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Effects of three coniferous plantation species on plant‐soil feedbacks and soil physical and chemical properties in semi‐arid mountain ecosystems

Effects of three coniferous plantation species on plant‐soil feedbacks and soil physical and... Background: Large-scale afforestation can significantly change the ground cover and soil physicochemical properties, especially the soil fertility maintenance and water conservation functions of artificial forests, which are very important in semi-arid mountain ecosystems. However, how different tree species affect soil nutrients and soil physicochemical properties after afforestation, and which is the best plantation species for improving soil fertility and water conservation functions remain largely unknown. Methods: This study investigated the soil nutrient contents of three different plantations (Larix principis-rupprechtii, Picea crassifolia, Pinus tabuliformis), soils and plant-soil feedbacks, as well as the interactions between soil physicochemical properties. Results: The results revealed that the leaves and litter layers strongly influenced soil nutrient availability through biogeochemical processes: P. tabuliformis had higher organic carbon, ratio of organic carbon to total nitrogen (C:N) and organic carbon to total phosphorus (C:P) in the leaves and litter layers than L. principis-rupprechtii or P. crassifolia, suggesting that higher C:N and C:P hindered litter decomposition. As a result, the L. principis-rupprechtii and P. crassifolia plantation forests significantly improved soil nutrients and clay components, compared with the P. tabuliformis plantation forest. Furthermore, the L. principis-rupprechtii and P. crassifolia plantation forests significantly improved the soil capacity, soil total porosity, and capillary porosity, decreased soil bulk density, and enhanced water storage capacity, compared with the P. tabuliformis plantation forest. The results of this study showed that, the strong link between plants and soil was tightly coupled to C:N and C:P, and there was a close correlation between soil particle size distribution and soil physicochemical properties. Conclusions: Therefore, our results recommend planting the L. principis-rupprechtii and P. crassifolia as the preferred tree species to enhance the soil fertility and water conservation functions, especially in semi-arid regions mountain forest ecosystems. Keywords: Plantation, C:N:P stoichiometry, Plant‐soil feedbacks, Soil physicochemical properties, Mountain ecosystems * Correspondence: zhaochm@lzu.edu.cn State Key Laboratory of Grassland and Agro-Ecosystems, School of Life Sciences, Lanzhou University, 730000 Lanzhou, China Gansu Provincial Field Scientific Observation and Research Station of Mountain Ecosystems, 730000 Lanzhou, China © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Han et al. Forest Ecosystems (2021) 8:3 Page 2 of 13 Introduction processes, which play a key role in determining plant The reforestation remains one of the most effective growth, community composition, and individual prod- strategies for coping with climate change (Jean-Francois uctivity (van der Putten et al. 2013). Besides, different et al. 2019), which is also the most effective management plant species tend to have species-specific effects on soil method to solve the problems of soil erosion all over the quality and quantity (Hobbie et al. 2006; Ayres et al. world (Clemente et al. 2004; Kou et al. 2016). It is con- 2009), and they also change the physical, chemical, and sidered to be an effective strategy to prevent soil erosion biological properties of soil (Qiao et al. 2019). Thus, and degradation and to promote the restoration of de- aboveground and belowground processes of forest eco- graded ecosystems (Zhang et al. 2011). For the past three systems determine plant-soil feedbacks and influence the decades, to prevent soil erosion and desertification and composition of the plant community and nutrient cyc- improve water conservation capacity, the Grain to Green ling processes (Kardol et al. 2006; van der Putten et al. Program (GTGP) has been implemented by the Chinese 2013), potentially affecting ecosystem functioning, such government (Chang et al. 2012). Large-scale afforest- as interactions between plants and other communities ation increased ground cover and caused changes in soil (van der Putten et al. 2013), conserving water resource physical and chemical properties (Fu et al. 2010). Forests and preventing soil losses. Therefore, understanding the as ecosystem engineers not only have species-specific ef- relationships between plantation types and soil physico- fects on soil physicochemical properties and soil com- chemical properties is of great significance for the soil munities (soil animal communities and soil microbial and water conservation, nutrient cycling, and soil health communities) (Vesterdal et al. 2008; Prescott and Grays- assessment of forest stands. ton 2013), but also regulate climate, mineral cycling and Soil particle-size distribution (PSD) refers to the per- prevent soil erosion (Kozlowski 2002). Besides, artificial centage of each particle size class in the soil, which can forests could potentially lead to circulation and feedback reflect the influence of soil water movement, solute effects of mineral nutrients between above-ground and transport, nutrient status, and vegetation types on soil below-ground ecosystems (Wang et al. 2009; Peichl et al. texture (Sun et al. 2016). Soil texture is divided into clay, 2012). Therefore, the study of vegetation restoration silt, and sand, which is one of the important physical pa- processes and their impacts on nutrient cycling and soil rameters of soil (Hu et al. 2011; Mohammadi and properties will provide an important guide to forest Meskini-Vishikaee 2013; Xu et al. 2013). The change of management aimed at improving the ecological restor- soil particle-size distribution is the result of the com- ation of natural and artificial forests, especially in semi- bined effects of soil evolution, vegetation restoration, arid mountain ecosystem regions. and environmental factors. Soil texture and organic mat- It is well known that vegetation is an important factor ter are the key factors affecting soil particle size (Qi affecting soil physical and chemical properties. Leaves of et al. 2018). Previous studies have shown that the above- different tree species have generated species-specific ef- ground part of plants can effectively increase the rough- fects on litter layer decomposition and nutrients released ness of the surface, thus increasing the content of fine into the soil (Norris et al. 2012; Aponte et al. 2013). Tree particles and nutrients in the soil, leading to the change species affect soil nutrient mineralization and availability of soil structure (Xiang et al. 2015). However, the rela- through soil microorganisms, thus affecting soil fertility tionship between soil physicochemical properties and (Aponte et al. 2013; Huang et al. 2013). Previous studies soil particle-size distribution and their effects on water have shown that environmental factors influence leaves conservation functions are scarce. and then affect many service functions of the ecosystems Xinglong Mountain is an important water conserva- (Ayres et al. 2009; Aponte et al. 2013). Thus, leaf quality tion area on semi-arid land in northwestern China. Since largely determines the decomposition of litter, as well as the implementation of China’s Three-North Shelterbelt the release of nutrients and minerals into the soil (Norris forest program in the 1980s, a large-scale artificial affor- et al. 2012; Aponte et al. 2013), indicating the relation- estation project has been carried out in Xinglong moun- ship among leaves, litter, and soil (Lucas-Borja et al. tain, and the planted forest species were Larix principis- 2018). However, the studies about the effects of leaves rupprechtii, Picea crassifolia, Pinus tabuliformis. Al- and litter from different tree species on soil organic car- though artificial afforestation has been carried out for bon, nitrogen cycling, and water conservation functions many years, there is no systematic evaluation of the soil in semi-arid mountain forest ecosystems are still lacking. and water conservation capacity and ecological construc- Soil plays an important fertility and stability function tion benefits of the plantations. In this study, we in forest ecosystems (Lucas-Borja et al. 2018), and it dir- hypothesize that there is a strong feedback effect of nu- ectly or indirectly regulates and influences many bio- trients between plants and soil. Tree species may influ- logical processes (Zhang et al. 2018). Soil properties are ence the soil organic carbon (SOC), total nitrogen (TN), determined by chemical, physical and biological and total phosphorus (TP) of different afforestation and Han et al. Forest Ecosystems (2021) 8:3 Page 3 of 13 then will affect the soil physicochemical properties, The climate in this region is classified as semi-arid con- structure, and texture. This study aimed to: (1) investi- tinental monsoon climate, and the annual precipitation gate the influence of three different tree species on the is about 450–622 mm. The precipitation frequency is nutrient status of plants and soil and plant-soil feed- not uniform, mostly concentrated in July to September. backs; (2) analyse the effects of three different tree spe- The effective accumulated temperature was 1800– cies on soil physical and chemical properties; and (3) 2800 °C, and the average annual relative air humidity explore the impacts of soil physical and chemical prop- was 68 %. erties of three different forest stands on soil particle-size distribution characteristics and their influence factors. We selected three study sites with different dominant Therefore, the results of this study can provide theoret- tree species planted 30 years ago, the planting distance is ical