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Article

Altitudinal Variation in Soil Acid Phosphomonoesterase Activity in Subalpine Coniferous Forests in China

by
Xiaoli He
1,
Shile Dai
1,
Tingting Ma
1,
Tao Zhang
1,
Junbo He
2,3 and
Yanhong Wu
2,*
1
College of Resource Environment and Tourism, Hubei University of Arts and Sciences, Xiangyang 441053, China
2
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China
3
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Forests 2024, 15(10), 1729; https://doi.org/10.3390/f15101729
Submission received: 29 August 2024 / Revised: 26 September 2024 / Accepted: 26 September 2024 / Published: 29 September 2024
(This article belongs to the Special Issue Forest Soil Physical, Chemical, and Biological Properties)
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Abstract

:
Studying the altitudinal variation and driving factors of soil acid phosphomonoesterase (ACP) activity in subalpine regions is crucial for understanding nutrient cycling processes within mountainous ecosystems. This study focused on fir (Abies fabri (Mast.) Craib) forests located at three altitudes (2781 m, 3044 m, and 3210 m) on the eastern slope of Mt. Gongga in southwest China. We measured soil ACP activity alongside soil climate, nutrients, and microorganisms at various depths and elevations to investigate how these factors influence ACP activity. The results indicated that in the organic matter horizons (Oe and Oa horizons), ACP activity gradually decreased with elevation. However, the surface mineral horizon (A horizon) did not show a decline in ACP activity with increasing elevation, which could be attributed to significantly lower ACP activity recorded at the 2781 m sample site compared to the 3044 m site. Variance partitioning analysis revealed that among soil climate, nutrients, and microorganisms, soil nutrients had the most substantial impact on ACP activity across all horizons, with a particularly high contribution of 89.4% observed in the A horizon. Random forest model analysis further demonstrated that soil total carbon (TC) played a crucial role in determining ACP activity in the Oe and Oa horizons, with importance values of 8.5% and 7.3%, respectively. Additionally, soil total nitrogen (TN) was identified as the primary factor influencing ACP activity in the A horizon, with an importance value of 12.6%. Furthermore, soil ACP activity was positively regulated by the soil TC:TP and TN:TP ratios, indicating a stoichiometric control of ACP activity in the Abies fabri (Mast.) Craib forests on Mt. Gongga.

