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Soil Biology & Biochemistry 46 (2012) 33e40

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Soil Biology & Biochemistry

journal homepage: www.elsevier .com/locate/soi lb io

The role of the exopolysaccharides in enhancing hydraulic conductivity ofbiological soil crusts

Federico Rossi a, Ruth M. Potrafka b, Ferran Garcia Pichel b, Roberto De Philippis a,*

aDepartment of Agricultural Biotechnology, University of Florence, Piazzale delle Cascine 24, 50144 Firenze, Italyb School of Life Sciences, Arizona State University, Tempe, AZ 85287-4501, USA

a r t i c l e i n f o

Article history:Received 23 June 2011Received in revised form6 September 2011Accepted 23 October 2011Available online 29 November 2011

Keywords:Biological soil crustsNorth American desertsExopolysaccharidesHydraulic conductivitySoil textureMicrobial community

* Corresponding author. Tel.: þ39 055 3288284; faE-mail address: roberto.dephilippis@unifi.it (R. De

0038-0717/$ e see front matter � 2011 Elsevier Ltd.doi:10.1016/j.soilbio.2011.10.016

a b s t r a c t

Biological soil crusts (BSCs) are highly specialized topsoil microbial communities commonly found in aridand semiarid environments, permeated by a polymeric matrix of polysaccharides. BSCs can in principleinfluence edaphic properties such as texture, pore formation and water retention, which in turn deter-mine water distribution and biological activity in dry lands. This paper investigates the influence of bioticand abiotic factors on BSC hydraulic conductivity, a parameter gauging the ease with which water canmove through the pore spaces. Texture, phototroph abundance, microbial composition, and extracellularcarbohydrate content were considered as potentially relevant parameters in a correlational study of BSCsamples that spanned 1.5 orders of magnitude in hydraulic conductivity. A newly developed,non-destructive extraction method enabled us to directly quantify the specific role of extracellularpolysaccharides on soil permeability on a variety of samples. Hydraulic conductivity showed a strongestcorrelation with texture (positive with sand content, negative with silt and clay). A weaker negativecorrelation with carbohydrate content, especially with polysaccharides having a molecular weight< 100 kDa, was also detected. In multiple regression analyses texture (silt content) was sufficient toexplain most of the variation in hydraulic conductivity However, experimental removal of polymericcarbohydrates, resulted invariably in a substantial decrease in hydraulic conductivity for any givensample (between 1.7 and 3.3 fold). Our results suggest that while soil texture determines overallhydraulic conductivity in BSCs, the presence of exopolysaccharides can significantly enhance it, likely byconferring a spongy structure to a BSC thus increasing the number of waterways within it.

� 2011 Elsevier Ltd. All rights reserved.

1. Introduction

Water movement is a critical process in the shaping of aridlandscapes, where, as a consequence of thewater retaining capacityof dry soils, nutrient-poor and nutrient-rich patches characterizedby large differences in biological activity typically alternate ina mosaic pattern (Boeken and Shachak, 1994; Boeken et al., 1995).This patchy distribution of both moisture and trophic resources,characteristic of arid and semiarid environments, and encompassedin the concept of “fertility islands”, can in some instances reflect thedistribution between hydrological run-off and sink areas, charac-terized by low and high water infiltration rates, respectively (Yair,1987). Water infiltration depends on a large variety of factors,some of which are intrinsic to the soil, ranging from cracking,microtopography, and sealing, to particle size and organic matterdistribution (Warren, 2003a, b).

x: þ39 055 3288272.Philippis).

