Soil moisture and texture primarily control the soil nutrient stoichiometry across the Tibetan grassland

Effects of drought stress and Morchella inoculation on the physicochemical properties, enzymatic activities, and bacterial community of Poa pratensis L. rhizosphere soil

Background

Soil microorganisms are crucial for plant growth, and both plants and their associated rhizosphere microbes are impacted by changes in soil moisture. Inoculation with beneficial fungi can improve bacterial community structure and soil parameters.

Aim

Under drought stress conditions, the effects of inoculation with Morchella on the physicochemical properties, enzyme activity, and bacterial community structure of the rhizosphere soil of Poa pratensis were studied.

Methods

High-throughput sequencing was employed to study rhizosphere soil bacterial communities in both Morchella-inoculated and uninoculated Poa pratensis rhizosphere soil subjected to moderate (50% soil moisture) and severe (30% soil moisture) drought stress, as well as under normal water conditions (70% soil moisture).

Results

Morchella inoculation significantly increased the alkaline nitrogen (AN) and available phosphorus (AP) contents, protease activity (PA), and alkaline phosphatase activity (APA) of Poa pratensis rhizosphere soil. Both Morchella inoculation and drought stress significantly altered the abundance and diversity of the P. pratensis rhizosphere community. The Chao1, Shannon, and Pielou diversity indices decreased with increasing drought stress. The effect of Morchella inoculation was improved under moderate drought stress and unstressed conditions. In addition, Morchella inoculation may help to stabilize the rhizosphere bacterial community under various levels of soil moisture.

The spatial variations and driving factors of C, N, P stoichiometric characteristics of plant and soil in the terrestrial ecosystem

Carbon(C), nitrogen(N), and phosphorus(P) are crucial elements in the element cycling in the terrestrial ecosystems. In the past decades, the spatial patterns and driving mechanisms of plant and soil ecological stoichiometry have been hot topics in ecological geography. So far, many studies at different spatial and ecological scales have been conducted, but systematic review has not been reported to summarize the research status. In this paper, we tried to fill this gap by reviewing both the spatial variations and driving factors of C, N, P stoichiometric characteristics of plant and soil at regional to large scale. Additionally, we synthesized researches on the relationships between plant and soil C, N and P stoichiometric characteristics. At the global scale, plant C, N, P stoichiometric characteristics exhibited some trends along latitude and temperature gradient. Plant taxonomic classification was the main factor controlling the spatial variations of plant C, N and P stoichiometric characteristics. Climate factor and soil properties showed varying impacts on the spatial variations of plant C, N, P stoichiometric characteristics across different spatial scales. Soil C, N, P stoichiometric characteristics also varied along climate gradient at large scale. Their spatial variations resulted from the combined effects of climate, topography, soil properties, and vegetation characteristics at regional scale. The spatial pattern of soil C, N, P stoichiometric characteristics and the driving effects from environmental factors could be notably different among different ecosystems and vegetation types. Plant C:N:P was obviously higher than that of soil, and there existed a positive correlation between plant and soil C:N:P. Their trends along longitude and latitude were similar, but this correlation varied significantly among different vegetation types. Finally, based on the issues identified in this paper, we highlighted eight potential research themes for the future studies.

A critical systematic review on spectral-based soil nutrient prediction using machine learning

The United Nations (UN) emphasizes the pivotal role of sustainable agriculture in addressing persistent starvation and working towards zero hunger by 2030 through global development. Intensive agricultural practices have adversely impacted soil quality, necessitating soil nutrient analysis for enhancing farm productivity and environmental sustainability. Researchers increasingly turn to Artificial Intelligence (AI) techniques to improve crop yield estimation and optimize soil nutrition management. This study reviews 155 papers published from 2014 to 2024, assessing the use of machine learning (ML) and deep learning (DL) in predicting soil nutrients. It highlights the potential of hyperspectral and multispectral sensors, which enable precise nutrient identification through spectral analysis across multiple bands. The study underscores the importance of feature selection techniques to improve model performance by eliminating redundant spectral bands with weak correlations to targeted nutrients. Additionally, the use of spectral indices, derived from mathematical ratios of spectral bands based on absorption spectra, is examined for its effectiveness in accurately predicting soil nutrient levels. By evaluating various performance measures and datasets related to soil nutrient prediction, this paper offers comprehensive insights into the applicability of AI techniques in optimizing soil nutrition management. The insights gained from this review can inform future research and policy decisions to achieve global development goals and promote environmental sustainability.

