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Article

Soil Invertebrates Play Key Roles in Stage-Specific Shifts in Elevational Patterns of Litter Decomposition in Dongling Mountain, Beijing

by
Shijie Zhang
1,2,
Yuxin Zhang
1,
Yinghua Lin
3,
Miao Wang
4,
Guorui Xu
5 and
Keming Ma
1,2,*
1
State Key Laboratory of Ecological Security of Regions and City, Research Center for Eco-Environment Sciences, Chinese Academy of Sciences, Beijing 100085, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Institute of Wetland Research, Chinese Academy of Forestry, Beijing 100091, China
4
Chengdu Academy of Governance, Chengdu 610110, China
5
Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Xishuangbanna 666303, China
*
Author to whom correspondence should be addressed.
Forests 2025, 16(4), 584; https://doi.org/10.3390/f16040584
Submission received: 25 January 2025 / Revised: 13 March 2025 / Accepted: 26 March 2025 / Published: 27 March 2025
(This article belongs to the Section Forest Soil)
Browse Figures
Versions Notes

Abstract

:
Litter decomposition is a fundamental ecological process that drives nutrient cycling and energy flow. However, little is known about the elevational patterns of this process in different stages. We established ten sites on Dongling Mountain in Beijing, China, to investigate the elevational patterns of oak leaf (Quercus liaotungensis) decomposition, as well as the underlying mechanisms. Our results revealed distinct elevational patterns of litter decomposition in different stages. There was no significant altitudinal pattern in the mass loss of Q. liaotungensis leaves at the 2nd, 4th, and 6th months of decomposition. By the 16th month, the mass loss decreased significantly along the elevation gradient (p = 0.008). By the 28th month, a reverse pattern emerged, with greater mass loss observed at higher elevations (p < 0.001). A similar change also took place in the altitudinal pattern of the abundance of invertebrates within the litter bag, which was lower at higher elevations at the 16th month (p = 0.002), but higher at higher elevations at the 28th month (p = 0.002). In addition, we examined the elevational patterns of carbon and nitrogen concentrations in different stages. The results of the structural equation model revealed that the invertebrate abundance at the 4th month influenced the litter residues at the 16th month (p < 0.001), yet nitrogen content at the 16th month affected litter residues at the 28th month(p < 0.001). This study provides novel insights into the temporal dynamics of litter decomposition along an elevational gradient and highlights the underlying mechanisms by which litter chemistry and biological factors regulate this process.