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One of the potentially important factors is the presence ofsurface crusts, which may originate as evaporitic or sedimentarydeposits, or as a consequence of rain-mediated disintegration ofsoil aggregates (Hillel, 1998). Such physico-chemical surface crustscan severely diminish water infiltration. Biological soil crusts(BSCs), organo-sedimentary topsoil microbial biofilms that developin interspaces between plants (Belnap and Lange, 2003;Garcia-Pichel, 2002), are widely distributed in arid and semiaridecosystems, and have also been studied for decades with respect totheir effect on soil hydrological properties. The case of BSCs is muchmore complex. While in some cases biological crusting of soil isassociated with a decrease in water infiltration rate (Bisdom et al.,1993; Brotherson and Rushforth, 1983; Loope and Gifford, 1972;Romkens et al., 1990; Warren, 2003a, b) or to an increase in run-offyields (Kidron et al., 2003), in others studies the opposite effect isreported (Belnap et al., 2001; Greene and Tongway, 1989; Seghieriet al., 1997). In studies carried out in Australia, for instance,BSC-covered soils displayed reduced infiltration in comparisonwith bare soil in sandy-loam sites (Graetz and Tongway, 1986),while in degraded massive red earth soils, the crusts enhanced

F. Rossi et al. / Soil Biology & Biochemistry 46 (2012) 33e4034

water penetration (Greene and Tongway, 1989). The end resultseems to reflect the cumulative, perhaps even interacting, effects ofmany factors that may range from crust type and maturity, bio-logical composition, moisture status, soil texture and intensity ofthe rainfall events. It seems that in order to understand thehydrological role of BSCs some of these factors should be studiedindependently.

Extracellular Polymeric Substances (EPS) of microbial origin arecommonly called upon as important for water movement in BSCcovered soils (Belnap et al., 2001), as it has been experimentallyproven for soil columns (Baveye et al., 1998). It has been postulatedthat EPS reduce infiltration due to their capacity to clog soil pores(Campbell, 1979; Durrell and Shields, 1961; Kidron et al., 1999),especially in well-developed BSCs of sandy soils. Nevertheless,other authors remind us that polysaccharides can positively affectsoil porosity, increasing the number of micropores, which areknown to promote water infiltration (Greene, 1992; Eldridge,2003). Finally, EPS can trap airborne particles, leading to theaccretion of new sand and clay layers that may, on the one hand,increase the sorptivity of the soil helping water infiltration, butmight decrease overall soil porosity (Belnap, 2006). Direct experi-mental assessment the role played by this polysaccharidic matrixare few and not definitive (Malam Issa et al., 2009; Fischer et al.,2010).

In order to define the actual role of the polysaccharidic exudatesin modifying the hydrological processes in BSCs, we evaluated therelationships between the presence and amount of exopoly-saccharides and the hydraulic conductivity in a variety of intactBSC-covered soils of varying texture, microbial composition andgeographic origin. We then evaluated the effect of non-sacrificialEPS extraction on hydraulic conductivity of BSCs.

2. Materials and methods

2.1. Sampling

BSC samples were collected from five geographically separatedsites. North from Soda Lake (NSD; 35�150 06.600 N, 115� 580 3800 W)and Hayden-Globe Road (HGR; 35� 020 10.800 N, 115� 340 3100 W)sites were in the Mojave Desert. The Sunday Churt site (SCS; 38�

380 01.300 N, 109� 380 20.200 W) was in the Colorado Plateau.TheYuma/Dateland Site (YDS; 32� 450 6.400 N, 113� 390 4.100 W) wasin the Sonoran Desert and Jornada Range Road (JRR; 32� 310 58.900

N, 106� 430 41.500 W) site belongs to the Chihuauan Desert. We usedfour samples from YDS (numbered 704, 707, 708 and 710); two(marked 1088 and 1089) taken from SCS, two (905 and 883) fromHGR and one (789) from JRR. Samples were collected using stan-dard plastic Petri dishes, as previously described (Nagy et al.,2005), and packed with soft paper to avoid cracking, coveredwith Petri dish covers and taped closed. Prior to all the experi-ments, samples were dried at 31e33 �C overnight to remove anymoisture, and then stored in the dark.

