Lignin and Cellulose Contents in Chinese Red Pine ( Pinus tabuliformis Carr.) Plantations Varied in Stand Structure, Soil Property, and Regional Climate

: The reserve of li�er is expected to be reduced on the forest ﬂoors of pine plantations dually for the prevention of high risks of forest ﬁres and with a more practical probability of reuse. Lignin and cellulose are the two key constitutive components in li�er residues that account for the highest proportion of carbon but are the last to be fully decomposed. The existing trials started examining the mechanisms behind decomposing these two components in response to the combined driving forces of microclimatic factors, forest structure, and stand properties. However, the results were mostly limited to a local-scale ecosystem, and the evidence was reported to be highly sca�ered across varied conditions globally. Awareness about the combined eﬀects of the driving forces behind the lignin and cellulose contents in the li�er of plantations on a large scale is still scarce. In this study, a total of 60 Pinus tabuliformis Carr. plantations (40-year-old) were investigated for their li�er quality, regional meteorological factors, soil properties, and stand structure in a provincial area across Liaoning, northeast China. High lignin (40%–43%) and cellulose contents (15%–20%) were found to be located mainly in stands around the biggest city of Shenyang. Rainfall was a key factor that determined the decomposition, but neither the forest structure nor soil nutrient content generated direct eﬀects on the two li�er components. The combined factors of low soil pH (~5.8) and high rainfall (~3.0 mm per day) together mainly accounted for the promotion of natural li�er decomposition.


