Submitted 9 May 2016Accepted 25 July 2016Published 18 August 2016

Corresponding authorFelipe Garciacutea-Olivafgarciaciecounammx

Academic editorCoen Ritsema

Additional Information andDeclarations can be found onpage 17

DOI 107717peerj2365

Copyright2016 Hernaacutendez-Becerra et al

Distributed underCreative Commons CC-BY 40

OPEN ACCESS

Agricultural land-use change in aMexican oligotrophic desert depletesecosystem stabilityNatali Hernaacutendez-Becerra1 Yunuen Tapia-Torres2 Ofelia Beltraacuten-Paz1Jazmiacuten Blaz3 Valeria Souza3 and Felipe Garciacutea-Oliva1

1 Laboratorio de biogeoquiacutemica de suelos Instituto de Investigaciones en Ecosistemas y SustentabilidadUNAM Morelia Michoacaacuten Mexico

2 ENES Unidad Morelia Universidad Nacional Autoacutenoma de Meacutexico Morelia Michoacaacuten Mexico3 Instituto de Ecologiacutea Universidad Nacional Autoacutenoma de Meacutexico Mexico

ABSTRACTBackground Global demand for food has led to increased land-use change particularlyin dry land ecosystems which has caused several environmental problems due to thesoil degradation In the Cuatro Cienegas Basin (CCB) alfalfa production irrigated byflooding impacts strongly on the soilMethods In order to analyze the effect of such agricultural land-use change on soilnutrient dynamics and soil bacterial community composition this work examined anagricultural gradient within the CCB which was comprised of a native desert grasslanda plot currently cultivated with alfalfa and a former agricultural field that had beenabandoned for over 30 years For each site we analyzed C N and P dynamic fractionsthe activity of the enzyme phosphatase and the bacterial composition obtained using16S rRNA clone librariesResults The results showed that the cultivated site presented a greater availabilityof water and dissolved organic carbon these conditions promoted mineralizationprocesses mediated by heterotrophic microorganisms while the abandoned land waslimited by water and dissolved organic nitrogen The low amount of dissolved organicmatter promoted nitrification which is mediated by autotrophic microorganisms ThemicrobialN immobilization process and specific phosphatase activitywere both favoredin the native grassland As expected differences in bacterial taxonomical compositionwere observed among sites The abandoned site exhibited similar compositions thannative grassland while the cultivated site differedDiscussion The results suggest that the transformation of native grassland intoagricultural land induces drastic changes in soil nutrient dynamics as well as in thebacterial community However with the absence of agricultural practices some of thesoil characteristics analyzed slowly recovers their natural state

Subjects Biodiversity Ecology Ecosystem Science Soil ScienceKeywords Alfalfa Resilience Bacteria community Soil nutrients Microbial activityMedicago sativa L

INTRODUCTIONRising global food demand due to population growth has caused an increase in rates ofland-use change to agricultural production in dry ecosystems (Lepers et al 2005Reynolds et

How to cite this article Hernaacutendez-Becerra et al (2016) Agricultural land-use change in a Mexican oligotrophic desert depletes ecosys-tem stability PeerJ 4e2365 DOI 107717peerj2365

al 2007) This has led to several environmental problems including deforestation habitatfragmentation biodiversity reduction changes to global biogeochemical cycles waterand soil contamination and degradation (Reynolds et al 2007 Rey-Benayas amp Bullock2012) In these perturbed dry lands the main drivers of desertification are soil nutrientlosses caused mainly by erosion soil salinization and the reduction of soil water retentioncapacity through the deterioration of soil physical properties (DrsquoOdorico et al 2013) Thissoil degradation reduces agricultural productivity and the fields are eventually abandoned

Themain characteristics of intensive agriculture that affect soil properties is the reductionof organic matter inputs soil tillage fertilization and irrigation (McLauchlan 2006) It hasbeen reported that soil organic matter (SOM) is reduced by 16ndash77 as a consequenceof agriculture (Murty et al 2002) This is mainly through the decrease in organic matterinputs and the increase in soil organic decomposition because of increased tillage and soiltemperatures (Trasar-Cepeda et al 2008 Beheshti Raiesi amp Golchin 2012) The practice oftillage disrupts the physical properties of the soil affecting soil water and nutrient dynamics(Six Elliott amp Paustian 1999 Zeleke et al 2004 Bronick amp Lal 2005) Fertilization withnitrogen mainly in the form of ammonium promotes faster nitrification and the releaseof H+ ions into the soil solution thus lowering soil pH (Moore Klose amp Tabatabai 2000)and the continuous irrigation increases the leaching of salts through the soil profile(Raiesi 2004) However when agricultural fields are abandoned some salts accumulatein the topsoil promoting salinization a process that is favored in desert ecosystems(Rietz amp Haynes 2003 Pan et al 2012) Furthermore plant succession is slower in desertecosystems than in wet tropical ecosystems for example recovery of vegetation requiresat least 40 years in the former while in the latter it can be achieved in less than 10 years(Lesschen et al 2008Wang et al 2011)

Agriculture also has an effect on the composition of the soil microbial communityFor instance some changes in microbial composition have been reported as a result ofagricultural land-use in tropical (Waldrop Balser amp Firestone 2000) as well as desert (Dinget al 2013) andMediterranean ecosystems (Garcia-Orenes et al 2013) However the effecton soil microbial diversity is unclear some studies have described increases in biodiversity(Jangid et al 2008) while others have reported decreases (Lupwayi Rice amp Clayton 1998)Chaudhry et al (2012) found higher soil microbial diversity in agricultural fields managedwith organic rather than chemical fertilization These authors found that the compositionof the bacterial community in the organically fertilized soil was dominated by the phylaProteobacteria Bacteroidetes and Gemmatimonadetes while the groups Actinobacteriaand Acidobacteria were predominant in the chemically fertilized soil The dominantphyla in the organically fertilized soil have been associated with high nutrient availabilitywhereas the Acidobacteria have been related to nutrient-poor soils (Fierer Bradfordamp Jackson 2007) The effect of long-term agricultural management on soil microbialcommunities is similarly unclear in some studies even after 9 years of abandonmentthe soil microbial composition remains similar to that of the cultivated soil (Buckley ampSchmidt 2001) However an agricultural field abandoned for over 45 years presented asoil microbial community that was similar to one in soil with native vegetation cover(Buckle amp Schmidt 2003) These results demonstrate the need for further study in order

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 224

to understand the effect of succession of agriculture management upon the compositionof the soil microbial community

The worldwide area of degraded agriculture fields was estimated to be 12400000 km2

in 2007 (Rey-Benayas amp Bullock 2012) of which 20 corresponded to dry ecosystems(Lepers et al 2005 Reynolds et al 2007) In Mexico around 121 km2 and 45 km2 ofgrassland were converted to agriculture and abandoned lands respectively between 2005and 2010 (Colditz Llamas amp Ressl 2014) For this reason evaluation of the capacity forsoil restoration in the cultivated fields of dry lands is a priority for crop production andecosystem conservation This capacity can be evaluated in the context of ecosystem stabilitywhich has two main components resistance and resilience (Pimm 1984) The former isthe capacity of the ecosystem to face a disturbance without undergoing structural changeswhile the latter reflects the time required for the ecosystem to return to its pre-disturbancecondition (Pimm 1984) Orwin amp Wardle (2004) proposed indices for evaluating thesetwo attributes of soil stability which are accurate for providing a relative quantitativemeasurement when comparing soil conditions under perturbation The quantitativemeasure of soil stability allows evaluation of the magnitude of soil degradation and itscapability for restoration

