Salix species and varieties affect the molecular composition and diversity of soil organic matter

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Dufour, Johanna Wetterlind, Naoise Nunan, Katell Quenea, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4214790/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background and aims Most studies of the relationships between the composition of soil organic matter and plant cover have been carried out at the plant genera level. Yet, they have largely overlooked the potential effects that plant varieties belonging to the same genus can have on soil organic matter. Methods We investigated whether plant varieties belonging to different Salix species ( S. dasyclados and S. viminalis) impacted the composition of organic matter using mid-infrared spectroscopy and pyrolysis GC/MS. Top-soils (0-20 cm) were taken from an 18 year-old long-term field trial where six Salix varieties were grown as short-rotation coppice under two fertilisation regimes. Results Significant differences in the molecular composition and diversity of the soil organic matter were observed in the fertilised plots. The effects were mostly visible at the species level, i.e. between varieties from S. dasyclados and S. viminalis , though smaller differences among varieties from the same species were also observed. No significant effects of Salix varieties were observed in the unfertilised plots, possibly due to the relatively high degree of spatial variability in several soil properties (pH, total N and total organic C contents). Conclusion This study provides evidence that the taxonomic distance, at the species level, among Salix plant varieties can affect the molecular composition and diversity of soil organic matter. Such an effect should be considered in breeding programmes for managing soil organic C, as it is one of the potential driver of organic C persistence in soils. soil organic matter composition molecular diversity mid-IR spectroscopy pyrolysis GC/MS plant varieties Salix Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction There has been a lot of recent interest in soil carbon (C) sequestration (Don et al. 2024 ) as it has several benefits: (i) the limitation of erosion, (ii) the improvement of water infiltration, purification and storage, (iii) the selection of more diverse and active communities of soil organisms (Rumpel et al. 2022 ). Additionally, the sequestration of C in soil has become a focus of attention as part of the strategy for mitigating on-going climate change in the context of climate agreements (Kuyper et al. 2018 ; Panagos et al. 2022 ). Changes in several land management practices are known to influence organic C sequestration in soil, but these can be associated with major trade-offs (Amelung et al. 2020 ). For instance, the conversion of arable land to grassland generally leads to increases in soil organic C, but affects food production (Boysen et al. 2017 ). In view of these potential trade-offs, the breeding of plant species and varieties with traits related to the quantity and quality of the C input to soil may be a way forward (Poffenbarger et al. 2023 ; Weih et al. 2014 ). It has also been shown that the use of management systems with greater interspecific plant diversity can result in, for example, greater aboveground C in forests (Huang et al. 2018 ; Hulvey et al. 2013 ) and greater belowground C in grasslands (Hungate et al. 2017 ; Lange et al. 2015 ; Prommer et al. 2020 ). Growing interest exists in developing more diverse agroecosystems (i.e. varietal and/or species mixtures) for agricultural crops (Kopp et al. 2023 ) and trees (i.e. mixed species stands) (Huuskonen et al. 2021 ; Stewart et al. 2023 ). Plant breeding may develop various intraspecific genotypes that may enhance the potential to sequester more C in soils. However, there is very little information on the potential effects that varietal diversity or varietal identity might have on soil C dynamics or soil organic C persistence (Semchenko et al. 2021 ). It is known that different plant species belonging to the same plant genus produce litter and rhizodeposits that differ in both quantity and composition (Smith 1969 ; Sun et al. 2017 ; Warembourg and Estelrich 2001 ). Furthermore, it has been widely shown that plant-microbe interactions influence both the composition of soil microbial communities (Korenblum et al. 2022 ; Seitz et al. 2022 ) and metabolites (Wiesenbauer et al. 2024 ), and their ability to decompose different forms of organic matter, i.e. their catabolic profiles (Brolsma et al. 2017 ; Yergeau et al. 2013 ). However, it is not clear whether these differences result in soil organic matter that differs substantially in quality and/or quantity, especially in the case of the small differences that might be expected across plant varieties (Pérez-Izquierdo et al. 2018 ). Changes in the amount of soil C are difficult to detect over short timescales when land use varies (Jandl et al. 2014 ; Poeplau et al. 2022 ). The composition of soil organic matter may be more responsive and so may serve as an early indicator of potential changes in organic C persistence and content. In addition to this, it has been argued that the molecular diversity of organic matter may be a driver of C persistence in soil (Lehmann et al. 2020 ). Furthermore, soil structure is influenced by organic matter composition (Bucka et al. 2019 ; Bucka et al. 2021 ) and may therefore influence C persistence indirectly, as the physical protection of soil organic C is thought to contribute to organic C persistence (von Lützow et al. 2006 ). Although there are trade-offs between the composition of soil organic matter and persistence mechanisms at the continental scale (Hall et al. 2020b ), it is unclear whether the composition of soil organic matter has an important role at the plot-scale where land management systems can change. The first step is to understand if and how varietal mixtures affect soil C dynamics, i.e. whether there are differences in (i) content and/or (ii) composition of organic matter in soils associated with different varieties. In this study, we chose to work with the plant genus Salix . Salix is a major woody-perennial bioenergy crop grown as short rotation coppice (Weih 2013 ). This system is often considered to be a model for studying the relationship between biodiversity and productivity, due to its simplicity and similarity with grassland systems (Weih et al. 2019 ). Specifically, this system is used here to study how the taxonomic proximity of Salix varieties constrain processes related to soil organic C dynamics. The aboveground characteristics of several varieties of the genus Salix grown as short rotation coppice in monoculture are well characterized, showing some variation in traits among varieties (Bonosi et al. 2013 ; Weih and Nordh 2002 ; Weih and Nordh 2005 ). Yet, there are only a few studies investigating their belowground traits, such as (i) root biomass (Baum et al. 2018 ; Hoeber et al. 2017 ), (ii) fine root composition and decomposition rates (He et al. 2019 ), (iii) soil and root-associated fungal communities (Baum et al. 2018 ; Hoeber et al. 2021 ; Hrynkiewicz et al. 2012 ; Koczorski et al. 2021 ), (iv) dehydrogenases activities (Baum et al. 2020 ), or (v) their impact on the increase of soil organic carbon stock (Baum et al. 2020 ). The objective of this study was to determine whether the molecular composition and diversity of soil organic matter was related to Salix varieties. Specifically, we hypothesised that different Salix plant varieties would lead to soil organic matter with different molecular compositions. The objective was addressed by characterising composition of organic matter in bulk soil under six different Salix varieties in a long term field trial using two complementary approaches: (i) spectroscopic measurement in the mid-infrared wavelength range (diffuse reflectance infrared Fourier transform (DRIFT)), (ii) analytical pyrolysis combined with gas-chromatography-mass spectrometry (Pyrolysis-GC/MS). Materials and Methods Long-term experimental field trial We used a field trial located in central Sweden (59°48'22"N 17°40'24"E). Within this field trial, willow varieties ( Salix spp.), across which taxonomic distance varied, were cultivated as short rotation coppice on a former arable cropland. The climate is temperate oceanic, and the soil is classified as a Vertic Cambisol, with a texture of 66% sand, 16% silt and 18% clay (Kalita et al. 2021 ; Weih and Nordh 2005 ). The field trial was set up in 2001 in a split plot design, with fertilisation as main plots and willow varieties in subplots. Four of the eight main plots were annually fertilised with approximately 100 kg nitrogen, 14 kg phosphorus and 47 kg potassium per hectare, and the remaining plots were left unfertilised (Baum et al. 2020 ). Within each main plot, six monoclonal subplots were randomly distributed (Fig. 1 a). The subplots measured 6.75 × 7 m and contained 3 double rows of plants and 84 plants in total (equivalent to a density of ~ 18000 plants ha -1 ) (Fig. 1 b). Each monoclonal subplot contained one of six commercial Salix varieties that were more or less taxonomically similar, from full-siblings to differential species (Table 1 ). Two of the varieties, Loden and Gudrun, are taxonomically close. They have in common morphological traits of the species S. dasyclados and are separated taxonomically at the species level compared to four others varieties, Björn, Tora, Tordis and Jorr that share some traits with the species S. viminalis . Table 1 Salix varieties planted in the long-term field trial established in 2001 at the site Pustnäs near Uppsala in central Sweden Name of Salix varieties Clone number Salix Varieties Taxonomic separation at the species level Björn SW 910006 S. schwerinii E. Wolf x S. viminalis L. S. viminalis Tora SW 910007 S. schwerinii x S. viminalis Tordis SW 960299 (S. schwerinii x S. viminalis) x S. viminalis L. Jorr SW 880013 S. viminalis Gudrun SW 940598 S. burjatica Nasarow x S. dasyclados Wimm. S. dasyclados Loden SW 890129 S. dasyclados Sampling strategy Soil samples were collected from the centre of each monoclonal subplot in April 2019, 18 years after the initiation of the long-term field trial (Fig. 1 b). Eighteen sub-samples were taken with an auger (38 mm diameter) from the surface 20 cm, after removal of the litter layer, in an area of approximately 2 m 2 . The eighteen sub-samples were mixed to form one composite sample per monoclonal subplot, then sieved (< 4 mm) and air-dried. In total, there were 48 composite samples (6 monoclonal subplots × 4 main plots × 2 fertilisation treatments). General soil properties Soil pH in each monoclonal subplot was determined using a pH Meter (Radiometer Copenhagen) in a soil:deionised water (1:5 soil:water) mixture at room temperature (23°C). The total N and organic C contents of the soils were determined by dry combustion using an elemental analyser (TruMac ® CN, Leco corp, S:t Joseph, MI, USA). The total C and total inorganic C contents were determined in two separate runs. Prior to the analysis of total inorganic C content, samples were heated to 550°C for four hours to remove organic matter. The total organic C content (% TOC) was calculated as the difference between total C and total inorganic C content. Spectroscopic measurements Mid-infrared spectra (mid-IR) were recorded in quadruplicate using dry, milled soil, resulting in a total of 192 spectra (48 samples x 4 analytical replicates). The samples were scanned using a Fourier transform IR (FT-IR) Alpha II Drift spectrometer (Bruker, Germany, Serial No. 12547393) equipped with a diffuse reflection (DRIFT) module. We used a spectral resolution of 4 cm -1 . Background measurements were carried out using a gold standard. Each spectrum was the average of 24 scans. The apparent absorbance (A) was determined from the reflectance (R) spectra (A = log 1/R) (Guillou et al. 2015 ). The signal of the spectra between 630 cm -1 and 400 cm -1 was very noisy and removed from further analyses. The spectra, therefore, contained data from 4000 cm -1 to 630 cm -1 (2500 nm to 15873 nm). Each spectrum was pre-processed using the Savitzky-Golay functions of the R package “prospectr” (Stevens and Ramirez-Lopez 2015 ) with a first derivative using three point smoothing and a second order polynomial (Savitzky and Golay 1964 ). Standard normal variate was applied to correct the light scattering (Morais et al. 2020 ). The mean of the apparent absorbance of the four mid-IR replicates was determined for each sample using the summarise function in the R package “dplyr” (version 1.8.6) (Wickham et al. 2019 ). The full mid-IR spectral range was used for multivariate statistics (Ramírez et al. 2021 ). Pyrolysis – Gas Chromatography – Mass Spectrometry (Pyrolysis-GC/MS) Soil samples were analysed by Pyrolysis-GC/MS in the presence of tetramethylammonium hydroxide (TMAH) (25% methanol), an alkylating agent that improves the detection of polar compounds. Around 6 mg of sample was loaded in a quartz tube with 10µl of TMAH. Glass wool was placed on top of the sample and the sample was then pyrolysed (Pyroprobe 6250, CDS) at 650°C for 15 s. The pyrolysis products were transferred via a transfer line, maintained at 300°C, to the injector of a gas chromatograph (7890B, Agilent) operated in split mode (20ml/min). The separation of pyrolysis products was carried out using a non-polar gas chromatograph column Rxi5Sil MS (30 m x 0.25 mm x 0.5 µm, Restek), with helium as the carrier gas (1 mL/min) and an oven ramp (initial temperature of 50°C maintained for 10min, raised by 2°C/min to 320°C, the final temperature, maintained for 13min). The gas chromatograph was connected to a mass spectrometer (5977B, Agilent), which was used in the scan mode and operated in electron ionization (electron impact source 70 eV; 230°C). The analysis was performed with a quadrupole mass spectrometer, working at 2 scans/s from 35 to 700 m / z . Compounds were identified on the basis of their mass spectra, retention times, and comparison with the Wiley mass spectra library (v 2.73) and with published mass spectra. Peaks were integrated using Agilent Masshunter (Version B. 09.00) on the total ion current trace and the relative contribution of each pyrolysis product was calculated as the area of the product over the sum of the peak areas of all of the pyrolysis products. Pyrolysis products were classified into biochemical categories based on previous publications (Barré et al. 2018 ; Derenne et al. 2015; Dignac et al. 2005 ; El Hayany et al. 2021 ; Lejay et al. 2016 ; Lejay et al. 2019 ; Vidal et al 2016 ). Their most probable origin were from (i) higher plants (lignin, long chain fatty acids, long chain alkanes, cutine and/or suberine derived compounds), (ii) microorganisms (short chain fatty acids and short chain alkanes), (iii) multiple sources (nitrogenous compounds, carbohydrates), (iv) an unspecific origin: pyrolysis products derived from aliphatics, aromatics (phenols, benzenes, polyaromatics) and N-heterocylic compounds, i.e. triazine as a probable by-product from TMAH (Templier et al. 2005 ). Diversity indices of pyrolysis products were estimated using the effective Simpson index of pyrolysis products (Jost 2007 ; Lagkouvardos et al. 2017 ). Statistics Rstudio (Version 1.3.1073 - © 2009–2020 Rstudio, Inc) (RStudio Team, 2015. RStudio: Integrated Development for R. RStudio, Inc., Boston, MA, USA) was used for all statistical analyses and plots. The level of significance for the following statistical analyses was set at P ≤ 0.05. Differences in means of soil N and organic C contents were tested using a one-way analysis of variance with block (the block effect was the “No. of main plots” of the field trial), first among “ Salix varieties” and then among “ Salix species”. This was followed by a Tukey honest significant difference post hoc test (implemented in the “agricolae” library version 1.3-7) (de Mendiburu 2023 ). The pH values were not normally distributed and therefore differences in medians among “ Salix varieties” and “No. of main plots” were analysed using a one-way Kruskal-Wallis test followed by a Dunn´s test of multiple comparisons (implemented in the “FSA” library version 0.9.3) (Ogle et al. 2022 ). The profiles of pyrolysis compound classes and full mid-IR spectral range were analysed using a principal component analysis (PCA) where the data were centered and scaled, followed by between class analysis (BCA) in order to determine whether the Salix varieties affected the profiles (implemented in the ade4 library version 1.7–19) (Thioulouse et al. 2018 ). The relationships between the profiles of pyrolysis compound classes and full mid-IR spectral range were assessed using Mantel tests on the respective distance matrix (implemented in the vegan library version 2.6-2) (Oksanen et al. 2020 ). The values of the effective Simpson index of identified pyrolysis products among “ Salix varieties” had different variances and therefore, differences in means were tested using a Welch’s one-way analysis of variance followed by a Games-Howell post hoc test (implemented in the rstatix library version 0.7.0) (Games and Howell 1976 ; Kassambara 2021 ). The fertilisation treatments in the field trial were not randomised, as the fertilised and unfertilised main plots were grouped together (see Fig. 1 a). However, the monoclonal subplots were randomised within each main plot. Therefore, we analysed the effect of Salix varieties on soil organic matter composition, soil organic C and N contents and pH in the unfertilised and fertilised treatments separately. The resulting number of replicates for each willow variety was four in both the unfertilised and fertilised treatments. Results General soil properties Soil total organic C content increased by a factor of approximately 1.3 relative to values at the beginning of the field trial in 2001, but total N content remained constant in both the fertilised and unfertilised treatments (Fig. 2 and Table 2 ). However, among Salix varieties, no significant differences in soil organic C or N contents, or pH were observed in both the fertilised and unfertilised treatments (Table 2 ). Table 2 Soil characteristics of the long-term field trial. Means of total N and organic C contents and medians of pH are presented for four field replicates. Means and medians suffixed by a different letter are significantly different at P < 0.05 Soil treatment Salix varieties Total organic C* content (%) Total N* content (%) pH (H 2 O) Unfertilised Björn 1.4 a 0.12 a 6.4 a Tora 1.4 a 0.12 a 6.6 a Tordis 1.4 a 0.12 a 6.4 a Jorr 1.4 a 0.12 a 6.6 a Gudrun 1.5 a 0.13 a 6.5 a Loden 1.5 a 0.13 a 6.4 a Fertilised Björn 1.4 a 0.12 a 6.0 a Tora 1.5 a 0.13 a 6.2 a Tordis 1.4 a 0.11 a 6.0 a Jorr 1.4 a 0.12 a 5.9 a Gudrun 1.3 a 0.11 a 6.0 a Loden 1.3 a 0.11 a 5.9 a Unfertilised Main plot 1 1.4 b 0.12 b 6.5 ab Main plot 2 1.1 a 0.10 a 6.3 a Main plot 3 1.7 c 0.14 c 7.8 b Main plot 4 1.5 b 0.13 cb 6.5 ab Fertilised Main plot 1 1.5 b 0.13 b 5.8 a Main plot 2 1.3 a 0.11 a 5.9 a Main plot 3 1.4 ab 0.11 a 6.1 a Main plot 4 1.3 a 0.11 a 6.1 a * At the start of the experimental field trial in 2001, total organic C and total N contents were on average 1.1% and 0.12% respectively and the bulk density was on average 1.3 g cm -1 (n = 4) across the trial (Weih and Nordh, 2005 ) At the species level, a small but significant effect of Salix species on soil organic C content was observed in the fertilised treatment ( P = 0.035). On average S. dasyclados