guidance in the selection of forest species for affor- about 4 m × 4 m, and all the plantations are in semi- estation and forest management, particularly in the sunny slope. The distance between each study site is less semi-arid mountain forest ecosystems. than 10 km, and the environmental, meteorological, soil and the parent material among stands were homoge- Materials and Methods neous. More basic information of the three plantation Study site description stands was summarized in Table 1. The type of lands be- The research area is located in the Gansu Xinglongshan fore plantations is a natural succession of grassland, no National Nature Reserve (35°44′20.12′′ N, 104°1′3.07′′ human disturbance and management to the forests and E, 2778 m a.s.l.), in the Loess Plateau, China (Fig. 1). As soils since the plantation. During the growth and succes- a “green rock island” in the Loess Plateau, it is an im- sion of different tree species, the soil physicochemical portant water conservation forest and biodiversity pro- properties changed accordingly, thus potentially affecting tection area in the upper reaches of the Yellow River. ecosystem functioning. Therefore, these differences Fig. 1 The location map of Xinglong Mountain in the Loess Plateau of China and sample plot information (A: L. principis-rupprechtii forest, B: P. crassifolia forest, C: P. tabuliformis forest) Han et al. Forest Ecosystems (2021) 8:3 Page 4 of 13 Table 1 The basic information of traits of the three plantation stands − 1 Forest stands Stand density (trees·ha ) Average DBH (cm) Average height (m) LAI Slope L. principis-rupprechtii 608 26.19 16.43 3.49 5° P. crassifolia 560 26.04 12.97 4.17 4.5° P. tabuliformis 592 23.69 12.10 2.68 8° among stands can be attributed to tree species. There determine soil physiochemical properties and particle- were a large amount of herbaceous vegetation (i.e., size distribution (PSD). Soil organic carbon (SOC) con- Carex rigescens, Fragaria orientalis, Aconitum sinomon- tent were determined using the K Cr O -H SO oxida- 2 2 7 2 4 tanum and Potentilla bifurca) and shrubs (i.e., Sorbus tion method (Bao 2000; Wang 2009). Soil total nitrogen koeheana, Berberis kansuensis, Rosa sweginzowii, Coto- (TN) values were determined using the micro-Kjeldahl neaster multiflorus, Spiraea alpine and Lonicera hispida) method (Yang et al. 2018), whilst soil total phosphorus growing on the forest floor and the litter thickness was (TP) and total potassium (TK) values were determined about 10 cm. colorimetrically (ammonium molybdate method) and flame photometer after wet digestion with HClO - H SO (Bao 2000; Cao and Chen 2017), respectively. In- 2 4 Analysis methods of nutrient contents in the leaves and organic nitrogen in the form of nitrate nitrogen litter layers (NO -N) and ammonium nitrogen (NH -N) were de- 3 4 Three sample plots (25 m × 25 m) in each forest stand termined through colorimetry (Bao 2000), and available − 1 were randomly selected, and two trees or points were se- phosphorus (AP) was extracted with 0.5 mol·L lected randomly in each sample plot to collect leaves NaHCO , then determined by molybdenum-antimony (i.e., needles), soil, and litter samples. There are six repli- colorimetry (Bao 2000; Kou et al. 2016). Available potas- − 1 cates for leaves, soil, or litter samples in each forest sium (AK) was extracted with 1 mol·L CH COONH 3 4 stand. The leaf samples were randomly collected from then determined by flame photometry (Bao 2000; Zhou each of the three different forest stand sites in August et al. 2015). TN, TP, NO -N and NH -N were mea- 3 4 2018, and litter samples were sampled under the canopy sured using an automatic intermittent chemical analyzer of each selected tree (The distance between each sam- (SmartChem140, France). The AK and TK in the soil pling tree or point is greater than 10 m. The collected were determined using flame atomic absorption spectro- − 1 litter is mainly fallen needles of trees). Leaves and litter photometric method (detection limit is 0–1000 mg·L ) samples were processed in a grinder (dried to constant (Aurora, AI-1200, Canada). weight at 75 °C) and sieved through a 60-mesh sieve. To determine soil physical properties, undisturbed Organic carbon values of the leaf and litter layer were samples were obtained from the 0–10, 10–20 and 20– determined using the K Cr O -H SO oxidation method 2 2 7 2 4 30 cm soil layers using a ring knife at each typically re- (Bao 2000; Wang 2009), the total nitrogen (TN) values peated plots for three different forest stands (six intact were determined using the micro-Kjeldahl method (Bao soil cores were obtained from each of the three soil 2000; Zhang et al. 2019a), whilst total phosphorus (TP) layers for each forest stand). The bulk density and soil values of leaf and litter layer were determined colorimet- capacity of the soil samples were measured using the rically (ammonium molybdate method) after wet diges- method exposed by Zhang et al. (2019b). The total por- tion with H O -H SO , and the total potassium (TK) 2 2 2 4 osity was determined by measuring soil moisture content values were determined using an atomic absorption at saturation (total volume of water-filled soil pores) and − 1 spectrophotometer (detection limit is 0–1000 mg·L ) capillary porosity (capillary porosity is the percentage of (Aurora, AI-1200, Canada) after wet digestion with soil voids in soil volume) was determined with the H O -H SO (Bao 2000; Zhang et al. 2019a). 2 2 2 4 method exposed by Qiu et al. (2019). Analysis methods of soil physical and chemical properties To determine soil nutrient contents, the soil samples Determination of the soil particle-size distribution of the were collected from the 0–10, 10–20 and 20–30 cm soil soil samples layers at each site. We randomly selected two pionts in The soil particle-size distribution was measured using a each sample plot (25 m × 25 m). For each forest stand, laser particle analyzer (Mastersizer 2000, Malvern Com- 18 soil samples, 6 leaf samples, and 6 litter samples were pany, UK), each 0.25 g soil sample was pretreated with collected. Totally, 48 soil samples, 18 leaf samples, and 10 % H O solution to remove organic matter, and 10 % 2 2 18 litter samples were collected. Air-dried soil samples HCl solution was added to remove carbonate salts. Add screened by 2- and 0.15-mm mesh sieve were used to deionized water to soak for 12 h, then the liquid Han et al. Forest Ecosystems (2021) 8:3 Page 5 of 13 supernatant was removed. The samples were chemically likelihood method to build a path model. All statistical − 1 dispersed with 0.06 mol·L sodium hexametaphosphate analyses were performed using SPSS 26.0 and AMOS and were mechanically dispersed in an ultrasonic bath 24.0 (SPSS Inc. an IBM Company, Chicago, IL, USA), for 10 min (Qi et al. 2018). The measurements were re- and all figures were prepared with Origin 2020 software peated three times for each sample, and the soil particle- (Origin Lab Inc., Northampton, MA, USA). size distribution (PSD) was classified into clay (< 2 µm), silt (2–50 µm), and sand (50–2000 µm) according to Results United States Department of Agriculture classification Nutrient contents of the leaves and litter layers for the (USDA) classification system (Xia et al. 2020; Zhai et al. three plantations 2020). The content of organic carbon (OC), TN, TP, TK, and C:N:P stoichiometry were different in leaves and Statistical analyses litter layers for different tree species (Fig. 2). The or- The effects of different forest species on the physical and ganic carbon content in the leaves and litter of P. chemical properties of the soil, nutrient contents in the tabuliformis was significantly higher than that of L. vegetation and litter layers, and soil particle-size distri- principis-rupprechtii (14 % and 2 % more, respectively) bution (PSD) were evaluated using one-way ANOVA and P. crassifolia (16 % and 3 % more, respectively) (the normal distribution and homogeneity of variance of (Fig. 2a). However, the content of N, P, and K in the the data had been checked), followed by least significant leaves and litter of P. tabuliformis was lower than difference (LSD) tests for different soil layer (P < 0.05). that of L. principis-rupprechtii (N: 36 % and 44 % less, Pearson correlation analysis was undertaken to identify P: 43 % and 45 % less, K: 37 % and 34 % less, respect- the relationships between SOC, TN, TP, TK, bulk dens- ively) and P. crassifolia (N: 46% and 25% less, P: ity, soil capacity, total porosity, and capillary porosity. 