1. Introduction

Phosphorus is a crucial nutrient regulating the function and primary productivity of terrestrial forest ecosystems [1]. In most alpine and sub-alpine soils, organic phosphorus constitutes the majority of total phosphorus [2,3]. Organisms can only assimilate free phosphate, which is primarily hydrolyzed from phosphomonoesters that constitute a significant portion of organic phosphorus in montane forest soil [4]. Phosphomonoesterases thus likely play a vital role in organic phosphorus mineralization and in mediating the overall phosphorus availability to organisms [5,6].
Scholars have made significant progress in researching the activity of forest soil phosphomonoesterases [7,8]. However, there remains no consensus regarding the impact of soil phosphomonoesterases along forest altitude gradients. For example, studies conducted in the temperate forests of Cuenca Mountain in Spain (960–1670 m a.s.l.) [9] and the Wuyi Mountains in China (650 and 1850 m a.s.l.) [10] observed an increase in soil phosphomonoesterase activities with altitude. In contrast, Hofmann et al. reported a decrease in soil phosphomonoesterases activities with increasing altitude across three vegetation types in the Austrian Alps, while Cao et al. noted similar trends in five vegetation types within the alpine valley area of Sichuan Province, China [11,12]. These discrepancies may be attributed to variations in altitude scales. Previous research has primarily focused on the activities of phosphomonoesterases across a broad range of altitudes and vegetation types. Changes in altitude gradients not only affect temperature and precipitation but also lead to shifts in vegetation types, impacting soil microbial communities and, consequently, soil phosphomonoesterase activity [13,14]. Furthermore, variations in vegetation types along altitude gradients can indirectly influence the physical and chemical properties of forest soil, such as pH, organic matter content, and soil structure, all of which are crucial for determining soil phosphomonoesterase activity [15,16]. Consequently, it is crucial to examine changes in soil phosphomonoesterase activity and its influencing factors at altitudes while controlling for vegetation types.
In addition to variations in vegetation types, the activity of soil phosphomonoesterase at different altitudes is also affected by factors including soil climate and nutrient properties. Changes in altitude create gradients of hydrothermal conditions [9,10]. Previous studies have demonstrated that temperature can directly or indirectly affect soil phosphomonoesterase activity, with optimal temperatures promoting this activity [17,18]. Furthermore, Zuccarini et al. [19] found that soil moisture significantly impacts soil phosphomonoesterase activity. It is important to note that an increase in temperature alone is insufficient; adequate moisture conditions are also necessary to enhance soil phosphomonoesterase activity. In terms of nutrient factors, the activity of phosphomonoesterase is mainly influenced by the organisms’ need for phosphorus and the environmental availability of this nutrient [20,21]. This regulation also encompasses other edaphic factors, such as the availability of carbon and nitrogen [22,23,24]. Soil phosphomonoesterase activity is typically inversely related to soil phosphorus availability due to negative feedback from available phosphorus on the production and activity of phosphomonoesterase [20]. However, a positive relationship may exist between phosphomonoesterase activity and the amount of extractable organic phosphorus in the soil, as the presence of hydrolyzable organic phosphorus sources can enhance phosphomonoesterase activity [25]. Additionally, soil phosphomonoesterase activity is usually reported to correlate positively with the availability of carbon and nitrogen present in the soil [22,23]. This correlation is primarily attributed to the fact that the production and release of phosphomonoesterase are significant processes that consume carbon and nitrogen [22]. Various environmental factors influence soil phosphomonoesterase activity, resulting in considerable variability in the relationships between this activity and soil properties within mountainous ecosystems [23,26]. Consequently, the underlying drivers of soil phosphomonoesterase activity in mountainous forests remain unclear.
Situated on the southeastern boundary of the Tibetan Plateau, Mt. Gongga features a diverse vertical spectrum of vegetation, making it a significant area for research on forest ecosystem material cycles [4]. The Abies fabri (Mast.) Craib forests, which characterize the dark coniferous forests in the alpine regions of Southwest China, are predominantly found at elevations ranging from 2700 to 3700 m on Mt. Gongga. Previous research has indicated that organic acids produced by the anaerobic decomposition of substantial amounts of organic matter in this region lead to the acidic leaching of the soil, resulting in a notable increase in soil acidity (pH range: 4.6–5.8) [27]. This phenomenon provides a natural experimental platform for investigating soil ACP activity within the same vegetation type. This study focuses on the soil of Abies fabri (Mast.) Craib forests at three altitudes on Mt. Gongga: specifically at 2781 m, 3044 m, and 3210 m. Given the similar bedrock and vegetation types, soil temperature and moisture may be the dominant factors influencing microbial activity [17,18,19]. We hypothesize that (1) soil ACP activity decreases significantly with increasing altitude due to the association of higher altitudes with harsher environmental conditions and (2) changes in soil ACP activity are significantly influenced by soil climate factors, such as soil temperature and moisture. The potential extracellular activity of ACP and the main soil properties were assessed. The objectives of this study were (1) to elucidate the altitudinal distributions of ACP activities in soil profiles and (2) to evaluate the primary factors that control ACP activities in the Abies fabri (Mast.) Craib forest of Mt. Gongga.

2. Materials and Methods

2.1. Site Description

Mt. Gongga is situated in the southwestern region of China, at the southeastern border of the Tibetan Plateau, with an elevation of 7556 m (Figure 1). The forest is dominated by Abies fabri (Mast.) Craib, which exists at elevations between 2700 and 3700 m a.s.l., making it the primary untouched forest along the eastern slope of Mt. Gongga [27]. This research area experiences the influence of the Eastern Asian Monsoon, and climatic data were obtained from the meteorological station located at 3000 m (29°35′ N, 102°00′ E, 2948 m a.s.l., Table 1). The parent rocks in the study area predominantly originate from glacial deposits and are primarily composed of granitoids [28]. Based on the World Reference Base for Soil Resources [29], the soil type is categorized as Luvisols. The mean oxalate-extractable iron content is 5.7 g kg−1 [27], and the average percentage of clay and silt particles in the surface mineral soils is 31% [30].

