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Article

Long-Term Effects of Potassium Fertilization and Wheat Straw Return on Cropland Soil Fertility and Microorganisms in the Qinghai–Tibet Plateau

by
Tingting Xu
1,2,
Rong Zhang
2,
Yang Zhang
2,
Xiaojun Wang
1,
Zhengpeng Li
2 and
Yajun Gao
1,*
1
College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, China
2
Academy of Agriculture and Forestry Sciences, Qinghai University, Xining 810016, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(3), 742; https://doi.org/10.3390/agronomy15030742
Submission received: 24 February 2025 / Revised: 14 March 2025 / Accepted: 18 March 2025 / Published: 19 March 2025
(This article belongs to the Section Soil and Plant Nutrition)
Browse Figures
Versions Notes

Abstract

:
Imbalanced fertilization and inadequate of straw return have led to soil potassium (K) depletion and fertility decline in croplands of the Qinghai–Tibet Plateau. However, how these changes affect soil microbial communities remains unclear. We analyzed soil properties, microbial biomass carbon and nitrogen, enzyme activities, and microbial communities in a long-term field experiment initiated in 1992 with K fertilization and varying wheat straw return amounts. Long-term K application significantly reduced microbial biomass carbon (MBC) and bacterial species richness and inhibited positive bacteria–fungi interactions. By contrast, long-term straw return not only enhanced soil organic carbon (SOC), total nitrogen (TN), available phosphorus (AP), and available potassium (AK) but also increased MBC, microbial biomass nitrogen (MBN), enzyme activities, and fungal species richness. Furthermore, it restructured microbial community composition and improved the stability and connectivity of microbial co-occurrence networks. Critically, these benefits did not scale linearly with straw input quantity. Excessive straw return (>5000 kg ha−1) reduced beneficial effects, destabilized microbial interactions, and elevated risks associated with parasitic protozoa. Balanced potassium application with moderate straw return (approximately 5000 kg ha−1) enhances soil fertility and promotes positive microbial effects in croplands on the Qinghai–Tibet Plateau.

1. Introduction

The Qinghai–Tibet Plateau (QTP) is recognized as a globally significant high-elevation agricultural and pastoral region distinguished by its unique climatic and geographical conditions. This region is characterized by the cultivation of crops such as spring wheat, barley, spring rape, and potatoes. Spring wheat is a traditional crop cultivated in the QTP region, particularly in areas with relatively favorable water and nutrient conditions. However, the primary ecological and environmental challenges for agricultural production on the QTP include low temperatures, frost damage, drought, and soil erosion [1,2,3,4]. Based on the findings from the second comprehensive scientific expedition to the QTP, it has been revealed that cropland soil in the region is confronted with issues of declining fertility and insufficient research on soil microorganisms [5]. Meanwhile, research on soil organic carbon (SOC), nitrogen, and soil microorganisms in glacial, grassland, wetland, and forest ecosystems of the region has garnered increasing attention [6,7,8,9,10]. On the QTP, the period suitable for soil microbial activity is relatively brief, lasting approximately six months annually. For the remainder of the year, the soil remains in a low-temperature and frozen state, which significantly constrains the effective conversion of potential soil fertility. Fertilization and straw return can substantially maintain and enhance soil fertility, particularly by increasing SOC content and the availability of essential nutrients [11,12,13,14]. However, current research on straw return amounts is still limited [15,16]. Particularly in the QTP, low temperatures and drought conditions significantly impact straw decomposition and nutrient transformation. Therefore, research on optimal straw return amounts is especially important in this region.
With the increasing use of nitrogen (N) and phosphate (P) fertilizers, K fertilizers have often been overlooked globally. Approximately 20% of the world’s agricultural soil is experiencing significant K deficiencies, with the amount of applied K fertilizer typically accounting for less than 35% of K uptake by crops [17,18,19]. Long-term K deficiency in soil reserves negatively impacts crop yield and quality, as well as soil fertility and overall quality [20]. In addition to K fertilizer application, straw return also effectively replenishes soil K, thereby reducing the reliance on limited and valuable K fertilizer resources [21,22]. Moreover, the distinct impacts of K fertilization and straw return on soil fertility and microbial communities require long-term positioning trials for verification. In 1992, a long-term K fertilization and varying wheat straw return amount experiment was initiated in Qinghai Province, situated in the northeastern part of the QTP. In this region, Kastanozems is the predominant soil type in croplands and is considered to be K rich [23]. Therefore, the non-application of K fertilizer often leads to N, P, and K imbalances in cropland soil. Conducting long-term field experiments to evaluate optimal fertilization and straw return practices will contribute to maintaining and enhancing the fertility and quality of cropland soil.
Soil microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) represent the carbon and nitrogen contents of bacteria and fungi. Despite their low contents in soil, MBC and MBN play an indispensable role in stimulating soil microbial activity [24,25]. Soil microorganisms contribute to nutrient cycling through the secretion of extracellular enzymes, facilitating the transformation of organic matter and energy exchange within the soil [26]. A majority of studies have demonstrated that long-term fertilization and straw return significantly influence microbial biomass carbon and nitrogen, as well as enzyme activity [27,28,29,30,31]. These properties serve as effective indicators for quantifying the activity of microbial communities. Soil bacteria and fungi are key components of soil microorganisms, playing crucial roles in substance and energy transformation, nutrient cycling and metabolism, and the decomposition and transformation of organic matter [32]. The soil microbiome is highly structured, with diverse microbial groups forming intricate interactions. Microbial co-occurrence networks help to elucidate these complex ecological relationships and provide insights into community structure and stability [33,34]. Microbial diversity, community composition, and co-occurrence networks are affected by climate change, crop rotation systems, and also by fertilization and straw return [35,36,37,38,39,40]. These factors collectively influence microorganisms by modifying key environmental conditions, such as temperature, moisture, and nutrient availability, thereby regulating and reshaping the structure of microbial communities and their interactions. These long-term complex changes and interrelationships require further research to elucidate.
Based on soil property analysis and high-throughput sequencing of bacterial 16S rRNA and fungal ITS1, this study investigates the differential effects of K fertilization and varying straw return amounts on soil nutrients, MBC, MBN, extracellular enzyme activity, bacterial and fungal diversity, community composition, co-occurrence networks, as well as the interrelationships between environmental factors and microorganisms. The objective of the present study was to optimize fertilization strategies, particularly in ecologically fragile high-altitude regions such as the QTP.