In the Cuatro Cienegas basin (CCB) in Mexico alfalfa (Medicago sativa L) productionwith gravity irrigation involves flooding the fields with oasis water that is channeled throughopen canals for hundreds of km This practice unequivocally threatens the sustainabilityof the CCB wetland and degrades the soil and vegetation In order to analyze the effect ofsuch agricultural land-use on the soil nutrient dynamics (C N and P) and compositionof the soil bacterial community we examined an agricultural gradient within the CCBcomposed of three sites with the same soil type but under contrasting management anative desert grassland a plot with an alfalfa crop and a former agricultural field that hadbeen abandoned for over 30 years We predicted that the alfalfa production disrupts themechanisms of soil nutrient transformation and strongly affects the composition of thesoil bacteria To test these hypotheses we analyzed C N and P dynamic fractions and usedthis data to calculate the homeostasis of the microbial community The enzymatic activityof alkaline phosphatase was also quantified and bacterial composition was determinedthrough the use of 16S rRNA clone libraries

MATERIAL AND METHODSSite descriptionThis study was carried out in the Cuatro Cienegas basin (CCB 2650primeN and 1028primeW)at 740 masl in the Chihuahuan desert in Mexico The climate is seasonally aridwith an average annual temperature of 21 C and annual precipitation of 252 mm(httpsmncnagobmx) Jurassic-era gypsum is the dominant parent material on thewestern side of the basin while Jurassic-era limestone dominates on the eastern side (McKeeJones amp Long 1990) According to theWRB classification (2007) the predominant soils areGypsisol and Calcisol on the western and eastern sides of the basin respectively The soilwithin the CCB is characterized by low P concentrations (ranging between 70ndash200 microg gminus1)

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 324

These values are lower than the P values of other soils within the Chihuahuan desert(500ndash1000 microg gminus1 Tapia-Torres amp Garcia-Oliva 2013) The main vegetation typesare halophyte-grassland dominated by Sporobolus airoides (Poaceae) and desert scrubdominated by species from the Euphorbiaceae and Zygophyllaceae families (PerroniGarcia-Oliva amp Souza 2014) Agricultural activity in the CCB began in the early decadesof the 20th century but has increased in the last 30 years and it mainly consists of theproduction of alfalfa for cattle fodder Alfalfa (Medicago sativa L) is grown by flooding thefields and introducing large quantities of fertilizer In some years sorghum (Sorghum spp)is cultivated but the alfalfa cultivation dominates the agricultural surface (INEGI 2011)However these fields must eventually be abandoned due to degradation of the soil mainlythrough salinization

Field samplingSampling sites were located on the eastern side of the CCB An agricultural gradient wasestablished comprising three sites of shared soil type (Calcisol) but contrastingmanagementwas all located in flat areas native desert grassland a plot cultivated with alfalfa and a formeragricultural field that had been abandoned for over 30 years The native desert grasslandwas in the Pozas Azules reserve (2649prime30

primeprime

N and 1021prime27primeprime

W) where Sporobolus airoidesis the dominant plant species (Tapia-Torres et al 2015a) The cultivated alfalfa field waslocated in the Cuatro Cienegas ejido (2658prime47

primeprime

N and 10202prime13primeprime

W) and covered an areaof 27 ha with high fertilizer inputs and irrigation by flooding every month The plot wasfertilized withmonoammonium phosphate (11-52-00) dissolved in the water for irrigationThe water for irrigation had a pH value of 85 with a high electrical conductivity (150 mSmminus1) This alfalfa plot has been under cultivation for 20 consecutive years and the alfalfa isharvested every month Finally the abandoned field was also in the Cuatro Cienegas ejido(2658prime57

primeprime

N and 10201prime8primeprime

W) and presented minimum plant cover (less than 30 of thearea) Oscar Saacutenchez Liceaga Heacutector Castillo Gonzaacutelez the personnel of APFF CuatroCienegas (CONANP) and the people in charge of Rancho Pozas Azules (PRONATURA)gave us the permission to collect soil samples on their respective properties At each site a100times 50 m plot was delimited and then divided into 10 sections at a distance of 10 m apartA random sampling transect was then established in each section with topsoil samplestaken to a depth of 15 cm at ten sampling points (every five meters) in September 2011these samples were then mixed to form one composite sample In total 10 such compositesamples were taken in each plot Soil for biogeochemical and enzymatic activity analysiswas stored in black plastic bags and refrigerated at 4 C In order to characterize thebacterial community at each site 100 g of composite samples were immediately stored inliquid nitrogen until subsequent DNA extraction

Laboratory analysesSoil nutrient and enzymatic analysesSoil pH was measured in deionized water (12 wv) using a digital pH meter (Corning)and soil electrical conductivity was measured by conductivity meter (Hannan InstrumentsInc Houston USA) A subsample (100 g) was oven-dried at 75 C to constant weightfor soil moisture determination using the gravimetric method in order to adjust for water

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 424

content when expressing nutrient concentration on the basis of dry soil mass All C formsanalyzed in all samples were determined in a total carbon analyzer (UIC model CM5012Chicago USA) while the N and P forms analyzed were determined colorimetrically ina Bran-Luebbe Auto analyzer 3 (Norderstedt Germany) Prior to the total soil nutrientanalyses soil samples were dried and ground with a pestle and mortar Total carbon (TC)and inorganic carbon (IC) were determined by combustion and coulometric detection(Huffman 1977) Total organic carbon (OC) was calculated as the difference between TCand IC For total N (TN) and total P (TP) determination samples were acid digested withH2SO4 H2O2 K2SO4 and CuSO4 at 360 C Soil N was determined by the macro-Kjeldahlmethod (Bremmer 1996) while P was determined by the molybdate colorimetric methodfollowing ascorbic acid reduction (Murphy amp Riley 1962)

Available dissolved and microbial nutrient forms were extracted from field moistsoil samples Available inorganic N (NH+4 and NOminus3 ) was extracted from 10 g of freshsoil subsamples with 2M KCl followed by filtration through a Whatman No 1 paperfilter (Robertson et al 1999) and determined colorimetrically by the phenol-hypochloritemethod Available (inorganic) and labile (organic) P was determined by extraction with05M NaHCO3 at pH 85 according to Hedley sequential P fractionation (Tiessen amp Moir1993) and quantified as described above for orthophosphate

Dissolved nutrients were extracted with deionized water after shaking for 45 min andfiltering through a Millipore 0 42 00B5m filter (Jones amp Willett 2006) Prior to aciddigestion one aliquot of the filtrate was used to determine dissolved ammonium (DNH+4 )and inorganic P (IP) in deionized water extract Total dissolved nitrogen (TDN) wasdigested using the macro-Kjeldahl method Total dissolved P (TDP) was also acid digestedand determined by colorimetry Total dissolved carbon (TDC) was measured with anAuto Analyzer of carbon (TOC CM 5012) module for liquids (UIC-COULOMETRICS)Inorganic dissolved carbon (IDC) was determined in an acidification module CM5130Dissolved organic carbon (DOC) dissolved organic nitrogen (DON) and dissolved organicphosphorous (DOP) were calculated as the difference between total dissolved forms andinorganic dissolved forms

Microbial C (Cmic) N (Nmic) and P (Pmic) concentrations were determined by thechloroform fumigation extraction method (Vance Brookes amp Jenkinson 1987) Fumigatedand non-fumigated samples were incubated for 24 h at 25 C and constant moistureMicrobial C was extracted from fumigated and non-fumigated samples with 05 M K2SO4

and filtered through Whatman No 42 filters (Brookes et al 1985) The concentration ofC was measured in each extract as total and inorganic C concentration by the methoddescribed before Microbial C was calculated by subtracting the extracted carbon innon-fumigated samples from that of fumigated samples and dividing the result by a KEC

value (the extractable part of microbial biomass C) of 045 (Joergensen 1996) MicrobialN was extracted with the same procedure used for Cmic but the extract was filteredthrough Whatman No 1 paper The filtrate was acid digested and determined as TN byMacro-Kjeldahl method (Brookes et al 1985) Microbial N was calculated as for Cmic butdivided by a KEN value (the extractable part of microbial biomass N after fumigation) of054 (Joergensen amp Mueller 1996) Microbial P was extracted using NaCO3 05M at pH

