# 2003 Oxford University Press Nucleic Acids Research , 2003 , Vol . 31 , No. 13 3423 3428 DOI : 10.1093 / nar/gkg614 Pfold : RNA secondary structure prediction using stochastic context-free grammars Bjarne Knudsen * and Jotun Hein1 BiRC -LRB- Bioinformatics Research Center -RRB- , University of Aarhus , H egh Guldbergsgade 10 , Building 090 , 8000 Arhus C , Denmark and 1Department of Statistics , Oxford University , The Peter Medawar Building for Pathogen Research , South Parks Road , Oxford OX1 3SY , UK Received February 15 , 2003 ; Revised and Accepted April 5 , 2003 ABSTRACT RNA secondary structures are important in many biological processes and efficient structure prediction can give vital directions for experimental investigations . Many available programs for RNA secondary structure prediction only use a single sequence at a time . This may be sufficient in some applications , but often it is possible to obtain related RNA sequences with conserved secondary structure . These should be included in structural analyses to give improved results . This work presents a practical way of predicting RNA secondary structure that is especially useful when related sequences can be obtained . The method improves a previous algorithm based on an explicit evolutionary model and a probabilistic model of structures . Predictions can be done on a web server at http://www.daimi.au . dk / ~ compbio/pfold . A thorough evaluation of performance under different circumstances is also included . This new method called Pfold is available through a web-based server www.daimi.au . dk / ~ compbio/pfold . METHODS Pfold is based on the KH-99 algorithm , which was only useful for a limited number of sequences due to its large computation time . This work makes the algorithm practically useful for larger numbers of sequences . The main concerns are treatment of gaps , computational speed and robustness . The KH-99 algorithm The KH-99 algorithm uses a stochastic context-free grammar -LRB- SCFG -RRB- to produce a prior probability distribution of RNA structures . Given an alignment and a phylogenetic tree relating the sequences , posterior probabilities of the structures can be calculated using the inside outside algorithm -LRB- 13 -RRB- . The posterior probability is based on individual probabilities for alignment columns or pairs of columns in the case of a base-pair . Column probabilities are calculated using the likelihood approach by Felsenstein -LRB- 14 -RRB- . The evolution of column pairs is modelled using a rate matrix for base-pairs -LRB- i.e. a 16 by 16 matrix -RRB- . The most likely structure is found using the CYK algorithm -LRB- 15 -RRB- . The tree is estimated using a maximum likelihood approach in the SCFG model described . Both the evolutionary and structural parameters of the KH99 model are based on extensive tRNA and large subunit rRNA databases -LRB- 12 -RRB- . Gaps Treating gaps in an appropriate way is a returning problem in biological sequence analysis . The best way to deal with gaps would probably be to make an explicit evolutionary model for insertions and deletions , and use that in the sequence analysis . Unfortunately , such calculations are often complicated , as in statistical alignment -LRB- 16,17 -RRB- . Two simpler ideas are to treat INTRODUCTION RNA structures are essential in many biological processes and are often conserved in evolution . Examples of such conserved structures are found in tRNA -LRB- 1 -RRB- , rRNA -LRB- 2,3 -RRB- , tmRNA -LRB- 4 -RRB- , RNase P RNA -LRB- 5 -RRB- and SRP RNA -LRB- 6 -RRB- . Many computational methods have been developed for predicting RNA structures . Early algorithms were made by Nussinov et al. -LRB- 7 -RRB- and Zuker and Stiegler -LRB- 8 -RRB- . Zuker 's energy calculations have been further improved -LRB- 9 11 -RRB- and are probably the most widely used RNA secondary structure prediction method today -LRB- with the MFOLD program -RRB- . The work of Knudsen and Hein -LRB- 12 -RRB- -LRB- here denoted as the KH-99 algorithm -RRB- combines an explicit evolutionary model of RNA sequences with a probabilistic model for secondary structures . It assumes an alignment and gives one common structural prediction for all the sequences . This work improves the KH-99 algorithm primarily by making it faster and more robust toward alignment errors . * To whom correspondence should be addressed at Department of Zoology , Box 118525 , University of Florida , Gainesville , FL 32611-8525 , USA . Tel : 1 3523927552 ; Fax : 1 3523923704 ; Email : bk@birc.dk Nucleic Acids Research , Vol . 31 , No. 13 # Oxford University Press 2003 ; all rights reserved 3424 Nucleic Acids Research , 2003 , Vol . 31 , No. 13 Figure 2 . A structure prediction for three hypothetical sequences . In the top alignment , gaps are treated as unknown nucleotides . The structure , shown as parentheses , include pairs between nucleotides and gaps . In the parenthesis notation , corresponding parentheses indicate positions forming base-pairs . In the bottom alignment , the columns with gaps have been left out of the prediction , because < 75 % of the sequences have nucleotides in these positions . given position is known to be a pyrimidine , its probability of being a U is set to one , and its probability of being a C is also set to one . Using this method , any symbols of the extended nucleotide alphabet can be treated correctly by Pfold . This is in accordance with Felsenstein -LRB- 14 -RRB- . Figure 1 . The effect of treating gaps as unknown nucleotides . Only a single column from the alignment is considered with the nucleotides put at the leaves of the phylogenetic tree . The two trees have identical probabilities since leaves with gaps can be removed . Tree estimation In the KH-99 algorithm , the tree was estimated through a maximum likelihood method using the SCFG model . While this gave good results and was interesting with respect to phylogenetic analysis , it was slow . A much faster method is to estimate the tree first . This can be done using standard methods . In Pfold , pairwise distances between sequences are calculated using maximum likelihood . The rate matrix used should correspond as closely as possible to what is used in the KH-99 algorithm . Since the tree is calculated before the structure has been estimated , a single rate matrix has to be used for this purpose . It was made from the KH-99 algorithm by summing the loop rate matrix and a reduction of the base-pair rate matrix to single positions . The rate matrices were weighted with the probabilities that a given position is in a loop region or a stem region , respectively . The tree is calculated from pairwise distances using the neighbour joining algorithm -LRB- 20 -RRB- and adjusting branch lengths to maximum likelihood estimates . This gives a large increase in speed , since the inside outside calculations only need to be performed once , as opposed to the multiple iterations used in the KH-99 method for estimating the tree . Robustness Pfold assumes that all sequences have exactly the same structure . This means that a single sequence with a slightly different structure might ruin a prediction . The same situation applies for alignment errors and sequencing errors . When a single error might change a prediction significantly , the method is not robust -LRB- the top of Fig. 3 -RRB- . A way to make the algorithm more robust is to let any nucleotide have a small probability of being any other nucleotide . The interpretation of this is most obvious in terms of sequencing errors , but the method works for alignment errors and structure differences , too . Figure 3 shows how gaps as a fifth nucleotide or to treat them as unknown nucleotides . When using an evolutionary model , a number of problems arise from treating a gap as a fifth nucleotide . First , the frequency of gaps will depend on how many sequences are being analysed and on their evolutionary distance . Furthermore , gaps can not be viewed as evolving in the same way as a nucleotide , thus the rates of evolution are difficult to specify . This approach does , however , have the advantage that it includes the