Over 150 Years of Long-Term Fertilization Alters Spatial Scaling ofMicrobial Biodiversity

Yuting Liangabc Liyou Wuc Ian M Clarkd Kai Xuec Yunfeng Yangb Joy D Van Nostrandc Ye Dengc Zhili Hec Steve McGrathd

Jonathan Storkeyd Penny R Hirschd Bo Suna Jizhong Zhoubce

State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing Chinaa State Key Joint Laboratory ofEnvironment Simulation and Pollution Control School of Environment Tsinghua University Beijing Chinab Institute for Environmental Genomics and Microbiology andPlant Biology University of Oklahoma Norman Oklahoma USAc Rothamsted Research Harpenden Herts United Kingdomd Earth Science Division Lawrence BerkeleyNational Laboratory Berkeley California USAe

ABSTRACT Spatial scaling is a critical issue in ecology but how anthropogenic activities like fertilization affect spatial scaling ispoorly understood especially for microbial communities Here we determined the effects of long-term fertilization on the spa-tial scaling of microbial functional diversity and its relationships to plant diversity in the 150-year-old Park Grass Experimentthe oldest continuous grassland experiment in the world Nested samples were taken from plots with contrasting inorganic fer-tilization regimes and community DNAs were analyzed using the GeoChip-based functional gene array The slopes of microbialgene-area relationships (GARs) and plant species-area relationships (SARs) were estimated in a plot receiving nitrogen (N)phosphorus (P) and potassium (K) and a control plot without fertilization Our results indicated that long-term inorganic fertil-ization significantly increased both microbial GARs and plant SARs Microbial spatial turnover rates (ie z values) were lessthan 01 and were significantly higher in the fertilized plot (00583) than in the control plot (00449) (P lt 00001) The z valuesalso varied significantly with different functional genes involved in carbon (C) N P and sulfur (S) cycling and with various phy-logenetic groups (archaea bacteria and fungi) Similarly the plant SARs increased significantly (P lt 00001) from 0225 in thecontrol plot to 0419 in the fertilized plot Soil fertilization plant diversity and spatial distance had roughly equal contributionsin shaping the microbial functional community structure while soil geochemical variables contributed less These results indi-cated that long-term agricultural practice could alter the spatial scaling of microbial biodiversity

IMPORTANCE Determining the spatial scaling of microbial biodiversity and its response to human activities is important butchallenging in microbial ecology Most studies to date are based on different sites that may not be truly comparable or on short-term perturbations and hence the results observed could represent transient responses This study examined the spatial pat-terns of microbial communities in response to different fertilization regimes at the Rothamsted Research Experimental Stationwhich has become an invaluable resource for ecologists environmentalists and soil scientists The current study is the firstshowing that long-term fertilization has dramatic impacts on the spatial scaling of microbial communities By identifying thespatial patterns in response to long-term fertilization and their underlying mechanisms this study makes fundamental contri-butions to predictive understanding of microbial biogeography

Received 11 February 2015 Accepted 4 March 2015 Published 7 April 2015

Citation Liang Y Wu L Clark IM Xue K Yang Y Van Nostrand JD Deng Y He Z McGrath S Storkey J Hirsch PR Sun B Zhou J 2015 Over 150 years of long-term fertilizationalters spatial scaling of microbial biodiversity mBio 6(2)e00240-15 doi101128mBio00240-15

Editor Mark J Bailey CEH-Oxford

Copyright copy 2015 Liang et al This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 30 Unportedlicense which permits unrestricted noncommercial use distribution and reproduction in any medium provided the original author and source are credited

Address correspondence to Jizhong Zhou jzhououedu

This article is a direct contribution from a Fellow of the American Academy of Microbiology

Microbial communities constitute a large portion of theEarthrsquos biosphere and play important roles in maintaining

various biogeochemical processes that mediate ecosystem func-tioning They inhabit almost all natural environments with pop-ulations undergoing dynamic changes in composition structureand function over space and time Understanding the geographicpatterns of microbial diversity and their relationships to plantdiversity is critical for understanding the mechanisms controllingmicrobial biodiversity (1 2) In recent years the spatial distribu-tion patterns of microbial diversity have attracted substantial at-tention (3ndash6) Taxon-area relationships (TARs) species-area re-lationships (SARs) and gene-area relationships (GARs) are

among the best known spatial patterns The power law equationS cAz where S is species richness A is area c is the intercept inlog-log space and the species-area exponent z is a measure of therate of species change with space is typically used to describeSARs Despite their ecological and biogeographical importancethe TARs of microbial communities have only been studied re-cently This is due to their complexity especially under naturalsettings and their unique features that differ considerably fromthose of macroorganisms such as high dispersal rates high func-tional redundancy massive population sizes rapid asexual repro-duction resistance to extinction and horizontal gene transfer (37ndash9) The slopes of TARs for microorganisms also vary substan-

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tially among different studies (z 0019 to 0470) especially insoils which could be due to variations in environmental condi-tions experimental design spatial scales and the analytical ap-proaches used (9) However it has been generally recognized thatthe slopes of the microbial TARs are considerably lower than theslopes of TARs associated with plants and animals (7)

In the past centuries human activity has greatly affected thebiosphere and global biogeochemical processes For example fer-tilization changes in land use and fuel combustion have substan-tially altered the structures of communities and their ecologicalfunctions (10) Although microbial TARs have been documentedin natural habitats of microorganisms such as natural forest soils(9 11) grassland soils (12 13) marsh sediments (3 4) lakes (1415) and marine environments (16) it is not yet clear how they areaffected by anthropogenic activities Thus there is an urgent needto determine how microbial communities respond to anthropo-genic activities at different spatial scales