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 524

85 after which the fumigation-extraction technique involving chloroform was performed(Cole et al 1978) Microbial P was calculated as for Cmic and Nmic and converted usinga KP value (the extractable part of microbial biomass P after fumigation) of 04 (Lathjaet al 1999) Microbial P was determined colorimetrically by the molybdate-ascorbic acidmethod using an Evolution 201 Thermo Scientific Inc spectrophotometer (Murphy ampRiley 1962) Finally Cmic Nmic and Pmic values were normalized on a dry soil basis

Because P is considered the most limited soil nutrient in the east-side of the CCB(Tapia-Torres et al 2015) alkaline phosphatase activity was analyzed colorimetricallyusing ρ-nitrophenol (ρNP) substrates according to Tabatabai amp Bremner (1969) andEivazi amp Tabatabai (1977) For this analysis 2 g of fresh soil and 30 ml of modifieduniversal buffer (MUB) at pH 9 were used for the exoenzyme extraction Three replicatesand one control (sample without substrate) were prepared per sample Three substratecontrols (substrate without sample) were also included per assay We centrifuged the tubesafter the incubation period and then 750 microl of supernatant was diluted in 2 ml of deionizedwater and absorbance of ρ-nitrophenol (ρNP) measured at 410 nm on an Evolution201 Thermo Scientific Inc spectrophotometer Exoenzyme activities were expressed asmicromoles of ρNP formed per gram dry weight of soil per hour (micromol ρNP [g SDW]minus1

hminus1) This value was standardized by Cmic concentration for expression as a specific enzymeactivity (micromol ρNP [mg Cmic]minus1 hminus1)

Molecular analysesTotal DNA was extracted using the hydroxyapatite spin-column method (Purdy et al1996) DNAmolecular weight and quality were confirmed using agarose gel electrophoresisThe 16S rRNA gene was amplified from each sample using a polymerase chain reaction(PCR) with the universal primers F27 (5primeAGAGTTTGATCMTGGCTCAG3prime) and R1492(5primeGGTTACCTTGTTACGACTT3prime) Three independent PCRs were performed for eachsample The PCR reactions were 50 microl in volume and contained 2microl of DNA 1 microl PCRbuffer 1times 05 mM MgCl2 02 mM dNTP mixture 02 mM of each primer 1 unit ofplatinum Taq DNA Polymerase High Fidelity (Invitrogen) 5 DMSO and 005 mg ofBSA The PCR was performed in a thermal cycler (MJ Research Watertown MA) underthe following cycling program initial denaturation step at 94 C for 5 min then 30 cyclesat 94 C for 1 min 52 C for 1 minand 72 C for 1 min 20 sec with a final extensionstep at 72 C for 30 min and storage at 4 C The three reactions were pooled and purifiedin a 1 agarose gel using the QIAquick gel extraction kit (Qiagen) The purified fragmentwas cloned into the vector PCR 21 and transformed into Escherichia coli following themanufacturerrsquos instructions (Invitrogen) Only plasmids containing inserts were isolatedfor sequencing with the Montage Plasmid Miniprepkit (Millipore) The insertion withinthe plasmids was sequenced with the Sanger method using the vector-based primer 27F

Data analysisStoichiometric homeostasisThe degree of community-level microbial CN and CP homeostasis (H prime) by soilmicroorganisms was calculated with the formula proposed by Sterner amp Elser (2002)

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 624

H prime= 1m (1)

In Eq (1) m is the slope of loge CNR (Carbon and Nitrogen in the resources) versus logeCNB (Carbon and Nitrogen in the microbial biomass) or slope of loge CPR (Carbon andPhosphorus in the resources) versus loge CPB (Carbon and Phosphorus in the microbialbiomass) scatterplot H prime 1 represents strong stoichiometric homeostasis while H primeasymp 1represents weak or no homeostasis (Sterner amp Elser 2002)

Resistance and resilience indexNutrient concentration and enzymatic activity data were both analyzed for resistance andresilience using the indices proposed by Orwin and Warlde (2004) The grassland sitewas considered as the control (C0) the cultivated site as the disturbance (P0) and theabandoned plot was used for measuring resilience 30 years after the cessation of agriculturemanagement (Px) Resistance (RS) was calculated as follows

RS= 1minus ((2|D0|)(C0+|D0|)) (2)

In Eq (2) C0 represents the control soil and D0 is the difference between C0 and thedisturbed plot (P0) In addition resilience (RL) was calculated as follows

RL= ((2|D0|)(|D0|+|DX |))minus1(3) (3)

In Eq (3) DX is the difference between C0 and Px Both indexes are bounded by minus1 and+1 if the value isminus1 means less resistance or resilience while the+1 value means maximalresistance or resilience

Bioinformatics analysisSequencing quality evaluation as well as cloning vector removal were performed using thesorftware PHRED (Ewing amp Green 1998) For processing and classification of the sequencedata the open source software package Mothur (v 1150 Schloss et al 2009) was usedSequences were screened for potential chimeric reads using Chimeraslayer (Haas et al2011) and the linked SILVA template database High-quality sequences were comparedagainst the SILVA database in order to obtain their taxonomic rank A pairwise distancematrix was calculated across the non-redundant sequences and reads were clustered intooperational taxonomic units (OTUs) at 3 distance using the furthest neighbor method(Schloss amp Handelsman 2005) In addition the Simpson and Shannon (H) indices Chaospecies richness estimator and rarefaction curves were estimated

Statistical analysisOne-way ANOVA was used to identify differences in nutrient concentrations andenzymatic activity between the sites of the agricultural gradient (grassland cultivatedfield and abandoned field) Log-transformations were applied where the data deviatedfrom normality When ANOVA indicated a significant site effect mean comparisons wereperformed with Tukeyrsquos multiple comparisons test (Von Ende 1993)

Pearson correlations were used to explore relationships among soil parameters PrincipalComponents Analysis (PCA) was conducted in order to group soil samples with active

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 724

nutrients forms (dissolved available and microbial) and enzymatic activity SimilarlyCanonical Analysis was conducted with soil nutrients (available dissolved organic andpH) as the independent variables and nutrients within microbial biomass and phosphataseactivity as dependent variables All analyses were performed using R software 2101(R Development Core Team 2009)

RESULTSSoil nutrientsSoil nutrientsThe abandoned and cultivated plots had the highest and the lowest soil pH and soilelectrical conductivity respectively (P lt 00001 and P = 00002 for pH and electricalconductivity respectively Table 1) Total organic C N and P concentrations differedamong management gradient plots Total organic C was almost two times greater in thecultivated plot than in the other two plots (P lt 00001 Table 1) whereas the cultivated andgrassland plots presented the highest and the lowest N and P concentrations respectively(P lt 0001 and P lt 00001 for N and P respectively Table 1) As a consequence thehighest CP and NP ratios were in the grassland plot (P lt 00001 for both CP and NP)while the CN ratio did not differ among plots (Table 1)The cultivated plot presentedhigher DOC and DOP than the other two plots (P lt 00001 and P lt 0001 for DOC andDOP respectively) but DON presented no differences among plots (Table 1) Similarlythe cultivated plot presented a greater concentration of ammonium than the other twoplots (P lt 00001) but the highest values of nitrate and available P were in the abandonedand the grassland plots respectively (P lt 00001 for both NO3 and available P Table 1)