1. Introduction

Litter decomposition is a fundamental ecological process essential for nutrient cycling and energy flow [1,2]; it improves soil fertility [3] and influences the physical and chemical characteristics of soil [4]. In addition, litter decomposition is one of the major sources of carbon that is stored in soil [5,6]. Therefore, it is especially crucial to research the factors influencing litter decomposition considering global climate change [7]. Litter decomposition is a complicated physicochemical process [8], and up to 50%–65% of the variance in decomposition rates can be explained by litter characteristics and abiotic factors (temperature, precipitation, etc.) [9,10]. Furthermore, litter decomposition has also been shown to be significantly influenced by biotic factors, such as microbes and soil invertebrates [11,12].
Among these, soil invertebrates play an important role in litter decomposition. Herbivorous fauna carry out processes such as feeding, chewing, moistening, and mixing on plant bodies, and saprophagous fauna further feed on them, accelerating litter decomposition [13]. Studies have shown that soil fauna have a rich enzyme system in their bodies, and after feeding on litter, they can convert plants into substances easy to utilize [14]. In addition, the presence of soil fauna can significantly accelerate the decomposition rate [15]. In temperate tree species, the decomposition rate of litter decreased by 13.1% after excluding soil animals [16]. However, invertebrates do not act independently. The impact of soil fauna on decomposition varies by climate: 28% in temperate regions, 47% in subtropical regions, and 200% in tropical regions [17]. Litter quality affects fauna’s decomposition contributions [18].
Elevation is a useful tool for investigating how abiotic factors affect ecosystem functions [19]; it shows significant environmental changes within a short spatial range. Temperature and humidity fluctuate to varying degrees across elevations [20], influencing the distributions of plants, microbes, and soil invertebrates [21,22,23,24]. The elevational patterns of decomposition are further influenced by the interaction of these factors. One study shows a significant positive correlation between litter mass loss and temperature along the elevation gradient [25]. Also, elevation indirectly increases the carbon residue of litter by negatively affecting the soil fauna community [26]. Many studies have reported that the decomposition rate decreases with increasing elevation [27,28,29]. However, the opposite result has also been observed. Elevation has been found to accelerate the decomposition of Sorbus rufopilosa in the eastern Tibetan Plateau [30]. Thus, it is imperative to conduct more research on the elevational patterns of litter decomposition.
Taking both space and time factors into comprehensive consideration, the spatial pattern of litter decomposition changes over time. On Changbai Mountain, China, Abies nephrolepis and Picea jezoensis decay more slowly at high elevations after ten months of decomposition; however, there is no discernible difference between the two elevations in the later stage [31]. In central New Hampshire, USA, after one year of decomposition, the residual mass in high-elevation plots is larger than that in low-elevation plots; after two years, the remaining mass at both elevations is comparable [32].
To investigate the spatiotemporal dynamics of the leaf litter decomposition process, this study focused on fallen leaves of Quercus liaotungensis on Dongling Mountain, Beijing, China. As a dominant species in the study area, the decomposition of the leaves of Q. liaotungensis has a significant impact on the local soil and the environment. Studies have shown that the release rates of carbon and nitrogen in the leaves of Q. liaotungensis are higher than those of Robinia pseudoacacia, but lower than those of Betula platyphylla [33]. We hypothesized that (1) the mass loss of Q. liaotungensis leaves shows no altitudinal pattern in the early decomposition stage, but later decreases with elevation; and (2) due to the influence of low temperature, the number of invertebrates inside the litter bags decreases with increasing elevation, which leads to the elevational pattern of mass loss in the later stage.

2. Materials and Methods

2.1. Site Description

The research region is located on Beijing Dongling Mountain, China (39°55′–40°5′ N, 115°20′–115°35′ E), which is a typical temperate semi-humid continental monsoon zone. The average annual temperature is between 5 and 10 °C, and the precipitation is between 500 and 600 mm, with July and August receiving the most precipitation [34]. The soil is mountain brown loam. Warm-temperate deciduous broadleaf forests and deciduous broadleaf mixed forests are the characteristic zonal vegetation, such as Betula davurica, Betula platyphylla, and Populus davidiana, etc. Q. liaotungensis is a significant dominant tree species in this study area [35]. Approximately 7% of the carbon stored above ground is found in the litter [36].

