From plant to soil: Quantitative changes in pine and juniper extractive compounds at diferent transformation stages

Vol.: (0123456789) 1 3 Plant Soil https://doi.org/10.1007/s11104-022-05631-x RESEARCH ARTICLE From plant tosoil: Quantitative changes inpine andjuniper extractive compounds atdifferent transformation stages CiprianoCarrero‑Carralero· AnaI.Ruiz‑Matute· JesúsSanz· LourdesRamos· MaríaLuzSanz · GonzaloAlmendros Received: 1 March 2022 / Accepted: 26 July 2022 © The Author(s) 2022 maps, was used to study changes in molecular assemblages during their transformation from plant to soil. Shannon Wiener diversity indices were also determined for the main groups of molecules to quantify the progressive removal or the appearance of new compounds throughout the transformation. Results In the lipid fraction up to 126 compounds were identified, mainly alkanes (C10–C30 in pine forest and C10–C36 in juniper forest), fatty acids and cyclic compounds. In the polar extracts, up to 22 compounds were found, mainly sugars, polyols, cyclic acids and fatty acids. Conclusion Comparing the successive stages of evolution of leaf extractive compounds, alkanoic acids and disaccharides tend to accumulate in the soil. On the other hand, the greatest molecular complexity was found in the intermediate stage (litter), and attributed to the coexistence of biogenic compounds with their transformation products, while the molecular complexity was simpler in soil extracts. This preliminary investigation could be extended to specific studies on the factors that determine the quality of soil organic matter under different environmental scenarios. Keywords Gas chromatography-mass spectrometry· Free lipids· Soluble carbohydrates· Biomarker compounds· Polar compounds Abstract Purpose The transformation of extractable plant compounds after their incorporation into soil was qualitatively and quantitatively studied in two forests under Juniperus communis L. and Pinus sylvestris L. Methods Leaf, litter and soil samples were taken from representative pine and juniper forests in central Spain. The lipid fraction was extracted with dichloromethane, while methanol was used for polar compounds, which were then derivatized (silylationoximation). Extracts were analyzed by gas chromatography-mass spectrometry. van Krevelen’s graphical-statistical method, enhanced as surface density Responsible Editor: Iain Paul Hartley. Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1007/ s1110402205631-x. C.Carrero-Carralero· A.I.Ruiz-Matute· J.Sanz· L.Ramos· M.L.Sanz(*) Instituto de Química Orgánica General (IQOG-CSIC), Juan de la Cierva 3, 28006Madrid, Spain e-mail: [email protected] C.Carrero-Carralero Basque Culinary Center, Facultad de Ciencias Gastronómicas, Mondragon Unibertsitatea, Donostia– SanSebastián, Spain G.Almendros Museo Nacional de Ciencias Naturales (MNCN, CSIC), Serrano 115-B, 28006Madrid, Spain Plant Soil 1 3 Vol:. (1234567890) Introduction Soil organic matter consists of a complex mixture of very different compounds in terms of molecular weight, chemical structure and physical properties, which derive from the degradation of lignocellulosic plant biomass accumulated in the litter layer (Tu etal. 2017), or are produced from the heterotrophic activity of mesofauna, bacteria and fungi in soil and on its surface (de Nobili etal. 2020; Spaccini and Piccolo, 2007). Although free organic compounds of low molecular weight are minor components of soils (from 0.2 to 4% of total carbon), this fraction may exert an important influence on many environmental processes, including allelopathic interactions and the effect on soil physico-chemical properties (El-Ghorab etal. 2008). The soil lipid fraction is a heterogeneous mixture that includes a wide variety of compounds soluble in organic solvents of low to medium polarity, including complex condensed non-volatile components and simpler functional classes such as hydrocarbons, fatty acids, wax esters, ketones, hydroxyl acids, terpenoids, steroids, acylglycerols, phospholipids, lipopolysaccharides, etc. (Dinel etal. 1990). These compounds fulfill crucial functions in the ecosystem, such as forming hydrophobic coatings on the surface of soil aggregates, turning them more hydrophobic and preventing their physical disruption and hindering the biodegradation of the encapsulated organic matter preserved within these soil microcompartments (Jambu et al. 1995). On the other hand, soil lipids could be considered a molecular record of diagnostic compounds that provide valuable biogeochemical information on the structure and dynamics of ecosystems (Aldana etal. 2020; Angst etal. 2016; Couvillion etal. 2020). Other important low molecular weight compounds, which have been poorly studied and are found in soils associated with lipid molecules, are soluble low molecular weight carbohydrates (LMWC). Although plants represent the main source of these compounds in soils, microorganisms (fungi, bacteria, algae) and edaphic fauna also contribute to a lesser extent. In fact, these compounds also influence structure, chemical processes, plant nutrition and microbial activity of soils (Medeiros etal. 2006). In any case, basic and applied research on the transformation processes of soil organic matter are of crucial importance to understand the mechanisms of carbon sequestration in the soil, as well as for the early diagnosis of soil degradation and the evaluation of the environmental impact (Jiménez-González etal. 2020) and the benefits of organic matter for soil resilience and productivity (Cotrufo and Lavallee 2022). However, the different processes involved in carbon stabilization have always been highly controversial, as no agreement has been reached to establish the relative importance of each of the different mechanisms (Schmidt et al. 2011; Lehmann and Kleber, 2015; Almendros etal. 2018; de Nobili etal. 2020). In this context, the analysis of molecular assemblages of soil components, including free lipids and soluble LMWC, can present very useful information, since it constitutes a biogeochemical record of biomarker compounds that provide information about organisms and processes involved in the transformation of organic matter (Tinoco etal. 2018). In particular, the study of the evolution of lipids and soluble LMWC from the plant to the soil would make it possible to assess to what extent the different types of soil present a different activity in terms of modifying the chemical composition of their biomass. This would constitute an objective molecular criterion to define the maturity of the humus. Free lipids and LMWC can be extracted from the soil using appropriate organic solvents. In the case of lipids, hexane, ethyl ether, dichloromethane or its admixtures have been frequently used (Stevenson 1982), whereas polar solvents, such as methanol, ethanol or water are used for the extraction of carbohydrates (Mena-García et al. 2019). Obviously, the chemical nature of the extracted compounds will vary with the polarity of the solvent system and the physical conditions used for the extraction (Bull etal. 2000; White etal. 2009). The analysis of compounds present in the free lipid and LMWC fractions has been carried out mainly by gas chromatography coupled to mass spectrometry (GC–MS) (Almendros et al. 1996; Bull etal. 2000; de Blas etal. 2013; Tinoco etal. 2018). This technique provides enough sensitivity and potential for structural identification in qualitative and quantitative analyses of these complex mixtures. However, the accurate identification of