Nutrients within microbial biomassThe cultivated plot had higher C and N concentrations within the microbial biomass(P lt 00001 for both Cmic and Nmic) but did not differ from the abandoned plot in termsof microbial P (Table 1) However the grassland plot had higher Nmic concentration thanthe abandoned plot and consequently the CN and CP ratios of the microbial biomassdid not differ among plots but the NP ratio was highest in the cultivated plot (P = 005)

Using the equation for CN and CP homeostasis (H prime) the soil microbial communitydid present a strong elemental homeostasis for phosphorus acquisition in the three sites(H prime= 625 935 and 129 respectively for cultivated grassland and abandoned plots) Fornitrogen acquisition however the microbial community of the cultivated soil presenteda weak homeostasis (H prime = 063) while the grassland (323) and abandoned plot (529)presented higher homeostasis

Enzymatic activityThe grassland soil had higher specific phosphatase activity than the other two managedplots (P lt 00001 Table 1) The DOC correlated positively with DOP ammoniumnutrients within microbial biomass and phosphanatase activity while nitrate correlatednegatively with available P and phosphanatase activity (Table 2) The first two principalcomponents explained 74 of the total variance in which 54 was explained by the first

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 824

Table 1 Means (standard error) of available dissolved microbial forms of C N and P and Specificphophonatase activity (SPA) of soil from an agricultural gradient at Cuatro Cieacutenegas BasinValues im-mediately followed by a different letter indicate that the means are significantly different (P le 005) amongagricultural gradient plots

Grassland Cultivated plot Abandoned plot

pH 85 (003)B 79 (004)C 88 (004)A

EC (mS mminus1) 87 (06)B 34 (01)C 156 (30)A

TOC (mg gminus1) 597 (071)B 2150 (117)A 954 (149)B

TN (mg gminus1) 063 (006)C 261 (007)A 113 (005)B

TP (mg gminus1) 0094 (001)C 0768 (004)A 053 (002)B

CN 93 (03) 83 (06) 83 (12)CP 64 (5)A 29 (2)B 18 (3)C

NP 69 (05)A 35 (02)B 21 (01)C

DOC (microg gminus1) 9 (2)C 116 (9)A 39 (7)B

DON (microg gminus1) 77(08) 66 (02) 136 (35)DOP (microg gminus1) 11 (03)B 146 (02)A 21 (08)B

NH+4 (microg gminus1) 164 (008)B 351 (040)A 155 (013)B

NOminus3 (microg gminus1) 0C 491 (041)B 1816 (130)A

HPOminus4 (microg gminus1) 0096 (0015)A 0010 (0002)B 0004 (0001)B

Cmic (microg gminus1) 108 (12)B 451 (68)A 145 (29)B

Nmic (microg gminus1) 14 (13)B 95 (236)A 4 (10)C

Pmic (microg gminus1) 195 (041)B 588 (121)A 320 (048)AB

CmicNmic 81 (09) 900 (23) 23 (69)CmicPmic 42 (9) 99 (17) 56 (13)NmicPmic 53 (11)A 332 (164)B 17 (03)A

SPA (micrommgCminus1mic hminus1) 150 (044)A 057 (008)B 046 (027)B

NotesEC Electrical conductivity TOC totalorganic Carbon TN total Nitrogen TP total Phophorus DOC dissolved organicCarbon DON dissolved organic nitrogen DOP dissolved organic phosphorus NH+4 ammonium NOminus3 nitrate HPOminus4 orthophosphate Cmic microbial carbon Nmic microbial nitrogen Pmic microbialphosphorus SPA specific phosphataseactivity

component In the first component the cultivated plot differed statistically to the othertwo non-cultivated plots while all three plots were significantly different in the secondcomponent (Fig 1) These results suggest that the difference between the cultivated plotand the other two plots explained 54 of the total variance in the soil nutrient dynamicThe dynamic forms of soil nutrients strongly correlated with nutrients within microbialbiomass and phosphatase activity as determined by canonical analysis (Canonical R= 098P lt 00001) The eigenvalue of root 1 was 095 and pH and POD had the highest canonicalweight in root 1

Soil resistance and resilienceIn general the soil variables analyzed showed low resistance to agricultural managementsince the majority of the resistance values were negative or close to zero with the exceptionof pH and DON (Table 3) Similarly the soil variables also had low resilience because noneof the values was close to 1 (Table 3) which means that these soil variables were dissimilar

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 924

Table 2 Pearson correlation coefficients for available nutrients and nutrients within microbial biomass in soil from agricultural gradient at Cuatro Cienegas Basin

pH DOC DON DOP NHlowast4 NOminus

3 HPOminus4 Cmic Nmic Pmic SPA

pH 1DOC minus070 1DON 046 minus012 1DOP minus085 088 minus037 1NH+4 minus068 065 minus023 072 1NOminus3 059 minus001 046 minus019 minus021 1HPOminus4 009 minus051 minus017 minus044 minus027 minus061 1Cmic minus068 079 minus024 074 070 minus009 minus032 1Nmic minus070 052 minus022 066 067 minus018 minus020 044 1Pmic minus041 068 minus021 057 039 minus001 minus030 062 015 1SPA minus088 065 minus040 084 minus076 minus052 minus011 064 062 030 1

NotesMeans significant correlation at P le 005DOC dissolved organic Carbon DON dissolved organic nitrogen DOP dissolved organic phosphorus NH4+ ammonium NOminus3 nitrate HPOminus4 orthophosphate Cmic microbial carbon Nmicmicrobial nitrogen Pmic microbial phosphorus SPA specific phosphatase activity

Hernaacutendez-B

ecerraetal(2016)PeerJD

OI107717peerj2365

1024

Figure 1 Principal component analysis of dynamic nutrient forms from an agricultural gradient atCuatro Cienegas Basin

to the grassland soil However the C and N concentrations within the microbial biomassDOC and DOP were closer in value to 1 (above 05) suggesting that these soil variableswere more resilient than the other soil variables analyzed (Table 3) although these valueswere insufficient to achieve recovery of these soil variables after 30 years

Soil bacteria compositionComposition of bacterial communitiesA total of 111 sequences were obtained for the grassland 107 sequences for the cultivatedplot and 93 sequences for the abandoned site In the grassland we obtained a clone librarywith 111 sequences while the cultivated plot had 107 sequences and the abandoned plot had93 In the grassland the sequences were distributed among 12 phyla and 19 classes whilethe cultivated plot sequences comprised 9 phyla and 14 classes and those of the abandoned

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1124

Table 3 Mean values (plusmnstandard error) of the resistance and resilience values of nutrient parametersfrom an agricultural gradient at Cuatro Cienegas Basin

Variable Resistance Resilience

pH 088 (plusmn001) 020 (plusmn012)DOC minus081 (plusmn006) 061 (plusmn006)DON 054 (plusmn008) minus028 (plusmn018)DOP minus084 (plusmn004) 081 (plusmn006)NH+4 004 (plusmn015) 042 (plusmn016)NOminus3 minus100 (plusmn000) minus057 (plusmn003)HPO+4 008 (plusmn002) minus004 (plusmn002)Cmic minus043 (plusmn009) 056 (plusmn013)Nmic minus045 (plusmn016) 056 (plusmn015)Pmic minus028 (plusmn017) 037 (plusmn013)SPA minus006 (010) 025 (plusmn012)

NotesDOC dissolved organic Carbon DON dissolved organic nitrogen DOP dissolved organic phosphorus NH4+ ammo-nium NO3minus nitrate HPO4minus orthophosphate Cmic microbial carbon Nmic microbial nitrogen Pmic microbial phosphorusSPA specific phosphatase activity

plot comprised 9 phyla and 12 classes These results suggest that the bacterial communityof the grassland soil was distributed in higher phyla than was the case in the other twomanaged plots For example Protobacteria was the more abundant bacteria phylum in thethree plots accounting for 50 of the results in the grassland and the abandoned plotbut representing only 35 in the cultivated plot (Fig 2) Similarly Actinobacteria was thesecond most dominant phylumin both the grassland and abandoned plot (20 and 21respectively) but only represented 15 in the cultivated plot The two most importantphototrophic phyla (Chloroflexi and Cyanobacteria) were not found in the cultivated plotbut Cyanobacteria was found in both the grassland soil and abandoned plot (Fig 2)