The use of nitrogen (N) and other fertilizers (eg phosphorus[P] and potassium [K]) has long been an agricultural practice toincrease the net primary productivity of plants While fertilizationincreases plant productivity it generally decreases plant speciesdiversity (17) It is also known that N fertilization has significantimpacts on microbial diversity and activity (18ndash20) but the im-pacts of other inorganic fertilizers such as P and K are less clearAlso most of those studies focused on short-term responseswhich are expected to differ considerably from those in the longterm Generally long-term fertilization can have more persistentimpacts on soil characteristics (21 22) plant growth (23) andfungal diversity by decreasing root exudates (24) A meta-analysisof 82 published field studies indicated that microbial biomass de-clines with N fertilization and that longer periods of fertilizationresulted in stronger decreases in microbial biomass (20) indicat-ing the significant influence of the duration of fertilization onmicrobes However one potential pitfall in examining spatial dy-namics in the context of human interference is the lack of studiesaddressing long-term response to fertilization To date little isknown about the effect of fertilization on microbial TARs espe-cially over long time periods

The Park Grass Experiment (PGE) at Rothamsted ResearchUnited Kingdom conducted on a permanent grassland is theoldest grassland experiment in the world (25) Since 1856 its plotshave received different amounts and combinations of inorganicN P and K fertilizers and lime while control plots have gonewithout fertilization During such long-term fertilization soilgeochemical characteristics and soil biota can represent a long-term response (26ndash28) As such the PGE provides a unique op-portunity to study spatial patterns of microbial and plant biodi-versity Here we examined microbial GARs under long-terminorganic fertilization using GeoChip-based metagenomics tech-nologies to address the following questions (i) Does long-terminorganic fertilization affect microbial GARs and plant SARs Ifyes does the influence on GARs vary across different functionaland phylogenetic groups in a community (ii) How do envi-ronmental variables contribute to the spatial scaling of micro-bial and plant diversity (iii) How do microbial GARs relate toplant SARs Our results indicate that long-term fertilizationhas significant impacts on spatial scaling of microbial commu-nities This study is important for predictive understanding ofmicrobial biogeography

RESULTSGene-area relationship under long-term inorganic fertilizationA total of 42 soil samples (21 samples each from the fertilized plotand the control plot see Fig S1 in the supplemental material) wereanalyzed with GeoChip 30 Altogether 2126 (459) (mean standard deviation) functional genes were detected in the controlplot and 1670 (434) in the fertilized plot The average percent-ages of genes common to pairwise samples in the 12D plot (con-trol) 112C plot (fertilization) and between these two plots were535 485 and 478 respectively The fertilized plot hadfewer genes in common than the control plot based on t testresults (t 8603 P 00001) Microbial z values (the exponentof GAR) for all functional genes were estimated by linear regres-sion of log-transformed raw data and they were 00583 in thefertilized plot and 00449 in the control plot (Fig 1A) The differ-ences of the z values were statistically significant as determined bythe pairwise t test based on bootstrapping (P 00001) (Table 1)

Plant species and abundance were also surveyed in nestedsquares with 0025 m2 for each quadrant in the same experimental

FIG 1 Microbial gene-area relationship (A) and plant species-area relation-ship (B) in a long-term fertilized plot and a control plot of the Park GrassExperiment

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plots to determine the plant species-area relationships (SARs)The z values were 0419 in the fertilized plot and 0225 in thecontrol plot (Fig 1B) respectively Statistical analysis using thepairwise t test with bootstrapping indicated that the plot withlong-term fertilization had significantly (P 00001) higher z val-ues than the control plot

Variations in gene-area relationships among different func-tional genes and phylogenetic groups Gene-area relationshipswere observed for different microbial functional groups (carbon[C] N P and sulfur [S] cycling) and the influence of fertilizationon the z values of each functional group was examined (see Ta-ble S1 and Fig S2 in the supplemental material) For all of thefunctional groups the mean z value was 00617 (00131) in thefertilized plot and 00512 (0014) in the control plot For C cy-cling genes the fertilized plot had much higher z values (zf) thanthe control plot (zc) for both C fixation (zc 00588 zf 0063)and degradation (zc 00421 zf 00754 P 001) For N cy-cling genes long-term fertilization resulted in higher z values fornitrification (zc 00671 zf 00842 P 00001) and denitrifi-cation (zc 00543 zf 00613 P 00001) but lower z values inassimilatory N reduction (P 00001) and N fixation (P 00001) No significant influence of fertilization on the z value ofdissimilatory N reduction was observed (P 0648) In additionfertilization resulted in higher z values for P cycling genes (zc 00234 zf 00609 P 00001) and sulfur cycling genes (zc 00367 zf 00724 P 00001)

For all phylogenetic groups obtained by mapping functionalgenes to their lineages the mean z value was 00517 (00121) inthe fertilized plot and 00433 (00130) in the control plot (seeTable S1 in the supplemental material) Fertilization resulted inhigher z values in alpha- beta- and gammaproteobacteria (P

005) often considered copiotrophic bacteria and a lower z valuein deltaproteobacteria (P 005) a class of oligotrophic anaero-bic bacteria (29)

Factors affecting microbial spatial patterns To determinewhether fertilization soil geochemical properties plant diversityand spatial distance affected microbial community compositionpartial Mantel tests were performed (Table 2) The results showedsignificant correlations between all functional genes as a groupand fertilization (Mantel correlation coefficient [rM] 0138 P 0010) soil geochemical properties (rM 0198 P 0003) plantspecies richness (rM 0181 P 0001) and spatial distance(rM 0165 P 0001) For C cycling genes both C degradationand C fixation genes were significantly (P 005) correlated withfertilization geochemical properties plant species and distanceFor N cycling genes dissimilatory N reduction genes and N fixa-tion were also significantly (P 005) correlated with those fourfactors Nitrification genes were significantly (P 005) correlatedwith plant species and distance Denitrification genes were signif-icantly (P 005) correlated with all except soil geochemical vari-ables In addition both P and S cycling genes were also signifi-cantly (P 005) correlated with all four factors