individual lipid and carbohydrate molecules is not straightforward. Regarding the quantitative analysis, previous exploratory studies have been Plant Soil 1 3 Vol.: (0123456789) based on relative peak area integration values of each compound as regards the total chromatographic area (Almendros etal. 1996; de Blas etal. 2013; Tinoco etal. 2018), so a reliable quantitative analysis of these compounds has not yet been performed. From a molecular point of view, the quality of the soil organic matter is defined by the extent to which the composition of the forest biomass turns into complex, humified organic matter by the action of biological activity, local and environmental factors resulting in the selective preservation of certain compounds, the transformation of biogenic precursor compounds and the incorporation of new products of microbial synthesis. Depending on the type of vegetation, the local factors and the successive stages of transformation, these processes would lead either to an increase in molecular diversity or to a simplification of its composition due to the preferential accumulation of specific structures that survive biodegradation. In any case, monitoring progressive changes over time in soil molecular assemblages would facilitate understanding the fate of biomass in different soil compartments. In fact, changes in the diversity patterns of the molecular assemblages of extractive compounds in soils have been an object of research for the recognition of source indicators and molecular tracers for environmental impacts on ecosystems (Eglinton etal. 1962a, b). Thus, the main objective of this work was to monitor the molecular transformations that occur in the soil during the processes of biodegradation and humification of organic matter in two Mediterranean forests in central Spain (Juniperus communis L. and Pinus sylvestris L.). These forests were selected taking into account their wide distribution throughout the world (Adams 2008; Eilmann etal. 2006) and the typical presence of slowly biodegradable terpene compounds, which retain the basic skeletal structures of their biological precursors and tend to accumulate in the soil as biomarker compounds. In particular, the study was oriented to the qualitative and quantitative GC–MS analysis of free lipids and LMWC in needles, litter and soils of these two forests for the establishment of molecular indicators to recognize the stage of evolution of the organic matter of soil and thus objectively define its quality and maturity. Materials andmethods Samples Samples (needles, litter and soils) were collected from forest ecosystems of J. communis L. (common juniper) and P. sylvestris L. (Scots pine) in El Espinar (Segovia, Central Spain) (N 40° 43.759’, W 04° 11.099’ at 1260m and N 40° 43.527’, W 04° 10.618’ at 1330m, respectively). Leafy twigs were cut from the plants, while soil samples were collected from the uppermost 6cm after removing the litter layer. Sampling was carried out at three different positions of each forest, separated at least 100m from each other. The subsamples were aggregated and homogenized to obtain representative pools of each species. All samples were air-dried before the extraction procedure. In the case of soil samples, the large aggregates were crushed with a wooden roller, the fragments of rocks and roots were removed by hand and the resulting soil material was sieved through a 2mm mesh (fine earth). Analytical standards Analytical standards of phenolic compounds such as acenaphthenequinone, benzil, 1-phenyl-1-butanol, perylene and phenanthrene (used as internal standards for non-polar compounds) and phenyl-β-Dglucoside (used for polar compounds) were acquired from Sigma Chemical Co. (St. Louis, US). Carbohydrate standards of polyalcohols (chiro-inositol, mannitol, muco-inositol, myo-inositol and pinitol), monosaccharides (fructose and glucose) and disaccharides (sucrose and trehalose) were also obtained from Sigma Chemical Co. Sequoyitol was purchased from Extrasynthese (Genay, France) and quebrachitol from Acros (Geel, Belgium). Methyl-1-muco-inositol was obtained from a honey sample as indicated by Sanz etal. (2004). Extraction procedure Needles were ground with a grinder, while the soil and litter samples were ground in an agate mortar to obtain a fine and homogeneous powder. The samples were sieved through a 500 μm mesh and stored in glass flasks under dry conditions and protected from direct light until analysis. Plant Soil 1 3 Vol:. (1234567890) To obtain the non-polar extracts, 0.3 g of leaf powder and 2 g of litter and soil powder samples were suspended in 6mL of dichloromethane; 20 µL of internal standard (acenaphthenequinone, benzil, 1-phenyl-1-butanol, perylene or phenanthrene) solution (1.6mg mL−1) were added to the sample solutions. Then, the suspensions were ultrasonicated for 30 min in a bath. The collected extracts were filtered using silanized glass wool and centrifuged at 4400g for 5min. The extracts were evaporated under vacuum (miVac Duo concentrator, Genevac TM, Ipswich, UK) at 37 °C until complete dryness and redissolved in 1mL of dichloromethane. The polar extracts were obtained from needle (0.3g), litter and soil (2g each) powder using methanol (6 mL) as extraction solvent. Ultrasound was applied for 30min in order to enhance the extraction of the compounds. The samples were then allowed to stand for 30min at room temperature. Extracts were filtered through Whatman No. 4 paper and centrifuged at 4400g for 5min. The extracts were evaporated under vacuum and redissolved in 2 mL of methanol. Derivatization procedure Prior to the GC–MS analysis of the polar extracts, a two-step derivatization was carried out as indicated by Ruiz-Matute etal. (2007). This two-step derivatization procedure (oximation + silylation) gave two peaks for reducing carbohydrates, corresponding to the syn (E) and anti (Z) forms, and a single peak for non-reducing sugars and inositols, corresponding to the O-persilylated derivative. Although it is a two step derivatization procedure, it is easy to be developed, resulting spectra give high structural information and derivatives are as volatile and much more stable than trimethylsilyl derivatives. Samples were prepared by mixing methanol extracts (0.5mL) with 0.1mL of a 70% ethanol solution of phenyl-β-D-glucoside (1 mg mL−1), which was used as internal standard. Samples were evaporated under vacuum and treated with 350 µL of 2.5% hydroxylamine chloride in pyridine at 75 °C for 30 min. Then, 350 µL of hexamethyldisilazane (HMDS) and 35 µL of trifluoroacetic acid (TFA) were added and kept at 45°C for 30min. The samples were centrifuged at 7000g for 5min at 5°C, and 1 μL of the supernatant was injected onto the GC column. GC–MS analysis Instrumental analysis of the extracts was carried out in a 6890A gas chromatograph coupled to a 5973 quadrupole mass detector (both from Agilent Technologies, Palo Alto, CA, USA), using He as carrier gas. A ZB-1MS (cross-linked methyl silicone) column (30m × 0.25mm i.d.; 0.25μm film thickness) from Phenomenex (Torrance, CA) was used. For dichloromethane extracts, the oven was kept at 70 °C during 1.5 min, then heated to 290 °C at 6°C min−1 and kept for 20min (total analysis time of 58min). Injections were carried out in splitless mode (1min) at 275°C. For the methanol extracts, the oven temperature was programmed from 120°C to 300°C at 5°C min−1 and kept for 20min (total analysis of 56min). The injections were carried out in split mode (1:50) at 300 °C. The transfer line and the