deviation (obtained from the five plots); Ia-aggregation index, Vj = mean of grouping index for clearings and Vi = mean of grouping index for spots. Component

Site

Frequency %

Ia ± SD

Biocrust

Semiarid Arid Hyperarid Semiarid Arid Hyperarid Semiarid Arid Hyperarid Semiarid Arid Hyperarid

20 20 80 20 40 100 60 20 80 40 20 80

1.27 1.28 1.62 1.28 1.35 1.77 1.42 1.20 1.69 1.27 1.26 1.86

Mosses

Cyanobacterias

Lichens

Table 2 Results of ANOVA (values of F, p, and degrees of freedom, gl) and the effect of the site on the values of the SADIE indices (transformed by a logarithm function), Ia = aggregation index, Vj = mean of the grouping index for the clear area and Vi = mean of the grouping index for the spots. (*) = Indicates significant differences. Component

Index SADIE

± ± ± ± ± ± ± ± ± ± ± ±

Vi ± SD 0.32 0.14 0.50 0.20 0.44 0.23 0.45 0.22 0.67 0.37 0.12 0.65

Cyanobacterias

Lichens

Mosses

Ia Vi Vj Ia Vi Vj Ia Vi Vj Ia Vi Vj

± ± ± ± ± ± ± ± ± ± ± ±

0.27 0.18 0.51 0.17 0.39 0.30 0.30 0.20 0.66 0.36 0.14 0.62

−1.26 −1.22 −1.57 −1.28 −1.31 −1.72 −1.39 −1.16 −1.67 −1.28 −1.25 −1.87

± ± ± ± ± ± ± ± ± ± ± ±

0.31 0.07 0.47 0.18 0.38 0.22 0.45 0.20 0.70 0.37 0.12 0.65

Table 3 Frequency values of the sampled squares showing a non-random spatial pattern (Ia ≠ 1, p < 0.005) for each evaluated site and summary of the SADIE analysis for the association evaluate. The data represent the mean and the standard deviation; Xi = global association index. Interaction

Site

Frequency %

Xi ± SD

Shrub*Biocrust

Semiarid Arid Hyperarid Semiarid Arid Hypearid Semiarid Arid Hyperarid Semiarid Arid Hyperarid

0 20 60 40 0 80 0 20 60 60 20 60

0.03 ± 0.25 0.07 ± 0.20 0.25 ± 0.13 0.31 ± 0.31 0.15 ± 0.20 0.32 ± 0.20 −0.03 ± 0.17 0.02 ± 0.19 0.21 ± 0.13 0.12 ± 0.29 0.06 ± 0.10 0.37 ± 0.19

Results of ANOVA Site

BCs

1.19 1.27 1.56 1.18 1.28 1.69 1.30 1.14 1.56 1.23 1.24 1.81

Vj ± SD

F

g.l.

p

1.76 1.86 1.89 1.47 1.35 1.6 2.79 2.83 2.98 3.41 4.11 3.84

2 2 2 2 2 2 2 2 2 2 2 2

0.21 0.19 0.19 0.26 0.29 0.24 0.1 0.09 0.08 0.04 (*) 0.04 (*) 0.04 (*)

Shrub*Mosses

Shrub*Cyanobacterias

Shrub*Lichens

2.1.1. Semiarid site The semiarid site is located at the southwest part of the province of San Juan (32°00′8.43 ″S; 68°45′10.18″ W) at 1139 m a.s.l. The site corresponds to the area called “Pedernal Protected Landscape” and it includes the conservation of 17700 ha (Dalmasso et al., 2011). The average annual rainfall is 370 mm and the average temperature 18 °C with a minimum of 6 °C and a maximum 20.7 °C. The soils correspond to Entisols in the typic Torriortentes (Regairaz, 2000). The area corresponds to the Monte phytogeographic unit with a recorded floristic richness of 345 vascular species. The communities of Zuccagnia punctata Cav., Larrea divaricata Cav., Baccharis salicifolia Ruiz and Pav. together with Hyalis argentea Don ex Hook. and Arn. are dominant in this area. In this site the communities of biocrust is dominated for mosses as Pseudocrossidium arenicola (Dusen) M.J. Cano, Pseudocrossidium chilense R. S. Williams and lichens as Enchylium coccophorum (Tuck.) Otálora, P.M. Jørg. and Wedin, Placidium lachneum (Ach.) Breuss, being the mean coverage value for the biocrust 21.1% (Navas Romero, 2019).

modified according to the aridity intensity of the system in the centralwest part of Argentina. Thus, the objective of this contribution is to determine the spatial variation of biocrusts and the interaction with the vegetation patches along a gradient of aridity in the central-west of Argentina.

2. Materials and methods 2.1. Study sites The study area comprehends three sampling sites. Two of them are distributed in the southern part of San Juan province (31°47′10.13″ S, 67°58′55.75″ W) and one site is located in the north part of Mendoza Province (32°43′24.3″ S, 68°50′29.69″ W), following an aridity gradient. The total distance of the transect is approximately 300 km long (Fig. 1). The annual aridity index according to De Martonne (1942) for each area is semiarid site: 10.9, arid site: 6.2, and hyperarid site: 5. We randomly selected 15 sampling plots following an environmental aridity gradient during the dry season (September–October) on 2016. The gradient consisted of the selection of semiarid, arid and hyperarid sites, considering a total of 5 plots per site. The selected sites did not present any anthropic impact. The aridity gradient causes stress due to high solar radiation and low rainfall and therefore, water availability.

