Tree Species Identity Drives Soil Carbon and Nitrogen Stocks in Nutrient-Poor Sites

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We examined the effect of admixture of conifers to beech forests on C stock. Methods We analyzed groups of European beech ( Fagus sylvatica ), Douglas fir ( Pseudotsuga menziesii ) and Norway spruce ( Picea abies ) stands as well as mixtures of beech with either Douglas fir or spruce under loamy versus sandy soils. We examined the stocks of C in the organic layer and upper mineral soil. Results The C stock of the organic layer was largely depending on tree species, whereas the C stock of the mineral soil varied among soil types. Total soil organic C stocks showed significant species identities and mixing effects were most obvious due to the high SOC stocks in the organic layer. Overall, under sandy soil conditions, conifers and mixed forests allocated 10% more SOC and N at the organic layer compared to loamy soils, whereas the SOC and N stocks under beech maintained the same proportion, independent of the site condition. The interaction between species and sites was significant only for Douglas Fir and mixed Douglas Fir/beech, indicating that the effect of species on C and N varied across sites, being significantly high at sandy soils. Conclusion The higher potential for carbon and N storage in mixed-species forests compared to pure stands emphasizes the capacity of mixed forest to provide valuable ecosystem services, enhancing C sequestration. mixed forests broadleaves conifers Fagus sylvatica Pseudotsuga menziesii Picea abies SOC Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Forest soils are complex ecosystems and their proper management, especially through the selection of trees with distinct species identities, may have a major impact on soil organic carbon (SOC) stocks and nitrogen (N) dynamics, leading to C sequestration potentials (Jandl et al., 2007; Vesterdal et al., 2008 ), as well as reducing N leaching. Typical driving forces of such tree species identities include the type of foliage, the quality of leaf litter, indicated e.g. by the C/N ratio, or the type of rooting characteristic in forest soils. Thus, tree species identity may have an important impact on the ecosystem level such as soil C stock and C/N ratios, particularly in the O-horizon and top mineral soil layers (Dawud et al., 2017 ; Vesterdal et al., 2013 ). Furthermore, the species diversity drives the fluxes of carbon and nitrogen in soils (Cepáková et al., 2016 ; Mueller et al., 2012 ; Vesterdal et al., 2002) and their role on SOC sequestration are been highlighted to improve the ecosystem functions as carbon sequestration. Different patterns of C storage in soil profile and organic horizons has been reported for conifers and deciduous trees on temperate ecosystems (Bolte and Villanueva, 2006 ). However, it is highly uncertain which processes are responsible for differences in soil C stocks in organic horizon and mineral soil. Differences in litter input (Díaz-Pinés et al., 2011), root distribution (Oulehle et al., 2007 ) as well as decomposition rates (Cools et al., 2014) have been suggested as the most likely explanation for tree species influence on soil C stocks. Often, Douglas fir ( Pseudotsuga menziesii menziesii ) and European beech ( Fagus sylvatica ) show high fine root density in deeper soil layers (Bolte and Villanueva, 2006 ; Oulehle et al., 2007 ) and thus increasing C allocation in mineral soil layers. In contrast, the native conifer Norway spruce ( Picea abies ), known as shallow-rooted tree species (Bolte and Villanueva, 2006 ) accumulates C preferentially in the upper mineral soil layers. Compositionally and structurally diverse forests represent an important element of approaches to deliver a wide range of ecosystem goods and services like carbon sequestration (Ammer, et al., 2020 ). Moreover, the establishment and management of mixed stands is also discussed as an effective measure to adapt forests stands to climate change (Berg and McClaugherty, 2020 ; Frouz et al., 2009 ). However, it has already been shown, that the admixtures of conifer (either with Douglas fir or Norway spruce) to beech forests modified the soil C and N input through the fine root distribution in the soil profile (Vesterdal and Raulund-Rasmussen, 1998 ). Additionally, the enhanced nutrient concentrations of beech litter increase litter decomposition of conifers needles (Krishna and Mohan, 2017 ; Neumann et al., 2018; Vesterdal et al., 2008 ), followed by less C accumulation in the organic soil layers and shift to potential stable C pools in mineral soil. However, still inconsistent information exist, on how mixed stands of beech with Douglas-fir would affect forest soil C and N vertical distribution. Due to the differences in litter input (Díaz-Pinés et al., 2011) as well as decomposition rates (Cools et al., 2014) its most likely that this mixture enhance the organic C stocks in the organic layers as well. Thus, the deep root system reported to Douglas fir and beech and the high SOC on organic layer might suggest that the admixture of Douglas fir into beech stands potentially results in higher total C in the whole soil profile. Therefore, the main objective of our study was to analyze the accumulation, vertical distribution as well as litter quality indices (C/N ratios) of the upper mineral C and N stocks of different pure and mixed stand types (pure European beech, pure Norway spruce, pure Douglas-fir, mixed European beech/Norway spruce and mixed European beech/Douglas-fir) along Northern Germany under distinct soil characteristics (loamy versus sandy soil conditions). We hypothesized that i) the admixture of Douglas fir to beech forests will increase C stocks at the mineral soil compared to respectively beech monocultures, ii) the C stocks at litter layer will decrease under the admixture of Douglas fir to beech and, shift to rather stables C pools (H-layer and mineral soil), compared to respectively monocultures, and iii) on nutrient poor sites (sandy soils), species-identity effects on organic layer will be stronger pronunced than on rich soils (loamy soil). Material and Methods Study sites We investigated seven sites in Lower Saxony, northern Germany. Each site contained quintet neighboring forest stands. Three of these stands were monospecific stands of European beech ( Fagus sylvatica ), Norway spruce ( Picea abies ), or Douglas fir ( Pseudotsuga menziesii ). The other two were mixed stands, one composed of spruce/beech and one composed of Douglas fir/beech. Essential criteria for the selection of the sites were the presence of the respective quintets in a similar advanced silvicultural development status, altogether, we employed a multi-criteria approach, considering factors such as climate, soil type (based on German soil inventory), stand age, and existing research on land-use, as well as a relevant single tree admixture in the mixed stands. However, on the basis of the available forest site mapping and also confirmed by Foltran et al. ( 2023 ), two groups with relatively homogeneous site conditions were distinguished in our data set, in particular via the texture data (Table 1 ; Fig. S3), but also addressing the geological substrate classes, the correspondently developed soil types as well as the given range of water and nutrient levels (Foltran et al., 2023 ). In the first region in southern Lower Saxony, we chose three sites (Dassel, Winnefeld, and Nienover). These three sites are located in the hills of the Solling plateau and lie between 300 and 450 m.a.s.l. They share similar climatic conditions, i.e. a mean annual air temperature of 7.2°C and mean annual precipitation of about 1040 mm/year. The age ranges between 45 and 90 years and the texture is relatively rich (23% of clay; Table 1 ). The soils at these locations are Dystric Cambisols (FAO, 2015) developed from Triassic sandstone material, covered by loess. In the second region, located in the northern Lower Saxony, we selected four sites (Unterlüß, Nienburg, and Göhrde I and II). These sites are in lowland Lower Saxony and lie between 80 to 150 m.a.s.l. and all have similar climatic conditions, i.e., a mean annual air temperature of 8.4°C, mean annual precipitation of 720 mm/year. The age ranges between 53 and 130 years. Most frequent soil types are therefore Podzols (Table 1 ) and their transitional forms towards Cambisols, developed on geological formations from the last ice ages and mostly with a high sand content, compared to the southern region With respect to nutrients and according to the official Lower Saxony forest site mapping and Foltran et al. ( 2023 ), the southern sites (loamy soils) are nutrient-rich, and the northern sites (sandy soils) are nutrient-poor Soil sampling In each forest stand type (50 m x 50 m) at all sites, 4 randomly selected points were chosen as representative sampling points. The selected points were oriented at stand-level, e.g., we standardized two meters minimal distance from the trees to avoid coarse roots. At each sampling plot, the forest floor was collected using a steel frame and sorted by identifiable foliar (O L – Litter), non-foliar (O F – decay layer), and non-identifiable and humified (O H – Humus) layers of the organic layer. Mineral soil was sampled using a core auger ( d = 8 cm) and, separated at 0–5, 5–10, and 10–30 cm soil depth. Bulk soil density from each depth was calculated using soil metal rings (250 cm³) to further stock analysis. Partly missing bulk density data due to frozen soil conditions, interfering tree roots or stones during sampling were estimated by Adams equation (ADAMS, 1973) adapted by(CHEN et al., 2017). The approach uses SOM and pH as bulk density predictors. Sample preparation and analysis All mineral soil samples were oven-dried at 40°C until constant weight and sieved through 2 mm mesh, subsamples from the fine soil fractions (< 2 mm diameter) were ground with a Retsch mortar grinder RM 200 (Retsch, Germany) for 10 min. The organic layer samples were dried at 60°C until constant weight, weighted and ball milled (MM2, Fa Retsch) for further analysis. All the samples were analyzed for total C and N by dry combustion in a Leco CSN 2000 analyzer. There was no inorganic C (CaCO 3 ) within 30 cm depth in soils and all measured C were consequently considered to be organic. The pH measurements for all mineral soil samples were performed in KCl solution, more detailed descriptions can be found in the Foltran et al. ( 2023 ). Calculations of Stocks We estimated the soil bulk density from the oven-dried and moisture corrected (105 ◦C) fine soil mass and its volume. The fine soil volume was estimated from the