The Use of Genus-Specific Amplicon Pyrosequencing to Assess Phytophthora Species Diversity Using eDNA from Soil and Water in Northern Spain

[EN] Phytophthora is one of the most important and aggressive plant pathogenic genera in agriculture and forestry. Early detection and identification of its pathways of infection and spread are of high importance to minimize the threat they pose to natural ecosystems. eDNA was extracted from soil and water from forests and plantations in the north of Spain. Phytophthora-specific primers were adapted for use in high-throughput Sequencing (HTS). Primers were tested in a control reaction containing eight Phytophthora species and applied to water and soil eDNA samples from northern Spain. Different score coverage threshold values were tested for optimal Phytophthora species separation in a custom-curated database and in the control reaction. Clustering at 99% was the optimal criteria to separate most of the Phytophthora species. Multiple Molecular Operational Taxonomic Units (MOTUs) corresponding to 36 distinct Phytophthora species were amplified in the environmental samples. Pyrosequencing of amplicons from soil samples revealed low Phytophthora diversity (13 species) in comparison with the 35 species detected in water samples. Thirteen of the MOTUs detected in rivers and streams showed no close match to sequences in international sequence databases, revealing that eDNA pyrosequencing is a useful strategy to assess Phytophthora species diversity in natural ecosystems.This project has been supported by the Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria (EUPHRESCO-CEP: "Current and Emerging Phytophthoras: Research Supporting Risk Assessment And Risk Management"). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Català, S.; Pérez Sierra, AM.; Abad Campos, P. (2015). The Use of Genus-Specific Amplicon Pyrosequencing to Assess Phytophthora Species Diversity Using eDNA from Soil and Water in Northern Spain. PLoS ONE. 10(3):1-14. doi:10.1371/journal.pone.0119311S114103REICHARD, S. H., & WHITE, P. (2001). Horticulture as a Pathway of Invasive Plant Introductions in the United States. BioScience, 51(2), 103. doi:10.1641/0006-3568(2001)051[0103:haapoi]2.0.co;2Brasier, C. M. (2008). The biosecurity threat to the UK and global environment from international trade in plants. Plant Pathology, 57(5), 792-808. doi:10.1111/j.1365-3059.2008.01886.xTABERLET, P., COISSAC, E., HAJIBABAEI, M., & RIESEBERG, L. H. (2012). Environmental DNA. Molecular Ecology, 21(8), 1789-1793. doi:10.1111/j.1365-294x.2012.05542.xSogin, M. L., Morrison, H. G., Huber, J. A., Welch, D. M., Huse, S. M., Neal, P. R., … Herndl, G. J. (2006). Microbial diversity in the deep sea and the underexplored «rare biosphere». Proceedings of the National Academy of Sciences, 103(32), 12115-12120. doi:10.1073/pnas.0605127103Roesch, L. F. W., Fulthorpe, R. R., Riva, A., Casella, G., Hadwin, A. K. M., Kent, A. D., … Triplett, E. W. (2007). Pyrosequencing enumerates and contrasts soil microbial diversity. The ISME Journal, 1(4), 283-290. doi:10.1038/ismej.2007.53Acosta-Martínez, V., Dowd, S., Sun, Y., & Allen, V. (2008). Tag-encoded pyrosequencing analysis of bacterial diversity in a single soil type as affected by management and land use. Soil Biology and Biochemistry, 40(11), 2762-2770. doi:10.1016/j.soilbio.2008.07.022Jumpponen, A., & Jones, K. L. (2009). Massively parallel 454 sequencing indicates hyperdiverse fungal communities in temperateQuercus macrocarpaphyllosphere. New Phytologist, 184(2), 