varieties had slightly more soil organic C (0.1%) than S. viminalis varieties. No effect was observed on the soil N content ( P = 0.071). Among the main plots there were, however, significant differences in soil total N and organic C contents in the unfertilised treatment ( P < 0.0001), with less pronounced but significant differences in the fertilised treatment ( P < 0.05) (Fig. 2 and Table 2 ). Similarly, soil pH varied significantly among the main plots, but only in the unfertilised treatment ( P 0.5, P < 0.0001) were found in the unfertilised treatment plots, but not in the fertilised treatments. Composition of soil organic matter below Salix species: mid-IR spectra The Between Class Analysis (BCA) of the mid-IR spectra did not reveal any significant separation between Salix varieties in the unfertilised treatment (Fig. 3 a), but a significant separation was found in the fertilised treatment ( P < 0.01, Fig. 3 b). The variable “ Salix varieties” explained 22.3% and 24.4% of the overall inertia of the principal component analysis of the unfertilised and fertilised treatments, respectively (Fig. 3 ). Overall, in the fertilised treatment, the composition of soil organic matter below Loden and Jorr varieties differed from the other four varieties (Fig. 3 b): Loden and Jorr were separated from Tora along the horizontal axis due to less abundant carboxylic acid C-O stretch, OH deformation, ester, phenol C-O asymmetric stretch (wavenumbers ranging from 1200 to 1280 cm -1 ) and C = O stretch (wavenumbers ranging from 1645 to 1717 cm -1 ). Furthermore, soil organic matter below Loden was enriched, relative to Tora, Björn, Tordis, in aromatic compounds, with more abundant aromatic C-H out-of-plane bend, aromatic C = C stretch and/or conjugated ketone C = O stretch, and/or amide N-H bend and C = O stretch (amide II) (wavenumbers ranging from 894 to 1036 cm -1 and from 1503 to 1639 cm -1 ). Additionally, Jorr also differed from Tordis, Björn and Gudrun due to less abundant alcohol, ether, phenol C-O-C stretch and poly OH stretch assigned molecular functional groups (wavenumbers ranging from 1160 to 1190 cm -1 ). The composition of soil organic matter below Jorr separated along the vertical axis due to higher abundances of aliphatic C-H asymmetric stretches (wavenumbers 2950–2917 and 2865–2849 cm -1 ) compared to Tordis and Gudrun (Fig. 3 b). In the unfertilised treatment, the mid-IR spectra did not differ among the six Salix varieties (Fig. 3 a). Yet, the composition of soil organic matter signifivantly differed among the four main plots ( P < 0.01) (data not shown). Here, the aliphatic C-H asymmetric stretches as well as carbonate and calcite stretches were least abundant in the second main plot and most abundant in third main plot. Changes in mid-IR spectra between the four main plots were similar to changes in other general soil properties such as pH and soil organic C (adjusted R 2 > 0.5; P < 0.0001). Composition of soil organic matter below Salix species: pyrolysis-GC/MS The BCA of the pyrolysis-GC/MS did not reveal any significant separation Salix varieties in the unfertilised treatment (Fig. 4 a), but a significant separation in the fertilised treatment was found ( P < 0.03, Fig. 4 b). The variable “ Salix varieties” explained 16.5% and 34.8% of the overall variation in the unfertilised and fertilised treatments, respectively (Fig. 4 ). The composition of soil organic matter below Gudrun differed the most from the varieties Tora and Jorr in the fertilised treatment (Fig. 4 b; Table 3 ). Table 3 Biochemical categories of identified pyrolysis products from the soils in the fertilised treatment. The relative abundances expressed as per mille (‰) are shown as the mean ± one standard deviation for four replicates (except for Björn that has one NA value). Polyaromatic compounds, cutin and/or suberine originated compounds, short chain alkane and long chain alkane are not presented because their relative abundances were similar among varieties Most probable origin Biochemical categories Björn Tora Tordis Jorr Gudrun Loden Higher plant Lignin 113 ± 14 96 ± 16 111 ± 38 133 ± 27 142 ± 10 152 ± 39 Long chain fatty acids 25 ± 6 23 ± 5 28 ± 9 30 ± 4 18 ± 7 19 ± 9 Microbial community Short chain fatty acids 44 ± 9 55 ± 10 47 ± 21 48 ± 12 42 ± 8 39 ± 5 Multiple origins Nitrogenous compounds 57 ± 32 53 ± 20 53 ± 19 61 ± 8 79 ± 21 71 ± 17 Carbohydrates 55 ± 17 32 ± 8 38 ± 21 38 ± 10 53 ± 11 50 ± 12 Other aliphatics 117 ± 96 179 ± 74 154 ± 81 303 ± 30 208 ± 30 207 ± 37 Phenols 13 ± 7 10 ± 8 11 ± 7 11 ± 2 26 ± 3 25 ± 10 Benzene derivatives 162 ± 108 190 ± 114 198 ± 81 101 ± 14 184 ± 67 198 ± 54 N-heterocyclic compounds 396 ± 142 340 ± 21 337 ± 82 253 ± 48 223 ± 21 213 ± 11 Gudrun and, to a lesser extent, Loden were separated from the other varieties along the horizontal axis due to a higher abundance of phenol derivatives of unspecific origin. Furthermore, Gudrun was enriched in nitrogenous compounds from proteins and nucleic acids compared to Tordis and Tora. Carbohydrates and lignin derived compounds from higher plants were enriched in Gudrun compared to Tora. Loden was depleted in short chain fatty acids derived from microorganisms compared to Tora. Loden and Gudrun clearly had a lower abundance of N-heterocylic compounds of unspecific origin compared to Tora, Björn and Tordis. The separation along the vertical axis between Jorr and the other varieties was due to more aliphatic compounds of unspecific origin and more abundant long chain fatty acids of higher plant origin, particularly in comparison to Gudrun and Loden. Furthermore, soil organic matter below Jorr was depleted in benzene derivatives of unspecific origin relative to the other varieties. Although soil organic matter below the six varieties was composed of similar compound classes differing only in relative abundances, we observed that the diversities of identified pyrolysis products were different among varieties in the fertilised treatment: Gudrun had a significantly higher effective Simpson index compared to Tora and Tordis ( P < 0.001) and Jorr ( P < 0.05), by a factor of about 1.7 (Fig. 5 ). In the unfertilised treatment, we did not observe any differences in pyrolysis-GC/MS profiles or diversity of pyrolysis products between varieties or between the four main plots. Discussion The link between the organic matter inputs from vegetation (rhizodeposition and litter) has long been established for different types of plant cover and plant diversities. For example, diverse plant communities tend to increase soil C stocks relative to monocultures (Chen et al. 2020 ). However, the links between soil organic matter and individual plant varieties or species are less well studied. It is important to understand the effects that plant varieties or species can have on soil organic matter as it can aid decision making when selecting plants for managing soil organic matter. This study looked at the content and composition of soil organic matter under different Salix varieties that were either fertilised or left unfertilised. The unfertilised plots showed a high degree of spatial variability in many soil properties (pH, total N and total organic C contents) (Table 2 ) which are likely to have masked any potential differences that might have occurred among varieties. As a result, no significant effects of Salix varieties were observed in the fertilised treatment on the molecular composition and diversity of soil organic matter. The fertilised plots were less variable and significant differences were observed. Therefore, the following only refers to the results obtained in the fertilised plots. Effects of Salix varieties and species on the amount of soil organic matter Even though there were differences in aboveground traits (biomass, N content and yield) among varieties (Weih and Nordh 2002 ; Weih and Nordh 2005 ), which might affect the organic matter inputs to the soil (Hirte et al. 2018 ), no differences in total soil organic C content among varieties were observed. This is contrary to what was found by Baum et al. ( 2020 ). The latter study analysed the surface 10 cm whereas the surface 20 cm were analysed here, which might explain the divergent results. Although it has been observed that about half the root biomass of Salix is found in the top 10 cm (Heinsoo et al. 2009 ), a significant proportion of the rooting system is found at greater depths (Chimento and Amaducci 2015 ). Therefore, we decided to sample soils down to 20 cm in this study. Nevertheless, the greater sampling depth may have diluted any potential varietal signal. The difference between the results of Baum et al. ( 2020 ) and those obtained here suggests that a varietal effect, although weak, might be greater in the upper 10 cm of the soil. This is in line with the work of Martani et al. ( 2021 ) where the authors observed a positive rate of soil organic C sequestration in the 0–10 cm layer for willow but either no effect or a negative effect in the 10–30 cm soil layer. At the species level, S. dasyclados varieties had significantly lower total soil organic C content than S. viminalis varieties (Fig. 2 ). This suggests that the differences in traits among species rather than varieties were sufficiently large to affect the amount of soil organic C. The accumulated shoot C in the fertilised plots of the four S. viminalis varieties was approximately twice that of the two S. dasyclados varieties (Rönnberg-Wästljung et al. 2021). S. dasyclados varieties tend to have both higher fine root biomass (Heinsoo et al. 2009 ) and higher ectomycorrhizal colonisation than S. viminalis (Püttsepp et al. 2004 ). On the one hand, roots that are colonised by ectomycorrhiza tend to be decomposed less rapidly than roots that are not mycorrhizal (Langley et al. 2006 ). On the other hand, the abundance of some genera of ectomycorrhizal fungi (i.e. Russela and Cortinarius ), that are capable of producing extracellular peroxidase, have been shown to correlate negatively with the proportion of soil organic matter associated with minerals (Hicks et al. 2023). S. dasyclados varieties are particularly colonised by Cortinarius spp., a morphotype that has been associated with reduced soil organic matter contents in boreal forests (Lindahl et al. 2021 ), potentially via the production of manganese-peroxidases (Kellner et al. 2014 ). No such colonisation of S. viminalis has been found (Püttsepp et al. 2004 ). However, it should be noted that Cortinarius spp. abundances (Jörgensen et al. 2022 ) and peroxidase activity (Bödeker et al. 2014 ) can be reduced by N fertilisation and therefore this interpretation might not be pertinent for forest soils. Yet, here in the context of arable land, this explanation may still remain relevant (BD Lindhal, personal communication). Effects of Salix varieties and species on composition of soil organic matter The most significant result obtained in this study is that the taxonomic proximity of the Salix varieties affected the molecular composition and diversity of the soil organic matter, as seen in both the pyrolysis-GC and mid-IR analyses (Figs. 3 and 4 ). Even though there is no simple way of quantifying the taxonomic distance of the Salix varieties (Fogelqvist et al. 2015 ), Loden and Gudrun are separated taxonomically at the species level from all other varieties (Table 1 ; Weih and Nordh 2005 ). Loden is a pure S. dasyclados clone whereas Gudrun contains two species, namely S. burjatica and S. dasyclados . Jorr is a pure S. viminalis clone, Tordis is derived from two species ( S. schwerinii and S. viminalis ) and Björn and Tora are full-siblings. The latter two are therefore expected to behave in very similar way in an ecological context. Hypothetically, the taxonomic proximity of the varieties may reflect a proximity of traits. Previous studies have suggested that S. viminalis varieties differ from S. dasyclados varieties in the following characteristics: (i) higher aboveground biomass yields (Kalita et al. 2021 ), (ii) higher sodium concentrations in leaves (Ågren and Weih 2012 ), (iii) higher contents in catechin and rutin (quercetin 3- O -rutinoside), lower naringenin and salicylic acid concentrations (Curtasu and Nørskov 2024 ), (iv) lower lignin contents (Kalita et al. 2023 ), (v) lower leaf area ratios, lower leaf area productivity (Weih and Nordh 2002 ), (vi) lower leaf N content (Hoeber et al. 2017 ), (vii) lower ectomycorrhyzal but higher arbuscular mycorrhizal colonization (Püttsepp et al. 2004 ), (viii) lower fine root biomass (Baum et al. 2018 ). Yet, Hoeber et al. ( 2020 ) showed variability of leaf litter decomposition across the four S. viminalis (Björn, Tora, Tordis and Jorr) which did not strictly follow the taxonomic proximity hypothesis in relation to remaining mass and N. Due to the complexity of the relationship between above- and belowground inputs and soil organic matter properties (Kögel-Knabner 2017 ), it is not possible to say which, if any, of these traits are responsible for the differences in composition of soil organic matter that were found here. Although it is likely to be a combination of a number of them. Most of these traits are not clearly reflected in the pyrolysis product profiles of soil organic matter. However, the soil organic matter under the S. dasyclados varieties contained more lignin compared to S. viminalis , possibly due to the higher lignin content of their aboveground biomass and the relatively lower decomposition rates of lignin compared to other constituents of the plant litter (Hall et al. 2020a ). The higher phenolic compound concentrations under S. dasyclados are likely related to the lignin contents, as phenolic compounds are formed upon the pyrolysis of lignin (Dignac et al. 2009 ). The differences in molecular diversity may be due to a combination of greater organic C inputs from S. viminalis varieties and greater microbial processing of the organic matter inputs in soil under S. dasyclados varieties. Others have found that microbial and enzymatic processing of organic matter can dramatically increase its molecular diversity (Kallenbach et al. 2016 ; Wang et al. 2023 ). In addition, a negative relationship between root biomass and the molecular diversity of soil organic matter has been found suggesting that higher inputs decrease molecular diversity (Wang et al. 2023 ). Moreover, there were more aromatic stretches, and carboxylate C-O and ketone C = O stretches beneath Loden than in other varieties. These are suggestive of more complex plant derived organic matter and a greater degree of transformation of the soil organic matter, respectively (Fissore et al. 2017 ; Ryals et al. 2014 ). This confirms the idea that there might be more microbial processing in the soil beneath Loden. Even though most of the differences in molecular composition and diversity of the soil organic matter were seen between varieties of different species, the soil organic C under Jorr also differed from that in the other S. viminalis varieties. Jorr biomass contains more cellobiose, galactose and arabinose, but contained less xylose and had a lower biomethane potential than other S. viminalis varieties (Kalita et al. 2023 ). The major differences in acetic acid derived compounds under Jorr may be due to differences in the composition of the hemicellulose monomer profiles in its above-ground biomass (Kalita et al. 2023 ). Acetic acid derived compounds can have multiple origins but the cleavage of hemicellulose acetyl groups is among them (Pouwels et al. 1987 ). The aliphatic region of the IR spectra and the aliphatic contents (long chain fatty acids and other aliphatics) obtained by pyrolysis were higher in Jorr than in the other varieties. It has been suggested that these may be indicators of plant derived organic matter with a molecular structure dense in C-H bonds such as in waxes from leaf litter or some root exudates dense in hydrocarbon bonds (Mainka et al. 2022 ). Comparison between pyrolysis GC/MS and mid-IR analyses Compared to the pyrolysis GC/MS method, the mid-IR spectral analysis approach is simpler, cheaper and has the advantage of being non-destructive. We were therefore interested in determining whether mid-IR spectral analyses could be used to determine differences in the composition of the organic matter in soil under different varieties of Salix . Although the mid-IR method discriminated certain varieties from others (Fig. 3 ), the discrimination was not identical to that found with pyrolysis. Indeed, a Mantel test showed that the two methods were not closely related (data not shown). The divergence between the two methods may be due to the fact that the mid-IR analysis discriminated Jorr and Loden from the other varieties while the pyrolysis analysis mainly discriminated Gudrun and Loden from the other varieties. Nevertheless, there were some similarities: for example, both the mid-IR and pyrolysis data suggest that the carbohydrate content of soil organic matter beneath Jorr was lower than that in Gudrun and, as indicated above, similarities were also seen in the aliphatics/long chain fatty acids. These similarities may be due to the relatively high variation of these molecular groups within our data and between the varieties (Table 3 ), allowing the mid-IR spectral analysis to detect them. Conclusions This study provides evidence that the taxonomic distance between plant varieties within the genera Salix can affect the molecular composition and diversity of soil organic matter. Our results suggest that plant breeding and adopting simultaneous plantation of varieties may affect molecular composition and diversity of organic matter in soils, which is considered as a driver of C persistence in soils (Lehmann et al. 2020 ). Such an effect should be considered in breeding programmes for biomass crop and multicrop systems (Moore et al. 2023 ). The smaller differences that were seen among varieties from the same species suggest that breeding for greater soil organic C content is a viable research avenue to follow. It would be interesting to determine whether these results are maintained or amplified in diversified systems, i.e. where different varieties are grown together. Declarations Competing Interests The authors declare they have no relevant financial or non-financial interests to disclose. Funding This work was supported by the Swedish Research Council for Sustainable Development, FORMAS project (22836000 and OPTUS 22551000). Author Contributions A.M.H. and M.W. conceptualized the study. Acknowledgments This research was funded by the Swedish Research Council for Sustainable Development, FORMAS projects (22836000 and OPTUS 22551000). The authors would like to thank N.