difference between the volume of the soil corer and the volume of stones and roots. Carbon and N stocks in each layer were estimated from the organic horizon mass (O-layers) and soil bulk density (mineral soil), concentrations of C and N and depth of the individual soil depths for each sampling point. Statistical Analyses To address the non-independent nature of multiple horizons within one soil profile for this subset of data, we chose linear mixed effect models (Rasmussen et al., 2018). To estimate the effect of Species and Site Conditions (loamy vs sandy), we fitted linear mixed models (LMMs) to log-transformed response variables (C and N stocks) and then applied planned contrasts (Piovia-Scott et al., 2019). All LMMs included Species (European beech, Douglas fir, Douglas fir/beech, Norway spruce, spruce/beech), Site Conditions (loamy and sandy sites), and Soil Depths (O L , O F , O H [organic layers] and 0–5, 5–10 and 10–30 cm [mineral soil]) as fixed effects. Models were stepwise selected by likelihood ratio test, and minimal models included all main effects and the interaction of forest type and region. The mean values for each site are given in the supplementary material (Table S3 and S4). There, the effect of the forest stand (pure or mixed forest) on the soil chemical parameters for individual depth was assessed by least significant difference test. As the assumption of normal distribution was not met (tested for with Shapiro Wilk test), we used the Kruskal Wallis test, followed by pairwise Mann-Whitney tests with a correction factor for multiple pairwise testing, to identify statistically significant differences among Species and site conditions by individual depth. All analyses were done in R 4.0.3 (R Core Team, 2020). We used the ‘nlme’ package to fit LMMs and the ‘emmeans’ package for planned contrasts. All mixed models met the assumptions of normality of residuals and homogeneity of variance. Results Organic horizon mass and soil density No effects of Species and Site conditions on organic horizon masses (OHM) was observed. Instead, organic layer depth and the interaction Species and Depth and Species and Site condition were consistency significant affecting the organic layer masses. Furthermore, the associated LMM model revealed a statistical significance (p < 0.001; r²=0.397), indicating that approximately 40% of the variation in the response variable (OHM) could be explained by the model (Figure S2). The effect of Depth was significant, with O H having a positive effect (p < 0.001) on OHM, its interaction term Depth and Site condition shows that O H layer presents a negative effect at southern sites compared to the northern sites (p < 0.001), meaning that this layer impacted the OHM at the northern sites, but not in the southern sites. The interaction Species and Depth show that both mixed stands (Douglas fir/beech and spruce/beech) and O H layer have significant and positive effects on OHM, in another words, both mixtures stand increased the OHM accumulated in the O H layer. The mineral soil bulk density ranges from 0.8 to 1.4 g cm − 3 . The southern sites showed significant lower soil bulk density (p < 0.001) than northern sites, and Douglas fir and Douglas fir/beech showed significant lower bulk soil density (p < 0.001) compared to beech. A significant interaction among Species and S ite conditions was observed (Fig. 1 ), where Douglas fir and its mixture with beech (Douglas fir/beech) showed higher soil densities at loamy soils (Southern sites) than at sandy soils (Northern sites) (Table S1 ). Organic-horizon and mineral soil C and N concentrations We used a linear mixed model (LMM) to investigate the relationship between carbon (C) and nitrogen (N) concentrations and Species , Depth , and their interaction across the Sites (Northern and Southern sites). The results showed that Species have a significant effect on carbon concentration, as well as the depth. The highest C concentration was found in the O H layer and decreased with depth. Furthermore, the effect of depth varied across species, with higher carbon concentrations found in the top layer of the organic horizon for all species, except Douglas fir. In terms of the species effect, the C concentration was significantly higher under beech and mixed spruce/beech stands compared to conifers, Douglas fir and spruce. Except at the O H layer where both conifers and mixed stands had higher concentrations of C than beech stands. Moreover, the interaction between Species and Sites was significant only for Douglas fir and mixed Douglas Fir/beech stands, indicating that the effect of species on C concentration varied across sites, being significantly high at sandy soils (Northern sites). The Species also showed a significant effect on the N concentration. Specifically, the N concentration was higher for both mixture forests (Douglas fir/beech, spruce/beech), and spruce than for the pure beech stand. The depth also significantly affected the N concentration. Compared to the reference depth (10–30 cm), all other depths were significantly associated with higher N concentration. Additionally, the interaction between Species and Sites was also found to be significant, indicating that the effect of species on the N concentration varies depending on the site. C and N stocks The results indicated that C stock was higher in the beech stands at the Southern sites (loamy soils) (23.33 Mg ha − 1 ) than in Douglas-fir stands (19.60 Mg ha − 1 ). On the contrary, at Northern sites (sandy soils), Douglas-fir stands had higher C stock (23.46 Mg ha − 1 ) than beech stands (16.29 Mg ha − 1 ). The LMM explained 49% of the variance in C stock and was found to be statistically significant (p < 0.001). Species , soil conditions , and depth were significant predictors of C stock (p < 0.05) (Fig. 2 ). The coefficient estimate for sandy soils was positive, indicating that C stock were higher in sandy soils compared to loamy soils. The interaction term between Species and sandy soil was statistically significant (p < 0.001) and negative, indicating that the effect of species on C stock differed between sandy and loamy soils, and it was attenuated in sandy soils. There, Douglas fir and Douglas fir/beech showed the highest C stocks compared to beech. The effect of species on C stock was stronger at litter layer (O L ). Additionally, the interactions between Species and depth and Species and sandy soils were found to be statistically significant (p < 0.05) with negative coefficients, indicating that the effect of species on C stock was more pronounced in the litter layer at sandy soils. The model was statistically significant (p < 0.001) and explained 63.53% of the variance in N stock. The results showed that Species had a significant effect on N stock (p = 0.02). Aditionally, the interaction effect between Species and Northern sites was also significant (p > 0.001), indicating that the effect of Species on N stock was attenueted in sandy soils compared to loamy soils. There, Douglas fir shower higher N stocks than spruce stand (Fig. 4 ). In contrast, at the loamy soils (Southern sites), total N stocks were higher under spruce stands than under Douglas fir stands. The effect of the mixtures showed the same site-dependent patterns as reported for SOC stocks, where the stocks under both beech–conifer mixtures were similar to those under the respective pure conifer stands. At the southern sites, significantly larger N stocks were observed under mixed spruce/beech stand than Douglas/beech, whereas at nouthern sites, the opposite were observed (Douglas/beech > Spruce/beech). At all sites, N stocks at organic layer under mixed beech–conifer stands (either Douglas/beech or spruce/beech), significantly exceeded beech stands. The soil depth was also a significant predictor of N stock, with 10–30 cm showing the highest N stock (p > 0.001). However, none of the interaction terms between Species and depth were significant, indicating that the effect of Species on N stock did not vary across different soil depths. SOC Distribution The contribution of the organic layer stocks (SOC Org ) to the total stocks (SOCt) was site-dependent. At southern sites, the SOC Org contributed between 15% and 22% for Douglas fir and spruce stands, respectively, whereas for beech it was only 8%. The mixture stands showed intermediate results, ranging from 10% (Douglas fir/beech) to 17% (spruce/beech). At northern sites, the contribution of SOC Org on SOCt stock was strong pronounced. Under the spruce stand, 33% of the SOC stock is allocated to the organic horizon, whereas 20% was observed in the Douglas fir stand. The contribution of SOC org to SOCt for mixed forests ranged between 23% (Douglas/beech) and 30% (spruce/beech) and only 10% for beech stands. The N allocation corresponded to the SOC vertical distribution. At the northern sites, the relative contribution ranged from 20–26% for conifers and mixed forest to 11% at the beech forest, whereas at the southern sites, it ranged from 13–17% for conifers to only 6% under beech forest. At northern sites, mixture stands showed a clear contrast: at the spruce/beech stand, the contribution of organic layer N stock to the total N stock was 30%, while at the Douglas/beech stand, it was only 7%. Overall, under sandy soil conditions, conifers and mixed forests allocated 10% more SOC and N at the organic layer compared to loamy soils, whereas the SOC and N stocks under beech maintained the same proportion (> 90% at SOC ms ), independent of the site condition. Effect of abiotic factors on C and N stocks The effect of abiotic factors like soil pH on C stock was investigated using linear mixed models (Fig. 5 ). The increase of pH caused significant decreased (P < 0.001) on SOC at mineral soil. The increase of 1 unit of pH (3.75 to 4.75) reduced in about 25% the total SOC. Whereas, the opposite was observed for N stocks, where the increased of pH showed increases in N stocks. Discussion Tree species effects We observed significant effects of tree species on organic C and N stocks as well as its vertical distribution across all investigated sites. Overall, the organic-horizon (O) stocks of C and N were significantly higher under conifer forests (Douglas fir and spruce) than under beech (Fig. 1 ). At the mineral soil (MS) the effects of tree species were site-dependent. The southern sites (loamy soil), beech and spruce stands accumulated higher C and N stocks than Douglas fir forest, confirming earlier results of (Antisari et al., 2015 ) where smallest SOC stocks of the organic horizon under beech stand are accompanied by enhanced SOC stock in the mineral topsoil. In contrast, at northern sites (sandy soil), the