ionization source were thermostated at 280 and 230 °C, respectively. Mass spectra were recorded in electron impact (EI) mode at 70eV within the mass range m/z 35 − 650. Data acquisition was performed using MSD ChemStation software (Agilent Technologies). The identification of compounds in non-polar extracts was based on the comparison of experimental linear retention indices (IT) and mass spectra with those reported on the literature (Adams 2007) and available databases (Wiley, NIST). Compounds of polar extracts were identified by comparing IT and mass spectra with those of corresponding commercial standards described above. Compounds for which commercial standards were not available were tentatively identified based on their mass spectral information. Quantitation was carried out by the internal standard method. Standard solutions of target compounds over the expected concentration range in the samples under study were prepared to calculate the response factor relative to internal standard. Phenyl-β-Dglucoside was selected as internal standard for polar extracts. The concentrations of compounds for which commercial standards were not available were estimated assuming a response factor equal to 1. Regarding non-polar compounds, several internal standards, chemically similar to the compounds to be analyzed but not expected to occur naturally in the samples Plant Soil 1 3 Vol.: (0123456789) and eluting in different regions of the chromatogram, were evaluated: i.e., 1-phenyl-1-butanol, phenanthrene, benzil, acenaphthenequinone and perylene. Inter-day precision and the limit of detection (LOD) and the limit of quantitation (LOQ) were evaluated using these internal standards and considering specific compounds representative for each group of analytes investigated (n-nonacosane (C29), hexadecanoic acid (C16), α-thujene, caryophyllene and abietatriene). According to Foley and Dorsey (1984), the LOD was calculated as three times the signal to noise ratio (S/N), where N was five times the standard deviation of the noise, whereas the LOQ was considered ten times this ratio. Inter-day precision (relative standard deviation, RSD) for the above specific compounds was calculated from the results obtained for a leaf extract analyzed on five different days. All analyses were carried out in triplicate. Data analysis and processing To express the changes in the molecular complexity of the lipid compound assemblages, the Shannon–Wiener (H’) diversity indices were calculated for the different groups (alkanes, fatty acids, monoterpenes, sesquiterpenes and diterpenes). This index could illustrate the extent to which molecules are synthesized, transformed or degraded in the plant-soil system, and was calculated using the program Species Diversity & Richness (Seaby andHenderson 2006). Van Krevelen plots The representation of the quantitative data of the different molecules was carried out using a graphicalstatistical approach based on the classic van Krevelen diagram (van Krevelen 1950). This procedure has proven useful in simplifying the interpretation of complex mixtures of compounds released by different analytical methods (Ikeya etal. 2015; JiménezMorillo etal. 2016; Ohno etal. 2014). The improved approach used consisted of plotting “surface density plots” constructed from the abundances of individual lipid compounds represented in the space defined by their H/C and O/C atomic ratios (Almendros et al. 2018). The scores for atomic O/C and H/C ratios of the molecules are plotted in the basal plane (x,y axes) and the vertical dimension (z axis) represents the normalized abundances (sum = 100) of the quantitative data of individual compounds (Tables 1, 2, and 3). The resulting plot shows a series of 3D peaks or compound clusters, whose sizes are proportional to the collective abundances of the compounds with similar elemental composition. Results Analysis of non-polar extracts Figure1 shows the GC–MS profiles of dichloromethane extracts from needles, litter and soils from samples collected from of J. communis and P. sylvestris forests, respectively. In general, complex chromatographic profiles were observed, in particular for leaves and litter extracts. Prior to the identification and quantitation of lipids in the samples, a selection of appropriate internal standards was required. Taking into account the complexity of the samples, coelutions of phenanthrene and acenaphthenequinone with compounds naturally present in the samples were observed; therefore, the use of these standards was discarded. Perylene eluted in a clean zone of the chromatogram, however, non-reproducible results were obtained when used as internal standard (RSD: 28–170%). Therefore, 1-phenyl-butanol and benzil were selected for the quantitative analysis of free lipids in the samples (RSD < 25%). LOD and LOQ on average were 1.3µg g−1 and 4.8µg g−1, respectively. Table1 shows the concentrations (μg g−1 dry sample) of lipids found in the needles, litter and soil of pine and juniper forests. In these samples, up to 126 compounds were identified mainly to alkanes, fatty acids and cyclic compounds (terpenoids and steroids). Alkyl series, including alcohols, ketones, etc., were also detected, although in much lower concentrations, so these compounds were indicated in Table1 as “other compounds”. Needle extracts showed the greatest lipid concentrations for both juniper (3.2mg g−1) and pine (5.6mg g−1). Only 28 free lipid compounds were found in pine soils; this sample also showed the lowest lipid concentration (65 µg g−1). In general, among the different lipids detected, terpenoids were the most abundant in needles and litter of both juniper and pine, while alkanes were the predominant family in soils. Overall, monoterpenes were less abundant than sesquiterpenes and diterpenes. Plant Soil 1 3 Vol:. (1234567890) Table 1 Concentration (µg g−1) of lipids identified in dichloromethane extracts obtained from needles, litter and soils from forests of Juniperus communis and Pinus sylvestris AnalytedITJuniperus communis Pinus sylvestris Needles Litter Soil Needles Litter Soil Alkanes Branched decane 998 16.2 (5.2)a2.6 (2.3) 8.1 (1.3) 19.9 (21.6) 3.1 (0.5) 2.4 (0.5) Decane 1003 37.1 (25.6) 11.9 (0.8) 66.0 (53.4) 43.9 (40.1) 6.9 (1.5) 4.6 (1.0) Branched undecane 1093 17.6 (6.7) 4.5 (0.1) 6.7 (1.0) 20.1 (21.1) 3.4 (0.6) 2.9 (0.8) Undecane 1096 44.2 (32.3) 14.1 (0.1) 72.0 (52.5) 49.4 (42.8) 7.7 (1.9) 4.9 (1.2) Dodecane 1198 2.1 (1.0) 0.8 (0.1) 1.0 (0.3) trb– – Tridecane 1301 – – 1.7 (0.1) 3.9 (0.1) 0.6 (0.1) – Tetradecane 1403 – – – 15.1 (0.5) 0.41 (0.05) – Pentadecane 1502 1.2 (0.5) – 0.9 (0.2) 3.6 (2.9) – – Hexadecane 1600 – – 1.3 (0.1) 3.1 (1.1) – – Heptadecane 1700 – – 1.1 (0.1) – – – Octadecane 1800 tr – 1.0 (0.4) – 0.4 (0.02) – Nonadecane 1900 – – 0.7 (0.3) – – – Eicosane 2000 – – 0.7 (0.3) – 0.52 (0.01) 0.2 (0.1) Heneicosane 2101 3.8 (0.2) 3.2 (0.8) 0.71 (0.01) – 2.6 (0.3) 0.5 (0.1) Docosane 2200 – – – – – 0.4 (0.1) Tricosane 2300 – 0.7 (0.1) 3.8 (1.6) – 2.2 (0.2) 0.6 (0.1) Pentacosane 2501 – 1.2 (0.5) 2.3 (0.2) 4.6 (0.7) 1.9 (0.2) 1.3 (0.4) Hexacosane 2601 – – 1.5 (0.1) – – – Heptacosane 2700 – 2.1 (0.6) 4.32 (0.42) 7.8 (1.5) 3.8 (1.0) 2.7 (1.5) Octacosane 2799 – – 1.6 (0.7) tr 0.9 (0.1) 0.7 (0.3) Nonacosane 2897 11.4 (3.0) 4.2 (1.2) 13.8 (0.7) 6.8 (1.6) 10.7 (2.6) 11.1 (1.5) Triacontane 3001 – 0.8 (0.1) 1.10 (0.01) tr 0.8 (0.1) 0.7 (0.6) Branched hentriacontane 3069 7.5 (1.8) 2.3 (0.4) 6.4 (4.2) – – – Hentriacontane 3099 52.6 (25.9) 14.6 (5.1) 10.4 (0.4) 238.0 (120.3) 15.2 (6.2) 13.1 (10.1) Dotriacontane 3199 