-E. Nordh for assistance with the field sampling, C. Baum, P. Barré, P. Smith and S. Manzoni for discussions related to the long-term field trial, material preparation, data collection and analysis to carry on, M. Spångberg, E. Ljunggren for assistance with laboratory work, E. Karltun and D. Wasner for assistance with mid-IR analysis as well as J. Forkman for assistance with statistical analysis. Thanks to E. Pihlap, M. Ota and Y. Tian for valuable comments on the manuscript. Data Availability The datasets generated during the current study and the custom R scripts used for data analysis are available from the corresponding author on reasonable request and from the public repository entitled Zenodo ( https://zenodo.org/records/10906904 ) (Creative Commons Attribution 4.0 International). References Amelung W, Bossio D, de Vries W, Kögel-Knabner I, Lehmann J, Amundson R, Bol R, Collins C, Lal R, Leifeld J, Minasny B, Pan G, Paustian K, Rumpel C, Sanderman J, van Groenigen JW, Mooney S, van Wesemael B, Wander M, Chabbi A (2020) Towards a global-scale soil climate mitigation strategy. Nat Commun 11: 5427. https://doi.org/10.1038/s41467-020-18887-7 Ågren GI, Weih M (2012) Plant stoichiometry at different scales: element concentration patterns reflect environment more than genotype. New Phytol 194: 944-952. https://doi.org/10.1111/j.1469-8137.2012.04114.x Barré P, Quénéa K, Vidal A, Cécillon L, Christensen BT, Kätterer T, Macdonald A, Petit L, Plante AF, van Oort F, Chenu C (2018) Microbial and plant-derived compounds both contribute to persistent soil organic carbon in temperate soils. Biogeochemistry 140: 81-92. https://doi.org/10.1007/s10533-018-0475-5 Baum C, Hrynkiewicz K, Szymańska S, Vitow N, Hoeber S, Fransson PMA, Weih M (2018) Mixture of Salix genotypes promotes root colonization with dark septate endophytes and changes P cycling in the mycorrhizosphere. Front Microbiol 9. https://doi.org/10.3389/fmicb.2018.01012 Baum C, Amm T, Kahle P, Weih M (2020) Fertilization effects on soil ecology strongly depend on the genotype in a willow ( Salix spp.) plantation. For Ecol Manage 466: 118126. https://doi.org/https://doi.org/10.1016/j.foreco.2020.118126 Bödeker ITM, Clemmensen KE, de Boer W, Martin F, Olson Å, Lindahl BD (2014) Ectomycorrhizal Cortinarius species participate in enzymatic oxidation of humus in northern forest ecosystems. New Phytol 203: 245-256. https://doi.org/10.1111/nph.12791 Bonosi L, Ghelardini L, Weih M (2013) Towards making willows potential bio-resources in the South: northern Salix hybrids can cope with warm and dry climate when irrigated. Biomass Bioenergy 51: 136-144. https://doi.org/10.1016/j.biombioe.2013.01.009 Boysen LR, Lucht W, Gerten D (2017) Trade-offs for food production, nature conservation and climate limit the terrestrial carbon dioxide removal potential. Glob Chang Biol 23: 4303-4317. https://doi.org/10.1111/gcb.13745 Brolsma KM, Vonk JA, Mommer L, Van Ruijven J, Hoffland E, De Goede RGM (2017) Microbial catabolic diversity in and beyond the rhizosphere of plant species and plant genotypes. Pedobiologia 61: 43-49. https://doi.org/10.1016/j.pedobi.2017.01.006 Bucka FB, Kölbl A, Uteau D, Peth S, Kögel-Knabner I (2019) Organic matter input determines structure development and aggregate formation in artificial soils. Geoderma 354: 113881. https://doi.org/10.1016/j.geoderma.2019.113881 Bucka FB, Felde VJMNL, Peth S, Kögel-Knabner I (2021) Disentangling the effects of OM quality and soil texture on microbially mediated structure formation in artificial model soils. Geoderma 403: 115213. https://doi.org/10.1016/j.geoderma.2021.115213 Chen X, Chen HYH, Chen C, Ma Z, Searle EB, Yu Z, Huang Z (2020) Effects of plant diversity on soil carbon in diverse ecosystems: a global meta-analysis. Biol Rev 95: 167-183. https://doi.org/10.1111/brv.12554 Chimento C, Amaducci S (2015) Characterization of fine root system and potential contribution to soil organic carbon of six perennial bioenergy crops. Biomass Bioenergy 83: 116-122. https://doi.org/10.1016/j.biombioe.2015.09.008 Curtasu MV, Nørskov NP (2024) Quantitative distribution of flavan-3-ols, procyanidins, flavonols, flavanone and salicylic acid in five varieties of organic winter dormant Salix spp. by LC-MS/MS. Heliyon 10: e25129. https://doi.org/10.1016/j.heliyon.2024.e25129 Derenne S, Quénéa K (2015) Analytical pyrolysis as a tool to probe soil organic matter. J Anal Appl Pyrolysis 111: 108-120. https://doi.org/10.1016/j.jaap.2014.12.001 Dignac MF, Houot S, Francou C, Derenne S (2005) Pyrolytic study of compost and waste organic matter. Org Geochem 36: 1054-1071. https://doi.org/10.1016/j.orggeochem.2005.02.007 Dignac M-F, Pechot N, Thevenot M, Lapierre C, Bahri H, Bardoux G, Rumpel C (2009) Isolation of soil lignins by combination of ball-milling and cellulolysis: evaluation of purity and isolation efficiency with pyrolysis/GC/MS. J Anal Appl Pyrolysis 85: 426-430. https://doi.org/10.1016/j.jaap.2008.10.012 Don A, Seidel F, Leifeld J, Kätterer T, Martin M, Pellerin S, Emde D, Seitz D, Chenu C (2024) Carbon sequestration in soils and climate change mitigation—definitions and pitfalls. Glob Chang Biol 30: e16983. https://doi.org/10.1111/gcb.16983 El Hayany B, El Fels L, Dignac M-F, Quenea K, Rumpel C, Hafidi M (2021) Pyrolysis-GCMS as a tool for maturity evaluation of compost from sewage sludge and green waste. Waste Biomass Valorization 12: 2639-2652. https://doi.org/10.1007/s12649-020-01184-1 Fissore C, Dalzell BJ, Berhe AA, Voegtle M, Evans M, Wu A (2017) Influence of topography on soil organic carbon dynamics in a Southern California grassland. CATENA 149: 140-149. https://doi.org/10.1016/j.catena.2016.09.016 Fogelqvist J, Verkhozina AV, Katyshev AI, Pucholt P, Dixelius C, Rönnberg-Wästljung AC, Lascoux M, Berlin S (2015) Genetic and morphological evidence for introgression between three species of willows. BMC Evol Biol 15: 193. https://doi.org/10.1186/s12862-015-0461-7 Games PA, Howell JF (1976) Pairwise multiple comparison procedures with unequal n’s and/or variances: a Monte Carlo study. J Educ Stat 1: 113-125. https://doi.org/10.3102/10769986001002113 Guillou FL, Wetterlind W, Viscarra Rossel RA, Hicks W, Grundy M, Tuomi S (2015) How does grinding affect the mid-infrared spectra of soil and their multivariate calibrations to texture and organic carbon? Soil Res 53: 913-921. https://doi.org/10.1071/SR15019 Guo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta analysis. Glob Chang Biol 8: 345-360. https://doi.org/10.1046/j.1354-1013.2002.00486.x Hall SJ, Huang W, Timokhin VI, Hammel, Kenneth E. (2020a) Lignin lags, leads, or limits the decomposition of litter and soil organic carbon. Ecology 101: e03113. https://doi.org/10.1002/ecy.3113 Hall SJ, Ye C, Weintraub SR, Hockaday WC (2020b) Molecular trade-offs in soil organic carbon composition at continental scale. Nat Geosci 13: 687-692. https://doi.org/10.1038/s41561-020-0634-x He L-X, Jia Z-Q, Li Q-X, Feng L-L, Yang K-Y (2019) Fine-root decomposition characteristics of four typical shrubs in sandy areas of an arid and semiarid alpine region in western China. Ecol Evol 9: 5407-5419. https://doi.org/10.1002/ece3.5133 Heinsoo K, Merilo E, Petrovits M, Koppel A (2009) Fine root biomass and production in a Salix viminalis and Salix dasyclados plantation. Estonian J Ecol 58: 27-37. https://doi.org/10.3176/eco.2009.1.03 Hicks Pries CE, Lankau R, Ingham GA, Legge E, Krol O, Forrester J, Fitch A, Wurzburger N (2023) Differences in soil organic matter between EcM- and AM-dominated forests depend on tree and fungal identity. Ecology 104: e3929. https://doi.org/10.1002/ecy.3929 Hirte J, Leifeld J, Abiven S, Oberholzer H-R, Mayer J (2018) Below ground carbon inputs to soil via root biomass and rhizodeposition of field-grown maize and wheat at harvest are independent of net primary productivity. Agric Ecosyst Environ 265: 556-566. https://doi.org/10.1016/j.agee.2018.07.010 Hoeber S, Fransson P, Prieto-Ruiz I, Manzoni S, Weih M (2017) Two Salix genotypes differ in productivity and nitrogen economy when grown in monoculture and mixture. Front Plant Sci 8. https://doi.org/10.3389/fpls.2017.00231 Hoeber S, Fransson P, Weih, M, Manzoni S (2020) Leaf litter quality coupled to Salix variety drives litter decomposition more than stand diversity or climate. Plant Soil 453: 313-328. https://doi.org/10.1007/s11104-020-04606-0 Hoeber S, Baum C, Weih M, Manzoni S, Fransson P (2021) Site-dependent relationships between fungal community composition, plant genotypic dDiversity and environmental drivers in a Salix biomass system. Front Fungal Biol 2. https://doi.org/10.3389/ffunb.2021.671270 Hrynkiewicz K, Toljander YK, Baum C, Fransson PMA, Taylor AFS, Weih M (2012) Correspondence of ectomycorrhizal diversity and colonisation of willows ( Salix spp.) grown in short rotation coppice on arable sites and adjacent natural stands. Mycorrhiza 22: 603-613. https://doi.org/10.1007/s00572-012-0437-z Huang Y, Chen Y, Castro-Izaguirre N, Baruffol M, Brezzi M, Lang A, Li Y, Härdtle W, von Oheimb G, Yang X, Liu X, Pei K, Both S, Yang B, Eichenberg D, Assmann T, Bauhus J, Behrens T, Buscot F, Chen X-Y, Chesters D, Ding B-Y, Durka W, Erfmeier A, Fang J, Fischer M, Guo L-D, Guo D, Gutknecht JLM, He J-S, He C-L, Hector A, Hönig L, Hu R-Y, Klein A-M, Kühn P, Liang Y, Li S, Michalski S, Scherer-Lorenzen M, Schmidt K, Scholten T, Schuldt A, Shi X, Tan M-Z, Tang Z, Trogisch S, Wang Z, Welk E, Wirth C, Wubet T, Xiang W, Yu M, Yu X-D, Zhang J, Zhang S, Zhang N, Zhou H-Z, Zhu C-D, Zhu L, Bruelheide H, Ma K, Niklaus PA, Schmid B (2018) Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362: 80-83. https://doi.org/10.1126/science.aat6405 Hulvey KB, Hobbs RJ, Standish RJ, Lindenmayer DB, Lach L, Perring MP (2013) Benefits of tree mixes in carbon plantings. Nat Clim Change 3: 869-874. https://doi.org/10.1038/nclimate1862 Hungate BA, Barbier EB, Ando AW, Marks SP, Reich PB, van Gestel N, Tilman D, Knops JMH, Hooper DU, Butterfield BJ, Cardinale BJ (2017) The economic value of grassland species for carbon storage. Sci Adv 3: e1601880. https://doi.org/10.1126/sciadv.1601880 Huuskonen S, Domisch T, Finér L, Hantula J, Hynynen J, Matala J, Miina J, Neuvonen S, Nevalainen S, Niemistö P, Nikula A , Piri T, Siitonen J, Smolander A, Tonteri T, Uotila K, Viiri H (2021) What is the potential for replacing monocultures with mixed-species stands to enhance ecosystem services in boreal forests in Fennoscandia? For Ecol Manage 479: 118558. https://doi.org/10.1016/j.foreco.2020.118558 Jandl R, Rodeghiero M, Martinez C, Cotrufo MF, Bampa F, van Wesemael B, Harrison RB, Guerrini IA, Richter Dd, Rustad L, Lorenz K, Chabbi A, Miglietta F (2014) Current status, uncertainty and future needs in soil organic carbon monitoring. Sci Total Environ 468-469: 376-383. https://doi.org/10.1016/j.scitotenv.2013.08.026 Jost L (2007) Partitioning diversity into independent alpha and beta components. Ecology 88: 2427-2439. https://doi.org/10.1890/06-1736.1 Jörgensen K, Granath G, Strengbom J, Lindahl BD (2022) Links between boreal forest management, soil fungal communities and below-ground carbon sequestration. Funct Ecol 36: 392-405. https://doi.org/10.1111/1365-2435.13985 Kalita S, Potter HK, Weih M, Baum C, Nordberg Å, Hansson P-A (2021) Soil carbon modelling in Salix biomass plantations: variety determines carbon sequestration and climate impacts. Forests 12: 1529. https://doi.org/10.3390/f12111529 Kalita S, Ohlsson JA, Karlsson Potter H, Nordberg Å, Sandgren M, Hansson P-A (2023) Energy performance of compressed biomethane gas production from co-digestion of Salix and dairy manure: factoring differences between Salix varieties. Biotech Biofuels Bioprod 16: 165. https://doi.org/10.1186/s13068-023-02412-1 Kallenbach CM, Frey SD, Grandy AS (2016) Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls. Nat Commun 7: 13630. https://doi.org/10.1038/ncomms13630 Kassambara A (2021) rstatix: Pipe-friendly framework for basic statistical tests. R package. https://CRAN.R-project.org/package=rstatix Kellner H, Luis P, Pecyna MJ, Barbi F, Kapturska D, Krüger D, Zak DR, Marmeisse R, Vandenbol M, Hofrichter M (2014) Widespread occurrence of expressed fungal secretory peroxidases in forest soils. PLoS One 9: e95557. https://doi.org/10.1371/journal.pone.0095557 Koczorski P, Furtado BU, Gołębiewski M, Hulisz P, Baum C, Weih M, Hrynkiewicz K (2021) The effects of host plant genotype and environmental conditions on fungal community composition and phosphorus solubilization in willow short rotation coppice. Front Plant Sci 12. https://doi.org/10.3389/fpls.2021.647709 Koga N, Shimoda S, Shirato Y, Kusaba T, Shima T, Niimi H, Yamane T, Wakabayashi K, Niwa K, Kohyama K, Obara H, Takata Y, Kanda T, Inoue H, Ishizuka S, Kaneko S, Tsuruta K, Hashimoto S, Shinomiya Y, Aizawa S, Ito E, Hashimoto T, Morishita T, Noguchi K, Ono K, Katayanagi N, Atsumi K (2020) Assessing changes in soil carbon stocks after land use conversion from forest land to agricultural land in Japan. Geoderma 377: 114487. https://doi.org/10.1016/j.geoderma.2020.114487 Kögel-Knabner I (2017) The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter: fourteen years on. Soil Biol Biochem 105: A3-A8. https://doi.org/10.1016/j.soilbio.2016.08.011 Kopp EB, Niklaus PA, Wuest SE (2023) Ecological principles to guide the development of crop variety mixtures. J Plant Ecol 16. https://doi.org/10.1093/jpe/rtad017 Korenblum E, Massalha H, Aharoni A (2022) Plant–microbe interactions in the rhizosphere via a circular metabolic economy. Plant Cell 34: 3168-3182. https://doi.org/10.1093/plcell/koac163 Kuyper J, Schroeder H, Linnér B-O (2018) The evolution of the UNFCCC. Annu Rev Environ Resour 43: 343-368. https://doi.org/10.1146/annurev-environ-102017-030119 Lagkouvardos I, Fischer S, Kumar N, Clavel T (2017) Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons. PeerJ 5: e2836. https://doi.org/10.7717/peerj.2836 Lange M, Eisenhauer N, Sierra CA, Bessler H, Engels C, Griffiths RI, Mellado-Vázquez PG, Malik AA, Roy J, Scheu S, Steinbeiss S, Thomson BC, Trumbore SE, Gleixner G (2015) Plant diversity increases soil microbial activity and soil carbon storage. Nat Commun 6: 6707. https://doi.org/10.1038/ncomms7707 Langley JA, Chapman SK, Hungate BA (2006) Ectomycorrhizal colonization slows root decomposition: the post-mortem fungal legacy. Ecol Lett 9: 955-959. https://doi.org/10.1111/j.1461-0248.2006.00948.x Lehmann J, Hansel CM, Kaiser C, Kleber M, Maher K, Manzoni S, Nunan N, Reichstein M, Schimel JP, Torn MS, Wieder WR, Kögel-Knabner I (2020) Persistence of soil organic carbon caused by functional complexity. Nat Geosci 13: 529-534. https://doi.org/10.1038/s41561-020-0612-3 Lejay M, Alexis M, Quénéa K, Sellami F, Bon F (2016) Organic signatures of fireplaces: experimental references for archaeological interpretations. Org Geochem 99: 67-77. https://doi.org/10.1016/j.orggeochem.2016.06.002 Lejay M, Alexis MA, Quénéa K, Anquetil C, Bon F (2019) The organic signature of an experimental meat-cooking fireplace: the identification of nitrogen compounds and their archaeological potential. Org Geochem 138: 103923. https://doi.org/10.1016/j.orggeochem.2019.103923 Lindahl BD, Kyaschenko J, Varenius K, Clemmensen KE, Dahlberg A, Karltun E, Stendahl J (2021) A group of ectomycorrhizal fungi restricts organic matter accumulation in boreal forest. Ecol Lett 24: 1341-1351. https://doi.org/10.1111/ele.13746 von Lützow M, Kögel-Knabner I, Ekschmitt K, Matzner E, Guggenberger G, Marschner B, Flessa H (2006) Stabilization of organic matter in temperate soils: mechanisms and their relevance under different soil conditions – a review. Eur J Soil Sci 57: 426-445. https://doi.org/10.1111/j.1365-2389.2006.00809.x Mainka M, Summerauer L, Wasner D, Garland G, Griepentrog M, Berhe AA, Doetterl S (2022) Soil geochemistry as a driver of soil organic matter composition: insights from a soil chronosequence. Biogeosciences 19: 1675-1689. https://doi.org/10.5194/bg-19-1675-2022 Martani E, Ferrarini A, Serra P, Pilla M, Marcone A, Amaducci S (2021) Belowground biomass C outweighs soil organic C of perennial energy crops: insights from a long-term multispecies trial. Glob Chang Biol Bioenergy 13: 459-472. https://doi.org/10.1111/gcbb.12785 de Mendiburu F (2023) agricolae: Statistical procedures for agricultural research. R Package. https://CRAN.R-project.org/package=agricolae Moore VM, Peters T, Schlautman B, Brummer EC (2023) Toward plant breeding for multicrop systems. Proc Natl Acad Sci USA 120: e2205792119. https://doi.org/10.1073/pnas.2205792119 Morais CLM, Lima KMG, Singh M, Martin FL (2020) Tutorial: multivariate classification for vibrational spectroscopy in biological samples. Nat Protoc 15: 2143-2162. https://doi.org/10.1038/s41596-020-0322-8 Ogle DH, Doll JC, Wheeler P, Dinno A (2022) FSA: fisheries stock analysis. R package. https://github.com/fishR-Core-Team/FSA Oksanen J, Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P.R., O’hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., Szoecs, E. (2020) vegan: Community ecology package. R package. https://CRAN.R-project.org/package=vegan Panagos P, Montanarella L, Barbero M, Schneegans A, Aguglia L, Jones A (2022) Soil priorities in the European Union. Geoderma Reg 29: e00510. https://doi.org/10.1016/j.geodrs.2022.e00510 Pérez-Izquierdo L, Saint-André L, Santenoise P, Buée M, Rincón A (2018) Tree genotype and seasonal effects on soil properties and biogeochemical functioning in Mediterranean pine forests. Eur J Soil Sci 69: 1087-1097. https://doi.org/10.1111/ejss.12712 Poeplau C, Prietz R, Don A (2022) Plot-scale variability of organic carbon in temperate agricultural soils—Implications for soil monitoring. J Plant Nutr Soil Sci 185: 403-416. https://doi.org/10.1002/jpln.202100393 Poffenbarger H, Castellano M, Egli D, Jaconi A, Moore V (2023) Contributions of plant breeding to soil carbon storage: Retrospect and prospects. Crop Sci 63: 990-1018. https://doi.org/10.1002/csc2.20920 Pouwels AD, Tom A, Eijkel GB, Boon JJ (1987) Characterisation of beech wood and its holocellulose and xylan fractions by pyrolysis-gas chromatography-mass spectrometry. J Anal Appl Pyrolysis 11: 417-436. https://doi.org/10.1016/0165-2370(87)85045-3 Prommer J, Walker TWN, Wanek W, Braun J, Zezula D, Hu Y, Hofhansl F, Richter A (2020) Increased microbial growth, biomass, and turnover drive soil organic carbon accumulation at higher plant diversity. Glob Chang Biol 26: 669-681. https://doi.org/10.1111/gcb.14777 Püttsepp Ü, Rosling A, Taylor AFS (2004) Ectomycorrhizal fungal communities associated with Salix viminalis L. and S. dasyclados Wimm. clones in a short-rotation forestry plantation. For Ecol Manage 196: 413-424. https://doi.org/10.1016/j.foreco.2004.04.003 Ramírez PB, Calderón FJ, Haddix M, Lugato E, Cotrufo MF (2021) Using diffuse reflectance spectroscopy as a high throughput method for quantifying soil C and N and their distribution in particulate and mineral-associated organic matter fractions. Front Environ Sci 9. https://doi.org/10.3389/fenvs.2021.634472 Rönnberg-Wästljung AC, Dufour L, Gao J, Hansson P-A, Herrmann A, Jebrane M, Johansson A-C, Kalita S, Molinder R, Nordh N-E, Ohlsson JA, Passoth V, Sandgren M, Schnürer A, Shi A, Terziev N, Daniel G, Weih M (2022) Optimized utilization of Salix —perspectives for the genetic improvement toward sustainable biofuel value chains. Glob Chang Biol Bioenergy 14: 1128-1144. https://doi.org/10.1111/gcbb.12991 Rumpel C, Amiraslani F, Bossio D, Chenu C, Henry B, Espinoza AF, Koutika L-S, Ladha J, Madari B, Minasny B, Olaleye AO, Shirato Y, Sall SN, Soussana J-F, Varela-Ortega C (2022) The role of soil carbon sequestration in enhancing human resilience in tackling global crises including pandemics. Soil Security 8: 100069. https://doi.org/10.1016/j.soisec.2022.100069 Ryals R, Kaiser M, Torn MS, Berhe AA, Silver WL (2014) Impacts of organic matter amendments on carbon and nitrogen dynamics in grassland soils. Soil Biol Biochem 68: 52-61. https://doi.org/10.1016/j.soilbio.2013.09.011 Savitzky A, Golay MJE (1964) Smoothing and differentiation of data by simplified least squares procedures. Anal Chem 36: 1627-1639. https://doi.org/10.1021/ac60214a047 Seitz VA, McGivern BB, Daly RA, Chaparro JM, Borton MA, Sheflin AM, Kresovich S, Shields L, Schipanski ME, Wrighton KC, Prenni JE (2022) Variation in root exudate composition influences soil microbiome membership and function. Appl Environ Microbiol 88: e00226-00222. https://doi.org/10.1128/aem.00226-22 Semchenko M, Xue P, Leigh T (2021) Functional