438-448. doi:10.1111/j.1469-8137.2009.02990.xNilsson, R. H., Ryberg, M., Abarenkov, K., Sjökvist, E., & Kristiansson, E. (2009). The ITS region as a target for characterization of fungal communities using emerging sequencing technologies. FEMS Microbiology Letters, 296(1), 97-101. doi:10.1111/j.1574-6968.2009.01618.xCoince, A., Caël, O., Bach, C., Lengellé, J., Cruaud, C., Gavory, F., … Buée, M. (2013). Below-ground fine-scale distribution and soil versus fine root detection of fungal and soil oomycete communities in a French beech forest. Fungal Ecology, 6(3), 223-235. doi:10.1016/j.funeco.2013.01.002Vannini, A., Bruni, N., Tomassini, A., Franceschini, S., & Vettraino, A. M. (2013). Pyrosequencing of environmental soil samples reveals biodiversity of thePhytophthoraresident community in chestnut forests. FEMS Microbiology Ecology, 85(3), 433-442. doi:10.1111/1574-6941.12132Jerde, C. L., Mahon, A. R., Chadderton, W. L., & Lodge, D. M. (2011). «Sight-unseen» detection of rare aquatic species using environmental DNA. Conservation Letters, 4(2), 150-157. doi:10.1111/j.1755-263x.2010.00158.xMonchy, S., Sanciu, G., Jobard, M., Rasconi, S., Gerphagnon, M., Chabé, M., … Sime-Ngando, T. (2011). Exploring and quantifying fungal diversity in freshwater lake ecosystems using rDNA cloning/sequencing and SSU tag pyrosequencing. Environmental Microbiology, 13(6), 1433-1453. doi:10.1111/j.1462-2920.2011.02444.xJobard, M., Rasconi, S., Solinhac, L., Cauchie, H.-M., & Sime-Ngando, T. (2012). Molecular and morphological diversity of fungi and the associated functions in three European nearby lakes. Environmental Microbiology, 14(9), 2480-2494. doi:10.1111/j.1462-2920.2012.02771.xLivermore, J. A., & Mattes, T. E. (2013). Phylogenetic detection of novel Cryptomycota in an Iowa (United States) aquifer and from previously collected marine and freshwater targeted high-throughput sequencing sets. Environmental Microbiology, 15(8), 2333-2341. doi:10.1111/1462-2920.12106NAKAYAMA, J., JIANG, J., WATANABE, K., CHEN, K., NINXIN, H., MATSUDA, K., … LEE, Y.-K. (2013). Up to Species-level Community Analysis of Human Gut Microbiota by 16S rRNA Amplicon Pyrosequencing. Bioscience of Microbiota, Food and Health, 32(2), 69-76. doi:10.12938/bmfh.32.69CREER, S., & SINNIGER, F. (2012). Cosmopolitanism of microbial eukaryotes in the global deep seas. Molecular Ecology, 21(5), 1033-1035. doi:10.1111/j.1365-294x.2012.05437.xDavey, M. L., Heegaard, E., Halvorsen, R., Kauserud, H., & Ohlson, M. (2012). Amplicon-pyrosequencing-based detection of compositional shifts in bryophyte-associated fungal communities along an elevation gradient. Molecular Ecology, 22(2), 368-383. doi:10.1111/mec.12122Weber, C. F., Vilgalys, R., & Kuske, C. R. (2013). Changes in Fungal Community Composition in Response to Elevated Atmospheric CO2 and Nitrogen Fertilization Varies with Soil Horizon. Frontiers in Microbiology, 4. doi:10.3389/fmicb.2013.00078Bergmark, L., Poulsen, P. H. B., Al-Soud, W. A., Norman, A., Hansen, L. H., & Sørensen, S. J. (2012). Assessment of the specificity of Burkholderia and Pseudomonas qPCR assays for detection of these genera in soil using 454 pyrosequencing. FEMS Microbiology Letters, 333(1), 77-84. doi:10.1111/j.1574-6968.2012.02601.xLi, L., Abu Al-Soud, W., Bergmark, L., Riber, L., Hansen, L. H., Magid, J., & Sørensen, S. J. (2013). Investigating the Diversity of Pseudomonas spp. in Soil Using Culture Dependent and Independent Techniques. Current Microbiology, 67(4), 423-430. doi:10.1007/s00284-013-0382-xSCHENA, L., HUGHES, K. J. D., & COOKE, D. E. L. (2006). Detection