2.2. Sample Collection and Processing

Ten plots (10 × 10 m2) were established at various elevations on the western slope of Dongling Mountain, ranging in elevation from 1020 m to 1770 m (Figure 1). Fallen Q. liaotungensis leaves were collected in the Nanguo region in October 2011 and air-dried for later use. We used 25 × 20 cm2 nylon litter bags with three mesh sizes (5 mm, 1 mm, and 0.1 mm). Litter bags filled with 10 g of litter were randomly placed in clearings away from tall trees and shrubs in the middle of April 2012. In total, 450 litter bags were placed (3 replicates × 5 sampling time × 3 mesh sizes × 10 plots). The distance between each litter bag was 0.5 m. In June, August, and October 2012, as well as August 2013 and August 2014, 90 samples were retrieved each time (3 replicates × 10 elevation sample plots × 3 mesh sizes). The samples were then packed in sterilized polyethylene Ziplock bags and placed in an ice box for subsequent laboratory use.
Later, the samples were removed from the nylon bags, carefully removingsoil clumps, stones, roots, etc. And larger invertebrates (earthworms, etc.) were manually picked up. The other invertebrates in the litter bags were separated using the modified Tullgren funnel method, baked continuously at approximately 50 °C for 48 h [37]. The invertebrates were stored in sealed, light-proof vials with 70% alcohol, identified and counted under Motic dissecting microscope. Due to time and effort constraints, the taxonomy of the soil invertebrates was identified only up to suborder and family. A total of 17,520 soil invertebrates were obtained from five samplings, belonging to 3 phylums, 9 classes, 24 orders, and 88 families. Mites (48.95%) and Collembola (40.53%) were the dominant species (Table A1).
Next, the litter was weighed, and the mass loss of the litter before and after decomposition (mass loss = 10 g-current mass) was calculated. Then, the samples were divided into two parts; one part was used for the determination of litter carbon and nitrogen content, and the other part was used for the determination of phospholipid fatty acids; the latter was stored in a refrigerator at −80 °C. The samples were cleaned with water and dried in an oven set at 80 °C until their weight remained consistent, then cut into small pieces and ground finely with a ball mill (MM400) until they could pass through a 100-mesh sieve. Weigh 10–50 mg of the sample and transfer it to elemental analyzer (Vario EL, Elementar, Rhein-Main-Gebiet, Germany) for the determination of the contents of carbon and nitrogen elements [38].
Litter samples removed from the −80 °C refrigerator were lyophilized in the lyophilizer (FreeZone 2.5, Labconco, Kansas City, MO, USA); the litter was brushed with a brush, sheared, and then ground in a ball mill (MM400) and placed in the −20 °C refrigerator for later use. PLFAs in the litter were extracted by the method described by Bligh and Dyer (2011) [39] and Frostegård et al. (1991) [40], and the samples were fed into GC-MS for determination. The naming rules for fatty acids are as follows: The chain length of fatty acids is calculated by the total number of carbon atoms. The number after the colon represents the number of double bonds, and the number after ω represents the position of the double bond (counted from the carboxyl end).Suffixes c, t denote cis and trans of the -H bond on both sides of the double bond; prefixes a, i denote isoform and homoform of the branched chain, respectively; and cyclopropane fatty acids are denoted by cy [41,42]. The classifications for PLFA signatures are shown in Table A2. Additionally, PLFA content was regarded as an indicator of microbial biomass [43,44]. Owing to missing data, we have microbial data only from the first three time points (the 2nd, 4th, and 6th months of decomposition).

2.3. Data Analysis

We used a generalized mixed-effects model with the lme4 package to examine the elevational patterns of litter mass loss, C content, N content, invertebrate abundance in the litter bags, and leaf microbial PLFAs in different stages. Elevation was set as the fixed effect and mesh as the random effect. Mass loss, C content, N content, and leaf microbial biomass are biomass data, so the Gamma regression was adopted. On the other hand, the abundance of invertebrates is counting data with zeros and high dispersion, so negative binomial regression is used. The link function is log in each case.
In addition, we calculated the stage decomposition amount from month 4–16 and 16–28; the formulas are as follows:
D 1 = M 4 − M 16
D 2 = M 16 − M 28
Notes: D 1 is the decomposition amount from month 4–16; D 2 is the decomposition amount from month 16–28. M 4 , M 16 , and M 28 are litter residues in months 4, 16, and 28, respectively. In addition, we did Pearson correlations with pre-stage carbon, nitrogen contents, and invertebrate abundance. That is, correlate D1 with 4th-month data and D2 with 16th-month data.
To investigate whether there were time lag effects between different factors, we constructed a structural equation model. We built an a priori model (Figure 2) based on three time points: the 4th, 16th, and 28th months of the decomposition (August 2012, August 2013, and August 2014, respectively). Our model explored the relationships among N concentration, soil invertebrates, and litter residues, as well as the relationships among N concentration, C concentration, and soil invertebrates. The structural equation model was performed using the lavaan package (ver. 0.6-19). All the analyses were conducted in R 4.2.3.