65 % and 30 % less, K: 24 % and 21 % less, respect- The relationship between soil physicochemical proper- ively) (Fig. 2b‒2d). The C:N ratio, C:P ratio and N:P ties and soil particle-size distribution was analyzed by ratio of leaves of P. tabuliformis were markedly higher confirmatory factor analysis using the maximum than that of L. principis-rupprechtii, but these ratios Fig. 2 Differences in OC, TN, TP, TK contents, and C:N:P stoichiometry in leaves and litter for three different plantation species. Different lowercase letters indicate significant differences (P < 0.05) among different plantation species Han et al. Forest Ecosystems (2021) 8:3 Page 6 of 13 of P. crassifolia were significantly lower than those of L. P ratio, and N:P ratio exhibited a gradually decreas- principis-rupprechtii (Fig. 2e‒2 g). The C:N ratio and C:P ra- ing trend from surface soil layers to deep soil layers; tio of the litter of P. tabuliformis were the highest, and were the exceptions were the C:N ratio of the P. crassifo- significantly higher in P. crassifolia than in L. principis- lia stand and the C:P ratio and N:P ratio of the P. rupprechtii (Fig. 2e‒2f). The N:P ratio of the litter of P. tabu- tabuliformis stand, where there was no significant liformis was higher than that of L. principis-rupprechtii and difference between the different soil layers (Fig. 3e‒ P. crassifolia,and therewas no statisticdifferencebetween L. 3g). On thewhole,the SOC, TN,TP, C:Nratio,C: principis-rupprechtii and P. crassifolia (Fig. 2g). P ratio and N:P ratio of the L. principis-rupprechtii stand were higher than those of the P. crassifolia and P. tabuliformis stands; except for individual nu- Soil nutrient contents for the three plantation stands trient indexes (such as TN and N:P ratio), for which Overall, SOC, TN, and TP showed a gradually de- there was no significant difference between the sur- creasing trend from the litter layer to deep soil face and the deep soil layers. layers for the three plantation stands (Fig. 3). The Available nutrients (NH -N, NO -N, AP, and AK) in the 4 3 only exception was for the TP in the L. principis- soil also exhibited a gradually decreasing trend from the top- rupprechtii stand, where there were no significant soil to deep soil layers for the three forest stands (Fig. 4). At differences between different soil layers (Fig. 3a‒3c). the same depth, the available nutrients were highest in the L. However, there was no significant difference in soil principis-rupprechtii stand, followed by the P. crassifolia TK in the different soil layers for the three planta- stand, and were lowest in the P. tabuliformis stand (Fig. 4). tion species (Fig. 3d). Furthermore, the C:N ratio, C: The differences declined with depth in the soil profile for Fig. 3 SOC, TN, TP, TK, C:N ratio, C:P ratio, and N:P ratio in 10 cm soil layers to a depth of 30 cm under three different plantation species. Different capital letters within the same depth indicate significant difference (P < 0.05) among three different plantation species. Different lowercase letters for the same study site indicate significant differences (P < 0.05) between different soil layers. The same is the case below Han et al. Forest Ecosystems (2021) 8:3 Page 7 of 13 Fig. 4 NH -N, NO -N, AP, and AK concentrations at different soil depths (0–30 cm) under three different plantation species 4 3 the three forest stands, so there was no significant while the soil capacity, soil total porosity, and soil ca- difference in AP and AK in the deepest layer. pillary porosity of the L. principis-rupprechtii stand were higher than those of the P. crassifolia and P. Soil physical properties for the three plantation stands tabuliformis stands (Fig. 5b‒d),exceptthatthere was The different tree species also had different effects on no significant difference in the soil capillary porosity the soil physical properties of the different soil layers in the 20–30 cm layer (Fig. 5d). (Fig. 5). There was no significant difference in soil bulk density, soil capacity, soil total porosity, and soil capillary porosity in soil layers down to 30 cm under The correlation between soil nutrient contents and the P. tabuliformis stand (Fig. 5a‒d). The soil cap- physical properties acity, soil total porosity, and soil capillary porosity ex- Pearson correlation analysis was performed to evaluate hibited a gradually decreasing trend from the topsoil the correlation between soil nutrient contents and phys- to deep soil layers under L. principis-rupprechtii and ical properties (Table 2). The results revealed that the P. crassifolia stands, while soil bulk density showed SOC, TN, NH -N, NO -N, AP, and AK in the soil were the opposite trend. The soil bulk density of P. crassi- 4 3 − 1 folia (0.92–1.26 g·cm )and P. tabuliformis stands significantly positively correlated with soil capacity, total − 1 (1.15–1.16 g·cm ) was higher than that of L. porosity, and capillary porosity (P < 0.05 or P < 0.01), but − 1 principis-rupprechtii (0.76–0.94 g·cm )(Fig. 5a), there were no significant correlations between soil total Fig. 5 Soil bulk density, soil capacity, total porosity, and capillary porosity in 10 cm soil layers to a depth of 30 cm under the different plantation species Han et al. Forest Ecosystems (2021) 8:3 Page 8 of 13 Table 2 Pearson correlation coefficients between soil nutrient contents and physical properties SOC TN TP TK NH -N NO -N AP AK Soil bulk Soil Total 4 3 density capacity porosity TN 0.98** TP 0.34 0.45 TK –0.50 –0.24 –0.44 NH -N 0.81** 0.81** 0.18 –0.24 NO -N 0.72* 0.73* 0.28 –0.20 0.95** AP 0.92** 0.88** 0.17 –0.28 0.81** 0.87** AK 0.79* 0.83** 0.30 0.03 0.91** 0.88** 0.88** Soil bulk density –0.88** –0.31 –0.82** –0.71* –0.91** 0.47 –0.69* –0.73* Soil capacity 0.95** 0.96** 0.27 –0.46 0.73* 0.82** 0.78* –0.97** 0.84** Total porosity 0.80** 0.87** 0.29 –0.25 0.55 0.61 0.70* –0.95** 0.69* 0.92** Capillary 0.85** 0.84** 0.11 –0.20 0.90** 0.91** 0.91** –0.79* 0.71* porosity 0.95** 0.87** ** indicates P < 0.01, * indicates P < 0.05 porosity and NO -N, TP, and TK. However, there were to subsoil (Table 3). The different soil layers of L. significant negative correlations between soil bulk dens- principis-rupprechtii and P. crassifolia plantations had similar soil particle size composition. The sand content ity and SOC, TN, NH -N, NO -N, AP, and AK (P < 4 3 of subsoil was generally higher than topsoil, and the clay 0.05 or P < 0.01). In addition, the SOC, TN, NH -N, content of topsoil was generally higher than the subsoil. NO -N, AP, and AK contents of soil were significantly Moreover, the distribution of sand and clay contents of positively correlated with each other (P < 0.05 or P < different soil layers had higher heterogeneity for the 0.01), and the soil capacity, total porosity, and capillary Pinus tabuliformis plantation stand. porosity were also significantly positively correlated with each other (P < 0.05 or P < 0.01). These results indicated that the water permeability and water storage capacity of the soil significantly increased with increasing soil or- The relationship between soil particle-size distribution ganic matter and available nutrients. and soil physical and chemical properties Path analysis showed that soil organic carbon (SOC) had direct effects on clay (0.76), silt (0.66), and sand (–0.94), while total potassium (TK) had indirect effects on clay Soil particle‐size distribution for the three plantation (0.75), silt (0.85), sand (–0.79). The SOC and TK had nega- stands tive effects on sand, while SOC and TK had positive effects The percentages of clay and silt in the topsoil of the on clay and silt (Fig. 6). In addition, we can also find that three plantation stands were higher than those in the SOC had a positive effect on TN, while SOC had a negative deep soil, which was gradually decreasing from topsoil Table 3 Characteristics of the various soil particle-size distribution (PSD) in the three soil profiles layers of different forest types Tree species Soil depth Clay (%) Silt (%) Sand (%) < 2 µm 2.00–20.00 µm 20.00–50.00 µm 50.00–100.00 µm 100.00–250.00 µm 250.00–500.00 µm 500–2000 µm Larix principis-rupprechtii 0–10 cm 8.66 ± 0.38a 48.75 ± 0.71a 27.21 ± 0.35a 9.24 ± 0.51b 4.46 ± 0.53b 3.38 ± 0.45b 0.18 ± 0.09c 10–20 cm 8.13 ± 0.35a 43.67 ± 0.96a 25.70 ± 0.26b 10.06 ± 0.10b 6.65 ± 0.44b 6.41 ± 0.46a 1.86 ± 0.22b 20–30 cm 5.96 ± 0.50b 31.92 ± 4.49b 22.99 ± 0.34c 13.90 ± 1.21a 10.65 ± 1.44a 7.10 ± 0.46a 3.06 ± 0.55a Picea crassifolia 0–10 cm 9.23 ± 0.17a 51.35 ± 0.79a 29.63 ± 0.49a 8.61 ± 0.41b 1.40 ± 0.23b 3.79 ± 0.63c – 10–20 cm 8.03 ± 0.32a 46.45 ± 2.23a 26.93 ± 0.56a 8.43 ± 0.34b 3.70 ± 1.11ab 6.51 ± 0.38b – 20–30 cm 6.31 ± 0.58b 32.72 ± 3.49b 18.23 ± 3.84b 11.75 ± 0.61a 5.83 ± 0.77a 10.30 ± 0.74a – Pinus tabuliformis 0–10 cm 8.88 ± 0.29a 47.07 ± 0.45c 18.62 ± 2.00b 8.37 ± 0.96a 1.03 ± 0.32a 20.63 ± 1.41a – 10–20 cm 7.78 ± 0.64ab 53.15 ± 1.07b 24.99 ± 0.42a 5.95 ± 0.58b 2.11 ± 0.26b 5.89 ± 0.89b – 20–30 cm 6.46 ± 0.54b 59.03 ± 1.82a 27.66 ± 1.68a 4.12 ± 0.63b 7.37 ± 2.31c 3.02 ± 0.59b – The different lowercase letters refer to significant differences among different soil layers in the same plantation stands (P < 0.05) – indicates no data Han et al. Forest Ecosystems (2021) 8:3 Page 9 of 13 effect on soil bulk density (BD). This also confirmed the re- rupprechtii and P. crassifolia. The possible reason for sults in Table 2. these results is that the C:N and the nutrient contents of the litter are the most directly factors influencing de- composition rate and nutrient release of litters (Prescott Discussion 2010; Ge et al. 2013), and higher C:N and C:P are im- The interaction between leaves, litter, and soil nutrient portant in hindering the decomposition of litter. Con- contents for three different plantations versely, the decrease in C:N and C:P means that litter is The plant-soil feedbacks as drivers of plant community converted into a decomposed state more readily (He composition and species coexistence are increasingly be- et al. 2010). Moreover, the C:N and C:P of litter are ing recognized (Kulmatiski et al. 2008; Aponte et al. negatively correlated with decomposition rate, and the 2013; Kardol et al. 2013). Previous studies have shown litter with higher C:N and C:P needs to obtain a large that the C, N, and P contents of plants will significantly amount of N and P from external sources to accelerate affect soil nutrient contents, and they are often species- decomposition (Wang and Huang 2001; He et al. 2010). specific in different species which have different nutrient In addition, because P. tabuliformis litter is richer in lig- contents and deliver different elemental contributions to nin than L. principis-rupprechtii and P. crassifolia, de- soil (Vesterdal et al. 2008). As a result, the C:N:P stoichi- composition is hampered (He et al. 2010). This ometry of the soil will inevitably occur due to different conclusion is also confirmed by previous studies indicat- litter inputs and rhizodeposition (Wang et al. 2009; ing that the lignin/N or crude fiber/N reflects the ease of Peichl et al. 2012; Zhang et al. 2019b), which is very im- litter decomposition: decomposition rate is negatively portant to improve our understanding of the relationship correlated with this ratio (Wang and Huang 2001;He between plants and soil nutrient contents (Cleveland et al. 2010). These reasons also explain why the soil nu- and Liptzin 2007; Zhao et al. 2015). In this study, we trient