2.2. Determination of microbial community composition by 16SrRNA gene tagged pyrosequencing

DNA was extracted from BSC samples using the UltraClean SoilDNA Extraction Kit (MoBio Laboratories, Inc., Carlsbad, CA).Bar-coded bacterial primerswith Roche 454 FLX adapterswere usedto amplify the V4 variable region (Claesson et al., 2009) of the 16SrDNA gene from template community DNA. These primers yieldedan amplicon of approximately 240 bp in length. The forward primer,V4F was 50-AYTGGGYDTAAAGNG-30. Equimolar mixtures of 4reverse primers were used. Reverse primers were: V4R,50-TACCRGGGTHTCTAATCC-30, V4R2, 50- TACCAGAGTATCTAATTC-30,

and, V4R3,50- CTACDSRGGTMTCTAATC-30, and V4R4,50-TACNVGG-GTATCTAATCC-30. Forward and reverse primers targeted positionsw560 and w800 by standard Escherichia coli numbering. The PCRconditionswere as described byBates andGarcia-Pichel (2009)with50 pmol of each primer, 2.5 units ExTaq polymerase and 10 ng ofcommunity DNA template. After initial denaturing, 30 cycles weredone at 94 �C for 1 min, 50 �C for 1 min, and 72 �C for 2 min, withafinal extensionat 72 �C for 5min. ThePCRproductswerequantifiedand quality checked in a 1% agarose gel, then purified using theQiaQuick PCR purification kit (Qiagen Inc. USA, Valencia, CA, cat.#28106), and commercially pyrosequencedand parsed by sampleaccording to the individual barcodes, to yield w7000e21,000sequences per sample. We used mothur (Schloss et al., 2009) pyro-sequencing analysis software to trim low-quality sequences fromthe sample files. The Pyrosequencing Pipeline Alignment and Clas-sification tools at Michigan State University’s Ribosomal DatabaseProject (RDP) website, Release 10 (Cole et al., 2009) were used toalign sequences and make taxonomic assignments (RDP NaiveBayesian rDNA Classifier, version 2.2) based on current taxonomy inBergey’s Manual of Systematic Bacteriology.

2.3. Soil texture determination

For each soil sample (both untreated and EDTA-extracted, seebelow) three to four 1-cm3subsamples were analyzed for grain size.These subsamples were disaggregated by hand until no aggregateswere seen, then heated at 70 �C for two days to remove moisture,and weighed. They were then incinerated in a muffle furnace at500 �C for 6 h, to remove organic matter, and weighed again.Weight differences were used to estimate the total content oforganic matter (Dean, 1974). The samples were then sealed insterile 1.5 mL plastic Eppendorf tubes until measurement. Grainsize measurements were made in triplicate for each subsampleusing a Malvern Mastersizer 2000 grain size analyzer (MalvernInstruments, Ltd., Malvern, UK) at the Environmental StudiesLaboratory at the University of Arizona. Cut off diameters were2 mm for clay, 2e53 mm for silt, and 53e2000 mm for sand. Eachsubsample was sonicated for 2 min before analysis. Texture classeswere assigned according to United States Department of Agricul-ture (USDA) nomenclature (USDA Soil Survey Manual, 1993), usingthe soil bulk density triangle, accounting for the percents of the soilseparates.

2.4. Chlorophyll a content

Chlorophyll a was extracted from pre-weighed samples bysubmersion in 80% acetone, in the dark, at 4 �C for at least 24 h, Cellsand mineral particles were pelleted by centrifugation at 2600g, andthe absorbance of the supernatant was measured at 663 nm usinga Cary 50 Spectrophotometer (Varian, USA). Absorbance at 750 nmwas subtracted to correct for possible residual scattering. Quanti-ties of Chlorophyll a were obtained using the specific extinctioncoefficient of McKinney (1941).