and quantification ofPhytophthora ramorum,P. kernoviae,P. citricolaandP. quercinain symptomatic leaves by multiplex real-time PCR. Molecular Plant Pathology, 7(5), 365-379. doi:10.1111/j.1364-3703.2006.00345.xTooley, P. W., Martin, F. N., Carras, M. M., & Frederick, R. D. (2006). Real-Time Fluorescent Polymerase Chain Reaction Detection ofPhytophthora ramorumandPhytophthora pseudosyringaeUsing Mitochondrial Gene Regions. Phytopathology, 96(4), 336-345. doi:10.1094/phyto-96-0336Pavón, C. F., Babadoost, M., & Lambert, K. N. (2008). Quantification of Phytophthora capsici Oospores in Soil by Sieving-Centrifugation and Real-Time Polymerase Chain Reaction. Plant Disease, 92(1), 143-149. doi:10.1094/pdis-92-1-0143Than, D. J., Hughes, K. J. D., Boonhan, N., Tomlinson, J. A., Woodhall, J. W., & Bellgard, S. E. (2013). A TaqMan real-time PCR assay for the detection ofPhytophthora‘taxon Agathis’ in soil, pathogen of Kauri in New Zealand. Forest Pathology, 43(4), 324-330. doi:10.1111/efp.12034Chen, W., Djama, Z. R., Coffey, M. D., Martin, F. N., Bilodeau, G. J., Radmer, L., … Lévesque, C. A. (2013). Membrane-Based Oligonucleotide Array Developed from Multiple Markers for the Detection of Many Phytophthora Species. Phytopathology, 103(1), 43-54. doi:10.1094/phyto-04-12-0092-rScibetta, S., Schena, L., Chimento, A., Cacciola, S. O., & Cooke, D. E. L. (2012). A molecular method to assess Phytophthora diversity in environmental samples. Journal of Microbiological Methods, 88(3), 356-368. doi:10.1016/j.mimet.2011.12.012Català S, Pérez-Sierra A, Berbegal M, Abad-Campos P. First approach into the knowledge of the Phytophthora species diversity in Mediterranean holm oak forests based on 454 parallel amplicon pyrosequencing of soil samples. Phytophthora in Forest and Natural Ecosystems 6th International IUFRO Working Party 7.02.09 Meeting, Córdoba, Spain, pp 34; 2012.Català S, Pérez-Sierra A, Beltrán A, Abad-Campos P. Next Generation Sequencing shows Phytophthora species diversity in soil samples of Macaronesian laurel forests from the Canary Islands. Phytophthora in Forest and Natural Ecosystems 6th International IUFRO Working Party 7.02.09 Meeting, Córdoba, Spain, pp. 86; 2012.Cooke, D. E. L., Drenth, A., Duncan, J. M., Wagels, G., & Brasier, C. M. (2000). A Molecular Phylogeny of Phytophthora and Related Oomycetes. Fungal Genetics and Biology, 30(1), 17-32. doi:10.1006/fgbi.2000.1202Andrews S. FastQC: a quality control tool for high throughput sequence data. Available: http://www.bioinformatics.bbsrc.ac.uk/projects/fastqc/Chou, H.-H., & Holmes, M. H. (2001). DNA sequence quality trimming and vector removal. Bioinformatics, 17(12), 1093-1104. doi:10.1093/bioinformatics/17.12.1093Altschul, S. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research, 25(17), 3389-3402. doi:10.1093/nar/25.17.3389Edgar, R. C. (2004). MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research, 32(5), 1792-1797. doi:10.1093/nar/gkh340Gouy, M., Guindon, S., & Gascuel, O. (2009). SeaView Version 4: A Multiplatform Graphical User Interface for Sequence Alignment and Phylogenetic Tree Building. Molecular Biology and Evolution, 27(2), 221-224. doi:10.1093/molbev/msp259Park, J., Park, B., Veeraraghavan, N., Jung, K., Lee, Y.