diversity and identity of plant genotypes regulate rhizodeposition and soil microbial activity. New Phytol 232: 776-787. https://doi.org/10.1111/nph.17604 Smith WH (1969) Release of organic materials from the roots of tree seedlings. For Sci 15: 138-143. https://doi.org/10.1093/forestscience/15.2.138 Stevens A, Ramirez-Lopez L (2015) prospectr: Miscellaneous functions for processing and sample selection of spectroscopic data. R package. https://CRAN.R-project.org/package=prospectr Stewart K, Passey T, Verheecke-Vaessen C, Kevei Z, Xu X (2023) Is it feasible to use mixed orchards to manage apple scab? Fruit Res 3. https://doi.org/10.48130/FruRes-2023-0028 Sun L, Kominami Y, Yoshimura K, Kitayama K (2017) Root-exudate flux variations among four co-existing canopy species in a temperate forest, Japan. Ecol Res 32: 331-339. https://doi.org/10.1007/s11284-017-1440-9 Templier J, Derenne S, Croué J-P, Largeau C (2005) Comparative study of two fractions of riverine dissolved organic matter using various analytical pyrolytic methods and a 13 C CP/MAS NMR approach. Org Geochem 36: 1418-1442. https://doi.org/10.1016/j.orggeochem.2005.05.003 Thioulouse J, Dray S, Dufour A, Siberchicot A, Jombart T, Pavoine S (2018) Multivariate analysis of ecological data with ade4. Springer, New York. https://doi.org/10.1007/978-1-4939-8850-1 Vidal A, Quenea K, Alexis M, Derenne S (2016) Molecular fate of root and shoot litter on incorporation and decomposition in earthworm casts. Org Geochem 101: 1-10. https://doi.org/10.1016/j.orggeochem.2016.08.003 Wang Y, Wang S, Liu C, Zhu E, Jia J, Feng X (2023) Shifting relationships between SOC and molecular diversity in soils of varied carbon concentrations: evidence from drained wetlands. Geoderma 433: 116459. https://doi.org/10.1016/j.geoderma.2023.116459 Warembourg FR, Estelrich HD (2001) Plant phenology and soil fertility effects on below-ground carbon allocation for an annual ( Bromus madritensis ) and a perennial ( Bromus erectus ) grass species. Soil Biol Biochem 33: 1291-1303. https://doi.org/10.1016/S0038-0717(01)00033-5 Weih M (2013) Willow. In: Singh BP (ed) Biofuel crops: production, physiology and genetics. CABI. 415–426. https://doi.org/10.1079/9781845938857.0415 Weih M, Nordh N-E (2002) Characterising willows for biomass and phytoremediation: growth, nitrogen and water use of 14 willow clones under different irrigation and fertilisation regimes. Biomass Bioenergy 23: 397-413. https://doi.org/10.1016/S0961-9534(02)00067-3 Weih M, Nordh N-E (2005) Determinants of biomass production in hybrid willows and prediction of field performance from pot studies. Tree Physiol 25: 1197-1206. https://doi.org/10.1093/treephys/25.9.1197 Weih M, Hoeber S, Beyer F, Fransson P (2014) Traits to ecosystems: the ecological sustainability challenge when developing future energy crops. Front Energy Res 2. https://doi.org/10.3389/fenrg.2014.00017 Weih M, Glynn C, Baum C (2019) Willow short-rotation coppice as model system for exploring ecological theory on biodiversity–ecosystem function. Diversity 11: 125. https://doi.org/10.3390/d11080125 Wickham H, Averick M, Bryan J, Chang W, D’Agostino McGowan L, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller M, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019) Welcome to the Tidyverse. J Open Source Softw 4: 1686. https://doi.org/10.21105/joss.01686 Wiesenbauer J, König A, Gorka S, Marchand L, Nunan N, Kitzler B, Inselsbacher E, Kaiser C (2024) A pulse of simulated root exudation alters the composition and temporal dynamics of microbial metabolites in its immediate vicinity. Soil Biol Biochem 189: 109259. https://doi.org/10.1016/j.soilbio.2023.109259 Yergeau E, Sanschagrin S, Maynard C, St-Arnaud M, Greer CW (2013) Microbial expression profiles in the rhizosphere of willows depend on soil contamination. ISME J 8: 344-358. https://doi.org/10.1038/ismej.2013.163 Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revisions 29 Apr, 2024 Reviewers agreed at journal 09 Apr, 2024 Reviewers invited by journal 09 Apr, 2024 Editor invited by journal 04 Apr, 2024 Editor assigned by journal 04 Apr, 2024 First submitted to journal 03 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4214790","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":289131676,"identity":"ae7c71d0-04cf-42bb-a327-01c93b545703","order_by":0,"name":"Louis J.P. Dufour","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIie3PMQqDMBSA4SeCLo+6ZvEOlkAR9DDNootCoUvHQMEppWuhx+gBagk4Cb1Cj2Dp4uDQKAidEscO+UFJwC95Athsf9hKPTWACz5Xqw5iM/FmgurtXIAsIzATFxcRX6wfPSRM+GLzSQfCeCBrPcE2kgg5E9jSa1kpQrKtnpAikgCS3UlB3ZKPBCMjUYNJJkYST4M9OyOpcSZqyzgUWqH+pdlJjHIqsNk7p4rQimT6wQL/eHv3hyQUagH9kIbnQL7010z9Hust+N5ms9lshr7JZzzsaE3gTQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-8569-6304","institution":"Swedish University of Agricultural Sciences: Sveriges lantbruksuniversitet","correspondingAuthor":true,"prefix":"","firstName":"Louis","middleName":"J.P.","lastName":"Dufour","suffix":""},{"id":289131677,"identity":"e72482d6-a548-44d2-a59f-8569bb1b993a","order_by":1,"name":"Johanna Wetterlind","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Johanna","middleName":"","lastName":"Wetterlind","suffix":""},{"id":289131678,"identity":"6b36343f-723d-40ec-89c0-b1b011d021e2","order_by":2,"name":"Naoise Nunan","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Naoise","middleName":"","lastName":"Nunan","suffix":""},{"id":289131679,"identity":"7c279cee-4507-49e0-90a9-2b41ab302de8","order_by":3,"name":"Katell Quenea","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Katell","middleName":"","lastName":"Quenea","suffix":""},{"id":289131680,"identity":"b3b35bac-3d2f-495f-b9af-d3a85ab3de51","order_by":4,"name":"Andong Shi","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Andong","middleName":"","lastName":"Shi","suffix":""},{"id":289131681,"identity":"2aa62553-28ca-4c7a-97e5-05fc37b268ea","order_by":5,"name":"Martin Weih","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Weih","suffix":""},{"id":289131682,"identity":"ea068fa9-efbd-4244-935f-14e1bdebbe9a","order_by":6,"name":"Anke M. Herrmann","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Anke","middleName":"M.","lastName":"Herrmann","suffix":""}],"badges":[],"createdAt":"2024-04-03 21:09:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4214790/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4214790/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":54556027,"identity":"484dda06-b123-460f-a78e-b8ef5dc9a5a9","added_by":"auto","created_at":"2024-04-12 08:36:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1367879,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of the long-term \u003cem\u003eSalix\u003c/em\u003e experimental field trial established in 2001 at Pustnäs, near Uppsala, in central Sweden, where six varieties of \u003cem\u003eSalix\u003c/em\u003e were cultivated as short rotation coppice. (a) Design of the field trial: unfertilised (UF) and fertilised (F) treatments. (b) Representation of one monoclonal subplot, Björn, with sampling area indicated in green, individual willow plants are indicated as dots\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4214790/v1/1e50dc414e7c8947798436ff.png"},{"id":54554996,"identity":"65f917f9-b604-4111-907e-a5500da993a5","added_by":"auto","created_at":"2024-04-12 08:28:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98347,"visible":true,"origin":"","legend":"\u003cp\u003eTotal soil organic C (%) in samples from different willow monoclonal subplots: (a) the four unfertilised and (b) the four fertilised main plots. Black crossbars represent the average values (n=4). The dashed line indicates total soil organic C (%) which was on average 1.1 % (n=4) at the start of the field trial\u003csup\u003e \u003c/sup\u003e(Weih and Nordh, 2005)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4214790/v1/8406fcb22ae96825a42db7ba.png"},{"id":54554994,"identity":"89ba80d4-0a35-40e2-8e04-3fc4afe507ec","added_by":"auto","created_at":"2024-04-12 08:28:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":189179,"visible":true,"origin":"","legend":"\u003cp\u003eBetween-class analysis (BCA) of the full mid-infrared spectra of the soil from beneath the different \u003cem\u003eSalix \u003c/em\u003evarieties: (a) unfertilised treatment and (b) fertilised treatment. The abbreviation “Obs” refers to the percentage of the overall inertia in the data explained by the variable “\u003cem\u003eSalix\u003c/em\u003e varieties”\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4214790/v1/3f55d3dead8d2ffd93ea770a.png"},{"id":54556533,"identity":"706e601e-14b9-421a-bf45-3e0f43ba9134","added_by":"auto","created_at":"2024-04-12 08:44:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":211443,"visible":true,"origin":"","legend":"\u003cp\u003eBetween-class analysis (BCA) of identified pyrolysis products of soil organic matter among different willow monoclonal subplots for (a) 23 soil samples in the unfertilised treatment (one NA value for Tora main plot 2) and (b) 23 soil samples in the fertilised treatment (one NA value for Björn main plot 1). Only the BCA ordination on samples from the fertilised treatment was significant. The abbreviation “Obs” refers to the percentage of the overall inertia in the data explained by the variable “\u003cem\u003eSalix\u003c/em\u003e varieties”\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4214790/v1/46c6143a78a2e38654bdb864.png"},{"id":54554998,"identity":"73357bd5-62c1-4eb8-a8dc-b8be9336e907","added_by":"auto","created_at":"2024-04-12 08:28:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":91129,"visible":true,"origin":"","legend":"\u003cp\u003eEffective Simpson diversity index of identified pyrolysis products of soil organic matter from different willow monoclonal subplots: (a) unfertilised treatment and (b) the fertilised treatment. Black crossbars represent the average (n=4, except for Tora in the unfertilised main plot 2 and for Björn in the fertilised main plot 1)\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4214790/v1/4e8f092eec49a9f95b966653.png"},{"id":54557203,"identity":"ed62b64e-72d5-4d61-9e9e-12c2a394f76c","added_by":"auto","created_at":"2024-04-12 08:52:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1776269,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4214790/v1/768c205f-e30c-4e68-b6a1-0e0f87312c1b.pdf"}],"financialInterests":"","formattedTitle":"Salix species and varieties affect the molecular composition and diversity of soil organic matter","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThere has been a lot of recent interest in soil carbon (C) sequestration (Don et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) as it has several benefits: (i) the limitation of erosion, (ii) the improvement of water infiltration, purification and storage, (iii) the selection of more diverse and active communities of soil organisms (Rumpel et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Additionally, the sequestration of C in soil has become a focus of attention as part of the strategy for mitigating on-going climate change in the context of climate agreements (Kuyper et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2018\u003c/span\u003e ; Panagos et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChanges in several land management practices are known to influence organic C sequestration in soil, but these can be associated with major trade-offs (Amelung et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). For instance, the conversion of arable land to grassland generally leads to increases in soil organic C, but affects food production (Boysen et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In view of these potential trade-offs, the breeding of plant species and varieties with traits related to the quantity and quality of the C input to soil may be a way forward (Poffenbarger et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Weih et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). It has also been shown that the use of management systems with greater interspecific plant diversity can result in, for example, greater aboveground C in forests (Huang et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hulvey et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and greater belowground C in grasslands (Hungate et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Lange et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Prommer et al. \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Growing interest exists in developing more diverse agroecosystems (i.e. varietal and/or species mixtures) for agricultural crops (Kopp et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and trees (i.e. mixed species stands) (Huuskonen et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Stewart et al. \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Plant breeding may develop various intraspecific genotypes that may enhance the potential to sequester more C in soils. However, there is very little information on the potential effects that varietal diversity or varietal identity might have on soil C dynamics or soil organic C persistence (Semchenko et al. \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is known that different plant species belonging to the same plant genus produce litter and rhizodeposits that differ in both quantity and composition (Smith \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e1969\u003c/span\u003e; Sun et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Warembourg and Estelrich \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Furthermore, it has been widely shown that plant-microbe interactions influence both the composition of soil microbial communities (Korenblum et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Seitz et al. \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and metabolites (Wiesenbauer et al. \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), and their ability to decompose different forms of organic matter, i.e. their catabolic profiles (Brolsma et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Yergeau et al. \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). However, it is not clear whether these differences result in soil organic matter that differs substantially in quality and/or quantity, especially in the case of the small differences that might be expected across plant varieties (P\u0026eacute;rez-Izquierdo et al. \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChanges in the amount of soil C are difficult to detect over short timescales when land use varies (Jandl et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Poeplau et al. \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The composition of soil organic matter may be more responsive and so may serve as an early indicator of potential changes in organic C persistence and content. In addition to this, it has been argued that the molecular diversity of organic matter may be a driver of C persistence in soil (Lehmann et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Furthermore, soil structure is influenced by organic matter composition (Bucka et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bucka et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and may therefore influence C persistence indirectly, as the physical protection of soil organic C is thought to contribute to organic C persistence (von L\u0026uuml;tzow et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Although there are trade-offs between the composition of soil organic matter and persistence mechanisms at the continental scale (Hall et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e), it is unclear whether the composition of soil organic matter has an important role at the plot-scale where land management systems can change.\u003c/p\u003e \u003cp\u003eThe first step is to understand if and how varietal mixtures affect soil C dynamics, i.e. whether there are differences in (i) content and/or (ii) composition of organic matter in soils associated with different varieties. In this study, we chose to work with the plant genus \u003cem\u003eSalix\u003c/em\u003e. \u003cem\u003eSalix\u003c/em\u003e is a major woody-perennial bioenergy crop grown as short rotation coppice (Weih \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). This system is often considered to be a model for studying the relationship between biodiversity and productivity, due to its simplicity and similarity with grassland systems (Weih et al. \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Specifically, this system is used here to study how the taxonomic proximity of \u003cem\u003eSalix\u003c/em\u003e varieties constrain processes related to soil organic C dynamics. The aboveground characteristics of several varieties of the genus \u003cem\u003eSalix\u003c/em\u003e grown as short rotation coppice in monoculture are well characterized, showing some variation in traits among varieties (Bonosi et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Weih and Nordh \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Weih and Nordh \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Yet, there are only a few studies investigating their belowground traits, such as (i) root biomass (Baum et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hoeber et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), (ii) fine root composition and decomposition rates (He et al. \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), (iii) soil and root-associated fungal communities (Baum et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Hoeber et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hrynkiewicz et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Koczorski et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), (iv) dehydrogenases activities (Baum et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), or (v) their impact on the increase of soil organic carbon stock (Baum et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe objective of this study was to determine whether the molecular composition and diversity of soil organic matter was related to \u003cem\u003eSalix\u003c/em\u003e varieties. Specifically, we hypothesised that different \u003cem\u003eSalix\u003c/em\u003e plant varieties would lead to soil organic matter with different molecular compositions. The objective was addressed by characterising composition of organic matter in bulk soil under six different \u003cem\u003eSalix\u003c/em\u003e varieties in a long term field trial using two complementary approaches: (i) spectroscopic measurement in the mid-infrared wavelength range (diffuse reflectance infrared Fourier transform (DRIFT)), (ii) analytical pyrolysis combined with gas-chromatography-mass spectrometry (Pyrolysis-GC/MS).