2. Materials and Methods

2.1. Site Description

The long-term K fertilization and wheat straw return experiment was initiated in 1992 at the experimental base of Qinghai Academy of Agriculture and Forestry Science (QAAF) in Xining (36°34′03″ N, 101°49′17″ E, altitude of 2360 m), Qinghai Province, China (Figure 1). The region is characterized by a semi-arid continental climate, with an average annual rainfall of 413.6 mm and an average annual temperature of 6.1 °C. Due to the high altitude and cold climate of the QTP, the crop rotation system is generally one crop per year and spring wheat–fallow–spring wheat was the crop rotation for the long-term experiment. The soil of this region is classified as Kastanozems with a medium loam texture, which is the dominant soil type for cultivation. The basic nutrient contents of the soil (0–20 cm) in 1992 were measured as follows: soil organic carbon (SOC) 10.6 g kg−1, total nitrogen (TN) 1.27 g kg−1, nitrate nitrogen (NO3--N) 42.6 mg kg−1, ammonium nitrogen (NH4+-N) 33.8 mg kg−1, available phosphorous (AP, Olsen-P) 30.4 mg kg−1, available potassium (AK, NH4OAc-K) 177.3 mg kg−1, and pH 7.6.

2.2. Experimental Design and Materials

The experiment used a two-factor randomized complete block design with four replicates, and each treatment was arranged in a 25 m2 plot. The two factors were fertilizer application (2 levels, NP and NPK) and wheat straw return (3 levels, None, Half, and Total) (Table 1). Therefore, the long-term experiment included six treatments: NP, NPS50, NPS100, NPK, NPKS50, and NPKS100. N, P, and K represent application of nitrogen, phosphorus, and potassium fertilizers, respectively. S50 and S100 indicate 50% and 100% wheat straw return (equivalent to 5000 kg ha−1 and 10,000 kg ha1− dry weight), respectively. The fertilizer application rates were 110 kg N ha−1 (as urea, 46% N), 55.2 kg P2O5 ha−1 (as calcium superphosphate, 12% P2O5), and 150 kg K2O ha−1 (as potassium chloride, 60% K2O). Before sowing spring wheat at the end of March, 70% of the N fertilizer and total P and K fertilizers were applied as basal fertilizer and incorporated into the soil using small-scale tillage. The remaining N fertilizer was applied as top dressing during the jointing stage. From 2019, the spring wheat variety “Plateau 448” was sown at the amount of 372 kg/hm2, with 31 rows per plot, and the row spacing was 15 cm. The spring wheat was flood-irrigated three times during the whole growth period, plus two times in winter and pre-sowing in spring, with five irrigation times in total. The spring wheat seeds were harvested at early August, subsequently dried, and the wheat straws were shred into small fragments with a farm machine and ploughed into different amounts of straw return plots before October (prior to soil freezing) by hand at a digging depth of 15~20 cm (the topsoil layer).

2.3. Soil Sample Processing and Determination

Following the 2021 spring wheat harvest, a total of 24 composite soil samples (6 treatments × 4 replicates) were collected. At each experimental plot, three subsamples were taken from the 0–20 cm depth at equidistant positions along diagonal transects using a stainless-steel auger (inner diameter: 4 cm). Each subsample consisted of 350 g of fresh soil, which was manually homogenized by quartering to form a single composite sample (total ~1.0 kg per plot). The composite fresh soil sample was divided into three portions: (1) one portion was sieved to determine soil water content, enzyme activity, and microbial biomass; (2) another portion was sieved and stored in 15 mL sterile cryogenic storage tubes for amplification of the bacterial 16S V4-V5 region and fungal ITS region (Genesky Biotechnologies Inc., Shanghai, China); and (3) the third portion was air-dried then sieved for the determination of soil properties.
Soil properties were analyzed using the methods described by Bao [41]. Specifically, soil water content (SWC) was determined using the oven-drying method; soil organic carbon (SOC) was measured via the K2Cr2O7 external heating method; total nitrogen (TN) was quantified through H2SO4 digestion followed by analysis with a Kjeldahl nitrogen analyzer (FOSS KjeltecTMT-MKT200, Hillerød, Denmark); total phosphorus (TP) was assessed using H2SO4-HClO4 digestion and molybdenum antimony anti-colorimetry (V5800 spectrophotometer, Shanghai, China); and total potassium (TK) was evaluated using the sodium hydroxide fusion method (AP1200 flame photometer, Shanghai, China). Nitrate nitrogen (NO3−-N) and ammonium nitrogen (NH4+-N) were extracted with 1 M KCl and analyzed using flow injection analysis (AA3, SEALAnalytical, Norderstedt, Germany). Available phosphorus (AP, Olsen-P) was extracted with 0.5 M NaHCO3 and measured on a V5800 spectrophotometer (China), while available potassium (AK, NH4OAc-K) was extracted with 1 M CH3COONH4 and analyzed using an AP1200 flame photometer (China). Soil pH was measured in a soil-to-water ratio of 1:2.5 (Mettler Toledo, FE28-Standard pH meter, Greifensee, Switzerland). Microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) were determined using the chloroform fumigation–extraction method [25,42]. MBC was measured using a total organic carbon analyzer (Shimadzu, TOC-VCPH, Kyoto, Japan), while MBN was analyzed using a flow injection analysis system (AA3, SEAL Analytical, Norderstedt, Germany). β-1,4-glucosidase (βG) and cellobiohydrolase (CBH) are C-acquiring enzymes that degrade fresh cellulose; leucineaminopeptidase (LAP) and N-acetyl-β-D-glucosaminidase (NAG) are N-acquiring enzymes that degrade chitin, peptidoglycan, and protein; and alkaline phosphatase (AKP) is a P-acquiring enzyme that degrades organic phosphorus compounds [43,44]. Soil enzyme activity was measured using the microplate fluorescence method [45].