3. Results

The mass loss of oak (Q. liaotungensis) leaves did not exhibit a significant elevational pattern in the 2nd, 4th, and 6th months of decomposition. By the 16th month, the mass loss decreased significantly along the elevation gradient. By the 28th month, a reverse pattern emerged, with greater mass loss observed at higher elevations. The abundance of invertebrates within the litter bags exhibited a descending trend with increasing elevation at the 2nd, 4th, 6th, and 16th months of the decomposition process. Similarly, a reversal took place at the 28th month, during which the abundance demonstrated an ascending trend along the elevation (Figure 3).
The C content showed no altitude-related pattern in the 4th month, but increased with altitude at other sampling times. The N content did not exhibit a significant elevational pattern in the first three sampling times, but increased with elevation in the 16th and 28th months of decomposition (Figure 4). The microbial PLFAs was also in a more chaotic state; in the 2nd month of decomposition, it increased with elevation; in the 4th month, it decreased with elevation; in the 6th month, there was no significant elevation-related trend (Figure A1).
The results of the structural equation model revealed that the invertebrate abundance at the 4th month influenced the litter residues at the 16th month, yet nitrogen content at the 16th month affected litter residues at the 28th month (Figure 5a,b). Pearson correlation results indicate that the decomposition amount from the 4th to 16th month correlates with invertebrate abundance in the 4th month, while the decomposition amount from the 16th to 28th month has no relation with invertebrate abundance in the 16th month but is related to carbon and nitrogen content. Moreover, invertebrates regulated the C and N content in the first and middle stages and, in turn, regulated the abundance of invertebrates in the later stage (Figure 5c,d).

4. Discussion

Hypothesis 1 has been verified, but based on hypothesis 1, the elevational pattern of mass loss reversed later. By the 16th month, the mass loss decreased significantly along the elevation gradient. By the 28th month, higher elevations show greater mass loss. Although this situation has not been reported, similar scenarios have occurred. Both on Changbai Mountain, China, and in central New Hampshire, USA, mass loss was lower at higher elevations after almost one year of decomposition, whereas there was no significant difference at different elevations later [31,32].
The non-significant elevational pattern of mass loss in the 2nd, 4th, and 6th months has two possible explanations: litter properties and external conditions. Research shows litter quality dominates early decomposition over climate or microenvironment [45,46]. In our experiment, using the same litter means no initial property differences. The soil moisture in our study area has a “bell-shaped” elevational distribution [34], and invertebrate abundance declines with elevation. Meanwhile, the microbial biomass on the leaves displayed different elevational patterns at the 2nd, 4th, and 6th months (Figure A1). Climate affects litter decomposition via microbes [47], and invertebrates do so by preying on microbes [13,48]. So, these external factors together may have caused the lack of elevational patterns in the early stage.
As decomposition time lengthened, our results revealed decreased mass loss with increasing elevation by the 16th month, consistent with most studies [49,50,51].Temperature decreases with elevation, which impacts litter decomposition by lowering the quantity and activity of invertebrates and microorganisms [32,52], which validates our findings. In our study area, temperature decreases as elevation rises [34]. This likely leads to a decline in invertebrate abundance (Figure 1), thereby influencing litter decomposition.
By the 28th month, mass loss and invertebrate abundance both showed an increasing elevational trend. Comparing invertebrate abundance in the 16th and 28th months (both summers) indicates a change in the main factors affecting invertebrates. The results show that the properties of the litter at the 16th month affect the abundance of invertebrates at the 28th month (Figure 5c,d). Litter quality has a strong effect on regulating the role of invertebrates in decomposition, with high-quality litter material being more readily consumed and degraded by soil invertebrates [53,54].This is slightly different from hypothesis 2. However, the nitrogen content difference at the 16th month caused invertebrate changes, causing the litter mass loss to increase with elevation at the 28th month (Table A3).
Climate and litter quality are key factors controlling decomposition rates in modern litter decomposition models [55]. Researchers have long argued about the relative importance of these two influencing factors at various stages of decomposition [8,56,57]. Research has suggested that as cumulative mass loss increases, the influence of the temperature on the rate of mass loss decreases, whereas nitrogen involvement becomes more significant in later stages [58]. Our results have confirmed this view from the perspective of the invertebrates involved in the decomposition process.
Currently, many studies use decomposition models [59,60], but litter decomposition is temporally variable [61,62]. Our research shows it has distinct elevational patterns in different stages, so caution is needed when interpreting decomposition model results. Also, decomposers, directly involved in decomposition, are mainly influenced by litter quality and the abiotic environment [55]. These three factors interact, but we might have overlooked the time effect. We found an interaction lag effect between the C and N concentrations and invertebrate abundance, which extended the time effect of the decomposition triangle. In addition, fewer studies have focused on the cross-lag effect of litter decomposition, and our paper provides a reference for studying the different stages of decomposition.
In addition, one study predicts climate change will accelerate litter decomposition with regional heterogeneity [63]. Warming reduces litter decomposition in warm–arid areas but slightly increases it in cold regions. Lower-quality litter is more sensitive to warming, possibly raising carbon release [64]. Climate change has caused most plants to migrate upward to higher altitudes, with fewer moving downward [65]. Therefore, in the future, it is also highly necessary to conduct research on the impact of climate change on litter decomposition in different altitude regions.