Canonical correspondence analysis (CCA) was performed tolink the most significant environmental variables to microbialspatial patterns (Fig 2) The results for samples from the two plotswere clearly separated and plot 112C (fertilized) revealed a moredivergent pattern which could be confirmed by the permutationalanalysis of dispersion showing that community dispersion in-creased significantly with fertilization (P 0017) (see Fig S3 inthe supplemental material) Of all the environmental variablesselected spatial distance (principal coordinates of neighbor ma-trices 1 [PCNM1]) fertilization treatment (total N [TN] and am-

TABLE 1 The slopes of gene-area relationships for various functional and phylogenetic groups under control or long-term fertilization

Control (12D plot) N fertilization (112C plot) t testc

z value 95 CI n t P z value 95 CI n t P t P

All functional genes 00449 147 103 4006 6021 0001 00583 210 103 3405 5459 0001 1022 00001

Functional groupsC degradation 00588a 190 103 432 5987 0001 00630b 226 103 414 535 0001 278 00053C fixation 00421 136 103 141 587 0001 00754b 252 103 129 5777 0001 2280 00001N fixation 0410a 138 103 174 5895 0001 00365b 136 103 151 525 0001 454 00001Assimilatory N reduction 00660a 218 103 34 5873 0001 00582 223 103 29 5171 0001 490 00001Dissimilatory N reduction 00599a 194 103 28 5759 0001 00592 229 103 25 5108 0001 045 06479Nitrification 00671a 291 103 14 4542 0001 00842b 286 103 7 5699 0001 821 00001Denitrification 00543a 181 103 190 5893 0001 00613 221 103 148 5473 0001 481 00001Phosphorus 00234a 802 104 76 5508 0001 00609 218 103 56 5755 0001 3171 00001Sulfur 00367a 122 103 193 5882 0001 00724b 256 103 176 5444 0001 2465 00001

Phylogenetic groupsArchaea 00428 142 103 94 5868 0001 00492b 172 103 79 5557 0001 560 00001Fungi 00604a 202 103 182 5893 0001 00704b 261 103 153 5413 0001 593 00001Bacteria 00444 147 103 3191 5803 0001 00565b 204 103 2705 537 0001 943 00001Gram-positive 00263a 879 104 539 596 0001 00347b 125 103 496 5328 0001 1075 00001Gram-negative 00254a 854 104 1998 593 0001 00312b 112 103 1656 5493 0001 805 00001-Proteobacteria 00356a 120 103 763 5971 0001 00567 202 103 661 5492 0001 1758 00001-Proteobacteria 00437 145 103 429 6084 0001 00557 207 103 356 5461 0001 930 00001-Proteobacteria 00496a 165 103 522 5856 0001 00528b 189 103 399 5376 0001 250 00123-Proteobacteria 00619a 203 103 144 5935 0001 00583 213 103 126 5488 0001 239 00165

a The z values of functional groups and phylogenetic groups are significantly different from all functional genes (P 005) in control plotb The z values of functional groups and phylogenetic groups are significantly different from all functional genes (P 005) in fertilized plotc The right-most columns test whether the z values for the two treatments were significantly different

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monium [NH4]) and plant diversity were the most significant

factors influencing microbial spatial scaling The pH and moistureexplained differences along the other axis which were most likelydue to lime application (see Text S1 in the supplemental material)

Variance partitioning analysis (VPA) was performed to furtherquantify the contributions of environmental variables to the mi-crobial community variation (Fig 3) Soil fertilization attributesspatial distance and plant diversity were found to contributeequally to the variations in microbial functional structure (47 to48) while soil geochemical properties contributed less (23)The joint effect of fertilization plant diversity and spatial distancewas 32 and other joint effects were less than 10 Meanwhilea substantial amount of the variation in microbial communitycomposition (784) could not be explained by the environmen-tal variables measured

Comparative analysis of TARs across different groups of or-ganisms To obtain reliable insights on the spatial scaling of bio-diversity across different organism types and the effect of long-term anthropogenic disturbance the z values obtained in bothcontrol and fertilized plots in this study were compared with allavailable published data (806 datasets) (Fig 4) Although detailedcomparisons could not be made due to the wide ranges of organ-isms and habitats the various spatial scales and the differences inexperimental design and analytical approaches used we were ableto show that microorganisms had lower z values than macroor-ganisms 3 to 5 times lower than those in plants in this studyFurthermore although long-term fertilization significantly in-creased the z values of bacteria fungi and archaea (P 005) theinfluence did not change the general pattern that the rates of

TABLE 2 Correlation analysis between microbial functional gene and soil geochemical variables plant and distance by partial Mantel testa

Fertilization Soil Plant Distance

rM P rM P rM P rM P

All functional genes 0138 0010 0198 0003 0181 0001 0165 0001

Functional groupsC degradation 0119 0011 0200 0002 0163 0001 0153 0002C fixation 0158 0003 0250 0002 0201 0001 0208 0001

Assimilatory N reduction 0043 0172 0098 0071 0043 017 00502 0066Dissimilatory N reduction 0090 0045 0145 0016 0165 0002 0108 0001Nitrification 0015 0362 0045 0275 0100 0027 0067 0048Denitrification 0088 0049 0111 0051 0169 0002 0124 0001N fixation 0156 0004 0202 0006 0185 0001 0174 0001Phosphorus 0115 0029 0119 0042 0141 0004 0145 0003Sulfur 0166 0003 0232 0002 0189 0001 0199 0001a The significant values (P 005) are indicated in boldface

FIG 2 Canonical correspondence analysis (CCA) of GeoChip hybridization signal intensities and environmental variables that were significantly related tomicrobial variation Subsets of soil variables distance and plant diversity were selected for analysis on the basis of variance in inflation factors Distance wasrepresented by eight primary variables from principal coordinates of neighbor matrices (PCNM) and the first two were used for CCA Triangles represent 12Dsample data (control) and circles represent 112C sample data (fertilization) Colors from dark to bright represent samples from the center to the periphery Therelationship was significant (P 0005)

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change of microorganisms in space are much lower than those ofother organisms (plants and animals)