2.5. Carbohydrate content determination

To determine total and ethanol-precipitable (i.e. high MW)carbohydrate content, soils were gently homogenized and extrac-ted with a 0.1M EDTA aqueous solution following the methoddescribed by Underwood et al. (1995). This extracts both extracel-lular loosely bound (soluble) polysaccharides and tightly boundpolysaccharides. High molecular weight (HMW) polysaccharideswere then precipitated by treating with 70% (v/v) ethanol (finalconcentration) for 8 h at 4 �C in the dark. The supernatant wasdiscarded and the precipitated sugars re-suspended in deionized

F. Rossi et al. / Soil Biology & Biochemistry 46 (2012) 33e40 35

water. Total carbohydrate and ethanol-precipitable carbohydratecontents in solution were estimated using the phenol-sulfuric acidassay (Dubois et al., 1956).

2.6. Hydraulic conductivity measurements

Hydraulic conductivity gauges the rate of water movementthrough the soil and accounts for the soil’s ability to transport waterwhen subject to a hydraulic gradient. Hydraulic conductivity wasmeasured in laboratory conditions on dried samples in Petri dishesusing a Mini Disk Tension Infiltrometer (Decagon Services, Inc.,Pullman, WA) with a suction range from 0.5 to 6 cm and a radiusof2.2 cm. The infiltrometer was placed on top of the sample and theheight of the column of water was measured at equal intervals oftime, as the water penetrated the soil, using the graduated cylinderof the instrument. Hydraulic conductivity was finally calculatedusing the method of Zhang (1997) for dry soils and using vanGenuchten parameters related to soil texture obtained from Carseland Parrish (1988). For every sample, hydraulic conductivity wasmeasured at least in triplicate, drying samples before everymeasurement at 31e33 �C for 12 h.

2.7. Non-destructive extraction of the polysaccharidic matrix

Four pairs of equidistant holes (1 mm diameter, approximately)were pierced through the peripheral section of the bottom of thePetri dish that held the samples, using a heated metal tip (Fig. 1a).The sample-containing the dish was then placed on top of a secondplastic Petri dish and the two dishes were sealed together withsilicone. The sample chamber was thus connected with an airtightlower chamber through the pre-formed holes (Fig. 1b). Twenty mlof a 0.1M EDTA solution was added to the sample chamber, whichwas covered to avoid evaporation and incubated for 3 h in the dark.During this period of time, the EDTA solution remained in the upper

Fig. 1. (a) Top view of the Petri dish containing the BSC samples showing the distri-bution of pierced holes on its floor. b) Cross-sectional view of the two-chamberexperimental system used for EPS extraction, indicating the sample-containing dishand the lower dish with the suction hole; thick lines indicate silicone sealed area.

chamber due to soil suction. After 3 h, a 1 mm diameter hole waspierced with a heated metal tip on the side of the lower chamber,and a �400 to �600 MPa vacuum line attached to this lower hole.This forced the EDTA solution to flow through the soil, moving fromthe upper to the lower chamber through the holes, and collecting itbefore being suctioned away. Subsequently, two water washes ofthe BSC sample in the upper chamber were performed in order toremove any residual EDTA solution, while the vacuum was still on.Samples were then dried overnight at 31e33 �C to remove theremaining moisture.