beech stands showed the smallest C stock at both layers (O and MS). According to (Neumann et al., 2018), broadleaves litter tends to decompose faster compared to conifer litter. This can be attributed to lower lignin and phenol concentrations, which promote rapid decomposition rates and efficient accumulation of mineral-associated organic matter, as reported by (Rasse et al., 2005 ). In our study, we observed a carbon (C) shift from the organic horizon to the mineral soil in the beech forest under loamy soil conditions, supporting the findings of previous research (Achilles et al., 2021). The higher C allocation on mineral soil than organic horizon under beech than conifers has also been reported in common garden studies (Vesterdal et al., 2013 ). The differences in vertical distribution has been attributed to the associated community of macrofauna species in forests dominated by beech (Achilles et al., 2021). Therefore, the quality of the soil organic matter (SOM) might be significantly different under coniferous and deciduous trees (Jaffrain et al., 2007). The O H layer under conifers results in a more recalcitrant and hydrophobic composition than that of O H layer at beech stand (Thomas et al., 2014 ), therefore, slowing C turnover of the SOM leads a greater accumulation of carbon in the transition layers, such O F and O H , and furthermore to the top mineral soil, as observed in our study under both conifers stands. Besides the litter quality, rooting patterns and microbial activity among beech, Douglas fir and Norway spruce might change the C inputs between tree species. Conifer roots contain lower lignin concentrations than roots of beech (Thomas et al., 2014 ) (Newman and Hart 2006), which might lead to a lower longevity and a faster decomposition. Additionally, fine roots necromass deliver a considerable amount of organic material (Cremer et al., 2016 ; Dawud et al., 2017 ) enhancing the root-derived SOM. Simultaneous studies on the turnover of fine root biomasses carried out by (Lwila et al., 2021) have shown that beech forests showed higher fine roots biomass than Douglas fir at the sandy soils, whereas the fine root necromass was higher for Douglas fir compared to beech. Additionally, high microbial activity at the upper mineral soil is reported in the same study area (Lu and Scheu, 2021), suggesting higher rhizosphere carbon inputs at the beech forest stand compared to Douglas fir, but also high root-derived SOM at the Douglas fir stand. Mixed forest effect Independent of the site conditions, the pure stands of beech showed relatively small total SOC stocks, whereas the pure conifer sites enhanced total SOC and N stocks, accumulated to a large extent in the organic layer. Furthermore, the admixture of conifers to beech enlarged the total SOC and N storage only in the northern sites, i.e. under sandy soil conditions, whereas in the southern sites, i.e., under loamy soil conditions, both mixtures of conifers to beech presented similar storages compared to pure beech. Overall, at the southern sites the carbon (C) stocks in the O H layer, as well as the total soil organic carbon (SOC) and nitrogen (N) stocks, were generally similar between mixed beech-conifer stands and their respective pure stands. The C stocks at both mixed stands at southern sites resembled those of the respective beech stands and approached the levels observed in conifer stands at northern sites. The admixture of conifers into beech stands in nutrient-poor soil conditions, particularly observed at the northern sites, had significant effects on soil organic carbon (SOC) and nitrogen (N) stocks, which aligns with the results reported by Dawud et al. ( 2017 ). Under these soil conditions, both the mixture of Douglas fir and beech and pure Douglas fir stands exhibited higher SOC stocks in the humus layer (O H ) and the 5–30 cm soil depth. This can be attributed to the competitive advantage of beech fine roots, which have the ability to access deeper soil layers and exploit areas less occupied by competing species. In contrast, Douglas fir fine roots tend to be restricted to the topsoil (15–30 cm), resulting in a shift in the distribution of beech fine roots towards the subsoil. This phenomenon has been reported in previous studies (Hendriks and Bianchi, 1995; Schmid and Kazda, 2002). These observed shifts of root vertical distribution are known as below-ground complementarity effects, e.g., through vertical segregation of roots of different species, which exploit soil at different depths allowing for reduced competition (Loreau M, 2001). It has been suggested as a mechanism by which species mixtures store more C in deeper soil layers than monocultures (Bauhus et al., 2009; Forrester et al., 2006). Additionally, the admixture of beech leaf litter to the more recalcitrant needle litter induced a faster litter mass loss and consequently shift of SOC stock from O L to O H layer. We observed similar litter decomposition rate for mixed stands and pure beech, and higher than pure conifers (Douglas fir and spruce), suggesting similar decomposability of litter in the mixed forest and in the beech forest (not published). Thus, allocation of C in soils is an important ecosystem service provided by forests (Pretzsch et al., 2017). Owing to the potential of higher SOC storages in mixed-species forests compared to pure stands and to shift the C into stable pools i.e., the shift from O L layers to O H layer, enhance the capacity of mixed forest to provide ecosystem services, such as improving the soil functioning like soil biodiversity and nutrient availability and, furthermore the resilience of the forest ecosystem to cope with future climate change scenarios. Abiotic effects The persistence of SOC is largely due to complex interactions between SOC and its environment, such as reactive mineral surfaces, climate, water availability and soil acidity (Leifeld et al., 2013 ; Mikutta et al., 2009 ; Zhou et al., 2019 ). The most important factor in SOC stabilization at sites with high clay contents, as partly observed in our study, is probably the association with soil minerals, irrespective of forest type (Fierer and Jackson, 2006 ; Meier et al., 2020 ). Indeed, enhanced clay and silt content increased the SOC in the mineral soil at our investigated sites and, in contrast decreased the SOC storage at organic horizon. Loamy soils are known to buffer influences by tree species more strongly than sandy soils (MEIER and LEUSCHNER, 2010) and this would explain why we see clear effects of species on the northern sites dominated by sandy soils than at southern sites, dominated by loamy soils. Therefore, differences in soil pH often go along with differences in soil mineralogy as well and the latter exerts control on the stabilization of mineral associated organic matter (Meier et al., 2020 ) and microbiota community (MEIER and LEUSCHNER, 2010). In our study, we found that the increase of pH caused significant decreased (P < 0.001) on SOC at mineral soil (Fig. 5 ). Thus, the accumulation of organic matter in soils is influenced by relatively low pH levels, which can reduce the decomposition of soil organic matter (SOM), as highlighted by Meier et al. ( 2020 ). This, in turn, leads to noticeable effects of tree species on organic matter accumulation, where lower pH is observed, as detected in our study. Interestingly, Meier et al. ( 2020 ) also suggested that soil acidity is associated with increased rates of root exudation in beech forests, particularly in the topsoil of glacial sandy soils found in the northern sites. This increased root exudation can be seen as an adaptation of the trees to low nutrient availability, a finding consistent with our study (Foltran et al., 2023 ). In these conditions, the majority of nutrient uptake occurs in the AE horizon, which is enriched with organic material, further explaining the adaptability and plasticity of beech forests in response to varying nutrient availability. Conclusion Site dependent effects of tree species (European beech, Douglas fir and Norway spruce) on SOC and N stocks as well as on SOC and N concentration were observed. The SOC and N stocks generally were smallest in pure beech stands compared with Douglas fir and Norway spruce. The SOC and N stocks in mixed stands of beech with Douglas fir or Norway spruce are generally between those of the respective pure stands. However, the results indicate that the effects of admixture of conifers into beech stands are site-dependent. At the Northern sites, the adaptability of Douglas fir under dry and poor-nutrient site conditions combined with high plasticity of beech promoted a favorable effect on total SOC and N, enhancing its storages as observed at pure Douglas fir and the mixture Douglas fir/beech. In contrast, at the Southern sites, spruce/beech showed higher SOC and N stocks than Douglas/beech. The Douglas fir/beech stand mixture showed significant increases of total SOC under sandy soils (Northern sites). Additionally, the potential shift of carbon into more stable pools (shifts from the O L layer to the O H layer), emphasizes the capacity of mixed forest to provide valuable ecosystem services, enhancing C sequestration, meanwhile reducing the risk of unintended losses. Declarations Author contributions All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by EF. The first draft of the manuscript was written by EF and NL commented on previous versions of the manuscript. All authors read and approved the final manuscript. Acknowledgements The study was conducted as part of the Research Training Group 2300 funded by the German research funding organization (Deutsche Forschungsgemeinschaft – DFG). We gratefully acknowledge the administrative support by Serena Müller and the indispensable help of Julian Meyer and Dirk Böttger during soil sampling. Furthermore, we thank Sylvia Bondzio, Karin Schmidt for their valuable advice during laboratory work. Conflicts of Interest The authors declare no conflict of interest. References Ammer, Christian; Annighöfer, Peter; Balkenhol, Niko; Hertel, Dietrich; Leuschner, Christoph; Polle, Andrea; Lamersdorf, Norbert; Scheu, Stefan; Glatthorn, J. (2020), 2020. RTG 2300 - study design, location, topography and climatic conditions of research plots in 2020. Pangaea. 