\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eLong-term experimental field trial\u003c/h2\u003e \u003cp\u003eWe used a field trial located in central Sweden (59\u0026deg;48'22\"N 17\u0026deg;40'24\"E). Within this field trial, willow varieties (\u003cem\u003eSalix\u003c/em\u003e spp.), across which taxonomic distance varied, were cultivated as short rotation coppice on a former arable cropland. The climate is temperate oceanic, and the soil is classified as a Vertic Cambisol, with a texture of 66% sand, 16% silt and 18% clay (Kalita et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Weih and Nordh \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). The field trial was set up in 2001 in a split plot design, with fertilisation as main plots and willow varieties in subplots. Four of the eight main plots were annually fertilised with approximately 100 kg nitrogen, 14 kg phosphorus and 47 kg potassium per hectare, and the remaining plots were left unfertilised (Baum et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Within each main plot, six monoclonal subplots were randomly distributed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). The subplots measured 6.75 \u0026times; 7 m and contained 3 double rows of plants and 84 plants in total (equivalent to a density of ~\u0026thinsp;18000 plants ha\u003csup\u003e-1\u003c/sup\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Each monoclonal subplot contained one of six commercial \u003cem\u003eSalix\u003c/em\u003e varieties that were more or less taxonomically similar, from full-siblings to differential species (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Two of the varieties, Loden and Gudrun, are taxonomically close. They have in common morphological traits of the species \u003cem\u003eS. dasyclados\u003c/em\u003e and are separated taxonomically at the species level compared to four others varieties, Bj\u0026ouml;rn, Tora, Tordis and Jorr that share some traits with the species \u003cem\u003eS. viminalis\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eSalix\u003c/em\u003e varieties planted in the long-term field trial established in 2001 at the site Pustn\u0026auml;s near Uppsala in central Sweden\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eName of \u003cem\u003eSalix\u003c/em\u003e varieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClone number\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eSalix\u003c/em\u003e Varieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTaxonomic separation at the species level\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBj\u0026ouml;rn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW 910006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. schwerinii\u003c/em\u003e E. Wolf x \u003cem\u003eS. viminalis\u003c/em\u003e L.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eS. viminalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTora\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW 910007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. schwerinii\u003c/em\u003e x \u003cem\u003eS. viminalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTordis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW 960299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e(S. schwerinii\u003c/em\u003e x \u003cem\u003eS. viminalis)\u003c/em\u003e x \u003cem\u003eS. viminalis L.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJorr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW 880013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. viminalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGudrun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW 940598\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. burjatica\u003c/em\u003e Nasarow x \u003cem\u003eS. dasyclados\u003c/em\u003e Wimm.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eS. dasyclados\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLoden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSW 890129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eS. dasyclados\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eSampling strategy\u003c/h2\u003e \u003cp\u003eSoil samples were collected from the centre of each monoclonal subplot in April 2019, 18 years after the initiation of the long-term field trial (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Eighteen sub-samples were taken with an auger (38 mm diameter) from the surface 20 cm, after removal of the litter layer, in an area of approximately 2 m\u003csup\u003e2\u003c/sup\u003e. The eighteen sub-samples were mixed to form one composite sample per monoclonal subplot, then sieved (\u0026lt;\u0026thinsp;4 mm) and air-dried. In total, there were 48 composite samples (6 monoclonal subplots \u0026times; 4 main plots \u0026times; 2 fertilisation treatments).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eGeneral soil properties\u003c/h2\u003e \u003cp\u003eSoil pH in each monoclonal subplot was determined using a pH Meter (Radiometer Copenhagen) in a soil:deionised water (1:5 soil:water) mixture at room temperature (23\u0026deg;C). The total N and organic C contents of the soils were determined by dry combustion using an elemental analyser (TruMac \u0026reg; CN, Leco corp, S:t Joseph, MI, USA). The total C and total inorganic C contents were determined in two separate runs. Prior to the analysis of total inorganic C content, samples were heated to 550\u0026deg;C for four hours to remove organic matter. The total organic C content (% TOC) was calculated as the difference between total C and total inorganic C content.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eSpectroscopic measurements\u003c/h2\u003e \u003cp\u003eMid-infrared spectra (mid-IR) were recorded in quadruplicate using dry, milled soil, resulting in a total of 192 spectra (48 samples x 4 analytical replicates). The samples were scanned using a Fourier transform IR (FT-IR) Alpha II Drift spectrometer (Bruker, Germany, Serial No. 12547393) equipped with a diffuse reflection (DRIFT) module. We used a spectral resolution of 4 cm\u003csup\u003e-1\u003c/sup\u003e. Background measurements were carried out using a gold standard. Each spectrum was the average of 24 scans. The apparent absorbance (A) was determined from the reflectance (R) spectra (A\u0026thinsp;=\u0026thinsp;log 1/R) (Guillou et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The signal of the spectra between 630 cm\u003csup\u003e-1\u003c/sup\u003e and 400 cm\u003csup\u003e-1\u003c/sup\u003e was very noisy and removed from further analyses. The spectra, therefore, contained data from 4000 cm\u003csup\u003e-1\u003c/sup\u003e to 630 cm\u003csup\u003e-1\u003c/sup\u003e (2500 nm to 15873 nm). Each spectrum was pre-processed using the Savitzky-Golay functions of the R package \u0026ldquo;prospectr\u0026rdquo; (Stevens and Ramirez-Lopez \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) with a first derivative using three point smoothing and a second order polynomial (Savitzky and Golay \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). Standard normal variate was applied to correct the light scattering (Morais et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The mean of the apparent absorbance of the four mid-IR replicates was determined for each sample using the summarise function in the R package \u0026ldquo;dplyr\u0026rdquo; (version 1.8.6) (Wickham et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The full mid-IR spectral range was used for multivariate statistics (Ram\u0026iacute;rez et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003ePyrolysis \u0026ndash; Gas Chromatography \u0026ndash; Mass Spectrometry (Pyrolysis-GC/MS)\u003c/h2\u003e \u003cp\u003eSoil samples were analysed by Pyrolysis-GC/MS in the presence of tetramethylammonium hydroxide (TMAH) (25% methanol), an alkylating agent that improves the detection of polar compounds. Around 6 mg of sample was loaded in a quartz tube with 10\u0026micro;l of TMAH. Glass wool was placed on top of the sample and the sample was then pyrolysed (Pyroprobe 6250, CDS) at 650\u0026deg;C for 15 s. The pyrolysis products were transferred via a transfer line, maintained at 300\u0026deg;C, to the injector of a gas chromatograph (7890B, Agilent) operated in split mode (20ml/min). The separation of pyrolysis products was carried out using a non-polar gas chromatograph column Rxi5Sil MS (30 m x 0.25 mm x 0.5 \u0026micro;m, Restek), with helium as the carrier gas (1 mL/min) and an oven ramp (initial temperature of 50\u0026deg;C maintained for 10min, raised by 2\u0026deg;C/min to 320\u0026deg;C, the final temperature, maintained for 13min). The gas chromatograph was connected to a mass spectrometer (5977B, Agilent), which was used in the scan mode and operated in electron ionization (electron impact source 70 eV; 230\u0026deg;C). The analysis was performed with a quadrupole mass spectrometer, working at 2 scans/s from 35 to 700 \u003cem\u003em\u003c/em\u003e/\u003cem\u003ez\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eCompounds were identified on the basis of their mass spectra, retention times, and comparison with the Wiley mass spectra library (v 2.73) and with published mass spectra. Peaks were integrated using Agilent Masshunter (Version B. 09.00) on the total ion current trace and the relative contribution of each pyrolysis product was calculated as the area of the product over the sum of the peak areas of all of the pyrolysis products.\u003c/p\u003e \u003cp\u003ePyrolysis products were classified into biochemical categories based on previous publications (Barr\u0026eacute; et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Derenne et al. 2015; Dignac et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; El Hayany et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Lejay et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Lejay et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Vidal et al \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Their most probable origin were from (i) higher plants (lignin, long chain fatty acids, long chain alkanes, cutine and/or suberine derived compounds), (ii) microorganisms (short chain fatty acids and short chain alkanes), (iii) multiple sources (nitrogenous compounds, carbohydrates), (iv) an unspecific origin: pyrolysis products derived from aliphatics, aromatics (phenols, benzenes, polyaromatics) and N-heterocylic compounds, i.e. triazine as a probable by-product from TMAH (Templier et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Diversity indices of pyrolysis products were estimated using the effective Simpson index of pyrolysis products (Jost \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Lagkouvardos et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eRstudio (Version 1.3.1073 - \u0026copy; 2009\u0026ndash;2020 Rstudio, Inc) (RStudio Team, 2015. RStudio: Integrated Development for R. RStudio, Inc., Boston, MA, USA) was used for all statistical analyses and plots. The level of significance for the following statistical analyses was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026le;\u0026thinsp;0.05. Differences in means of soil N and organic C contents were tested using a one-way analysis of variance with block (the block effect was the \u0026ldquo;No. of main plots\u0026rdquo; of the field trial), first among \u0026ldquo;\u003cem\u003eSalix\u003c/em\u003e varieties\u0026rdquo; and then among \u0026ldquo;\u003cem\u003eSalix\u003c/em\u003e species\u0026rdquo;. This was followed by a Tukey honest significant difference post hoc test (implemented in the \u0026ldquo;agricolae\u0026rdquo; library version 1.3-7) (de Mendiburu \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The pH values were not normally distributed and therefore differences in medians among \u0026ldquo;\u003cem\u003eSalix\u003c/em\u003e varieties\u0026rdquo; and \u0026ldquo;No. of main plots\u0026rdquo; were analysed using a one-way Kruskal-Wallis test followed by a Dunn\u0026acute;s test of multiple comparisons (implemented in the \u0026ldquo;FSA\u0026rdquo; library version 0.9.3) (Ogle et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe profiles of pyrolysis compound classes and full mid-IR spectral range were analysed using a principal component analysis (PCA) where the data were centered and scaled, followed by between class analysis (BCA) in order to determine whether the \u003cem\u003eSalix\u003c/em\u003e varieties affected the profiles (implemented in the ade4 library version 1.7\u0026ndash;19) (Thioulouse et al. \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The relationships between the profiles of pyrolysis compound classes and full mid-IR spectral range were assessed using Mantel tests on the respective distance matrix (implemented in the vegan library version 2.6-2) (Oksanen et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe values of the effective Simpson index of identified pyrolysis products among \u0026ldquo;\u003cem\u003eSalix\u003c/em\u003e varieties\u0026rdquo; had different variances and therefore, differences in means were tested using a Welch\u0026rsquo;s one-way analysis of variance followed by a Games-Howell post hoc test (implemented in the rstatix library version 0.7.0) (Games and Howell \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Kassambara \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe fertilisation treatments in the field trial were not randomised, as the fertilised and unfertilised main plots were grouped together (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea). However, the monoclonal subplots were randomised within each main plot. Therefore, we analysed the effect of \u003cem\u003eSalix\u003c/em\u003e varieties on soil organic matter composition, soil organic C and N contents and pH in the unfertilised and fertilised treatments separately. The resulting number of replicates for each willow variety was four in both the unfertilised and fertilised treatments.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eGeneral soil properties\u003c/h2\u003e \u003cp\u003eSoil total organic C content increased by a factor of approximately 1.3 relative to values at the beginning of the field trial in 2001, but total N content remained constant in both the fertilised and unfertilised treatments (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). However, among \u003cem\u003eSalix\u003c/em\u003e varieties, no significant differences in soil organic C or N contents, or pH were observed in both the fertilised and unfertilised treatments (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSoil characteristics of the long-term field trial. Means of total N and organic C contents and medians of pH are presented for four field replicates. Means and medians suffixed by a different letter are significantly different at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSoil treatment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSalix\u003c/em\u003e varieties\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal organic C* content (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTotal N* content (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003epH (H\u003csub\u003e2\u003c/sub\u003eO)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnfertilised\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBj\u0026ouml;rn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTora\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.6 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTordis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJorr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.6 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGudrun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFertilised\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBj\u0026ouml;rn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTora\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.2 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTordis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJorr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.9 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGudrun\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLoden\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.9 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnfertilised\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.3 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.7 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14 \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.8 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13 \u003csup\u003ecb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFertilised\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13 \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.8 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.9 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4 \u003csup\u003eab\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMain plot 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.1 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e* At the start of the experimental field trial in 2001, total organic C and total N contents were on average 1.1% and 0.12% respectively and the bulk density was on average 1.3 g cm\u003csup\u003e-1\u003c/sup\u003e (n\u0026thinsp;=\u0026thinsp;4) across the trial (Weih and Nordh, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAt the species level, a small but significant effect of \u003cem\u003eSalix\u003c/em\u003e species on soil organic C content was observed in the fertilised treatment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035). On average \u003cem\u003eS. dasyclados\u003c/em\u003e varieties had slightly more soil organic C (0.1%) than \u003cem\u003eS. viminalis\u003c/em\u003e varieties. No effect was observed on the soil N content (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.071).\u003c/p\u003e \u003cp\u003eAmong the main plots there were, however, significant differences in soil total N and organic C contents in the unfertilised treatment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), with less pronounced but significant differences in the fertilised treatment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Similarly, soil pH varied significantly among the main plots, but only in the unfertilised treatment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Positive and significant relationships between soil pH, soil N and organic C contents (adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.5, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) were found in the unfertilised treatment plots, but not in the fertilised treatments.\u003c/p\u003e \u003cp\u003e \u003cb\u003eComposition of soil organic matter below\u003c/b\u003e \u003cb\u003eSalix\u003c/b\u003e \u003cb\u003especies: mid-IR spectra\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe Between Class Analysis (BCA) of the mid-IR spectra did not reveal any significant separation between \u003cem\u003eSalix\u003c/em\u003e varieties in the unfertilised treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea), but a significant separation was found in the fertilised treatment (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The variable \u0026ldquo;\u003cem\u003eSalix\u003c/em\u003e varieties\u0026rdquo; explained 22.3% and 24.4% of the overall inertia of the principal component analysis of the unfertilised and fertilised treatments, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOverall, in the fertilised treatment, the composition of soil organic matter below Loden and Jorr varieties differed from the other four varieties (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb):\u003c/p\u003e \u003cp\u003eLoden and Jorr were separated from Tora along the horizontal axis due to less abundant carboxylic acid C-O stretch, OH deformation, ester, phenol C-O asymmetric stretch (wavenumbers ranging from 1200 to 1280 cm\u003csup\u003e-1\u003c/sup\u003e) and C\u0026thinsp;=\u0026thinsp;O stretch (wavenumbers ranging from 1645 to 1717 cm\u003csup\u003e-1\u003c/sup\u003e). Furthermore, soil organic matter below Loden was enriched, relative to Tora, Bj\u0026ouml;rn, Tordis, in aromatic compounds, with more abundant aromatic C-H out-of-plane bend, aromatic C\u0026thinsp;=\u0026thinsp;C stretch and/or conjugated ketone C\u0026thinsp;=\u0026thinsp;O stretch, and/or amide N-H bend and C\u0026thinsp;=\u0026thinsp;O stretch (amide II) (wavenumbers ranging from 894 to 1036 cm\u003csup\u003e-1\u003c/sup\u003e and from 1503 to 1639 cm\u003csup\u003e-1\u003c/sup\u003e). Additionally, Jorr also differed from Tordis, Bj\u0026ouml;rn and Gudrun due to less abundant alcohol, ether, phenol C-O-C stretch and poly OH stretch assigned molecular functional groups (wavenumbers ranging from 1160 to 1190 cm\u003csup\u003e-1\u003c/sup\u003e).