3. Results

3.1. Grain size analysis and microbial community composition

From the grain size analysis, three classes of textures wereidentified (Table 1). The BSC soil samples were found to be mainlycomposed of silt and sand, with clay fractions ranging from 0.2 to3.43 %. The samples YDS 704, 707, 708 and 710, from the SonoranDesert, the sample JJR 789, from the Chihuauan Desert, and thesample HGR 883, from the Mojave desert, showed similarpercentages of sand and silt (around 50%), while sand waspredominant in the samples SCS 1088 and 1089, from the ColoradoPlateau, (77e79% sand and 22% silt) and in sample HGR 905, fromthe Mojave desert (83% sand and 16,5% silt). 16S DNA taggedpyrosequencing data analyses revealed the presence of a variedmicrobial community in all samples, where Cyanobacteria, Pro-teobacteria and Acidobacteria were major phyla, though the pres-ence of Verrucomicrobia and Actinobacteria was also significant(Fig. 2). In all sites, Proteobacteria were represented mostly bya-proteobacteria while the other subgroups were not as common.In most sites (Sonoran, Chihuauan and Colorado Plateau sites),cyanobacteria turned out to be the most abundant taxonomicgroup present (35e37% abundance), while Proteobacteria andAcidobacteria represented a smaller fraction (13%e20%), with theexception of site JRR 789, where Acidobacteria represented 28% andProteobacteria only 10% of the taxa. TheMojave desert sites showeda peculiar abundance distribution compared to the rest of thesampling sites, in that a-proteobacteria (32e36%) displaced cya-nobacteria to a secondary role (10e19%). Thus, significant compo-sitional differences in community structure could be detectedamong the samples.

3.2. Hydraulic conductivity and texture

Hydraulic conductivity varied significantly among samples aswell (Table 1), spanning almost 1.5 orders of magnitude froma minimum of 0.4 to a maximum of 18.4 � 10�4 cm s�1. Hydraulicconductivity correlated positively with the sand content of soils(R2 ¼ 0.99, P < 0.01; Fig. 3a), and negatively with the percentage of

Table 1Texture and hydraulic conductivity (as average � standard deviation with n ¼ 3independent replicate determinations) of the various biological soil crust samples.

Sample Soil texture Hydraulicconductivity, �10�4 cm s�1

YDS 704 Sandy loam 4.55 � 1.40YDS 707 Silt loam 0.62 � 0.20YDS 708 Silt loam 0.40 � 0.10YDS 710 Silt loam 0.84 � 0.15JRR 789 Sandy loam 1.63 � 0.43HGR 883 Sandy loam 6.40 � 0.39NSD 905 Loamy sand 18.40 � 0.76SCS 1088 Loamy sand 10.83 � 3.47SCS 1089 Loamy sand 13.90 � 6.50

Fig. 2. Relative abundance of bacterial phyla in BSCs investigated (framed designations), according to BLAST assignments of 16S rRNA gene fragments obtained from pyrose-quencing. White wedges represent fraction of unassignable sequences. Major phyla are indicated by abbreviations, in addition to the color coding according to the legend. cy:cyanobacteria; ac: acidobacteria; vc: verrucomicrobia; a: alpha-proteobacteria; at: actinobacteria.

Fig. 3. Correlations of BSC hydraulic conductivity with soil texture (panels a-c) and extracellular carbohydrates (panels d-f). Reported values are the means of at least threereplicates.

F. Rossi et al. / Soil Biology & Biochemistry 46 (2012) 33e4036

Fig. 4. Correlations between Chlorophyll a content and extracellular carbohydrates interms of total carbohydrates (panel a), HMW carbohydrates (panel a), SMW carbo-hydrates (panel b) and between Chlorophyll a content and hydraulic conductivity(panel c). Reported values are the means of at least three replicates.

F. Rossi et al. / Soil Biology & Biochemistry 46 (2012) 33e40 37

silt (R2¼ 0.93, P< 0.01; Fig. 3b). Although the percentage of clay didnot vary much among samples, clay content was also negativelycorrelated with hydraulic conductivity (R2 ¼ 0.70, P< 0.01; Fig. 3c).

3.3. Hydraulic conductivity and biotic parameters

Carbohydrate content of BSCs was determined both as totalextracellular carbohydrates and as ethanol-precipitable carbohy-drates. The latter represents sugars with high molecular weight(HMW) (�100 kD; Decho, 1990; de Brouwer and Stal, 2001). Smallmolecular weight (SMW) sugar content (�100 kD) was calculatedsubtracting the content of ethanol-precipitable carbohydrates fromthe total content of carbohydrates. High molecular weight (HMW)

Table 2Hydraulic conductivity and carbohydrate content in BSCs before and after the non-dconductivity; TE-carbohydrates, total extractable carbohydrates; EP-carbohydrates, ethresults of at least three triplicates and SD are reported in the table.