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Soil acidity and exchangeable base cation stocks under pure and mixed stands of European beech, Douglas fir and Norway spruce. Plant and Soil 415, 393–405. https://doi.org/10.1007/s11104-017-3177-1 Dawud, S.M., Raulund-Rasmussen, K., Domisch, T., Finér, L., Jaroszewicz, B., Vesterdal, L., 2016. Is Tree Species Diversity or Species Identity the More Important Driver of Soil Carbon Stocks, C/N Ratio, and pH? Ecosystems 19, 645–660. https://doi.org/10.1007/s10021-016-9958-1 Dawud, S.M., Vesterdal, L., Raulund-Rasmussen, K., 2017. Mixed-species effects on soil C and N stocks, C/N ratio and pH using a transboundary approach in adjacent common garden douglas-fir and beech stands. Forests 8. https://doi.org/10.3390/f8040095 FAO, 2014. World reference base for soil resources 2014. International soil classification system for naming soils and creating legends for soil maps, World Soil Resources Reports No. 106. Fierer, N., Jackson, R.B., 2006. The diversity and biogeography of soil bacterial communities. Proceedings of the National Academy of Sciences of the United States of America 103, 626–631. https://doi.org/10.1073/pnas.0507535103 Foltran, E.C., Ammer, C., Lamersdorf, N., 2023. Do admixed conifers change soil nutrient conditions of European beech stands? Soil Research 63 https://doi.org/10.1071/ SR22218 bioRxiv 2020.09.25.313213. https://doi.org/10.1101/2020.09.25.313213 Frouz, J., Pižl, V., Cienciala, E., Kalčík, J., 2009. Carbon Storage in Post-Mining Forest Soil, the Role of Tree Biomass and Soil Bioturbation. Biogeochemistry 94, 111–121. Krishna, M.P., Mohan, M., 2017. Litter decomposition in forest ecosystems: a review. Energy, Ecology and Environment 2, 236–249. https://doi.org/10.1007/s40974-017-0064-9 Leifeld, J., Bassin, S., Conen, F., Hajdas, I., Egli, M., Fuhrer, J., 2013. Control of soil pH on turnover of belowground organic matter in subalpine grassland. Biogeochemistry 112, 59–69. https://doi.org/10.1007/s10533-011-9689-5 Lorenz, K., Lal, R., 2014. Soil organic carbon sequestration in agroforestry systems. A review. Agronomy for Sustainable Development 34, 443–454. https://doi.org/10.1007/s13593-014-0212-y Lu, J.-Z., Scheu, S., 2020. Mixing coniferous and deciduous trees (Fagus sylvatica): Site-specific response of soil microorganisms 1–29. https://doi.org/: https://doi.org/10.1101/2020.07.21.213900 Meier, I.C., Tückmantel, T., Heitkötter, J., Müller, K., Preusser, S., Wrobel, T.J., Kandeler, E., Marschner, B., Leuschner, C., 2020. Root exudation of mature beech forests across a nutrient availability gradient: the role of root morphology and fungal activity. New Phytologist 226, 583–594. https://doi.org/10.1111/nph.16389 MEIER, I.N.A.C., LEUSCHNER, C., 2010. Variation of soil and biomass carbon pools in beech forests across a precipitation gradient. Global Change Biology 16, 1035–1045. https://doi.org/https://doi.org/10.1111/j.1365-2486.2009.02074.x Mikutta, R., Schaumann, G.E., Gildemeister, D., Bonneville, S., Kramer, M.G., Chorover, J., Chadwick, O.A., Guggenberger, G., 2009. Biogeochemistry of mineral-organic associations across a long-term mineralogical soil gradient (0.3-4100 kyr), Hawaiian Islands. Geochimica et Cosmochimica Acta 73, 2034–2060. https://doi.org/10.1016/j.gca.2008.12.028 Mueller, K.E., Eissenstat, D.M., Hobbie, S.E., Oleksyn, J., Jagodzinski, A.M., Reich, P.B., Chadwick, O.A., Chorover, J., 2012. Tree species effects on coupled cycles of carbon, nitrogen, and acidity in mineral soils at a common garden experiment. Biogeochemistry 111, 601–614. https://doi.org/10.1007/s10533-011-9695-7 Oulehle, F., Hofmeister, J., Hruška, J., 2007. Modeling of the long-term effect of tree species (Norway spruce and European beech) on soil acidification in the Ore Mountains. Ecological Modelling 204, 359–371. https://doi.org/10.1016/j.ecolmodel.2007.01.012 Rasse, D.P., Rumpel, C., Dignac, M.F., 2005. Is soil carbon mostly root carbon? Mechanisms for a specific stabilisation. Plant and Soil 269, 341–356. https://doi.org/10.1007/s11104-004-0907-y Renger, M.;, Bohne, K.;, Facklam, M.;, Harrach, T.;, Riek, W.;, Schäfer, W.;, Wessolek, G.;, Zacharias, S., 2008. Ergebnisse und Vorschläge der DBG-Arbeitsgruppe „Kennwerte des Bodengefüges“ zur Schätzung bodenphysikalischer Kennwerte. Bodenökologie und Bodengenese 51. Robertson, A.D., Paustian, K., Ogle, S., Wallenstein, M.D., Lugato, E., Francesca Cotrufo, M., 2019. Unifying soil organic matter formation and persistence frameworks: The MEMS model. Biogeosciences 16, 1225–1248. https://doi.org/10.5194/bg-16-1225-2019 Schmidt, M.W.I., Torn, M.S., Abiven, S., Dittmar, T., Guggenberger, G., Janssens, I.A., Lehmann, J., Manning, D.A.C., Nannipieri, P., Rasse, D.P., Kleber, M., Ko, I., 2011. Persistence of soil organic matter as an ecosystem property. Nature 478. https://doi.org/10.1038/nature10386 Thomas, F.M., Molitor, F., Werner, W., 2014. Lignin and cellulose concentrations in roots of Douglas fir and European beech of different diameter classes and soil depths. Trees - Structure and Function 28, 309–315. https://doi.org/10.1007/s00468-013-0937-2 Vesterdal, L., Clarke, N., Sigurdsson, B.D., Gundersen, P., 2013. Do tree species influence soil carbon stocks in temperate and boreal forests? Forest Ecology and Management 309, 4–18. https://doi.org/10.1016/j.foreco.2013.01.017 Vesterdal, L., Raulund-Rasmussen, K., 1998. Forest floor chemistry under seven tree species along a soil fertility gradient. Canadian Journal of Forest Research 28, 1636–1647. https://doi.org/10.1139/cjfr-28-11-1636 Vesterdal, L., Schmidt, I.K., Callesen, I., Nilsson, L.O., Gundersen, P., 2008. Carbon and nitrogen in forest floor and mineral soil under six common European tree species. Forest Ecology and Management 255, 35–48. https://doi.org/https://doi.org/10.1016/j.foreco.2007.08.015 Zhou, W., Han, G., Liu, M., Li, X., 2019. Effects of soil pH and texture on soil carbon and nitrogen in soil profiles under different land uses in Mun River Basin, Northeast Thailand. PeerJ 2019. https://doi.org/10.7717/peerj.7880 Supplementary Files SupportinginformationpaperCarbon2023.docx Cite Share Download PDF Status: Published Journal Publication published 31 Aug, 2024 Read the published version in Forest Ecology and Management → Version 1 posted 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. 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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-3160848","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":223005291,"identity":"42d10bc0-85a0-47e2-882b-c04bdde2a6c5","order_by":0,"name":"Estela Covre Foltran","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIiWNgGAWjYLCCBwwM/AzsYKYNEDM2HsCvnpmBIYGBQbKBmRnESwNpaSBJy2GwGF4t/PznDz5IqLGT4GfmP/bh547zdmvbDwNtqbGJxqVFckYys0HCsWQJyWZm5pm9Z24nbzuTCNRyLC23AYcWgxvMbBIJbAfqDA4DXcbbdjvZ7ABQC2PDYZxa7M8fZv+R8O+ABEgL49+2c8lm5x/i12LAkMzGkNgG0cLM23bAzuwGAVskbiQbSyT2gf1izCzblpxgdgNoSwIev/D3H3z44cM3YIixNz5mfNtmZ292Pv3hgw81Nji1YIBEsMoEYpWDgD0pikfBKBgFo2BkAAC4zV1r852IyQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0001-5752-9675","institution":"Georg-August-Universitat Gottingen","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Estela","middleName":"Covre","lastName":"Foltran","suffix":""},{"id":223005292,"identity":"47de6020-0e2e-4046-949f-08327d41914d","order_by":1,"name":"Norbert Lamersdorf","email":"","orcid":"","institution":"","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Norbert","middleName":"","lastName":"Lamersdorf","suffix":""}],"badges":[],"createdAt":"2023-07-11 15:20:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3160848/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3160848/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1016/j.foreco.2024.122090","type":"published","date":"2024-09-01T00:26:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":41086329,"identity":"82906acb-ca91-40b0-a793-903bd3665a81","added_by":"auto","created_at":"2023-08-04 17:05:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":38040,"visible":true,"origin":"","legend":"\u003cp\u003eLinear mixed-effects model on soil bulk density. The figure shows the estimate coefficient (β), t-test and significance\u003cem\u003ep\u003c/em\u003e for each term included in the model. Species (D: Douglas fir, S: spruce; Be: beech; Douglas fir/beech: DB; and, spruce/beech: SB), Region (Southern sites [loamy soils] and Northern sites [sandy soils]) and depth (0-5, 5-10 and 10-30 cm]).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-3160848/v1/76baae01e0b058c29aeee650.png"},{"id":41086334,"identity":"3e827795-4c9d-4a62-a5e0-84b17e439181","added_by":"auto","created_at":"2023-08-04 17:05:49","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":414600,"visible":true,"origin":"","legend":"\u003cp\u003eLinear mixed-effects model on Carbon (a), Nitrogen (b) concentration and CN ratio (c). The figure shows the estimate coefficient (β), t-test and significance\u003cem\u003e p\u003c/em\u003e for each term included in the model. Species (D: Douglas fir, S: spruce; Be: beech; Douglas fir/beech: DB; and, spruce/beech: SB), Region (Southern sites [loamy soils] and Northern sites [sandy soils]) and depth [O\u003csub\u003eL\u003c/sub\u003e, O\u003csub\u003eF\u003c/sub\u003e, O\u003csub\u003eH\u003c/sub\u003e, 0-5, 5-10 and 10-30 cm]).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-3160848/v1/e6994e44c5fa5a2400d1a572.png"},{"id":41086331,"identity":"49694bd1-f64d-429f-831c-3c73877afe57","added_by":"auto","created_at":"2023-08-04 17:05:49","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":448705,"visible":true,"origin":"","legend":"\u003cp\u003eLinear mixed-effects model on Carbon stock (a) and Carbon stock (b; Mg ha\u003csup\u003e-1\u003c/sup\u003e). The figure (a) shows the estimate coefficient (β), t-test and significance\u003cem\u003e p\u003c/em\u003e for each term included in the model. Species (D: Douglas fir, S: spruce; Be: beech; Douglas fir/beech: DB; and, spruce/beech: SB), Region (Southern sites [loamy soils] and Northern sites [sandy soils]) and depth [L,F,H,0-5, 5-10 and 10-30 cm]). The figure (b) shows the C stock in the organic layer (brown bars) and mineral soil (green bars), and the standard error (n=16).\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3160848/v1/cfe416820a4ea48714f86870.png"},{"id":41086333,"identity":"3e8a2baf-180f-4ef3-922d-6546a3a6caf4","added_by":"auto","created_at":"2023-08-04 17:05:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":403142,"visible":true,"origin":"","legend":"\u003cp\u003eLinear mixed-effects model on Nitrogen stock (a) and Nitrogen stock (b; Mg ha\u003csup\u003e-1\u003c/sup\u003e). The figure (a) shows the estimate coefficient (β), t-test and significance\u003cem\u003e p\u003c/em\u003e for each term included in the model. Species (D: Douglas fir, S: spruce; Be: beech; Douglas fir/beech: DB; and, spruce/beech: SB), Region (Southern sites [loamy soils] and Northern sites [sandy soils]) and depth [L,F,H,0-5, 5-10 and 10-30 cm]). The figure (b) shows the N stock in the organic layer (brown bars) and mineral soil (green bars), and the standard error (n=16).