Introduction
Defoliated woody tissues in the li er residues of forests are an inevitable solid waste that incurs environmental problems in terms of dense bulk stacks, stand nutrient retention, leaching contamination, and as a potential cause of forest fires [1].Given that leaves are a sink of mineral nutrients, their residues have been suggested to be reused post decomposition [2,3].Lignin and cellulose together account for most of the structural and abundant components in forest li er, and they are the last to be degraded through natural decomposition [4].They both account for more than half of the carbon (C) sequestered in li er [5], and 30% of that is derived from C storage in lignin [6].Lignin is structurally characterized by an assemblage of diverse phenylpropane units [7], whose polymers can be cleaved mainly by reactions with intensive chemical oxidization species [8].The decomposition rate of lignin preconditions that of the li er residue, which is terminated by the full consumption of unprotected carbohydrates in the dry mass [8].Compared with the degradation of lignin, that of cellulose proceeds much faster, especially at the early decay stage [9].However, cellulose rarely degrades independently from lignin because the la er protects the earlier from enzymatic hydrolysis [10].Therefore, the late-stage degradation of cellulose may be accelerated if the lignin components are labile in the plant cell walls [11].The inner mechanism has been well elucidated for explaining these changes, but their responses to exogeneous driving forces are more worthy of being detected.
Regional climate is a strong driver that drives changes in the environmental factors at the understory layer in local forests [12].Cellulose decomposes at an increasing rate with the increase in soil temperature [13], a process that was supported by evidence that high soil temperatures promoted soil fauna activities and further accelerated li er decay [14].Air temperature, however, may not be so determinative of li er decomposition compared to soil moisture in stands at high elevations [15].The daily average temperature was found to solely generate a negative effect on cellulose decomposition in riparian forests.In an alpine fir forest, however, the daily temperature promoted local cellulose degradation [16].In a gorge reservoir, the air temperature interacted with local precipitation and together generated the direct promotion of lignin loss and an indirect effect on cellulose decay [17].Wind velocity was also found to reduce the cellulose decomposition rate [18].Overall, the existing finding were mostly conducted in studies on stands near watersheds, where air moisture may function as a driving force that determines the rate of decomposition, while other meteorological factors more likely took part in the effect as interactive factors.The existing findings are limited to ecosystem types mostly near riparian forests; hence, they need to be identified in a large-scale investigation along a latitudinal gradient to test the decay rates in moist ranges over a larger range.
Li er decomposition has a close relationship with soil characteristics, which change across forest types to a larger extent than that which is derived from the range of variation among stand locations [19,20].The soil pH value balances the tradeoff between fungal and bacterial growth and diversity.Acidic soils often incubate larger fungal communities with a higher diversity relative to bacteria [21,22].Cellulose decomposition, however, was found to be reduced by a lower pH due to decreased cellulase activity [13].The key fungi that play a leading role in cellulose degradation, such as filamentous fungi, function to accelerate decay mostly at the later stage in acidic soils.In contrast, a high pH can result in strong competition with bacteria for C and nutrients, which may further suppress additional growth of lignin-degrading fungi [21].A high cellulose decomposition rate was found in soils with high pH values in volcanic forest soils [23].These pieces of evidence together suggest that acidic soils can benefit lignin decay, but the peak may be delayed to a later stage [7].Given that microclimates also drive the formation of regional soil properties along latitudinal gradients, it is necessary to detect their interacted effects on li er decomposition.
Nutrient cycling is another important factor that determines li er decomposition [24,25].Nitrogen (N) addition contributes to at least an important part of the interplay with water availability to li er decomposition over long-term vegetation development [24].In short-rotation forests, however, N release has several ecological functions for estimating the li er decomposition rate not only in that against retention but also as a response to the local environment [25].However, the initial N content in li er was reported to have no relationship with decomposition rate in a desert basin [15].It was the initial macro-nutrient content in the soils that was found to be highly correlated with li er decomposition in an alpine forest river ecosystem [4].In a lotic ecosystem, the degradation rates were found to be related with the soluble nutrient availability in river water [4].In a riparian zone, mineral nutrients may result in contrasting effects on cellulose degradation.That is, ammonium N tends to depress cellulose decay, while nitrate N can generate a positive effect.To our knowledge, li le information has been revealed on the effects of the N form on the li er decay rate.More information is needed about the combined effects of soil N and other properties on li er decomposition.
All the environmental factors that determine lignin and cellulose decompositions can be determined by the forest structure.Canopy density is the most important a ribute that a racts a big amount of a ention [5,26,27].Changes in the canopy density have been identified to cause changes in the microclimate, solar radiation, wind speed, soil property, and soil fauna activity, which are all determinative factors that determine li er decay [5,27].In alpine forests, it was found that a large forest gap slowed the rate of lignin and cellulose degradation, and a small gap did not affect their decay rates [5].However, more evidence demonstrated the promotion of a large forest gap on li er decomposition, such as examples in pine forests subjected to Mediterranean [28] and temperate climates [27].As a type of coniferous species, pine presented a higher ability to degrade li er in its forests than in those dominated by coppices and broadleaf species [14].To reuse li er in a post-decomposition form is a practical way to reduce heaped piles and decrease their potential threat to pine forests.It is necessary to strengthen the understanding about the many factors that can affect the decay rate of li er.
In this study, we investigated Pinus tabuliformis Carr.plantations with the study objectives of (i) mapping the lignin and cellulose contents at the provincial scale of Liaoning, where (ii) combined factors across the meteorological factors, soil properties, and forest types were detected for their effects as driving forces that result in li er.Based on the current findings, we hypothesized that the lignin and cellulose contents were lower (i) in planted forests with low canopy densities with (ii) low soil pH subjected to (iii) a warm climate with frequent events of Rainfall.To control the conditions evenly in order to fully fulfill our hypotheses, all the planted forests were chosen from a similar context with a similar stand age and with a uniform species that would result in even states of li er layers with defoliation at a similar time.