potentially useful information from the insertions and deletions . This method was successfully used in the RNA part of the non-coding RNA gene finding algorithm by Rivas and Eddy -LRB- 18 -RRB- . When treating gaps as unknown nucleotides , a gapped sequence position should have probability one for any nucleotide . This has the advantage that the probability of a column with gaps is equal to the probability of the same column in an alignment without the gapped sequences , and the tree correspondingly pruned -LRB- Fig. 1 -RRB- . Pfold uses the latter approach , which is often done in situations where different alignment columns are looked at individually -LRB- 19 -RRB- . In RNA structure prediction , pairs of columns are analysed together , which can give rise to some difficulties : when treating gaps as unknowns , gaps can form pairs with nucleotides -LRB- the top of Fig. 2 -RRB- . This problem was handled by removing columns where less than 75 % of the sequences have nucleotides -LRB- the bottom of Fig. 2 -RRB- . Unknown nucleotides In biological sequences , some nucleotides may be unknown or only partial information may be available . These situations can be treated by letting the unknown nucleotide have a probability of one for each of the possible nucleotides . This means that if a Nucleic Acids Research , 2003 , Vol . 31 , No. 13 3425 of the plot -LRB- Fig. 5 -RRB- . These calculations resemble the work by McCaskill -LRB- 21 -RRB- . Making the obvious individual structure changes Sometimes , a structure in a single sequence will have a slightly longer stem than its homologues . This can be incorporated in the prediction by extending a stem if immediate neighbours can form base pairs . Another obvious change is to remove nonstandard base pairs from individual sequences . This is done after the structure predictions given by Pfold . INPUT AND OUTPUT introduction of this probability changes the results . In Pfold this probability was set to 1 % . Partially known structure Often , something is known about the structure being predicted and including this knowledge in the analysis can give improved results . Different kinds of knowledge can be used : That two given columns form a pair together . That a given column is involved in a pair . That a given column is unpaired . This can all be included in the calculations by letting the structures that do not satisfy the previous knowledge have a probability of zero . This approach does not change relative prior distributions of allowed structures . As a side note , no loops of length two are allowed in this implementation , as opposed to the KH-99 algorithm . This was implemented by disallowing pairs between positions of distance less than four . What structure should be chosen ? A prediction program should of course report a single prediction as the best . The CYK algorithm for finding the most likely parsing from the grammar is often used -LRB- 15 -RRB- . An alternative to this has been chosen here : Pfold reports the nested structure with the highest expected number of correct predictions . Appendix 1 -LRB- available as Supplementary Material -RRB- describes how this structure can be found . Notice that this removes some of the problems associated with using the CYK algorithm on ambiguous grammars . Once the best nested structure has been chosen , the reliability of the prediction is evaluated for each position . This is done by finding the probability that each prediction -LRB- specific pair or unpaired -RRB- was correct , given the model and the data . The variables from the inside outside algorithm can easily be used to give this information -LRB- Appendix 1 available as Supplementary Material -RRB- . Knowing which parts of the prediction are reliable is very important when using the prediction in further work -LRB- Fig. 4 -RRB- . Finding a single best structure may not always give all the information that would be useful . To give an overview of the prediction , a dot plot is produced as well . It is a square plot of pairing probabilities for all different pairs . Each probability is represented by the size of a dot in the appropriate position . Probabilities of not pairing are shown on the sides The input to the web server is an alignment of up to 40 sequences and 500 positions . The alignment should be given in the FASTA format with gaps represented by hyphens -LRB- ` - ' -RRB- . Previously known structural elements can be incorporated in the prediction by adding a specific sequence with the relevant information -LRB- see web site for details -RRB- . When a prediction is done , the web server returns an email to the user . This email contains a link to a web page with the results . On the web page , the following is available in multiple formats : A summary of the input . The calculated tree . The predicted structure given as a bracket notation . Reliabilities of individual predictions . A dot plot . RESULTS For all predictions in this section , two versions were made . The first version was made using the alignment from the database of the sequences being analysed . This alignment was assumed to be ` correct ' . In the second version , sequences from databases were aligned using the ClustalW alignment program by Thompson et al. -LRB- 22 -RRB- to imitate a realistic scenario of RNA structure prediction . Test sets A number of test sets were made -LRB- Table 1 -RRB- . The sets A , B and C are used in evaluating the prediction accuracy as a function of the number of sequences used in the analysis . Test set D is used to show how prediction accuracy varies as a function of evolutionary distance . Prediction accuracy An evaluation of the prediction accuracy is shown in Figure 6 . The accuracy was calculated as the percentage of positions for which the secondary structure was correctly predicted . For a pairing position to be counted as correct , the position of the predicted pair had to be correct . Sequences in the test sets used here have a maximum pairwise distance of 0.50 units in the Jukes Cantor model -LRB- 23 -RRB- . This means that the sequences are quite diverse , but still possible to align without too many errors . As expected , prediction accuracy rises with the number of sequences used , as more covariance information becomes Figure 3 . In the top alignment , the KH-99 result is given . The bottom alignment shows the structure when all nucleotides have a 1 % chance of being any other nucleotide . The result is a longer stem , which includes one nonstandard pair . 3426 Nucleic Acids Research , 2003 , Vol . 31 , No. 13 Figure 4 . Prediction of the Klebsiella pneumoniae RNase P RNA structure -LRB- 5 -RRB- with the KH-99 method based on the four sequence alignment in the work of Knudsen and Hein -LRB- 12 -RRB- . The left side shows which areas are correctly predicted and the right side shows the reliability of the prediction . Notice the high correlation between the two . Positions 359 366 form a pseudoknot with positions 68 70 and 72 76 . Furthermore , positions 84 87 form a pseudoknot with positions 282 285 . Since the algorithm described here does not take pseudoknots into account , this explains why these areas are incorrectly predicted while some of them seem reliable . Table 1 . Test sets from Zwieb et al. -LRB- 4 -RRB- and Rosenblad et al. -LRB- 6 -RRB- Test set A : 9 tmRNAs -LRB- 363.8 -RRB- B : 13 bacterial SRP RNAs -LRB- 270.5 -RRB- C : 10 eukaryotic SRP RNAs -LRB- 300.9 -RRB- D : 51 eukaryotic SRP RNAs -LRB- 297.4 -RRB- Sequences act.act. , hae.inf. , kle.pne. , pas.mul. , sal.par. , sal.typ. , she.put. , vib.cho. , yer.pes . bac.alc. , bac.bre. , bac.cer. , bac.cir. , bac.mac. , bac.meg. , bac.pol. , bac.pum. , bac.sph. , bac.ste. , bac.thu. , bre.bre. , clo.per . ory.sat. , tri.ae-a , tri.ae-b , zea.ma-a , zea.ma-b , zea.ma-c , zea.ma-d , zea.ma-e , zea.ma-f , zea.ma-h ara.th-a , ara.th-b , cae.el-a , cae.el-b , cae.el-c , cae.el-d , can.spe. , cin.hyb. , dro.mel. , fug.rub. , hom.sa-a , hom.sa-b , hom.sa-c , hum.ja-a , hum.ja-b , hum.lu-a , hum.lu-b , hum.lu-c , hum.lu-d , lep.col. , lyc.es-a , lyc.es-b , lyc.es-c , lyc.es-e , lyc.es-f , lyc.es-g , lyc.es-h , lyc.es-i , lyc.es-j , lyc.es-k , lyc.es-m , lyc.es-n , lyc.es-o , ory.sat. , rat.rat. , sch.pom. , tet.ros. , tet.the. , tri.ae-a , tri.ae-b , try.br-a , try.br-b , xen.lae. , yar.li-a , yar.li-b , zea.ma-a , zea.ma-b , zea.ma-c , zea.ma-d , zea.ma-e , zea.ma-f Sets A , B and C were chosen so that no pairwise distance within each set is more than 0.5 units in the Jukes-Cantor model -LRB- 23 -RRB- . Set D has unique sequences , all of length greater than 250 from the eukaryotic SRP RNA database . No two sequences are identical within any of the sets . The average sequence length of each test set is written in parentheses . available . This shows that when related sequences are available , they should generally be used in the structure prediction -LRB- exceptions to this are discussed below -RRB- . An accuracy of 75 % is obtainable with six sequences and Pfold can cope with many more sequences , so even higher accuracies are possible . Pfold was also used on the original test set of Knudsen and Hein -LRB- 12 -RRB- . There were a few small differences in the results compared to the KH-99 algorithm and the overall performance was slightly better in this new version of the algorithm . Evolutionary distance effect There are two effects of evolutionary distance on prediction accuracy : large distances imply much covariation information , but it also means that sequences are difficult to align . Another issue with large evolutionary distances is that secondary structures may not be conserved between the sequences . Since Pfold assumes a single common structure for all sequences , this can pose a problem . These effects are illustrated in Figure 7 . When using ` correct ' alignments , the accuracy rises with distance , as the evolutionary information increases . The accuracy levels off at 80 % , which seems to be the maximum obtainable average for two sequences of this type using Pfold . The graph made from the ClustalW alignments show how accuracy increases until an evolutionary distance of 0.60 . After this , the accuracy drops due to alignment errors . At a distance of 0.90 the quality of alignments become so low that the structures might as well be predicted individually . Speed The algorithmical improvements made in this work reduces the computation time substantially . The largest improvement is from estimating a single evolutionary tree and fixing it , rather than estimating all the branch lengths under the RNA model . For details on the computation times , see Appendix 2 -LRB- available as Supplementary Material -RRB- . DISCUSSION Some aspects of this method remain to be explored , as described by Knudsen and Hein -LRB- 12 -RRB- . These include : base Nucleic Acids Research , 2003 , Vol . 31 , No. 13 3427 Figure 7 . Accuracy as a function of pairwise distance between two sequences being analysed . As in Figure 6 , crosses are from results using ` correct ' alignments , while boxes are from ClustalW alignments . The pairs were grouped according to their Jukes Cantor distances , in the intervals -LSB- 0 ; 0.2 -RRB- , -LSB- 0.2 ; 0.4 -RRB- , -LSB- 0.4 ; 0.6 -RRB- etc. . The points represent average results for 50 random sequence combinations from a specific range of distances . The x-value of a point is the average of the 50 distances . Figure 5 . A dot plot made from GCA-tRNA sequences from rat , chicken , mouse and cow -LRB- 1 -RRB- . The lower left corner represents the beginning of the alignment . Imagining the alignment laid out upwards from here and toward the right , the dots inside the square represent pairing probabilities between positions . The dots outside the square represent probabilities of not pairing . The tRNA structure is clearly visible . closely linked to the quality of the alignment . Some work has been done in the field of RNA structural sequence alignment -LRB- 28 -RRB- . Rivas and Eddy -LRB- 18 -RRB- developed an RNA model that takes the alignment of two sequences into consideration through a pair-SCFG . They did , however , assume the alignment to be given since computational time would be prohibitive in using their method to align sequences . The RNAGA method by Chen et al. -LRB- 29 -RRB- predicts consensus structures without trying to align the sequences which might be a useful approach to avoiding the alignment problem . stacking interactions , a grammar more closely describing real RNA structures and other models for base-pair evolution . If base-stacking interactions and a better grammar is incorporated in Pfold , the prediction accuracies should become close to the MFOLD results for single sequences -LRB- 9 11 -RRB- , since the methods resemble each other closely in that situation . For multiple sequences , Pfold should still be able to perform even better . When structures are conserved in evolution , inclusion of information from multiple related sequences improves predictions . A number of methods have been developed that combine energy calculations with evolutionary information through a given alignment -LRB- 24 27 -RRB- . These methods have proven quite reliable but lack an explicit evolutionary model . As emphasised by this work , an important aspect of RNA structure prediction is the alignment problem . In methods that depend on a sequence alignment , the success of the method is SUPPLEMENTARY MATERIAL Supplementary Material is available at NAR Online . ACKNOWLEDGEMENTS B.K. would like to thank the University of Florida , the Carlsberg Foundation -LRB- grant no . ANS-0604 / 20 -RRB- and the Danish National Science Research Council -LRB- grant no. 21-00-0283 -RRB- for their support . B.K. also thanks Christian N. S. Pedersen for his great help in answering questions about Unix and programming . We acknowledge the help of Ebbe S. Andersen in making this method practically useful and in illustrating the web server . Finally , we thank Jakob S. Pedersen for helpful comments on the manuscript . Figure 6 . Accuracy as a function of the number of sequences used in the prediction . Crosses are from results using ` correct ' alignments , while boxes are from ClustalW alignments . Each point represents average results for either all possible combinations of the relevant number of sequences or 50 random combinations , whichever is the lowest number . 3428 Nucleic Acids Research , 2003 , Vol . 31 , No. 13 REFERENCES 1 . Sprinzl , M. , Horn , C. , Brown , M. , Ioudovitch , A. and Steinberg , S. -LRB- 1998 -RRB- Compilation of tRNA sequences and sequences of tRNA genes . Nucleic Acids Res. , 26 , 148 153 . 2 . Wuyts , J. , De Rijk , P. , Van de Peer , Y. , Winkelmans , T. and De Wachter , R. -LRB- 2001 -RRB- The European large subunit ribosomal RNA database . Nucleic Acids Res. , 29 , 175 177 . 3 . Wuyts , J. , Van de Peer , Y. , Winkelmans , T. and De Wachter , R. -LRB- 2002 -RRB- The European database on small subunit ribosomal RNA . Nucleic Acids Res. , 30 , 183 185 . 4 . Zwieb , C. , Gorodkin , J. , Knudsen , B. , Burks , J. and Wower , J. -LRB- 2003 -RRB- tmRDB -LRB- tmRNA database -RRB- . Nucleic Acids Res. , 31 , 446 447 . 5 . Brown , J.W. -LRB- 1999 -RRB- The ribonuclease P database . Nucleic Acids Res. , 27 , 314 . 6 . Rosenblad , M.A. , Gorodkin , J. , Knudsen , B. , Zwieb , C. and Samuelsson , T. -LRB- 2003 -RRB- Nucleic Acids Res. , 31 , 363 364 . 7 . Nussinov , R. , Pieczenik , G. , Griggs , J.R. and Kleitman , D.J. -LRB- 1978 -RRB- Algorithms for loop matchings . SIAM J. Appl . Math. , 35 , 68 82 . 8 . Zuker , M. and Stiegler , P. -LRB- 1981 -RRB- Optimal computer folding of large RNA sequences using thermodynamic and auxiliary information . Nucleic Acids Res. , 9 , 133 148 . 9 . Zuker , M. -LRB- 1989 -RRB- Computer prediction of RNA structure . Methods Enzymol. , 180 , 262 288 . 10 . Walter , A.E. , Turner , D.H. , Kim , J. , Lyttle , M.H. , Mueller , P. , Mathews , D.H. and Zuker , M. -LRB- 1994 -RRB- Coaxial stacking of helixes enhances binding of oligoribonucleotides and improves predictions of RNA folding . Proc . Natl Acad . Sci . USA , 91 , 9218 9222 . 11 . Mathews , D.H. , Sabina , J. , Zuker , M. and Turner , D.H. -LRB- 1999 -RRB- Expanded sequence dependence of thermodynamic parameters improve prediction of RNA secondary structure . J. Mol . Biol. , 288 , 911 940 . 