-H., Blair, J. E., … Kang, S. (2008). Phytophthora Database: A Forensic Database Supporting the Identification and Monitoring of Phytophthora. Plant Disease, 92(6), 966-972. doi:10.1094/pdis-92-6-0966Vettraino, A. M., Bonants, P., Tomassini, A., Bruni, N., & Vannini, A. (2012). Pyrosequencing as a tool for the detection ofPhytophthoraspecies: error rate and risk of false Molecular Operational Taxonomic Units. Letters in Applied Microbiology, 55(5), 390-396. doi:10.1111/j.1472-765x.2012.03310.xJung, T., & Burgess, T. I. (2009). Re-evaluation of Phytophthora citricola isolates from multiple woody hosts in Europe and North America reveals a new species, Phytophthora plurivora sp. nov. Persoonia - Molecular Phylogeny and Evolution of Fungi, 22(1), 95-110. doi:10.3767/003158509x442612Deagle, B. E., Eveson, J. P., & Jarman, S. N. (2006). Quantification of damage in DNA recovered from highly degraded samples – a case study on DNA in faeces. Frontiers in Zoology, 3(1). doi:10.1186/1742-9994-3-11Dejean, T., Valentini, A., Duparc, A., Pellier-Cuit, S., Pompanon, F., Taberlet, P., & Miaud, C. (2011). Persistence of Environmental DNA in Freshwater Ecosystems. PLoS ONE, 6(8), e23398. doi:10.1371/journal.pone.0023398Guha Roy S, Grunwald NJ. The plant destroyer genus Phytophthora in the 21st century. In book: Review of Plant Pathology, Edition: Volume 6, Publisher: Scientific Publishers (India), Jodhpur, Editors: B.N.Chakraborty, B.B.L.Thakore, pp. In press; 2014.Brasier, C. M., Cooke, D. E. L., Duncan, J. M., & Hansen, E. M. (2003). Multiple new phenotypic taxa from trees and riparian ecosystems in Phytophthora gonapodyides-P. megasperma ITS Clade 6, which tend to be high-temperature tolerant and either inbreeding or sterile. Mycological Research, 107(3), 277-290. doi:10.1017/s095375620300738xHüberli, D., Hardy, G. E. S. J., White, D., Williams, N., & Burgess, T. I. (2013). Fishing for Phytophthora from Western Australia’s waterways: a distribution and diversity survey. Australasian Plant Pathology, 42(3), 251-260. doi:10.1007/s13313-012-0195-6Jung, T., Stukely, M. J. C., Hardy, G. E. S. J., White, D., Paap, T., Dunstan, W. A., & Burgess, T. I. (2011). Multiple new Phytophthora species from ITS Clade 6 associated with natural ecosystems in Australia: evolutionary and ecological implications. Persoonia - Molecular Phylogeny and Evolution of Fungi, 26(1), 13-39. doi:10.3767/003158511x557577Brasier, C. M., Sanchez-Hernandez, E., & Kirk, S. A. (2003). Phytophthora inundata sp. nov., a part heterothallic pathogen of trees and shrubs in wet or flooded soils. Mycological Research, 107(4), 477-484. doi:10.1017/s0953756203007548Hansen, E. M., Reeser, P. W., & Sutton, W. (2012). PhytophthoraBeyond Agriculture. Annual Review of Phytopathology, 50(1), 359-378. doi:10.1146/annurev-phyto-081211-172946Reeser, P. W., Sutton, W., Hansen, E. M., Remigi, P., & Adams, G. C. (2011). Phytophthora species in forest streams in Oregon and Alaska. Mycologia, 103(1), 22-35. doi:10.3852/10-013Nechwatal, J., Bakonyi, J., Cacciola, S. O., Cooke, D. E. L., Jung, T., Nagy, Z. Á., … Brasier, C. M. (2012). The morphology, behaviour and molecular phylogeny ofPhytophthorataxon Salixsoil and its redesignation asPhytophthora lacustrissp. nov. Plant Pathology, 62(2), 355-369. doi:10.1111/j.1365-3059.2012.02638.xHuai, W. -x., Tian, G., Hansen, E. M., Zhao, W. -x., Goheen, E. M., Grünwald, N. J., & Cheng, C. (2013). Identification ofPhytophthoraspecies baited and isolated from forest soil and streams in northwestern Yunnan province, China. Forest Pathology, 43(2), 87-103. doi:10.1111/efp.12015Oh, E., Gryzenhout, M., Wingfield, B. D., Wingfield, M. J., & Burgess, T. I. (2013). Surveys of soil and water reveal a goldmine of Phytophthora diversity in South African natural ecosystems. IMA Fungus, 4(1), 123-131. doi:10.5598/imafungus.2013.04.01.1