Study Area and Plots
A total of 60 P. tabuliformis plantations were targeted as the study plots, which were distributed in the whole area across Liaoning province in an area of 0.149 million square kilometers (Figure 1), northeast China.Most of these plantations were established in the 1980s and are aged ~40 years old.The establishment of P. tabuliformis plantations selected in this study was adapted from the 3rd national land resource survey in mainland China in 2021, which was managed by the Ministry of Natural Resources of the People's Republic of China.Local soils were classified as thermo-black soil (CN 35) and argillic brown soil (CN 36), as termed by FAO-UNESCO as haplic phaeozem and chromic luvisol in the taxonomies of cumulic hapludoll and udic haplustalf, respectively [29].
The study area was subjected to a temperate monsoon climate.The annual temperature ranged between 3.5-15.4°C with an average of 9.4 ± 1.1 °C.The yearly rainfall was higher in the eastern mountainous areas and lower in the west, with an average in 600-1100 mm.Frost-free days lasted for 130-200 days of the year, which increased along an increasing gradient from the northwest to the southeastern parts.The chosen plantations had to meet screening standards that were required to meet the hypotheses, and they had to be located in local forest farms that were free from artificial interruption (grazing or farming) or visible natural destruction (thunderstrikes or natural fires).

Data Collection and Sampling
In each plot, three 600 m 2 (20 m × 30 m) stands were randomly placed, and adjacent plots were kept away from each other at a distance of at least 1 km.Each stand was further divided into 24 grids (each area: 5 m × 5 m), and li er was collected from every other grid.About 200 g of samples, including defoliated needles and fallen twigs and branches, were collected from each grid and from all collected samples.The li er components were composed of defoliated needles (70%; v/v), fallen branches (20%), and fallen twigs (10%).The samples were mixed together as a bulk for each stand.The samples were artificially screened to make sure all the collected parts were obtained from the li er of P. tabuliformis.In the same grids as those during the li er collection, the soils were sampled by a drill (inner diameter of 4 cm and height of 7 cm, and all the sampled soils were kept in canvas bags to facilitate air-drying when they were transported to the laboratory.After all the samples were finished, the stands were investigated to measure the stem density and diameter at breast height, the height of the lowest alive branch, the canopy density, and the canopy area for every P. tabuliformis individual.All stands were investigated and sampled in two months in the growing season from May to July in 2023.Sampling was conducted during the growing season when the windy season and interruptions due to snow cover could be avoided, a method which was adapted from an approach used in previous studies [5,30]. Local microclimates were characterized by meteorological factors of highest temperature, lowest temperature, rainfall, and air quality index (AQI).Data for the stand were obtained from monthly records provided by a climatic station located near the stand.Monthly data were obtained for the nearest two years and averaged for the stand.This arrangement was carried out according to the term of li er decay that usually lasted for 1.5 years or up to about two years [14,30].Elevation was estimated at the location of the center of a stand using the digital elevation model (DEM) using Aster GDEM 30 M data.

Chemical Analysis
Li er samples were smashed to chips and dried in an oven at 70 °C for 72 h.The cellulose and lignin contents were determined using a modified methodology from De Marco et al. [30], adapted from Van Soest and Wine [31].Briefly, 200 mg of fine-powered samples were suspended in sulfuric acid (H2SO4) solution (0.5 M) mixed with cetyl-trimethyl ammonium bromide (CTAB) at 20 g L −1 .The suspensions were bathed in distilled water at 100 °C for 1 h and centrifuged at 4000 rpm for 10 min until pellets were formed in the supernatant.The processes of centrifugation and pellet formation were repeated twice, and the pH value of the supernatant was adjusted to about 6.0.The pellets were washed using acetone, centrifuged, and dried in an oven, and the amount of acid detergent fiber (ADF) was weighed.The pellets were treated with a mineralizing solution (50 g of of oxalic acid dihydrate in 0.5 L muriatic acid and 0.7 L of 95% (v/v) ethanol) until fully decolorated.The post-oxidation ADF pellets were dried at 75 °C, weighed, and ashed at 550 °C for 2 h.The cellulose content was determined as the loss of weight through ashing.The lignin content was calculated by subtracting the weight of the post-oxidation ADF from that of the ash-free ADF biomass.
The soil properties were characterized by the parameters of the pH value, organic ma er content, total N content, ammonium N content, nitrate N content, available phosphorus (P) content, and total P content, which were determined using previously described methods [32].Briefly, the soil total N content was determined using Kjeldahl's method, and the total P was determined using the molybdenum anticolorimetry method.The ammonium N and nitrate N contents were determined using a flow injection analysis system (Lachat Inst., Loveland, CO, USA).