2.1.2. Arid site The study area is located in the Capdevile district (32°43′24.3 ″S, 68°50′29.69″ W), Mendoza at 741 m a.s.l., in the morphostructural area of the Andes Precordillera. The average annual rainfall is 220 mm and 38% of the precipitation occurs during the summer season (December–February). The average annual temperature is 17.5 °C with a maximum value of 30 °C and a minimum value of 3 °C. The soils correspond to Entisols in the typical Torrifluvents (Regairaz, 2000). According to the vegetation, the area corresponds to the Monte phytogeographic unit, where Larrea cuneifolia (750–1200 m a.s.l.) is the dominant species. In this site the communities of biocrust is abundant and was dominated for mosses as Pseudocrossidium arenicola, 3

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Fig. 2. Cluster index maps (v) for biocrust along the stress gradient.

4 = 51–75% and 5 = 76–100%. We recorded The X and Y coordinates for each sample.

Pterygoneurum ovatum (Hedw.) Dixon, Bryum argenteum Hedw., lichens as Psora decipiens (Hedwig) Hoffm., Enchylium coccophorum, and cyanobacteria in particular the genus Microcoleus sp., Oscillatoria sp. and Nostoc sp., being the mean coverage value for biocrusts of 42.3% (Navas Romero, 2019).

2.3. Analysis of the spatial pattern for each component of biocrusts We used the spatial analysis by distance index (SADIE) developed by Perry (1998) to determine the spatial distribution pattern of the biological soils crusts and the degree of association with vascular plants. We performed the spatial analysis for mosses, lichens, cyanobacteria, and the dominant shrubs in each sampling plot using the coverage and position values, (X and Y) to evaluate the individual variations of each element along the stress gradient. This analysis is based on the “distance to regularity” (D), which evaluates the distance that the values of the variable under study (coverage) need to move in space to obtain a regular distribution, and where the coverage is the same at all sampling points (Perry, 1998). To estimate the magnitude of “D”, its value is compared with the results of a Monte Carlo test, based on a series of permutations where the coverage values are randomly distributed among the sampling points. Then, the observed value of D is divided by the average value obtained from the permutations and the aggregation index, Ia, was obtained (Perry, 1998). We used this index to describe the spatial pattern of the data. According to Perry (1998), an aggregate distribution has values Ia > 1, a random distribution if Ia = 1 and a regular distribution if Ia < 1. We compared the obtained D value with the tails of the distribution of values as resulted of the permutations and we observed the statistical significance (Perry et al., 1999). Finally, we calculated the “index of clustering” (v) to measure the grouping of the data in spots (areas with above-average cover) and clear area (areas with below-average cover). This dimensionless index quantifies the degree to which each sample contributes to the overall clustering of the data. Sampling units located within a spot have values of v (by convention vi) higher than 1.5, while those located in regions of lower cover (clear area) present values of v (by convention vj) below of −1.5; values close to 1 indicate a random placement of that unit (Perry et al., 1999). To test for the presence of significant patches and or gaps in the data we performed two permutation tests for donor and receiver units, respectively. For a donor unit i (sampling point with above-average abundance) that has a flow of counts to nj receiver units (sampling points with below-average abundance), the average distance of outflow

2.1.3. Hyperarid site The study area is located in Los Médanos Grandes, in the province of San Juan (31°47′10.13 ″S, 67°58′55.75″ W), on the eastern side of the Sierra Pie de Palo at 729 m a.s.l. The area belongs to the Central Monte Desert (Carrera et al., 2009; Martínez Carretero, 2013). The bioclimate of the region corresponds to the Hyperarid (Pastrán et al., 2011). The average annual rainfall is 103 mm and it occurs mainly from December (early summer) to May (autumn). The average annual temperature is 18 °C; with a maximum of 40 °C and a minimum of 10 °C. The soils correspond to Entisols in the typic Torripsamments (Regairaz, 2000). The vegetation is dominated by species of the family Zigofilaceae. The dominant vegetation consists of shrubs of Bulnesia retama and Larrea divaricata, with a few representatives of Prosopis flexuosa DC. Burkart subinermis in depressed areas. Other present species are Tricomaria usillo Hook. and Arn., Senna aphylla (Cav.) H.S. Irwin and Barneby, L. cuneifolia, Lycium spp., Atamisquea emarginata Miers ex Hook. and Arn., and Bougainvillea spinosa (Cav.) Heimerl. In this site, the communities of biocrust are dominated by mosses such as Pseudocrossidium arenicola, Bryum argenteum and cyanobacteria in particular the genus Scytonema sp. and Oscillatoria sp., being the mean coverage value for the biocrust is 25% (Navas Romero, 2019). 2.2. Experimental design The size of each sampled plot was determined according to the physiognomic and structural characteristics of the plant community developed in each site following to Maestre and Quero (2008). For the semiarid site, the dimensions of the plots were 5 × 10 m (50 m2), for the arid site of 6 × 10 (60 m2), and for the hyperarid site of 15 × 8 m (120 m2). In each site we selected 5 plots randomly. To avoid pseudoreplicas, plots were separated by 150 m of distance according to field observations. We set a reference point for the “X” axis and the “Y” axis. We subdivided each plot into 1 × 1 m squares to estimate the coverage of mosses, lichens, cyanobacteria and dominant shrubs following the Braun-Blanquet scale: 0 = 0%, 1 = 1–5%, 2 = 6–25%, 3 = 26–50%, 4

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Fig. 3. Cluster index maps (v) for mosses, cyanobacteria, and lichens obtained along the stress gradient.

the mean value for gaps, Vj, is compared with its expectation of — 1 using randomization tests as described above for Ia.

is computed as follows (nomenclature and formula following (Perry et al., 1999):