DISCUSSION

Spatial scaling of biodiversity is a central issue in ecology It hasbeen shown that anthropogenic activities influence the SARs ofanimals and plants (27 30ndash32) However the impact of anthro-pogenic activities on microbial spatial scaling has rarely been ex-plored In this study our results showed that more than 150 yearsof fertilization has had significant impacts on the spatial scaling ofsoil microbial communities and plant species simultaneously

A number of short-term studies observed that fertilization al-tered soil microbial biomass community structure and certainfunctional groups (eg autotrophic ammonia-oxidizing bacteria)(20 33) Such changes of microbes and fungi were more evident in

studies of longer duration and with larger amounts of fertilizerused (20) For example long-term application of inorganic N fer-tilizer (140 years) caused significant differences in the ability ofsoil to oxidize CH4 while no significant short-term effects couldbe observed (34) Moreover microbial community compositionand abundance are influenced by changes in soil characteristicswhich could be more significant in long-term fertilization re-gimes For example it has been proven that all forms of soil P areenriched when fertilized for over 100 years (26) In this study theexperimental plots have been fertilized for more than 150 yearswhich is the longest grassland experiment available in the worldThus we believe that the changes of microbial community struc-ture observed in this site could represent permanent and stablerather than transient responses of microbial communities to fer-tilization Consequently the estimated z values are likely to be areliable reflection of the effects of fertilization on the spatial scal-ing of soil microbial communities

Microbial TARs can be affected by long-term N fertilization indifferent ways First long-term fertilization may reduce the heter-ogeneity of nutrient availability allowing a few species that areadapted for higher nutrient levels to spread into and dominatelocal communities Second long-term fertilization may unevenlymagnify the initial differences resulting in more divergent spatialpatterns Our study showed that long-term nutrient fertilizationsignificantly increased the slopes of both microbial GARs (P 00001) and plant TARs (P 00001) supporting the second pos-sibility This is also consistent with a previous observation show-ing that N supply could cause communities to diverge to a moreheterogeneous pattern (35) Slight variations in initial speciescomposition could be unevenly magnified in the fertilized treat-ments as observed from the data in Fig S4 in the supplementalmaterial Agricultural practice could increase certain microbialspecies growth (36 37) and community interactions (38ndash40) re-sulting in a decrease in species evenness and eventually speciesrichness through their spatial aggregation around plants thedominance of some species and the loss of rare species (41) Thiscould also happen with soil microbes For example N fertilizationresulted in the dominance of Nitrosospira cluster 3 in soil (42) and

FIG 3 Variation partitioning analysis (VPA) of microbial distribution patterns explained by soil geochemical properties (S) fertilization (F) spatial distance(D) and plant diversity (P) Each diagram represents the biological variation partitioned into the relative effects of each factor or a combination of factorsDistance is represented by eight primary variables from principal coordinates of neighbor matrices (PCNM) analysis Soil geochemical properties included soilpH and moisture Fertilization was quantified by total nitrogen and ammonium

FIG 4 A comparison of z values of macroorganism and microbial taxonomicgroups Data were obtained from supplemental data of Drakare et al (1) ex-cept for groups that are less defined taxonomically Some recent data for mi-crobial communities were also included A total of 806 datasets were analyzedError bars show standard deviations

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pronounced shifts in bacterial community composition (18) Fur-ther analysis with metagenomic sequencing and molecular eco-logical networks (43 44) will be helpful to validate the microbialspecies spatial aggregation and competition processes

We observed that long-term inorganic fertilization not onlyincreased microbial and plant spatial turnover but also decreasedthe intercept of the GAR curves (c values) sometimes called theheight of the curve which were significantly different (lnccontrol 3582 lncfertilization 3509 P 0001) as shown in Fig 1 Inspecies-area relationships diversity can be measured as theheight of the curve at a given area (45) so the lower curves indicatethat long-term fertilization decreased both plant and microbial diversity At the smallest spatial scales (01 m2) the total genenumbers were 2615 74 in the control plot and 1771 346 inthe fertilized plot At the plot scale (5 m2) the total gene numberswere 3655 96 in the control plot and 3023 165 in the fertil-ized plot The diversity was reduced more at the smallest spatialscales than at the largest plot scale causing steeper spatial turnover(z values)

It has been recognized that plant and soil microbial communi-ties are tightly linked together (1 46 47) Here we also observedsignificant correlations between plant diversity and microbialfunctional genes (P 005) (see Table S2 in the supplementalmaterial) Plant diversity contributed ~5 to microbial commu-nity variation equal to soil fertilization and spatial distance Amore divergent spatial pattern of plant species (Fig S4) and lowerplant species diversity ( diversity) (Fig S5) under long-term Nfertilization may result in a more heterogeneous habitat such asthe rhizospheric environment (48) Different microbial speciesmay be favored in different patches leading to greater spatialchange in community composition Furthermore soils with dif-ferent grass species differed in the composition and abundance ofmicrobial communities (48 49) In this study more plant specieswere found in the control plot including among different quad-rats Festuca rubra (905) Briza media (714) Agrostis capil-laris (524) Leontodon hispidus (429) and Ranunculus sp(429) while only Poa pratensis (810) was dominant amongthe quadrats of the fertilized plot with other plant species ac-counting for less than 40 (Table S3) Since plant species differ inboth the quantity and quality of nutrients they return to soil dif-ferent dominant plant species could have important effects oncomponents of the soil available to microbes and the processesthat they regulate (47) which then affects the microbial spatialpatterns of different functional groups For example soil C inputvaried among plant species (50) and could be altered by N addi-tion (51) Thus microbial communities functioning in C degra-dation may be more heterogeneous with different C input in thefertilized plot resulting in a higher spatial turnover (higher z val-ues) In all cases the effect of agricultural practice on microbialspatial patterns and the linkage between these patterns and theplant is interesting yet little studied More systematic studies bothempirical and theoretical are needed to generalize these phenom-ena and to elucidate the underlying mechanisms