12 . Knudsen , B. and Hein , J. -LRB- 1999 -RRB- RNA secondary structure prediction using stochastic context-free grammars and evolutionary history . Bioinformatics , 15 , 446 454 . 13 . Lari , K. and Young , S.J. -LRB- 1990 -RRB- The estimation of stochastic context-free grammars using the inside outside algorithm . Comput . Speech Lang. , 4 , 35 56 . 14 . Felsenstein , J. -LRB- 1981 -RRB- Evolutionary trees from DNA sequences : a maximum likelihood approach . J. Mol . Evol. , 17 , 368 376 . 15 . Durbin , R. , Eddy , S. , Krogh , A. and Mitchison , G. -LRB- 1998 -RRB- Biological Sequence Analysis : Probabilistic Models of Proteins and Nucleic Acids . Cambridge University Press , Cambridge , UK . 16 . Thorne , J.L. , Kishino , H. and Felsenstein , J. -LRB- 1991 -RRB- An evolutionary model for maximum likelihood alignment of DNA sequences . J. Mol . Evol. , 33 , 114 124 . 17 . Hein , J. , Wiuf , C. , Knudsen , B. , M ller , M. and Wibling , G. -LRB- 2000 -RRB- Statistical alignment : computational properties , homology testing and goodness-offit . J. Mol . Biol. , 302 , 265 279 . 18 . Rivas , E. and Eddy , S.R. -LRB- 2001 -RRB- Noncoding RNA gene detection using comparative sequence analysis . BMC Bioinformatics , 2 , 8 . 19 . Thorne , J.L. , Goldman , N. and Jones , D.T. -LRB- 1996 -RRB- Combining protein evolution and secondary structure . Mol . Biol . Evol. , 13 , 666 673 . 20 . Saitou , N. and Nei , M. -LRB- 1987 -RRB- The neighbor-joining method : a new method for reconstructing phylogenetic trees . Mol . Biol . Evol. , 4 , 406 425 . 21 . McCaskill , J.S. -LRB- 1990 -RRB- The equilibrium partition function and base pair binding probabilities for RNA secondary structure . Biopolymers , 29 , 1105 1119 . 22 . Thompson , J.D. , Higgins , D.G. and Gibson , T.J. -LRB- 1994 -RRB- CLUSTAL W : improving the sensitivity of progressive multiple sequence alignment through sequence weighting , position specific gap penalties and weight matrix choice . Nucleic Acids Res. , 22 , 4673 4680 . 23 . Jukes , T.H. and Cantor , C.R. -LRB- 1969 -RRB- Evolution of protein molecules . In Munro , H.N. -LRB- ed . -RRB- , Mammalian Protein Metabolism . Academic Press , New York , pp. 21 132 . 24 . Hofacker , I.L. and Stadler , P.F. -LRB- 1999 -RRB- Automatic detection of conserved base pairing patterns in RNA virus genomes . Comput . Chem. , 23 , 401 414 . 25 . Juan , V and Wilson , C. -LRB- 1999 -RRB- RNA secondary structure prediction based . on free energy and phylogenetic analysis . J. Mol . Biol. , 289 , 935 947 . 26 . Luck , R. , Graf , S. and Steger , G. -LRB- 1999 -RRB- ConStruct : a tool for thermo dynamic controlled prediction of conserved secondary structure . Nucleic Acids Res. , 27 , 4208 4217 . 27 . Hofacker , I.L. , Fekete , M. and Stadler , P.F. -LRB- 2002 -RRB- Secondary structure prediction for aligned RNA sequences . J. Mol . Biol. , 319 , 1059 1066 . 28 . Gorodkin , J. , Heyer , L.J. and Stormo , G.D. -LRB- 1997 -RRB- Finding the most significant common sequence and structure motifs in a set of RNA sequences . Nucleic Acids Res. , 25 , 3724 3732 . 29 . Chen,J.-H. , Len,S.-Y . and Maizel , J.V. -LRB- 2000 -RRB- Prediction of common secondary structures of RNAs : a genetic algorithm approach . Nucleic Acids Res. , 28 , 991 999 .

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O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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Impact of anthropogenic atmospheric nitrogen and sulfur deposition on ocean acidification and the inorganic carbon system Scott C. Doney * , Natalie Mahowald , Ivan Lima * , Richard A. Feely , Fred T. Mackenzie , Jean-Francois Lamarque , and Phil J. Rasch * Marine Chemistry and Geochemistry Department , Woods Hole Oceanographic Institution , 266 Woods Hole Road , Woods Hole , MA 02543 ; Divisions of Climate and Global Dynamics and Atmospheric Chemistry , National Center for Atmospheric Research , 1850 Table Mesa Drive , Boulder , CO 80303 ; Pacific Marine Environmental Laboratory , National Oceanic and Atmospheric Administration , 7600 Sand Point Way NE , Seattle , WA 98115-6349 ; and Department of Oceanography , School of Ocean and Earth Science and Technology , University of Hawaii at Manoa , 100 Pope Road , Honolulu , HI 96822 Edited by Michael L. Bender , Princeton University , Princeton , NJ , and approved July 9 , 2007 -LRB- received for review March 9 , 2007 -RRB- Fossil fuel combustion and agriculture result in atmospheric deposition of 0.8 Tmol/yr reactive sulfur and 2.7 Tmol/yr nitrogen to the coastal and open ocean near major source regions in North America , Europe , and South and East Asia . Atmospheric inputs of dissociation products of strong acids -LRB- HNO3 and H2SO4 -RRB- and bases -LRB- NH3 -RRB- alter surface seawater alkalinity , pH , and inorganic carbon storage . We quantify the biogeochemical impacts by using atmosphere and ocean models . The direct acid/base flux to the ocean is predominately acidic -LRB- reducing total alkalinity -RRB- in the temperate Northern Hemisphere and alkaline in the tropics because of ammonia inputs . However , because most of the excess ammonia is nitrified to nitrate -LRB- NO3 -RRB- in the upper ocean , the effective net atmospheric input is acidic almost everywhere . The decrease in surface alkalinity drives a net air sea efflux of CO2 , reducing surface dissolved inorganic carbon -LRB- DIC -RRB- ; the alkalinity and DIC changes mostly offset each other , and the decline in surface pH is small . Additional impacts arise from nitrogen fertilization , leading to elevated primary production and biological DIC drawdown that reverses in some places the sign of the surface pH and air sea CO2 flux perturbations . On a global scale , the alterations in surface water chemistry from anthropogenic nitrogen and sulfur deposition are a few percent of the acidification and DIC increases due to the oceanic uptake of anthropogenic CO2 . However , the impacts are more substantial in coastal waters , where the ecosystem responses to ocean acidification could have the most severe implications for mankind . alkalinity biogeochemistry nutrient eutrophication global change ocean chemistry eastern North America , Europe , and South and East Asia -LRB- 4 7 -RRB- . The subsequent acidification of terrestrial and freshwater ecosystems by dry deposition and more acidic rainfall is a well known environmental problem -LRB- 8 11 -RRB- . Anthropogenic nitrogen and sulfur deposition to the ocean surface alters surface seawater chemistry , leading to acidification and reduced total alkalinity . Lower pH and resulting lower CO2 3 concentrations are of particular concern for a range of benthic and pelagic organisms that form calcareous -LRB- CaCO3 -RRB- shells -LRB- e.g. , corals , coralline algae , foraminifera , pteropods , and coccolithophores -RRB- -LRB- 12 , 13 -RRB- . The acidification effects , although not as large globally as those of anthropogenic CO2 uptake -LRB- 14 , 15 -RRB- , could be significant in coastal ocean regions because these regions are already vulnerable to other human impacts , including nutrient fertilization -LRB- 15 , 16 -RRB- , pollution , overfishing , and climate change . Here we compute bounds on the potential impact of anthropogenic nitrogen and sulfur deposition on seawater chemistry , using simulated atmospheric deposition fields applied to a coupled 3D ocean ecosystem biogeochemical model -LRB- see Methods -RRB- . We also compare these model results with field observations for U.S. coastal regions . Basic Principles of the Effects of Atmospheric C , N , and S Deposition on Seawater Chemistry . It is useful to frame the impact of anthro - H umans are dramatically altering the global nitrogen and sulfur budgets , with one result being the release of large fluxes of nitrogen oxides -LRB- NOx , 2 Tmol/yr -RRB- , ammonia -LRB- NH3 , 4 Tmol/yr -RRB- , and sulfur dioxide -LRB- SO2 , 2 Tmol/yr -RRB- to the atmosphere -LRB- 1 -RRB- . Globally , fossil fuel combustion and biomass burning fluxes of NOx exceed the natural fluxes from land to the atmosphere -LRB- 2 -RRB- ; NH3 fluxes to the atmosphere are overwhelmed by those from human activities , mainly livestock husbandry -LRB- 3 -RRB- ; and oxidized sulfur fluxes from land are 10 times the natural fluxes , again because of combustion of fossil fuels and biomass burning -LRB- 2 -RRB- . After chemical transformations in the atmosphere , much of the anthropogenic nitrogen and sulfur is deposited to the surface as the dissociation products of nitric acid -LRB- HNO3 -RRB- and sulfuric acid -LRB- H2SO4 -RRB- . HNO3 and H2SO4 are strong acids that completely dissociate in water : HNO3 3 H NO3 and H2SO4 3 2H SO2 . 