contents of the P. tabuliformis plantation are found that the C:N, C:P and N:P of leaves and litter of P. lower than those of the L. principis-rupprechtii and P. tabuliformis were higher than those of L. principis- crassifolia plantations. Fig. 6 Path diagram for the relationship between soil particle-size distribution and soil physical and chemical properties. Red solid lines indicate standardized regression weights are positive paths, black solid lines indicate standardized regression weights negative paths (***: P < 0.001, **: P < 0.01, *: P < 0.05, χ /df = 3.07), and dashed lines indicate standardized regression weights are not significant (P > 0.05). The numbers in the top-right corner of each box are the squared multiple correlations, and the numbers on the lines among these parameters are the standardized regression weights Han et al. Forest Ecosystems (2021) 8:3 Page 10 of 13 Soil C:N, C:P, and N:P are important indexes for de- (Mishra et al. 2017), and the availability of potassium in termining the mineralization and fixation of soil nutri- the soil is maintained by the decomposition of organic ents during soil development (Tian et al. 2010). The N:P matter (Basumatary and Bordoloi 1992). This is the rea- of soil not only reflect the availability of P and N in the son that there is no significant difference in TK, al- forest ecosystem but also reveal nutrient movements be- though there was a significant difference in AK content tween the plants and soils (Fan et al. 2015; Cao and between different soil layers in the three stands. Chen 2017). Our research results showed that the soil nutrient contents of the three plantations gradually de- The relationship between soil nutrient contents and soil creased from the topsoil to deep soil layers. This trend physical properties for three different plantations was because that C, N and P released by litter decom- The water storage capacity of the soil is influenced by position were mainly concentrated in the topsoil layer, soil physical and chemical properties (Guzman et al. with only a small percentage of nutrients reaching the 2019). Soil bulk density and soil capacity play an import- deeper soil layers. Besides, the L. principis-rupprechtii ant role in hydrological processes, which are essential to stand had the highest soil C:N, C:P, and N:P, the C:N the supply and storage of water, nutrients, and oxygen in and C:P in leaves of P. tabuliformis were higher than the soil (Wang et al. 2010; Krainovica et al. 2020). The those of the other two species. Therefore, it can be spec- size of soil porosity plays a key role in quantifying soil ulated that the P. tabuliformis forest requires a larger structure because it can affect soil hydraulic conductiv- amount of phosphorus than L. principis-rupprechtii and ity, solute convection and water retention (Zhang et al. P. crassifoliastands, resulting in a decrease in phos- 2019a). Therefore, these indicators can be used to evalu- phorus content in the soil. These also confirm the idea ate the impact of vegetation restoration on soil proper- that the higher C:N and C:P values in plants usually rep- ties (Gu et al. 2018). The results of this study indicated resent higher N and P utilization (Wardle et al. 2004). that the SOC, TN, soil available nutrients and soil cap- acity, soil total porosity, and soil capillary porosity exhib- ited the same changing trends for different plantation Effects of three different plantations on soil nutrients species, and the correlation analysis (Table 2) also It is well known that the soil is critical to maintaining showed that the SOC, TN and available nutrient con- the productivity and sustainability of forest ecosystems, tents (NH -N, NO -N, AP, and AK) were positively 4 3 and the ability of forest soil to store and transform or- correlated with soil capacity, soil total porosity, and soil ganic material is influenced by the soil organic matter, capillary porosity, while negatively correlated with soil which can be influenced by forest vegetation types (Liu bulk density. Furthermore, soil bulk density increased et al. 2018; Xia et al. 2019). Therefore, knowledge about with the soil depth, and the differences in soil bulk dens- the soil nutrients in different forest soils is of great im- ity between the different species stands were mainly re- portance to understanding biogeochemical cycles (Yang lated to the degree of decomposition and amounts of et al. 2010). The results of this study showed that the easily decomposable litters. Our results are in agreement SOC, TN, and available nutrients (NH -N, NO -N, AP, 4 3 with previous studies showing that increases in SOC are and AK) were highest in the L. principis-rupprechtii associated with an increase in soil total porosity (Abu stand, followed by the P. crassifolia stand, and lowest in 2013) and decreases in soil bulk density (Koestel et al. the P. tabuliformis stand. Moreover, all nutrient contents 2013). Besides, there was also a significant positive cor- declined with depth in the soil profile layer in the three relation between SOC and available nutrients (NH -N, different stands. This is because L. principis-rupprechtii NO -N, AP, and AK) (Table 2). These results indicate is a deciduous coniferous species, so the biomass of litter that the soil physical characters and water conservation input is higher than that of P. crassifolia or P. tabulifor- capacity are largely affected by soil nutrient contents mis. In addition, the soil organic carbon accumulation after afforestation. may be mainly driven by litter inputs (Zhao et al. 2017), higher C:N and C:P hinder the decomposition of the lit- ter layer (He et al. 2010). This suggests that the SOC, The relationship between soil particle-size distribution TN, and available nutrient contents in the L. principis- and soil physical and chemical properties of three rupprechtii stands are higher than in the P. crassifolia different plantations and P. tabuliformis stands. Besides, the amount of potas- In general, the vegetation can not only improve soil fer- sium in the soil is directly related to the parent material tility, increase carbon storage, enhance water conserva- (Mishra et al. 2017). Potassium in plants is involved in tion capacity, etc., but also improve soil particle many important biochemical processes, such as activa- composition, reduce the content of sand and silt, in- tion of biological enzymes, ion channels, synthesis of crease the content of clay, and thus improve soil struc- macromolecules, and regulation of transpiration, etc. ture (Su et al. 2018; Xia et al. 2020). The results of this Han et al. Forest Ecosystems (2021) 8:3 Page 11 of 13 study indicated that L. principis-rupprechtii and P. cras- capacity. In conclusion, we recommend planting L. sifolia plantations could significantly improve the nutri- principis-rupprechtii and P. crassifolia as the preferred ent contents of topsoil, make the topsoil particles finer, tree species to enhance the water conservation function increase the clay content and decrease the sand content, and increase soil fertility, which should be useful for eco- compared with P. tabuliformis plantation. The main rea- logical vegetation construction and management in son is that L. principis-rupprechtii and P. crassifolia semi-arid mountain forest ecosystems. plantations had higher soil nutrient returning capacity Acknowledgements than P. tabuliformis plantations, which further increased The authors thank the personnel at the Gansu Xinglongshan National Nature the soil nutrient contents, improved the soil structure, Reserve and Gansu provincial field scientific observation and research station of mountain ecosystems for providing assistance. and promoted the formation of soil clay. The soil particle-size distribution is closely related to soil organic Authors' contributions carbon content and has a significant influence on soil or- Changming Zhao and Chun Han conceived and designed the experiments. Cankun Zhang, Yongjing Liu, and Yage Li performed the experiments. Chun ganic carbon conversion (von Lützow and Kögel-Knab- Han and Yage Li analyzed the data, Chun Han wrote the manuscript. All ner 2009). Generally, soil organic carbon is easy to authors provided editorial advice and gave final approval for publication. combine with finer soil particles (silt and clay) to form Funding organic-inorganic complexes. Meanwhile, the surface This work was supported by the Strategic Priority Research Program of the area is relatively large of silt and clay, which will expose Chinese Academy of Sciences (XDA20100101), a Major Special Science and more positive charges and combine with negatively Technology Project of Gansu Province (18ZD2FA009) and the National Natural Science Foundation of China (NSFC) (31522013). charged humus (Zhao et al. 2014). On the other hand, the finer particles have poor permeability, and the or- Availability of data and materials ganic carbon is more difficult to be decomposed by mi- The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. croorganisms once it combines with them. Compared with finer clay, sand particles are opposite to each other. Ethics approval and consent to participate Because sand has fewer positive charge sites and larger Not applicable. particles, they have fewer opportunities to combine with Consent for publication organic carbon. Moreover, sand has strong permeability, Not applicable. looser soil structure and poorer soil water holding cap- Competing interests acity, which can be easily decomposed by microorgan- The authors declare that they have no competing interests. isms (Zhao et al. 2014; Xia et al. 2020). Therefore, this is also the reason why the clay has a negative effect on soil Received: 6 August 2020 Accepted: 11 January 2021 bulk density. References Conclusions Abu ST (2013) Evaluating long-term impact of land use on selected soil physical quality indicators. 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Effects of three coniferous plantation species on plant‐soil feedbacks and soil physical and chemical properties in semi‐arid mountain ecosystems