2.4. DNA Extraction and High Throughput Sequencing

Total genomic DNA from fresh soil was extracted using the FastDNA® SPIN Kit (MP Biomedicals, Santa Ana, CA, USA). The integrity of the total genomic DNA was assessed using agarose gel electrophoresis, the concentration and purity were determined using Nanodrop 2000 and Qubit 3.0 spectrophotometers, and subsequently, the qualified sample was amplified by high-fidelity PCR using the standard bacterial/fungal genomic DNA mix as a positive control. Bacterial genomic DNA and fungus genomic DNA were used as the template to amplify the V4–V5 hypervariable region of the 16S rRNA gene and the ITS1 hypervariable region, respectively. High-throughput sequencing was performed using the Illumina NovaSeq 6000 sequencer. The amplification products were assessed through agarose gel electrophoresis and purified using the Agencourt AMPure XP Kit (Beckman Coulter, CA, USA) to obtain the original library of the sample. After quality inspection of the original library, a double-ended sequencing strategy was used to sequence the library, and then bioinformatics analysis was carried out. The raw sequence data were deposited in the NCBI’s Sequence Read Archive (SRA) under accession numbers PRJNA1226293 and PRJNA1226365 (bacterial and fungal sequences, respectively).

2.5. Statistical and Bioinformatics Analysis

Statistical analysis of soil properties, MBC, MBN, and enzyme activities were performed with IBM SPSS Statistics 26.0. Two-factor analysis of variance (ANOVA) with Tukey’s LSD multiple-comparison test at a significance level of 0.05 was employed to assess the significant differences among K fertilization treatments, varying wheat straw return amount treatments, and the interaction effects of both. The alpha diversity of soil bacteria and fungi was calculated using the vegan package in R version 3.5.1, and the resulting diagrams were generated using Origin 2016. Beta diversity PCoA (principal coordinates analysis) with weighted unifrac distances was calculated using the R packages scatterplot3d, pheatmap, and phyloseq. The resulting plots were generated using the OmicShare platform (https://www.omicshare.com/tools/Home/Soft/pcoa, accessed on 23 December 2024). The linear discriminant analysis effect size (LEfSe) method supports high-dimensional classification comparisons and was used to identify species that were most likely to explain the differences among the six treatments, with a threshold of |LDA| > 2.0 and p < 0.05. The composition and interrelationships of soil bacterial and fungal communities with environmental factors were analyzed using the R packages vegan and ggplot2. LEfSe analysis, redundancy analysis (RDA), and heat maps were generated using the Genesky Biotech Cloud Platform (http://cloud.geneskybiotech.com/#/tools/all, accessed on 25 December 2024). Microbial co-occurrence networks were analyzed with the R package igraph. Phyla with relative abundance greater than 0.1% were used for Spearman correlation analysis, and species with high betweenness centrality were defined as the key species in the co-occurrence networks [33,35]. According to the visualization of Cytoscape V.3.4.0, the top 20 and top 10 bacterial and fungal relative abundances at the phylum level were selected for graphs [46].

3. Results

3.1. Soil Properties, Microbial Biomass, and Enzyme Activities of Long-Term K Fertilization and Wheat Straw Return

Based on nearly three decades of long-term K fertilization and wheat straw return, the fertility of cropland soil has been significantly enhanced (Table 2). Long-term straw return significantly increased the soil water content (SWC) (p < 0.05), soil organic carbon (SOC) (p < 0.01), total nitrogen (TN) (p < 0.01), total potassium (TK) (p < 0.01), ammonium nitrogen (NH4+-N) (p < 0.01), available phosphorus (AP) (p < 0.01), available potassium (AK) (p < 0.01), microbial biomass carbon (MBC) (p < 0.01), microbial biomass nitrogen (MBN) (p < 0.01), β-glucosidase (βG) (p < 0.05), cellobiohydrolase (CBH) (p < 0.01), leucine aminopeptidase (LAP) (p < 0.01), and alkaline phosphatase (AKP) (p < 0.01). Additionally, it significantly reduced the soil pH (p < 0.05), while having no significant effect on total phosphorus (TP), nitrate nitrogen (NO3−-N), and N-acetyl-β-D-glucosaminidase (NAG). By contrast, long-term K fertilization significantly increased AP (p < 0.05), AK (p < 0.01), NAG (p < 0.05), and AKP (p < 0.05), while significantly decreasing MBC (p < 0.05). The interaction between K fertilization and straw return was highly significant for AK and pH (p < 0.01). Except for NO3−-N and NAG, all other properties exhibited significant differences among the six treatments. SOC, TN, AP, and AK showed significant differences between 50% and 100% straw return without K fertilization, whereas only AK exhibited significant differences among varying amounts of straw return with K fertilization. Although the balanced fertilization with total amount of straw return treatment (NPKS100) generally had the highest values for most properties, no statistically significant differences were observed among the NPKS100, NPKS50, and NPS100 treatments, except for AK. Compared with the NP treatment, there were no significant differences in most properties with the balanced fertilization treatment (NPK), except for AK and pH.

3.2. Diversity and Composition of Soil Bacterial and Fungal Communities

3.2.1. Alpha Diversity

Long-term K fertilization significantly reduced the richness (species number, Chao1 and ACE indexes) of soil bacterial communities, whereas 100% straw return significantly increased the number of fungal species and Chao1 and ACE indexes compared to the non-straw return treatments (Figure 2). Long-term K fertilization and straw return had no significant effect on the diversity (Shannon and Simpson indexes) of soil bacterial and fungal communities, except for the Simpson index of soil bacterial communities (Figure 3). Notably, the 50% straw return without K fertilization treatment (NPS50) exhibited the highest bacterial species richness, significantly higher than both the NPK and NPKS100 treatments. Meanwhile, the NPS100 treatment showed the highest bacterial Shannon index and the lowest bacterial Simpson index. Additionally, the NPKS50 treatment had the highest fungal species richness and Shannon index but the lowest Simpson index, whereas the NP treatment exhibited the opposite trend.

3.2.2. Beta Diversity

Unconstrained principal coordinate analysis (PCoA) of soil bacterial and fungal communities using weighted unifrac distances showed that the straw return treatments were distinctly separated from the non-straw return treatments along the first two principal coordinate axes (p < 0.001, PERMANOVA by Adonis) (Figure 4). The result indicated significant differences in community composition between the straw return and non-straw return treatments. However, bacterial and fungal communities exhibited similar compositions across the varying amounts of straw return treatments, particularly the NPS100 and NPKS100 treatments.