13.8 (7.6) 3.6 (1.7) 6.3 (6.2) 15.3 (3.6) 3.0 (2.2) 1.0 (0.1) Tritriacontane 3301 447.3 (235.6) 81.75 (44.9) 22.2 (13.5) 9.8 (2.4) 11.9 (4.5) 4.8 (2.9) Tetratriacontane 3401 12.7 (7.7) 5.2 (3.2) – – – – Pentatriacontane 3499 59.5 (40.4) 8.3 (4.4) 3.35 (0.01) – – – Hexatriacontane 3600 5.5 (3.5) 4.06 (0.02) – – – – Fatty acids Hexanoic acid 961 8.9 (0.5) 176.0 (47.5) – – Oxononanoic acid 1452 – – – 52.9 (19.4) – – Dodecanoic acid 1545 16.3 (4.0) – – 59.8 (60.8) – – Tetradecanoic acid 1741 11.4 (0.6) 6.4 (3.5) – – – Pentadecanoic acid 1866 12.5 (5.5) 12.6 (5.8) 0.61 (0.05) – – – Plant Soil 1 3 Vol.: (0123456789) Table 1 (continued) AnalytedITJuniperus communis Pinus sylvestris Needles Litter Soil Needles Litter Soil Hexadecanoic acid 1940 90.0 (16.9) 5.7 (1.0) – 53.1 (10.8) – – Heptadecanoic acid 2036 – – – –3.6 (1.8) – Octadecanoic acid 2139 19.1 (6.4) – – – – – Cyclic compounds Monoterpenes Artemisiatriene 933 – – – 26.2 (4.3) – – α-Thujene 942 39.6 (4.2) 66.1 (18.5) 3.81 (0.05) 466.2 (21.5) 0.56 (0.01) 0.53 (0.02) α-Pinene 948 43.8 (21.9) 83.4 (20.9) – 168.3 (5.0) – – Camphene 952 – – – 67.1 (3.8) – – Monoterpene (C10H16) 971 6.0 (0.2) 1.9 (1.3) – – – – Sabinene 976 12.9 (1.6) 27.7 (3.5) – 24.8 (4.7) – – β-Pinene 978 – – – 14.6 (3.6) – – p-Cymene 1011 10.0 (0.9) tr 6.2 (3.6) – – – Limonene 1020 15.0 (6.5) 14.0 (14.8) – – – – Monoterpene (C10H16) 1024 15.5 (1.8) 2.8 (2.9) – – – – Monoterpene (C10H16) 1050 10.9 (2.2) 19.6 (6.6) – – – – Sabinene hydrate 1079 6.2 (0.8) 1.9 (2.3) – – – p-Cymenene 1107 – – 7.86 (0.04) – – – α-Campholene aldehyde 1104 – – – 38.6 (8.5) 1.5 (0.8) 4.1 (0.7) Verbenol 1124 13.5 (2.3) 17.5 (17.5) – 50.7 (5.3) 11.2 (3.6) – α-Terpineol 1168 21.8 (14.7) 12.9 (7.6) 3.5 (0.1) – – – Verbenone 1176 – – – 73.9 (8.1) 10.6 (5.3) – Carvone 1213 9.7 (0.7) 2.0 (0.4) – – – – Monoterpene (C10H16) 1300 – – – 8.2 (2.4) – – Limonene glycol 1306 18.7 (0.4) 3.3 (0.1) – – – – Sesquiterpenes α-Cubebene 1350 – – 1.6 (0.3) 28.2 (1.8) 11.7 (5.1) 0.4 (0.2) Sesquiterpene (C15H24) 1352 – – 0.70 (0.01) – – – α-Ylangene 1372 – – 2.1 (0.2) 11.6 (3.1) 3.8 (0.3) – α-Copaene 1377 – – 1.4 (0.4) 33.0 (0.8) 5.4 (1.2) – β-Bourbonene 1385 4.2 (0.3) 1.5 (0.6) – 35.9 (6.7) 12.9 (2.4) – Junipene + sesquiterpene (C15H24) 1391 19.3 (1.6) 22.6 (9.7) 14.3 (0.6) – 11.6 (2.9) – Junipene isomer 1407 – – 46.5 (0.1) – – – di-epi-αCedrene 1414 – – 7.7 (0.6) – – – Plant Soil 1 3 Vol:. (1234567890) Table 1 (continued) AnalytedITJuniperus communis Pinus sylvestris Needles Litter Soil Needles Litter Soil Caryophyllene 1418 30.4 (1.9) 82.4 (21.9) 8.4 (1.3) 269.7 (57.3) 20.2 (3.1) – γ-Elemene 1429 17.8 (0.5) 13.5 (5.6) 6.5 (0.2) – – – β-Copaene 1430 – – – 35.4 (18.7) 5.5 (0.5) – Sesquiterpene (C15H24) 1441 – – – 11.5 (0.7) 4.3 (0.07) – Sesquiterpene (C15H24) 1449 19.7 (1.7) – – 10.0 (6.4) 2.1 (0.2) – α-Humulene 1454 – – – 52.9 (19.4) 2.9 (0.9) – Muurola4(14),5-diene 1459 – – – 28.2 (7.3) 2.0 (0.3) – Germacrene D 1471 9.4 (0.8) 9.3 (3.9) 1.0 (0.2) 144.4 (19.6) 31.0 (1.5) – Germacrene isomer 1477 – – – 112.1 (30.7) 4.6 (0.2) – β-Selinene 1483 9.0 (7.2) 22.5 (10.4) 2.2 (0.2) 29.3 (5.6) 10.2 (0.1) – trans-Cadina1(6),4-diene 1488 – – – 41.70 (7.41) 9.3 (0.18) – α-Muurolene 1495 7.7 (1.7) – – 64.8 (14.4) 18.4 (0.1) – γ-Muurolene 1501 – – – 18.3 (9.3) – – Sesquiterpene alcohol 1504 – – – 128.5 (16.8) 4.8 (0.6) – γ-Cadinene 1507 17.0 (3.2) 11.8 (4.3) 3.4 (0.4) 11.91 (0.01) 31.2 (1.1) 0.4 (0.2) δ-Cadinene 1516 – – – 119.5 (3.6) 18.1 (0.8) 0.27 (0.03) Sesquiterpene (C15H24) 1560 – – 3.2 (0.7) – – – Spathulenol 1565 52.8 (8.8) 31.7 (16.6) 3.6 (0.6) 144.3 (16.3) 7.2 (0.5) – Caryophyllene oxide 1571 644.0 (16.2) 173.7 (57.5) 3.7 (0.7) 370.1 (32.8) 22.4 (0.9) – Sesquiterpene alcohol 1584 – – – 7.7 (1.4) – – Humulene epoxide 1595 328.9 (15.6) 103.5 (36.4) – 91.3 (1.0) 5.4 (0.7) – Caryophylla4,8-dien-5-ol 1621 22.9 (2.0) 9.2 (5.3) 2.3 (0.3) 8.9 (2.5) – – Sesquiterpene alcohol 1626 – – – 73.1 (8.1) 5.2 (1.1) – γ-Costol 1637 – 9.1 (0.5) – – – – Sesquiterpene alcohol 1638 – – 0.6 (0.1) 56.6 (7.7) – – Sesquiterpene alcohol 1641 26.3 (5.9) 7.3 (4.7) – – – – Sesquiterpene alcohol 1653 119.8 (17.9) 59.4 (19.1) – 70.7 (2.7) – – Sesquiterpene alcohol 1674 6.6 (1.4) 2.6 (0.2) 5.4 (1.7) – – – Oplopanone 1707 120.1 (7.8) 41.1(17.7) – 107.3 (18.0) 4.0 (0.5) – Spathulenol derivative 1791 11.5 (4.1) 1.9 (1.4) – – – – Diterpenes Dehydroabietal 1960 – – – 13.0 (0.8) 4.7 (1.4) – Plant Soil 1 3 Vol.: (0123456789) Table 1 (continued) AnalytedITJuniperus communis Pinus sylvestris Needles Litter Soil Needles Litter Soil Diterpene (C20H32) 1976 – – – 42.7 (37.3) 4.1 (1.4) 0.2 (0.03) Epimanoyl oxide 1981 12.3 (1.1) 10.0 (3.7) 2.4 (1.0) 11.2 (0.5) 2.9 (0.3) – Pimaradiene 1987 22.7 (2.3) 38.5 (14.3) 3.8 (0.4) – – – Abietatriene I 2034 6.8 (0.3) 10.9 (2.8) 5.0 (0.9) 55.9 (4.1) 6.7 (0.6) 0.3 (0.1) Pimaradiene 2072 9.9 (1.9) 7.6 (1.9) – – – – Diterpene (C20H32) 2117 – – – 12.2 (3.1) 12.8 (6.1) Abietatriene II 2176 – – – tr 1.7 (0.2) 0.10 (0.01) Diterpene (C20H32) 2215 – – – tr 0.90 (0.01) – Totarol 2250 – – 10.1(4.5) – – – Ferruginol I 2275 – 7.3 (4.4) 40.8 (10.3) – – – Ferruginol II 2290 – 1.9 (1.3) 19.4 (18.8) – – – Dehydroabietic acid I 2303 – – – 354.4 (98.8) 71.0 (28.4) 0.47 (0.01) Isopimaric acid 2331 74.8 (3.3) 100.9 (16.8) 50.1 (24.8) 128.4 (132.9) 10.4 (4.6) – Diterpene (C20H32) 2371 – – – 318.3 (56.2) 72.5 (61.5) 0.99 (0.02) Dehydroabietic acid II 2401 – – – 375.9 (84.4) 45.4 (17.8) 0.65 (0.05) Diterpenoid (C20H28O2) 2562 12.7 (4.1) 12.8 (1.0) 2.3 (0.7) – – – Triterpenes D:A-Friedoolean6-ene 3331 –– – – 7.4 (2.8) – α-Amyrin acetate 3358 –– – – 9.3 (4.8) – Steroids Anthraergostatetraenol 2951 –– – – 2.8 (1.6) – Ergosta-4,22dien-3-one 3235 –– – – 6.2 (0.1) – β-Sitosterol 3291 76.3 (20.1) 27.5 (0.1) 7.2 (3.3) 25.1 (3.3) 83.5 (31.4) – Stigmast-4-en3-one 3406 –47.5 (5.4) 6.5 (3.7) – 51.5 (24.6) 3.3 (0.4) Other compounds Benzoic acid 1135 – – – 31.6 (8.3) – – 5,7-Octadien4-one, 2,6,dimethyl 1151 9.1 (1.4) – – – – – Benzaldehyde, 3,4,5-trimethoxy1554 1.6 (0.2) – – – – – 2-Pentadecanone, 6,10,14-trimethyl1828 35.0 (3.3) 20.9 (4.1) – 82.8 (5.1) – – Heptadecanone 1829 39.9 (10.7) – 48.2 (0.1) – – – Plant Soil 1 3 Vol:. (1234567890) percentage was higher in juniper soil (50%). Juniper diterpenes belonged mainly to the chemical families of abietanes and pimaranes (Fig.2S), the latter being the most abundant in needles and litter, while abietanes predominated in soils. Isopimaric acid, pimaradiene isomers and epimanoyl oxide were the pimaranes found in juniper needles, litter and soil; the first one was the most abundant pimarane found in these samples (74.8, 100.9 and 50.1μg g−1, respectively). Regarding the abietanes, abietatriene was detected in the three juniper samples; however, ferruginol was only detected in litter and soil samples. Meanwhile, totarol was only found in soil samples. Abietane diterpenes were abundant in pine needles; among them, isomers of dehydroabietic acid showed the highest concentrations (375.9 and 354.4μg g−1), while a noticeable reduction in the concentration of these compounds was observed in the litter (45.4 and 71.0μg g−1). Other cyclic compounds Two triterpenes (friedoolean-6-ene and α-amyrin acetate) were only detected in pine litter at relatively low concentrations (7.4 and 9.3μg g−1, respectively). Regarding steroids, β-sitosterol was the most abundant, and was detected in all samples, except in pine soil. Stigmast-4-en-3-one was also detected at relatively high concentrations in both the litter and soil of juniper and pine. Analysis ofpolar extracts Figure5 shows the GC–MS profiles