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10.1186/s40663-021-00281-4
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Abstract

Background: Large-scale afforestation can significantly change the ground cover and soil physicochemical properties, especially the soil fertility maintenance and water conservation functions of artificial forests, which are very important in semi-arid mountain ecosystems. However, how different tree species affect soil nutrients and soil physicochemical properties after afforestation, and which is the best plantation species for improving soil fertility and water conservation functions remain largely unknown. Methods: This study investigated the soil nutrient contents of three different plantations (Larix principis-rupprechtii, Picea crassifolia, Pinus tabuliformis), soils and plant-soil feedbacks, as well as the interactions between soil physicochemical properties. Results: The results revealed that the leaves and litter layers strongly influenced soil nutrient availability through biogeochemical processes: P. tabuliformis had higher organic carbon, ratio of organic carbon to total nitrogen (C:N) and organic carbon to total phosphorus (C:P) in the leaves and litter layers than L. principis-rupprechtii or P. crassifolia, suggesting that higher C:N and C:P hindered litter decomposition. As a result, the L. principis-rupprechtii and P. crassifolia plantation forests significantly improved soil nutrients and clay components, compared with the P. tabuliformis plantation forest. Furthermore, the L. principis-rupprechtii and P. crassifolia plantation forests significantly improved the soil capacity, soil total porosity, and capillary porosity, decreased soil bulk density, and enhanced water storage capacity, compared with the P. tabuliformis plantation forest. The results of this study showed that, the strong link between plants and soil was tightly coupled to C:N and C:P, and there was a close correlation between soil particle size distribution and soil physicochemical properties. Conclusions: Therefore, our results recommend planting the L. principis-rupprechtii and P. crassifolia as the preferred tree species to enhance the soil fertility and water conservation functions, especially in semi-arid regions mountain forest ecosystems. Keywords: Plantation, C:N:P stoichiometry, Plant‐soil feedbacks, Soil physicochemical properties, Mountain ecosystems * Correspondence: zhaochm@lzu.edu.cn State Key Laboratory of Grassland and Agro-Ecosystems, School of Life Sciences, Lanzhou University, 730000 Lanzhou, China Gansu Provincial Field Scientific Observation and Research Station of Mountain Ecosystems, 730000 Lanzhou, China © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Han et al. Forest Ecosystems (2021) 8:3 Page 2 of 13 Introduction processes, which play a key role in determining plant The reforestation remains one of the most effective growth, community composition, and individual prod- strategies for coping with climate change (Jean-Francois uctivity (van der Putten et al. 2013). Besides, different et al. 2019), which is also the most effective management plant species tend to have species-specific effects on soil method to solve the problems of soil erosion all over the quality and quantity (Hobbie et al. 2006; Ayres et al. world (Clemente et al. 2004; Kou et al. 2016). It is con- 2009), and they also change the physical, chemical, and sidered to be an effective strategy to prevent soil erosion biological properties of soil (Qiao et al. 2019). Thus, and degradation and to promote the restoration of de- aboveground and belowground processes of forest eco- graded ecosystems (Zhang et al. 2011). For the past three systems determine plant-soil feedbacks and influence the decades, to prevent soil erosion and desertification and composition of the plant community and nutrient cyc- improve water conservation capacity, the Grain to Green ling processes (Kardol et al. 2006; van der Putten et al. Program (GTGP) has been implemented by the Chinese 2013), potentially affecting ecosystem functioning, such government (Chang et al. 2012). Large-scale afforest- as interactions between plants and other communities ation increased ground cover and caused changes in soil (van der Putten et al. 2013), conserving water resource physical and chemical properties (Fu et al. 2010). Forests and preventing soil losses. Therefore, understanding the as ecosystem engineers not only have species-specific ef- relationships between plantation types and soil physico- fects on soil physicochemical properties and soil com- chemical properties is of great significance for the soil munities (soil animal communities and soil microbial and water conservation, nutrient cycling, and soil health communities) (Vesterdal et al. 2008; Prescott and Grays- assessment of forest stands. ton 2013), but also regulate climate, mineral cycling and Soil particle-size distribution (PSD) refers to the per- prevent soil erosion (Kozlowski 2002). Besides, artificial centage of each particle size class in the soil, which can forests could potentially lead to circulation and feedback reflect the influence of soil water movement, solute effects of mineral nutrients between above-ground and transport, nutrient status, and vegetation types on soil below-ground ecosystems (Wang et al. 2009; Peichl et al. texture (Sun et al. 2016). Soil texture is divided into clay, 2012). Therefore, the study of vegetation restoration silt, and sand, which is one of the important physical pa- processes and their impacts on nutrient cycling and soil rameters of soil (Hu et al. 2011; Mohammadi and properties will provide an important guide to forest Meskini-Vishikaee 2013; Xu et al. 2013). The change of management aimed at improving the ecological restor- soil particle-size distribution is the result of the com- ation of natural and artificial forests, especially in semi- bined effects of soil evolution, vegetation restoration, arid mountain ecosystem regions. and environmental factors. Soil texture and organic mat- It is well known that vegetation is an important factor ter are the key factors affecting soil particle size (Qi affecting soil physical and chemical properties. Leaves of et al. 2018). Previous studies have shown that the above- different tree species have generated species-specific ef- ground part of plants can effectively increase the rough- fects on litter layer decomposition and nutrients released ness of the surface, thus increasing the content of fine into the soil (Norris et al. 2012; Aponte et al. 2013). Tree particles and nutrients in the soil, leading to the change species affect soil nutrient mineralization and availability of soil structure (Xiang et al. 2015). However, the rela- through soil microorganisms, thus affecting soil fertility tionship between soil physicochemical properties and (Aponte et al. 2013; Huang et al. 2013). Previous studies soil particle-size distribution and their effects on water have shown that environmental factors influence leaves conservation functions are scarce. and then affect many service functions of the ecosystems Xinglong Mountain is an important water conserva- (Ayres et al. 2009; Aponte et al. 2013). Thus, leaf quality tion area on semi-arid land in northwestern China. Since largely determines the decomposition of litter, as well as the implementation of China’s Three-North Shelterbelt the release of nutrients and minerals into the soil (Norris forest program in the 1980s, a large-scale artificial affor- et al. 2012; Aponte et al. 2013), indicating the relation- estation project has been carried out in Xinglong moun- ship among leaves, litter, and soil (Lucas-Borja et al. tain, and the planted forest species were Larix principis- 2018). However, the studies about the effects of leaves rupprechtii, Picea crassifolia, Pinus tabuliformis. Al- and litter from different tree species on soil organic car- though artificial afforestation has been carried out for bon, nitrogen cycling, and water conservation functions many years, there is no systematic evaluation of the soil in semi-arid mountain forest ecosystems are still lacking. and water conservation capacity and ecological construc- Soil plays an important fertility and stability function tion benefits of the plantations. In this study, we in forest ecosystems (Lucas-Borja et al. 2018), and it dir- hypothesize that there is a strong feedback effect of nu- ectly or indirectly regulates and influences many bio- trients between plants and soil. Tree species may influ- logical processes (Zhang et al. 2018). Soil properties are ence the soil organic carbon (SOC), total nitrogen (TN), determined by chemical, physical and biological and total phosphorus (TP) of different afforestation and Han et al. Forest Ecosystems (2021) 8:3 Page 3 of 13 then will affect the soil physicochemical properties, The climate in this region is classified as semi-arid con- structure, and texture. This study aimed to: (1) investi- tinental monsoon climate, and the annual precipitation gate the influence of three different tree species on the is about 450–622 mm. The precipitation frequency is nutrient status of plants and soil and plant-soil feed- not uniform, mostly concentrated in July to September. backs; (2) analyse the effects of three different tree spe- The effective accumulated temperature was 1800– cies on soil physical and chemical properties; and (3) 2800 °C, and the average annual relative air humidity explore the impacts of soil physical and chemical prop- was 68 %. erties of three different forest stands on soil particle-size distribution characteristics and their influence factors. We selected three study sites with different dominant Therefore, the results of this study can provide theoret- tree species planted 30 years ago, the planting distance is ical guidance in the selection of forest species