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3160848/v1/717d166a840eeddadd464c4c.png"},{"id":41087806,"identity":"f2f9debe-a620-434c-bb43-e46568e94809","added_by":"auto","created_at":"2023-08-04 17:13:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":427480,"visible":true,"origin":"","legend":"\u003cp\u003eRelationship between the soil organic carbon (SOC) (a) and Nitrogen (b) on mineral soil. The grey line denotes a linear mixed-effect model (LMM; P \u0026lt; 0.05) with the predictor variables as fixed effect and species as random intercept terms. The dashed line represents a 95% confidence interval. All response variables (C stock, and N stock) were transformed with natural logarithm, whereas predictor variable (pH) were standardized by subtracting the mean and dividing by the standard deviation.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-3160848/v1/0463daed8049cc2868eef4d4.png"},{"id":59225069,"identity":"b356730e-5637-4571-a44d-bde4ccc32db9","added_by":"auto","created_at":"2024-06-28 00:27:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2235934,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3160848/v1/2af02684-fc39-46d5-b53e-0a78f15dbabb.pdf"},{"id":41086330,"identity":"381eafcd-d56f-4bf7-81e9-41bb9d710592","added_by":"auto","created_at":"2023-08-04 17:05:49","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":487216,"visible":true,"origin":"","legend":"","description":"","filename":"SupportinginformationpaperCarbon2023.docx","url":"https://assets-eu.researchsquare.com/files/rs-3160848/v1/df2f518646902ef03068aa26.docx"}],"financialInterests":"","formattedTitle":"Tree Species Identity Drives Soil Carbon and Nitrogen Stocks in Nutrient-Poor Sites","fulltext":[{"header":"Introduction","content":"\u003cp\u003eForest soils are complex ecosystems and their proper management, especially through the selection of trees with distinct species identities, may have a major impact on soil organic carbon (SOC) stocks and nitrogen (N) dynamics, leading to C sequestration potentials (Jandl et al., 2007; Vesterdal et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), as well as reducing N leaching.\u003c/p\u003e \u003cp\u003eTypical driving forces of such tree species identities include the type of foliage, the quality of leaf litter, indicated e.g. by the C/N ratio, or the type of rooting characteristic in forest soils.\u003c/p\u003e \u003cp\u003eThus, tree species identity may have an important impact on the ecosystem level such as soil C stock and C/N ratios, particularly in the O-horizon and top mineral soil layers (Dawud et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Vesterdal et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Furthermore, the species diversity drives the fluxes of carbon and nitrogen in soils (Cep\u0026aacute;kov\u0026aacute; et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mueller et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Vesterdal et al., 2002) and their role on SOC sequestration are been highlighted to improve the ecosystem functions as carbon sequestration.\u003c/p\u003e \u003cp\u003eDifferent patterns of C storage in soil profile and organic horizons has been reported for conifers and deciduous trees on temperate ecosystems (Bolte and Villanueva, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However, it is highly uncertain which processes are responsible for differences in soil C stocks in organic horizon and mineral soil. Differences in litter input (D\u0026iacute;az-Pin\u0026eacute;s et al., 2011), root distribution (Oulehle et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) as well as decomposition rates (Cools et al., 2014) have been suggested as the most likely explanation for tree species influence on soil C stocks. Often, Douglas fir (\u003cem\u003ePseudotsuga menziesii menziesii\u003c/em\u003e) and European beech (\u003cem\u003eFagus sylvatica\u003c/em\u003e) show high fine root density in deeper soil layers (Bolte and Villanueva, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Oulehle et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) and thus increasing C allocation in mineral soil layers. In contrast, the native conifer Norway spruce (\u003cem\u003ePicea abies\u003c/em\u003e), known as shallow-rooted tree species (Bolte and Villanueva, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2006\u003c/span\u003e) accumulates C preferentially in the upper mineral soil layers.\u003c/p\u003e \u003cp\u003eCompositionally and structurally diverse forests represent an important element of approaches to deliver a wide range of ecosystem goods and services like carbon sequestration (Ammer, et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, the establishment and management of mixed stands is also discussed as an effective measure to adapt forests stands to climate change (Berg and McClaugherty, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Frouz et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). However, it has already been shown, that the admixtures of conifer (either with Douglas fir or Norway spruce) to beech forests modified the soil C and N input through the fine root distribution in the soil profile (Vesterdal and Raulund-Rasmussen, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Additionally, the enhanced nutrient concentrations of beech litter increase litter decomposition of conifers needles (Krishna and Mohan, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Neumann et al., 2018; Vesterdal et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), followed by less C accumulation in the organic soil layers and shift to potential stable C pools in mineral soil. However, still inconsistent information exist, on how mixed stands of beech with Douglas-fir would affect forest soil C and N vertical distribution. Due to the differences in litter input (D\u0026iacute;az-Pin\u0026eacute;s et al., 2011) as well as decomposition rates (Cools et al., 2014) its most likely that this mixture enhance the organic C stocks in the organic layers as well. Thus, the deep root system reported to Douglas fir and beech and the high SOC on organic layer might suggest that the admixture of Douglas fir into beech stands potentially results in higher total C in the whole soil profile.\u003c/p\u003e \u003cp\u003eTherefore, the main objective of our study was to analyze the accumulation, vertical distribution as well as litter quality indices (C/N ratios) of the upper mineral C and N stocks of different pure and mixed stand types (pure European beech, pure Norway spruce, pure Douglas-fir, mixed European beech/Norway spruce and mixed European beech/Douglas-fir) along Northern Germany under distinct soil characteristics (loamy \u003cem\u003eversus\u003c/em\u003e sandy soil conditions). We hypothesized that i) the admixture of Douglas fir to beech forests will increase C stocks at the mineral soil compared to respectively beech monocultures, ii) the C stocks at litter layer will decrease under the admixture of Douglas fir to beech and, shift to rather stables C pools (H-layer and mineral soil), compared to respectively monocultures, and iii) on nutrient poor sites (sandy soils), species-identity effects on organic layer will be stronger pronunced than on rich soils (loamy soil).\u003c/p\u003e"},{"header":"Material and Methods","content":"\u003cp\u003eStudy sites\u003c/p\u003e\n\u003cp\u003eWe investigated seven sites in Lower Saxony, northern Germany. Each site contained quintet neighboring forest stands. Three of these stands were monospecific stands of European beech (\u003cem\u003eFagus sylvatica\u003c/em\u003e), Norway spruce (\u003cem\u003ePicea abies\u003c/em\u003e), or Douglas fir (\u003cem\u003ePseudotsuga menziesii\u003c/em\u003e). The other two were mixed stands, one composed of spruce/beech and one composed of Douglas fir/beech.\u003c/p\u003e\n\u003cp\u003eEssential criteria for the selection of the sites were the presence of the respective quintets in a similar advanced silvicultural development status, altogether, we employed a multi-criteria approach, considering factors such as climate, soil type (based on German soil inventory), stand age, and existing research on land-use, as well as a relevant single tree admixture in the mixed stands.\u003c/p\u003e\n\u003cp\u003eHowever, on the basis of the available forest site mapping and also confirmed by Foltran et al. (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), two groups with relatively homogeneous site conditions were distinguished in our data set, in particular via the texture data (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e; Fig. S3), but also addressing the geological substrate classes, the correspondently developed soil types as well as the given range of water and nutrient levels (Foltran et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eIn the first region in southern Lower Saxony, we chose three sites (Dassel, Winnefeld, and Nienover). These three sites are located in the hills of the Solling plateau and lie between 300 and 450 m.a.s.l. They share similar climatic conditions, i.e. a mean annual air temperature of 7.2\u0026deg;C and mean annual precipitation of about 1040 mm/year. The age ranges between 45 and 90 years and the texture is relatively rich (23% of clay; Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). The soils at these locations are Dystric Cambisols (FAO, 2015) developed from Triassic sandstone material, covered by loess.\u003c/p\u003e\n\u003cp\u003eIn the second region, located in the northern Lower Saxony, we selected four sites (Unterl\u0026uuml;\u0026szlig;, Nienburg, and G\u0026ouml;hrde I and II). These sites are in lowland Lower Saxony and lie between 80 to 150 m.a.s.l. and all have similar climatic conditions, i.e., a mean annual air temperature of 8.4\u0026deg;C, mean annual precipitation of 720 mm/year. The age ranges between 53 and 130 years.\u003c/p\u003e\n\u003cp\u003eMost frequent soil types are therefore Podzols (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e) and their transitional forms towards Cambisols, developed on geological formations from the last ice ages and mostly with a high sand content, compared to the southern region\u003c/p\u003e\n\u003cp\u003eWith respect to nutrients and according to the official Lower Saxony forest site mapping and Foltran et al. (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), the southern sites (loamy soils) are nutrient-rich, and the northern sites (sandy soils) are nutrient-poor\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1691164840.