3.2.3. Community Composition and Differential Microorganisms

For the bacterial community, all sequences were classified into 28 phyla. The dominant bacterial phyla (relative abundance > 1%) across all six treatments were as follows: Proteobacteria (29.14–35.43%), Actinobacteria (14.55–20.56%), Acidobacteria (10.78–14.99%), Chloroflexi (7.36–12.02%), Planctomycetes (7.00–9.43%), Bacteroidetes (4.54–11.31%), WPS-1 (1.77–2.34%), Gemmatimonadetes (1.00–2.04%), Nitrospirae (1.12–2.00%), Firmicutes (0.68–1.22%), and Verrucomicrobia (0.70–1.60%) (Figure 5a). The relative abundances of Proteobacteria, Planctomycetes, and Bacteroidetes were significantly higher in the straw return treatments compared to the non-straw return treatments (NP and NPK), while those of Chloroflexi, Gemmatimonadetes, and Armatimonadetes were significantly lower. LEfSe analysis (linear discriminant analysis effect size) identified a total of 141 species with significant differences among the six treatments. Proteobacteria (43 species) were significantly enriched in the NPKS100 and NPS100 treatments. Actinobacteria (32 species), Bacteroidetes (8 species), and Firmicutes (7 species) were significantly enriched in the NPKS100 treatment. Planctomycetes (8 species) were enriched in the NPS100 treatment. Gemmatimonadetes (8 species) were present exclusively in both the NP and NPK treatments. Chloroflexi (23 species) and Nitrospirae (7 species) were the most enriched in the NP treatment, while Armatimonadetes (5 species) were exclusive to the NP treatment (Figure 5b).
For the fungal community, all sequences were classified into 14 phyla. The dominant fungal phyla (relative abundance > 1%) across all six treatments were as follows: Ascomycota (51.28–70.87%), Mortierellomycota (11.24–26.81%), Basidiomycota (2.62–8.63%), and Chytridiomycota (0.41–7.05%) (Figure 5c). The relative abundances of Chytridiomycota, Zoopagomycota, and Rozellomycota were significantly higher in the straw return treatments compared to the non-straw return treatments. LEfSe analysis identified a total of 158 species with significant differences among the six treatments. Ascomycota (114 species) were significantly enriched in the NPK and NP treatments, while Mortierellomycota (4 species) were present in both the NP and NPK treatments. Basidiomycota (29 species) were significantly enriched in the NPS100, NPKS100, and NPS50 treatments. Chytridiomycota (5 species) were exclusive to the NPKS100 treatment, while Rozellomycota (6 species) were exclusive to the NPS100 treatment (Figure 5d).

3.3. Co-Occurrence Network Analysis of Soil Bacterial and Fungal Communities

Soil bacterial and fungal co-occurrence network analysis showed that the NPKS50 treatment had the highest number of links (83), comprising 51 positive and 32 negative links (Figure 6 and Table 3). This treatment notably increased the proportion of positive bacteria–fungi and fungi–fungi interactions, suggesting a more stable microbial network structure. By contrast, the NPS100 treatment had the lowest number of links (39), comprising 19 positive and 20 negative links. The NPKS100 treatment showed an intermediate number of links, higher than NPS100 but lower than other treatments, suggesting that excessive straw return did not consistently stabilize the microbial network. Both the NP and NPK treatments displayed fewer positive links compared to negative links, whereas the straw return treatments generally exhibited a higher proportion of positive interactions. These results implied that moderate straw return enhances cooperative effects within the microbial network. Notably, the NP treatment had significantly more bacteria–fungi links than the NPK treatment. Key bacterial phyla with higher degree and betweenness centrality included Bacteroidetes, Armatimonadetes, Actinobacteria, Elusimicrobia, Nitrospirae, Proteobacteria, Gemmatimonadetes, and Chloroflexi. The key fungal phyla comprised Ascomycota, Kickxellomycota, Basidiomycota, Chytridiomycota, and Mortierellomycota. However, the dominant bacterial and fungal phyla varied across treatments. The NPKS50 treatment uniquely demonstrated greater taxonomic diversity and distinct community composition compared to other treatments.

3.4. Correlations Between Soil Microbial Communities and Environmental Factors

Redundancy analysis (RDA) showed that both primary environmental factors and most straw return treatments (NPKS50, NPS100, NPKS100) were predominantly distributed on the positive side of axis 1 (Figure 7). These treatments and associated explanatory variables (MBC, TN, SOC, MBN, SWC, LAP, CBH, AP, βG, TP, AKP, AK, NH4+-N, NAG, TK) correlated strongly with bacterial taxa, including Planctomycetes, Bacteroidetes, Proteobacteria, and Actinobacteria. By contrast, the non-straw return treatments (NP, NPK) and variables such as pH and NO3−-N clustered on the negative side of axis 1, showing associations with Chloroflexi, Gemmatimonadetes, Armatimonadetes, Firmicutes, and Nitrospirae. For fungal communities, the straw return treatments (NPS100, NPKS100) and their explanatory variables (MBC, TP, TN, SOC, MBN, SWC, AP, AK, LAP, CBH, AKP, NH4+-N, βG, TK) were linked to Chytridiomycota, Blastocladiomycota, and Mortierellomycota. Conversely, the non-straw return treatments and variables (pH, NO3−-N, NAG) aligned with Ascomycota on the negative side of axis 1. Bacterial community composition was primarily driven by SOC and TN, while fungal communities showed stronger responses to TN and TP.
Significant correlations were observed between environmental factors and microbial taxa (Figure 8). TN, SOC, SWC, MBC, MBN, AKP, AK, and AP showed positive associations (p < 0.01 or p < 0.05) with Bacteroidetes, Proteobacteria, and Hydrogenedentes but negative associations (p < 0.01 or p < 0.05) with Chloroflexi, Gemmatimonadetes, and Armatimonadetes (Figure 8a). For fungal taxa, Rozellomycota exhibited positive correlations (p < 0.01 or p < 0.05) with all environmental factors except pH, TK, NO3−-N, and TP. Blastocladiomycota showed positive associations (p < 0.01 or p < 0.05) with AKP, LAP, CBH, βG, SWC, NAG, AP, AK, and TN. Chytridiomycota were positively correlated (p < 0.01 or p < 0.05) with AP, AK, TN, MBN, SWC, and TP. Zoopagomycota demonstrated positive associations (p < 0.01 or p < 0.05) with AK, SOC, TP, and MBC. Notably, only NH4+-N and TP displayed significant negative correlations (p < 0.01 or p < 0.05) with Basidiomycota and Ascomycota, while no other factors showed negative associations with key fungal taxa (Figure 8b).