for affor- about 4 m × 4 m, and all the plantations are in semi- estation and forest management, particularly in the sunny slope. The distance between each study site is less semi-arid mountain forest ecosystems. than 10 km, and the environmental, meteorological, soil and the parent material among stands were homoge- Materials and Methods neous. More basic information of the three plantation Study site description stands was summarized in Table 1. The type of lands be- The research area is located in the Gansu Xinglongshan fore plantations is a natural succession of grassland, no National Nature Reserve (35°44′20.12′′ N, 104°1′3.07′′ human disturbance and management to the forests and E, 2778 m a.s.l.), in the Loess Plateau, China (Fig. 1). As soils since the plantation. During the growth and succes- a “green rock island” in the Loess Plateau, it is an im- sion of different tree species, the soil physicochemical portant water conservation forest and biodiversity pro- properties changed accordingly, thus potentially affecting tection area in the upper reaches of the Yellow River. ecosystem functioning. Therefore, these differences Fig. 1 The location map of Xinglong Mountain in the Loess Plateau of China and sample plot information (A: L. principis-rupprechtii forest, B: P. crassifolia forest, C: P. tabuliformis forest) Han et al. Forest Ecosystems (2021) 8:3 Page 4 of 13 Table 1 The basic information of traits of the three plantation stands − 1 Forest stands Stand density (trees·ha ) Average DBH (cm) Average height (m) LAI Slope L. principis-rupprechtii 608 26.19 16.43 3.49 5° P. crassifolia 560 26.04 12.97 4.17 4.5° P. tabuliformis 592 23.69 12.10 2.68 8° among stands can be attributed to tree species. There determine soil physiochemical properties and particle- were a large amount of herbaceous vegetation (i.e., size distribution (PSD). Soil organic carbon (SOC) con- Carex rigescens, Fragaria orientalis, Aconitum sinomon- tent were determined using the K Cr O -H SO oxida- 2 2 7 2 4 tanum and Potentilla bifurca) and shrubs (i.e., Sorbus tion method (Bao 2000; Wang 2009). Soil total nitrogen koeheana, Berberis kansuensis, Rosa sweginzowii, Coto- (TN) values were determined using the micro-Kjeldahl neaster multiflorus, Spiraea alpine and Lonicera hispida) method (Yang et al. 2018), whilst soil total phosphorus growing on the forest floor and the litter thickness was (TP) and total potassium (TK) values were determined about 10 cm. colorimetrically (ammonium molybdate method) and flame photometer after wet digestion with HClO - H SO (Bao 2000; Cao and Chen 2017), respectively. In- 2 4 Analysis methods of nutrient contents in the leaves and organic nitrogen in the form of nitrate nitrogen litter layers (NO -N) and ammonium nitrogen (NH -N) were de- 3 4 Three sample plots (25 m × 25 m) in each forest stand termined through colorimetry (Bao 2000), and available − 1 were randomly selected, and two trees or points were se- phosphorus (AP) was extracted with 0.5 mol·L lected randomly in each sample plot to collect leaves NaHCO , then determined by molybdenum-antimony (i.e., needles), soil, and litter samples. There are six repli- colorimetry (Bao 2000; Kou et al. 2016). Available potas- − 1 cates for leaves, soil, or litter samples in each forest sium (AK) was extracted with 1 mol·L CH COONH 3 4 stand. The leaf samples were randomly collected from then determined by flame photometry (Bao 2000; Zhou each of the three different forest stand sites in August et al. 2015). TN, TP, NO -N and NH -N were mea- 3 4 2018, and litter samples were sampled under the canopy sured using an automatic intermittent chemical analyzer of each selected tree (The distance between each sam- (SmartChem140, France). The AK and TK in the soil pling tree or point is greater than 10 m. The collected were determined using flame atomic absorption spectro- − 1 litter is mainly fallen needles of trees). Leaves and litter photometric method (detection limit is 0–1000 mg·L ) samples were processed in a grinder (dried to constant (Aurora, AI-1200, Canada). weight at 75 °C) and sieved through a 60-mesh sieve. To determine soil physical properties, undisturbed Organic carbon values of the leaf and litter layer were samples were obtained from the 0–10, 10–20 and 20– determined using the K Cr O -H SO oxidation method 2 2 7 2 4 30 cm soil layers using a ring knife at each typically re- (Bao 2000; Wang 2009), the total nitrogen (TN) values peated plots for three different forest stands (six intact were determined using the micro-Kjeldahl method (Bao soil cores were obtained from each of the three soil 2000; Zhang et al. 2019a), whilst total phosphorus (TP) layers for each forest stand). The bulk density and soil values of leaf and litter layer were determined colorimet- capacity of the soil samples were measured using the rically (ammonium molybdate method) after wet diges- method exposed by Zhang et al. (2019b). The total por- tion with H O -H SO , and the total potassium (TK) 2 2 2 4 osity was determined by measuring soil moisture content values were determined using an atomic absorption at saturation (total volume of water-filled soil pores) and − 1 spectrophotometer (detection limit is 0–1000 mg·L ) capillary porosity (capillary porosity is the percentage of (Aurora, AI-1200, Canada) after wet digestion with soil voids in soil volume) was determined with the H O -H SO (Bao 2000; Zhang et al. 2019a). 2 2 2 4 method exposed by Qiu et al. (2019). Analysis methods of soil physical and chemical properties To determine soil nutrient contents, the soil samples Determination of the soil particle-size distribution of the were collected from the 0–10, 10–20 and 20–30 cm soil soil samples layers at each site. We randomly selected two pionts in The soil particle-size distribution was measured using a each sample plot (25 m × 25 m). For each forest stand, laser particle analyzer (Mastersizer 2000, Malvern Com- 18 soil samples, 6 leaf samples, and 6 litter samples were pany, UK), each 0.25 g soil sample was pretreated with collected. Totally, 48 soil samples, 18 leaf samples, and 10 % H O solution to remove organic matter, and 10 % 2 2 18 litter samples were collected. Air-dried soil samples HCl solution was added to remove carbonate salts. Add screened by 2- and 0.15-mm mesh sieve were used to deionized water to soak for 12 h, then the liquid Han et al. Forest Ecosystems (2021) 8:3 Page 5 of 13 supernatant was removed. The samples were chemically likelihood method to build a path model. All statistical − 1 dispersed with 0.06 mol·L sodium hexametaphosphate analyses were performed using SPSS 26.0 and AMOS and were mechanically dispersed in an ultrasonic bath 24.0 (SPSS Inc. an IBM Company, Chicago, IL, USA), for 10 min (Qi et al. 2018). The measurements were re- and all figures were prepared with Origin 2020 software peated three times for each sample, and the soil particle- (Origin Lab Inc., Northampton, MA, USA). size distribution (PSD) was classified into clay (< 2 µm), silt (2–50 µm), and sand (50–2000 µm) according to Results United States Department of Agriculture classification Nutrient contents of the leaves and litter layers for the (USDA) classification system (Xia et al. 2020; Zhai et al. three plantations 2020). The content of organic carbon (OC), TN, TP, TK, and C:N:P stoichiometry were different in leaves and Statistical analyses litter layers for different tree species (Fig. 2). The or- The effects of different forest species on the physical and ganic carbon content in the leaves and litter of P. chemical properties of the soil, nutrient contents in the tabuliformis was significantly higher than that of L. vegetation and litter layers, and soil particle-size distri- principis-rupprechtii (14 % and 2 % more, respectively) bution (PSD) were evaluated using one-way ANOVA and P. crassifolia (16 % and 3 % more, respectively) (the normal distribution and homogeneity of variance of (Fig. 2a). However, the content of N, P, and K in the the data had been checked), followed by least significant leaves and litter of P. tabuliformis was lower than difference (LSD) tests for different soil layer (P < 0.05). that of L. principis-rupprechtii (N: 36 % and 44 % less, Pearson correlation analysis was undertaken to identify P: 43 % and 45 % less, K: 37 % and 34 % less, respect- the relationships between SOC, TN, TP, TK, bulk dens- ively) and P. crassifolia (N: 46% and 25% less, P: ity, soil capacity, total porosity, and capillary porosity. 