2.2. Sampling and Sample Preparation

Three altitudes were selected for sampling: site S1 at 2781 m a.s.l., site S2 at 3044 m a.s.l., and site S3 at 3210 m a.s.l., during May 2016 (Figure 1). Six subplots were randomly established at each site, ensuring a distance of more than 10 m between them. Soil samples were collected from the Oe (fermented/shredded litter, mean thickness of 3.2 cm), Oa (humified litter, mean thickness of 6.9 cm), and A (surface mineral soils, mean thickness of 9.6 cm) horizons. The samples were refrigerated at 4 °C within 4 h post-collection. Following sample collection, hygrochron temperature logger iButtons (MAXIM DS 1923, Wodisen Electronic Technology Co., Ltd., Shanghai, China) were installed to continuously monitor the soil temperature (Temp.) of the organic matter horizons and A horizons.
All samples were sieved through a 2 mm mesh and stored at 4 °C for the determination of ACP, microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and microbial biomass phosphorus (MBP). A subsample was air-dried for 2 weeks before determining other soil chemical properties.

2.3. Analytical Methods

For each sample, a random segment was extracted before it was processed through a 2 mm sieve. The weight was measured when fresh, and the samples were then dried in an oven at 105 °C until a stable weight was determined for soil moisture (Mois.). The pH values were assessed in soil suspensions with a ratio of 1:10 for the Oe and Oa horizons and 1:2.5 for the A horizon. Soil total carbon (TC) and total nitrogen (TN) concentrations were determined using an element analyzer (Elementar vario MACRO cube, Langenselbold, Germany). Total phosphorus (TP) was quantified through sulfuric/perchloric acid digestion followed by colorimetric analysis [31] with a UV2450 (Shimadzu, Kyoto, Japan).
The sequential analysis of soil phosphorus fractions was conducted following the procedure established by Bowman and Cole [32], which was subsequently modified by Sharpley and Smith [33] and Ivanoff et al. [34]. To assess phosphorus bioavailability, inorganic and organic phosphorus extracted with 0.5 mol L−1 NaHCO3 were categorized as labile inorganic phosphorus (LIP) and labile organic phosphorus (LOP), respectively. Organic phosphorus extracted from soil residue using 1 mol L−1 H2SO4 was classified as moderately labile organic phosphorus. The soil residue was further treated with 0.5 mol L−1 NaOH and concentrated HCl to extract the moderately resistant organic phosphorus and highly resistant organic phosphorus fractions. Total organic phosphorus (TOP) was calculated as the sum of LOP, moderately labile organic phosphorus, moderately resistant organic phosphorus, and highly resistant organic phosphorus [32].
The quantification of MBC, MBN, and MBP was conducted through the chloroform fumigation–extraction technique [35,36]. For the determination of MBC and MBN, a 0.5 mol L−1 K2SO4 solution was employed, while Bray-1 solution (0.03 mol L−1 NH4F-0.025 mol L−1 HCl) was utilized for MBP. The concentrations of carbon, nitrogen, and phosphorus in the fumigated soil were subtracted from the corresponding concentrations in the unfumigated soil. The resulting values were then divided by their respective conversion coefficients (0.45 for MBC and 0.4 for both MBN and MBP) to derive the estimated concentrations of MBC, MBN, and MBP. The ACP (EC 3.1.3.2) activity was measured following the standard procedure established by Tabatabai [37], employing p-nitrophenyl phosphate (PNPP) as the substrate at a pH of 6.5 and a temperature of 37 °C. The enzymatic activity was reported in terms of micrograms of p-nitrophenyl produced per gram of soil per hour (μg PNP g−1 h−1).