Analytical solution of velocity distribution for flow through submerged large deflection flexible vegetation

An analytical solution for predicting the vertical distribution of streamwise mean velocity in an open channel flow with submerged flexible vegetation is proposed when large bending occurs. The flow regime is separated into two horizontal layers: a vegetation layer and a free water layer. In the vegetation layer, a mechanical analysis for the flexible vegetation is conducted, and an approximately linear relationship between the drag force of bending vegetation and the streamwise mean flow velocity is observed in the case of large deflection, which differes significantly from the case of rigid upright vegetation. Based on the theoretical analysis, a linear streamwise drag force-mean flow velocity expression in the momentum equation is derived, and an analytical solution is obtained. For the free water layer, a new expression is presented, replacing the traditional logarithmic velocity distribution, to obtain a zero velocity gradient at the water surface. Finally, the analytical predictions are compared with published experimental data, and the good agreement demonstrates that this model is effective for the open channel flow through the large deflection flexible vegetation

Steady nonuniform shallow flow within emergent vegetation

Surface flow redistribution on flat ground from crusted bare soil to vegetated patches following intense rainfall events elevates plant available water above that provided by rainfall. The significance of this surface water redistribution to sustaining vegetation in arid and semiarid regions is undisputed. What is disputed is the quantity and spatial distribution of the redistributed water. In ecohydrological models, such nonuniform flows are described using the Saint-Venant equation (SVE) subject to a Manning roughness coefficient closure. To explore these assumptions in the most idealized setting, flume experiments were conducted using rigid cylinders representing rigid vegetation with varying density. Flow was induced along the streamwise x direction by adjusting the free water surface height H(x) between the upstream and downstream boundaries mimicking the nonuniformity encountered in nature. In natural settings, such H(x) variations arise due to contrasts in infiltration capacity and ponded depths during storms. The measured H(x) values in the flume were interpreted using the SVE augmented with progressively elaborate approximations to the roughness representation. The simplest approximation employs a friction factor derived from a drag coefficient (Cd) for isolated cylinders in a locally (but not globally) uniform flow and upscaled using the rod density that was varied across experiments. Comparison between measured and modeled H(x) suggested that such a "naive" approach overpredicts H(x). Blockage was then incorporated into the SVE model calculations but resulted in underestimation of H(x). Biases in modeled H(x) suggest that Cd must be varying in x beyond what a local or bulk Reynolds number predicts. Inferred Cd(x) from the flume experiments exhibited a near-parabolic shape most peaked in the densest canopy cases. The outcome of such Cd(x) variations is then summarized in a bulk resistance formulation that may be beneficial to modeling runon-runoff processes on shallow slopes using SVE

Steady nonuniform shallow flow within emergent vegetation

Surface flow redistribution on flat ground from crusted bare soil to vegetated patches following intense rainfall events elevates plant available water above that provided by rainfall. The significance of this surface water redistribution to sustaining vegetation in arid and semiarid regions is undisputed. What is disputed is the quantity and spatial distribution of the redistributed water. In ecohydrological models, such nonuniform flows are described using the Saint-Venant equation (SVE) subject to a Manning roughness coefficient closure. To explore these assumptions in the most idealized setting, flume experiments were conducted using rigid cylinders representing rigid vegetation with varying density. Flow was induced along the streamwise x direction by adjusting the free water surface height H(x) between the upstream and downstream boundaries mimicking the nonuniformity encountered in nature. In natural settings, such H(x) variations arise due to contrasts in infiltration capacity and ponded depths during storms. The measured H(x) values in the flume were interpreted using the SVE augmented with progressively elaborate approximations to the roughness representation. The simplest approximation employs a friction factor derived from a drag coefficient (Cd) for isolated cylinders in a locally (but not globally) uniform flow and upscaled using the rod density that was varied across experiments. Comparison between measured and modeled H(x) suggested that such a "naive" approach overpredicts H(x). Blockage was then incorporated into the SVE model calculations but resulted in underestimation of H(x). Biases in modeled H(x) suggest that Cd must be varying in x beyond what a local or bulk Reynolds number predicts. Inferred Cd(x) from the flume experiments exhibited a near-parabolic shape most peaked in the densest canopy cases. The outcome of such Cd(x) variations is then summarized in a bulk resistance formulation that may be beneficial to modeling runon-runoff processes on shallow slopes using SVE