4. Discussion

4.1. The Impacts of Long-Term Potassium Fertilization and Wheat Straw Return on Soil Properties

Due to its rich content of essential nutrients, wheat straw return has considerable potential to mitigate deficiencies in soil carbon (C), nitrogen (N), phosphorus (P), and potassium (K) [47,48]. Long-term straw return significantly increased SWC, SOC, TN, TK, NH4+-N, AP, and AK (Table 2), and these results were consistent with those reported in most related studies [13,22,49,50,51,52]. Moreover, SOC, TN, AP, and AK showed significant differences between half and total amounts of straw return without K fertilization. However, most soil properties showed no statistically significant differences between 50% and 100% straw return with balanced fertilization. Although the balanced fertilization with 100% straw return treatment (NPKS100) resulted in the highest values for most soil properties, the rate of increase in these properties declined as the quantity of straw return increased. Straw return at rates of 3000 to 6000 kg ha−1 had the greatest improvement effect on crop yield, SOC, AP, AK, and TN [15,21,53]. In our experiment, a half rate of straw return was set at 5000 kg ha−1, representing the moderate amount of straw return under balanced fertilization. Straw return exceeding a certain quantity is not conducive to improving soil structure and may adversely affect soil nutrient transformation [54,55]. Compared with the NP treatment, most soil properties showed no significant differences under the balanced fertilization treatment (NPK). This is likely attributable to the soil’s inherently high AK content (177.3 mg kg−1 In 1992). Over the course of nearly three decades, the AK content in the NP and NPS50 treatments decreased by 46.25% and 27.54%, respectively, while the NPS100 treatment remained consistent with the initial level. By contrast, the AK content in the NPK, NPKS50, and NPKS100 treatments increased by 39.34%, 79.78%, and 122.97%, respectively, indicating significantly higher potassium levels in the soil.

4.2. The Impacts of Long-Term Potassium Fertilization and Wheat Straw Return on Microbial Biomass and Enzyme Activities

With or without K fertilization, long-term straw return significantly increased the contents of microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) (Table 2). A majority of studies indicate that straw return increases MBC, and there is a linear relationship between the amount of straw return and MBC change [15,29,30,56,57]. However, there were no significant differences between 50% and 100% straw return in this experiment. A meta-analysis revealed that as the quantity of straw return increases, the rate of increase in MBC exhibits a diminishing trend [29,30]. Notably, MBC was higher without K fertilization, suggesting that K fertilization lead to a decline in MBC, but MBN was not significantly affected by K fertilization. Chen et al. found that in soil with the content of AK exceeding 150 kg ha−1, AK exhibited a significant negative correlation with both MBC and MBN [49]. Excessive AK in the soil may lead to increased soil salinity and degraded soil structure, characterized by elevated chloride ion concentrations, which inhibit microbial metabolic processes.
Compared to the non-straw return treatments (NP and NPK) and NPS50 treatment, the 100% straw return with K fertilization treatment (NPKS100) significantly increased the activities of C-acquisition enzymes βG and CBH. Straw return exhibited a tendency to increase N-acquiring enzyme (NAG) activity, although the difference was not statistically significant. The 100% straw return with K fertilization treatment (NPKS100) significantly increased N-acquiring enzyme (LAP) and P-acquiring enzyme (AKP) activities. Unlike soil properties, enzyme activities exhibited an increasing trend with greater amounts of straw return. Additionally, potassium fertilization significantly enhanced the activities of NAG and AKP. In contrast to soil microbial biomass, high enzyme activities of NAG and AKP require environments with elevated potassium concentrations.