Current knowledge about microbial TARs largely comes fromstudies of bacterial communities and the extent to which thisapplies to fungal communities which have very different life his-tories and dispersal mechanisms remains to be elucidated It wasrecently reported that spatial scaling of arbuscular mycorrhizalfungal diversity is affected by farming practice and that the z valueswere greater under organic than under conventional farm man-

agement 061 and 045 respectively (52) Here we also observedthat long-term fertilization significantly increased the z values offungi which were 00704 in the fertilized plot and 00604 in thecontrol plot It has been proposed that N fertilization may affectfungal communities by altering plant C inputs (53) Thus moreinternally heterogeneous patterns of plants under N addition mayresult in steeper spatial changes in fungal communities In addi-tion the difference in estimated z values in these two studies mightbe due to the different approaches used with different ecosystemsHere we estimated the TARs of all fungi in bulk soil of grasslandand used a microarray hybridization-based approach which con-tains tens of thousands of functional gene markers so that manymicrobial populations and functional groups can be simultane-ously detected at the whole-community-wide scale (9) Thus anydirect comparison of z values with different methods would bedifficult

Generally the mean z value for plants was 0306 (0018)(Fig 4) which was significantly affected by variables in terms ofthe sampling schemes spatial scales and habitats involved (31 5455) In this study the observed z values for plants were 0225 and0419 in the control and fertilization plots respectively Our re-sults are generally in accordance with a previous metastudy thatshowed that N enrichment reduced plant diversity within plotsby an average of 25 (ranging from a reduction of 61 to anincrease of 5) and frequently enhanced diversity (31) Theenhancement of diversity was proposed to be related to in-creases in productivity following nutrient enrichment (56 57)

The factors driving microbial spatial patterns could be verycomplex depending on both environmental factors (eg tempo-ral variation spatial heterogeneity and soil properties and distur-bances) and biotic factors (eg reproductive behavior dispersalability competition niche differentiation and extinction and in-teractions with the plant community) (55 58 59) Soil biogeo-chemical properties fertilization spatial distance and plant spe-cies diversity have influences on the diversity patterns of microbialcommunities in the grassland soils because significant correla-tions were detected for all functional genes and most of the func-tional gene groups examined using both partial Mantel test andvariation partition analysis (see Table S2 in the supplemental ma-terial) However all the environmental factors examined contrib-uted only a small portion to the total variation in microbial func-tional structure (216) (Fig 2) Similar to other studies (6 9) alarge percentage of the total variation remained unexplainedwhich could be due to unmeasured biotic and abiotic factors suchas time span the small spatial scale and ecologically neutral pro-cesses of diversification (3 6 9 59ndash61) The knowledge gained inthis study may only be applicable at the meter scale used here andmay not hold at smaller (eg micrometer or soil aggregate scales)or larger (eg tens of thousands of kilometers) scales of study Toavoid over- or underestimating the effects of agricultural practicelike fertilization on microbial spatial scaling further work is re-quired to address the importance of multiple spatial scales forunderstanding the influence of human perturbations on micro-bial biogeography In addition it should be noted that if onewould like to experimentally test the differences of z values be-tween treatment and control nested samples (21 in this case) froma minimum of three biological replicates under each condition arerequired However since the plots of the Park Grass Experimentwere set up 150 years ago and have received different amounts andcombinations of inorganic N P and K fertilizers and lime over the

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years no biologically replicated plots under each condition areavailable As a result we were unable to identify biologically rep-licated plots to perform such experimental tests Due to high het-erogeneity of the soil environment the results from the currentstudy based on a single plot might underestimate the microbialspatial turnover rates Thus more biologically replicated plotsshould be considered in examining microbial spatial patterns infuture studies

In conclusion this study examined spatial patterns of micro-bial communities in response to over 150 years of fertilization atthe Rothamsted Research site and demonstrated spatial scaling ofmicrobial biodiversity and its relationship to plant diversity Thelong-term experiment enabled us to avoid transient responsesand instead provided a long-term response to assess the influenceof farming practice on spatial patterns of plant and microbialcommunities The results showed that long-term fertilization hasdramatic impacts on the spatial scaling of microbial communitiesThese findings make a fundamental contribution to predictiveunderstanding of microbial biogeography

MATERIALS AND METHODSDetails for all methods are provided in Text S1 in the supplemental ma-terial Briefly soil samples were taken from the PGE using a spatiallyexplicit nested sampling design (01 m2 025 m2 1 m2 25 m2 and 5 m2)in two treatment areas of which one was fertilized with inorganic fertil-izers for more than 150 years (112C) and the other was a control with nofertilizer or lime (12D) in September 2009 Plant species richness was alsorecorded in each of the nested squares (0025 m2 01 m2 0625 m21 m2 625 m2 and 25 m2) in plots 112C and 12D Soil geochemicalvariables were measured including soil pH moisture total N (TN)total C (TC) NO3

-N and NH4-N by Brookside Laboratories Inc

(New Knoxville OH)GeoChip 30 was used for analyzing microbial community functional

gene structure it is a functional gene array containing ~28000 probescovering approximately 57000 gene variants from 292 functional genefamilies involved in C N P and S cycling energy metabolism antibioticresistance metal resistance and organic contaminant degradationGeoChip hybridization imaging and data preprocessing were describedpreviously (62ndash64)

The power law form of GAR (S cAz) was fitted by logarithmic trans-formation The exponent z was estimated by linear regression as followslogS logc zlogA where S is observed gene richness (Sobs) and A is thearea in the nested design (01 m2 025 m2 1 m2 25 m2 or 5 m2) Thelog-based linear equation was applied to all individual functional genes aswell as functional groups and phylogenetic groups The estimated z valueswere compared with the observed z values by one-tailed t test after 10000bootstraps between area and richness (9) All the analyses were performedin R (version 2111 httpwwwr-projectorg) with packages vegan andecodist

SUPPLEMENTAL MATERIALSupplemental material for this article may be found at httpmbioasmorglookupsuppldoi101128mBio00240-15-DCSupplemental