Steady nonuniform shallow flow within emergent vegetation

Surface flow redistribution on flat ground from crusted bare soil to vegetated patches following intense rainfall events elevates plant available water above that provided by rainfall. The significance of this surface water redistribution to sustaining vegetation in arid and semiarid regions is undisputed. What is disputed is the quantity and spatial distribution of the redistributed water. In ecohydrological models, such nonuniform flows are described using the Saint-Venant equation (SVE) subject to a Manning roughness coefficient closure. To explore these assumptions in the most idealized setting, flume experiments were conducted using rigid cylinders representing rigid vegetation with varying density. Flow was induced along the streamwise x direction by adjusting the free water surface height H(x) between the upstream and downstream boundaries mimicking the nonuniformity encountered in nature. In natural settings, such H(x) variations arise due to contrasts in infiltration capacity and ponded depths during storms. The measured H(x) values in the flume were interpreted using the SVE augmented with progressively elaborate approximations to the roughness representation. The simplest approximation employs a friction factor derived from a drag coefficient (Cd) for isolated cylinders in a locally (but not globally) uniform flow and upscaled using the rod density that was varied across experiments. Comparison between measured and modeled H(x) suggested that such a "naive" approach overpredicts H(x). Blockage was then incorporated into the SVE model calculations but resulted in underestimation of H(x). Biases in modeled H(x) suggest that Cd must be varying in x beyond what a local or bulk Reynolds number predicts. Inferred Cd(x) from the flume experiments exhibited a near-parabolic shape most peaked in the densest canopy cases. The outcome of such Cd(x) variations is then summarized in a bulk resistance formulation that may be beneficial to modeling runon-runoff processes on shallow slopes using SVE

Analytical solution of velocity distribution for flow through submerged large deflection flexible vegetation

An analytical solution for predicting the vertical distribution of streamwise mean velocity in an open channel flow with submerged flexible vegetation is proposed when large bending occurs. The flow regime is separated into two horizontal layers: a vegetation layer and a free water layer. In the vegetation layer, a mechanical analysis for the flexible vegetation is conducted, and an approximately linear relationship between the drag force of bending vegetation and the streamwise mean flow velocity is observed in the case of large deflection, which differes significantly from the case of rigid upright vegetation. Based on the theoretical analysis, a linear streamwise drag force-mean flow velocity expression in the momentum equation is derived, and an analytical solution is obtained. For the free water layer, a new expression is presented, replacing the traditional logarithmic velocity distribution, to obtain a zero velocity gradient at the water surface. Finally, the analytical predictions are compared with published experimental data, and the good agreement demonstrates that this model is effective for the open channel flow through the large deflection flexible vegetation

The mechanism of energy loss and transition in a flow with submerged vegetation

The mechanism of energy balance in an open-channel flow with submerged vegetation was investigated. The energy borrowed from the local flow, energy spending caused by vegetation drag and flow resistance, and energy transition along the water depth were calculated on the basis of the computational results of velocity and Reynolds stress. Further analysis showed that the energy spending in a cross-section was a maximum around the top of the vegetation, and its value decreased progressively until reaching zero at the flume bed or water surface. The energy borrowed from the local flow in the vegetated region could not provide for spending; therefore, surplus borrowed energy in the non-vegetated region was transmitted to the vegetated region. In addition, the total energy transition in the cross-section was zero; therefore, the total energy borrowed from the flow balanced the energy loss in the whole cross-section. At the same time, we found that there were three effects of vegetation on the flow: turbulence restriction due to vegetation, turbulence source due to vegetation and energy transference due to vegetation, where the second effect was the strongest one. Crown Copyright (C) 2010 Published by Elsevier Ltd. All rights reserved

Geochemical characteristics and environmental significance of Talede loess-paleosol sequences of Ili Basin in Central Asia

The loess-paleosol deposit in Central Asia is a sensitive indicator of the evolution of the quaternary paleoclimate in the Westerlies, providing insight into the quaternary climate history and its relationship with global climatic changes. Based on the geochemical analysis of elemental composition of densely sampled strata from Talede loess-paleosol sequence in the Ili Basin, the results showed that SiO2had the highest major elements content, followed by Al2O3. The order of compositional abundance of major elements was generally as follows: SiO2&gt; Al2O3&gt; CaO &gt; Fe2O3&gt; MgO &gt; Na2O &gt; K2O. Trace elements (i.e. Rb, Sr, Sc, Ni, Cu, Ga, Mo, Y, Pb, Th) in the paleosol layers (i.e. S0, Sm, S1) and the loess layer of L1were enriched relative to underlain loess (L2) horizons, except for the contents of Zr, Cs, Nd, and La in paleosol layers. All of geochemical proxies, such as enrichment factor, Rb/Sr ratio, eluvial coefficient (Ki) and chemical weathering index, display no obvious differentiation in the Talede loess-paleosol deposit. The results indicate that the weak chemical weathering, greater evaporation and low effective moisture in Ili Basin, are to a degree weaker than those in the China Loess Plateau and the climate was warm-dry during the interglacial period. In addition, the loess of Ili area is rich in schistose minerals and implies that the loess may come from the deserts of Central Asia and it may be closely related to the widespread aridification of Central Asia.</p