65 % and 30 % less, K: 24 % and 21 % less, respect- The relationship between soil physicochemical proper- ively) (Fig. 2b‒2d). The C:N ratio, C:P ratio and N:P ties and soil particle-size distribution was analyzed by ratio of leaves of P. tabuliformis were markedly higher confirmatory factor analysis using the maximum than that of L. principis-rupprechtii, but these ratios Fig. 2 Differences in OC, TN, TP, TK contents, and C:N:P stoichiometry in leaves and litter for three different plantation species. Different lowercase letters indicate significant differences (P < 0.05) among different plantation species Han et al. Forest Ecosystems (2021) 8:3 Page 6 of 13 of P. crassifolia were significantly lower than those of L. P ratio, and N:P ratio exhibited a gradually decreas- principis-rupprechtii (Fig. 2e‒2 g). The C:N ratio and C:P ra- ing trend from surface soil layers to deep soil layers; tio of the litter of P. tabuliformis were the highest, and were the exceptions were the C:N ratio of the P. crassifo- significantly higher in P. crassifolia than in L. principis- lia stand and the C:P ratio and N:P ratio of the P. rupprechtii (Fig. 2e‒2f). The N:P ratio of the litter of P. tabu- tabuliformis stand, where there was no significant liformis was higher than that of L. principis-rupprechtii and difference between the different soil layers (Fig. 3e‒ P. crassifolia,and therewas no statisticdifferencebetween L. 3g). On thewhole,the SOC, TN,TP, C:Nratio,C: principis-rupprechtii and P. crassifolia (Fig. 2g). P ratio and N:P ratio of the L. principis-rupprechtii stand were higher than those of the P. crassifolia and P. tabuliformis stands; except for individual nu- Soil nutrient contents for the three plantation stands trient indexes (such as TN and N:P ratio), for which Overall, SOC, TN, and TP showed a gradually de- there was no significant difference between the sur- creasing trend from the litter layer to deep soil face and the deep soil layers. layers for the three plantation stands (Fig. 3). The Available nutrients (NH -N, NO -N, AP, and AK) in the 4 3 only exception was for the TP in the L. principis- soil also exhibited a gradually decreasing trend from the top- rupprechtii stand, where there were no significant soil to deep soil layers for the three forest stands (Fig. 4). At differences between different soil layers (Fig. 3a‒3c). the same depth, the available nutrients were highest in the L. However, there was no significant difference in soil principis-rupprechtii stand, followed by the P. crassifolia TK in the different soil layers for the three planta- stand, and were lowest in the P. tabuliformis stand (Fig. 4). tion species (Fig. 3d). Furthermore, the C:N ratio, C: The differences declined with depth in the soil profile for Fig. 3 SOC, TN, TP, TK, C:N ratio, C:P ratio, and N:P ratio in 10 cm soil layers to a depth of 30 cm under three different plantation species. Different capital letters within the same depth indicate significant difference (P < 0.05) among three different plantation species. Different lowercase letters for the same study site indicate significant differences (P < 0.05) between different soil layers. The same is the case below Han et al. Forest Ecosystems (2021) 8:3 Page 7 of 13 Fig. 4 NH -N, NO -N, AP, and AK concentrations at different soil depths (0–30 cm) under three different plantation species 4 3 the three forest stands, so there was no significant while the soil capacity, soil total porosity, and soil ca- difference in AP and AK in the deepest layer. pillary porosity of the L. principis-rupprechtii stand were higher than those of the P. crassifolia and P. Soil physical properties for the three plantation stands tabuliformis stands (Fig. 5b‒d),exceptthatthere was The different tree species also had different effects on no significant difference in the soil capillary porosity the soil physical properties of the different soil layers in the 20–30 cm layer (Fig. 5d). (Fig. 5). There was no significant difference in soil bulk density, soil capacity, soil total porosity, and soil capillary porosity in soil layers down to 30 cm under The correlation between soil nutrient contents and the P. tabuliformis stand (Fig. 5a‒d). The soil cap- physical properties acity, soil total porosity, and soil capillary porosity ex- Pearson correlation analysis was performed to evaluate hibited a gradually decreasing trend from the topsoil the correlation between soil nutrient contents and phys- to deep soil layers under L. principis-rupprechtii and ical properties (Table 2). The results revealed that the P. crassifolia stands, while soil bulk density showed SOC, TN, NH -N, NO -N, AP, and AK in the soil were the opposite trend. The soil bulk density of P. crassi- 4 3 − 1 folia (0.92–1.26 g·cm )and P. tabuliformis stands significantly positively correlated with soil capacity, total − 1 (1.15–1.16 g·cm ) was higher than that of L. porosity, and capillary porosity (P < 0.05 or P < 0.01), but − 1 principis-rupprechtii (0.76–0.94 g·cm )(Fig. 5a), there were no significant correlations between soil total Fig. 5 Soil bulk density, soil capacity, total porosity, and capillary porosity in 10 cm soil layers to a depth of 30 cm under the different plantation species Han et al. Forest Ecosystems (2021) 8:3 Page 8 of 13 Table 2 Pearson correlation coefficients between soil nutrient contents and physical properties SOC TN TP TK NH -N NO -N AP AK Soil bulk Soil Total 4 3 density capacity porosity TN 0.98** TP 0.34 0.45 TK –0.50 –0.24 –0.44 NH -N 0.81** 0.81** 0.18 –0.24 NO -N 0.72* 0.73* 0.28 –0.20 0.95** AP 0.92** 0.88** 0.17 –0.28 0.81** 0.87** AK 0.79* 0.83** 0.30 0.03 0.91** 0.88** 0.88** Soil bulk density –0.88** –0.31 –0.82** –0.71* –0.91** 0.47 –0.69* –0.73* Soil capacity 0.95** 0.96** 0.27 –0.46 0.73* 0.82** 0.78* –0.97** 0.84** Total porosity 0.80** 0.87** 0.29 –0.25 0.55 0.61 0.70* –0.95** 0.69* 0.92** Capillary 0.85** 0.84** 0.11 –0.20 0.90** 0.91** 0.91** –0.79* 0.71* porosity 0.95** 0.87** ** indicates P < 0.01, * indicates P < 0.05 porosity and NO -N, TP, and TK. However, there were to subsoil (Table 3). The different soil layers of L. significant negative correlations between soil bulk dens- principis-rupprechtii and P. crassifolia plantations had similar soil particle size composition. The sand content ity and SOC, TN, NH -N, NO -N, AP, and AK (P < 4 3 of subsoil was generally higher than topsoil, and the clay 0.05 or P < 0.01). In addition, the SOC, TN, NH -N, content of topsoil was generally higher than the subsoil. NO -N, AP, and AK contents of soil were significantly Moreover, the distribution of sand and clay contents of positively correlated with each other (P < 0.05 or P < different soil layers had higher heterogeneity for the 0.01), and the soil capacity, total porosity, and capillary Pinus tabuliformis plantation stand. porosity were also significantly positively correlated with each other (P < 0.05 or P < 0.01). These results indicated that the water permeability and water storage capacity of the soil significantly increased with increasing soil or- The relationship between soil particle-size distribution ganic matter and available nutrients. and soil physical and chemical properties Path analysis showed that soil organic carbon (SOC) had direct effects on clay (0.76), silt (0.66), and sand (–0.94), while total potassium (TK) had indirect effects on clay Soil particle‐size distribution for the three plantation (0.75), silt (0.85), sand (–0.79). The SOC and TK had nega- stands tive effects on sand, while SOC and TK had positive effects The percentages of clay and silt in the topsoil of the on clay and silt (Fig. 6). In addition, we can also find that three plantation stands were higher than those in the SOC had a positive effect on TN, while SOC had a negative deep soil, which was gradually decreasing from topsoil Table 3 Characteristics of the various soil particle-size distribution (PSD) in the three soil profiles layers of different forest types Tree species Soil depth Clay (%) Silt (%) Sand (%) < 2 µm 2.00–20.00 µm 20.00–50.00 µm 50.00–100.00 µm 100.00–250.00 µm 250.00–500.00 µm 500–2000 µm Larix principis-rupprechtii 0–10 cm 8.66 ± 0.38a 48.75 ± 0.71a 27.21 ± 0.35a 9.24 ± 0.51b 4.46 ± 0.53b 3.38 ± 0.45b 0.18 ± 0.09c 10–20 cm 8.13 ± 0.35a 43.67 ± 0.96a 25.70 ± 0.26b 10.06 ± 0.10b 6.65 ± 0.44b 6.41 ± 0.46a 1.86 ± 0.22b 20–30 cm 5.96 ± 0.50b 31.92 ± 4.49b 22.99 ± 0.34c 13.90 ± 1.21a 10.65 ± 1.44a 7.10 ± 0.46a 3.06 ± 0.55a Picea crassifolia 0–10 cm 9.23 ± 0.17a 51.35 ± 0.79a 29.63 ± 0.49a 8.61 ± 0.41b 1.40 ± 0.23b 3.79 ± 0.63c – 10–20 cm 8.03 ± 0.32a 46.45 ± 2.23a 26.93 ± 0.56a 8.43 ± 0.34b 3.70 ± 1.11ab 6.51 ± 0.38b – 20–30 cm 6.31 ± 0.58b 32.72 ± 3.49b 18.23 ± 3.84b 11.75 ± 0.61a 5.83 ± 0.77a 10.30 ± 0.74a – Pinus tabuliformis 0–10 cm 8.88 ± 0.29a 47.07 ± 0.45c 18.62 ± 2.00b 8.37 ± 0.96a 1.03 ± 0.32a 20.63 ± 1.41a – 10–20 cm 7.78 ± 0.64ab 53.15 ± 1.07b 24.99 ± 0.42a 5.95 ± 0.58b 2.11 ± 0.26b 5.89 ± 0.89b – 20–30 cm 6.46 ± 0.54b 59.03 ± 1.82a 27.66 ± 1.68a 4.12 ± 0.63b 7.37 ± 2.31c 3.02 ± 0.59b – The different lowercase letters refer to significant differences among different soil layers in the same plantation stands (P < 0.05) – indicates no data Han et al. Forest Ecosystems (2021) 8:3 Page 9 of 13 effect on soil bulk density (BD). This also confirmed the re- rupprechtii and P. crassifolia. The possible reason for sults in Table 2. these results is that the C:N and the nutrient contents of the litter are the most directly factors influencing de- composition rate and nutrient release of litters (Prescott Discussion 2010; Ge et al. 2013), and higher C:N and C:P are im- The interaction between leaves, litter, and soil nutrient portant in hindering the decomposition of litter. Con- contents for three different plantations versely, the decrease in C:N and C:P means that litter is The plant-soil feedbacks as drivers of plant community converted into a decomposed state more readily (He composition and species coexistence are increasingly be- et al. 2010). Moreover, the C:N and C:P of litter are ing recognized (Kulmatiski et al. 2008; Aponte et al. negatively correlated with decomposition rate, and the 2013; Kardol et al. 2013). Previous studies have shown litter with higher C:N and C:P needs to obtain a large that the C, N, and P contents of plants will significantly amount of N and P from external sources to accelerate affect soil nutrient contents, and they are often species- decomposition (Wang and Huang 2001; He et al. 2010). specific in different species which have different nutrient In addition, because P. tabuliformis litter is richer in lig- contents and deliver different elemental contributions to nin than L. principis-rupprechtii and P. crassifolia, de- soil (Vesterdal et al. 2008). As a result, the C:N:P stoichi- composition is hampered (He et al. 2010). This ometry of the soil will inevitably occur due to different conclusion is also confirmed by previous studies indicat- litter inputs and rhizodeposition (Wang et al. 2009; ing that the lignin/N or crude fiber/N reflects the ease of Peichl et al. 2012; Zhang et al. 2019b), which is very im- litter decomposition: decomposition rate is negatively portant to improve our understanding of the relationship correlated with this ratio (Wang and Huang 2001;He between plants and soil nutrient contents (Cleveland et al. 2010). These reasons also explain why the soil nu- and Liptzin 2007; Zhao et al. 2015). In this study, we trient contents of the P. tabuliformis plantation