4 -LSB- 1 -RSB- pogenic nitrogen and sulfur inputs in terms of the changes in surface water dissolved inorganic carbon -LRB- DIC -RRB- and total alkalinity -LRB- Alk -RRB- . DIC and Alk are conservative quantities with respect to mixing and temperature and pressure changes and , together with temperature and salinity , determine seawater pH and the partial pressure of carbon dioxide , pCO2 -LRB- 17 -RRB- , an important factor driving air sea CO2 exchange . Processes that increase DIC or decrease Alk lower seawater pH -LRB- ocean acidification -RRB- and raise pCO2 . CO2 combines with water to form carbonic acid -LRB- H2CO3 -RRB- , which then undergoes a series of acid/base dissociation reactions : CO2 aq H2O 7 H2CO3 7 H HCO3 7 2H DIC concentration -LRB- -LSB- DIC -RSB- ; mol/kg -RRB- is Author contributions : S.C.D. and N.M. designed research ; S.C.D. , N.M. , and I.L. performed research ; J.-F.L. and P.J.R. contributed new reagents/analytic tools ; S.C.D. , N.M. , and I.L. analyzed data ; and S.C.D. , N.M. , R.A.F. , and F.T.M. wrote the paper . The authors declare no conflict of interest . This article is a PNAS Direct Submission . Freely available online through the PNAS open access option . Abbreviations : Alk , total alkalinity ; DIC , dissolved inorganic carbon . To CO2 . 3 -LSB- 2 -RSB- Because of the relatively short lifetime of reactive nitrogen and sulfur species in the atmosphere -LRB- days to about a week -RRB- , the majority of the acid deposition occurs on land , in the coastal ocean , and in the open ocean downwind of the primary source regions in 14580 14585 PNAS September 11 , 2007 vol . 104 no. 37 whom correspondence should be addressed . E-mail : sdoney@whoi.edu . 2007 by The National Academy of Sciences of the USA www.pnas.org cgi doi 10.1073 pnas .0702218104 DIC CO2 aq H2CO3 HCO3 CO2 3 . -LSB- 3 -RSB- Anthropogenic CO2 uptake increases surface -LSB- DIC -RSB- and lowers pH -LRB- 14 , 18 -RRB- . Total alkalinity -LRB- -LSB- Alk -RSB- ; eq/kg -RRB- , a measure of the acid/base balance of the fluid -LRB- 19 -RRB- , is defined conventionally as the excess of proton acceptors -LRB- bases formed from weak acids -RRB- over proton donors relative to a reference point -LRB- formally , acid dissociation pKa 4.5 ; approximately the H2CO3 equivalence point -RRB- : Alk H NH3 OH HCO3 2 CO2 3 -LSB- 4 -RSB- minor species , or , alternatively , as the net positive charge from strong mineral bases minus strong mineral acids -LRB- 20 -RRB- : Alk Na 2 SO2 4 K 2 Ca2 NO3 . 2 Mg2 Cl -LSB- 5 -RSB- because the protonated species is the primary form at the CO2 equivalence pH -LRB- pKa of NH4 for seawater 9.5 -RRB- . However , in rainwater the main proton source for forming the ammonium ion is water , and the resulting release of OH increases alkalinity similar to NH3 deposition . A fraction of the atmospheric N and S is deposited as ammonia sulfate aerosols , -LRB- NH4 -RRB- 2SO4 and -LRB- NH4 -RRB- HSO4 ; in our calculations we assume that the aerosols dissociate in surface seawater and include the aerosol N and S in the NH4 and SO2 fluxes . Our alkalinity flux -LRB- Eq . 7 -RRB- is similar 4 to the atmosphere acidity equation for wet deposition from ref . 6 , although of course with opposite signs . One difference is that we include additional SO2 and NH3 terms because of dry deposition . The impact of atmospheric NH4 NH3 input on ocean alkalinity depends on the extent to which the NH4 is converted to NO3 by nitrification : NH4 2O2 3 NO3 2H H2O . -LSB- 8 -RSB- In Eq . 4 , we neglect for clarity terms from other weak acids in seawater , such as B -LRB- OH -RRB- 3 , H2SiO3 , and H2PO4 , which are included in our seawater thermodynamics code -LRB- 21 -RRB- . Atmospheric C , N , and S inputs can be converted into fluxes of inorganic carbon , f DIC -LRB- mol m 2 y 1 -RRB- , and alkalinity , f Alk -LRB- eq m 2 y 1 -RRB- . The f DIC flux f DIC fCOgas 2 fCorganic fCaCO3 f DICrain -LSB- 6 -RSB- Note that almost all of the deposited NH3 will be converted to NH4 at seawater pH. Nitrification reduces alkalinity by 2 equivalents for every mole of NH4 consumed . Assuming complete nitrification changes the alkaline NH3 and NH4 flux to an effective acidity flux : fAlknitrif 2fCa2 fNH3 2fSO2 fNH4 . 2fSO2 4 fNO3 -LSB- 9 -RSB- is governed by CO2 air sea gas exchange fCOgas , net respiration 2 of atmospheric dissolved and particulate organic matter inputs fCorganic , and net dissolution of CaCO3 from atmospheric dust deposition fCaCO3 , as well as by dissolution of DIC in rainwater f DICrain , a small term that is usually neglected . The anthropogenic changes in fCorganic and fCaCO3 are not well characterized and are not considered further here . The chemical forms of the atmospheric C , N , and S inputs are important for determining their impact on the alkalinity flux : fAlk 2fCa2 2fSO2 2fSO2 4 fNO3 fNH3 fNH4 . -LSB- 7 -RSB- Dissolution of calcareous mineral dust , CaCO3 , in rainwater , denoted by the input of dissolved Ca2 ion in Eq . 7 , acts to add alkalinity to the surface ocean -LRB- fAlk 0 -RRB- . Note the factor of 2 conversion for alkalinity , reflecting the charge on Ca2 and CO2 3 -LRB- Eqs . 4 and 5 -RRB- . Air sea CO2 gas exchange , the pathway for almost all anthropogenic carbon input to the ocean , does not enter Eq . 7 because adding CO2 does not alter ocean total alkalinity -LRB- Eq . 4 -RRB- but does change carbonate alkalinity -LRB- Alkcarb -LSB- HCO3 -RSB- 2 -LSB- CO2 -RSB- -RRB- 3 -LRB- 22 -RRB- . Similarly , the release of CO2 from organic carbon respiration does not affect alkalinity except through related conversion of organic nitrogen -LRB- and to an even smaller extent phosphorus -RRB- to inorganic form . Inorganic sulfur deposition adds acidity to the surface ocean -LRB- fAlk 0 -RRB- , reducing surface water alkalinity . About 40 80 % of atmospheric S is oxidized to H2SO4 by gas-phase and aqueous reactions and deposited to the surface by wet -LRB- dominant -RRB- and dry processes . An input of 1 mole SO2 is equivalent to 2 equivalents 4 Alk . The remaining sulfur emissions are dry-deposited as SO2 . We assume for surface seawater that all of the SO2 combines with water to form H2SO4 and thus has a similar effect on alkalinity as SO2 4 deposition . Atmospheric nitrogen deposition can add either acidity or alkalinity , depending on the chemical form . The wet deposition of NO3 is acidic , and the dry deposition of NH3 is alkaline -LRB- Eqs . 4 and 5 -RRB- . From Eq . 4 , one might expect that wet deposition of the ammonium ion NH4 should result in no change in alkalinity Doney et al. . Results and Discussion Model atmospheric nitrogen , sulfur , and alkalinity deposition fields are computed based on estimated changes in climate and emissions between the preindustrial and current climates -LRB- 1990 2000 -RRB- -LRB- Fig. 1 -RRB- -LRB- see Methods -RRB- . The global Community Climate System Model 3 -LRB- CCSM-3 -RRB- nitrogen and sulfur deposition fluxes -LRB- Table 1 -RRB- are similar to the results reported in the 2001 Intergovernmental Panel on Climate Change report -LRB- 1 , 23 -RRB- . For comparison , air sea CO2 fluxes are reported from the CCSM-3 ocean model . About one-third of anthropogenic NOx and SOx emissions , mostly from fossil fuel combustion , are deposited to the ocean . Because of the short atmospheric residence time , deposition is concentrated downwind of the emission sources , mostly in the temperate North Atlantic , temperate and eastern subtropical North Pacific , and northern Indian Ocean , with maximum values approaching 0.03 mol m 2 y 1 . Approximately half of agricultural NHx emissions are deposited to the ocean and are more evenly spread over the Northern Hemisphere . The anthropogenic alkalinity flux fAlk is negative -LRB- acidic -RRB- in the temperate regions of the Northern Hemisphere dominated by fossil fuel fSO2 fSO2 and fNO3 deposition and is positive -LRB- alkaline -RRB- 4 in the tropics owing to fNH4 fNH3 deposition -LRB- Fig. 1 displays acidity , the negative of fAlk and fAlknitrif , for comparison with other fluxes -RRB- . On a global basis , the alkalinity reduction from fSO2 4 fSO2 and fNO3 is largely canceled by fNH4 fNH3 inputs , and the global ocean integrated anthropogenic fAlk input is only 0.24 Teq y 1 . Maximum deposition fluxes to the coastal ocean are 0.01 eq m 2 y 1 . Assuming complete nitrification of fNH4 fNH3 changes global ocean anthropogenic fAlknitrif input dramatically to 4.22 Teq y 1 , with maximum coastal fluxes of 0.01 to 0.10 eq m 2 y 1 . PNAS September 11 , 2007 vol . 