<p>Methods: additional information</p><p>California is an appropriate location for the commercial strawberry farms in our study because it is the leading producer in the U.S., accounting for 87% of the nation’s production, with nearly 5% of its total strawberry acreage in organic production </p><p>(California Strawberry Commission, 2009). In 2005, the Watsonville/Salinas growing region, where this study was done, grew strawberries on 4,857 hectares, 42% of the fall- planted strawberries in the state (California Strawberry Commission, 2009). This large strawberry growing region not only provided this study with two different farming systems (organic and conventional) but also with two different major soil types, coarse- textured (stabilized sand dunes) and fine-textured (alluvial deposits). The organic fields had been certified organic for at least 5 years, providing sufficient time for the organic farming practices to influence soil properties. The organic fields relied only on organically certified fertilizers and pesticides and no soil fumigation. The conventional fields also had been managed conventionally for at least 5 years and included the use of inorganic and organic fertilizers, synthetic pesticides, and soil fumigation (methyl bromide with or without chloropicrin) to control soil-borne diseases, nematodes, soil- dwelling insects, and weeds. </p><p>Soil chemical and physical properties were analyzed for the following properties using methods described in Gavlak et al. (2003): Particle size (sand, silt, and clay percentages) by the hydrometer method (Method S14.10); nitrate N with the chromotropic acid method (Method S3.30); ammonium N with the salicylate method </p><p>(Method S3.50); Olsen P (Method S4.10); NH4OAc extractable K, Ca, Mg and Na </p><p>(Method S5.10) and total bases by summation of extractable bases; DTPA-Sorpitol </p><p>1 extractable S. B. Mn, Zn, Cu and Fe (Method S6.11); pH (Method S2.20) and electrical conductivity (Method S2.30) in a 1:1 w/v water saturated paste; and SMP soil buffer pH </p><p>(Method S2.50).</p><p>For microarray analysis conducted at ORNL, soil community DNA was extracted using an SDS-based method (Zhou et al, 1996). Due to low yields of DNA, a total of 10g soil from organic fields and 20g soil from conventional fields was used for extractions. </p><p>DNA was purified using the Wizard PCR cleanup system (Promega, Madison, WI) and precipitated with ice-cold ethanol (100%). The pellet was washed in 500 μl ethanol </p><p>(70%) before being resuspended in 20 μl 10 mM Tris (pH 8.0). Microarray slides were constructed according to methods described previously (Rhee et al., 2004; Wu et al., </p><p>2006; He et al., 2007). Arrays consisted of more than 24,000 oligonucleotide probes (50 mer design) targeting genes involved in denitrification, nitrification, nitrogen fixation, phosphorus storage, carbon polymer degradation, degradation of xenobiotic compounds and metal resistance (He et al., 2007).</p><p>Thirty to 150 ng Purified DNA was randomly amplified using rolling circle PCR with a GenomiPhi DNA amplification kit (GE Healthcare, Piscataway, NJ) (Wu et al., 2006). </p><p>While differences in DNA amplification and labeling efficiency between samples are unavoidable, the mean labeling efficiency per treatment was calculated to ensure no overall bias. The amplification product (20µl) was fluorescently labeled with Cy5 dye with an extended 6 h incubation time and applied directly to the microarray (Rhee et al., </p><p>2004). Slides and all solutions were kept at 60°C during assembly to minimize cross hybridization. Hybridizations were carried out at 50°C with 50% formamide (Rhee et al., </p><p>2004). After hybridization processed through a series of washes of decreasing stringency</p><p>2 as outlined by the manufacture (Corning Life Sciences, TOWN COUNTRY) and dried using compressed air. All samples were run with triplicate technical replicate arrays and were scanned using a ScanArray 5000 microarray analysis system (Perkin-Elmer, </p><p>Wellesley, Mass.). </p><p>Multivariate data analysis</p><p>Both environmental data types were first standardized (z-transformation) to compensate for scale difference among measurements. The constraining environmental variables were selected based on variation inflation factor (VIF) for canonical correspondence analysis </p><p>(CCA) and the Bio-Env procedure (Clarke and Ainsworth, 1993) for the Mantel test. </p><p>Variations in the microbial communities were partitioned into soil processes, soil properties and management scheme. Variance partitioning analysis (VPA) was carried based on the adjusted R2 (Peres-Neto et al., 2003). Microbial communities were represented by Non-metric multidimensional scaling (NMDS) and the ordination configuration was tested by analysis of similarity (anosim). Multivariate statistical analyses were carried in R (v.2.6.1) and functions of vegan package (v.1.13-1).</p><p>References</p><p>Clarke KR, Ainsworth M (1993) A method of linking multivariate community structure </p><p> to environmental variables. Mar Ecol Prog Ser 92:205-219</p><p>California Strawberry Commission (2009) California Strawberry Commission Website. </p><p>Available: www.calstrawberry.com/. Accessed on 2009 Nov 27.</p><p>3 Gavlak R, Horneck D, Miller RO, Kotuby-Amacher J (2003) Soil, Plant and Water </p><p>Reference Methods for the Western Region, 2nd edn. WCC-103 Publication, Colorado </p><p>State University, Ft. Collins, Colorado, USA.</p><p>He, Z., T. J. Gentry, C. W. Schadt, L. Wu, J. Liebich, S. C. Chong, Z. Huang, W. Wu, B. </p><p>Gu, P. Jardine, C. Criddle, and J. Zhou. 2007. GeoChip: a comprehensive microarray </p><p> for investigating biogeochemical, ecological and environmental processes. ISME J. </p><p>1:67-77.</p><p>Peres-Neto PR, Legendre P, Dray S, Borcard, D (2006) Variation partitioning of species </p><p> data matrices: estimation and comparison of fractions. Ecology 87: 2614-2625.</p><p>Reganold JP, Palmer AS, Lockhart JC, Macgregor AN (1993) Soil quality and financial </p><p> performance of biodynamic and conventional farms in New Zealand. Science </p><p>260:344-349.</p><p>Rhee, S.-K., X. Liu, L. Wu, S.C. Chong, X. Wan, and J. Zhou. 2004. Detection of genes</p><p> involved in biodegradation and biotransformation in microbial communities by using </p><p>50-mer oligonucleotide microarrays. Appl. Environ. Microbiol. 70:4303-4317.</p><p>Wu, L., X. Liu, C.W. Schadt, and J. Zhou. 2006. Microarray-based analysis of </p><p> subnanogram quantities of microbial community DNAs by using whole-community </p><p> genome amplification. Appl. Environ. Microbiol. 72:4931-4941.</p><p>Zhou J., Bruns M.A., Tiedje J.M. (1996) DNA recovery from soils of diverse </p><p> composition. Am. Soc. Microbiol. 62:316-322.</p><p>4</p>