Data Processing and Statistical Analysis
The spatial distributions of the lignin and cellulose contents were mapped using the ArcGIS software, version 10.2 (Eris, Redlands, CA, USA).The data investigated in the stands were used to interpolate the values across the whole study area.The data were analyzed using the SAS software, version 9.4 (SAS Institute Inc., Cary, NC, USA).Microclimatic factors and forest structure parameters were correlated with latitude to detect their changes along the geographical gradient.Principal component analysis was used to detect relationships among the eigenvalues of the variables.Structural equation models (SEMs) were employed to detect the powers of the paths from the driving forces across the latent variables of climate, soil property, and forest structure together towards the lignin and cellulose contents.Variables with collinearity were removed from the SEMs if the variance inflation value (VIF) was higher than 10.Multiple linear regression (MLR) was used to detect the effects of multiple driving factors on the lignin and cellulose contents.Finally, Poisson's regression model was used to estimate the maximum likelihood parameters of the driving factors on the lignin and cellulose contents.

Microclimatic Changes along Latitudinal Gradient
The microclimatic factors that showed gradient changes along the latitude included the highest daily temperature, lowest daily temperature, AQI, and rainfall (Figure 3).Changes in highest daily temperature (Thigh) along the latitude (lat.) were fi ed by a curve of a quadratic polynomial equation (R 2 = 0.5279; p = 0.0013) (Figure 3A): According to Equation (1), Thigh reached a maximum value of 15.77 °C at a lat. of 40.5086°N. Changes in the lowest daily temperature (Tlow) along the lat.gradient were fi ed by a curve of a linear equation (R 2 = 0.6632; p < 0.0001) (Figure 3B): Changes in the air quality index (AQI) along the lat.were fi ed by a curve of an exponential growth equation (R 2 = 0.3784; p < 0.0001) (Figure 3C): Changes of rainfall (Rainfall) along the lat.were again fi ed by a curve of a quadratic polynomial equation (R 2 = 0.4799; p = 0.0078) (Figure 3D): Rainfall = 0.1964 lat. 2

Microclimatic Changes along Latitudinal Gradient
The first two principal components (PCs) together accounted for 44.53% of the data variation.The first and second PCs accounted for 25.09% and 19.44%, respectively.The eigenvalues for the variables in the first PC ranged between −0.4 and +0.4 (Figure 4).In the first PC, individual tree parameters showed highly positive relationships with longitude against stem density, which changed positively with the Thigh and negatively with the longitude.In the second PC, the lignin and cellulose contents showed positive relationships with the AQI and negative relationships with rainfall and the nitrate N content, organic ma er content, and total N content in the soils.In addition, lat.showed negative relationships with Tlow and canopy density, and the ammonium N content showed another negative relationship with the pH value in the soils.

Structural Equation Models of Driving Forces
In the SEM for lignin, the VIF was higher than 10.0 for tree height (16.11), diameter at breast height (12.25), height of lowest alive branch (14.31), soil organic ma er (13.80), and total N content (10.76); hence, these parameters were removed from the list of fixed factors from the SEM evaluations.As shown in Figure 5, the latent variable of microclimatic factors showed strong and positive effects on the latent variables of forest structure and soil property and a tiny negative effect on the lignin content.The forest structure showed a negative effect on the soil property, and both showed tiny positive effects on the lignin content.The fixed factors of the Thigh, Tlow, rainfall, and AQI all showed negative effects on the latent variable of microclimatic factors.In the soils, stand elevation showed a negative effect and the pH value showed a positive effect on the soil property.None of the fixed factors showed significant effects on the forest structure.In the SEM for cellulose, the VIF was higher than 10.0 for tree height (15.37), diameter at breast height (11.73), height of lowest alive branch (13.56), soil organic ma er (13.11), and total N content (10.44); hence, these parameters were removed from the list of fixed factors from the SEM evaluations.As shown in Figure 6, the latent variable of microclimatic factors showed strong and negative effects on the latent variables of forest structure and cellulose content.Microclimate and forest structure also showed positive effects on the soil property, which further showed a tiny positive effect on the cellulose content.The fixed factors of Thigh, Tlow, rainfall, and AQI all showed negative effects on the latent variable of microclimatic factors.In the soils, both the stand elevation and pH value showed positive effects on the soil property.Again, none of fixed factors showed significant effects on the forest structure.