\u003c/p\u003e \u003cp\u003eThe composition of soil organic matter below Jorr separated along the vertical axis due to higher abundances of aliphatic C-H asymmetric stretches (wavenumbers 2950\u0026ndash;2917 and 2865\u0026ndash;2849 cm\u003csup\u003e-1\u003c/sup\u003e) compared to Tordis and Gudrun (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb).\u003c/p\u003e \u003cp\u003eIn the unfertilised treatment, the mid-IR spectra did not differ among the six \u003cem\u003eSalix\u003c/em\u003e varieties (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). Yet, the composition of soil organic matter signifivantly differed among the four main plots (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (data not shown). Here, the aliphatic C-H asymmetric stretches as well as carbonate and calcite stretches were least abundant in the second main plot and most abundant in third main plot. Changes in mid-IR spectra between the four main plots were similar to changes in other general soil properties such as pH and soil organic C (adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.5; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003cb\u003eComposition of soil organic matter below\u003c/b\u003e \u003cb\u003eSalix\u003c/b\u003e \u003cb\u003especies: pyrolysis-GC/MS\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe BCA of the pyrolysis-GC/MS did not reveal any significant separation \u003cem\u003eSalix\u003c/em\u003e varieties in the unfertilised treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), but a significant separation in the fertilised treatment was found (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.03, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). The variable \u0026ldquo;\u003cem\u003eSalix\u003c/em\u003e varieties\u0026rdquo; explained 16.5% and 34.8% of the overall variation in the unfertilised and fertilised treatments, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The composition of soil organic matter below Gudrun differed the most from the varieties Tora and Jorr in the fertilised treatment (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBiochemical categories of identified pyrolysis products from the soils in the fertilised treatment. The relative abundances expressed as per mille (\u0026permil;) are shown as the mean\u0026thinsp;\u0026plusmn;\u0026thinsp;one standard deviation for four replicates (except for Bj\u0026ouml;rn that has one NA value). Polyaromatic compounds, cutin and/or suberine originated compounds, short chain alkane and long chain alkane are not presented because their relative abundances were similar among varieties\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMost probable origin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBiochemical categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBj\u0026ouml;rn\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTora\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTordis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eJorr\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGudrun\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLoden\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher plant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLignin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e113\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e96\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e111\u0026thinsp;\u0026plusmn;\u0026thinsp;38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e133\u0026thinsp;\u0026plusmn;\u0026thinsp;27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e142\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e152\u0026thinsp;\u0026plusmn;\u0026thinsp;39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLong chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e23\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e28\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e30\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e18\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e19\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicrobial community\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShort chain fatty acids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e44\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e47\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e42\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e39\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple origins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNitrogenous compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e79\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e71\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCarbohydrates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e55\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e38\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e53\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther aliphatics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e117\u0026thinsp;\u0026plusmn;\u0026thinsp;96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e179\u0026thinsp;\u0026plusmn;\u0026thinsp;74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e154\u0026thinsp;\u0026plusmn;\u0026thinsp;81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e303\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e208\u0026thinsp;\u0026plusmn;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e207\u0026thinsp;\u0026plusmn;\u0026thinsp;37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePhenols\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e13\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e10\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e11\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e26\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e25\u0026thinsp;\u0026plusmn;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBenzene derivatives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e162\u0026thinsp;\u0026plusmn;\u0026thinsp;108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e190\u0026thinsp;\u0026plusmn;\u0026thinsp;114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e198\u0026thinsp;\u0026plusmn;\u0026thinsp;81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e101\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e184\u0026thinsp;\u0026plusmn;\u0026thinsp;67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e198\u0026thinsp;\u0026plusmn;\u0026thinsp;54\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN-heterocyclic compounds\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e396\u0026thinsp;\u0026plusmn;\u0026thinsp;142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c4\"\u003e \u003cp\u003e340\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e \u003cp\u003e337\u0026thinsp;\u0026plusmn;\u0026thinsp;82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c6\"\u003e \u003cp\u003e253\u0026thinsp;\u0026plusmn;\u0026thinsp;48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c7\"\u003e \u003cp\u003e223\u0026thinsp;\u0026plusmn;\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c8\"\u003e \u003cp\u003e213\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eGudrun and, to a lesser extent, Loden were separated from the other varieties along the horizontal axis due to a higher abundance of phenol derivatives of unspecific origin. Furthermore, Gudrun was enriched in nitrogenous compounds from proteins and nucleic acids compared to Tordis and Tora. Carbohydrates and lignin derived compounds from higher plants were enriched in Gudrun compared to Tora. Loden was depleted in short chain fatty acids derived from microorganisms compared to Tora. Loden and Gudrun clearly had a lower abundance of N-heterocylic compounds of unspecific origin compared to Tora, Bj\u0026ouml;rn and Tordis.\u003c/p\u003e \u003cp\u003eThe separation along the vertical axis between Jorr and the other varieties was due to more aliphatic compounds of unspecific origin and more abundant long chain fatty acids of higher plant origin, particularly in comparison to Gudrun and Loden. Furthermore, soil organic matter below Jorr was depleted in benzene derivatives of unspecific origin relative to the other varieties.\u003c/p\u003e \u003cp\u003eAlthough soil organic matter below the six varieties was composed of similar compound classes differing only in relative abundances, we observed that the diversities of identified pyrolysis products were different among varieties in the fertilised treatment: Gudrun had a significantly higher effective Simpson index compared to Tora and Tordis (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and Jorr (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), by a factor of about 1.7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the unfertilised treatment, we did not observe any differences in pyrolysis-GC/MS profiles or diversity of pyrolysis products between varieties or between the four main plots.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe link between the organic matter inputs from vegetation (rhizodeposition and litter) has long been established for different types of plant cover and plant diversities. For example, diverse plant communities tend to increase soil C stocks relative to monocultures (Chen et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the links between soil organic matter and individual plant varieties or species are less well studied. It is important to understand the effects that plant varieties or species can have on soil organic matter as it can aid decision making when selecting plants for managing soil organic matter. This study looked at the content and composition of soil organic matter under different \u003cem\u003eSalix\u003c/em\u003e varieties that were either fertilised or left unfertilised. The unfertilised plots showed a high degree of spatial variability in many soil properties (pH, total N and total organic C contents) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) which are likely to have masked any potential differences that might have occurred among varieties. As a result, no significant effects of \u003cem\u003eSalix\u003c/em\u003e varieties were observed in the fertilised treatment on the molecular composition and diversity of soil organic matter. The fertilised plots were less variable and significant differences were observed. Therefore, the following only refers to the results obtained in the fertilised plots.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEffects of\u003c/b\u003e \u003cb\u003eSalix\u003c/b\u003e \u003cb\u003evarieties and species on the amount of soil organic matter\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEven though there were differences in aboveground traits (biomass, N content and yield) among varieties (Weih and Nordh \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Weih and Nordh \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), which might affect the organic matter inputs to the soil (Hirte et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), no differences in total soil organic C content among varieties were observed. This is contrary to what was found by Baum et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The latter study analysed the surface 10 cm whereas the surface 20 cm were analysed here, which might explain the divergent results. Although it has been observed that about half the root biomass of \u003cem\u003eSalix\u003c/em\u003e is found in the top 10 cm (Heinsoo et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), a significant proportion of the rooting system is found at greater depths (Chimento and Amaducci \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Therefore, we decided to sample soils down to 20 cm in this study. Nevertheless, the greater sampling depth may have diluted any potential varietal signal. The difference between the results of Baum et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and those obtained here suggests that a varietal effect, although weak, might be greater in the upper 10 cm of the soil. This is in line with the work of Martani et al. (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) where the authors observed a positive rate of soil organic C sequestration in the 0\u0026ndash;10 cm layer for willow but either no effect or a negative effect in the 10\u0026ndash;30 cm soil layer.\u003c/p\u003e \u003cp\u003eAt the species level, \u003cem\u003eS. dasyclados\u003c/em\u003e varieties had significantly lower total soil organic C content than \u003cem\u003eS. viminalis\u003c/em\u003e varieties (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This suggests that the differences in traits among species rather than varieties were sufficiently large to affect the amount of soil organic C. The accumulated shoot C in the fertilised plots of the four \u003cem\u003eS. viminalis\u003c/em\u003e varieties was approximately twice that of the two \u003cem\u003eS. dasyclados\u003c/em\u003e varieties (R\u0026ouml;nnberg-W\u0026auml;stljung et al. 2021). \u003cem\u003eS. dasyclados\u003c/em\u003e varieties tend to have both higher fine root biomass (Heinsoo et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) and higher ectomycorrhizal colonisation than \u003cem\u003eS. viminalis\u003c/em\u003e (P\u0026uuml;ttsepp et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). On the one hand, roots that are colonised by ectomycorrhiza tend to be decomposed less rapidly than roots that are not mycorrhizal (Langley et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). On the other hand, the abundance of some genera of ectomycorrhizal fungi (i.e. \u003cem\u003eRussela\u003c/em\u003e and \u003cem\u003eCortinarius\u003c/em\u003e), that are capable of producing extracellular peroxidase, have been shown to correlate negatively with the proportion of soil organic matter associated with minerals (Hicks et al. 2023). \u003cem\u003eS. dasyclados\u003c/em\u003e varieties are particularly colonised by \u003cem\u003eCortinarius\u003c/em\u003e spp., a morphotype that has been associated with reduced soil organic matter contents in boreal forests (Lindahl et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), potentially via the production of manganese-peroxidases (Kellner et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). No such colonisation of \u003cem\u003eS. viminalis\u003c/em\u003e has been found (P\u0026uuml;ttsepp et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). However, it should be noted that \u003cem\u003eCortinarius\u003c/em\u003e spp. abundances (J\u0026ouml;rgensen et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and peroxidase activity (B\u0026ouml;deker et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) can be reduced by N fertilisation and therefore this interpretation might not be pertinent for forest soils. Yet, here in the context of arable land, this explanation may still remain relevant (BD Lindhal, personal communication).\u003c/p\u003e \u003cp\u003e \u003cb\u003eEffects of\u003c/b\u003e \u003cb\u003eSalix\u003c/b\u003e \u003cb\u003evarieties and species on composition of soil organic matter\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe most significant result obtained in this study is that the taxonomic proximity of the \u003cem\u003eSalix\u003c/em\u003e varieties affected the molecular composition and diversity of the soil organic matter, as seen in both the pyrolysis-GC and mid-IR analyses (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Even though there is no simple way of quantifying the taxonomic distance of the \u003cem\u003eSalix\u003c/em\u003e varieties (Fogelqvist et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), Loden and Gudrun are separated taxonomically at the species level from all other varieties (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Weih and Nordh \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Loden is a pure \u003cem\u003eS. dasyclados\u003c/em\u003e clone whereas Gudrun contains two species, namely \u003cem\u003eS. burjatica\u003c/em\u003e and \u003cem\u003eS. dasyclados\u003c/em\u003e. Jorr is a pure \u003cem\u003eS. viminalis\u003c/em\u003e clone, Tordis is derived from two species (\u003cem\u003eS. schwerinii\u003c/em\u003e and \u003cem\u003eS. viminalis\u003c/em\u003e) and Bj\u0026ouml;rn and Tora are full-siblings. The latter two are therefore expected to behave in very similar way in an ecological context.\u003c/p\u003e \u003cp\u003eHypothetically, the taxonomic proximity of the varieties may reflect a proximity of traits. Previous studies have suggested that \u003cem\u003eS. viminalis\u003c/em\u003e varieties differ from \u003cem\u003eS. dasyclados\u003c/em\u003e varieties in the following characteristics: (i) higher aboveground biomass yields (Kalita et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), (ii) higher sodium concentrations in leaves (\u0026Aring;gren and Weih \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), (iii) higher contents in catechin and rutin (quercetin 3-\u003cem\u003eO\u003c/em\u003e-rutinoside), lower naringenin and salicylic acid concentrations (Curtasu and N\u0026oslash;rskov \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), (iv) lower lignin contents (Kalita et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), (v) lower leaf area ratios, lower leaf area productivity (Weih and Nordh \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), (vi) lower leaf N content (Hoeber et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), (vii) lower ectomycorrhyzal but higher arbuscular mycorrhizal colonization (P\u0026uuml;ttsepp et al. \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), (viii) lower fine root biomass (Baum et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Yet, Hoeber et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) showed variability of leaf litter decomposition across the four \u003cem\u003eS. viminalis\u003c/em\u003e (Bj\u0026ouml;rn, Tora, Tordis and Jorr) which did not strictly follow the taxonomic proximity hypothesis in relation to remaining mass and N. Due to the complexity of the relationship between above- and belowground inputs and soil organic matter properties (K\u0026ouml;gel-Knabner \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), it is not possible to say which, if any, of these traits are responsible for the differences in composition of soil organic matter that were found here. Although it is likely to be a combination of a number of them.