Sample HC beforetreatment,�10�4 cm s�1

HC aftertreatment,�10�4 cm s�1

TE-carbohydrates beforetreatment, mg g�1

TEaf

YDS 704 4.55 � 1.40 1.00 � 0.01 0.62 � 0.01 0.YDS 710 0.84 � 0.15 0.49 � 0.15 1.51 � 0.29 1.JRR 789 1.63 � 0.43 0.50 � 0.30 1.00 � 0.01 0.NSD 905 18.40 � 0.76 6.78 � 0.10 0.21 � 0.01 bdSCS 1089 13.90 � 6.50 4.80 � 2.80 0.75 � 0.01 0.

carbohydrates always constituted a significant fraction of extra-cellular total sugars, ranging from 25 to 73%. No significant corre-lation was found between HMW carbohydrate content andhydraulic conductivity (R2 ¼ 0.13, P ¼ 0.31; Fig. 3d). Hydraulicconductivity showed a better correlation with total extracellularcarbohydrates (R2 ¼ 0.58, P ¼ 0.02; Fig. 3e) and even strongernegative correlation with SMW carbohydrates (R2 ¼ 0.72, P < 0.01;Fig. 3f). No significant correlation was observed between chloro-phyll a, which is an indicator of the phototrophic biomass presentin the soils, and hydraulic conductivity (Fig. 4c). Chlorophylla correlated well with HMW carbohydrates (R2 ¼ 0.71, P < 0.01),but only weakly with the total carbohydrate content (R2 ¼ 0.25,P ¼ 0.16). SMW carbohydrate content showed no correlation withChlorophyll a (R2 ¼ 0.05, P ¼ 0.54; Fig. 4b).

3.4. Statistical regression models for the hydraulic conductivity

Backward multiple regression analyses were run wherehydraulic conductivity was the single dependent variable regressedagainst all other variables. A regression model excluding claycontent had the highest fit (R2

adj ¼ 0.998; F ¼ 536). A modelengaging silt content, and Chlorophyll a content, explained stillmost of the variability (R2

adj ¼ 0.938; F ¼ 62). A model with a singletextural regressor (silt content) was still a quite robust(R2

adj ¼ 0.917; F ¼ 89).

3.5. Effects of extraction of the polysaccharidic matrix from BSCs

We investigated experimentally the role of EPS in five samples(YDS 704, YDS 710, JRR 789, SCS 1089 and HGR 905). The extra-cellular polysaccharidic matrix was removed using a methodexpressly developed to maintain the structural integrity of thecrusts, so that hydraulic conductivity could bemeasured before andafter removal. The method was effective for all the five samples,reducing the carbohydrate content per gram of soil in five cases outof five (Table 2). Indeed, the content of both total sugars and HMWcarbohydrates decreased after the extraction, showing that at leasta fraction the polysaccharidic matrix was removed. The efficiencyin the removal varied from sample to sample, the lowest efficiencybeing achieved in silt loam sample YDS 710, which maintainedabout 60% of its total carbohydrate content after the extraction. Thetreatment resulted in a significant reduction in hydraulic conduc-tivity in all samples, ranging from 1.7 to 4.7 fold. It is noteworthythat the first visible effect of EPS removal was a conspicuous changein albedo. While untreated BSCs presented typically homogenouslylight brown appearance, overall albedowas noticeably decreased inall cases after the extraction procedure, with crust displayinga patchy, darker coloration thereafter (Fig. 5).

estructive extraction of the polysaccharidic matrix. Abbreviations: HC, hydraulicanol-precipitable carbohydrates; bdl, below detection limit. Values shown are the