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003c/table\u003e\n\u003cp\u003eSoil sampling\u003c/p\u003e\n\u003cp\u003eIn each forest stand type (50 m x 50 m) at all sites, 4 randomly selected points were chosen as representative sampling points. The selected points were oriented at stand-level, e.g., we standardized two meters minimal distance from the trees to avoid coarse roots. At each sampling plot, the forest floor was collected using a steel frame and sorted by identifiable foliar (O\u003csub\u003eL\u003c/sub\u003e \u0026ndash; Litter), non-foliar (O\u003csub\u003eF\u003c/sub\u003e \u0026ndash; decay layer), and non-identifiable and humified (O\u003csub\u003eH\u003c/sub\u003e \u0026ndash; Humus) layers of the organic layer. Mineral soil was sampled using a core auger (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8 cm) and, separated at 0\u0026ndash;5, 5\u0026ndash;10, and 10\u0026ndash;30 cm soil depth. Bulk soil density from each depth was calculated using soil metal rings (250 cm\u0026sup3;) to further stock analysis.\u003c/p\u003e\n\u003cp\u003ePartly missing bulk density data due to frozen soil conditions, interfering tree roots or stones during sampling were estimated by Adams equation (ADAMS, 1973) adapted by(CHEN et al., 2017). The approach uses SOM and pH as bulk density predictors.\u003c/p\u003e\n\u003cp\u003eSample preparation and analysis\u003c/p\u003e\n\u003cp\u003eAll mineral soil samples were oven-dried at 40\u0026deg;C until constant weight and sieved through 2 mm mesh, subsamples from the fine soil fractions (\u0026lt;\u0026thinsp;2 mm diameter) were ground with a Retsch mortar grinder RM 200 (Retsch, Germany) for 10 min. The organic layer samples were dried at 60\u0026deg;C until constant weight, weighted and ball milled (MM2, Fa Retsch) for further analysis.\u003c/p\u003e\n\u003cp\u003eAll the samples were analyzed for total C and N by dry combustion in a Leco CSN 2000 analyzer. There was no inorganic C (CaCO\u003csub\u003e3\u003c/sub\u003e) within 30 cm depth in soils and all measured C were consequently considered to be organic.\u003c/p\u003e\n\u003cp\u003eThe pH measurements for all mineral soil samples were performed in KCl solution, more detailed descriptions can be found in the Foltran et al. (\u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eCalculations of Stocks\u003c/p\u003e\n\u003cp\u003eWe estimated the soil bulk density from the oven-dried and moisture corrected (105 ◦C) fine soil mass and its volume. The fine soil volume was estimated from the difference between the volume of the soil corer and the volume of stones and roots. Carbon and N stocks in each layer were estimated from the organic horizon mass (O-layers) and soil bulk density (mineral soil), concentrations of C and N and depth of the individual soil depths for each sampling point.\u003c/p\u003e\n\u003cp\u003eStatistical Analyses\u003c/p\u003e\n\u003cp\u003eTo address the non-independent nature of multiple horizons within one soil profile for this subset of data, we chose linear mixed effect models (Rasmussen et al., 2018). To estimate the effect of \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eSite Conditions\u003c/em\u003e (loamy \u003cem\u003evs\u003c/em\u003e sandy), we fitted linear mixed models (LMMs) to log-transformed response variables (C and N stocks) and then applied planned contrasts (Piovia-Scott et al., 2019). All LMMs included \u003cem\u003eSpecies\u003c/em\u003e (European beech, Douglas fir, Douglas fir/beech, Norway spruce, spruce/beech), \u003cem\u003eSite Conditions\u003c/em\u003e (loamy and sandy sites), and \u003cem\u003eSoil Depths\u003c/em\u003e (O\u003csub\u003eL\u003c/sub\u003e, O\u003csub\u003eF\u003c/sub\u003e, O\u003csub\u003eH\u003c/sub\u003e [organic layers] and 0\u0026ndash;5, 5\u0026ndash;10 and 10\u0026ndash;30 cm [mineral soil]) as fixed effects. Models were stepwise selected by likelihood ratio test, and minimal models included all main effects and the interaction of forest type and region.\u003c/p\u003e\n\u003cp\u003eThe mean values for each site are given in the supplementary material (Table S3 and S4). There, the effect of the forest stand (pure or mixed forest) on the soil chemical parameters for individual depth was assessed by least significant difference test. As the assumption of normal distribution was not met (tested for with Shapiro Wilk test), we used the Kruskal Wallis test, followed by pairwise Mann-Whitney tests with a correction factor for multiple pairwise testing, to identify statistically significant differences among \u003cem\u003eSpecies\u003c/em\u003e and site conditions by individual depth.\u003c/p\u003e\n\u003cp\u003eAll analyses were done in R 4.0.3 (R Core Team, 2020). We used the \u0026lsquo;nlme\u0026rsquo; package to fit LMMs and the \u0026lsquo;emmeans\u0026rsquo; package for planned contrasts. All mixed models met the assumptions of normality of residuals and homogeneity of variance.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eOrganic horizon mass and soil density\u003c/p\u003e\n\u003cp\u003eNo effects of \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eSite conditions\u003c/em\u003e on organic horizon masses (OHM) was observed. Instead, organic layer depth and the interaction \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eDepth\u003c/em\u003e and \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eSite condition\u003c/em\u003e were consistency significant affecting the organic layer masses. Furthermore, the associated LMM model revealed a statistical significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; r\u0026sup2;=0.397), indicating that approximately 40% of the variation in the response variable (OHM) could be explained by the model (Figure S2).\u003c/p\u003e\n\u003cp\u003eThe effect of \u003cem\u003eDepth\u003c/em\u003e was significant, with O\u003csub\u003eH\u003c/sub\u003e having a positive effect (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) on OHM, its interaction term \u003cem\u003eDepth\u003c/em\u003e and \u003cem\u003eSite condition\u003c/em\u003e shows that O\u003csub\u003eH\u003c/sub\u003e layer presents a negative effect at southern sites compared to the northern sites (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), meaning that this layer impacted the OHM at the northern sites, but not in the southern sites. The interaction \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eDepth\u003c/em\u003e show that both mixed stands (Douglas fir/beech and spruce/beech) and O\u003csub\u003eH\u003c/sub\u003e layer have significant and positive effects on OHM, in another words, both mixtures stand increased the OHM accumulated in the O\u003csub\u003eH\u003c/sub\u003e layer.\u003c/p\u003e\n\u003cp\u003eThe mineral soil bulk density ranges from 0.8 to 1.4 g cm\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e. The southern sites showed significant lower soil bulk density (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than northern sites, and Douglas fir and Douglas fir/beech showed significant lower bulk soil density (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to beech. A significant interaction among \u003cem\u003eSpecies\u003c/em\u003e and S\u003cem\u003eite conditions\u003c/em\u003e was observed (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e), where Douglas fir and its mixture with beech (Douglas fir/beech) showed higher soil densities at loamy soils (Southern sites) than at sandy soils (Northern sites) (Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eOrganic-horizon and mineral soil C and N concentrations\u003c/p\u003e\n\u003cp\u003eWe used a linear mixed model (LMM) to investigate the relationship between carbon (C) and nitrogen (N) concentrations and \u003cem\u003eSpecies\u003c/em\u003e, \u003cem\u003eDepth\u003c/em\u003e, and their interaction across the \u003cem\u003eSites\u003c/em\u003e (Northern and Southern sites). The results showed that \u003cem\u003eSpecies\u003c/em\u003e have a significant effect on carbon concentration, as well as the depth. The highest C concentration was found in the O\u003csub\u003eH\u003c/sub\u003e layer and decreased with depth. Furthermore, the effect of depth varied across species, with higher carbon concentrations found in the top layer of the organic horizon for all species, except Douglas fir.\u003c/p\u003e\n\u003cp\u003eIn terms of the species effect, the C concentration was significantly higher under beech and mixed spruce/beech stands compared to conifers, Douglas fir and spruce. Except at the O\u003csub\u003eH\u003c/sub\u003e layer where both conifers and mixed stands had higher concentrations of C than beech stands. Moreover, the interaction between \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eSites\u003c/em\u003e was significant only for Douglas fir and mixed Douglas Fir/beech stands, indicating that the effect of species on C concentration varied across sites, being significantly high at sandy soils (Northern sites).\u003c/p\u003e\n\u003cp\u003eThe \u003cem\u003eSpecies\u003c/em\u003e also showed a significant effect on the N concentration. Specifically, the N concentration was higher for both mixture forests (Douglas fir/beech, spruce/beech), and spruce than for the pure beech stand. The depth also significantly affected the N concentration. Compared to the reference depth (10\u0026ndash;30 cm), all other depths were significantly associated with higher N concentration. Additionally, the interaction between \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eSites\u003c/em\u003e was also found to be significant, indicating that the effect of species on the N concentration varies depending on the site.\u003c/p\u003e\n\u003cp\u003eC and N stocks\u003c/p\u003e\n\u003cp\u003eThe results indicated that C stock was higher in the beech stands at the Southern sites (loamy soils) (23.33 Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) than in Douglas-fir stands (19.60 Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e). On the contrary, at Northern sites (sandy soils), Douglas-fir stands had higher C stock (23.46 Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e) than beech stands (16.29 Mg ha\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e).\u003c/p\u003e\n\u003cp\u003eThe LMM explained 49% of the variance in C stock and was found to be statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). \u003cem\u003eSpecies\u003c/em\u003e, \u003cem\u003esoil conditions\u003c/em\u003e, and \u003cem\u003edepth\u003c/em\u003e were significant predictors of C stock (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). The coefficient estimate for sandy soils was positive, indicating that C stock were higher in sandy soils compared to loamy soils. The interaction term between \u003cem\u003eSpecies\u003c/em\u003e and sandy soil was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and negative, indicating that the effect of species on C stock differed between sandy and loamy soils, and it was attenuated in sandy soils. There, Douglas fir and Douglas fir/beech showed the highest C stocks compared to beech.