2.4. Statistical Analyses

The soil properties at various sampling sites were statistically compared using a one-way analysis of variance (ANOVA). When the variables satisfied the criteria for homogeneity, the post hoc tests of Ryan–Einot–Gabriel–Welsch F (R) were employed to identify differences among the groups. Conversely, when the assumption of homogeneity was not met, Tamhane’s post hoc tests were utilized to ensure the accuracy of the findings. A threshold for statistical significance was established at p < 0.05, indicating that any p-value below this threshold would suggest a statistically significant effect. In addition to the ANOVA, a variance partitioning analysis (VPA) [38] and a random forest model (RFM) were applied to assess the extent to which various soil properties contributed to ACP activity. In the results of VPA, a rectangle illustrates 100% of the variation in ACP activity. Soil properties are categorized into three types: soil climate (indicated by the red circle), soil nutrients (blue circle), and soil microorganisms (purple circle). A positive explanatory rate (%) within the circles indicates a more pronounced positive effect on ACP activity, while a negative explanatory rate is interpreted as 0.0%. The overlapping components represent the intersection (not the interaction) of the variation explained by linear models of two or three types of soil properties. The residuals account for the unexplained variation. p < 0.05 indicates statistical significance. RFM employs the increase in mean squared error (%IncMSE) to assess the significance of soil properties. These %IncMSE values may be either positive or negative; a positive value indicates a significant positive influence on ACP activity, while a negative %IncMSE suggests that the removal of this soil property does not result in a substantial increase in mean squared error, implying a minimal effect on ACP activity. For the statistical analysis and graphical representation of the data, several software packages were employed, specifically SPSS version 19.0, Origin version 8.0, and R version 4.0.5.

3. Results

3.1. ACP Activity and Some Other Soil Properties

Although no significant differences were observed among the S1, S2, and S3 sites in the Oa horizon, the ACP activity in the organic matter horizons (Oe and Oa) demonstrated a decreasing trend with increasing altitude (Figure 2). However, the surface mineral horizon (A horizon) did not show a decline in ACP activity with increasing elevation, which could be attributed to the significantly lower ACP activity recorded at the 2781 m sample site compared to the 3044 m site.
As altitude increases, the climatic conditions of the soil become more severe, characterized by a gradual decrease in both soil temperature and moisture across all horizons (Figure 3).
Spatial variations in soil nutrients were observed across different sites and soil horizons (Figure 4). In the Oe horizon, the concentration of TC gradually decreased with elevation (Figure 4a). Other soil nutrients exhibited no significant differences across altitudes (p > 0.05). In the Oa horizon, both TC and TN were found to decrease with increasing altitude, while the opposite trend was noted for TP, LIP, and LOP. In the A horizon, TC, TN, LIP, and TOP were highest at the S2 site, which was consistent with ACP activity.
The variation in soil microorganisms in this study was not pronounced. Aside from the significant difference in MBP among sites in the A horizon, no considerable differences in MBC and MBN were found among the three sites and horizons (Figure 5).
The study also revealed that soil ACP activity at each altitude gradually decreased as the depth of the soil horizon increased (Figure 2), aligning with the observed vertical trends in soil climate, nutrients (with the exception of TOP and TP), and microorganisms across the soil horizons (Figure 3, Figure 4 and Figure 5).

3.2. Impacts of Soil Properties on the ACP Activity

To investigate the effects of soil climate, nutrients, and microorganisms at varying depths and elevations on ACP activity, this study utilized VPA and an RFM on soil samples (Figure 6). The results from the VPA indicated that soil climate, nutrients, and microorganisms exerted similar effects on ACP activity in the Oe and Oa horizons (Figure 6a,b); however, these factors differed significantly in the A horizon (Figure 6c). Notably, soil nutrients had the most substantial impact on ACP activity across all horizons, with a particularly high contribution of 89.4% observed in the A horizon. RFM revealed that TC played a crucial role in determining ACP activity in the Oe and Oa horizons, with importance values of 8.5% and 7.3%, respectively (Figure 6d,e). Furthermore, TN was identified as the primary factor influencing ACP activity in the A horizon, with an importance value of 12.6% (Figure 6f).
Plots of the TC:TP and TN:TP ratios (as X-axis) against ACP activities (as Y-axis) showed that these relationships were more accurately represented by power function curves rather than linear curves (Figure 7).