Maximum Likelihood Estimate of Effects on Lignin and Cellulose Contents
Poisson's regression indicated significant maximum likelihood estimates on the parameters of the effects on the lignin and cellulose contents (Figure 7).The relationship between the maximum likelihood estimate on the lignin content (MLElignin) and the parameter of the canopy density ratio (CDR) was fi ed by a polynomial quadratic curve (R 2 = 0.5599; p = 0.0232) (Figure 7A): According to Equation ( 5), MLElignin reached a minimum value of 32.83 when the CDR was 49.50%.The relationship between the maximum likelihood estimate on the lignin content and the parameter of the canopy area (CA) was fi ed by a linear curve (R 2 = 0.3960; p = 0.0169) (Figure 7B): Again, the relationship between the maximum likelihood estimate on the cellulose content (MLEcellulose) and the parameter of the CA was fi ed by a polynomial quadratic curve (R 2 = 0.4899; p = 0.0363) (Figure 7C): MLEcellulose = 482.9849CDR 2 − 497.2846 × CDR + 157.9146 (7) According to Equation (7), MLEcellulose reached a minimum value of 29.91 when the CDR was 51.13%.The relationship between the maximum likelihood estimate on the lignin content and the parameter of the canopy area (CA) was fi ed by a linear curve (R 2 = 0.3339; p = 0.0111) (Figure 7D):

Multivariate Linear Regression against Driving Forces
The li er lignin content was regressed strongly against positive effects of the longitude and soil pH value as well as a tiny positive effect from the available P content in the soil (Figure 8A).In contrast, the combined factors of AQI, rainfall, ammonium N content, and nitrate N content all had negative joint effects on the lignin content.The li er cellulose content was regressed against positive effects of the longitude and soil pH value, whilst it was regressed against negative effects from Tlow, AQI, rainfall, and elevation (Figure 8B).