\u003c/p\u003e \u003cp\u003eMost of these traits are not clearly reflected in the pyrolysis product profiles of soil organic matter. However, the soil organic matter under the \u003cem\u003eS. dasyclados\u003c/em\u003e varieties contained more lignin compared to \u003cem\u003eS. viminalis\u003c/em\u003e, possibly due to the higher lignin content of their aboveground biomass and the relatively lower decomposition rates of lignin compared to other constituents of the plant litter (Hall et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e). The higher phenolic compound concentrations under \u003cem\u003eS. dasyclados\u003c/em\u003e are likely related to the lignin contents, as phenolic compounds are formed upon the pyrolysis of lignin (Dignac et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe differences in molecular diversity may be due to a combination of greater organic C inputs from \u003cem\u003eS. viminalis\u003c/em\u003e varieties and greater microbial processing of the organic matter inputs in soil under \u003cem\u003eS. dasyclados\u003c/em\u003e varieties. Others have found that microbial and enzymatic processing of organic matter can dramatically increase its molecular diversity (Kallenbach et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In addition, a negative relationship between root biomass and the molecular diversity of soil organic matter has been found suggesting that higher inputs decrease molecular diversity (Wang et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Moreover, there were more aromatic stretches, and carboxylate C-O and ketone C\u0026thinsp;=\u0026thinsp;O stretches beneath Loden than in other varieties. These are suggestive of more complex plant derived organic matter and a greater degree of transformation of the soil organic matter, respectively (Fissore et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ryals et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). This confirms the idea that there might be more microbial processing in the soil beneath Loden.\u003c/p\u003e \u003cp\u003eEven though most of the differences in molecular composition and diversity of the soil organic matter were seen between varieties of different species, the soil organic C under Jorr also differed from that in the other \u003cem\u003eS. viminalis\u003c/em\u003e varieties. Jorr biomass contains more cellobiose, galactose and arabinose, but contained less xylose and had a lower biomethane potential than other \u003cem\u003eS. viminalis\u003c/em\u003e varieties (Kalita et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The major differences in acetic acid derived compounds under Jorr may be due to differences in the composition of the hemicellulose monomer profiles in its above-ground biomass (Kalita et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Acetic acid derived compounds can have multiple origins but the cleavage of hemicellulose acetyl groups is among them (Pouwels et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e1987\u003c/span\u003e). The aliphatic region of the IR spectra and the aliphatic contents (long chain fatty acids and other aliphatics) obtained by pyrolysis were higher in Jorr than in the other varieties. It has been suggested that these may be indicators of plant derived organic matter with a molecular structure dense in C-H bonds such as in waxes from leaf litter or some root exudates dense in hydrocarbon bonds (Mainka et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eComparison between pyrolysis GC/MS and mid-IR analyses\u003c/h2\u003e \u003cp\u003eCompared to the pyrolysis GC/MS method, the mid-IR spectral analysis approach is simpler, cheaper and has the advantage of being non-destructive. We were therefore interested in determining whether mid-IR spectral analyses could be used to determine differences in the composition of the organic matter in soil under different varieties of \u003cem\u003eSalix\u003c/em\u003e. Although the mid-IR method discriminated certain varieties from others (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), the discrimination was not identical to that found with pyrolysis. Indeed, a Mantel test showed that the two methods were not closely related (data not shown). The divergence between the two methods may be due to the fact that the mid-IR analysis discriminated Jorr and Loden from the other varieties while the pyrolysis analysis mainly discriminated Gudrun and Loden from the other varieties.\u003c/p\u003e \u003cp\u003eNevertheless, there were some similarities: for example, both the mid-IR and pyrolysis data suggest that the carbohydrate content of soil organic matter beneath Jorr was lower than that in Gudrun and, as indicated above, similarities were also seen in the aliphatics/long chain fatty acids. These similarities may be due to the relatively high variation of these molecular groups within our data and between the varieties (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), allowing the mid-IR spectral analysis to detect them.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study provides evidence that the taxonomic distance between plant varieties within the genera \u003cem\u003eSalix\u003c/em\u003e can affect the molecular composition and diversity of soil organic matter. Our results suggest that plant breeding and adopting simultaneous plantation of varieties may affect molecular composition and diversity of organic matter in soils, which is considered as a driver of C persistence in soils (Lehmann et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Such an effect should be considered in breeding programmes for biomass crop and multicrop systems (Moore et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The smaller differences that were seen among varieties from the same species suggest that breeding for greater soil organic C content is a viable research avenue to follow. It would be interesting to determine whether these results are maintained or amplified in diversified systems, i.e. where different varieties are grown together.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting Interests\u003c/h2\u003e \u003cp\u003eThe authors declare they have no relevant financial or non-financial interests to disclose.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Swedish Research Council for Sustainable Development, FORMAS project (22836000 and OPTUS 22551000).\u003c/p\u003e\u003ch2\u003eAuthor Contributions\u003c/h2\u003e \u003cp\u003eA.M.H. and M.W. conceptualized the study.\u003c/p\u003e\u003ch2\u003eAcknowledgments\u003c/h2\u003e \u003cp\u003eThis research was funded by the Swedish Research Council for Sustainable Development, FORMAS projects (22836000 and OPTUS 22551000). The authors would like to thank N.-E. Nordh for assistance with the field sampling, C. Baum, P. Barr\u0026eacute;, P. Smith and S. Manzoni for discussions related to the long-term field trial, material preparation, data collection and analysis to carry on, M. Sp\u0026aring;ngberg, E. Ljunggren for assistance with laboratory work, E. Karltun and D. Wasner for assistance with mid-IR analysis as well as J. Forkman for assistance with statistical analysis. Thanks to E. Pihlap, M. Ota and Y. Tian for valuable comments on the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e \u003cp\u003eThe datasets generated during the current study and the custom R scripts used for data analysis are available from the corresponding author on reasonable request and from the public repository entitled Zenodo (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://zenodo.org/records/10906904\u003c/span\u003e\u003cspan address=\"https://zenodo.org/records/10906904\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Creative Commons Attribution 4.0 International).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmelung W, Bossio D, de Vries W, K\u0026ouml;gel-Knabner I, Lehmann J, Amundson R, Bol R, Collins C, Lal R, Leifeld J, Minasny B, Pan G, Paustian K, Rumpel C, Sanderman J, van Groenigen JW, Mooney S, van Wesemael B, Wander M, Chabbi A (2020) Towards a global-scale soil climate mitigation strategy. Nat Commun 11: 5427. https://doi.org/10.1038/s41467-020-18887-7\u003c/li\u003e\n\u003cli\u003e\u0026Aring;gren GI, Weih M (2012) Plant stoichiometry at different scales: element concentration patterns reflect environment more than genotype. New Phytol 194: 944-952. https://doi.org/10.1111/j.1469-8137.2012.04114.x\u003c/li\u003e\n\u003cli\u003eBarr\u0026eacute; P, Qu\u0026eacute;n\u0026eacute;a K, Vidal A, C\u0026eacute;cillon L, Christensen BT, K\u0026auml;tterer T, Macdonald A, Petit L, Plante AF, van Oort F, Chenu C (2018) Microbial and plant-derived compounds both contribute to persistent soil organic carbon in temperate soils. Biogeochemistry 140: 81-92. https://doi.org/10.1007/s10533-018-0475-5\u003c/li\u003e\n\u003cli\u003eBaum C, Hrynkiewicz K, Szymańska S, Vitow N, Hoeber S, Fransson PMA, Weih M (2018) Mixture of \u003cem\u003eSalix\u003c/em\u003e genotypes promotes root colonization with dark septate endophytes and changes P cycling in the mycorrhizosphere. Front Microbiol 9. https://doi.org/10.3389/fmicb.2018.01012\u003c/li\u003e\n\u003cli\u003eBaum C, Amm T, Kahle P, Weih M (2020) Fertilization effects on soil ecology strongly depend on the genotype in a willow (\u003cem\u003eSalix\u003c/em\u003e spp.) plantation. For Ecol Manage 466: 118126. https://doi.org/https://doi.org/10.1016/j.foreco.2020.118126\u003c/li\u003e\n\u003cli\u003eB\u0026ouml;deker ITM, Clemmensen KE, de Boer W, Martin F, Olson \u0026Aring;, Lindahl BD (2014) Ectomycorrhizal \u003cem\u003eCortinarius\u003c/em\u003e species participate in enzymatic oxidation of humus in northern forest ecosystems. New Phytol 203: 245-256. https://doi.org/10.1111/nph.12791\u003c/li\u003e\n\u003cli\u003eBonosi L, Ghelardini L, Weih M (2013) Towards making willows potential bio-resources in the South: northern \u003cem\u003eSalix\u003c/em\u003e hybrids can cope with warm and dry climate when irrigated. Biomass Bioenergy 51: 136-144. https://doi.org/10.1016/j.biombioe.2013.01.009\u003c/li\u003e\n\u003cli\u003eBoysen LR, Lucht W, Gerten D (2017) Trade-offs for food production, nature conservation and climate limit the terrestrial carbon dioxide removal potential. Glob Chang Biol 23: 4303-4317. https://doi.org/10.1111/gcb.13745\u003c/li\u003e\n\u003cli\u003eBrolsma KM, Vonk JA, Mommer L, Van Ruijven J, Hoffland E, De Goede RGM (2017) Microbial catabolic diversity in and beyond the rhizosphere of plant species and plant genotypes. Pedobiologia 61: 43-49. https://doi.org/10.1016/j.pedobi.2017.01.006\u003c/li\u003e\n\u003cli\u003eBucka FB, K\u0026ouml;lbl A, Uteau D, Peth S, K\u0026ouml;gel-Knabner I (2019) Organic matter input determines structure development and aggregate formation in artificial soils. Geoderma 354: 113881. https://doi.org/10.1016/j.geoderma.2019.113881\u003c/li\u003e\n\u003cli\u003eBucka FB, Felde VJMNL, Peth S, K\u0026ouml;gel-Knabner I (2021) Disentangling the effects of OM quality and soil texture on microbially mediated structure formation in artificial model soils. Geoderma 403: 115213. https://doi.org/10.1016/j.geoderma.2021.115213\u003c/li\u003e\n\u003cli\u003eChen X, Chen HYH, Chen C, Ma Z, Searle EB, Yu Z, Huang Z (2020) Effects of plant diversity on soil carbon in diverse ecosystems: a global meta-analysis. Biol Rev 95: 167-183. https://doi.org/10.1111/brv.12554\u003c/li\u003e\n\u003cli\u003eChimento C, Amaducci S (2015) Characterization of fine root system and potential contribution to soil organic carbon of six perennial bioenergy crops. Biomass Bioenergy 83: 116-122. https://doi.org/10.1016/j.biombioe.2015.09.008\u003c/li\u003e\n\u003cli\u003eCurtasu MV, N\u0026oslash;rskov NP (2024) Quantitative distribution of flavan-3-ols, procyanidins, flavonols, flavanone and salicylic acid in five varieties of organic winter dormant \u003cem\u003eSalix\u003c/em\u003e spp. by LC-MS/MS. Heliyon 10: e25129. https://doi.org/10.1016/j.heliyon.2024.e25129\u003c/li\u003e\n\u003cli\u003eDerenne S, Qu\u0026eacute;n\u0026eacute;a K (2015) Analytical pyrolysis as a tool to probe soil organic matter. J Anal Appl Pyrolysis 111: 108-120. https://doi.org/10.1016/j.jaap.2014.12.001\u003c/li\u003e\n\u003cli\u003eDignac MF, Houot S, Francou C, Derenne S (2005) Pyrolytic study of compost and waste organic matter. Org Geochem 36: 1054-1071. https://doi.org/10.1016/j.orggeochem.2005.02.007\u003c/li\u003e\n\u003cli\u003eDignac M-F, Pechot N, Thevenot M, Lapierre C, Bahri H, Bardoux G, Rumpel C (2009) Isolation of soil lignins by combination of ball-milling and cellulolysis: evaluation of purity and isolation efficiency with pyrolysis/GC/MS. J Anal Appl Pyrolysis 85: 426-430. https://doi.org/10.1016/j.jaap.2008.10.012\u003c/li\u003e\n\u003cli\u003eDon A, Seidel F, Leifeld J, K\u0026auml;tterer T, Martin M, Pellerin S, Emde D, Seitz D, Chenu C (2024) Carbon sequestration in soils and climate change mitigation\u0026mdash;definitions and pitfalls. Glob Chang Biol 30: e16983. https://doi.org/10.1111/gcb.16983\u003c/li\u003e\n\u003cli\u003eEl Hayany B, El Fels L, Dignac M-F, Quenea K, Rumpel C, Hafidi M (2021) Pyrolysis-GCMS as a tool for maturity evaluation of compost from sewage sludge and green waste. Waste Biomass Valorization 12: 2639-2652. https://doi.org/10.1007/s12649-020-01184-1\u003c/li\u003e\n\u003cli\u003eFissore C, Dalzell BJ, Berhe AA, Voegtle M, Evans M, Wu A (2017) Influence of topography on soil organic carbon dynamics in a Southern California grassland. CATENA 149: 140-149. https://doi.org/10.1016/j.catena.2016.09.016\u003c/li\u003e\n\u003cli\u003eFogelqvist J, Verkhozina AV, Katyshev AI, Pucholt P, Dixelius C, R\u0026ouml;nnberg-W\u0026auml;stljung AC, Lascoux M, Berlin S (2015) Genetic and morphological evidence for introgression between three species of willows. BMC Evol Biol 15: 193. https://doi.org/10.1186/s12862-015-0461-7\u003c/li\u003e\n\u003cli\u003eGames PA, Howell JF (1976) Pairwise multiple comparison procedures with unequal n\u0026rsquo;s and/or variances: a Monte Carlo study. J Educ Stat 1: 113-125. https://doi.org/10.3102/10769986001002113\u003c/li\u003e\n\u003cli\u003eGuillou FL, Wetterlind W, Viscarra Rossel RA, Hicks W, Grundy M, Tuomi S (2015) How does grinding affect the mid-infrared spectra of soil and their multivariate calibrations to texture and organic carbon? Soil Res 53: 913-921. https://doi.org/10.1071/SR15019\u003c/li\u003e\n\u003cli\u003eGuo LB, Gifford RM (2002) Soil carbon stocks and land use change: a meta analysis. Glob Chang Biol 8: 345-360. https://doi.org/10.1046/j.1354-1013.2002.00486.x\u003c/li\u003e\n\u003cli\u003eHall SJ, Huang W, Timokhin VI, Hammel, Kenneth E. (2020a) Lignin lags, leads, or limits the decomposition of litter and soil organic carbon. Ecology 101: e03113. https://doi.org/10.1002/ecy.3113\u003c/li\u003e\n\u003cli\u003eHall SJ, Ye C, Weintraub SR, Hockaday WC (2020b) Molecular trade-offs in soil organic carbon composition at continental scale. Nat Geosci 13: 687-692. https://doi.org/10.1038/s41561-020-0634-x\u003c/li\u003e\n\u003cli\u003eHe L-X, Jia Z-Q, Li Q-X, Feng L-L, Yang K-Y (2019) Fine-root decomposition characteristics of four typical shrubs in sandy areas of an arid and semiarid alpine region in western China. Ecol Evol 9: 5407-5419. https://doi.org/10.1002/ece3.5133\u003c/li\u003e\n\u003cli\u003eHeinsoo K, Merilo E, Petrovits M, Koppel A (2009) Fine root biomass and production in a \u003cem\u003eSalix\u003c/em\u003e \u003cem\u003eviminalis\u003c/em\u003e and \u003cem\u003eSalix\u003c/em\u003e \u003cem\u003edasyclados\u003c/em\u003e plantation. Estonian J Ecol 58: 27-37. https://doi.org/10.3176/eco.2009.1.03\u003c/li\u003e\n\u003cli\u003eHicks Pries CE, Lankau R, Ingham GA, Legge E, Krol O, Forrester J, Fitch A, Wurzburger N (2023) Differences in soil organic matter between EcM- and AM-dominated forests depend on tree and fungal identity. Ecology 104: e3929. https://doi.org/10.1002/ecy.3929\u003c/li\u003e\n\u003cli\u003eHirte J, Leifeld J, Abiven S, Oberholzer H-R, Mayer J (2018) Below ground carbon inputs to soil via root biomass and rhizodeposition of field-grown maize and wheat at harvest are independent of net primary productivity. Agric Ecosyst Environ 265: 556-566. https://doi.org/10.1016/j.agee.2018.07.010\u003c/li\u003e\n\u003cli\u003eHoeber S, Fransson P, Prieto-Ruiz I, Manzoni S, Weih M (2017) Two \u003cem\u003eSalix\u003c/em\u003e genotypes differ in productivity and nitrogen economy when grown in monoculture and mixture. Front Plant Sci 8. https://doi.org/10.3389/fpls.2017.00231\u003c/li\u003e\n\u003cli\u003eHoeber S, Fransson P, Weih, M, Manzoni S (2020) Leaf litter quality coupled to \u003cem\u003eSalix\u003c/em\u003e variety drives litter decomposition more than stand diversity or climate. Plant Soil 453: 313-328. https://doi.org/10.1007/s11104-020-04606-0\u003c/li\u003e\n\u003cli\u003eHoeber S, Baum C, Weih M, Manzoni S, Fransson P (2021) Site-dependent relationships between fungal community composition, plant genotypic dDiversity and environmental drivers in a \u003cem\u003eSalix\u003c/em\u003e biomass system. Front Fungal Biol 2. https://doi.org/10.3389/ffunb.2021.671270\u003c/li\u003e\n\u003cli\u003eHrynkiewicz K, Toljander YK, Baum C, Fransson PMA, Taylor AFS, Weih M (2012) Correspondence of ectomycorrhizal diversity and colonisation of willows (\u003cem\u003eSalix\u003c/em\u003e spp.) grown in short rotation coppice on arable sites and adjacent natural stands. Mycorrhiza 22: 603-613. https://doi.org/10.1007/s00572-012-0437-z\u003c/li\u003e\n\u003cli\u003eHuang Y, Chen Y, Castro-Izaguirre N, Baruffol M, Brezzi M, Lang A, Li Y, H\u0026auml;rdtle W, von Oheimb G, Yang X, Liu X, Pei K, Both S, Yang B, Eichenberg D, Assmann T, Bauhus J, Behrens T, Buscot F, Chen X-Y, Chesters D, Ding B-Y, Durka W, Erfmeier A, Fang J, Fischer M, Guo L-D, Guo D, Gutknecht JLM, He J-S, He C-L, Hector A, H\u0026ouml;nig L, Hu R-Y, Klein A-M, K\u0026uuml;hn P, Liang Y, Li S, Michalski S, Scherer-Lorenzen M, Schmidt K, Scholten T, Schuldt A, Shi X, Tan M-Z, Tang Z, Trogisch S, Wang Z, Welk E, Wirth C, Wubet T, Xiang W, Yu M, Yu X-D, Zhang J, Zhang S, Zhang N, Zhou H-Z, Zhu C-D, Zhu L, Bruelheide H, Ma K, Niklaus PA, Schmid B (2018) Impacts of species richness on productivity in a large-scale subtropical forest experiment. Science 362: 80-83. https://doi.org/10.1126/science.aat6405\u003c/li\u003e\n\u003cli\u003eHulvey KB, Hobbs RJ, Standish RJ, Lindenmayer DB, Lach L, Perring MP (2013) Benefits of tree mixes in carbon plantings. Nat Clim Change 3: 869-874. https://doi.org/10.1038/nclimate1862\u003c/li\u003e\n\u003cli\u003eHungate BA, Barbier EB, Ando AW, Marks SP, Reich PB, van Gestel N, Tilman D, Knops JMH, Hooper DU, Butterfield BJ, Cardinale BJ (2017) The economic value of grassland species for carbon storage. Sci Adv 3: e1601880. https://doi.org/10.1126/sciadv.1601880\u003c/li\u003e\n\u003cli\u003eHuuskonen S, Domisch T, Fin\u0026eacute;r L, Hantula J, Hynynen J, Matala J, Miina J, Neuvonen S, Nevalainen S, Niemist\u0026ouml; P, Nikula A , Piri T, Siitonen J, Smolander A, Tonteri T, Uotila K, Viiri H (2021) What is the potential for replacing monocultures with mixed-species stands to enhance ecosystem services in boreal forests in Fennoscandia? For Ecol Manage 479: 118558. https://doi.org/10.1016/j.foreco.2020.118558\u003c/li\u003e\n\u003cli\u003eJandl R, Rodeghiero M, Martinez C, Cotrufo MF, Bampa F, van Wesemael B, Harrison RB, Guerrini IA, Richter Dd, Rustad L, Lorenz K, Chabbi A, Miglietta F (2014) Current status, uncertainty and future needs in soil organic carbon monitoring. Sci Total Environ 468-469: 376-383. https://doi.org/10.1016/j.scitotenv.2013.08.026\u003c/li\u003e\n\u003cli\u003eJost L (2007) Partitioning diversity into independent alpha and beta components. Ecology 88: 2427-2439. https://doi.org/10.1890/06-1736.1\u003c/li\u003e\n\u003cli\u003eJ\u0026ouml;rgensen K, Granath G, Strengbom J, Lindahl BD (2022) Links between boreal forest management, soil fungal communities and below-ground carbon sequestration. Funct