of the derivatized methanol extract of needles, litter and soil from (A) juniper and (B) pine. Several peaks with characteristic mass spectra compatible with LMWC structures such as monosaccharides, disaccharides and polyols were identified in these samples. In addition, cyclic acids (such as shikimic, quinic, pimaric and isopimaric acids) and fatty acids (such as n-hexadecanoic (C16) and n-octadecanoic (C18) acids) were also found. Regarding LMWC, glucose, fructose and sucrose were detected in all extracts, except from those of pine soil. The presence of trehalose in these extracts was also confirmed by comparison with the corresponding standard. It should be noted that this compound was the only LMWC detected in pine soil. Linear polyols, such as mannitol, were also detected in these samples. Furthermore, different free inositols such as myo-inositol, and methylinositols such as pinitol (3-O-methyl-D-chiroinositol), 1-methyl-muco-inositol, sequoyitol (5-O-methyl-myo-inositol) and quebrachitol (2-O-methyl-L-chiro-inositol), were detected in both pine and juniper leaves; muco-inositol was also found in leaves of the latter species. Different small peaks with mass spectra compatible with LMWC, mainly inositol derivatives, were also found in pine and juniper needles and litter. However, due to coelution problems, it was not possible to identify them. Table 2 shows the IT values and concentrations (mg g−1) of the LMWC and acids quantified in the extracts studied. The highest concentration of total LMWC was accounted by pine needles (116.3 mg g−1), followed by juniper needles (111.3 mg g−1). The concentration of these compounds was much smaller in the litter and soils of both forest species. 1-Methyl-muco-inositol was the most abundant LMWC detected in juniper needles, followed by glucose and sucrose and pinitol was also found in relatively high concentrations in this particular extract (10.4mg g−1). Mannitol and trehalose were the most abundant LMWC of juniper litter (0.23 and 0.24mg g−1, respectively) and soil (0.03 and 0.15mg g−1, respectively). Regarding the pine forest samples, pinitol was the most abundant LMWC of pine needles, its concentration (108.5mg g−1) notably higher than that observed in juniper needles. As for juniper litter, trehalose and mannitol (0.23 and 0.12mg g−1, respectively) were the most abundant LMWCs found in pine litter and, as previously commented, only low concentrations of trehalose (0.09 mg g−1) were detected in pine soil. The concentrations (mg g−1) of cyclic and fatty acids found in juniper and pine needles, litter and soil are shown in Table3. The highest amounts of these compounds were found in the juniper needles (23.13mg g−1), mainly due to the high contribution of shikimic (10.7mg g−1) and quinic (10.6µg g−1) acids. On the other hand, n-hexadecanoic (C16) and n-octadecanoic (C18) acids were dominant in the soil samples. This trend was also previously observed for fatty acids extracted using the nonpolar solvent. Plant Soil 1 3 Vol.: (0123456789) Evolution of free lipid and polar compounds in van Krevelen diagrams To monitor the molecular transformations during the different stages of biodegradation and humification of soil organic matter, van Krevelen diagrams were used. An interesting aspect of this graphical representation procedure is that it is possible to quickly compare samples using subtracted density maps that represent differences between the normalized concentrations of each of the compounds in different samples (quantitative data from Tables1, 2, and 3 in this study). In these diagrams, with positive and negative values resulting from the subtraction, the differences between the successive stages (leaves → litter → soil) can immediately be interpreted in the form of concentration or selective loss of the different types of compounds. Since the calculation is made by subtracting the concentration values of the leaves from those of the litter or the soil, the positive values (represented in green) indicate the compounds formed by the leaf or predominant in the leaf, whereas negative values (in red) indicate new compounds that appeared in the litter or soil during the transformation, or leaf 12 3 4 5 10 11 12 14 15 19 20 21 17 18 16 13 16 17 7 8 Lier B 1 3 4 5 6 12 13 14 14 15 1819 20 A Needles 9 ecnadnubA ×10 6 510152025303540 Time (min) 4 110 14 19 21 13 16 Soil 510152025303540 Time (min) Soil 1 19 21 16 13 510152025303540 Time (min) Lier 1 2 5 10 14 19 20 21 13 16 510152025303 54 0 Time (min) Needles 1 2 34 5 6 8 10 11 12 13 14 1415 16 17 18 19 20 21 7 510152025303 54 0 Time (min) 11 510152025303540 Time (min) 10 20 30 40 Abundance ×10 6 5 10 20 30 3 5 7 10 ecnadnubA ×10 6 10 20 30 40 Abundance ×10 5 8 12 16 20 ecnadnubA ×10 5 8 16 24 32 Abundance ×10 5 Fig. 5 GC–MS profile of methanol extracts of needles, litter and soil in juniper (A) and pine (B) forests. Peak identification1glycerol; 2pentitol; 3shikimic acid; 41-methyl-mucoinositol; 5pinitol; 6quinic acid; 7quebrachitol; 8inositol; 9muco-inositol; 10mannitol; 11fructose 1 and 2; 12chiroinositol + sequoyitol; 13hexadecanoic acid; 14glucose E and Z; 15myo-inositol; 16octadecanoic acid; 17pimaric acid; 18isopimaric acid; 19phenyl-β-D-glucoside (internal standard); 20sucrose; 21trehalose Plant Soil 1 3 Vol:. (1234567890) compounds that increased their concentration during this process. Free lipid compounds Free lipid compounds quantified in samples from the pine and juniper forest were plotted in the space defined by their H/C and O/C atomic ratios on a van Krevelen diagram (Fig.3S A of Supplementary Material shows the average concentration values of all the samples studied). The coincidence of isomers is noted, but also of compounds of similar elementary composition that are grouped in more or less sharp clusters corresponding to alkanes, low molecular weight terpenes (monoand sesquiterpenoids), mid-oxidation terpenoids (alcohols, oxides and acetates) and highly oxidized terpenoids (resin acids, terpenones…). Other less abundant compounds also tend to cluster as independent groups, mainly steroids, alcohols and aliphatic ketones. Polar compounds Fig.3S B illustrates the average composition of polar compounds found in all the samples (needles, litter and soil) from the pine and juniper forest (the quantitative values corresponded to the normalized average concentration of all the compounds found in the samples studied). The major compounds correspond to the three large groups of cyclitols, disaccharides and alkanoic acids. The remaining minor compounds are grouped into four main clusters, referred to as linear polyols (pentitol and mannitol), monosaccharides, diterpene resin acids and cyclohexanecarboxylic acids Discussion Evaluation of non-polar compounds in pine and juniper forests Shannon (H’) diversity indices, calculated for alkanes, monoterpenes, sesquiterpenes and diterpenes in juniper and pine leaves, litter and soils (Fig.3), traditionally have been used in ecology to describe the composition of populations defined by the number of individuals of different species. Also, they have been related to the degree of maturity or evolution of plant associations, as they are progressively colonized for new species. However, the H’ index can also be very useful to define the molecular populations of the soil as a whole, the complexity of which also increases during humus formation processes. In particular, the greatest diversity is related to emergent properties related to the biogeochemical activity of the soil. Such is the case of resilience