Diversity of bacterial communitiesRarefaction curve analysis showed that the cultivated plot had the richest bacterialcommunity followed by the abandoned plot and finally the grassland soil (Fig 3) Inaddition the cultivated plot had the highest expected OTUs by the Chao analyses (659)while the abandoned plot had the lowest expected value of OTUs (179) The latter plotalso had the lowest values of Simpson and Shannon indices (D= 0025 and H = 38respectively) suggesting that the bacterial community of the abandoned plotwas dominatedby fewer OTUs in comparison with the bacterial communities in the cultivated plot andthe grassland soil (D= 004 H = 44 and D= 0013 H = 42 respectively)

From the total of 307 sequences obtained for all sites 223 OTUs were recognized at 97of similitude The cultivated plot again had the highest number of OTUs (92) followedby grassland (84 OTUs) and finally the abandoned plot with the lowest number of OTUs(59) The three sites shared four OTUs corresponding to the Proteobacteria (RhizobialesPseudomonadales Burkholderiales and Xanthomonadales) The abandoned plot sharedtwo OTUs with the other sites but there were no OTUs shared between the grassland

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1224

Figure 2 Taxonomic distribution of the 16 rRNA gene sequences obtained from clone libraries of anagricultural gradient at Cuatro Cienegas Basin

Figure 3 Rarefaction curves of an agricultural gradient at Cuatro Cienegas Basin OTUs were deter-mined at 97 sequence identity

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1324

and the cultivated plot Finally the grassland soil and abandoned plot presented highersimilitude between them relative to the cultivated plot using the 16S rRNA communitycomposition at 97 similarity based on the Bray-Curtis algorithm

DISCUSSIONSoil nutrient dynamicsIn the Cuatro Cienegas basin (CCB) alfalfa production by flooding the fields threatens thewetlands sustainability and contributes to the degradation of soil and vegetation systemThe results showed that the cultivated plot presented a lower soil pH than the other twosites which could be associated with the fertilization and continuous irrigation it hasbeen reported in other agriculture sites (Moore Klose amp Tabatabai 2000 Raiesi 2004)Soil N fertilization mainly with ammonium as it is applied to the site of the presentstudy promotes nitrification by releasing H+ ions into the soil solution (Moore Klose ampTabatabai 2000) while continuous irrigation increases the leaching of salt through the soilprofile (Raiesi 2004) However the cultivated plot presented higher concentrations of totalC N and P than the other two plots These increases are caused by fertilization and by theparticular crop under cultivation with the latter mainly affecting the SOC concentrationPerennial legumes such as alfalfa promote higher SOC accumulation in comparisonwith the annual crops since they feature high root biomass production and require lowsoil tillage (Franzluebbers 2009 Sainju amp Lenssen 2011 Bell et al 2012 Yang et al 2013)Furthermore the alfalfa plot had a greater availability of dissolved organic carbon (DOC)which could be explained by higher organic matter input and soil water availability Theseconditions promoted depolymerization of organic molecules andmineralization of organicnutrients mediated by the activity of heterotrophic microorganisms (Wardle 1992 Vineelaet al 2008) Associated with this higher activity of heterotrophic microorganisms organicN is mainly released as NH+4 and then immobilized within microbial biomass as suggestedby the NH+4 and Nmic values of the cultivated plot All of these results suggest that thecultivated plot presented higher soil nutrient transformations mainly of N promoted bythe availability of water and nutrient fertilization and thus the soil nutrient dynamics ofthis plot differ from the plots without management as suggested by the results of the PCAIn contrast the low amount of soil organic matter in the native grassland is consequenceof low availability of soil water in the east-side of CCB (Tapia-Torres et al 2015a) Thelow water availability reduces plant productivity and in consequence there is a lower inputof organic matter input to the soil as Tapia-Torres et al (2015b) reported for soils underdesert scrub within CCB Consequently the activity of microbial populations is constrainedby low availability of organic carbon (Wardle 1992)

The nutrients within microbial biomass and phosphatase activity are strongly affectedby the dynamics of soil nutrients as Canonical Analysis confirmed While the cultivatedplot presented higher nutrient concentrations within microbial biomass than the othertwo plots microbial CN and CP did not differ among plots These results suggest thatthe soil microbial community had different strategies for nutrient acquisition in order toequilibrate nutrient stoichiometry (Sterner amp Elser 2002) The soil microbial communities

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1424

of the plots showed elemental homeostasis with the exception of the cultivated soil inwhich N acquisition showed weak homeostasis probably in response to the constantfertilization with ammonium Tapia-Torres et al (2015a) also reported a strong N andP homeostasis for two native grasslands within the CCB These results suggest that soilmicrobial communities adopt different strategies for nutrient acquisition including theproduction of eco-enzymes which clave the organic molecules for microbial assimilation(Waring Weintraub amp Sinsabaugh 2014) Phosphatase is the main eco-enzyme thatmineralizes organic P molecules (Tabatabai amp Bremner 1969) In our study site thenative grassland had higher specific phosphatase activity indicating that members of thesoil microbial community in this plot invest more in production of this enzyme than ingrowth which suggests that this microbial community is co-limited by C and P as reportedbefore for the same study site by Tapia-Torres et al (2015a) Moreover themicrobial CNPratio of the cultivated plot (99331) is wider than that proposed by Cleveland amp Liptzin(2007) for different terrestrial ecosystems (6071) while the non-managed plots are closerto this ratio (4251 and 5621 for the natural grassland and abandoned plot respectively)These results suggest that the agricultural management strongly disrupts soil microbialactivity and its homeostasis

As expected the sites under no current management were limited by water and DOC Atthe abandoned site these conditions promoted the nitrification process which is mediatedby autotrophic microorganisms that can use NH+4 as their energy source (Hart et al1994 Chen amp Stark 2000) The microbial N immobilization process was favored in thenative grassland this process promotes N conservation within the ecosystem as previouslyreported for native grassland in the CCB (Tapia-Torres et al 2015b)

Soil bacteria compositionThe agricultural land-use change affected the soil bacteria composition Agriculturalmanagement increased the numbers of OTUs and diversity indices associated with higheravailability of soil water and energy for microbial activity Such increases due to agricultureactivity have been reported for other desert sites (Koumlberl et al 2011 Wang et al 2012)However the abandoned plot had lower OTUs and diversity indexes in comparison withthe other two plots probably associated with more stressful soil conditions (ie highersalinity lower water and nutrient availability) as reported by Keshri Mody amp Jha (2013)for desert soils

The two dominant phyla from the three plots analyzed were Proteobacteria andActinobacteria which are both very common in agricultural (Buckle amp Schmidt 2003Chaudhry et al 2012) and desert (Chanal et al 2006 Loacutepez-Lozano et al 2012) soilsHowever their relative proportion differed among plots especially in the case of thecultivated plot Moreover the two most important phototrophic phyla (Chloroflexi andCyanobacteria) were not found in the cultivated plot where N input and soil disruptionselected against their presence As expected Cyanobacteria were present in both thegrassland soil and the abandoned plot forming a desert crust (Li et al 2012) In contrastthe Acidobacteria were more abundant in the cultivated plot (ca 18) while in the non-cultivated plot had decreased to 2 This phylum is associated with pH neutral or acid soils