Yi =

∑j dij vij 2.4. Analysis of the spatial association between shrubs and biocrusts

∑i vij

We calculated the “Xi” “index of spatial association” to evaluate the interactions between the dominant shrub and components of biocrusts (lichens, mosses, and cyanobacteria). This index reveals the degree of interaction between the components and the dominant shrub. With SADIE, this analysis can be performed by using the contribution of each sampling unit towards the overall correlation coefficient of the values

where vij is the outflow to the j th of ni receiver units, and dij is the distance of this flow [(xi − xj)2 + (yi − yj)2] 1/2. Hence, there is an average outflow distance for each of the donor units. For receiver units, the calculations are the same with the convention that the index is negative. In each case, the mean value of the clustering index for patches, Vi, is usually compared with its expectation of 1 and separately, 5

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Fig. 4. Maps of local association between biocrusts and the dominant shrub in the stress gradient (hyperarid-arid-semiarid). The white and gray areas indicate a negative and positive spatial association, respectively. The areas with a significant association (p < 0.05) are surrounded in black.

Cyanobacteria showed an aggregate distribution pattern for two of the studied sites. This pattern is present in 80% and 60% of the samples for the hyperarid and semiarid site, respectively. For both sites, the absolute values of Ia, Vi, Vj indices were higher than 1.1. In the arid site, cyanobacteria showed an aggregate pattern but only for 20% of the samples. The highest values for these indices were obtained in the hyperarid site (Ia = 1.69, Vi = 1.56, Vj = −1.67) (Table 2). Their spatial pattern was not affected by the site, and we found no significant differences among sites for the SADIE indices (Table 3). Lichens showed some fluctuations in the aggregate spatial pattern with a value of 80% in samples from the hyperarid site (Table 1). In the semiarid and arid sites, the lichens showed a pattern aggregate for 40% and 20% of the samples, respectively. We found no significant differences among the three studied sites (Table 2). The obtained absolute values of the indices Ia, Vi, Vj for this component of biocrusts were higher than 1.2 (Table 3). The highest value was obtained for the hyperarid site (Ia = 1.86, Vi = 1.81, Vj = −1.87). Finally, mosses showed a completely aggregate pattern for the hyperarid site in all the samples with Ia values significantly different from 1 (Table 1). The individual spatial pattern of this component of the biocrust was affected by the site due to the number of squares where the value of Ia was statistically different from 1 and was higher in the hyperarid, but only concerning to the semiarid site. The obtained values of the Ia, Vi, Vj indices for this component were higher than 1.1. The highest values for these indices were obtained in the hyperarid site (Ia = 1.77, Vi = 1.69, Vj = −1.72) (Tables 2 and 3). The maps of v index showed the distribution of the spots of aggregation and clear area within the sampled squares (Figs. 2 and 3). We observed a higher level of aggregation in the site with a higher level of stress (hyperarid) and a decrease of this aggregation pattern both in the arid and semiarid site (Fig. 2). For mosses, the distribution pattern followed the hyperarid > arid > semiarid stress gradient. However, the lichens and cyanobacteria, followed the pattern hyperarid > semiarid > arid aridity gradient (Fig. 3).

of v (Perry and Dixon, 2002). If the values of v for variable A are denoted vA, with mean qA and those of variable B are denoted vB, with mean qB, a measure of local spatial association for a sampling unit I (Xi) is given by (Perry and Dixon, 2002):

Xi =

n (viA − qA)(viB − qB ) ∑i (viA − qA)2 (viB − qB )2

Where n is the number of sampling units (100 in this study). Positive values of Xi indicate the presence of coincidences in the spots or clear area in both components (biocrusts and shrubs), while negative values indicate the presence of a spot in one component and a clear area in the other one. The values of Xi are continuous and are self-correlated, so they can be represented on a map in two dimensions in order to visualize the areas where association or dissociation occurs within each sampled square (Perry and Dixon, 2002). We performed the analysis of correlations and local association for each sampled plot using the software described in Perry and Dixon (2002). We utilized the SURFER program with 5967 permutations (maximum value of permutations) to evaluate the local association and 12345 permutations to evaluate the statistical significance of the correlation analysis. We constructed maps of the grouping index and local association by linear interpolation with the SURFER program (Golden Software, Colorado, USA). We used the SPSS software (SPSS Inc., Chicago, Illinois, USA) to perform the statistical analysis. 3. Results 3.1. Spatial pattern for each component of biocrusts Biocrusts showed an aggregate pattern for the hyperarid site with values significantly different from 1 for 80% of the samples (Table 1). In the semiarid and arid site, biocrusts showed a non-random pattern only for 20% of the samples (Table 1). The absolute values for Ia, Vi, Vj indices were higher than 1.1 in the three sites (Table 2). The spatial pattern of biocrusts was not affected by the site and we found no significant differences among sites for any of the SADIE indices for the interaction between biocrusts and shrubs (Table 3).

3.2. Distribution pattern between shrubs with mosses, lichens, and cyanobacteria There was a positive interaction between shrub-biocrusts for the 6

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Fig. 5. Maps of local association between the different components of the biological crust and the dominant shrub in the stress gradient (hyperarid-arid-semiarid). The white and gray areas indicate a negative and positive spatial association, respectively. The areas with a significant association (p < 0.05) are surrounded in black.