or resistance to biodegradation, related to the potential carbon sequestration of soils (Jiménez-González etal. 2018), and could allow an early evaluation of the humification quality, defined by the physicochemical activity of the soil humus i.e., the enhancement of its interactions with organic compounds and with mineral surfaces. Indeed, the effectiveness of these interactions depends on the accumulation in soil of organic matter with chaotic structures that progressively differs from the precursor biogenic macromolecules of plant and microbial biomass, where the increase in molecular diversity paralleling humus maturity would be explained by the structural alteration of the precursor compounds in addition to the incorporation of new microbial metabolites (Almendros etal. 1996). The increase observed in this work of H’ values of alkanes, sesquiterpenes and diterpenes from needles to soil could be due to the contribution of microbial products in soils and/or to molecular rearrangements, leading to new lipid molecules. On the other hand, the decrease in the diversity of monoterpenes, indicating a simplification in the molecular composition of the apolar fraction, points to their selective biodegradation, their condensation or fixation into macromolecular structures, or both, with a corresponding decrease in the concentration of these molecules as free extractive compounds (Almendros etal. 1996). Regarding alkanes (Fig.4), the predominance of long-chain (> C20) alkanes in juniper needles and litter and of short-chain (< C20) alkanes in juniper soil indicated that most of the alkanes in the litter are inherited from the plant rather than derived from microbial metabolism (Simoneit and Mazurek 1982). The high predominance of short-chain alkanes in juniper soils could be attributed to the degradation of long chain alkanes from needles and litter due to active microbial metabolism in the soil (Fustec etal. 1985; Moucawi etal. 1981). In general, in pine samples, the higher total concentration of the alkanes with an odd number of C atoms than that of even Plant Soil 1 3 Vol.: (0123456789) number of C atoms pointed to a biogenic signature of alkanes inherited from epicuticular waxes of higher plants (Eglinton etal. (1962a, b). Regarding monoterpenes, the low concentration of these compounds in pine litter and soil compared to pine needles, could be due to the fact that most of these monoterpenes could be physically entrapped into macromolecular lipid substances or in the organomineral matrix of the soil (Almendros and Sanz 1991; Almendros et al. 2001). On the other hand, sesquiterpenes are also major biogenic compounds that allow recognizing the different stages of transformation of the soil organic matter. In fact, cadinenerelated molecules are ubiquitous in plants and are the main odor constituents of some conifer woods and leaves, but can also be metabolites of various fungi (Rowe 1989). Sesquiterpenes such as spathulenol, β-selinene, γ-cadinene and junipene, among others, had been previously reported in juniper essential oils (Adams 2008; El-Sawi etal. 2007; Kosalec etal. 2005; Orav etal. 2010; Rezvani 2010). Diterpenes found in juniper samples, such as abietanes, abietatriene, ferruginol and totarol are considered as diagnostic molecules of this forest ecosystems (Almendros et al. 1996). Abietane diterpenes have already been described as oxidation and thermal rearrangement products of methyl levopimarate (Rowe 1989) and have also been identified in pine soils affected by fires (Almendros etal. 1996). Evaluation of polar compounds in pine and juniper forests As expected, glucose, fructose and sucrose were present in all extracts, except from those of pine soil. These carbohydrates are ubiquitous in plants and have previously been found in pine needles (Kltšeiko 2006) and in juniper berries (Türkoglu etal. 2008). The presence of pinitol, sequoyitol and myo-inositol in pine needles has been previously reported in the literature (Duquesnoy etal. 2008). Moreover, it is known that 1-methyl-muco-inositol is ubiquitous in gymnosperms (Dittrich and Kandler, 1972) and probably comes from the epimerization of pinitol. However, Dittrich and Kandler (1972) did not find this compound in the Pinaceae family, and suggested the absence of the enzyme that converts pinitol into methyl-muco-inositol in these plants. In the present work, 1-methyl-muco-inositol was found in pine needles at very low levels. Methyl-inositols are usually secondary plant metabolites and are not directly involved in their normal growth, but these compounds play an important role the defense against stressful environmental conditions (Al-Suod etal. 2017). Evolution of free lipid and polar compounds in van Krevelen diagrams Free lipid compounds Figure 6 shows surface density maps displaying the cumulative abundances of different groups of compounds present in lipid fractions extracted from needles, litter and soil samples collected in pine and juniper forests. Contour density maps showing the differences between the normalized values of the proportions of the different lipid compounds in the course of their transformation are shown in Fig.4S. In the case of the pine forest samples, moderate differences are observed when comparing the leaf samples with respect to the litter (Fig.4S A), where most of the transformations correspond to the relative decrease in the proportion of medium-oxidation products (both aliphatic alcohols, alkanones and fatty acids), as well as aromatic compounds (mainly alcohols, triterpenoidal acetates or oxides). In contrast, steroids, alkanes and diterpene resin acids tend to increase in relative terms in litter. Higher differences were observed when comparing the lipids of the leaves with those of the soil (Fig.4S C). In the pine soil, a large relative enrichment in long-chain aliphatic compounds was observed, mainly long-chain alkanes (presumably derived from epicuticular waxes), while the relative concentration of most aromatic compounds decreased, especially in the case of hydrocarbons (mono-, sesquiand diterpenes) compared to compounds with a high oxidation degree. The most persistent compounds correspond to steroids and sesquiterpene alcohols. Compared to pine, juniper leaves showed a different molecular composition where the predominant fraction consists mainly of terpenoidal alcohols and oxides, whereas the proportions of hydrocarbons, both alkanes and monoand sesquiterpenes were comparatively low (Fig.6). In the course of lipid evolution from juniper needles to litter (Fig.5S A) a large accumulation of terpenes, but also of highly oxidized terpenoids, i.e., acetates, ketones and resin acids, was observed. This is in agreement with the typical Plant Soil 1 3 Vol:. (1234567890) trends described for the progressive transformation of terpenoids in soil, accompanied by progressive aromatization and oxidation (Simoneit and Mazurek 1982). However, there was a decrease in the proportion of intermediate oxidation degree terpenoids, mainly alcohols, as well as all aliphatic products, such as alkanes and alkanols, which is also expected with the tendency of selective degradation of compounds traditionally considered more easily biodegradable. In the case of soil lipid compounds (Fig.5S B and C), there was a relative enrichment in alkanes (mainly of short chain) and terpenoidal phenols while a depletion of aromatic compounds in oxidized forms, such as alcohols, oxides and triterpenoidal acetates, was observed. Also in accordance with the aboveindicated trends during