\u003c/p\u003e\n\u003cp\u003eThe effect of species on C stock was stronger at litter layer (O\u003csub\u003eL\u003c/sub\u003e). Additionally, the interactions between \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003edepth\u003c/em\u003e and \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003esandy soils\u003c/em\u003e were found to be statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) with negative coefficients, indicating that the effect of species on C stock was more pronounced in the litter layer at sandy soils.\u003c/p\u003e\n\u003cp\u003eThe model was statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and explained 63.53% of the variance in N stock. The results showed that \u003cem\u003eSpecies\u003c/em\u003e had a significant effect on N stock (p\u0026thinsp;=\u0026thinsp;0.02). Aditionally, the interaction effect between \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003eNorthern sites\u003c/em\u003e was also significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.001), indicating that the effect of \u003cem\u003eSpecies\u003c/em\u003e on N stock was attenueted in sandy soils compared to loamy soils. There, Douglas fir shower higher N stocks than spruce stand (Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). In contrast, at the loamy soils (Southern sites), total N stocks were higher under spruce stands than under Douglas fir stands.\u003c/p\u003e\n\u003cp\u003eThe effect of the mixtures showed the same site-dependent patterns as reported for SOC stocks, where the stocks under both beech\u0026ndash;conifer mixtures were similar to those under the respective pure conifer stands. At the southern sites, significantly larger N stocks were observed under mixed spruce/beech stand than Douglas/beech, whereas at nouthern sites, the opposite were observed (Douglas/beech\u0026thinsp;\u0026gt;\u0026thinsp;Spruce/beech).\u003c/p\u003e\n\u003cp\u003eAt all sites, N stocks at organic layer under mixed beech\u0026ndash;conifer stands (either Douglas/beech or spruce/beech), significantly exceeded beech stands. The soil depth was also a significant predictor of N stock, with 10\u0026ndash;30 cm showing the highest N stock (p\u0026thinsp;\u0026gt;\u0026thinsp;0.001). However, none of the interaction terms between \u003cem\u003eSpecies\u003c/em\u003e and \u003cem\u003edepth\u003c/em\u003e were significant, indicating that the effect of \u003cem\u003eSpecies\u003c/em\u003e on N stock did not vary across different soil depths.\u003c/p\u003e\n\u003cp\u003eSOC Distribution\u003c/p\u003e\n\u003cp\u003eThe contribution of the organic layer stocks (SOC\u003csub\u003eOrg\u003c/sub\u003e) to the total stocks (SOCt) was site-dependent. At southern sites, the SOC\u003csub\u003eOrg\u003c/sub\u003e contributed between 15% and 22% for Douglas fir and spruce stands, respectively, whereas for beech it was only 8%. The mixture stands showed intermediate results, ranging from 10% (Douglas fir/beech) to 17% (spruce/beech). At northern sites, the contribution of SOC\u003csub\u003eOrg\u003c/sub\u003e on SOCt stock was strong pronounced. Under the spruce stand, 33% of the SOC stock is allocated to the organic horizon, whereas 20% was observed in the Douglas fir stand. The contribution of SOC\u003csub\u003eorg\u003c/sub\u003e to SOCt for mixed forests ranged between 23% (Douglas/beech) and 30% (spruce/beech) and only 10% for beech stands.\u003c/p\u003e\n\u003cp\u003eThe N allocation corresponded to the SOC vertical distribution. At the northern sites, the relative contribution ranged from 20\u0026ndash;26% for conifers and mixed forest to 11% at the beech forest, whereas at the southern sites, it ranged from 13\u0026ndash;17% for conifers to only 6% under beech forest. At northern sites, mixture stands showed a clear contrast: at the spruce/beech stand, the contribution of organic layer N stock to the total N stock was 30%, while at the Douglas/beech stand, it was only 7%.\u003c/p\u003e\n\u003cp\u003eOverall, under sandy soil conditions, conifers and mixed forests allocated 10% more SOC and N at the organic layer compared to loamy soils, whereas the SOC and N stocks under beech maintained the same proportion (\u0026gt;\u0026thinsp;90% at SOC\u003csub\u003ems\u003c/sub\u003e), independent of the site condition.\u003c/p\u003e\n\u003cp\u003eEffect of abiotic factors on C and N stocks\u003c/p\u003e\n\u003cp\u003eThe effect of abiotic factors like soil pH on C stock was investigated using linear mixed models (Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). The increase of pH caused significant decreased (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) on SOC at mineral soil. The increase of 1 unit of pH (3.75 to 4.75) reduced in about 25% the total SOC. Whereas, the opposite was observed for N stocks, where the increased of pH showed increases in N stocks.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eTree species effects\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eWe observed significant effects of tree species on organic C and N stocks as well as its vertical distribution across all investigated sites. Overall, the organic-horizon (O) stocks of C and N were significantly higher under conifer forests (Douglas fir and spruce) than under beech (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). At the mineral soil (MS) the effects of tree species were site-dependent. The southern sites (loamy soil), beech and spruce stands accumulated higher C and N stocks than Douglas fir forest, confirming earlier results of (Antisari et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) where smallest SOC stocks of the organic horizon under beech stand are accompanied by enhanced SOC stock in the mineral topsoil. In contrast, at northern sites (sandy soil), the beech stands showed the smallest C stock at both layers (O and MS).\u003c/p\u003e \u003cp\u003eAccording to (Neumann et al., 2018), broadleaves litter tends to decompose faster compared to conifer litter. This can be attributed to lower lignin and phenol concentrations, which promote rapid decomposition rates and efficient accumulation of mineral-associated organic matter, as reported by (Rasse et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In our study, we observed a carbon (C) shift from the organic horizon to the mineral soil in the beech forest under loamy soil conditions, supporting the findings of previous research (Achilles et al., 2021). The higher C allocation on mineral soil than organic horizon under beech than conifers has also been reported in common garden studies (Vesterdal et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The differences in vertical distribution has been attributed to the associated community of macrofauna species in forests dominated by beech (Achilles et al., 2021).\u003c/p\u003e \u003cp\u003eTherefore, the quality of the soil organic matter (SOM) might be significantly different under coniferous and deciduous trees (Jaffrain et al., 2007). The O\u003csub\u003eH\u003c/sub\u003e layer under conifers results in a more recalcitrant and hydrophobic composition than that of O\u003csub\u003eH\u003c/sub\u003e layer at beech stand (Thomas et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), therefore, slowing C turnover of the SOM leads a greater accumulation of carbon in the transition layers, such O\u003csub\u003eF\u003c/sub\u003e and O\u003csub\u003eH\u003c/sub\u003e, and furthermore to the top mineral soil, as observed in our study under both conifers stands.\u003c/p\u003e \u003cp\u003eBesides the litter quality, rooting patterns and microbial activity among beech, Douglas fir and Norway spruce might change the C inputs between tree species. Conifer roots contain lower lignin concentrations than roots of beech (Thomas et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) (Newman and Hart 2006), which might lead to a lower longevity and a faster decomposition. Additionally, fine roots necromass deliver a considerable amount of organic material (Cremer et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Dawud et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) enhancing the root-derived SOM. Simultaneous studies on the turnover of fine root biomasses carried out by (Lwila et al., 2021) have shown that beech forests showed higher fine roots biomass than Douglas fir at the sandy soils, whereas the fine root necromass was higher for Douglas fir compared to beech. Additionally, high microbial activity at the upper mineral soil is reported in the same study area (Lu and Scheu, 2021), suggesting higher rhizosphere carbon inputs at the beech forest stand compared to Douglas fir, but also high root-derived SOM at the Douglas fir stand.\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eMixed forest effect\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eIndependent of the site conditions, the pure stands of beech showed relatively small total SOC stocks, whereas the pure conifer sites enhanced total SOC and N stocks, accumulated to a large extent in the organic layer. Furthermore, the admixture of conifers to beech enlarged the total SOC and N storage only in the northern sites, i.e. under sandy soil conditions, whereas in the southern sites, i.e., under loamy soil conditions, both mixtures of conifers to beech presented similar storages compared to pure beech. Overall, at the southern sites the carbon (C) stocks in the O\u003csub\u003eH\u003c/sub\u003e layer, as well as the total soil organic carbon (SOC) and nitrogen (N) stocks, were generally similar between mixed beech-conifer stands and their respective pure stands. The C stocks at both mixed stands at southern sites resembled those of the respective beech stands and approached the levels observed in conifer stands at northern sites.\u003c/p\u003e \u003cp\u003eThe admixture of conifers into beech stands in nutrient-poor soil conditions, particularly observed at the northern sites, had significant effects on soil organic carbon (SOC) and nitrogen (N) stocks, which aligns with the results reported by Dawud et al. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Under these soil conditions, both the mixture of Douglas fir and beech and pure Douglas fir stands exhibited higher SOC stocks in the humus layer (O\u003csub\u003eH\u003c/sub\u003e) and the 5\u0026ndash;30 cm soil depth. This can be attributed to the competitive advantage of beech fine roots, which have the ability to access deeper soil layers and exploit areas less occupied by competing species. In contrast, Douglas fir fine roots tend to be restricted to the topsoil (15\u0026ndash;30 cm), resulting in a shift in the distribution of beech fine roots towards the subsoil. This phenomenon has been reported in previous studies (Hendriks and Bianchi, 1995; Schmid and Kazda, 2002). These observed shifts of root vertical distribution are known as below-ground complementarity effects, e.g., through vertical segregation of roots of different species, which exploit soil at different depths allowing for reduced competition (Loreau M, 2001). It has been suggested as a mechanism by which species mixtures store more C in deeper soil layers than monocultures (Bauhus et al., 2009; Forrester et al., 2006). Additionally, the admixture of beech leaf litter to the more recalcitrant needle litter induced a faster litter mass loss and consequently shift of SOC stock from O\u003csub\u003eL\u003c/sub\u003e to O\u003csub\u003eH\u003c/sub\u003e layer. We observed similar litter decomposition rate for mixed stands and pure beech, and higher than pure conifers (Douglas fir and spruce), suggesting similar decomposability of litter in the mixed forest and in the beech forest (not published).\u003c/p\u003e \u003cp\u003eThus, allocation of C in soils is an important ecosystem service provided by forests (Pretzsch et al., 2017). Owing to the potential of higher SOC storages in mixed-species forests compared to pure stands and to shift the C into stable pools i.e., the shift from O\u003csub\u003eL\u003c/sub\u003e layers to O\u003csub\u003eH\u003c/sub\u003e layer, enhance the capacity of mixed forest to provide ecosystem services, such as improving the soil functioning like soil biodiversity and nutrient availability and, furthermore the resilience of the forest ecosystem to cope with future climate change scenarios.\u003c/p\u003e \u003cp\u003eAbiotic effects\u003c/p\u003e \u003cp\u003eThe persistence of SOC is largely due to complex interactions between SOC and its environment, such as reactive mineral surfaces, climate, water availability and soil acidity (Leifeld et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Mikutta et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Zhou et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The most important factor in SOC stabilization at sites with high clay contents, as partly observed in our study, is probably the association with soil minerals, irrespective of forest type (Fierer and Jackson, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Meier et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Indeed, enhanced clay and silt content increased the SOC in the mineral soil at our investigated sites and, in contrast decreased the SOC storage at organic horizon. Loamy soils are known to buffer influences by tree species more strongly than sandy soils (MEIER and LEUSCHNER, 2010) and this would explain why we see clear effects of species on the northern sites dominated by sandy soils than at southern sites, dominated by loamy soils.\u003c/p\u003e \u003cp\u003eTherefore, differences in soil pH often go along with differences in soil mineralogy as well and the latter exerts control on the stabilization of mineral associated organic matter (Meier et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and microbiota community (MEIER and LEUSCHNER, 2010). In our study, we found that the increase of pH caused significant decreased (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) on SOC at mineral soil (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Thus, the accumulation of organic matter in soils is influenced by relatively low pH levels, which can reduce the decomposition of soil organic matter (SOM), as highlighted by Meier et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This, in turn, leads to noticeable effects of tree species on organic matter accumulation, where lower pH is observed, as detected in our study. Interestingly, Meier et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) also suggested that soil acidity is associated with increased rates of root exudation in beech forests, particularly in the topsoil of glacial sandy soils found in the northern sites. This increased root exudation can be seen as an adaptation of the trees to low nutrient availability, a finding consistent with our study (Foltran et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In these conditions, the majority of nutrient uptake occurs in the AE horizon, which is enriched with organic material, further explaining the adaptability and plasticity of beech forests in response to varying nutrient availability.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSite dependent effects of tree species (European beech, Douglas fir and Norway spruce) on SOC and N stocks as well as on SOC and N concentration were observed. The SOC and N stocks generally were smallest in pure beech stands compared with Douglas fir and Norway spruce. The SOC and N stocks in mixed stands of beech with Douglas fir or Norway spruce are generally between those of the respective pure stands. However, the results indicate that the effects of admixture of conifers into beech stands are site-dependent. At the Northern sites, the adaptability of Douglas fir under dry and poor-nutrient site conditions combined with high plasticity of beech promoted a favorable effect on total SOC and N, enhancing its storages as observed at pure Douglas fir and the mixture Douglas fir/beech. In contrast, at the Southern sites, spruce/beech showed higher SOC and N stocks than Douglas/beech.\u003c/p\u003e \u003cp\u003eThe Douglas fir/beech stand mixture showed significant increases of total SOC under sandy soils (Northern sites). Additionally, the potential shift of carbon into more stable pools (shifts from the O\u003csub\u003eL\u003c/sub\u003e layer to the O\u003csub\u003eH\u003c/sub\u003e layer), emphasizes the capacity of mixed forest to provide valuable ecosystem services, enhancing C sequestration, meanwhile reducing the risk of unintended losses.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAuthor contributions\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by EF. The first draft of the manuscript was written by EF and NL commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eThe study was conducted as part of the Research Training Group 2300 funded by the German research funding organization (Deutsche Forschungsgemeinschaft \u0026ndash; DFG). We gratefully acknowledge the administrative support by Serena M\u0026uuml;ller and the indispensable help of Julian Meyer and Dirk B\u0026ouml;ttger during soil sampling. Furthermore, we thank Sylvia Bondzio, Karin Schmidt for their valuable advice during laboratory work.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConflicts of Interest\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAmmer, Christian; Annigh\u0026ouml;fer, Peter; Balkenhol, Niko; Hertel, Dietrich; Leuschner, Christoph; Polle, Andrea; Lamersdorf, Norbert; Scheu, Stefan; Glatthorn, J. (2020), 2020. RTG 2300 - study design, location, topography and climatic conditions of research plots in 2020. Pangaea.\u003c/li\u003e\n\u003cli\u003eAntisari, L.V., Falsone, G., Carbone, S., Marinari, S., Vianello, G., 2015. 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PeerJ 2019. https://doi.org/10.7717/peerj.7880\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":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"mixed forests, broadleaves, conifers, Fagus sylvatica, Pseudotsuga menziesii, Picea abies, SOC","lastPublishedDoi":"10.21203/rs.3.rs-3160848/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3160848/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAims\u003c/h2\u003e \u003cp\u003eThe establishment of mixed forest stands can be seen as an option to enhance soil organic carbon stock and to protect forest ecosystems from various impacts of climate change. We examined the effect of admixture of conifers to beech forests on C stock.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe analyzed groups of European beech (\u003cem\u003eFagus sylvatica\u003c/em\u003e), Douglas fir (\u003cem\u003ePseudotsuga menziesii\u003c/em\u003e) and Norway spruce (\u003cem\u003ePicea abies\u003c/em\u003e) stands as well as mixtures of beech with either Douglas fir or spruce under loamy \u003cem\u003eversus\u003c/em\u003e sandy soils. We examined the stocks of C in the organic layer and upper mineral soil.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe C stock of the organic layer was largely depending on tree species, whereas the C stock of the mineral soil varied among soil types. Total soil organic C stocks showed significant species identities and mixing effects were most obvious due to the high SOC stocks in the organic layer. Overall, under sandy soil conditions, conifers and mixed forests allocated 10% more SOC and N at the organic layer compared to loamy soils, whereas the SOC and N stocks under beech maintained the same proportion, independent of the site condition. The interaction between species and sites was significant only for Douglas Fir and mixed Douglas Fir/beech, indicating that the effect of species on C and N varied across sites, being significantly high at sandy soils.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe higher potential for carbon and N storage in mixed-species forests compared to pure stands emphasizes the capacity of mixed forest to provide valuable ecosystem services, enhancing C sequestration.\u003c/p\u003e","manuscriptTitle":"Tree Species Identity Drives Soil Carbon and Nitrogen Stocks in Nutrient-Poor Sites","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-08-04 17:05:44","doi":"10.21203/rs.3.rs-3160848/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f709248a-b79b-4b58-a53e-2f7035c06cd4","owner":[],"postedDate":"August 4th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-06-28T00:26:55+00:00","versionOfRecord":{"articleIdentity":"rs-3160848","link":"https://doi.org/10.1016/j.foreco.2024.122090","journal":{"identity":"forest-ecology-and-management","isVorOnly":true,"title":"Forest Ecology and Management"},"publishedOn":"2024-09-01 00:26:55","publishedOnDateReadable":"September 1st, 2024"},"versionCreatedAt":"2023-08-04 17:05:44","video":"","vorDoi":"10.1016/j.foreco.2024.122090","vorDoiUrl":"https://doi.org/10.1016/j.foreco.2024.122090","workflowStages":[]},"version":"v1","identity":"rs-3160848","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3160848","identity":"rs-3160848","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}