4.3. The Impacts of Long-Term Potassium Fertilization and Wheat Straw Return on Soil Microorganisms

Wheat straw, characterized by a high carbon-to-nitrogen ratio, serves as a stable energy source and microbial substrate with slow mineralization and humification rates [58]. The accumulation and stabilization of carbon improve soil structure stability, enhance nutrient availability, and promote a nutrient-rich environment for microbial activity [14,47,59]. In this study, long-term K fertilization and straw return had no significant effect on the Shannon and Simpson indexes of soil bacterial and fungal communities (Figure 3). Long-term fertilization and straw return promoted the preferential growth of specific bacterial taxa, thereby reducing the diversity of soil microbial communities [27,38]. Straw return had a limited effect on microbial diversity; significant changes in microbial communities occur with major soil alterations [30,60]. However, long-term K fertilization significantly reduced the species number and Chao1 and ACE indexes of soil bacterial communities. By contrast, straw return significantly increased fungal species richness compared to no straw return (Figure 2). Straw return enhances straw decomposition efficiency, facilitates nutrient release, and promotes soil enzymes synthesis and secretion, thereby increasing fungal species richness [60,61]. This is consistent with the observed higher soil nutrient availability and enzyme activities with straw return in this study.
The PCoA results indicated significant differences in the composition of soil bacterial and fungal communities between the straw return and non-straw return treatments (Figure 4). Moreover, the relative abundances of Proteobacteria, Planctomycetes, and Bacteroidetes were significantly higher in the straw return treatments (Figure 5). Proteobacteria play a crucial role in cellulose decomposition and organic carbon accumulation in soil [62,63]. Planctomycetes are predominant degraders of exopolysaccharides (EPS) and are influenced by SOC, Ca2⁺, and pH [64,65]. Bacteroidetes contribute to SOC accumulation and decompose hemicellulose and xylan [66]. Actinobacteria and Firmicutes were significantly enriched in the NPKS100 treatment, rapidly utilizing wheat straw and other degradable carbon compounds in the carbon-rich environment [67,68]. However, Gemmatimonadetes, Chloroflexi, Nitrospirae, and Armatimonadetes were enriched in the NP treatment, suggesting that they may not be suited to high-potassium or high-carbon environments. Gemmatimonadetes shows low sensitivity to soil management and correlates with soil moisture and pH [69].
Ascomycota, Mortierellomycota, and Basidiomycota, which exhibit relatively high abundance among fungal communities, play a dominant role in the decomposition of straw and organic matter [70,71,72]. Ascomycota and Mortierellomycota were enriched in the NP and NPK treatments, while Basidiomycota were significantly enriched in the straw return treatments (Figure 5). Ascomycetes are resilient to environmental stress, utilize diverse resources, and adopt strategies that confer a competitive advantage in soil ecosystems [73]. However, Ascomycota have limited capacity to degrade lignin-rich residues, while Basidiomycota exhibit remarkable efficiency in the degradation of lignocellulosic materials [72]. Ascomycetes possess an enzyme system that is more efficient in degrading cellulose and holocellulose relative to lignin, enabling them to utilize these readily degradable components for rapid growth [71]. As decomposition progresses, the depletion of these components and accumulation of recalcitrant compounds stimulate Basidiomycota activity [70]. Chytridiomycota, Zoopagomycota, and Rozellomycota were exclusively associated with the straw return treatments, indicating a potential risk related to parasitic amoebas [74,75].
Soil microorganisms play a crucial role in regulating nutrient cycling and maintaining biogeochemical processes, which are interconnected and act synergistically to form a complex network. Fungi and bacteria engage in both cooperative and competitive interactions, thereby enhancing the stability and interconnectivity of microbial co-occurrence networks [33]. Soil bacterial and fungal co-occurrence network analysis revealed that the half amount of straw return with balanced fertilization treatment (NPKS50) significantly promoted positive interspecies interactions (Figure 6), thereby enhancing soil nutrient content through the synergistic effects of bacteria and fungi involved in straw decomposition and utilization. And the key bacterial and fungal phyla with higher degree and betweenness centrality exhibited increased mutual interactions, playing a crucial role in nutrient transformation [35]. Moderate straw return was conducive to enhancing positive interactions within the microbial network, consistent with findings from most related studies [51,54]. Compared to the NPK treatment, the NP treatment resulted in a greater degree of association between bacterial and fungal communities and a more robust microbial network structure (Table 3). Long-term application of K fertilizer without straw return appears to negatively affect the stability of the bacterial and fungal interaction network.
Redundancy analysis revealed that bacteria thrive in environments with high levels of both C and N, whereas fungi have higher requirements for N and P (Figure 7). Bacteroidetes, Proteobacteria, Hydrogenedentes, Rozellomycota, Blastocladiomycota, and Chytridiomycota exhibited highly significant or significant positive correlations with SWC, SOC, TN, MBC, MBN, AP, AK, AKP, LAP, CBH, and βG (Figure 8). These findings indicate that these key soil microorganisms thrive in environments where C, N, P, and K are balanced. Key groups within bacterial and fungal communities play multiple roles in C, N, and P cycling, driving changes in the soil microenvironment and modifying soil nutrients. Long-term agricultural practices of single chemical fertilizer application lead to a lack of carbon in the soil, which in turn intensifies the competition among microorganisms [49,76]. Soil pH was negatively correlated with these key bacterial and fungal communities. Among the 145 investigated field experiments, straw return significantly exacerbated soil acidification [77]. Bacteria and fungi can actively alter soil pH and, in turn, soil pH is a major factor that affects soil microbial communities [78].

5. Conclusions

Long-term imbalanced fertilization depletes the soil potassium pool, even in soil initially rich in potassium. Potassium fertilization, particularly when combined with straw return, effectively replenishes soil potassium and maintains nutrient equilibrium. Long-term straw return significantly promotes the accumulation and transformation of carbon, nitrogen, phosphorus, and potassium nutrients, as well as MBC, MBN, and relative enzymes. It also significantly increases the relative abundance of microorganisms involved in straw decomposition and nutrient cycling. Notably, this practice has a stronger influence on bacterial communities compared to fungal communities, with specific bacterial phyla such as Proteobacteria, Actinobacteria, Planctomycetes, and Bacteroidetes and the fungal phylum Basidiomycota being particularly affected. These dominant microbial species exhibit significant positive correlations with the majority of nutrient indicators, implying a requirement for a more nutritionally balanced environment. Unlike straw return, long-term potassium fertilization significantly increased AP, AK, NAG, and AKP, while significantly decreasing MBC and species richness of bacterial communities, thereby negatively impacting the stability of the bacterial–fungal interaction network. The establishment of a nutrient-balanced and microbial stable soil environment through potassium fertilizer application (as part of balanced fertilization) also necessitates moderate straw return. Therefore, optimizing fertilization strategies—especially integrating balanced potassium application with moderate straw return (approximately 5000 kg ha1−)—is essential for regions with fragile ecosystems, such as the Qinghai–Tibet Plateau. This approach enhances soil biological function resilience and supports sustainable agroecosystem development in high-altitude cropland.

Author Contributions

Conceptualization, Y.G. and T.X.; methodology, T.X. and R.Z.; validation, Y.Z., X.W., and Z.L.; formal analysis, T.X. and Z.L.; resources, R.Z.; data curation T.X., Y.Z., and X.W.; writing—original draft preparation, T.X.; writing—review and editing, Y.G.; supervision, Y.G. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Natural Science Foundation of China (NSFC) under Grant No. 32160759 and by the Major Science and Technology Project of Qinghai Province under Grant No. 2019-NK-A11.

Data Availability Statement

The data presented in this study are available upon request from the corresponding author.

Acknowledgments

We are grateful to the Institute of Soil and Fertilizer at the Qinghai Academy of Agricultural and Forestry Sciences for providing the long-term field experimental platform. We also thank all researchers who have made significant contributions to maintaining this platform.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
QTPQinghai–Tibet Plateau
SWCSoil water content
SOCSoil organic carbon
TNTotal nitrogen
TPTotal phosphorus
TKTotal potassium
NO3−-NNitrate nitrogen
NH4+-NAmmonium nitrogen
APAvailable phosphorus
AKAvailable potassium
MBCMicrobial biomass carbon
MBNMicrobial biomass nitrogen
βGβ-1,4-glucosidase
CBHCellobiohydrolase
LAPLeucineaminopeptidase
NAGN-acetyl-β-D-glucosaminidase
AKPAlkaline phosphatase