-carbohydratester treatment. mg g�1

EP-carbohydrates beforetreatment, mg g�1

EP-carbohydratesafter treatment, mg g�1

03 � 0.02 0.17 � 0.01 bdl20 � 0.01 0.42 � 0.01 0.32 � 0.0561 � 0.14 0.33 � 0.01 0.31 � 0.04l 0.06 � 0.02 bdl25 � 0.05 0.55 � 0.01 0.02 � 0.01

F. Rossi et al. / Soil Biology & Biochemistry 46 (2012) 33e4038

4. Discussion

The role of biological soil crusts in the hydrological cycles ofdrylands remains controversial. The apparent contradictions in theresults reported in the literature reveal the impossibility of defininga simple, precise and unique role for BSCs. Factors, both biotic andabiotic, that concurrently affect water penetration and distributionand that may vary in importance among different BSCs, must beunderstood in isolation first. We focused our efforts on probing therole of EPS as a determinant of BSC hydrological behavior. For thiswe carried out a dual investigation that involved correlation anal-yses on the one hand, and specific manipulation of EPS level on theother. For the former, we chose a set of samples that was diverse.This was deemed important, in that much of the previous contro-versial results were based on studies of a single type of BSC thatpurposefully avoided much diversity. Our sample set was not onlydiverse in geographic origin, but in a variety of structural parame-ters. Sand content varied among them by two-fold, and the contentof fines by approximately three-fold. The level of colonization bymicrobial phototrophs, gauged by Chlorophyll a content, varied byan order ofmagnitude, as did the total content of carbohydrates. Thecontent of HMW carbohydrates varied by nearly as much. In somesamples, the Cyanobacteriawere the dominant phylum, but in otherthey lost preminence to the a-proteobacteria; many other differ-ences in microbial community composition were detected amongthe samples. Thus, we consider our set diverse enough to potentiallygauge correlations with hydraulic conductivity in a robust manner,particularly since hydraulic conductivity in itself varied by almost50-fold within the set. In fact, the level of colonization by photo-trophic microorganisms (i.e., Chl a content) correlated with HMWcarbohydrates, namely exopolysaccharides. This tight couplingstrongly supports the suspected key role played by cyanobacteria

Fig. 5. Albedo of BSCs before and after the removal of EPS. Upper panels: sample 704 beextraction.

living in the crusts in synthesizing the polysaccharidic material thatconnects binds microorganisms and soil particles together.

Our survey of t hydraulic conductivity in BSCs strongly supportsthe notion that soil texture remains the paramount factorcontrolling the overall speed of water infiltration, whereby sandcontent correlates positively with faster water flow, while thecontent of fines shows negative correlations with it. In this sense,BSCs do not depart from the general behavior of soils and sedi-ments (Brady and Weil, 1996). Multiple regression models clearlypointed to this fact, with the addition of biotic factors improvingthe predictability only marginally. None of the biotic factorsselected, alone or in combination, could explain the variability inhydraulic conductivity at the same statistical significance as soiltexture.

Indeed, unlike texture, phototrophic biomass, indirectly quan-tified through the determination of chlorophyll a content, was nota good predictor of hydraulic conductivity in our surveys. However,total carbohydrate content, possibly a proxy for microbial biomass,showed a more significant negative correlation with hydraulicconductivity. If this is the correct interpretation, then BSCs do notbehave much differently to other soil systems where unusualaccumulations of microbial biomass can lead to significantdecreases in hydraulic conductivity (Vandevivere andBaveye,1992).Clearly, however, and contrary to the conventionalwisdom, the totalamount of HMW (i.e. � 100 kDa) EPS, was only very weakly corre-lated to the variability in hydraulic conductivity. If EPS has an effecton water infiltration through pore clogging by virtue of theirotherwise proven ability to hold up and retainwater (by as much as10 times its ownweight; Mazor et al., 1996; Malam Issa et al., 2009;Fischer et al., 2010), it is one that plays a secondary role to soiltexture and possibly cellular mass. Nonetheless, the content of EPSwith a molecular weight smaller than 100 kDa (SMW) correlated

fore (a) and after (a’) extraction. Lower panels: sample 710 before (b) and after (b’)

F. Rossi et al. / Soil Biology & Biochemistry 46 (2012) 33e40 39

with hydraulic conductivity, suggesting a somewhat possible directrole of this smaller fraction in hydraulic conductivity variations.