the evolution of terpenoids, these changes would be characteristic of the advanced stages of transformation, in which defunctionalized hydrocarbons tend to accumulate preferentially, predominating over the oxygen-containing compounds that would characterize the intermediate stages. It seems clear that there were two marked transformation trends of the molecular assemblages of biogenic lipids, depending on whether the transformation occurred in the presence of the mineral fraction of the soil studied or not. In both species (pine and juniper), the lipid evolution from leaf to litter was typically characterized by the oxidation of terpenoidal compounds or, in more advanced phases, by their defunctionalization with accumulation of the corresponding cyclic hydrocarbons. However, in the presence of the soil mineral fraction, most of the oxygen-containing compounds were depleted and a considerable concentration of alkanes remained as a major fraction of the lipid fraction. These results suggest polymerization or condensation of lipid compounds on the organomineral matrix of the soil, in particular humic substances, which would result due to the fact that the less reactive compounds would be those remaining in free, solvent-extractable forms. Fig. 6 Surface density maps displaying cumulative abundances of different groups of compounds present in lipid fractions extracted from needles, litter and soil samples collected in pine and juniper forests Plant Soil 1 3 Vol.: (0123456789) Polar compounds Although differences were observed between pine and juniper samples when the polar compounds were grouped together in the van Krevelen diagrams (Fig. 6), their evolution during the transformations from leaf to soil showed common characteristics (Fig.6S A–C), similar to those observed in the case of lipid compounds. In the case of pine, it was observed that the greatest increase in molecular diversity occurred during litter formation, where alkanoic acids, presumably from microbial metabolism, and linear polyalcohols appeared as additional groups of major compounds (Fig.6S A). However, as the evolution of the polar fraction in the soil progressed, a simplification of the polar compound fraction occurred, in which acids and disaccharides hardly remained as main compounds (Fig.6S B and C). Regarding juniper samples (Fig.6), the evolution was similar to pine, although there was a higher diversity of compounds, both in the needles and the litter. This latter was the sample that presented the greatest complexity as cyclitols and monosaccharides. These compounds were preserved from the needles, where an enrichment in linear polyols was also observed (Fig.7S A). The final evolution in the soil led to a simplified composition, in which alkanoic acids, disaccharides and, to a lesser extent, polyols, produced in earlier stages, survived (Fig.7S B and C). Conclusion To the best of our knowledge, this study represents the first comparative assessment based on the absolute quantitation of up to 148 compounds (free lipids, LMWC and acids) present in pine and/or in juniper extracts during the course of their transformation in the soil. In this preliminary study, different characteristic compounds which may be associated with the different stages of transformation were suggested. Differences were also observed in the two investigated forest species. In general, the evolution of the lipid and LMWC compound assemblages of both juniper and pine samples monitored by van Krevelen diagrams showed a simplification, i.e. a decreasing molecular diversity: in the case of lipids, terpenoids were the most abundant in needles and litter of both species, whereas alkanes were the predominant compound family in the case of soil lipids; the lipid fraction found in the intermediate evolution stage (i.e. litter) of both species presents a great molecular complexity attributed to the mixture of biogenic compounds with their transformation products. Regarding polar compounds, alkanoic acids and disaccharides tend to accumulated in the soil. This work is a preliminary investigation demonstrating that the methodology used allows changes that occur during soil transformations to be monitored. Using experimental designs similar to the one used in this research, with a higher number of samples and other environmental scenarios, with different soil types and forest species, could be useful to establish objective quantitative criteria to assess factors involved in the impact of vegetation on the composition of organic matter in soils. Acknowledgements This work is part of the I+D+i project PID2019-106405GB-I00 financed by MCIN/ AEI/https:// doi. org/ 10. 13039/ 50110 00110 33 and the project 202080E216 funded by CSIC. Authors thank the Comunidad of Madrid and European funding from FSE and FEDER programs for financial support (project S2018/BAA-4393, AVANSECALII-CM). We would like to thank three anonymous referees for their valuable suggestions for our manuscript. Author contributions J. Sanz, L. Ramos, M.L. Sanz and G. Almendros contributed to the study conception and design. Material preparation, data collection and analysis were performed by C. Carrero-Carralero and Ana I. Ruiz. The first draft of the manuscript was written by J. Sanz, L. Ramos, M.L. Sanz and G. Almendros and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by the I + D + i project PID2019-106405 GB-I00 financed by MCIN/ AEI/https:// doi. org/ 10. 13039/ 50110 00110 33 and the project 202080E216 funded by CSIC. Authors have received research support from the Comunidad of Madrid and European funding from FSE and FEDER programs (project S2018/BAA-4393, AVANSECAL-II-CM). Declarations Competing interests The authors have no relevant financial or non-financial interests to disclose. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any Plant Soil 1 3 Vol:. (1234567890) medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. References Adams RP (2007) Identification of Essential Oil Components by Gas Chromatography/Mass Spectrometry. Allured Publishing Corporation, Illinois (ISBN-13: 978-1932633214) Adams R (2008) The Junipers of the World: The Genus Juniperus, 4th edn. Trafford Publ, Victoria (ISBN-13: 978-1490723259) Aldana J, Romero-Otero A, Cala MP (2020) Exploring the lipidome: Current lipid extraction techniques for mass spectrometry analysis. Metabolites 10(231):1–32 Almendros G, Sanz J (1991) A structural study on the soil humin fraction.