Xi index were positive and higher than 0.2 for all the interactions in the hyperarid site, which suggest a positive interaction between shrubs and each component of biocrusts (Table 3). The arid site showed the lowest positive values for interactions with mosses, lichens, and cyanobacteria. The semiarid site showed intermediate values compared with the other two sites. At least 60% of the sampled squares had a positive Xi and were significantly different from 1 for the shrub-lichen interaction. Only 40% of the sampled squares had a positive Xi for shrub-moss interaction. The shrub-cyanobacteria interaction turned out to be negative in this site (Table 3).

hyperarid site with values significantly different from 1 for 60% of the samples (Table 3). In the arid site, the shrub-biocrust interaction showed a positive interaction with values significantly different from 1 only for 20% of the samples (Table 2). The values for Xi indices were positive and higher than 1.1, except for the semiarid site (Table 3). Finally, in the semiarid site, the shrub-biocrust interaction is not significant in none of the sampled squares (Table 3). The hyperarid site showed a positive interaction between the dominant shrub and each of the components of biocrusts, with values from 60 to 80%, a positive Xi and significantly different from 1 (Table 2). These differences were observed on the maps of the local associations (Fig. 4). The values of the 7

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4. Discussion

(Maestre et al., 2010; Zhang et al., 2016). Mosses must reduce the hydric potential of their own cells to absorb water and keep the normal physiological functions with a minimal loss of water (Lan et al., 2014). To perform this process of protection, they reduce the activity of protective enzymes and also the osmoregulation substances (Bu et al., 2017). The dew is another important source of water for biocrusts in arid and semiarid environments and these organisms are probably adapted to this condition (Kidron et al., 2002; Veste and Littmann, 2006). Often, the quantity of dew is not high enough, a good value of up to 0.17 mm (equal to precipitation) was suggested and occasionally occurs up to 0.3 mm (Uclés et al., 2014). Higher levels of hydration can be obtained catching the drops from fog or clouds as an important source of water for biocrusts even for re-hydration or to extend their biological activity (Csintalan et al., 2000; Reiter et al., 2008). Precipitation, dew, and fog are more frequent in arid and semiarid site, while in the hyperarid site only the precipitation and dew are present but they are rare (own field observations). According to Zhang et al. (2016), the approaching of mosses to vegetation will be mainly attributed to the increase of the humidity in the air and the decrease of damage by desiccation and the light, taking advantage of shade areas, as the case of mosses in the hyperarid site. The water in the cells of mosses can be very low during long periods of time and the tolerance is −20 a −40 MPa (Oliver et al., 2005; Proctor et al., 2007), according to the adaptation to the environment. Consequently, the water of the cells in some mosses can stay longer in the hyperarid site. This strategy reduces the metabolism processes during dry periods and the physiological activities are restricted to hydration periods (Coe et al., 2014). Lichens showed an irregular distribution pattern with a higher level of aggregation and a positive interaction in the hyperarid site (Table 1, Fig. 3). It is followed by the semiarid site which showed the lowest level of aggregation and in the arid site, they showed a regular distribution pattern. The interaction with the dominant shrub did not show any relationship with the level of aridity (Fig. 4–5, Table 3). The lack of association between lichens and shrubs in the arid and semiarid site may be related to two main causes: First, the less acute or intense limits between these two sites, which are more obvious in the hyperarid site. Second, the capacity of lichens to tolerate high temperatures and low humidity conditions in both sites, such as Enchylium coccophorum and Placidium lachneum. It has been shown that lichens are often promoted by higher intensity of light than mosses (Sedia and Ehrenfeld, 2003). The high tolerance to desiccation of lichens allows them to live in places where none plant can survive (Kranner et al., 2008). They suffer oxidative stress during desiccation and antioxidants of low molecular weight as glutathione are important for surviving. The enzymes that produce ROS (reactive oxygen species) such as SOD (superoxide dismutase), CAT (catalase), and peroxidases are also involved in the elimination of ROS. Others enzymes as GR (glutathione reductase) and G6PDH (glucose-6-phosphate dehydrogenase) could be an important role in the fast recovery of species with higher tolerance to desiccation. Multiple lichen species produce a unique range of secondary metabolites with aromatic structures that make them able to tolerate desiccation and have the protection provided by secondary UV-absorbing metabolites that allow lichens to live in extreme or open environments (Green and Lange, 1995). The overall pattern of recovery from desiccation after the re-wetting process is similar for both lichens and mosses, although it is faster in lichens (Proctor, 2010). Lichens quickly recover but they remain active only briefly, while many mosses recover slowly but they remain active longer (Kappen and Valladares, 2007; Green et al., 2011). In all the studied sites, the most frequent species of lichen was Enchylium coccophorum (Tuck.) Otálora, Jorg. and Wedin. The genus Enchylium Ach. (Gray) has been shown to be saturated at light intensities as high as 1500 μmol fotones·m2·s−1 (Lange, 2003). This genus is characterized by pigments from the group of xanthophyll, B-carotene, canthaxanthin, echinone and scytonemin (Belnap et al., 2007). These compounds increase after exposure to solar ultra violet (UV) radiation, functioning as a sunscreen protection (Ehling-Schulz