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1524

such as the soils of the cultivated plot The results suggest that agricultural managementhas a strong effect on soil bacterial composition because the agricultural plot sharedlower OTUs (only 4) with the plot under no management Furthermore according to theBray-Curtis algorithm the grassland soil and the abandoned plot had a higher similitudebetween them relative to the cultivated plot For example in both the native grasslandand the abandoned plots some extremophile OTUs were present eg that associatedwith the phylum Deinococcus-Thermus which is adapted to stressful soil conditions suchas salinity high temperatures aridity etc (Nienow 2009) however these OTUs werenot presented in the cultivated plot These results suggest that some OTUs recover afterabandonment of agricultural management although the soil bacteria community is not yetsimilar to that in the native grassland even after more than 30 years since abandonmentOne study has reported similar soil bacteria in native vegetation and sites abandonedfor over 45 years in agro-ecosystems of Michigan State (Buckle amp Schmidt 2003)

In soil microbial communities microfungi are an important and diverse component ofmicrobial diversity representing a large proportion of microbial diversity in soils (FiererBradford amp Jackson 2007) These microorganisms play an immense role in regulatingenergy and nutrient fluxes through natural ecosystems via their involvement in soildevelopment decomposition and uptake of nutrients by plants (Dighton 1997) mainlyphosphate uptake Future studies should be aimed at understanding the role of microfungiin soil nutrient cycling in this ecosystem However tagging of ITS markers for soil fungi inCCB have been challenging so there is still further research needed in this field

Soil resistance and resilienceAll of the variables evaluated presented low resistance and resilience suggesting that thenative grassland soil may be very vulnerable to agricultural transformation The resilience ofsoil is determined by its intrinsic characteristics as well as by prevailing climatic conditions(Blanco-Canqui amp Lal 2010) For instance soil with high organic matter content is moreresilient since organic compounds represent important reservoirs of energy and nutrientsfor both the soil microbial community and plants (Bronick amp Lal 2005) In additionecosystems in humid climates are also more resilient than arid ecosystems because they arenot constrained by water availability For example the wet tropical ecosystem requires lessthan 10 years for recovery of its vegetal community following perturbation while the desertecosystem requires at least 40 years (Lesschen et al 2008 Wang et al 2011) Our resultssuggest that the native grassland presents slow recovery and this characteristic is critical forthe design of alternative agricultural management as well as appropriate strategies for soilreclamation This is important because the rate of soil degradation is faster than that of soilrestoration which acts to increase the area of degraded lands in these arid ecosystems

The design of soil restoration practices is critical for CCB because the ecosystemswithin CCB are very vulnerable to the disruption of nutrient dynamics and the nativespecies have low competition capacity against invasive species under higher availability ofresources (Souza et al 2006) This situation is critical for the soils of CCB because theycontain a high diversity of native species that can face up the scarcity of nutrients mainlyP (Tapia-Torres et al 2016) The organic agriculture with low pesticide inputs and the use

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1624

of native microbial strains with different capabilities to use transform and recycle the soilnutrients (ie phosphorus solubilizing bacteria) could be the best solution for agriculturein this particular and highly diverse important ecosystem These agricultural practices notonly will allow the maintenance of soil microbial biodiversity but also will contribute to thesoil conservation Therefore ensuring long-term availability and accessibility to healthysoil mainly for food security is a global challenge

CONCLUSIONSOur results suggest that land-use change transforming native grassland into agriculturalland induces drastic modifications in the soil nutrient dynamics as well as in thebacterial community However with the suspension of agricultural practices some soilcharacteristics tend to slowly recover their natural state

ACKNOWLEDGEMENTSWe are thankful to Rodrigo Velaacutezquez-Duraacuten for assisting with chemical analysis and toAlberto Valencia for assisting data analyses We also thank Oscar Saacutenchez Liceaga HeacutectorCastillo Gonzaacutelez the personnel of APFF Cuatro Cienegas (CONANP) and the people incharge of Rancho Pozas Azules (PRONATURA) for permission to collect soil samples ontheir respective properties

ADDITIONAL INFORMATION AND DECLARATIONS

FundingThis work was financed by the National Autonomous University of Mexico (PAPIITDGAPA-UNAM grant to FGO Anaacutelisis de la vulnerabilidad de la dinaacutemica de nutrientesen un ecosistema aacuterido deMeacutexico IN204013) as well as a grant from the alianzeWWF-FCSto VS The funders had no role in study design data collection and analysis decision topublish or preparation of the manuscript

Grant DisclosuresThe following grant information was disclosed by the authorsNational Autonomous University of Mexico

Competing InterestsValeria Souza is an Academic Editor for PeerJ

Author Contributionsbull Natali Hernaacutendez-Becerra conceived and designed the experiments performed theexperiments wrote the paper prepared figures andor tablesbull Yunuen Tapia-Torres conceived and designed the experiments analyzed the data wrotethe paper prepared figures andor tablesbull Ofelia Beltraacuten-Paz and Jazmiacuten Blaz performed the experiments reviewed drafts of thepaper

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1724

bull Valeria Souza analyzed the data contributed reagentsmaterialsanalysis tools revieweddrafts of the paperbull Felipe Garciacutea-Oliva conceived and designed the experiments analyzed the data wrotethe paper

Field Study PermissionsThe following information was supplied relating to field study approvals (ie approvingbody and any reference numbers)

Oscar Saacutenchez LiceagaHeacutector CastilloGonzaacutelez the personnel of APFFCuatroCienegas(CONANP) and the people in charge of Rancho Pozas Azules (PRONATURA) gave uspermission to collect soil samples on their respective properties

The owners gave us oral permission to collect soil samples

Data AvailabilityThe following information was supplied regarding data availability

The raw data has been supplied as Data S1

Supplemental InformationSupplemental information for this article can be found online at httpdxdoiorg107717peerj2365supplemental-information

REFERENCESBeheshti A Raiesi F Golchin A 2012 Soil properties C fractions and their dynamics in

land use conversion from native forest to croplands in a northern Iran AgricultureEcosystem and Environment 148121ndash133 DOI 101016jagee201112001

Bell LW Sparling B Tenuta M Entz MH 2012 Soil profile carbon and nutrientstocks under long-term conventional and organic crop and alfalfa-crop rotationsand re-established grassl Agriculture Ecosystem amp Environment 158156ndash163DOI 101016jagee201206006

Blanco-Canqui H Lal R 2010 Soil resilience and conservation In Principles of soilconservation and management New York Springer 425ndash447

Bremmer JM 1996 Nitrogen-Total In Spark DL Page AL Summer ME TabatabaiMA Helmke PA edsMethods of soil analyses part 3 chemical analyses soil scienceMadison Society of America 1085ndash1121

Bronick CJ Lal R 2005 Soil structure and management a review Geoderma 1243ndash22DOI 101016jgeoderma200403005

Brookes P Landman A Pruden G Jenkinson D 1985 Chloroform fumigationand the release of soil nitrogen a rapid direct extraction method to measuremicrobial biomass nitrogen in soil Soil Biology and Biochemistry 17837ndash842DOI 1010160038-0717(85)90144-0

Buckle DH Schmidt TM 2003 Diversity and dynamics of microbial communi-ties in soils from agro-ecosystems Environmental Microbiology 5441ndash452DOI 101046j1462-2920200300404x

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1824

Buckley DH Schmidt TM 2001 The structure of microbial communities in soil and thelasting impact of cultivationMicrobial Ecology 4211ndash21 DOI 101007s002480000108

Chanal A Chapon V Benzerara K Barakat M Christen R AchouakW Barras FHeulin T 2006 The desert of Tataouine an extreme environment that hosts a widediversity of microorganisms and radio tolerant bacteria Environmental Microbiology8514ndash525 DOI 101111j1462-2920200500921x

Chaudhry V Rehman A Mishra A Chauhan PS Nautiyal CC 2012 Changes in bacte-rial community structure of agriculture land due to long-term organic and chemicalamendmentsMicrobial Ecology 64450ndash460 DOI 101007s00248-012-0025-y