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Figure 1. Study area (spring wheat seedling stage and post-harvest straw return).
Figure 1. Study area (spring wheat seedling stage and post-harvest straw return).
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Figure 2. Soil bacterial species number (a), Chao1 index (b), and ACE index (c), as well as soil fungal species number (d), Chao1 index (e), and ACE index (f) of varying potassium fertilization and straw return treatments (NP, nitrogen and phosphorus fertilizer; NPS50, nitrogen and phosphorus fertilizer with 50% straw return; NPS100, nitrogen and phosphorus fertilizer with 100% straw return; NPK, nitrogen, phosphorus, and potassium fertilizer; NPKS50, nitrogen, phosphorus, and potassium fertilizer with 50% straw return; NPKS100, nitrogen, phosphorus, and potassium fertilizer with 100% straw return). Different lowercase letters indicate significant differences among the six treatments (Tukey’s LSD, p < 0.05), while capital letters denote significant differences associated with potassium fertilization (K) or varying straw return amounts (S) (Tukey’s LSD, p < 0.05). One asterisk (*) represents a significant difference, and “ns” signifies no significant difference. Each treatment had four replicates (n = 4).
Figure 2. Soil bacterial species number (a), Chao1 index (b), and ACE index (c), as well as soil fungal species number (d), Chao1 index (e), and ACE index (f) of varying potassium fertilization and straw return treatments (NP, nitrogen and phosphorus fertilizer; NPS50, nitrogen and phosphorus fertilizer with 50% straw return; NPS100, nitrogen and phosphorus fertilizer with 100% straw return; NPK, nitrogen, phosphorus, and potassium fertilizer; NPKS50, nitrogen, phosphorus, and potassium fertilizer with 50% straw return; NPKS100, nitrogen, phosphorus, and potassium fertilizer with 100% straw return). Different lowercase letters indicate significant differences among the six treatments (Tukey’s LSD, p < 0.05), while capital letters denote significant differences associated with potassium fertilization (K) or varying straw return amounts (S) (Tukey’s LSD, p < 0.05). One asterisk (*) represents a significant difference, and “ns” signifies no significant difference. Each treatment had four replicates (n = 4).
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Figure 3. Soil bacterial Shannon index (a) and Simpson index (b), as well as soil fungal Shannon index (c) and Simpson index (d) of varying potassium fertilization and straw return treatments. Different lowercase letters indicate significant differences among the six treatments (Tukey’s LSD, p < 0.05), while capital letters denote significant differences associated with potassium fertilization (K) or varying straw return amounts (S) (Tukey’s LSD, p < 0.05). while double asterisks (**) represent a highly significant difference (Tukey’s LSD, p < 0.01), and “ns” signifies no significant difference. Each treatment had four replicates (n = 4).
Figure 3. Soil bacterial Shannon index (a) and Simpson index (b), as well as soil fungal Shannon index (c) and Simpson index (d) of varying potassium fertilization and straw return treatments. Different lowercase letters indicate significant differences among the six treatments (Tukey’s LSD, p < 0.05), while capital letters denote significant differences associated with potassium fertilization (K) or varying straw return amounts (S) (Tukey’s LSD, p < 0.05). while double asterisks (**) represent a highly significant difference (Tukey’s LSD, p < 0.01), and “ns” signifies no significant difference. Each treatment had four replicates (n = 4).
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Figure 4. Unconstrained PCoA analysis with weighted unifrac distances of soil bacterial communities (a) and fungal communities (b) among the six treatments.
Figure 4. Unconstrained PCoA analysis with weighted unifrac distances of soil bacterial communities (a) and fungal communities (b) among the six treatments.
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Figure 5. High relative abundance (a) and LEfSe analysis (b) of soil bacterial communities and high relative abundance (c) and LEfSe analysis (d) of soil fungal communities among the six treatments. Distinct colors denote varying treatments. Nodes of distinct colors indicate species with significantly different relative abundance under the corresponding treatment, while yellow nodes denote no significant difference in relative abundance across varying treatments.
Figure 5. High relative abundance (a) and LEfSe analysis (b) of soil bacterial communities and high relative abundance (c) and LEfSe analysis (d) of soil fungal communities among the six treatments. Distinct colors denote varying treatments. Nodes of distinct colors indicate species with significantly different relative abundance under the corresponding treatment, while yellow nodes denote no significant difference in relative abundance across varying treatments.
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Figure 6. Microbial co-occurrence networks at the phylum level among the six treatments. The color of the circles denotes different kingdoms (red for bacteria, blue for fungi), while the size of the circles indicates the degree and betweenness centrality. Red lines signify positive correlations, whereas green lines represent negative correlations.
Figure 6. Microbial co-occurrence networks at the phylum level among the six treatments. The color of the circles denotes different kingdoms (red for bacteria, blue for fungi), while the size of the circles indicates the degree and betweenness centrality. Red lines signify positive correlations, whereas green lines represent negative correlations.