4. Discussion

4.1. Variation in Soil ACP Activity among Sites and Horizons

The ACP activity in the Oe (7577–15,032 μg PNP g−1 h−1) and Oa (2568–6336) horizons was comparable to previous studies conducted on the Hailuogou glacier chronosequence soils in China (Oe horizon: 6200–12,433; Oa horizon: 2837–8883) [39], mature subtropical forests in China (mixture of Oe to Oa horizon: 6594) [40], and a pine plantation in New Zealand (mixture of Oe to Oa horizon: 6691) [41]. However, these values were generally higher than those observed in a Douglas-fir forest in Canada (mixture of Oe to Oa horizon: 4938) [42], which employed a similar analytical procedure. The mineral soil ACP activity (549–1190) was comparable to previous reports from Hailuogou glacier chronosequence soils (662–1989) [39] and a karri forest in Australia (97–1308) [43]. However, it tended to be higher than measurements from a temperate woodland in northern China (250) [44] and five natural forests in Spain (292–501) [45] while being lower than values reported for mature subtropical forests in China (709–3659) [40] and a jarrah forest in southwestern Australia (654–4132) [46].
In the Oe and Oa horizons, ACP activity exhibited a gradual decrease with elevation (Figure 2), which was consistent with our first hypothesis. However, ACP activity in the A horizon did not demonstrate a decline with increasing elevation. This discrepancy can be attributed primarily to the significantly lower ACP activity observed at the 2781 m site compared to the 3044 m site (p < 0.05, Figure 2). Spatial variations in soil enzyme activity are influenced by a combination of biotic and abiotic factors, including vegetation types [13], soil hydrothermal conditions [9], soil nutrients [21,22,23,24], and soil organisms [1]. Studies conducted by Li et al. and Lucas-Borja et al. have shown that as altitude gradients shift, environmental factors—including plant community composition, litter characteristics, microclimate, and the physical and chemical properties of soil—also undergo corresponding changes [4,9]. Consequently, soil ACP activity was found to be responsive to these environmental alterations [10,11,12]. Considering the similarity in bedrock and vegetation types, it is likely that soil climate and soil nutrients were the primary factors influencing soil ACP activity in the subalpine coniferous forest on the eastern slope of Mt. Gongga.

4.2. Drivers of Spatial Variation in Soil ACP Activity

4.2.1. Soil Climate

Altitude is a crucial factor in mountainous terrain, as variations in altitude lead to changes in hydrothermal conditions [9,10]. Research conducted by Liu et al. and Feng et al. has demonstrated that temperature can directly or indirectly influence enzyme activity, with optimal temperatures promoting ACP activity [17,18]. Zuccarini et al. found that soil moisture significantly affected ACP activity. Specifically, an increase in temperature could enhance soil enzyme activity only under adequate moisture conditions [19]. This study observed that both Temp. and Mois. decreased significantly with increasing altitude, which aligned with the trends observed in ACP activity within the Oe and Oa horizons (Figure 2 and Figure 3). However, ACP activity in the mineral horizons did not show a significant decrease with increasing altitude, which contradicted the observed trends in soil climate within the A horizon (Figure 2). Furthermore, the results of VPA indicated that as soil depth increased, the contribution of soil climate to explaining ACP activity diminished. The explanation rates for the Oe, Oa, and A horizons were 34.2%, 33.7%, and 22.7%, respectively (Figure 6a–c). Additionally, the results of RFM demonstrated that, with the exception of Temp. in the Oe horizon—which exhibited a higher explanation for ACP activity at 7.55%, albeit lower than the 8.50% explanation for TC—the soil climate in the Oa and A horizons displayed lower explanations for ACP activity. Specifically, Mois. in the Oa horizon accounted for only 1.80%, and Temp. in the A horizon contributed an explanation of 5.46% (Figure 6d–f). Consequently, given the similar bedrock and vegetation types in this study area, the observed decreasing trend in ACP activity could be partly attributed to the relatively poorer soil climate. However, it is important to note that soil climate was not the primary controlling factor of ACP activity, particularly in the mineral horizons.