Chen J Stark JM 2000 Plant species effects carbon and nitrogen cycling in a sagebrush-crested wheatgrass soil Soil Biology Biochemistry 3247ndash57DOI 101016S0038-0717(99)00124-8

Cleveland CC Liptzin D 2007 CNP stiochiometry in soil is there a lsquolsquoRedfield ratiorsquorsquofor the microbial biomass Biogeochemistry 85235ndash253DOI 101007s10533-007-9132-0

Colditz RR Llamas RM Ressl RA 2014 Detecting change areas in Mexico between2005 and 2010 using 250 mMODIS images IEEE Journal on Selected Topics in Ap-plied Earth Observation and Remote Sensing 73358ndash3372DOI 101109JSTARS20132280711

Cole CV Elliott ET Hunt HW Coleman DC 1978 Trophic interactions in soils as theyaffect energy and nutrient dynamics V Phosphorus transformationsMicrobialEcology 4381ndash387

Dighton J 1997 Nutrient cycling by saprotrophic fungi in terrestrial habitats TheMycota 4271ndash279

Ding G Piceno YM Heuer HWeinert N Dohrmann AB Carrillo A Andersen GLCastellanos T Tebbe CC Smalla K 2013 Changes of soil bacteria diversity as aconsequence of agriculture land use in a semi-arid ecosystem PLoS ONE 8e59497DOI 101371journalpone0059497

Drsquoodorico P Bhattachan A Davis KF Ravi S Runyan CW 2013 Global deser-tification drivers and feedback Advances in Water Resources 51326ndash344DOI 101016jadvwatres201201013

Eivazi F Tabatabai MA 1977 Phosphatases in soils Soil Biology and Biochemistry9167ndash172 DOI 1010160038-0717(77)90070-0

Ewing B Green P 1998 Base-calling of automated sequencer traces using phred IIError probabilities Genome Research 8186ndash194 DOI 101101gr83186

Fierer N BradfordMA Jackson RB 2007 Toward an ecological classification of soilbacteria Ecology 881354ndash1364 DOI 10189005-1839

Franzluebbers AJ 2009 Achieving soil organic carbon sequestration with conservationagricultural systems in the southeastern United States Soil Science Society of Ameri-can Journal 74347ndash357 DOI 102136sssaj20090079

Garcia-Orenes F Morugaacuten-Coronado A Zornoza R Scow K 2013 Changesin soil microbial community structure influenced by agricultural manage-

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 1924

ment practices in a Mediterranean Agro-Ecosystem PLoS ONE 8(11)e80522DOI 101371journalpone0080522

Haas BJ Gevers D Earl AM FeldgardenMWard DV Giannoukos G Ciulla D TabbaD Highlander SK Sodergren E Metheacute B Desantis TZ humanmicrobiomesConsortium T Petrosino JF Knight R Birren BW 2011 Chimeric 16S rRNAsequence formation and detection in Sanger and 454-pyrosequenced PCR ampliconsGenome Research 21494ndash504 DOI 101101gr112730110

Hart S Nason GE Myrlod D Perry DA 1994 Dynamic of gross nitrogen transfor-mations in an old-growth forest the carbon connection Ecology 75880ndash891DOI 1023071939413

Huffman EN 1977 Performance of a new automatic carbon dioxide coulometerMicrochemical Journal 2567ndash573

INEGI Instituto Nacional de Estadstica y Geografia II 2011 Anuario Estadistico deCoahuila de Zaragoza Meacutexico INEGI

Jangid KWilliamsMA Franzluebbers AJ Sanderlin JS Reeves JH Jenkins MBEndale DM Coleman DCWhitmanWB 2008 Relative impacts of land-use management intensity and fertilization upon soil microbial communitystructure in agricultural systems Soil Biology and Biochemistry 402843ndash2853DOI 101016jsoilbio200807030

Joergensen RG 1996 The fumigation-extraction method to estimate soil microbialbiomass Calibration of the KEC value Soil Biology and Biochemistry 2825ndash31DOI 1010160038-0717(95)00102-6

Joergensen RG Mueller T 1996 The fumigation-extraction method to estimate soilmicrobial biomass calibration of de KEN value Soil Biology and Biochemistry2833ndash37 DOI 1010160038-0717(95)00101-8

Jones DLWillett VB 2006 Experimental evaluation of methods to quantify dissolvedorganic nitrogen (DON) and dissolved organic carbon (DOC) in soil Soil Biologyand Biochemistry 38991ndash999 DOI 101016jsoilbio200508012

Keshri J Mody K Jha B 2013 Bacterial community structure in a semi-arid haloalkalinesoil using culture independent method Geomicrobiology Journal 30517ndash529DOI 101080014904512012737092

Lathja K Driscoll CT Jarrell WM Elliott ET 1999 Soil phosphorus characterizationand total element analysis In Robertson GP Coleman DC Bledsoe CS SollinsP eds Standard soil methods for long-term ecological research New York OxfordUniversity Press 115ndash142

Lepers E Lambin EF Janetos AC Fries RD Archad F Ramankutty N Scholes RJ2005 A synthesis of rapid land-cover change information for the 1981ndash2000 periodBioScience 55115ndash124 DOI 1016410006-3568(2005)055[0115ASOIOR]20CO2

Lesschen JP Cammeraat LH Kooijman AMWesemael B 2008 Developmentof spatial heterogeneity in vegetation and soil properties after land abandon-ment in a semi-arid ecosystem Journal of Arid Environment 722082ndash2092DOI 101016jjaridenv200806006

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 2024

Li XR Zhang P Su YG Jia RL 2012 Carbon fixation by biological soil crusts followingrevegetation of sand dunes in arid desert regions of China a four-year field studyCatena 97119ndash126 DOI 101016jcatena201205009

Loacutepez-Lozano NE Eguiarte LE Bonilla-Rosso G Garcia-Oliva F Martinez-PiedragilC Rooks C Souza V 2012 Bacteria communities and nitrogen cycle in the gypsumsoil in CuatroCienegas Basin Coahuila a Mars analogue Astrobiology 12699ndash709DOI 101089ast20120840

Lupwayi NZ RiceWA Clayton GW 1998 Soil microbial diversity and communitystructure under wheat as influenced by tillage and crop rotation Soil Biology andBiochemistry 301733ndash1741 DOI 101016S0038-0717(98)00025-X

McKee JW Jones NW Long LE 1990 Stratigraphy and provenance of strata along theSan Marcos fault central Coahuila Mexico Geological Society of America Bulletin102593ndash614 DOI 1011300016-7606(1990)102lt0593SAPOSAgt23CO2

McLauchlan KK 2006 The nature and longevity of agriculture impacts on soil carbonand nutrients a review Ecosystems 91364ndash1382 DOI 101007s10021-005-0135-1

Moore JM Klose S Tabatabai MA 2000 Soil microbial biomass carbon and nitro-gen as affected by cropping systems Biology and Fertility of Soils 31200ndash210DOI 101007s003740050646

Murphy J Riley JP 1962 A modified single solution method for the determi-nation of phosphate in natural waters Analytica Chimica Acta 2731ndash36DOI 101016S0003-2670(00)88444-5

Murty D KirschbaumMUF McMurtrie RE McGilvray H 2002 Does conversion offorest to agricultural land change soil carbon and nitrogen A review of the literatureGlobal Change Biology 8105ndash123 DOI 101046j1354-1013200100459x

Nienow J 2009 Extremophiles dry environments (including cryptoendoliths) InSchaechter M ed Encyclopedia of microbiology Oxford Elsevier 159ndash173

Orwin KHWardle DA 2004 New indices for quantifying the resistence and resilienceof soil biota to exogenous disturbances Soil Biology and Biochemistry 361907ndash1912DOI 101016jsoilbio200404036