Sptatial Distributions of Li er Lignin and Cellulose Contents
In our study, the li er lignin content ranged between 18.9%-49.3%,and the cellulose content ranged between 10.0% and 22.7%.Therefore, their sums accounted for 31.94%-71.95%with an average of 51.22 ± 9.76%, which fell in the reasonable range from previous studies [5,6].The range of the lignin content was close to that in other ecosystems, such as the one for semiarid plants between 20.2% (Bouteloua gracilis) and 45.5% (Pinus edulis) [15] and another one in alpine fir (Abies faxoniana) forests (32.4-43.6%)[5].The cellulose content in the P. tabuliformis plantations was also comparable to that in previous studies.For example, cellulose ranged between 16.6% (Pinus edulis) and 25.4% (Gutierrezia sarothrae) in a semiarid ecosystem [15], between 14.4%-21.1% of Black pine (Pinus nigra) plantations [30], and between 11.9%-1.43% in forests dominated by Masson pine (Pinus massoniana), cypress (Cupressus funebris), and oak (Quercus variabilis).Therefore, the li er decomposition was at an ordinary rate, which resulted in the lignin and cellulose contents being at intermediate levels compared to the results from similar studies.Based on this, any further analysis using these data can be deemed reliable, with minimal suspicions about possible other variances.
Most of the P. tabuliformis plantations were aged around 40 years old, which was especially controlled during the experimental design with the expectation of eliminating any effects of chronical variation on the li er decomposition.Chronical effects on li er decomposition may not be remarkable in forests receiving short rotations in terms of decades unless the stand age is up to over 100 years old [33].In old pine forests with ages up to 120 years old, chronical effects were shown to be significant in terms of the contents of P and metal and in terms of the sulfur enzymatic activity in the li er, with no apparent evidence being found to demonstrate any responses of li er decay [34].Therefore, it is not reasonable to suspect that the possible variation in the stand age among the Chinese red pine plantations could have caused any remarkable interruption to the li er decomposition.
Although we conducted a large-scale investigation to place the stands in a geographical range across four degrees of lat., neither the lignin nor the cellulose contents in the li er showed routine and expected changes along the longitudinal or latitudinal gradients.Regions with high lignin and cellulose contents indicated relatively slower decay rates compared to those in other regions.These high-reserve regions were distributed mostly around the municipal area of Shenyang, which is the capital of and the most developed city in Liaoning.According to the MLR and SEM analyses, both a low level of rainfall and a high soil pH together resulted in high contents of lignin and cellulose in the li er at stands around Shenyang.These regional environmental characteristics were shown to be typical drivers of a dry microclimate following the heat-island effect and anthropogenic environmental pressure on soil ecosystems [35,36].Currently, the findings revealed that the decomposition of li er showed an altitudinal gradient that was mainly accounted for by the temperature [37] and soil microbial activity [38].Liaoning has an intact landform with highlands frequently distributed in eastern mountainous areas following the end of the ranges from Changbai Mountain.This was unlikely to have affected the spatial distribution pa erns of the lignin and cellulose contents in our study.The PCA results did not indicate any apparent relationship between elevation and the lignin or cellulose contents.Therefore, elevation should not be considered the driving force shaping the spatial distributions of the li er components in our study.Otherwise, distance could also be a precondition of distributions for decomposing li er.For example, li er decomposition was also shown to vary along a disturbance gradient in tropical forests [39].The high reverses of li er in the plantations around Shenyang may have resulted from local ecological protection policies that ban the over-exploitation of plantations with higher levels of protection.

Combined Effects of Climate and Forest Structure on Li er Lignin and Cellulose Contents
Evidence in the current literature suggests that air temperature can mostly generate an indirect impact on lignin and cellulose contents [15], which is usually effective in the interaction with the local moisture state in stands.It was surprising to find that the Thigh and rainfall showed contrasting changing trends along the lat.gradient.Their critical values together suggested a latitudinal location ranging between 40.51-41.04°N, where Thigh could reach a maximum point around 15 °C at a lat. of 40.5086°N, and where the rainfall could reach a minimum value of ~1.00 mm.The variable of Thigh, however, showed an unclear relationship with the lignin and cellulose contents according to the PCA results, but rainfall showed negative relationships with both of these two li er components.The results of the SEM also revealed that a negative effect of rainfall on the microclimate was passed on to further the negative effects on the lignin and cellulose contents.Therefore, in regions located within the critical lat.range, the minimum rainfall probably meant the highest li er reserve due to the lowered decomposition rate in dry air.Our results were in agreement with previous findings with the common conclusion that a high moisture level is the most necessary factor for li er decomposition [16].
In the SEM results, although the latent variable of forest structure generated significant effects on the lignin and cellulose contents, none of the stand characteristic variables (stem density, canopy density, or canopy area) worked as fixed factors that made any significant contributions to the forest structure.The effect of the forest structure on the lignin and cellulose contents were passed from earlier pathing effects of microclimatic factors on the forest structure.In detail, the microclimate generated a positive effect on the forest structure by a power of 4.97, which was passed on to be another positive effect of the forest structure on the lignin content, with the power reduced to 0.02.Similarly, the microclimate generated a negative effect on the forest structure with a strong power of −1.68, which was reduced to e −0.17 in another negative effect of the forest structure on the cellulose content.These findings have rarely been reported in previous studies, which are contradictory regarding large forest gaps as a positive driver [5] or limits [27,28] on lignin and cellulose contents.The rare effects of the forest structure on li er may result from the dual explanations that the plantation stands were distributed over a large geographical scale but with a tiny variation in the stand characteristics.The large geographical scale resulted in the fatal condition that the varied regional meteorological factors determined the variations in the factors determining the li er decomposition among the stands.The effect of the microclimatic variation overcame and covered that of the forest structure.
People also believe that the canopy-density-dependent gap determines the microclimatic conditions at the understory layer for li er decay through the controlling determinants of solar radiation, wind speed, soil property, and soil fauna activity [5,27].The maximum likelihood estimation results indicated that the change in the canopy density could only generate potential effects on the lignin content with no effects on the cellulose content.Poisson's regression indicated that the change in the canopy density resulted in a range of responses of the estimated effects on the lignin content.As soon as the canopy density covered a ratio away from ~50%, the effect on the lignin and cellulose contents were estimated to be higher than the minimum critical value of 32.83.These results can be referred to by future studies that detect the effect of the canopy ratio on li er decomposition.Existing studies, however, have revealed more pieces of evidence on the relationship between the canopy area and li er decomposition.Ni et al. (2018) reported that li er exposed to gaps in an alpine forest showed a higher mass loss than that under a closed canopy [40].The results of the study by Wu et al. [5] agreed with this only in terms of the cellulose loss rate, but their lignin results varied with much more complicated situations.Our results agreed with these trends in terms of the responses of both the lignin and cellulose contents, which both showed increasing responses to the estimated effects derived from increasing the canopy area (decreasing the gap).This could be because we focused on plantations that varied in their stand structure among the different locations to a low extent.We surmise that natural forests or secondary forests may harbor li er that decomposes more directly due to canopy size.