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Figure 7. RDA analysis of key soil bacterial communities in relation to environmental factors (a) and key soil fungal communities in relation to environmental factors (b) among the six treatments.
Figure 7. RDA analysis of key soil bacterial communities in relation to environmental factors (a) and key soil fungal communities in relation to environmental factors (b) among the six treatments.
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Figure 8. Correlation analysis between key soil bacterial communities and environmental factors (a), and between key soil fungal communities and environmental factors (b). Asterisks denote significance levels: * p < 0.05, ** p < 0.01.
Figure 8. Correlation analysis between key soil bacterial communities and environmental factors (a), and between key soil fungal communities and environmental factors (b). Asterisks denote significance levels: * p < 0.05, ** p < 0.01.
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Table 1. Experimental treatments in the long-term field experiment.
Table 1. Experimental treatments in the long-term field experiment.
FactorLevelDescription
Fertilizer ApplicationNPNitrogen (N) + Phosphate (p) fertilizers (no potassium)
NPKNitrogen (N) + Phosphate (p) + Potassium (K) fertilizers
Wheat Straw ReturnNoneNo straw return
Half50% wheat straw return
Total100% wheat straw return
Table 2. Soil properties, microbial biomass carbon and nitrogen, and enzyme activities of varying potassium fertilization and straw return treatments.
Table 2. Soil properties, microbial biomass carbon and nitrogen, and enzyme activities of varying potassium fertilization and straw return treatments.
PropertiesField Trial TreatmentsSources of Variation
NPNPS50NPS100NPKNPKS50NPKS100Potassium Fertilizer (K)Straw-Return (S)K × S
SWC %18.12 ± 1.15 c19.02 ± 0.40 bc20.38 ± 0.80 ab18.79 ± 1.49 bc20.91 ± 1.82 a20.86 ± 1.13 ans*ns
SOC g kg−113.17 ± 0.75 c15.03 ± 1.37 b16.83 ± 1.20 a13.17 ± 0.67 c15.79 ± 0.69 ab16.97 ± 1.20 ans**ns
TN g kg−11.13 ± 0.12 d1.27 ± 0.02 bc1.39 ± 0.11 a1.18 ± 0.04 cd1.34 ± 0.02 ab1.42 ± 0.09 ans**ns
TP g kg−11.11 ± 0.10 b1.14± 0.04 ab1.17 ± 0.06 ab1.15 ± 0.04 ab1.21 ± 0.06 a1.22 ± 0.08 ansnsns
TK g kg−119.42 ± 0.29 bc19.17 ± 0.19 bc19.47 ± 0.38 bc19.90 ± 0.28 abc20.57 ± 1.38 a19.95 ± 0.59 abcns**ns
NO3−-N mg kg−14.79 ± 0.29 a4.41 ± 0.34 a4.34 ± 0.28 a5.22 ± 1.01 a4.85 ± 0.94 a4.94 ± 0.32 ansnsns
NH4+-N mg kg−15.04 ± 0.34 b5.25 ± 0.62 ab5.80 ± 0.70 a4.79 ± 0.33 b5.37 ± 0.28 ab5.92 ± 0.12 ans**ns
AP mg kg−122.05 ± 3.15 c23.53 ± 2.68 bc28.98 ± 3.45 a23.80 ± 1.35 bc27.98 ± 4.43 ab32.38 ± 3.79 a***ns
AK mg kg−195.30 ± 9.21 f128.47 ± 20.09 e163.40 ± 29.18 d247.05 ± 24.56 c318.75 ± 5.36 b395.33 ± 16.73 a******
pH8.26 ± 0.02 a8.20 ± 0.03 bc8.15 ± 0.02 c8.19 ± 0.06 bc8.19 ± 0.01 bc8.21 ± 0.04 abns***
MBC g kg−1227.31 ± 32.18 ab277.64 ± 59.04 a300.47 ± 57.40 a190.84 ± 45.36 b244.622 ± 60.40 ab294.56 ± 55.97 a***ns
MBN g kg−127.77 ± 4.31 c33.87 ± 4.29 ab37.56 ± 3.68 a 28.96 ± 4.80 bc 32.83 ± 4.61 abc38.28 ± 1.05 ans**ns
βG nmol g−1| h−124.18 ± 6.54 b25.54 ± 3.23 b34.57 ± 3.11 ab24.11 ± 11.56 b32.57 ± 13.80 ab42.17 ± 17.07 ans*ns
CBH nmol g−1 h−13.47 ± 2.10 b3.49 ± 0.11 b7.09 ± 1.17 ab4.16 ± 3.43 b6.23 ± 3.42 ab9.14 ± 5.03 ans**ns
NAG nmol g− 1h−12.24 ± 0.73 a2.49 ± 0.45 a2.32 ± 0.74 a2.41 ± 1.36 a3.16 ± 1.89 a4.06 ± 1.98 a*nsns
LAP nmol g−1 h−114.78 ± 3.47 c19.29 ± 4.09 abc22.91 ± 3.08 ab17.20 ± 4.47 bc19.97 ± 5.11 abc25.72 ± 7.86 ans**ns
AKP nmol g−1 h−169.11 ± 12.91 c89.26 ± 14.54 abc109.32 ± 15.20 abc78.24 ± 27.70 bc111.89 ± 37.01 ab127.00 ± 40.99 a***ns
Different lowercase letters indicate significant differences among the six treatments (Tukey’s LSD, p < 0.05). Asterisks denote significant differences associated with varying levels and interaction effects of potassium fertilization (K) and straw return (S): one asterisk (*) represents a significant difference (Tukey’s LSD, p < 0.05), while double asterisks (**) represent a highly significant difference (Tukey’s LSD, p < 0.01). The notation “ns” signifies no significant difference. Values represent mean ± SD based on four replicates (n = 4).
Table 3. The number of links in the co-occurrence networks among the six treatments.
Table 3. The number of links in the co-occurrence networks among the six treatments.
TreatmentsPositive LinksNegative LinksSum
Bacteria–BacteriaBacteria–FungiFungi–FungiTotalBacteria–BacteriaBacteria–FungiFungi–FungiTotal
NP1015227191113158
NPK15822516522348
NPS50187126191023157
NPKS50143165118953283
NPS1001171198842039
NPKS10011131259621742
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Xu, T.; Zhang, R.; Zhang, Y.; Wang, X.; Li, Z.; Gao, Y. Long-Term Effects of Potassium Fertilization and Wheat Straw Return on Cropland Soil Fertility and Microorganisms in the Qinghai–Tibet Plateau. Agronomy 2025, 15, 742. https://doi.org/10.3390/agronomy15030742

AMA Style

Xu T, Zhang R, Zhang Y, Wang X, Li Z, Gao Y. Long-Term Effects of Potassium Fertilization and Wheat Straw Return on Cropland Soil Fertility and Microorganisms in the Qinghai–Tibet Plateau. Agronomy. 2025; 15(3):742. https://doi.org/10.3390/agronomy15030742

Chicago/Turabian Style

Xu, Tingting, Rong Zhang, Yang Zhang, Xiaojun Wang, Zhengpeng Li, and Yajun Gao. 2025. "Long-Term Effects of Potassium Fertilization and Wheat Straw Return on Cropland Soil Fertility and Microorganisms in the Qinghai–Tibet Plateau" Agronomy 15, no. 3: 742. https://doi.org/10.3390/agronomy15030742

APA Style

Xu, T., Zhang, R., Zhang, Y., Wang, X., Li, Z., & Gao, Y. (2025). Long-Term Effects of Potassium Fertilization and Wheat Straw Return on Cropland Soil Fertility and Microorganisms in the Qinghai–Tibet Plateau. Agronomy, 15(3), 742. https://doi.org/10.3390/agronomy15030742

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