Text S1 PDF file 01 MBFigure S1 PDF file 01 MBFigure S2 PDF file 03 MBFigure S3 PDF file 004 MBFigure S4 PDF file 01 MBFigure S5 PDF file 005 MBTable S1 PDF file 005 MBTable S2 PDF file 01 MBTable S3 PDF file 005 MB

ACKNOWLEDGMENTS

This research was supported by National Natural Scientific Foundation ofChina (grants 41430856 and 41371256) Strategic Priority Research Pro-gram of the Chinese Academy of Sciences (grants XDB15010100 andXDB15010200) an Underwood Fellowship from the United KingdomBiotechnology and Biological Sciences Research Council to LW the USNational Science Foundation (NSF) MacroSystems Biology program un-der contract NSF EF-1065844 the United States Department of Agricul-ture (project 2007-35319-18305) through NSF-USDA Microbial Obser-vatories Program the State Key Joint Laboratory of EnvironmentSimulation and Pollution Control and Foundation for DistinguishedYoung Talents in State Key Laboratory of Soil and Sustainable Agriculture(grant Y412010008)

All authors contributed intellectual input and assistance to this studyand the manuscript preparation JZ and YL developed the originalframework YL LW IC KX YY CB JV YD ZH SH SMJS and BS contributed reagents and data analysis YL and LW didGeoChip analysis YL and J Z wrote the paper with help from PH ICand SM

REFERENCES1 Bardgett R Wardle D 2010 Aboveground-belowground linkages biotic

interactions ecosystem processes and global change Oxford UniversityPress Oxford United Kingdom

2 Hanson CA Fuhrman JA Horner-Devine MC Martiny JB 2012 Be-yond biogeographic patterns processes shaping the microbial landscapeNat Rev Microbiol 10497ndash506 httpdxdoiorg101038nrmicro2795

3 Martiny JB Eisen JA Penn K Allison SD Horner-Devine MC 2011Drivers of bacterial beta-diversity depend on spatial scale Proc Natl AcadSci U S A 1087850 ndash7854 httpdxdoiorg101073pnas1016308108

4 Horner-Devine MC Lage M Hughes JB Bohannan BJ 2004 A taxa-area relationship for bacteria Nature 432750 ndash753 httpdxdoiorg101038nature03073

5 Wang J Shen J Wu Y Soininen J Stegen J He JC Liu X Zhang LZhang E Zhang E 2013 Phylogenetic beta diversity in bacterial assem-blages across ecosystems deterministic versus stochastic processes ISMEJ 71310 ndash1321 httpdxdoiorg101038ismej201330

6 Ramette A Tiedje JM 2007 Biogeography an emerging cornerstone forunderstanding prokaryotic diversity ecology and evolution Microb Ecol53197ndash207 httpdxdoiorg101007s00248-005-5010-2

7 Green J Bohannan BJ 2006 Spatial scaling of microbial biodiversity TrendsEcol Evol 21501ndash507 httpdxdoiorg101016jtree200606012

8 Ranjard L Dequiedt S Chemidlin Preacutevost-Boureacute N Thioulouse J SabyNPA Lelievre M Maron PA Morin FER Bispo A Jolivet C ArrouaysD Lemanceaul P 2013 Turnover of soil bacterial diversity driven bywide-scale environmental heterogeneity Nat J Commun 41434

9 Zhou J Kang S Schadt CW Garten CT Jr 2008 Spatial scaling offunctional gene diversity across various microbial taxa Proc Natl Acad SciU S A 1057768 ndash7773 httpdxdoiorg101073pnas0709016105

10 Chapin FS III Zavaleta ES Eviner VT Naylor RL Vitousek PMReynolds HL Hooper DU Lavorel S Sala OE Hobbie SE Mack MCDiacuteaz S 2000 Consequences of changing biodiversity Nature 405234 ndash242 httpdxdoiorg10103835012241

11 Noguez AM Arita HT Escalante AE Forney LJ Garciacutea-Oliva F SouzaV 2005 Microbial macroecology highly structured prokaryotic soil as-semblages in a tropical deciduous forest Glob Ecol Biogeogr 14241ndash248httpdxdoiorg101111j1466-822X200500156x

12 Fierer N Jackson RB 2006 The diversity and biogeography of soil bac-terial communities Proc Natl Acad Sci U S A 103626 ndash 631 httpdxdoiorg101073pnas0507535103

13 Sayer EJ Wagner M Oliver AE Pywell RF James P Whiteley ASHeard MS 2013 Grassland management influences spatial patterns ofsoil microbial communities Soil Biol Biochem 6161ndash 68 httpdxdoiorg101016jsoilbio201302012

14 Reche I Pulido-Villena E Morales-Baquero R Casamayor EO 2005Does ecosystem size determine aquatic bacterial richness Ecology 861715ndash1722 httpdxdoiorg10189004-1587

15 Van der Gucht K Cottenie K Muylaert K Vloemans N Cousin SDeclerck S Jeppesen E Conde-Porcuna JM Schwenk K Zwart GDegans H Vyverman W De Meester L 2007 The power of species

Fertilization and Microbial Spatial Scaling

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orgD

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sorting local factors drive bacterial community composition over a widerange of spatial scales Proc Natl Acad Sci U S A 10420404 ndash20409 httpdxdoiorg101073pnas0707200104

16 Zinger L Boetius A Ramette A 2014 Bacterial taxa-area and distance-decay relationships in marine environments Mol Ecol 23954 ndash964 httpdxdoiorg101111mec12640

17 Stevens CJ Dise NB Mountford JO Gowing DJ 2004 Impact ofnitrogen deposition on the species richness of grasslands Science 3031876 ndash1879 httpdxdoiorg101126science1094678

18 Ramirez KS Lauber CL Knight R Bradford MA Fierer N 2010Consistent effects of nitrogen fertilization on soil bacterial communities incontrasting systems Ecology 913463ndash3470 httpdxdoiorg10189010-04261

19 Kaštovskaacute E Šantrukovaacute H Picek T Vaškovaacute M Edwards KR 2010Direct effect of fertilization on microbial carbon transformation in grass-land soils in dependence on the substrate quality J Plant Nutr Soil Sci173706 ndash714 httpdxdoiorg101002jpln200900013