are found that the C:N, C:P and N:P of leaves and litter of P. lower than those of the L. principis-rupprechtii and P. tabuliformis were higher than those of L. principis- crassifolia plantations. Fig. 6 Path diagram for the relationship between soil particle-size distribution and soil physical and chemical properties. Red solid lines indicate standardized regression weights are positive paths, black solid lines indicate standardized regression weights negative paths (***: P < 0.001, **: P < 0.01, *: P < 0.05, χ /df = 3.07), and dashed lines indicate standardized regression weights are not significant (P > 0.05). The numbers in the top-right corner of each box are the squared multiple correlations, and the numbers on the lines among these parameters are the standardized regression weights Han et al. Forest Ecosystems (2021) 8:3 Page 10 of 13 Soil C:N, C:P, and N:P are important indexes for de- (Mishra et al. 2017), and the availability of potassium in termining the mineralization and fixation of soil nutri- the soil is maintained by the decomposition of organic ents during soil development (Tian et al. 2010). The N:P matter (Basumatary and Bordoloi 1992). This is the rea- of soil not only reflect the availability of P and N in the son that there is no significant difference in TK, al- forest ecosystem but also reveal nutrient movements be- though there was a significant difference in AK content tween the plants and soils (Fan et al. 2015; Cao and between different soil layers in the three stands. Chen 2017). Our research results showed that the soil nutrient contents of the three plantations gradually de- The relationship between soil nutrient contents and soil creased from the topsoil to deep soil layers. This trend physical properties for three different plantations was because that C, N and P released by litter decom- The water storage capacity of the soil is influenced by position were mainly concentrated in the topsoil layer, soil physical and chemical properties (Guzman et al. with only a small percentage of nutrients reaching the 2019). Soil bulk density and soil capacity play an import- deeper soil layers. Besides, the L. principis-rupprechtii ant role in hydrological processes, which are essential to stand had the highest soil C:N, C:P, and N:P, the C:N the supply and storage of water, nutrients, and oxygen in and C:P in leaves of P. tabuliformis were higher than the soil (Wang et al. 2010; Krainovica et al. 2020). The those of the other two species. Therefore, it can be spec- size of soil porosity plays a key role in quantifying soil ulated that the P. tabuliformis forest requires a larger structure because it can affect soil hydraulic conductiv- amount of phosphorus than L. principis-rupprechtii and ity, solute convection and water retention (Zhang et al. P. crassifoliastands, resulting in a decrease in phos- 2019a). Therefore, these indicators can be used to evalu- phorus content in the soil. These also confirm the idea ate the impact of vegetation restoration on soil proper- that the higher C:N and C:P values in plants usually rep- ties (Gu et al. 2018). The results of this study indicated resent higher N and P utilization (Wardle et al. 2004). that the SOC, TN, soil available nutrients and soil cap- acity, soil total porosity, and soil capillary porosity exhib- ited the same changing trends for different plantation Effects of three different plantations on soil nutrients species, and the correlation analysis (Table 2) also It is well known that the soil is critical to maintaining showed that the SOC, TN and available nutrient con- the productivity and sustainability of forest ecosystems, tents (NH -N, NO -N, AP, and AK) were positively 4 3 and the ability of forest soil to store and transform or- correlated with soil capacity, soil total porosity, and soil ganic material is influenced by the soil organic matter, capillary porosity, while negatively correlated with soil which can be influenced by forest vegetation types (Liu bulk density. Furthermore, soil bulk density increased et al. 2018; Xia et al. 2019). Therefore, knowledge about with the soil depth, and the differences in soil bulk dens- the soil nutrients in different forest soils is of great im- ity between the different species stands were mainly re- portance to understanding biogeochemical cycles (Yang lated to the degree of decomposition and amounts of et al. 2010). The results of this study showed that the easily decomposable litters. Our results are in agreement SOC, TN, and available nutrients (NH -N, NO -N, AP, 4 3 with previous studies showing that increases in SOC are and AK) were highest in the L. principis-rupprechtii associated with an increase in soil total porosity (Abu stand, followed by the P. crassifolia stand, and lowest in 2013) and decreases in soil bulk density (Koestel et al. the P. tabuliformis stand. Moreover, all nutrient contents 2013). Besides, there was also a significant positive cor- declined with depth in the soil profile layer in the three relation between SOC and available nutrients (NH -N, different stands. This is because L. principis-rupprechtii NO -N, AP, and AK) (Table 2). These results indicate is a deciduous coniferous species, so the biomass of litter that the soil physical characters and water conservation input is higher than that of P. crassifolia or P. tabulifor- capacity are largely affected by soil nutrient contents mis. In addition, the soil organic carbon accumulation after afforestation. may be mainly driven by litter inputs (Zhao et al. 2017), higher C:N and C:P hinder the decomposition of the lit- ter layer (He et al. 2010). This suggests that the SOC, The relationship between soil particle-size distribution TN, and available nutrient contents in the L. principis- and soil physical and chemical properties of three rupprechtii stands are higher than in the P. crassifolia different plantations and P. tabuliformis stands. Besides, the amount of potas- In general, the vegetation can not only improve soil fer- sium in the soil is directly related to the parent material tility, increase carbon storage, enhance water conserva- (Mishra et al. 2017). Potassium in plants is involved in tion capacity, etc., but also improve soil particle many important biochemical processes, such as activa- composition, reduce the content of sand and silt, in- tion of biological enzymes, ion channels, synthesis of crease the content of clay, and thus improve soil struc- macromolecules, and regulation of transpiration, etc. ture (Su et al. 2018; Xia et al. 2020). The results of this Han et al. Forest Ecosystems (2021) 8:3 Page 11 of 13 study indicated that L. principis-rupprechtii and P. cras- capacity. In conclusion, we recommend planting L. sifolia plantations could significantly improve the nutri- principis-rupprechtii and P. crassifolia as the preferred ent contents of topsoil, make the topsoil particles finer, tree species to enhance the water conservation function increase the clay content and decrease the sand content, and increase soil fertility, which should be useful for eco- compared with P. tabuliformis plantation. The main rea- logical vegetation construction and management in son is that L. principis-rupprechtii and P. crassifolia semi-arid mountain forest ecosystems. plantations had higher soil nutrient returning capacity Acknowledgements than P. tabuliformis plantations, which further increased The authors thank the personnel at the Gansu Xinglongshan National Nature the soil nutrient contents, improved the soil structure, Reserve and Gansu provincial field scientific observation and research station of mountain ecosystems for providing assistance. and promoted the formation of soil clay. The soil particle-size distribution is closely related to soil organic Authors' contributions carbon content and has a significant influence on soil or- Changming Zhao and Chun Han conceived and designed the experiments. Cankun Zhang, Yongjing Liu, and Yage Li performed the experiments. Chun ganic carbon conversion (von Lützow and Kögel-Knab- Han and Yage Li analyzed the data, Chun Han wrote the manuscript. All ner 2009). Generally, soil organic carbon is easy to authors provided editorial advice and gave final approval for publication. combine with finer soil particles (silt and clay) to form Funding organic-inorganic complexes. Meanwhile, the surface This work was supported by the Strategic Priority Research Program of the area is relatively large of silt and clay, which will expose Chinese Academy of Sciences (XDA20100101), a Major Special Science and more positive charges and combine with negatively Technology Project of Gansu Province (18ZD2FA009) and the National Natural Science Foundation of China (NSFC) (31522013). charged humus (Zhao et al. 2014). On the other hand, the finer particles have poor permeability, and the or- Availability of data and materials ganic carbon is more difficult to be decomposed by mi- The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. croorganisms once it combines with them. Compared with finer clay, sand particles are opposite to each other. Ethics approval and consent to participate Because sand has fewer positive charge sites and larger Not applicable. particles, they have fewer opportunities to combine with Consent for publication organic carbon. Moreover, sand has strong permeability, Not applicable. looser soil structure and poorer soil water holding cap- Competing interests acity, which can be easily decomposed by microorgan- The authors declare that they have no competing interests. isms (Zhao et al. 2014; Xia et al. 2020). Therefore, this is also the reason why the clay has a negative effect on soil Received: 6 August 2020 Accepted: 11 January 2021 bulk density. References Conclusions Abu ST (2013) Evaluating long-term impact of land use on selected soil physical quality indicators. 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Published: Jan 21, 2021

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