– Boron trifluoride-methanol transesterification of soil humin preparations. Soil Biol Biochem 23:1147–1154 Almendros G, Sanz J, Velasco F (1996) Signature of lipid assemblages in soils under continental Mediterranean forests. Eur J Soil Sci 47:183–196 Almendros G, Tinoco P, González-Vila FJ, Lüdemann H-D, Sanz J, Velasco F (2001) 13C NMR of forest soil lipids. Soil Sci 166:186–196 Almendros G, Hernández Z, Sanz J, Rodríguez-Sánchez S, Jiménez-González MA, González-Pérez JA (2018) Graphical statistical approach to soil organic matter resilience using analytical pyrolysis data. J Chromatogr A 1533:164–173 Al-Suod H, Ligor M, Rațiu IA, Rafińsk K, Górecki R, Buszewsk B (2017) A window on cyclitols: Characterization and analytics of inositols. Phytochem Lett 20:507–519 Angst G, John S, Mueller CW, Kögel-Knabner I, Rethemeyer J (2016) Tracing the sources and spatial distribution of organic carbon in subsoils using a multi-biomarker approach. Sci Rep 6:29478 Bull ID, van Bergen PF, Nott CJ, Poulton PR, Evershed RP (2000) Organic geochemical studies of soils from the Rothamsted classical experiments V. The fate of lipids in different long-term experiments. Org Geochem 31:389–408 Cotrufo MF, Lavallee JM (2022) Chapter One – Soil organic matter formation, persistence, and functioning: A synthesis of current understanding to inform its conservation and regeneration. In: Sparks DL (ed) Advances in Agronomy. Academic Press, pp 1–66 Couvillion SP, Naylor D, Wu R., Smith ML, Paurus, VL, Bloodsworth K, Stratton KG, Bramer L, Lipton M S, Jansson J, Metz TO, Hofmockel KS (2020) Leveraging the soil lipidome to elucidate microbial community response to shifting environmental conditions. American Geophysical Union, Fall Meeting, B113-0019 De Blas E, Almendros G, Sanz J (2013) Molecular characterization of lipid fractions from extremely water-repellent pine and eucalyptus forest soils. Geoderma 206:75–84 De Nobili M, Bravo C, Chen Y (2020) The spontaneous secondary synthesis of soil organic matter components: A critical examination of the soil continuum model theory. Appl Soil Ecol 154:103655 Del Castillo JB, Brooks C, Cambie R, Eglinton G, Hamilton R, Pellitt P (1967) The taxonomic distribution of some hydrocarbons in gymnosperms. Phytochemistry 6:391–398 Dinel H, Schnitzer M, Mehuys G (1990) Soil lipids: Origin, nature, content, decomposition, and effect on soil physical properties. Soil Biochem 6:397–429 Dittrich P, Kandler, (1972) Biosynthesis of D-glucaric acid in needles of Larix decidua. Z. Pflanzenphysiol 66:368–371 Duquesnoy E, Castola V, Casanova J (2008) Identification and quantitative determination of carbohydrates in ethanolic extracts of two conifers using 13C NMR spectroscopy. Carbohydr Res 343:893–902 Eglinton G, Gonzalez AG, Hamilton RJ, Raphael RA (1962a) Hydrocarbon constituents of the wax coatings of plant leaves: A taxonomic survey. Phytochem 1:89–102 Eglinton G, Hamilton RJ, Raphael RA, Gonzalez AG (1962b) Hydrocarbon constituents of the wax coatings of plant leaves: A taxonomic survey. Nature 193:739–742 Eilmann B, Weber P, Rigling A, Eckstein D (2006) Growth reactions of Pinus sylvestris L. and Quercus pubescens Willd. to drought years at a xeric site in Valais, Switzerland. Dendrochronologia 23:121–132 El-Ghorab A, Shaaban HA, El-Massry KF, Shibamoto T (2008) Chemical composition of volatile extract and biological activities of volatile and less-volatile extracts of juniper berry (Juniperus drupacea L.) fruit. J Agric Food Chem 56:5021–5025 El-Sawi SA, Motawae HM, Ali AM (2007) Chemical composition, cytotoxic activity and antimicrobial activity of essential oils of leaves and berries of Juniperus phoenicea L. grown in Egypt. Afr J Tradit Complement Altern Med 4:417–426 Foley JP, Dorsey JG (1984) Clarification of the limit of detection in chromatography. Chromatographia 18:503 Fustec E, Moucawi J, Jambu P, Amblès A, Jacquesy R (1985) Principaux facteurs influençant l’évolution des lipides végétaux dans le sol. Agrochimica 29:174–185 Ikeya K, Sleighter RL, Hatcher PG, Watanabe A (2015) Characterization of the chemical composition of soil humic acids using Fourier transform ion cyclotron resonance mass spectrometry. Geochim Cosmochim Acta 153:169–182 Jambu P, Amblès A, Magnoux P, Parlanti E (1995) Effects of addition of clay minerals on the fatty acid fraction of a podzol soil. Eur J Soil Sci 46:187–192 Jiménez-González MA, Álvarez AM, Hernández Z, Almendros G (2018) Soil carbon storage predicted from the diversity of pyrolytic alkanes. Biol Fertil Soils 54:617–629 Jiménez-González MA, Álvarez AM, Carral P, Almendros G (2020) Influence of soil forming factors on the molecular structure of soil organic matter and carbon levels. CATENA 189:104501 Jiménez-Morillo NT, de la Rosa JM, Waggoner D, Almendros G, González-Vila FJ, González-Pérez JA (2016) Fire effects in the molecular structure of soil organic matter fractions under Quercus suber cover. CATENA 145:266–273 Plant Soil 1 3 Vol.: (0123456789) Kltšeiko J (2006) Evaluation of microwave radiation method for sample preparation of pine needles and wood for carbohydrate analysis. Acta Physiol Plant 28:547–555 Kosalec I, Pepeljnjak S, Bakmaz M, Vladimir-Knezević S (2005) Flavonoid analysis and antimicrobial activity of commercially available propolis products. Acta Pharm 55:423–430 Lehmann J, Kleber M (2015) The contentious nature of soil organic matter. Nature 528:60–68 Maffei M, Badino S, Bossi S (2004) Chemotaxonomic significance of leaf wax n-alkanes in the Pinales (Coniferales). J Biol Res 1:3–19 Medeiros PM, Fernandes MF, Dickc RP, Simonei BRT (2006) Seasonal variations in sugar contents and microbial community in a ryegrass soil. Chemosphere 65:832–839 Mena-García A, Ruiz-Matute AI, Soria AC, Sanz ML (2019) Green techniques for extraction of bioactive carbohydrates. TrAC Trends Anal Chem 119:115612–115622 Moucawi J, Fustec E, Jambu P, Jacquesy R (1981) Decomposition of lipids in soils: Free and esterified fatty acids, alcohols and ketones. Soil Biol Biochem 13:461–468 Ohno T, Parr TB, Gruselle M-CI, Fernandez IJ, Sleighter RL, Hatcher PG (2014) Molecular composition and biodegradability of soil organic matter: A case study comparing two New England forest types. Environ Sci Technol 48:7229–7236 Orav A, Kailas T, Muurisepp M (2010) Chemical investigation of the essential oil from berries and needles of common juniper (Juniperus communis L.) growing wild in Estonia. Nat Prod Res 24:1789–1799 Rezvani S (2010) Investigation and comparison of Juniperus polycarpos & Juniperus communis essential oil from Golestan Province. J Med Plants 9:83–89 Rowe JW (1989) Natural products of woody plants: Chemicals extraneous to the Lignocellulosic Cell Wall. 2. Springer. ISBN-13: 978–3540503002 Ruiz-Matute AI, Soria AC, Martínez-Castro I, Sanz ML (2007) A new methodology based on GC-MS to detect honey adulteration with commercial syrups. J Agric Food Chem 55:7264–7269 Sanz ML, Sanz J, Martínez-Castro I (2004) Presence of some cyclitols in honey. Food Chem 84:133–135 Schmidt MWI, Torn MS, Abiven S, Dittmar T, Guggenberger G, Janssens IA, Kleber M, Kögel-Knabner I, Lehmann J, Manning DAC, Nannipieri P, Rasse DP, Weiner S, Trumbore SE (2011) Persistence of soil organic matter as an ecosystem property. Nature 478:49–56 Seaby RM, Henderson PA (2006) Species diversity and richness version 4. Pisces Conservation Ltd., Lymington, England Simoneit BRT, Mazurek MA (1982) Organic matter of the troposphere—II. Natural background of biogenic lipid matter in aerosols over the rural western United States. Atmos Environ 16:2139–2159 Spaccini R, Piccolo A (2007) Molecular characterization of compost at increasing stages of maturity. 1. Chemical fractionation and infrared spectroscopy. J Agric Food Chem 55:2293–2302 Stevenson F (1982) Soil lipids. In Humus Chemistry: Genesis, Composition, Reactions, Wiley, New York, pp. 172–194 Tinoco P, Almendros G, Sanz J (2018) Soil perturbation in Mediterranean ecosystems reflected by differences in free-lipid biomarker assemblages. J Agric Food Chem 66:9895–9906 Tu TTN, Egasse C, Anquetil C, Zanetti F, Zeller B, Huon S, Derenne S (2017) Leaf lipid degradation in soils and surface sediments: A litterbag experiment. Org Geochem 104:35–41 Türkoglu N, Balta MF, Cig A (2008) Sugar contents of juniper plants. Asian J Chem 20:3307–3309 van Krevelen DW (1950) Graphical-statistical method for the study of structure and reaction processes of coal. Fuel 24:269–284 White PM, Potter TL, Strickland TC (2009) Pressurized liquid extraction of soil microbial phospholipid and neutral lipid fatty acids. J Agric Food Chem 57:7171–7177 Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.