4.2.2. Soil Phosphorus Fractions

Several studies have indicated that ACP activity was influenced by the phosphorus demands of both plants and microorganisms, as well as by the availability of organophosphorus compounds and the degree of phosphorus limitation in the soil [47]. Soil phosphomonoesterase activity is generally inversely associated with the availability of phosphorus in the soil, a phenomenon attributed to negative feedback from available phosphorus on the production and activity of phosphomonoesterase, commonly referred to as endproduct-dependent [20]. Conversely, phosphomonoesterase activity may be positively correlated with the quantity of extractable organic phosphorus, as the presence of hydrolyzable organic phosphorus sources can enhance this activity, termed sources-dependent [25]. In this study, we analyzed the gradient trends of ACP activity in relation to four phosphorus fractions (LIP, LOP, TOP, and TP) across different soil horizons, finding no significant relationships as mentioned above (Figure 2 and Figure 4). Specifically, in the Oe horizon, the concentrations of the four phosphorus fractions showed no significant differences across altitudes (p > 0.05), while ACP activity demonstrated a gradual decline with increasing elevation (Figure 2). In the Oa horizon, TP, LIP, and LOP increased with altitude, whereas ACP activity did not exhibit significant differences across altitudes (p > 0.05). In the A horizon, LIP was highest at the S2 site, consistent with ACP activity, while LOP showed no significant differences across altitudes (p > 0.05). RFM further revealed that each phosphorus fraction had a minimal impact on ACP activity. In the Oe horizon, the phosphorus fraction contributing most significantly was LIP at 3.68%. In the Oa horizon, LOP was the most contributing fraction at 3.28%. In the A horizon, TOP had the highest contribution at 7.81% (Figure 6d–f). These findings suggested that the activation of soil ACP is neither endproduct-dependent nor sources-dependent [48].

4.2.3. Soil TC and TN

Changes in the vertical climate of mountainous areas along the altitude gradient can lead to significant alterations in both the amount and quality of litter input, resulting in notable differences in the structure and activity of soil enzymes at varying altitudes [9,10]. Typically, the activity of soil phosphomonoesterase is found to have a positive correlation with the availability of carbon and nitrogen in the soil [22,23]. This relationship is primarily attributed to the fact that the production and release of phosphomonoesterase are significant processes that consume carbon and nitrogen [22]. In this study, Abies fabri (Mast.) Craib at lower altitudes exhibited a dense canopy, substantial litter input, an abundance of roots and secretions, and thicker humus horizons [49]. These factors contributed to a marked increase in soil carbon and nitrogen content (Figure 4a,b). The nutrients released during decomposition provided optimal energy for enzymatic reactions. By comparing the gradient changes in ACP activity alongside TC and TN across each soil horizon, it was observed that their trends were largely consistent (Figure 2 and Figure 4a,b). Furthermore, the results of VPA indicated that soil nutrients were the most significant predictors of ACP activity in all horizons. The explanation rates for the Oe, Oa, and A horizons were 51.6%, 37.6%, and 89.4%, respectively (Figure 6a–c). RFM further revealed that TC was a critical determinant of ACP activity in the Oe and Oa horizons, while TN emerged as the primary factor influencing ACP activity in the A horizon (Figure 6d–f). Additionally, soil ACP activity was positively regulated by the ratios of TC:TP and TN:TP (Figure 7). This indicated a stoichiometric regulation of ACP activity within the Abies fabri (Mast.) Craib forests are located on Mt. Gongga, thus reinforcing the proposed model of resource distribution for the production of extracellular enzymes [50,51]. Subalpine forests in the eastern Tibetan Plateau are influenced by the monsoon climate and are generally established on young substrates characterized by a phosphorus-rich status due to the rapid uplift of the Tibetan Plateau [52]. Consequently, carbon and nitrogen are more likely to become limiting resources for soil microorganisms compared to phosphorus, given the scarcity of assimilable organic carbon [53] and the absence of nitrogen-fixing plant species in mature forests outside tropical regions [54]. Unlike the Oe and Oa horizons, ACP activity in the A horizon did not exhibit a decrease with increasing elevation. This observation was attributed to the significantly lower ACP activity recorded at the 2781 m sample site compared to the 3044 m site (Figure 2). Previous research on the distribution characteristics of soil carbon, nitrogen, and phosphorus on the eastern slope of Mt. Gongga indicated that a significant leaching process at the 2781 m site resulted in substantial losses of carbon and nitrogen nutrients [27], leading to a marked reduction in ACP activity at this elevation. In summary, given the similar bedrocks, soil types, and vegetation types, soil TC and TN exerted a more pronounced influence on soil ACP activity than climatic factors [55].