Relationship between Soil Properties and Li er Lignin and Cellulose Contents
The soil properties showed very small relationships with the lignin and cellulose contents in the P. tabuliformis plantations according to the PCA results.The results obtained from the SEM indicated positive effects of the soil property as a latent variable on the lignin and cellulose contents, which were driven by an earlier positive effect of the soil pH value.Therefore, low-acid soils (high-pH) obstructed the li er decomposition and resulted in higher reserves.This part of our results agreed with results reported in previous studies [21,22] that showed that acidic soils often incubate larger fungal communities with a higher diversity relative to bacteria that benefit decomposition; hence, a high pH would negate all these effects and restrict the decay process.Our results also concur with viewpoints regarding strong competition in high-pH soils with bacteria for C and nutrients, which may suppress the additional growth of lignin-degrading fungi [21].However, our results disagreed with Hayakawa et al. [13], who argued that cellulose decomposition can be reduced by low pH levels due to decreased cellulase activity.It is possible that cellulase was not the key enzyme whose activity determined the cellulose decomposition, but more confirmative results require more evidence.
The stand elevation generated a negative effect on the soil property when estimating the further effects on lignin, but the elevational effect on the soil property switched to become positive when estimating the effects on cellulose.These changes in the path effects were in agreement with the effects of the forest structure on the soil property but contradicted the earlier effects of climate on the forest structure.Hence, the stand conditions of the plantations located in high-elevation stands promoted cellulose decomposition while their effect on lignin was contrasting and negative.Based on above-discussed content, we speculate that the high-elevation plantations were subjected to moister conditions, which promoted cellulose decomposition and reduced its accumulation.Rainfall, however, was not the a factor in the decomposition of lignin at high elevation.Instead, the low soil pH may be the critical factor that hindered the lignin reserve, which was generated by microclimatic factors.These differences between the lignin and cellulose contents were reasonable because lignin can be decomposed at an earlier stage of decay, and the late-stage degradation of cellulose may be accelerated if lignin components are labile in the plant cell walls [11].More work is needed to provide more reliable results.

Limits of the Current Study
Our study focused on abiotic factors that shape the spatial distributions of lignin and cellulose in the li er of stands, but biotic factors that have strong effects were ignored in this study [14,41].Further work is strongly recommended to complement the analyses with a new data pool with soil fungal and fauna communities and to detect their joint effects on li er decay.The other limit in our study was a lack of any investigation into secondary forests.Some plantations may have been converted to secondary forests during our investigation, especially in the large areas of western Liaoning province [12].Plantations and secondary forests should be compared in terms of the difference in their li er decomposition abilities so as to obtain a more comprehensive map of an intact provincial area.