The study of changes in the distribution patterns of biocrusts and their interactions with the dominant shrubs along aridity gradients is fundamental to understand the ecosystem functioning (Maestre et al., 2010). Our results support partially the hypothesis that the aggregation pattern increases when the aridity gradient increased, resulting in a higher level of aggregation and global association in the hyperarid (maximum evaluated stress level). However, these changes did not follow a continuum (Figs. 2–5) as we expected. Consequently, variations in distribution levels and interactions could be more complex and influenced by characteristics specific of each component of biocrust and by other variables such as soil texture, stoniness and litter. Then, variations do not result clearly differentiate in site with similar temperature and humidity conditions as showed in the arid and semiarid site (Belnap et al., 2003; Maestre, 2003; Maestre and Cortina, 2004). Changes in the responses of biocrusts along a rainfall gradient have been observed in some zone desert (Yair et al., 2011; Kidron and Tal, 2012; Zaady et al., 2014). Biocrusts stay inactive during desiccation and they can tolerate extremely high or even low temperatures and light. The tolerance of them to these extreme conditions is adaptive and does not occur in poikilohydric organisms that do not meet these environmental stresses (Green et al., 2011). Thus, differences among groups could be because species or functional groups have different optimum ecological niches and the stress level is relative for the groups (Liancourt et al., 2013). In our study we only analyzed the role of the dominant shrub as facilitating organism and we do not consider the gramineas or sub-shrub roles. Therefore, the result of the interaction between each species and its neighbor depend on the stress level in their micro-habitats. The interaction with other components of the site, more specifically herbs or succulents could have similar effects or not in the distribution pattern and the biocrust can be associated with a specific type of plant. Mosses were the components with higher changes in the spatial distribution pattern along the aridity gradient (Table 3; Fig. 3). They showed a lower aggregation level in the semiarid site and a higher one in the hyperarid site; as well as an increase in a positive interaction with the dominant shrub when stress increases in the site. They presented a continuous spot pattern (Vi = 1.18) but it changed to isolated spots (Vi = 1.69) if the degree of aridity in the system increases (Table 1). In the hyperarid site, the areas occupied by mosses were smaller and isolated. This result is clearly observed in the different values of Ia (Table 1). Mosses are especially vulnerable to partial hydration and need more time to activate the photosynthesis than lichens. According to Stark et al. (2005) to fully hydrate patches of Crossidium crassinerve in the desert of Mojave it is necessary a rainfall of at least 2 mm. Lower values of precipitation together with a fast-drying after rainfall can produce substantial damage and the death of these organisms (Barker et al., 2005). Moreover, dry mosses repel water when they start getting wet, which indicates that the recovery of mosses does not occur with low rainfalls (Green and Proctor, 2016). Poikilohydric organisms, like mosses, can also be hydrated catching the humidity in the air, the dew and the fog (Veste et al., 2008). Results found in the hyperarid site suggested that dominant shrubs facilitate the development of mosses and the aridity gradient is determined by high temperatures, which used to reach values of 70 °C in the soil and a rainfall of 103 mm per year with events of less than 2 mm of rainfall and 62 mm during the three warmest months (De Fina, 1992). The drought period is extensive with up to 145 days without rainfall. Precipitations are in a specific area and consist of a few millimeters when they occur (Servicio Metereológico Nacional, 1991–2017). Physiological changes, during dry periods, limit the photosynthesis activity and the growth of mosses. Microclimate conditions generated by shrubs seem to be the principal mechanism involved in the facilitation (Zhang et al., 2016). In soils under shrubs the repellence of water is low, the increase of the porosity, humidity and the shade from shrubs reduces the PAR radiation and the temperature of the soil compared with areas without vegetation 8

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supported by the Agencia Nacional de Promoción Científica y Tecnológica. We are grateful for the comments and suggestions made by the reviewers that improved our manuscript.

and Scherer, 1999). Belnap et al. (2007) demonstrated that this genus also has both scytonemin (Absorbs UV-A) and microsporin (absorbs UVB). Cyanobacteria showed a similar pattern that lichens, evidencing a higher level of aggregation in the hyperarid site and a lower aggregation pattern in the arid site. The interaction between shrub and cyanobacteria was negative for the semiarid site. In this site no significant interaction between the dominant shrub and cyanobacteria (Table 2, Fig. 3) was found. In the semiarid and arid sites, the biocrust was dominated by cyanobacteria with a wide distribution. On the other hand, both studied sites developed a layer of biocrust which was present in almost all the surface. The lack of interaction between cyanobacteria and shrubs in all the studied systems resulted as we expected because the better micro-climate conditions promoted by shrubs was not significative if we consider the high tolerance of this group organisms to low humidity values and high temperatures. Cyanobacteria are the organisms with more resistance to drought periods and high levels of light intensity compared with the other groups (Belnap, 2006). They segregate a protection layer of EPS (exopolysacarids) that plays a fundamental role in the resistance to different types of stress (Potts, 2001; Kidron et al., 2008) and it can migrate through the soil profile (Garcia-Pichel and Pringault, 2001; Lan et al., 2014). Moreover, they synthezise UV detection pigments, particularly in the genus Nostoc Vaucher ex Bornet and Flahault, Scytonema Vaucher Agardh ex Bornet and Flahault, Calothrix Agardh ex Bornet and Flahault, which allows them to survive on the soil surface (García-Pichel and Castenholz, 1993). All these features about cyanobacteria would explain why high levels of drought do not produce changes in their spatial distribution.