20 Treseder KK 2008 Nitrogen additions and microbial biomass a meta-analysis of ecosystem studies Ecol Lett 111111ndash1120 httpdxdoiorg101111j1461-0248200801230x

21 Rousk J Brookes PC Baringaringth E 2011 Fungal and bacterial growth re-sponses to N fertilization and pH in the 150-year lsquoPark Grassrsquo UK grass-land experiment FEMS Microbiol Ecol 7689 ndash99 httpdxdoiorg101111j1574-6941201001032x

22 Vitousek PM Aber JD Howarth RW Likens GE Matson PA SchindlerDW Schlesinger WH Tilman DG 1997 Human alteration of the globalnitrogen cycle sources and consequences Ecol Appl 7737ndash750 httpdxdoiorg1018901051-0761(1997)007[0737HAOTGN]20CO2

23 Clark CM Cleland EE Collins SL Fargione JE Gough L Gross KLPennings SC Suding KN Grace J 2007 Environmental and plant com-munity determinants of species loss following nitrogen enrichment EcolLett 10596 ndash 607 httpdxdoiorg101111j1461-0248200701053x

24 Wang FY Hu JL Lin XG Qin SW Wang JH 2011 Arbuscular mycor-rhizal fungal community structure and diversity in response to long-termfertilization a field case from China World J Microbiol Biotechnol 2767ndash74 httpdxdoiorg101007s11274-010-0427-2

25 Silvertown J Poulton P Johnston E Edwards G Heard M Biss PM2006 The Park Grass Experiment 1856-2006 its contribution to ecologyJ Ecol 94801ndash 814 httpdxdoiorg101111j1365-2745200601145x

26 Crews TE Brookes PC 2014 Changes in soil phosphorus forms throughtime in perennial versus annual agroecosystems Agric Ecosyst Environ184168 ndash181 httpdxdoiorg101016jagee201311022

27 Crawley MJ Johnston AE Silvertown J Dodd M de Mazancourt CHeard MS Henman DF Edwards GR 2005 Determinants of speciesrichness in the Park Grass Experiment Am Nat 165179 ndash192 httpdxdoiorg101086427270

28 Silvertown J Biss PM Freeland J 2009 Community genetics resourceaddition has opposing effects on genetic and species diversity in a 150-yearexperiment Ecol Lett 12165ndash170 httpdxdoiorg101111j1461-0248200801273x

29 Fierer N Bradford MA Jackson RB 2007 Toward an ecological classi-fication of soil bacteria Ecology 881354 ndash1364 httpdxdoiorg10189005-1839

30 Dumbrell AJ Clark EJ Frost GA Randell TE Pitchford JW Hill JK2008 Changes in species diversity following habitat disturbance are de-pendent on spatial scale theoretical and empirical evidence J Appl Ecol451531ndash1539 httpdxdoiorg101111j1365-2664200801533x

31 Chalcraft DR Cox SB Clark C Cleland EE Suding KN Weiher EPennington D 2008 Scale-dependent responses of plant biodiversity tonitrogen enrichment Ecology 892165ndash2171 httpdxdoiorg10189007-09711

32 Tittensor DP Micheli F Nystroumlm M Worm B 2007 Human impactson the species-area relationship reef fish assemblages Ecol Lett 10760 ndash772 httpdxdoiorg101111j1461-0248200701076x

33 He JZ Shen JP Zhang LM Zhu YG Zheng YM Xu MG Di H 2007Quantitative analyses of the abundance and composition of ammonia-oxidizing bacteria and ammonia-oxidizing archaea of a Chinese uplandred soil under long-term fertilization practices Environ Microbiol92364 ndash2374 httpdxdoiorg101111j1462-2920200701358x

34 Huumltsch BW Webster CP Powlson DS 1993 Long-term effects of nitro-gen fertilization on methane oxidation in soil of the broadbalk wheatexperiment Soil Biol Biochem 251307ndash1315 httpdxdoiorg1010160038-0717(93)90045-D

35 Houseman GR Mittelbach GG Reynolds HL Gross KL 2008 Pertur-bations alter community convergence divergence and formation of mul-tiple community states Ecology 892172ndash2180 httpdxdoiorg10189007-12281

36 Hopkins DW Shiel RS 1996 Size and activity of soil microbial commu-nities in long-term experimental grassland plots treated with manure andinorganic fertilizers Biol Fertil Soils 2266 ndash70 httpdxdoiorg101007BF00384434

37 Enwall K Philippot L Hallin S 2005 Activity and composition of thedenitrifying bacterial community respond differently to long-term fertil-ization Appl Environ Microbiol 718335ndash 8343 httpdxdoiorg101128AEM71128335-83432005

38 Wang F Zhou J Sun B 2014 Structure of functional ecological networksof soil microbial communities for nitrogen transformations and their re-sponse to cropping in major soils in eastern China Chinese Sci Bull 59387ndash396 httpdxdoiorg101360972013-751

39 Aerts R 1999 Interspecific competition in natural plant communitiesmechanisms trade-offs and plantndashsoil feedbacks J Exp Bot 5029 ndash37

40 Wedin D Tilman D 1993 Competition among grasses along a nitrogengradient initial conditions and mechanisms of competition Ecol Monogr63199 ndash229 httpdxdoiorg1023072937180

41 Suding KN Collins SL Gough L Clark C Cleland EE Gross KLMilchunas DG Pennings S 2005 Functional- and abundance-basedmechanisms explain diversity loss due to N fertilization Proc Natl AcadSci U S A 1024387ndash 4392 httpdxdoiorg101073pnas0408648102

42 Chu H Fujii T Morimoto S Lin X Yagi K Hu J Zhang J 2007Community structure of ammonia-oxidizing bacteria under long-term appli-cation of mineral fertilizer and organic manure in a sandy loam soil ApplEnviron Microbiol 73485ndash491 httpdxdoiorg101128AEM01536-06