104 no. 37 14581 ENVIRONMENTAL SCIENCES SUSTAINABILITY SCIENCE As shown below in our 3D ocean simulations , Eq . 9 is a good approximation when examining ocean alkalinity inventory changes because 98 % of anthropogenic NH3 NH4 deposition is nitrified to NO3 . When referring to atmospheric precipitation , the inclusion of nitrification is often termed potential acidity -LRB- 19 -RRB- . For the spatial flux maps below -LRB- Fig. 1 -RRB- , we compute both fAlk and fAlknitrif . Fig. 1 . Model-estimated anthropogenic -LRB- 1990 2000 minus preindustrial -RRB- atmospheric deposition fluxes for carbon , nitrogen , and sulfur -LRB- mol m NH3 -LRB- eq m 2 y 1 -RRB- . alkalinity ; and potential alkalinity , assuming complete nitrification of NH4 2 y 1 -RRB- ; Model ocean anthropogenic CO2 uptake is 138 Tmol y 1 , with spatial fDIC fluxes ranging from 0.1 to 2.0 mol C m 2 y 1 . Highest anthropogenic fDIC values occur in regions of upwelling and water mass transformation -LRB- 2 , 24 , 25 -RRB- . Globally , the ocean alkalinity reduction due to anthropogenic sulfur and nitrogen deposition , fAlknitrif , is at most , assuming full nitrification of ammonium deposition , approximately 3 % of the fDIC inputs because of anthropogenic CO2 uptake . However , the alkalinity fluxes can be significant relative to anthropogenic fDIC fluxes in some coastal ocean and margin areas . Previous modeling studies -LRB- Terrestrial Ocean Atmosphere Ecosystem Model , TOTEM ; refs . 26 and 27 -RRB- estimate anthropogenic atmospheric nitrogen deposition to the global coastal ocean of 0.03 mol m 2 y 1 for the turn of the 21st century , very similar to the estimates in Table 1 . It was also shown that this flux will increase significantly during the next several decades , as will the reactive nitrogen flux to the coastal ocean from anthropogenic sources via rivers and groundwaters . The anthropogenic alkalinity perturbation is redistributed by ocean circulation and initiates feedbacks by means of alterations in surface pH , air sea CO2 flux , and -LSB- DIC -RSB- . Biogeochemical transformations must also be considered because of nitrogen buildup or eutrophication of surface waters , stimulating increased ocean primary production and organic matter export -LRB- 27 30 -RRB- . We evaluate the responses by using a 3D marine physical/ecological / biogeochemical model -LRB- see Methods -RRB- , focusing on three sensitivity Table 1 . Model-estimated anthropogenic -LRB- 1990 2000 minus preindustrial -RRB- and preindustrial atmospheric deposition fluxes Integrated anthropogenic deposition , Tmol/y or Teq/y -LRB- preindustrial -RRB- Flux fCO2 f NH4 f NH3 f NO3 f SO2 f SO2 4 fAlk fAlknitrif Global -- 4.11 -LRB- 0.00 -RRB- 1.84 -LRB- 1.18 -RRB- 2.21 -LRB- 0.58 -RRB- 2.15 -LRB- 2.34 -RRB- 10.37 -LRB- 2.34 -RRB- Ocean-only 138 1.99 -LRB- 0.00 -RRB- 0.67 -LRB- 0.73 -RRB- 0.78 -LRB- 0.49 -RRB- 0.24 -LRB- 1.71 -RRB- 4.22 -LRB- 1.71 -RRB- Anthropogenic coastal ocean flux , mol or eq m 2 y Model 0.10 to 2.00 0.00 to 0.03 0.00 to 0.03 0.00 to 0.03 0.01 to 0.01 0.01 to 0.10 1 Observed 0.02 0.02 0.01 Field observations are shown for comparison -LRB- 4 , 5 -RRB- . 14582 www.pnas.org cgi doi 10.1073 pnas .0702218104 Doney et al. . Biological feedbacks depend on three factors : -LRB- i -RRB- the extent to which nitrification transforms excess NH4 into NO3 ; -LRB- ii -RRB- vertical redistribution of the excess nitrogen by means of biological nitrogen uptake in the surface , particle sinking , and subsurface remineralization ; and -LRB- iii -RRB- biological drawdown of surface -LSB- DIC -RSB- from eutrophication . The effect of primary production on alkalinity depends on the source of nitrogen -LRB- 31 , 32 -RRB- . NO3 supported growth produces alkalinity -LRB- 1:1 eq/mol -RRB- , and NH4 - supported growth removes alkalinity -LRB- 1:1 eq/mol -RRB- : 106CO2 16NO3 138H2O 3 organics 16OH 138O2 -LSB- 10 -RSB- 106CO2 16NH4 106H2O 7 organics 16H 106O2 . -LSB- 11 -RSB- Alkalinity sources/sinks from phosphorus uptake and release are an order of magnitude smaller . Note that the alkalinity changes resulting from biological nitrogen uptake are opposite in sign to those generated directly by the original atmospheric deposition flux -LRB- Eq . 7 -RRB- . Eventually , most of the extra organic nitrogen will be transported downward and remineralized in subsurface waters , releasing excess NH4 that is almost immediately nitrified to NO3 in oxygenated waters . The net effect of biological nitrogen cycling -LRB- case 3 -RRB- is to reduce surface -LSB- Alk -RSB- caused by atmospheric nitrogen deposition and to redistribute -LSB- Alk -RSB- downward through the water column -LRB- Fig. 2 -RRB- . The impact , however , does not qualitatively alter the surface water alkalinity perturbations . The strongest negative surface -LSB- Alk -RSB- anomalies in case 3 are somewhat smaller than those in case 2 but with greater spatial variability and some regions of positive trends -LRB- Fig. 3 -RRB- . Some of the spatial variability reflects the patterns of surface nutrient utilization , iron limitation , and the preferential biological uptake of NH4 over NO3 . The increase in ocean nitrogen inventory in case 3 is smaller than the cumulative atmospheric nitrogen deposition of 2.7 Tmol N y 1 because elevated surface NO3 and productivity reduces simulated N2 fixation by 0.6 Tmol N y 1 and increases denitrification by 0.1 Tmol N y 1 . Overall , nitrification modulates the acid/base signal from atmospheric nitrogen deposition , and fAlknitrif with net alkaline effects everywhere is a reasonable approximation for the vertically integrated alkalinity sink in most locations . Increased primary production stimulated by atmospheric nitrogen deposition lowers surface DIC with a ratio of 6.6 C/N -LRB- mol/mol -RRB- -LRB- Eqs . 10 and 11 -RRB- . This results in qualitatively different solutions for pH and air sea CO2 flux perturbations -LRB- case 3 ; Fig. 3 -RRB- . The negative -LSB- DIC -RSB- anomalies are amplified substantially relative to case 2 in some regions , with -LSB- DIC -RSB- / t trends of 0.3 to 0.5 mmol m 3 y 1 over large areas . In many locations , -LSB- DIC -RSB- decreases faster than -LSB- Alk -RSB- and thus reverses the sign of the pH signal , with pH / t typically ranging from 0.2 to 0.2 10 3 pH units y 1 . The case 3 spatial fields are also considerably more patchy , reflecting small-scale readjustments in model primary production , subsurface nutrients , and DIC . Implications and Future Research On a global scale , the alterations in surface water chemistry from anthropogenic nitrogen and sulfur deposition are only a few percent of the ocean acidification and -LSB- DIC -RSB- increases expected from the oceanic uptake of anthropogenic CO2 . However , impacts on seawater chemistry can be much more substantial in coastal waters , on the order of 10 50 % or more of the anthropogenic CO2-driven changes near the major source regions and in marginal seas . Although there are certainly caveats with the simulated coastal signals because the global ocean model does not fully resolve complex coastal physical and biological dynamics , the coastal amplification is clear . Ocean acidification is thought to be a PNAS September 11 , 2007 vol . 