5. Conclusions

To elucidate the altitudinal variation and driving factors influencing ACP activity in Abies fabri (Mast.) Craib forests on the eastern slope of Mt. Gongga, we measured soil ACP activity alongside soil climate, nutrients, and microorganisms at various depths and elevations. Our findings revealed that ACP activity in the organic matter horizons exhibited a gradual decline with increasing elevation; however, the surface mineral horizon did not demonstrate a similar decrease. Variance partitioning analyses and the random forest model indicated that TC was pivotal in determining ACP activity within the organic matter horizons, while TN emerged as the primary factor affecting ACP activity in the surface mineral horizon. Furthermore, the observed positive correlations between the soil TC:TP and TN:TP ratios and ACP activity supported the resource allocation model for the production of extracellular enzymes, highlighting the advantages of employing a stoichiometric perspective to identify the essential environmental factors that govern ACP activity. Although this study has demonstrated that the production and release of ACP are critical processes consuming carbon and nitrogen, it is limited by the availability of data concerning microbial communities and their associated genes. This deficiency poses challenges in accurately quantifying the role of soil microorganisms in ACP activity. In response to this limitation, future studies are planned to investigate the microbial community structure and gene expression patterns related to ACP activity.

Author Contributions

Conceptualization, X.H. and Y.W.; Methodology, Y.W.; Software, S.D.; Data curation, T.Z.; Writing—original draft, X.H.; Writing—review & editing, T.M. and J.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Hubei Provincial Natural Science Foundation of China (No. 2022CFB783); the Scientific Research Plan of Hubei Provincial Education Department (No. B2023151); the Young Top-notch Talent Cultivation Program of Hubei Province, Outstanding Young and Middle-aged Science and Technology Innovation Team Project of the Hubei Provincial Department of Education (HPDE) (T2020016); the Training Fund Program for Scientific Research of Hubei University of Arts and Science (No. 2021kpgpzk10). And The APC was funded by the Scientific Research Plan of Hubei Provincial Education Department (No. B2023151).