References Barker, D., Stark, L., Zimpfer, J., Mcletchie, N., Smith, S., 2005. Evidence of droughtinduced stress on biotic crust moss in the Mojave Desert. Plant Cell Environ. 28, 939–947. Belnap, J., 2006. The potential roles of biological soil crusts in dryland hydrologic cycles. Hydrol. Process. 20, 3159–3178. Belnap, J., Weber, B., Büdel, B., 2016. Biological soil crusts as an organizing principle in drylands. In: Weber, B., Büdel, B., Belnap, J. (Eds.), Biological Soil Crusts as an Organizing Principle in Drylands. Springer Cham., Switzerland, pp. 3–13. Belnap, J., Hawkes, C., Firestone, M., 2003. Boundaries in miniature: two examples from soil. Bioscience 53, 739–749. Belnap, J., Phillips, S., Smith, S., 2007. Dynamics of cover, UV-protective pigments, and quantum yield in biological soil crust communities of an undisturbed Mojave Desert shrubland. Flora Morphol. Distrib. Funct. Ecol. Plants 202, 674–686. Bertness, M., Callaway, R., 1994. Positive interactions in communities: a post-cold war perspective. Trends Ecol. Evol. 9, 191–193. Bolker, B., Pacala, S., Neuhauser, C., 2003. Spatial dynamics in model plant communities: what do we really know? Am. Nat. 162, 135–148. Brooker, R., Maestre, F., Callaway, R., Lortie, C., Cavieres, L., Kunstler, G., Liancourt, P., Tielbörger, K., Travis, J., Anthelme, F., Armas, C., Coll, L., Corcket, E., Delzon, S., Forey, E., Kikvidze, Z., Olofsson, J., Pugnaire, F., Quiroz, C., Saccone, P., Schiffers, K., Seifan, M., Touzard, B., Michalet, R., 2008. Facilitation in plant communities: the past, the present, and the future. J. Ecol. 23, 18–34. Bu, C., Wang, C., Yang, Y., Zhang, L., Bowker, M.A., 2017. Physiological responses of artificial moss biocrusts to dehydration-rehydration process and heat stress on the Loess Plateau, China. J. Arid Land 9, 419–431. Callaway, R., 2007. Positive Interactions and Interdependence in Plant Communities. Springer Science and Business Media, Dordrecht, The Netherlands. Carrera, A., Mazzarino, M., Bertiller, M., Del Valle, H., Martinez Carretero, E., 2009. Plant impacts on nitrogen and carbon cycling in the Monte Phytogeographical Province, Argentina. J. Arid Environ. 73, 192–201. Coe, K., Sparks, J., Belnap, J., 2014. Physiological ecology of dryland biocrust mosses. In: Hanson, D., Rice, S. (Eds.), Photosynthesis in Bryophytes and Early Land Plants, Advances in Photosynthesis and Respiration. Springer Science Business Media, Dordrecht, The Netherlands, pp. 291–308. Csintalan, Z., Takács, Z., Proctor, M., Nagy, Z., Tuba, Z., 2000. Early morning photosynthesis of the moss Tortula ruralis following summer dew fall in a Hungarian temperate dry sandy grassland. Plant Ecol. 151, 51–54. Dalmasso, A., Márquez, J., Abarca, A., Montecchiani, R., Rosales, M., Zabaleta, E., 2011. Flórula del paraje de Pedernal y alrededores: departamento Sarmiento. INCA, San Juan (San Juan). De Fina, A.L., 1992. Aptitud agroclimática de la República Argentina. Academia nacional de agronomía y veterinaria, Buenos Aires. De Martonne, E., 1942. Nouvelle Carte Mondial de l’indice d’aridité. Ann. Geograph. 51, 241–250. Dullinger, S., Kleinbauer, I., Pauli, H., Gottfried, M., Brooker, R., Nagy, L., Theurillat, J.P., Holten, J.I., Abdaladze, O., Benito, J., Borel, J., Coldea, G., Ghosn, D., Kanka, R., Merzouki, A., Klettner, C., Moiseev, P., Molau, U., Reiter, K., Rossi, G., Stanisci, A., Tomaselli, M., Unterlugauer, P., Vittoz, P., Grabherr, G., 2007. Weak and variable relationships between environmental severity and small-scale co-occurrence in alpine plant communities. J. Ecol. 95, 1284–1295. Ehling-Schulz, M., Scherer, S., 1999. UV protection in cyanobacteria. Eur. J. Phycol. 34, 329–338. Ferrenberg, S., Reed, S.C., Belnap, J., 2015. Climate change and physical disturbance cause similar community shifts in biological soil crusts. Proc. Natl. Acad. Sci. 112, 12116–12121. García-Pichel, F., Pringault, O., 2001. Cyanobacteria track water in desert soils. Nature 413, 380–381. Garcia-Pichel, F., Castenholz, R., 1993. Occurrence of UV-absorbing, mycosporine-like compounds among cyanobacterial isolates and an estimate of their screening capacity. Appl. Environ. Microbiol. 59, 163–169. Graff, P., Aguiar, M., 2011. Testing the role of biotic stress in the stress gradient hypothesis. Processes and patterns in arid rangelands. Oikos 120, 1023–1030. Green, T., Sancho, L., Pintado, A., 2011. Ecophysiology of desiccation/rehydration cycles in mosses and lichens. In: Weber, B., Büdel, B., Belnap, J. (Eds.), Biological Soil Crusts: an Organizing Principle in Drylands. Springer Cham., Switzerland, pp. 385–406. Green, A., Proctor, M., 2016. Carbon budgets of biological soil crusts. In: Weber, B., Büdel, B., Belnap, J. (Eds.), Biological Soil Crusts: an Organizing Principle in Drylands. Springer Cham., Switzerland, pp. 287–304. Green, T., Lange, O., 1995. Photosynthesis in poikilohydric plants: a comparison of lichens and bryophytes. In: Schulze, E.D., Caldwell, M.M. (Eds.), Ecophysiology of Photosynthesis. Springer, Berlin, Heidelberg, pp. 319–341. Harel, Y., Ohad, I., Kaplan, A., 2004. Activation of photosynthesis and resistance to photoinhibition in cyanobacteria within biological desert crust. Plant Physiol. 136, 3070–3079. Hui, R., Li, X., Chen, C., Zhao, X., Jia, R., Liu, L., Wei, Y., 2013. Responses of photosynthetic properties and chloroplast ultrastructure of Bryum argenteum from a desert biological soil crust to elevated ultraviolet-B radiation. Physiol. Plant. 147, 489–501.