104 no. 37 14583 experiments . Case 1 simulates direct alkalinity perturbations with no nutrient fertilization ; fAlk alters surface -LSB- Alk -RSB- . Case 2 is similar to case 1 , except assuming complete nitrification of f NH4 f NH3 ; fAlknitrif alters surface -LSB- Alk -RSB- . Case 3 incorporates explicit nitrogen cycle perturbations and allows for nutrient fertilization ; fAlk alters surface -LSB- Alk -RSB- , f NO3 alters surface -LSB- NO3 -RSB- , and f NH4 f NH3 alters surface -LSB- NH4 -RSB- . All cases and a control -LRB- no atmospheric nitrogen and sulfur deposition -RRB- are integrated from 1990 to 2000 , with repeat annual physics and increasing anthropogenic atmospheric CO2 based on observations . The direct effects of anthropogenic nitrogen and sulfur deposition in case 1 are small , in global integral , because alkalinity reductions from f NO3 and f SO4 f SO2 are nearly balanced by increases from f NH4 f NH3 -LRB- Fig. 2 -RRB- . In case 2 , with complete nitrification , we find a more clear reduction in surface water pH , -LSB- Alk -RSB- , and -LSB- DIC -RSB- relative to the control simulation -LRB- Figs. 2 and 3 -RRB- . The lower surface water -LSB- DIC -RSB- arises because the negative -LSB- Alk -RSB- perturbations raise -LSB- pCO2 -RSB- and drive a perturbation efflux of CO2 into the atmosphere , counter to the anthropogenic CO2 flux . The negative -LSB- DIC -RSB- perturbations are comparable , although slightly smaller than -LSB- Alk -RSB- in an absolute sense , so that pH still declines but with significantly smaller amplitude than would occur from the original -LSB- Alk -RSB- perturbation alone . The largest surface water anomalies are found in coastal regions surrounding the emission areas , with trends pH / t of 0.02 to 0.12 10 3 pH units y 1 , -LSB- Alk -RSB- / t of 0.05 to 0.40 meq m 3 y 1 , and -LSB- DIC -RSB- / t of 0.05 to 0.30 mmol m 3 y 1 . For comparison , the temporal trends in the anthropogenic CO2 control simulation are pH / t of 0.8 to 1.8 10 3 pH units y 1 and -LSB- DIC -RSB- / t of 0.4 mmol m 3 y 1 near the poles to 1.2 mmol m 3 y 1 in the subtropics . Doney et al. . ENVIRONMENTAL SCIENCES SUSTAINABILITY SCIENCE Fig. 2 . Perturbations to simulated global vertical profiles due to 10 years of anthropogenic atmospheric nitrogen and sulfur deposition . -LRB- Upper -RRB- Alkalinity -LRB- solid lines -RRB- and DIC -LRB- dashed lines -RRB- . -LRB- Lower -RRB- NO3 -LRB- solid lines -RRB- and NH4 -LRB- dashed lines -RRB- . Case 1 is forced with alkalinity flux from Fig. 1 , case 2 with the potential alkalinity flux -LRB- assuming complete nitrification -RRB- , and case 3 with alkalinity and nitrogen fluxes allowing for biological feedbacks . Fig. 3 . Perturbation maps of simulated surface water pH , DIC , and total alkalinity trends and air sea CO2 flux due to anthropogenic atmospheric nitrogen and sulfur deposition . significant threat to ecosystems , including coral reefs and coastal benthic and planktonic foodwebs dominated by calcifying organisms -LRB- 10 13 -RRB- . Our study highlights the need to also consider the effects of non-CO2 acidification sources from atmospheric nitrogen and sulfur deposition , both through their direct effects on reducing ocean alkalinity and their indirect effects through nitrogen fertilization of marine phytoplankton . Uncertainties regarding the magnitude of non-CO2 ocean acidification arise from errors in the anthropogenic sulfur and nitrogen deposition fluxes to the ocean , ocean circulation , and marine biogeochemical responses . Global deposition depends strongly on total emissions , with emission ranges of approximately 16 % for NOx -LRB- total plus lightning -RRB- -LRB- 7 , 33 -RRB- , 27 % for NHx -LRB- 7 , 34 -RRB- , and 20 % for SO2 -LRB- 35 -RRB- . Spatial differences in emissions and atmospheric transport pathways will change the downwind deposition fluxes to the oceans . The overall spatial patterns are generally similar across most models but can vary locally because of small shifts in steep deposition gradients . For example , sulfate residence times for models range between 3 and 5 days -LRB- 35 -RRB- , with our model at 3.4 days . This means that deposition to remote regions in other models could be larger , but that uncertainties should be within 50 % , even in 14584 www.pnas.org cgi doi 10.1073 pnas .0702218104 remote regions . The response of seawater carbonate thermodynamics to acidification is well constrained . Better estimates of the uncertainties due to ocean circulation and biology require exploration of the effect in other numerical models and against field observations . Here we highlight the first-order impacts associated with anthropogenic atmospheric nitrogen and sulfur . More comprehensive studies on global change and coastal acid/base chemistry would need to include a range of additional processes . The extent of atmospheric neutralization of acidic compounds may be varying because of changes in mineral dust emissions and alkaline fly ash from coal-fired power plants . There is evidence , for example , of reduced atmospheric deposition of basic cations -LRB- e.g. , Ca2 -RRB- -LRB- 36 -RRB- . Although much of the acidity flux that falls on land will likely be neutralized by soils , some fraction may be transported to the ocean -LRB- 10 , 11 , 29 -RRB- , and there are substantial riverine inputs of anthropogenic nitrogen and organic matter to the coastal domain -LRB- 27 , 30 , 37 -RRB- . In the water column , secondorder biological effects arise from altered rates of nitrogen fixation , water-column and sediment denitrification , calcification , and CaCO3 remineralization -LRB- 14 , 15 , 38 40 -RRB- . Doney et al. . Methods Preindustrial and current nitrogen deposition -LRB- including nitrate and ammonia -RRB- are simulated -LRB- 33 -RRB- in the MOZART model -LRB- 41 -RRB- , based on climate simulations from the Parallel Climate Model -LRB- 42 -RRB- for 1890 and 1990 , respectively . Emissions for both preindustrial and present-day come from the EDGAR HYDE inventory -LRB- 43 -RRB- . Present-day emissions of ammonia follow ref . 7 , whereas preindustrial emissions are assumed to be zero . For the sulfate species , simulations are conducted within the Community Atmospheric Model -LRB- CAM3 -RRB- -LRB- 44 -RRB- , using sulfate chemistry based on ref . 45 . Emissions for preindustrial and current climate for sulfur are based on ref . 46 , and the preindustrial and current climates were simulated by using slab ocean model versions -LRB- 47 -RRB- . The ocean model combines a state-of-the-art marine ecosystem module -LRB- 48 -RRB- with phytoplankton functional groups -LRB- pico / nanoplankton , diatoms , diazotrophs , and calcifiers -RRB- , multiple limiting nutrients -LRB- N , P , Si , and Fe -RRB- , zooplankton , and several detrital pools . The model explicitly tracks both NO3 and NH4 pools and 1 . Intergovernmental Panel on Climate Change -LRB- 2001 -RRB- Climate Change 2001 : The Scientific Basis , eds Houghton JT , Ding Y , Griggs DJ , Noguer M , van der Linden PJ , Dai X , Maskell K , Johnson CA -LRB- Cambridge Univ Press , New York -RRB- . 2 . Mackenzie FT -LRB- 1995 -RRB- in Biotic Feedbacks in the Global Climatic System , eds Woodwell G , Mackenzie FT -LRB- Oxford Univ Press , New York -RRB- , pp 22 46 . 3 . Schlesinger WH -LRB- 1997 -RRB- Biogeochemistry : An Analysis of Global Change -LRB- Academic , San Diego -RRB- . 4 . National Acid Precipitation Assessment Program -LRB- 1991 -RRB- Acidic Deposition : State of Science and Technology , ed Irving PM -LRB- Govt Printing Office , Washington , DC -RRB- , Vol 1 . 5 . Howarth RW , Billen G , Swaney D , Townsend A , Jaworski N , Lajtha K , Downing JA , Elmgren R , Caraco N , Jordan T , et al. -LRB- 1996 -RRB- Biogeochemistry 35:75 139 . 6 . Rodhe H , Dentener F , Schulz M -LRB- 2002 -RRB- Environ Sci Technol 36:4382 4388 . 7 . Dentener F , Drevet J , Lamarque JF , Bey I , Eickhout B , Fiore AM , Hauglustaine D , Horowitz LW , Krol M , Kulshrestha UC , et al. -LRB- 2006 -RRB- Global Biogeochem Cycles 20 : GB4003 . 