5. Conclusions

This study investigated the elevational patterns of Q. liaotungensis leaf decomposition over time in Dongling Mountain, Beijing. The results show that elevation impacts litter decomposition via abiotic and biotic factors. We found that elevation-induced invertebrate differences led to property variations in decomposing Q. liaotungensis leaves, which in turn affected decomposition through invertebrates. In addition, our results indicate that time is of great importance in the process of litter decomposition, and the dominant factors influencing litter decomposition vary at different decomposition stages.

Author Contributions

Conceptualization, S.Z., Y.Z., Y.L. and K.M.; methodology, Y.Z., Y.L. and K.M.; validation, Y.Z. and K.M.; formal analysis, S.Z.; investigation, Y.Z., Y.L., M.W. and G.X.; resources, Y.Z. and K.M.; data curation, S.Z.; writing—original draft preparation, S.Z.; writing—review and editing, S.Z., Y.Z. and K.M.; visualization, S.Z.; supervision, K.M.; project administration, Y.Z. and K.M.; funding acquisition, Y.Z. and K.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (32071543, 31470481).

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

We would like to thank Yanpeng Xu and Ping Lu for their help with the identification of the soil invertebrates. We also thank Quan Chen, Qiang Zhang, Zihan Jiang, and Bingbing Wang for help with the field sampling of soil invertebrates.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Forests 16 00584 g0a1
Figure A1. Elevational patterns of leaf microbes in different stages. For p values less than 0.05, fitted trend lines were drawn with 95% confidence intervals. R2m represents the goodness of fit of the fixed effect, and R2c represents the total goodness of fit of the fixed effect and the random effect.
Figure A1. Elevational patterns of leaf microbes in different stages. For p values less than 0.05, fitted trend lines were drawn with 95% confidence intervals. R2m represents the goodness of fit of the fixed effect, and R2c represents the total goodness of fit of the fixed effect and the random effect.
Forests 16 00584 g0a1
Table A1. Overview of invertebrate community composition.
Table A1. Overview of invertebrate community composition.
ClassOrderFamilyAbundance (Specimens)Percent
(%)
OligochaetaHaplotaxidaLumbricidae1851.056
TubificidaEnchytraeidae220.126
ArachnidaAraneaeClubionidae110.063
Heteropodidae240.137
Agelenidae40.023
Oonopidae120.068
Zodariidae40.023
Gnaphosidae70.040
Salticidae10.006
Titanoecidae10.006
PseudoscorpionesAtemnidae340.194
Cheiridiidae20.011
Acariformes 1210.691
Parasiformes 628635.879