43 Zhou J Deng Y Luo F He Z Yang Y 2011 Phylogenetic molecularecological network of soil microbial communities in response to elevatedCO2 mBio 2(4)00122-11 httpdxdoiorg101128mBio00122-11

44 Zhou J Deng Y Luo F He Z Tu Q Zhi X 2010 Functional molecularecological networks mBio 1(4)e00169-10 httpdxdoiorg101128mBio00169-10

45 Scheiner SM 2004 A meacutelange of curvesmdashfurther dialogue about species-area relationships Glob Ecol Biogeogr 13479 ndash 484 httpdxdoiorg101111j1466-822X200400127x

46 Regan KM Nunan N Boeddinghaus RS Baumgartner V Berner DBoch S Oelmann Y Overmann J Prati D Schloter M Schmitt BSorkau E Steffens M Kandeler E Marhan S 2014 Seasonal controls ongrassland microbial biogeography are they governed by plants abioticproperties or both Soil Biol Biochem 7121ndash30 httpdxdoiorg101016jsoilbio201312024

47 Wardle DA Bardgett RD Klironomos JN Setaumllauml H van der PuttenWH Wall DH 2004 Ecological linkages between aboveground and be-lowground biota Science 3041629 ndash1633 httpdxdoiorg101126science1094875

48 Bardgett R Mawdsley J Edwards S Hobbs P Rodwell J Davies W1999 Plant species and nitrogen effects on soil biological properties oftemperate upland grasslands Funct Ecol 13650 ndash 660

49 Griffiths BS Welschen R van Arendonk JJCM Lambers H 1992 Theeffect of nitrate-nitrogen supply on bacteria and bacterial-feeding fauna inthe rhizosphere of different grass species Oecologia 91253ndash259 httpdxdoiorg101007BF00317793

50 Kemp PR Waldecker DG Owensby CE Reynolds JF Virginia RA1994 Effects of elevated CO2 and nitrogen fertilization pretreatments ondecomposition on tallgrass prairie leaf litter Plant Soil 165115ndash127httpdxdoiorg101007BF00009968

51 Liu L Greaver TL 2010 A global perspective on belowground carbondynamics under nitrogen enrichment Ecol Lett 13819 ndash 828 httpdxdoiorg101111j1461-0248201001482x

52 van der Gast CJ Gosling P Tiwari B Bending GD 2011 Spatial scalingof arbuscular mycorrhizal fungal diversity is affected by farming practiceEnviron Microbiol 13241ndash249 httpdxdoiorg101111j1462-2920201002326x

53 Allison SD Hanson CA Treseder KK 2007 Nitrogen fertilization re-duces diversity and alters community structure of active fungi in borealecosystems Soil Biol Biochem 391878 ndash1887 httpdxdoiorg101016jsoilbio200702001

54 Crawley MJ Harral JE 2001 Scale dependence in plant biodiversityScience 291864 ndash 868 httpdxdoiorg101126science2915505864

55 Drakare S Lennon JJ Hillebrand H 2006 The imprint of the geograph-

Liang et al

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orgD

ownloaded from

ical evolutionary and ecological context on species-area relationshipsEcol Lett 9215ndash227 httpdxdoiorg101111j1461-0248200500848x

56 Chase JM 2003 Community assembly when should history matterOecologia 136489 ndash 498 httpdxdoiorg101007s00442-003-1311-7

57 Liira J Ingerpuu N Kalamees R Moora M Paumlrtel M Puumlssa K Roosa-luste E Saar L Tamme R Zobel K Zobel M 2012 Grassland diversityunder changing productivity and the underlying mechanismsmdashresults ofa 10-yr experiment J Veg Sci 23919 ndash930 httpdxdoiorg101111j1654-1103201201409x

58 Wang J Soininen J Zhang Y Wang B Yang X Shen J 2012 Patternsof elevational beta diversity in micro- and macroorganisms Glob EcolB i o g e o g r 2 1 7 4 3 ndash 7 5 0 h t t p d x d o i o r g 1 0 1 1 1 1 j 1 4 6 6-8238201100718x

59 Martiny JB Bohannan BJ Brown JH Colwell RK Fuhrman JA GreenJL Horner-Devine MC Kane M Krumins JA Kuske CR Morin PJNaeem S Ovrearings L Reysenbach AL Smith VH Staley JT 2006 Micro-bial biogeography putting microorganisms on the map Nat Rev Micro-biol 4102ndash112 httpdxdoiorg101038nrmicro1341

60 Zhou J Deng Y Zhang P Xue K Liang Y Van Nostrand JD Yang Y He ZWu L Stahl DA Hazen TC Tiedje JM Arkin AP 2014 Stochasticity succes-sion and environmental perturbations in a fluidic ecosystem Proc Natl Acad SciU S A 111E836ndashE845 httpdxdoiorg101073pnas1324044111

61 Zhou J Liu W Deng Y Jiang Y- Xue K He Z Van Nostrand JD WuL Yang Y Wang A 2013 Stochastic assembly leads to alternative com-munities with distinct functions in a bioreactor microbial communitymBio 4(2)e00584-12 httpdxdoiorg101128mBio00584-12

62 Zhou J Bruns MA Tiedje JM 1996 DNA recovery from soils of diversecomposition Appl Environ Microbiol 62316 ndash322

63 Wu L Liu X Schadt CW Zhou J 2006 Microarray-based analysis ofsubnanogram quantities of microbial community DNAs by using whole-community genome amplification Appl Environ Microbiol 724931ndash 4941 httpdxdoiorg101128AEM02738-05

64 Liang Y He Z Wu L Deng Y Li G Zhou J 2010 Development of acommon oligonucleotide reference standard for microarray data normaliza-tion and comparison across different microbial communities Appl EnvironMicrobiol 761088ndash1094 httpdxdoiorg101128AEM02749-09

Fertilization and Microbial Spatial Scaling

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on October 31 2020 by guest

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orgD

ownloaded from