Pan C Liu C Zhao HWang Y 2012 Changes of soil physical-chemical properties andenzyme activities in relation to grassland salinization European Journal of Soil Biology5513ndash19 DOI 101016jejsobi201209009

Perroni Y Garcia-Oliva F Souza V 2014 Plant species identity and soil P forms in anoligotrophic grasslandndashdesert scrub system Journal of Arid Environments 10829ndash37DOI 101016jjaridenv201404009

Pimm SL 1984 The complexity and stability of ecosystems Nature 307321ndash326DOI 101038307321a0

Purdy KJ Embley TM Takii S Nedwell DB 1996 Rapid extraction of DNA and rRNAfrom sediments by a novel hydroxyapatite spin-column method Applied andEnvironmental Microbiology 623905ndash3907

RDevelopment Core Team 2009 R a language and environment for statistical comput-ing Vienna R foundation for Statistical Computing

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 2124

Raiesi F 2004 Soil properties and N application effects on microbial activities intwo winter wheat cropping systems Biology and Fertility of Soils 4088ndash92DOI 101007s00374-004-0741-7

Rey-Benayas JM Bullock JM 2012 Restoration of biodiversity and ecosystem serviceson agricultural land Ecosystems 15883ndash899 DOI 101007s10021-012-9552-0

Reynolds JF Smith D Lambin EF Turner BL MortimoreM Batterbury S DowningTE Dowlatabadi H Fernaacutendez RJ Herrick JE Huber-Sannwald E Juang HLeemans R Lynam T Maestre FT Ayarza MWalker B 2007 Global deser-tification building a science for dryland development Science 316847ndash851DOI 101126science1131634

Rietz D Haynes R 2003 Effects of irrigation-induced salinity and sodicity on soilmicrobial activity Soil Biology and Biochemistry 35845ndash854DOI 101016S0038-0717(03)00125-1

Robertson PG Coleman DC Bledsoe CS Sollins P 1999 Standard soil methods for long-term ecological research (LTER) Oxford University Press

Sainju UM Lenssen AW 2011 Dryland soil carbon under alfalfa and durum-foragecropping sequences Soil Tillage Research 11330ndash37 DOI 101016jstill201102002

Schloss PD Handelsman J 2005 Introducing DOTUR a computer program fordefining operational taxonomic units and estimating species richness AppliedEnvironmental Microbiology 711501ndash1506 DOI 101128AEM7131501-15062005

Schloss PDWestcott SL Ryabin T Hall JR HartmannM Hollister EB LesniewskiRA Oakley BB Parks DH Robinson CJ Sahl JW Stres B Thallinger GGVan Horn DJ Weber CF 2009 Introducing mothur open- source platform-independent community-supported software for describing and comparingmicrobial communities Applied Environmental Microbiology 757537ndash7541DOI 101128AEM01541-09

Six J Elliott ET Paustian K 1999 Aggregate and soil organic matter dynamics un-der conventional and no-tillage systems Soil Science Society of America Journal631350ndash1358 DOI 102136sssaj19996351350x

Souza V Esponosa_Asuar L Escalante AE Eguiarte LE Farmer J Forney L LloretL Rodriacuteguez-Martiacutenez JM Soberon X Dirzo R Elser JJ 2006 An endangeredoasis of aquatic microbial biodiversity in the Chihuahuan Desert Proceedings ofthe National Academy of Sciences of the United States of America 1036565ndash6570DOI 101073pnas0601434103

Sterner RW Elser JJ 2002 Ecological stoichiometry the biology of elements from moleculesto the biosphere Princeton Princeton University Press

Tabatabai MA Bremner JM 1969 Use of p-Nitrophenyl phosphate for assay of soilphosphatase activity Soil Biology and Biochemistry 1301ndash307DOI 1010160038-0717(69)90012-1

Tapia-Torres Y Elser JJ Souza V Garciacutea-Oliva F 2015a Ecoenzymatic stoichiometry atthe extremes How microbes cope an ultra-oligotrophic desert soil Soil Biology andBiochemistry 8734ndash42 DOI 101016jsoilbio201504007

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 2224

Tapia-Torres Y Garcia-Oliva F 2013 La disponibilidad del foacutesforo es producto de laactividad bacteriana en el suelo en ecosistemas oligotroacuteficos una revisioacuten criacuteticaTerra-Latinoamericana 31231ndash242

Tapia-Torres Y Loacutepez-Lozano NE Souza V Garciacutea-Oliva F 2015b Vegetation-soilsystem controls soil mechanisms for nitrogen transformations in an oligotrophicMexican desert Journal of Arid Environments 11462ndash69DOI 101016jjaridenv201411007

Tapia-Torres Y Rodriacuteguez-Torres MD Islas A Elser J Souza V 2016How to livewith phosphorus scarcity in soil and sediment lessons from bacteria Applied andEnvironmental Microbiology 8200ndash00 DOI 101128AEM00160-16

Tiessen H Moir JO 1993 Characterization of available P by sequential extraction InCarter MR Gregorich EG eds Soil sampling and methods of analysis New YorkCRC Press 75ndash85

Trasar-Cepeda C Leiroacutes MC Seoane S Gil-Sotres F 2008 Biochemical properties ofsoils under crop rotation Applied Soil Ecology 39133ndash143DOI 101016japsoil200712003

Vance ED Brookes AC Jenkinson DS 1987 An extraction method for mea-suring soil microbial biomass C Soil Biology and Biochemistry 19703ndash707DOI 1010160038-0717(87)90052-6

Vineela CWani SP Srinivasarao C Padmaja B Vittal KPR 2008Microbial propertiesof soils as affected by cropping and nutrient management practices in several long-term manorial experiments in the semi-arid tropics of India Applied Soil Ecology40165ndash173 DOI 101016japsoil200804001

Von Ende CN 1993 Repeated measures analysis growth and other time-dependentmeasures In Scheiner SM Gurevitch J eds Design and analysis of ecologicalexperiments New York Chapman and Hall 113ndash117

WaldropMP Balser TC FirestoneMK 2000 Linking microbial community compo-sition to function in a tropical soil Soil Biology and Biochemistry 321837ndash1846DOI 101016S0038-0717(00)00157-7

Wang B Liu G Xue S Zhu B 2011 Changes in soil physico-chemical and microbio-logical properties during natural succession on abandoned farmland in the LoessPlateau Environmental Earth Science 62915ndash925 DOI 101007s12665-010-0577-4

Wang B Zhang C Liu J Zeng X Li F Wu Y Lin X Xiong ZQ Xu J Jia ZJ 2012Microbial community changes along a land-use gradient of desert soil originPedosphere 22593ndash603 DOI 101016S1002-0160(12)60044-7

Wardle DA 1992 A comparative assessment of factors which influence microbialbiomass carbon and nitrogen levels in soil Biological Reviews 67321ndash358DOI 101111j1469-185X1992tb00728x

Waring BGWeintraub SR Sinsabaugh RL 2014 Ecoenzymatic stoichiometry ofmicrobial nutrient acquisition in tropical soils Biogeochemistry 117101ndash113DOI 101007s10533-013-9849-x

Yang R Su Y Gan Y DuMWangM 2013 Field-scale spatial distribution char-acteristics of soil nutrients in a newly reclaimed sandy cropland in the Hexi

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 2324

Corridor of Northwest China Environmental Earth Science 702987ndash2996DOI 101007s12665-013-2356-5

Zeleke TB Grevers MCJ Si BC Mermut AR Beyene S 2004 Effect of residue incor-poration on physical properties of the surface soil in the South Central Rift Basin ofEtiopia Soil Tillage Research 7735ndash46 DOI 101016jstill200310005

Hernaacutendez-Becerra et al (2016) PeerJ DOI 107717peerj2365 2424