OribatidaPtychoid
Oribatida mites		700.400
Macropyline
Oribatida mites		7834.469
Apterogasterine
Oribatida mites		12076.889
Pterogasterine
Oribatida mites		1090.622
MalacostracaIsopodaArmadillidiidae80.046
Porcellionidae90.051
DiplopodaSpirostreptidaHarpagophoridae20.011
SpirobolidaePseudospirobolellidae10.006
ChilopodaLithobiomorpha 690.394
Geophilomorpha 20.011
CollembolaCollembolaIsotomidae181210.342
Onychiuridae13037.437
Tomoceridae5062.888
Neanridae8074.606
Sminthuridae1000.571
Entomobryidae257214.680
DipluraDipluraCampodeidae10.006
SymphylaSymphylaScolopendrellidae20.011
Scutigerellidae130.074
InsectaHemipteraMeenoplidae50.029
Cicadidae20.011
Cicadellidae240.137
Pyrrhocoridae40.023
Hebridae60.034
Cydnidae40.023
Tingidae20.011
Coccoidea160.091
Aphididae400.228
DermapteraChelisochidae120.068
ThysanopteraPhlaeothripidae70.040
HymenopteraPergidae50.029
Formicidae430.245
NeuropteraChrysopidae30.017
PsocopteraEpipsocidae70.040
Liposcelididae50.029
Amphientomidae3642.078
Diptera (larvae)Platypezidae340.194
Pachyneuridae10.006
Tipulidae90.051
Scatopsidae190.108
Bombyliidae30.017
Sciaridae110.063
Bibionidae20.011
Ceratopogonidae10.006
Empididae60.034
Mycetophilidae300.171
Phoridae1430.816
Diadocididae4472.551
Hesperinidae180.103
Dolichopodidae130.074
Lepidoptera (larvae)Hepialidae100.057
Geometridae10.006
Limacodidae210.120
Tortricidae210.120
Psychidae20.011
ColeopteraCantharidae220.126
Carabidae10.006
Geotrupidae10.006
Cicindelidae10.006
Scarabaeoidae80.046
Silvanidae10.006
Cleridae80.046
Elateridae10.006
Tenebrionidae20.011
Dermestidae20.011
Ladybirds10.006
Scydmaeninae10.006
Curculionidae60.034
Mycetophagidae60.034
Meloidae10.006
Pselaphidae10.006
Staphlinidae110.063
Ptiliidae10.006
Silphidae140.080
Total 17,520100.000
Table A2. Classifications for PLFA signatures.
Table A2. Classifications for PLFA signatures.
Classifications for PLFAsPLFA SignaturesReferences
G+i15:0, a15:0, i16:0, i17:0, a17:0[39,66]
G−15:1ω6c, 16:1ω9c, 16:1ω7c, 17:1ω8c, 18:1ω5c, 15:0 3-OH, cy17:0, cy19:0[40,66]
F18:1ω9, 18:2ω6, 9[67,68]
BG+, G−, 14:0, 15:0, 16:0, 17:0, 18:0, 20:0, i15:1, i16:1, i17:1, 16:1 2-OH[41,68,69]
Notes: G+, Gram-positive bacteria; G−, Gram-negative bacteria; F, fungi; B, bacteria.
Table A3. Pearson correlation of decomposition amount with litter quality and invertebrate abundance in different stages.
Table A3. Pearson correlation of decomposition amount with litter quality and invertebrate abundance in different stages.
FactorsCorrelation Coefficient
D1D2
C Content−0.172880.27453
N Content0.1952660.27992
Abundance0.42561−0.02923
Notes: Significant correlations (p < 0.05) are shown in bold.