The correlation of HMW with Chl a was found to be significant,suggesting that phototrophic microorganisms are likely the mostrelevant producers of this HMW EPS fraction. In this connection, itis worth stressing that molecular weights ranging from 100 to2000 kDa have been reported for the few cyanobacterial EPS so farcharacterized for their MW (Pereira et al., 2009). On the other hand,the poor correlation between SMW carbohydrates and Chla suggests that this fraction is probably influenced by the largechemoheterotrophic microbial community present in the crusts.,This is consistent with the notion, that part of the SMW carbohy-drates found in BSCs derive from the hydrolytic activity of thechemoheterotrophs on the HMW EPS released in the soil byphototrophs.

We developed the non-destructive EPS extraction method inthe hope of detecting and quantifying the magnitude of anyincreases in conductivity associated with removal of EPS withoutthe masking effect of other parameters. Not only did we not detectany such unclogging, but a very significant, reproducible reductionof the hydraulic conductivity in all the samples tested. In generalterms, a removal of a given fraction of the total extracellularcarbohydrate resulted in a reduction of flow of roughly about thesame magnitude (Table 2). How the presence of EPS can enhancethe flow of water to such an extent is not immediately obvious.Since hydraulic conductivity depends on the characteristics of thesolid matrix, including shape, number and size distribution of thepores (Bear, 1972), a possible change in these factors due to theextraction of the polysaccharides must be considered. Indeed,Malam Issa et al. (2009) report that cyanobacterial exopoly-saccharidic exudates increase the number of micropores withinBSC and affect their geometry. It is then perhaps possible thatremoving EPS induced significantly altered micropore numberand/or shape, a phenomenon that has been correlated toa decrease in the hydraulic conductivity (Belnap, 2006). Moreover,it is worth mentioning that polysaccharides can induce theformation of surface cracking (Danin et al., 1998; Kidron et al.,1999) and otherwise shape the architecture of surface crusts(Beraldi-Campesi and Garcia-Pichel, 2010). It appeared to us thatthe removal of polysaccharides resulted in a loss of sponginess ofthe wet crusts, and a “caking up” or compaction of the soil,consistent with a collapse of the spatial organization of a BSC poresystem held together by EPS. These hypotheses are supported bythe significant decreases in albedo that came about without netpigment increases: a collapse of the large pores should result ina much more homogenous medium for light to travel through,decreasing multiple scattering, and the total amount or back-scattered light (radiance reflectance; see for example Garcia-Picheland Belnap, 2003, for an account of the light fields in soil crusts),effectively darkening the crusts to the sight.

From the data reported in this study, it is possible to concludethat the amount of EPS is a less powerful predictor of hydraulicconductivity in crusts compared to textural parameters. However,for any given type of soil, EPS can play a significant role inenhancing BSC conductivity, likely because of their ability to imparta “spongy” texture to these organo-sedimentary assemblages. EPSthus plays a role in forming (soil) structure and increasing thenumber of viablewaterways within BSCs, and likely helps conditionthe microenvironment for optimal function.

Acknowledgments

F.R. was hosted at Arizona State University, for a 3 months stage,thanks to a fellowship given by CIB (Italian Consortium forBiotechnologies). The research was partially supported by a grant

from the US NRI (USDA) Soils Program to FGP. Authors gratefullyacknowledge Yevgenyi Marusenko for his help with statisticalanalyses.

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