5. Conclusions Mosses, lichens, and cyanobacteria showed different responses to changes in the precipitation and temperature patterns. Changes in the precipitation and temperature patterns could have notorious influence in the spatial distribution of the studied components of biocrusts such as mosses, lichens and cyanobacteria. Differences in the distribution pattern of these organisms, according to the aridity degree, could be related to physiological characteristics and the adaptation mechanisms for each functional group, which allow them to tolerate different aridity levels. Additionally, the distribution of studied functional groups of biocrusts is related to the available safe places for colonization and growth. In this sense, dominant shrubs allow the persistence and settlement of some functional groups as mosses and lichens but they are not important for cyanobacteria. Consequently a decrease of dominant shrubs have a direct impact in the spatial distribution of biocrusts with a negative environmental impact in the studied ecosystems in central-western of Argentina. CRediT authorship contribution statement Ana L. Navas Romero: Writing - original draft, Formal analysis, Investigation, Methodology. Mario A. Herrera Moratta: Formal analysis, Writing - review & editing. Eduardo Martinez Carretero: Supervision, Methodology, Writing - review & editing. Rosa Ana Rodriguez: Writing - review & editing. Bárbara Vento: Writing - review & editing. Declaration of competing interest There is not any potential conflict of interest by the authors. Acknowledgments We thank to Heber Merenda, Yamil Rodriguez, David Ponce, and Yanina Rivas for the collaboration in the fieldwork. This study was 9

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103–115. Miriti, M., Howe, H., Wright, S., 1998. Spatial patterns of mortality in a Colorado desert plant community. Plant Ecol. 136, 41–51. Navas Romero, A.L., 2019. Funciones ecosistémicas y atributos ecológicos de las costras biológicas en ecosistemas semiáridos-áridos-hiperáridos del centro-oeste de la Argentina. Tesis de doctorado. Universidad Nacional de Cuyo, Mendoza, Argentina. Noy-Meir, I., 1973. Desert ecosystems: environment and producers. Annu. Rev. Ecol. Systemat. 4, 25–51. Oliver, M., Velten, J., Mishler, B., 2005. Desiccation tolerance in bryophytes: a reflection of the primitive strategy for plant survival in dehydrating habitats? Integr. Comp. Biol. 45, 788–799. Pastrán, G., Martinez Carretero, E., Mamani, M., Vich, A., Sánchez, V., 2011. Dinámica eólica e hídrica en el sistema de Médanos Grandes, SE de San Juan, Argentina. Multequina 20, 15–26. Penalba, O., Rivera, J., 2016. Regional aspects of future precipitation and meteorological drought characteristics over Southern South America projected by a CMIP5 multi‐model ensemble. Int. J. Climatol. 36, 974–986. Perry, J., Dixon, P., 2002. A new method to measure spatial association for ecological count data. Ecoscience 9, 133–141. Perry, J., 1998. Measures of spatial pattern for counts. Ecology 79, 1008–1017. Perry, J., Winder, L., Holland, J., Alston, R., 1999. Red-blue plots for detecting clusters in count data. Ecol. Lett. 2, 106–113. Potts, M., 2001. Desiccation tolerance: a simple process? Trends Microbiol. 9, 553–559. Proctor, M., 2010. Recovery rates of chlorophyll-fluorescence parameters in desiccationtolerant plants: fitted logistic curves as a versatile and robust source of comparative data. Plant Growth Regul. 62, 233–240. Proctor, M., Oliver, M., Wood, A., Alpert, P., Stark, L., Cleavitt, N., Mishler, B., 2007. Desiccation-tolerance in bryophytes: a review. Bryologist 110, 595–621. Regairaz, M., 2000. Suelos de Mendoza. In: Abraham, E., Rodríguez Martínez, F. (Eds.), Argentina. Recurso y problemas ambientales de la zona árida. Provincia de Mendoza, San Juan y La Rioja. Universidades y centros de investigación de la región andina Argentina, Mendoza, pp. 59–62. Reiter, R., Höftberger, M., Green, T., Türk, R., 2008. Photosynthesis of lichens from lichen-dominated communities in the alpine/nival belt of the alps - II: laboratory and field measurements of CO2 exchange and water relations. Flora 203, 34–46. Sedia, E., Ehrenfeld, J., 2003. Lichens and mosses promote alternate stable plant communities in the New Jersey Pinelands. Oikos 100, 447–458. Stark, L., Mcletchie, D., Mishler, B., 2005. Sex Expression, plant size, and spatial segregation of the sexes across a stress gradient in the desert moss Syntrichia Caninervis. Bryologist 108, 183–193. Tewksbury, J., Lloyd, J., 2001. Positive interactions under nurse-plants: spatial scale, stress gradients and benefactor size. Oecologia 127, 425–434. Uclés, O., Villagarcía, L., Moro, M., Canton, Y., Domingo, F., 2014. Role of dewfall in the water balance of a semiarid coastal steppe ecosystem. Hydrol. Process. 28, 2271–2280. Veste, M., Littmann, T., 2006. Dewfall and its geo-ecological implication for biological surface crusts in desert sand dunes (north-western Negev, Israel). J. Arid Land Stud. 16, 139–147. Veste, M., Staudinger, M., Küppers, M., 2008. Spatial and temporal variability of soil water in drylands: plant water potential as a diagnostic tool. For. Stud. China 10, 74–80. Yair, A., Almog, R., Veste, M., 2011. Differential hydrological response of biological topsoil crusts along a rainfall gradient in a sandy arid area: Northern Negev desert, Israel. Catena 87, 326–333. Zaady, E., Katra, I., Yizhaq, H., Kinast, S., Ashkenazy, Y., 2014. Inferring the impact of rainfall gradient on biocrusts' developmental stage and thus on soil physical structures in sand dunes. Aeolian Res. 13, 81–89. Zhang, Y., Aradottir, A., Serpe, M., Boeken, B., 2016. Interactions of biological soil crusts with vascular plants. In: Weber, B., Büdel, B., Belnap, J. (Eds.), Biological Soil Crusts: an Organizing Principle in Drylands. Springer, Cham, Switzerland, pp. 385–406.