Ecol 36: 392-405. https://doi.org/10.1111/1365-2435.13985\u003c/li\u003e\n\u003cli\u003eKalita S, Potter HK, Weih M, Baum C, Nordberg \u0026Aring;, Hansson P-A (2021) Soil carbon modelling in \u003cem\u003eSalix\u003c/em\u003e biomass plantations: variety determines carbon sequestration and climate impacts. Forests 12: 1529. https://doi.org/10.3390/f12111529\u003c/li\u003e\n\u003cli\u003eKalita S, Ohlsson JA, Karlsson Potter H, Nordberg \u0026Aring;, Sandgren M, Hansson P-A (2023) Energy performance of compressed biomethane gas production from co-digestion of \u003cem\u003eSalix\u003c/em\u003e and dairy manure: factoring differences between \u003cem\u003eSalix\u003c/em\u003e varieties. Biotech Biofuels Bioprod 16: 165. https://doi.org/10.1186/s13068-023-02412-1\u003c/li\u003e\n\u003cli\u003eKallenbach CM, Frey SD, Grandy AS (2016) Direct evidence for microbial-derived soil organic matter formation and its ecophysiological controls. Nat Commun 7: 13630. https://doi.org/10.1038/ncomms13630\u003c/li\u003e\n\u003cli\u003eKassambara A (2021) rstatix: Pipe-friendly framework for basic statistical tests. R package. https://CRAN.R-project.org/package=rstatix\u003c/li\u003e\n\u003cli\u003eKellner H, Luis P, Pecyna MJ, Barbi F, Kapturska D, Kr\u0026uuml;ger D, Zak DR, Marmeisse R, Vandenbol M, Hofrichter M (2014) Widespread occurrence of expressed fungal secretory peroxidases in forest soils. PLoS One 9: e95557. https://doi.org/10.1371/journal.pone.0095557\u003c/li\u003e\n\u003cli\u003eKoczorski P, Furtado BU, Gołębiewski M, Hulisz P, Baum C, Weih M, Hrynkiewicz K (2021) The effects of host plant genotype and environmental conditions on fungal community composition and phosphorus solubilization in willow short rotation coppice. Front Plant Sci 12. https://doi.org/10.3389/fpls.2021.647709\u003c/li\u003e\n\u003cli\u003eKoga N, Shimoda S, Shirato Y, Kusaba T, Shima T, Niimi H, Yamane T, Wakabayashi K, Niwa K, Kohyama K, Obara H, Takata Y, Kanda T, Inoue H, Ishizuka S, Kaneko S, Tsuruta K, Hashimoto S, Shinomiya Y, Aizawa S, Ito E, Hashimoto T, Morishita T, Noguchi K, Ono K, Katayanagi N, Atsumi K (2020) Assessing changes in soil carbon stocks after land use conversion from forest land to agricultural land in Japan. Geoderma 377: 114487. https://doi.org/10.1016/j.geoderma.2020.114487\u003c/li\u003e\n\u003cli\u003eK\u0026ouml;gel-Knabner I (2017) The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter: fourteen years on. Soil Biol Biochem 105: A3-A8. https://doi.org/10.1016/j.soilbio.2016.08.011\u003c/li\u003e\n\u003cli\u003eKopp EB, Niklaus PA, Wuest SE (2023) Ecological principles to guide the development of crop variety mixtures. J Plant Ecol 16. https://doi.org/10.1093/jpe/rtad017\u003c/li\u003e\n\u003cli\u003eKorenblum E, Massalha H, Aharoni A (2022) Plant\u0026ndash;microbe interactions in the rhizosphere via a circular metabolic economy. Plant Cell 34: 3168-3182. https://doi.org/10.1093/plcell/koac163\u003c/li\u003e\n\u003cli\u003eKuyper J, Schroeder H, Linn\u0026eacute;r B-O (2018) The evolution of the UNFCCC. Annu Rev Environ Resour 43: 343-368. https://doi.org/10.1146/annurev-environ-102017-030119\u003c/li\u003e\n\u003cli\u003eLagkouvardos I, Fischer S, Kumar N, Clavel T (2017) Rhea: a transparent and modular R pipeline for microbial profiling based on 16S rRNA gene amplicons. PeerJ 5: e2836. https://doi.org/10.7717/peerj.2836\u003c/li\u003e\n\u003cli\u003eLange M, Eisenhauer N, Sierra CA, Bessler H, Engels C, Griffiths RI, Mellado-V\u0026aacute;zquez PG, Malik AA, Roy J, Scheu S, Steinbeiss S, Thomson BC, Trumbore SE, Gleixner G (2015) Plant diversity increases soil microbial activity and soil carbon storage. Nat Commun 6: 6707. https://doi.org/10.1038/ncomms7707\u003c/li\u003e\n\u003cli\u003eLangley JA, Chapman SK, Hungate BA (2006) Ectomycorrhizal colonization slows root decomposition: the post-mortem fungal legacy. Ecol Lett 9: 955-959. https://doi.org/10.1111/j.1461-0248.2006.00948.x\u003c/li\u003e\n\u003cli\u003eLehmann J, Hansel CM, Kaiser C, Kleber M, Maher K, Manzoni S, Nunan N, Reichstein M, Schimel JP, Torn MS, Wieder WR, K\u0026ouml;gel-Knabner I (2020) Persistence of soil organic carbon caused by functional complexity. Nat Geosci 13: 529-534. https://doi.org/10.1038/s41561-020-0612-3\u003c/li\u003e\n\u003cli\u003eLejay M, Alexis M, Qu\u0026eacute;n\u0026eacute;a K, Sellami F, Bon F (2016) Organic signatures of fireplaces: experimental references for archaeological interpretations. Org Geochem 99: 67-77. https://doi.org/10.1016/j.orggeochem.2016.06.002\u003c/li\u003e\n\u003cli\u003eLejay M, Alexis MA, Qu\u0026eacute;n\u0026eacute;a K, Anquetil C, Bon F (2019) The organic signature of an experimental meat-cooking fireplace: the identification of nitrogen compounds and their archaeological potential. Org Geochem 138: 103923. https://doi.org/10.1016/j.orggeochem.2019.103923\u003c/li\u003e\n\u003cli\u003eLindahl BD, Kyaschenko J, Varenius K, Clemmensen KE, Dahlberg A, Karltun E, Stendahl J (2021) A group of ectomycorrhizal fungi restricts organic matter accumulation in boreal forest. Ecol Lett 24: 1341-1351. https://doi.org/10.1111/ele.13746\u003c/li\u003e\n\u003cli\u003evon L\u0026uuml;tzow M, K\u0026ouml;gel-Knabner I, Ekschmitt K, Matzner E, Guggenberger G, Marschner B, Flessa H (2006) Stabilization of organic matter in temperate soils: mechanisms and their relevance under different soil conditions \u0026ndash; a review. Eur J Soil Sci 57: 426-445. https://doi.org/10.1111/j.1365-2389.2006.00809.x\u003c/li\u003e\n\u003cli\u003eMainka M, Summerauer L, Wasner D, Garland G, Griepentrog M, Berhe AA, Doetterl S (2022) Soil geochemistry as a driver of soil organic matter composition: insights from a soil chronosequence. Biogeosciences 19: 1675-1689. https://doi.org/10.5194/bg-19-1675-2022\u003c/li\u003e\n\u003cli\u003eMartani E, Ferrarini A, Serra P, Pilla M, Marcone A, Amaducci S (2021) Belowground biomass C outweighs soil organic C of perennial energy crops: insights from a long-term multispecies trial. Glob Chang Biol Bioenergy 13: 459-472. https://doi.org/10.1111/gcbb.12785\u003c/li\u003e\n\u003cli\u003ede Mendiburu F (2023) agricolae: Statistical procedures for agricultural research. R Package. https://CRAN.R-project.org/package=agricolae\u003c/li\u003e\n\u003cli\u003eMoore VM, Peters T, Schlautman B, Brummer EC (2023) Toward plant breeding for multicrop systems. Proc Natl Acad Sci USA 120: e2205792119. https://doi.org/10.1073/pnas.2205792119\u003c/li\u003e\n\u003cli\u003eMorais CLM, Lima KMG, Singh M, Martin FL (2020) Tutorial: multivariate classification for vibrational spectroscopy in biological samples. Nat Protoc 15: 2143-2162. https://doi.org/10.1038/s41596-020-0322-8\u003c/li\u003e\n\u003cli\u003eOgle DH, Doll JC, Wheeler P, Dinno A (2022) FSA: fisheries stock analysis. R package. https://github.com/fishR-Core-Team/FSA\u003c/li\u003e\n\u003cli\u003eOksanen J, Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., Minchin, P.R., O\u0026rsquo;hara, R.B., Simpson, G.L., Solymos, P., Stevens, M.H.H., Szoecs, E. (2020) vegan: Community ecology package. R package. https://CRAN.R-project.org/package=vegan\u003c/li\u003e\n\u003cli\u003ePanagos P, Montanarella L, Barbero M, Schneegans A, Aguglia L, Jones A (2022) Soil priorities in the European Union. Geoderma Reg 29: e00510. https://doi.org/10.1016/j.geodrs.2022.e00510\u003c/li\u003e\n\u003cli\u003eP\u0026eacute;rez-Izquierdo L, Saint-Andr\u0026eacute; L, Santenoise P, Bu\u0026eacute;e M, Rinc\u0026oacute;n A (2018) Tree genotype and seasonal effects on soil properties and biogeochemical functioning in Mediterranean pine forests. Eur J Soil Sci 69: 1087-1097. https://doi.org/10.1111/ejss.12712\u003c/li\u003e\n\u003cli\u003ePoeplau C, Prietz R, Don A (2022) Plot-scale variability of organic carbon in temperate agricultural soils\u0026mdash;Implications for soil monitoring. J Plant Nutr Soil Sci 185: 403-416. https://doi.org/10.1002/jpln.202100393\u003c/li\u003e\n\u003cli\u003ePoffenbarger H, Castellano M, Egli D, Jaconi A, Moore V (2023) Contributions of plant breeding to soil carbon storage: Retrospect and prospects. Crop Sci 63: 990-1018. https://doi.org/10.1002/csc2.20920\u003c/li\u003e\n\u003cli\u003ePouwels AD, Tom A, Eijkel GB, Boon JJ (1987) Characterisation of beech wood and its holocellulose and xylan fractions by pyrolysis-gas chromatography-mass spectrometry. J Anal Appl Pyrolysis 11: 417-436. https://doi.org/10.1016/0165-2370(87)85045-3\u003c/li\u003e\n\u003cli\u003ePrommer J, Walker TWN, Wanek W, Braun J, Zezula D, Hu Y, Hofhansl F, Richter A (2020) Increased microbial growth, biomass, and turnover drive soil organic carbon accumulation at higher plant diversity. Glob Chang Biol 26: 669-681. https://doi.org/10.1111/gcb.14777\u003c/li\u003e\n\u003cli\u003eP\u0026uuml;ttsepp \u0026Uuml;, Rosling A, Taylor AFS (2004) Ectomycorrhizal fungal communities associated with \u003cem\u003eSalix\u003c/em\u003e \u003cem\u003eviminalis L.\u003c/em\u003e and \u003cem\u003eS. dasyclados Wimm.\u003c/em\u003e clones in a short-rotation forestry plantation. For Ecol Manage 196: 413-424. https://doi.org/10.1016/j.foreco.2004.04.003\u003c/li\u003e\n\u003cli\u003eRam\u0026iacute;rez PB, Calder\u0026oacute;n FJ, Haddix M, Lugato E, Cotrufo MF (2021) Using diffuse reflectance spectroscopy as a high throughput method for quantifying soil C and N and their distribution in particulate and mineral-associated organic matter fractions. Front Environ Sci 9. https://doi.org/10.3389/fenvs.2021.634472\u003c/li\u003e\n\u003cli\u003eR\u0026ouml;nnberg-W\u0026auml;stljung AC, Dufour L, Gao J, Hansson P-A, Herrmann A, Jebrane M, Johansson A-C, Kalita S, Molinder R, Nordh N-E, Ohlsson JA, Passoth V, Sandgren M, Schn\u0026uuml;rer A, Shi A, Terziev N, Daniel G, Weih M (2022) Optimized utilization of \u003cem\u003eSalix\u003c/em\u003e\u0026mdash;perspectives for the genetic improvement toward sustainable biofuel value chains. Glob Chang Biol Bioenergy 14: 1128-1144. https://doi.org/10.1111/gcbb.12991\u003c/li\u003e\n\u003cli\u003eRumpel C, Amiraslani F, Bossio D, Chenu C, Henry B, Espinoza AF, Koutika L-S, Ladha J, Madari B, Minasny B, Olaleye AO, Shirato Y, Sall SN, Soussana J-F, Varela-Ortega C (2022) The role of soil carbon sequestration in enhancing human resilience in tackling global crises including pandemics. Soil Security 8: 100069. https://doi.org/10.1016/j.soisec.2022.100069\u003c/li\u003e\n\u003cli\u003eRyals R, Kaiser M, Torn MS, Berhe AA, Silver WL (2014) Impacts of organic matter amendments on carbon and nitrogen dynamics in grassland soils. Soil Biol Biochem 68: 52-61. https://doi.org/10.1016/j.soilbio.2013.09.011\u003c/li\u003e\n\u003cli\u003eSavitzky A, Golay MJE (1964) Smoothing and differentiation of data by simplified least squares procedures. Anal Chem 36: 1627-1639. https://doi.org/10.1021/ac60214a047\u003c/li\u003e\n\u003cli\u003eSeitz VA, McGivern BB, Daly RA, Chaparro JM, Borton MA, Sheflin AM, Kresovich S, Shields L, Schipanski ME, Wrighton KC, Prenni JE (2022) Variation in root exudate composition influences soil microbiome membership and function. Appl Environ Microbiol 88: e00226-00222. https://doi.org/10.1128/aem.00226-22\u003c/li\u003e\n\u003cli\u003eSemchenko M, Xue P, Leigh T (2021) Functional diversity and identity of plant genotypes regulate rhizodeposition and soil microbial activity. New Phytol 232: 776-787. https://doi.org/10.1111/nph.17604\u003c/li\u003e\n\u003cli\u003eSmith WH (1969) Release of organic materials from the roots of tree seedlings. For Sci 15: 138-143. https://doi.org/10.1093/forestscience/15.2.138\u003c/li\u003e\n\u003cli\u003eStevens A, Ramirez-Lopez L (2015) prospectr: Miscellaneous functions for processing and sample selection of spectroscopic data. R package. https://CRAN.R-project.org/package=prospectr\u003c/li\u003e\n\u003cli\u003eStewart K, Passey T, Verheecke-Vaessen C, Kevei Z, Xu X (2023) Is it feasible to use mixed orchards to manage apple scab? Fruit Res 3. https://doi.org/10.48130/FruRes-2023-0028\u003c/li\u003e\n\u003cli\u003eSun L, Kominami Y, Yoshimura K, Kitayama K (2017) Root-exudate flux variations among four co-existing canopy species in a temperate forest, Japan. Ecol Res 32: 331-339. https://doi.org/10.1007/s11284-017-1440-9\u003c/li\u003e\n\u003cli\u003eTemplier J, Derenne S, Crou\u0026eacute; J-P, Largeau C (2005) Comparative study of two fractions of riverine dissolved organic matter using various analytical pyrolytic methods and a \u003csup\u003e13\u003c/sup\u003eC CP/MAS NMR approach. Org Geochem 36: 1418-1442. https://doi.org/10.1016/j.orggeochem.2005.05.003\u003c/li\u003e\n\u003cli\u003eThioulouse J, Dray S, Dufour A, Siberchicot A, Jombart T, Pavoine S (2018) Multivariate analysis of ecological data with ade4. Springer, New York. https://doi.org/10.1007/978-1-4939-8850-1\u003c/li\u003e\n\u003cli\u003eVidal A, Quenea K, Alexis M, Derenne S (2016) Molecular fate of root and shoot litter on incorporation and decomposition in earthworm casts. Org Geochem 101: 1-10. https://doi.org/10.1016/j.orggeochem.2016.08.003\u003c/li\u003e\n\u003cli\u003eWang Y, Wang S, Liu C, Zhu E, Jia J, Feng X (2023) Shifting relationships between SOC and molecular diversity in soils of varied carbon concentrations: evidence from drained wetlands. Geoderma 433: 116459. https://doi.org/10.1016/j.geoderma.2023.116459\u003c/li\u003e\n\u003cli\u003eWarembourg FR, Estelrich HD (2001) Plant phenology and soil fertility effects on below-ground carbon allocation for an annual (\u003cem\u003eBromus madritensis\u003c/em\u003e) and a perennial (\u003cem\u003eBromus erectus\u003c/em\u003e) grass species. Soil Biol Biochem 33: 1291-1303. https://doi.org/10.1016/S0038-0717(01)00033-5\u003c/li\u003e\n\u003cli\u003eWeih M (2013) Willow. In: Singh BP (ed) Biofuel crops: production, physiology and genetics. CABI. 415\u0026ndash;426. https://doi.org/10.1079/9781845938857.0415\u003c/li\u003e\n\u003cli\u003eWeih M, Nordh N-E (2002) Characterising willows for biomass and phytoremediation: growth, nitrogen and water use of 14 willow clones under different irrigation and fertilisation regimes. Biomass Bioenergy 23: 397-413. https://doi.org/10.1016/S0961-9534(02)00067-3\u003c/li\u003e\n\u003cli\u003eWeih M, Nordh N-E (2005) Determinants of biomass production in hybrid willows and prediction of field performance from pot studies. Tree Physiol 25: 1197-1206. https://doi.org/10.1093/treephys/25.9.1197\u003c/li\u003e\n\u003cli\u003eWeih M, Hoeber S, Beyer F, Fransson P (2014) Traits to ecosystems: the ecological sustainability challenge when developing future energy crops. Front Energy Res 2. https://doi.org/10.3389/fenrg.2014.00017\u003c/li\u003e\n\u003cli\u003eWeih M, Glynn C, Baum C (2019) Willow short-rotation coppice as model system for exploring ecological theory on biodiversity\u0026ndash;ecosystem function. Diversity 11: 125. https://doi.org/10.3390/d11080125\u003c/li\u003e\n\u003cli\u003eWickham H, Averick M, Bryan J, Chang W, D\u0026rsquo;Agostino McGowan L, Fran\u0026ccedil;ois R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller M, Bache SM, M\u0026uuml;ller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019) Welcome to the Tidyverse. J Open Source Softw 4: 1686. https://doi.org/10.21105/joss.01686\u003c/li\u003e\n\u003cli\u003eWiesenbauer J, K\u0026ouml;nig A, Gorka S, Marchand L, Nunan N, Kitzler B, Inselsbacher E, Kaiser C (2024) A pulse of simulated root exudation alters the composition and temporal dynamics of microbial metabolites in its immediate vicinity. Soil Biol Biochem 189: 109259. https://doi.org/10.1016/j.soilbio.2023.109259\u003c/li\u003e\n\u003cli\u003eYergeau E, Sanschagrin S, Maynard C, St-Arnaud M, Greer CW (2013) Microbial expression profiles in the rhizosphere of willows depend on soil contamination. ISME J 8: 344-358. https://doi.org/10.1038/ismej.2013.163\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"soil organic matter composition, molecular diversity, mid-IR spectroscopy, pyrolysis GC/MS, plant varieties, Salix","lastPublishedDoi":"10.21203/rs.3.rs-4214790/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4214790/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground and aims\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMost studies of the relationships between the composition of soil organic matter and plant cover have been carried out at the plant genera level. Yet, they have largely overlooked the potential effects that plant varieties belonging to the same genus can have on soil organic matter.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated whether plant varieties belonging to different \u003cem\u003eSalix \u003c/em\u003especies (\u003cem\u003eS. dasyclados\u003c/em\u003e and \u003cem\u003eS. viminalis)\u003c/em\u003e impacted the composition of organic matter using mid-infrared spectroscopy and pyrolysis GC/MS. Top-soils (0-20 cm) were taken from an 18 year-old long-term field trial where six \u003cem\u003eSalix\u003c/em\u003e varieties were grown as short-rotation coppice under two fertilisation regimes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSignificant differences in the molecular composition and diversity of the soil organic matter were observed in the fertilised plots. The effects were mostly visible at the species level, i.e. between varieties from \u003cem\u003eS. dasyclados\u003c/em\u003eand \u003cem\u003eS. viminalis\u003c/em\u003e, though smaller differences among varieties from the same species were also observed.\u003c/p\u003e\n\u003cp\u003eNo significant effects of \u003cem\u003eSalix\u003c/em\u003evarieties were observed in the unfertilised plots, possibly due to the relatively high degree of spatial variability in several soil properties (pH, total N and total organic C contents).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study provides evidence that the taxonomic distance, at the species level, among \u003cem\u003eSalix\u003c/em\u003e plant varieties can affect the molecular composition and diversity of soil organic matter. Such an effect should be considered in breeding programmes for managing soil organic C, as it is one of the potential driver of organic C persistence in soils.\u003c/p\u003e","manuscriptTitle":"Salix species and varieties affect the molecular composition and diversity of soil organic matter","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-12 08:28:44","doi":"10.21203/rs.3.rs-4214790/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2024-04-29T04:24:48+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-04-10T00:34:28+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-09T06:42:26+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Plant and Soil","date":"2024-04-04T09:14:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-04T09:12:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Plant and Soil","date":"2024-04-03T17:08:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"plant-and-soil","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"plso","sideBox":"Learn more about [Plant and Soil](https://www.springer.com/journal/11104)","snPcode":"11104","submissionUrl":"https://submission.nature.com/new-submission/11104/3","title":"Plant and Soil","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f9195239-d320-4cfd-bd4b-d76dbb896739","owner":[],"postedDate":"April 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-06-25T23:32:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-12 08:28:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4214790","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4214790","identity":"rs-4214790","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}