Conclusions
In the area of Liaoning province, high lignin and cellulose contents were found to be distributed in P. tabuliformis plantations in the regions around the biggest city of Shenyang.These were mainly characterized by a high soil pH value and low moisture distributed along an increasing trend of longitude.Microclimatic factors of low temperate, low rainfall, and low AQI together determined the high reserves of lignin and cellulose that accumulated in the plantation stands.Neither the stand structure nor the soil nutrient contents accounted for the lignin and cellulose contents because they were investigated in stands from evenly aged plantations, the variations in whose conditions were also determined by the microclimate.Overall, the stand conditions of P. tabuliformis plantations can be characterized as located at high elevation with a low soil pH, where both rainfall and AQI are high if the li er is expected to be decomposed naturally at a higher rate.

Figure 1 .
Figure 1.Distribution of investigated plots of Chinese red pine (Pinus tabuliformis Carr.) plantations across Liaoning province, northeast China.

Figure 2 .
Figure 2. Spatial distributions of li er lignin (A) and cellulose contents (B) in stands of P. tabuliformis plantations in Liaoning, northeast China.

Figure 3 .
Figure 3. Curve fits for changes in gradient of Thigh (A), Tlow (B), AQI (C), and rainfall (D) in stands of P. tabuliformis plantations in Liaoning, northeast China.

Figure 4 .
Figure 4. Principal component analysis (PCA) of lignin and cellulose contents and driving factors in stands of P. tabuliformis plantations in Liaoning, northeast China.Abbreviations: Cellulose, cellulose content; Lignin, lignin content; pH, soil pH value; TP, total P content in soil; Density, stem density of plantation; CD, canopy density; NN, nitrate N content in soil; OM, organic ma er content in soil; TN, total N content in soil; AN, ammonium N content in soil; AP, available P content in soil; DEM, elevation; ABH, lowest alive branch height; CA, canopy area; DBH, diameter at breast height; TreeH, tree height.

Figure 5 .
Figure 5. Structural equation model of latent variables of microclimatic factors (Climate), soil property (Soil), and forest structure (Forest), together accounting for effects driving changes in lignin content in li er at stands of P. tabuliformis plantations in Liaoning, northeast China.Boxed values indicate effects from the start of an arrow to the end of it.Positive value indicates a positive effect along an arrow in blue color, and negative value indicates a negative effect along an arrow in red color.Arrows in bold lines indicate effects from latent variables towards lignin content, and arrows in thin lines indicate effects from fixed variables.Abbreviations: Dem, elevation; TP, total P content in soil; AP, available P content in soil; AN, ammonium N content in soil; NN, nitrate N content in soil; Den, stem density; CD, canopy density; CA, canopy density.

Figure 6 .
Figure 6.Structural equation model of latent variables of microclimatic factors (Climate), soil property (Soil), and forest structure (Forest), together accounting for effects driving changes in cellulose content in li er at stands of P. tabuliformis plantations in Liaoning, northeast China.Boxed values indicate effects from the start of an arrow to the end of it.Positive value indicates a positive effect along an arrow in blue color, and negative value indicates a negative effect along an arrow in red color.Arrows in bold lines indicate effects from latent variables towards cellulose content, and arrows in thin lines indicate effects from fixed variables.

Figure 7 .
Figure 7. Curve fits for changes in likelihood parameter estimates of effects on lignin (A,B) and cellulose contents (C,D) in response to canopy density ratio (A,C) and canopy area (B,D) in li er at stands of P. tabuliformis plantations in Liaoning, northeast China.

Figure 8 .
Figure 8. Multivariate linear regressions of lignin (A) and cellulose contents (B) in li er against explanatory variables at stands of P. tabuliformis plantations in Liaoning, northeast China.Dots represent effect of estimated parameters with error bars (standard errors).Thigh.