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Figure 1. Location of samples.
Figure 1. Location of samples.
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Figure 2. Initial model representing the hypothesized causal relationships of X and Y. X represents the C concentration, N concentration, and soil invertebrate abundance, and Y represents the soil invertebrate abundance and mass of litter residues.
Figure 2. Initial model representing the hypothesized causal relationships of X and Y. X represents the C concentration, N concentration, and soil invertebrate abundance, and Y represents the soil invertebrate abundance and mass of litter residues.
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Figure 3. Elevational patterns of mass loss and soil invertebrate abundance in different stages. For p values less than 0.05, fitted trend lines were drawn with 95% confidence intervals. R2m represents the goodness of fit of the fixed effect, and R2c represents the total goodness of fit of the fixed effect and the random effect.
Figure 3. Elevational patterns of mass loss and soil invertebrate abundance in different stages. For p values less than 0.05, fitted trend lines were drawn with 95% confidence intervals. R2m represents the goodness of fit of the fixed effect, and R2c represents the total goodness of fit of the fixed effect and the random effect.
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Figure 4. Elevational patterns of C and N concentrations in different stages. For p values less than 0.05, fitted trend lines were drawn with 95% confidence intervals. R2m represents the goodness of fit of the fixed effect, and R2c represents the total goodness of fit of the fixed effect and the random effect.
Figure 4. Elevational patterns of C and N concentrations in different stages. For p values less than 0.05, fitted trend lines were drawn with 95% confidence intervals. R2m represents the goodness of fit of the fixed effect, and R2c represents the total goodness of fit of the fixed effect and the random effect.
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Figure 5. Summary of structural equation model results. Model (a) (p = 0.08), Model (b) (p = 0.45), Model (c) (p = 0.49), and Model (d) (p = 0.84). The p-value is greater than 0.05, which indicates that the model fits well. Significant relationships are shown with solid lines; red indicates positive effects, and blue indicates negative effects. The double-headed arrows represent exogenous correlations. The gray dashed lines represent no significant correlation.
Figure 5. Summary of structural equation model results. Model (a) (p = 0.08), Model (b) (p = 0.45), Model (c) (p = 0.49), and Model (d) (p = 0.84). The p-value is greater than 0.05, which indicates that the model fits well. Significant relationships are shown with solid lines; red indicates positive effects, and blue indicates negative effects. The double-headed arrows represent exogenous correlations. The gray dashed lines represent no significant correlation.
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Zhang, S.; Zhang, Y.; Lin, Y.; Wang, M.; Xu, G.; Ma, K. Soil Invertebrates Play Key Roles in Stage-Specific Shifts in Elevational Patterns of Litter Decomposition in Dongling Mountain, Beijing. Forests 2025, 16, 584. https://doi.org/10.3390/f16040584

AMA Style

Zhang S, Zhang Y, Lin Y, Wang M, Xu G, Ma K. Soil Invertebrates Play Key Roles in Stage-Specific Shifts in Elevational Patterns of Litter Decomposition in Dongling Mountain, Beijing. Forests. 2025; 16(4):584. https://doi.org/10.3390/f16040584

Chicago/Turabian Style

Zhang, Shijie, Yuxin Zhang, Yinghua Lin, Miao Wang, Guorui Xu, and Keming Ma. 2025. "Soil Invertebrates Play Key Roles in Stage-Specific Shifts in Elevational Patterns of Litter Decomposition in Dongling Mountain, Beijing" Forests 16, no. 4: 584. https://doi.org/10.3390/f16040584

APA Style

Zhang, S., Zhang, Y., Lin, Y., Wang, M., Xu, G., & Ma, K. (2025). Soil Invertebrates Play Key Roles in Stage-Specific Shifts in Elevational Patterns of Litter Decomposition in Dongling Mountain, Beijing. Forests, 16(4), 584. https://doi.org/10.3390/f16040584

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