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Location of the Mt. Gongga and sampling sites.
Figure 1. Location of the Mt. Gongga and sampling sites.
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Figure 2. Comparison of ACP activity among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga. The different lowercase letters positioned above the error bars signify statistically significant differences (p < 0.05) among the sites.
Figure 2. Comparison of ACP activity among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga. The different lowercase letters positioned above the error bars signify statistically significant differences (p < 0.05) among the sites.
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Figure 3. Comparison of soil climate among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga: (a,b) Soil temperature and moisture at the sampling sites. Different lowercase letters in the point plot denote significant differences (p < 0.05) among the sites. Soil temperature for the Oa horizon derived from data collected in the Oe horizon.
Figure 3. Comparison of soil climate among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga: (a,b) Soil temperature and moisture at the sampling sites. Different lowercase letters in the point plot denote significant differences (p < 0.05) among the sites. Soil temperature for the Oa horizon derived from data collected in the Oe horizon.
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Figure 4. Comparison of soil nutrients among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga: (a–c) Soil total carbon, nitrogen, and phosphorus at the sampling sites. (d–f) Soil labile inorganic phosphorus, labile organic phosphorus, and total organic phosphorus at the sampling sites. Different lowercase letters above the error bars indicate significant differences (p < 0.05) among the sites.
Figure 4. Comparison of soil nutrients among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga: (a–c) Soil total carbon, nitrogen, and phosphorus at the sampling sites. (d–f) Soil labile inorganic phosphorus, labile organic phosphorus, and total organic phosphorus at the sampling sites. Different lowercase letters above the error bars indicate significant differences (p < 0.05) among the sites.
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Figure 5. Comparison of soil microorganisms among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga: (a–c) Soil microbial biomass carbon, microbial biomass nitrogen, and microbial biomass phosphorus for the sampling sites. Different lowercase letters positioned above the error bars denote statistically significant differences (p < 0.05) among the sites.
Figure 5. Comparison of soil microorganisms among sites and horizons in the Abies fabri (Mast.) Craib forest on Mt. Gongga: (a–c) Soil microbial biomass carbon, microbial biomass nitrogen, and microbial biomass phosphorus for the sampling sites. Different lowercase letters positioned above the error bars denote statistically significant differences (p < 0.05) among the sites.
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Figure 6. VPA and RFM determining the influences of soil climate, soil nutrients, and soil microorganisms on ACP activity: (a–c) VPA determining the influences of soil properties on ACP activity in the Oe, Oa, and A horizons, respectively. Soil climate encompasses Temp. and Mois. Soil nutrients include the concentrations of soil TC, TN, TP, LIP, LOP, and TOP. Soil microorganisms are represented by the concentrations of MBC, MBN, and MBP. (d–f) RFM determining the influences of soil properties on ACP activity in the Oe, Oa, and A horizons, respectively. %IncMSE values are visually represented by orange, yellow, and green bars corresponding to the Oe, Oa, and A horizons, respectively. Temp. denotes soil temperature. Mois. refers to soil moisture. TC, TN, and TP represent the concentrations of soil total carbon, nitrogen, and phosphorus, respectively. LIP stands for labile inorganic phosphorus, LOP for labile organic phosphorus, and TOP for total organic phosphorus. MBC, MBN, and MBP represent the concentrations of microbial biomass carbon, nitrogen, and phosphorus, respectively.
Figure 6. VPA and RFM determining the influences of soil climate, soil nutrients, and soil microorganisms on ACP activity: (a–c) VPA determining the influences of soil properties on ACP activity in the Oe, Oa, and A horizons, respectively. Soil climate encompasses Temp. and Mois. Soil nutrients include the concentrations of soil TC, TN, TP, LIP, LOP, and TOP. Soil microorganisms are represented by the concentrations of MBC, MBN, and MBP. (d–f) RFM determining the influences of soil properties on ACP activity in the Oe, Oa, and A horizons, respectively. %IncMSE values are visually represented by orange, yellow, and green bars corresponding to the Oe, Oa, and A horizons, respectively. Temp. denotes soil temperature. Mois. refers to soil moisture. TC, TN, and TP represent the concentrations of soil total carbon, nitrogen, and phosphorus, respectively. LIP stands for labile inorganic phosphorus, LOP for labile organic phosphorus, and TOP for total organic phosphorus. MBC, MBN, and MBP represent the concentrations of microbial biomass carbon, nitrogen, and phosphorus, respectively.
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Figure 7. ACP activity as a function of (a) soil TC:TP ratio and (b) soil TN:TP ratio in the Abies fabri (Mast.) Craib forest on Mt. Gongga. The solid lines in both panels represent power function curves.
Figure 7. ACP activity as a function of (a) soil TC:TP ratio and (b) soil TN:TP ratio in the Abies fabri (Mast.) Craib forest on Mt. Gongga. The solid lines in both panels represent power function curves.
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Table 1. Climate characteristics of the Mt. Gongga.
Table 1. Climate characteristics of the Mt. Gongga.
Latitude
and Longitude		Mean Annual Temperature
(°C)		Monthly Mean Temperature
(°C)		Mean Annual Precipitation
(mm)		Mean Annual Humidity
(%)		Mean Annual Potential Evaporation
(mm)
JanuaryJuly
29°20′–30°20′ N, 101°30′–102°15′ E4.2−4.612.5194790327
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He, X.; Dai, S.; Ma, T.; Zhang, T.; He, J.; Wu, Y. Altitudinal Variation in Soil Acid Phosphomonoesterase Activity in Subalpine Coniferous Forests in China. Forests 2024, 15, 1729. https://doi.org/10.3390/f15101729

AMA Style

He X, Dai S, Ma T, Zhang T, He J, Wu Y. Altitudinal Variation in Soil Acid Phosphomonoesterase Activity in Subalpine Coniferous Forests in China. Forests. 2024; 15(10):1729. https://doi.org/10.3390/f15101729

Chicago/Turabian Style

He, Xiaoli, Shile Dai, Tingting Ma, Tao Zhang, Junbo He, and Yanhong Wu. 2024. "Altitudinal Variation in Soil Acid Phosphomonoesterase Activity in Subalpine Coniferous Forests in China" Forests 15, no. 10: 1729. https://doi.org/10.3390/f15101729

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