8 . Likens GE , Bormann HF , Johnson NM -LRB- 1981 -RRB- in Some Perspectives of the Major Biogeochemical Cycles , ed Likens GE -LRB- Wiley , New York -RRB- , SCOPE Report No 17 , pp 93 112 . 9 . Driscoll CT , Lawrence GB , Bulger AJ , Butler TJ , Cronan CS , Eagar C , Lambert KF , Likens GE , Stoddard JL , Weathers KC -LRB- 2001 -RRB- Biosciences 51:180 198 . 10 . Galloway JN -LRB- 2001 -RRB- Water Air Soil Pollut 130:17 24 . 11 . Galloway JN -LRB- 2003 -RRB- in Interactions of the Major Biogeochemical Cycles , eds Melillo JM , Field CB , Moldan B -LRB- Island Press , Washington , DC -RRB- , pp 259 272 . 12 . Orr JC , Fabry VJ , Aumont O , Bopp L , Doney SC , Feely RA , Gnanadesikan A , Gruber N , Ishida A , Joos F , et al. -LRB- 2005 -RRB- Nature 437:681 686 . 13 . Kleypas JA , Feely RA , Fabry VJ , Langdon C , Sabine CL , Robbins LL -LRB- 2006 -RRB- Impacts of Ocean Acidification on Coral Reefs and Other Marine Calcifiers : A Guide for Future Research -LRB- Univ Corp Atmos Res , Boulder , CO -RRB- . 14 . Feely RA , Sabine CL , Lee K , Berelson W , Kleypas J , Fabry VJ , Millero FJ -LRB- 2004 -RRB- Science 305:362 366 . 15 . Andersson AJ , Mackenzie FT , Lerman A -LRB- 2006 -RRB- Global Biogeochem Cycles 20 : GB1S92 . 16 . Jickells TD -LRB- 1998 -RRB- Science 281:217 222 . 17 . Zeebe RE , Wolf-Gladrow D -LRB- 2005 -RRB- CO2 in Seawater : Equilibrium , Kinetics , Isotopes -LRB- Elsevier , Amsterdam -RRB- . 18 . Sabine CL , Feely RA , Gruber N , Key RM , Lee K , Bullister JL , Wanninkhof R , Wong CS , Wallace DWR , Tilbrook B , et al. -LRB- 2004 -RRB- Science 305:367 371 . 19 . Dickson AG -LRB- 1981 -RRB- Deep-Sea Res 28:609 623 . 20 . Morel FMM -LRB- 1983 -RRB- Principles of Aquatic Chemistry -LRB- Wiley , New York -RRB- . 21 . Department of Energy -LRB- 1994 -RRB- Handbook of Methods for the Analysis of the Various Parameters of the Carbon Dioxide System in Sea Water , eds Dickson AG , Goyet C -LRB- ORNL/CDIAC -74 -RRB- -LRB- Oak Ridge National Laboratory , US Dept Energy , Oak Ridge , TN -RRB- . Available at http://cdiac.ornl.gov/oceans/ handbook.html . 22 . Morse JW , Mackenzie FT -LRB- 2006 -RRB- Geochemistry of Sedimentary Carbonates -LRB- Elsevier , Amsterdam -RRB- . 23 . Nakicenovic N , Alcamo J , Davis G , de Vries B , Fenhann J , Gaffin S , Gregory K , Grubler A , Jung TY , Kram T , et al. -LRB- 2000 -RRB- Emissions Scenarios : A Special Report of Working Group III of the Intergovernmental Panel on Climate Change -LRB- Cambridge Univ Press , New York -RRB- . 24 . Doney SC -LRB- 1999 -RRB- Global Biogeochem Cycles 13:705 714 . includes nitrification , nitrogen fixation , and water-column denitrification -LRB- 39 , 49 -RRB- . The biogeochemistry module -LRB- 50 -RRB- has full carbonate system thermodynamics -LRB- 21 -RRB- , and air sea CO2 fluxes follow a quadratic wind-speed gas exchange relationship . The ecobiogeochemistry is embedded in the low-resolution -LRB- zonal 3.6 ; meridional 0.8 1.8 ; 25 vertical layers with a 12-m-thick surface layer -RRB- National Center for Atmospheric Research ocean physical model -LRB- CCSM3 .1 -RRB- , based on the Parallel Ocean Program -LRB- 51 -RRB- . This model is integrated with a repeat annual cycle of surface forcing based on National Centers for Environmental Prediction reanalysis and satellite data products -LRB- 52 54 -RRB- . This work was supported by National Aeronautics and Space Administration Grant NNG05GG30G and National Science Foundation -LRB- NSF -RRB- Grant ATM06-28582 -LRB- to S.C.D. and I.L. -RRB- , National Oceanic and Atmospheric Administration Grant GC05-285 -LRB- to R.A.F. -RRB- , and NSF Grants EAR02-23509 and ATM04-39051 -LRB- to F.T.M. -RRB- . The National Center for Atmospheric Research is supported by the NSF . 25 . Mikaloff Fletcher SE , Gruber N , Jacobson AR , Doney SC , Dutkiewicz S , Gerber S , Follows M , Joos F , Lindsay K , Menemenlis D , et al. -LRB- 2006 -RRB- Global Biogeochem Cycles 20 : GB2002 . 26 . Ver LM , Mackenzie FT , Lerman A -LRB- 1999 -RRB- Am J Sci 299:762 801 . 27 . Mackenzie FT , Ver LM , Lerman A -LRB- 2002 -RRB- Chem Geol 190:13 32 . 28 . Paerl HW -LRB- 1993 -RRB- Can J Fish Aquat Sci 50:2254 2269 . 29 . Mackenzie FT , Ver LM , Sabine C , Lane M , Lerman A -LRB- 1993 -RRB- in Interactions of C , N , P , and S Biogeochemical Cycles and Global Change , eds Wollast R , Mackenzie FT , Chou L -LRB- Springer , Berlin -RRB- , pp 1 62 . 30 . Galloway JN , Dentener FJ , Capone DG , Boyer EW , Howarth RW , Seitzinger SP , Asner GP , Cleveland CC , Green PA , Holland EA , et al. -LRB- 2004 -RRB- Biogeochemistry 70:153 226 . 31 . Brewer PG , Goldman JC -LRB- 1976 -RRB- Limnol Oceanogr 21:108 117 . 32 . Goldman JC , Brewer PG -LRB- 1980 -RRB- Limnol Oceanogr 25:352 357 . 33 . Lamarque J-F , Kiehl JT , Brasseur GP , Butler T , Cameron-Smith P , Collins WD , Collins WJ , Granier C , Hauglustaine D , Hess PG , et al. -LRB- 2005 -RRB- J Geophys Res 110 : D19303 . 34 . Bouwman AF , Lee DS , Asman WAH , Dentener FJ , Van Der Hoek KW , Olivier JGJ -LRB- 1997 -RRB- Global Biogeochem Cycles 11:561 588 . 35 . Textor C , Schulz M , Guibert S , Kinne S , Balkanski Y , Bauer S , Berntsen T , Berglen T , Boucher O , Chin M , et al. -LRB- 2006 -RRB- Atmos Chem Phys 6:1777 1813 . 36 . Hedin LO , Granat L , Likens GE , Adri Buishand T , Galloway JN , Butler TJ , Rodhe H -LRB- 1994 -RRB- Nature 367:351 354 . 37 . Boyer EW , Howarth RW , Galloway JN , Dentener FJ , Green PA , Vorosmarty CJ -LRB- 2006 -RRB- Global Biogeochem Cycles 20 : GB1S91 . 38 . Fennel K , Wilkin J , Levin J , Moisan J , O'Reilly J , Haidvogel D -LRB- 2006 -RRB- Global Biogeochem Cycles 20 : GB3007 . 39 . Moore JK , Doney SC -LRB- 2007 -RRB- Global Biogeochem Cycles 21 : GB2001 . 40 . Krishnamurthy A , Moore JK , Luo C , Zender CS -LRB- 2007 -RRB- J Geophys Res 112 : G02019 . 41 . Horowitz LW , Walters S , Mauzerall DL , Emmons LK , Rasch PJ , Granier C , Tie X , Lamarque J-F , Schultz MG , Tyndall GS , et al. -LRB- 2003 -RRB- J Geophys Res 108:4784 . 42 . Washington WM , Weatherly JW , Meehl GA , Semtner AJ , Jr , Bettge TW , Craig AP , Strand WG , Jr , Arblaster J , Wayland VB , James R , Zhang Y -LRB- 2000 -RRB- Clim Dyn 16:755 774 . 43 . van Aardenne JA , Dentener FJ , Olivier JGJ , Klein CGM -LRB- 2001 -RRB- Global Biogeochem Cycles 15:909 928 . 44 . Collins WD , Blackmon M , Bitz CM , Bonan GB , Bretherton CS , Carton JA , Chang P , Doney S , Hack JJ , Kiehl JT , et al. -LRB- 2006 -RRB- J Clim 19:2122 2143 . 45 . Rasch PJ , Collins W , Eaton BE -LRB- 2001 -RRB- J Geophys Res 106:7337 7355 . 46 . Smith SJ , Conception E , Andres R , Lurz J -LRB- 2004 -RRB- Historical Sulfur Dioxide Emissions 1850 2000 : Methods and Results -LRB- Pacific Northwest Natl Lab , Richland , WA -RRB- , PNNL-14537 . 47 . Kiehl J , Shields C , Hack J , Collins W -LRB- 2006 -RRB- J Clim 19:2584 2596 . 48 . Moore JK , Doney SC , Lindsay K -LRB- 2004 -RRB- Global Biogeochem Cycles 18 : GB4028 . 49 . Moore JK , Doney SC , Lindsay K , Mahowald N , Michaels AF -LRB- 2006 -RRB- Tellus B Chem Phys Meteorol 58:560 572 . 50 . Doney SC , Lindsay K , Fung I , John J -LRB- 2006 -RRB- J Clim 19:3033 3054 . 51 . Smith R , Gent P -LRB- 2004 -RRB- Reference Manual for the Parallel Ocean Program -LRB- POP -RRB- -LRB- Los Alamos Natl Lab , Los Alamos , NM -RRB- , LAUR-02-2484 . 52 . Doney SC , Large WG , Bryan FO -LRB- 1998 -RRB- J Clim 11:1420 1441 . 53 . Large WG , Yeager SG -LRB- 2004 -RRB- Diurnal to Decadal Global Forcing for Ocean and Sea-Ice Models : The Data Sets and Flux Climatologies -LRB- Natl Center Atmos Res , Boulder , CO -RRB- , Technical Note NCAR/TN -460 STR . 54 . Doney SC , Yeager S , Danabasoglu G , Large WG , McWilliams JC , J Phys Oceanogr 37:1918 1938 . Doney et al. . PNAS September 11 , 2007 vol . 104 no. 37 14585 ENVIRONMENTAL SCIENCES SUSTAINABILITY SCIENCE

O O O O B O B O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O B O B O O O O O B O O O O O O O O O O O O O O O O O O O B O O O O O O O O O B O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O B O O O O O O O B O B O O O O O O O O B O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O 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