Johnson, S.L., Kuske, C.R., Carney, T.D., Housman, D.C., Gallegos‐Graves, L.V., Belnap, J., 2012. Increased temperature and altered summer precipitation have differential effects on biological soil crusts in a dryland ecosystem. Glob. Chang. Biol. 18, 2583–2593. Kappen, L., Valladares, F., 2007. Opportunistic growth and desiccation tolerance: the ecological success of poikilohydrous autotrophs. In: Pugnaire, F., Valladares, F. (Eds.), Functional Plant Ecology. Taylor and Francis, New York, pp. 7–48. Kidron, G., Tal, S., 2012. The effect of biocrusts on evaporation from sand dunes in the Negev Desert. Geoderma 179, 104–112. Kidron, G., Herrnstadt, I., Barzilay, E., 2002. The role of dew as a moisture source for sand microbiotic crusts in the Negev Desert, Israel. J. Arid Environ. 52, 517–533. Kidron, G., Vonshak, A., Abeliovich, A., 2008. Recovery rates of microbiotic crusts within a dune ecosystem in the Negev desert. Geomorphology 100, 444–452. Kidron, G., Curtis Monger, H., Vonshak, A., Conrod, W., 2012. Contrasting effects of microbiotic crusts on runoff in desert surfaces. Geomorphology 139, 484–494. Kikvidze, Z., Callaway, R., 2009. Ecological facilitation may drive major evolutionary transitions. Bioscience 59, 399–404. Kranner, I., Beckett, R., Hochman, A., Nash, T., 2008. Desiccation-tolerance in lichens: a review. Bryologist 576–593. Lan, S., Wu, L., Zhang, D., Hu, C., 2014. Desiccation provides photosynthetic protection for crust cyanobacteria Microcoleus vaginatus from high temperature. Physiol. Plant. 152, 345–354. Lange, O., 2003. Photosynthetic productivity of the epilithic lichen Lecanora muralis: long-term field monitoring of CO2 exchange and its physiological interpretation II. Diel and seasonal patterns of net photosynthesis and respiration. Flora 198, 277–292. Liancourt, P., Spence, L., Song, D., Lkhagva, A., Sharkhuu, A., Boldgiv, B., Brent, R., Helliker, P., Petraitis, B., Brenda, B., Casper, B., 2013. Plant response to climate change varies with topography, interactions with neighbors, and ecotype. Ecology 94, 444–453. Lortie, C., Callaway, R., 2006. Re-analysis of meta-analysis: support for the stress-gradient hypothesis. J. Ecol. 94, 7–16. Maestre, F., 2003. Variaciones en el patrón espacial a pequeña escala de los componentes de la costra biológica en un ecosistema Mediterráneo semiárido. Rev. Chil. Hist. Nat. 76, 35–46. Maestre, F., Cortina, J., 2002. Spatial patterns of surface soil properties and vegetation in a Mediterranean semi-arid steppe. Plant Soil 241, 279–291. Maestre, F., Cortina, J., 2004. Do positive interactions increase with abiotic stress? A test from a semi-arid steppe. Proc. R. Soc. Ser. B: Biol. Sci. 271, S331–S333. Maestre, F., Quero, J., 2008. Análisis espacial mediante índices de distancia (SADIE). In: Maestre, F., Escudero, A., Bonet, A. (Eds.), Introducción al análisis espacial de datos en ecología y ciencias ambientales: métodos y aplicaciones. Dykinson, S.L., Madrid, pp. 129–182. Maestre, F., Martínez, I., Escolar, C., Escudero, A., 2009. On the relationship between abiotic stress and co-occurrence patterns: an assessment at the community level using soil lichen communities and multiple stress gradients. Oikos 118, 1015–1022. Maestre, F., Bowker, M., Escolar, C., Puche, M., Soliveres, S., Maltez-Mouro, S., GarcíaPalacios, P., Castillo-Monroy, P., Martínez, I., Escudero, A., 2010. Do biotic interactions modulate ecosystem functioning along stress gradients? Insights from semi-arid plant and biological soil crust communities. Philos. Trans. R. Soc.: Biol. Sci. 365, 2057–2070. Martens, S., Breshears, D., Meyer, C., Barnes, F., 1997. Scales of aboveground and belowground competition in a semi-arid woodland detected from spatial pattern. J. Veg. Sci. 8, 655–664. Martínez Carretero, E., 2013. La Diagonal Árida Argentina: entidad bioclimática. In: Pérez, D., Rovere, E., Rodriguez Araujo, E. (Eds.), Restauración ecológica en la diagonal árida de la Argentina. Universidad Nacional del Comahue, Neuquén, pp. 14–31. Memmott, J., Fowler, S., Hill, R., 1998. The effect of release size on the probability of establishment of biological control agents: gorse thrips (Sericothrips staphylinus) released against gorse (Ulex europaeus) in New Zealand. Biocontrol Sci. Technol. 8,

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