Grazing weakens the linkages between plants and soil biotic communities in the alpine grassland

Livestock grazing alters the diversity and composition of plants and soil biota in grassland ecosystems. However, whether and how grazing affects plant-soil biota interactions are limited. Here, we performed a field investigation on the Tibetan grasslands to determine the relationships between plant community properties (biomass, diversity and richness) and soil biota (abundance, diversity and composition of bacteria, fungi and nematodes) in the long-term yak grazing and ungrazed plots, and responses of plant-soil biota linkages to grazing in alpine meadows and alpine swampy meadows were compared. The results found that grazing did not cause significant changes in plant community properties but increased the soil water content. Further, grazing weakened plant-soil microbes/nematode relationships in alpine meadows. The bacterial and fungal abundances were correlated with plant belowground biomass and Simpson index in the ungrazed plots of alpine meadows, while the correlation was not significant under grazing. Bacterial composition was correlated with plant richness only in the ungrazed meadows. Plant-soil nematode linkages were more sensitive to grazing than plant-microbes linkages. Grazing decoupled the relationships between the abundances of nematode trophic groups and plant aboveground biomass, richness and Simpson index in alpine meadows, while the decoupling phenomenon is less evident in alpine swampy meadows. The SEM results indicate that grazing altered the plant above- and belowground biomass to affect the soil nematode community, while influenced soil microbes only through alterations of plant belowground biomass. The findings highlight the importance of grazing in influencing the interactions between aboveground plant communities and soil biological communities in Tibetan grasslands.

Responses of C:N:P stoichiometric correlations among plants, soils and microorganisms to warming: A meta-analysis

Plants, soils and microorganisms play important roles in maintaining stable terrestrial stoichiometry. Studying how nutrient balances of these biotic and abiotic players vary across temperature gradients is important when predicting ecosystem changes on a warming planet. The respective responses of plant, soil and microbial stoichiometric ratios to warming have been observed, however, whether and how the stoichiometric correlations among the three components shift under warming has not been clearly understood and identified. In the present study, we have performed a meta-analysis based on 600 case studies from 74 sites or locations to clarify whether and how warming affects plant, soil and microbial stoichiometry, respectively, and their correlations. Our results indicated that: (1) globally, plants had higher C:N and C:P values compared to soil and microbial pools, but their N:P distributions were similar; (2) warming did not significantly alter plant, soil and microbial C:N and C:P values, but had a noticeable effect on plant N:P ratios. When ecosystem types, duration and magnitude of warming were taken into account, there was an inconsistent and even inverse warming response in terms of the direction and magnitude of changes in the C:N:P ratios occurring among plants, soils and microorganisms; (3) despite various warming responses of the stoichiometric ratios detected separately for plants, soils and microorganisms, the stoichiometric correlations among all three parts remained constant even under different warming scenarios. Our study highlighted the complexity of the effect of warming on the C:N:P stoichiometry, as well as the absence and importance of simultaneous measurements of stoichiometric ratios across different components of terrestrial ecosystems, which should be urgently strengthened in future studies.

Soil bacterial succession with different land uses along a millennial chronosequence derived from the Yangtze River flood plain

Wetlands reclamation has been a traditional and effective practice for obtaining new land to alleviate the pressure induced by population growth. However, the evolution of soil-dwelling microorganisms along with reclamation and the potential influence of land-use patterns on them remain unclear. In this study, a soil chronosequence derived from Yangtze River sediments was established, comprising of circa 0, 60, 160, 280, 2000, and 3000 years, to examine the succession of soil bacterial communities across different land uses. Our analysis revealed obvious development in soil properties and orderly bacterial succession along reclamation gradients. Over time, reclaimed land suffered from varying degrees of abundance loss and biodiversity simplification, with dryland being the most sensitive to reclamation duration changes, whereas woodland and paddies showed slight reductions. Bacterial communities tended to shift from oligotrophs (K-strategist) to copiotrophs (r-strategist) at the phylum level as reclamation proceeded for all land use types. The relative abundance of certain bacterial functional groups associated with the carbon (C) and nitrogen (N) cycles were significantly increased, including those involved in Aerobic chemoheterotrophy, Chitinolysis, Nitrate reduction, Nitrate respiration, and Ureolysis, while other groups, such as those related to Fermentation, Methylotrophy, Nitrification, and Hydrocarbon degradation, exhibited decreased expression. Notably, prolonged reclamation can also trigger ecological issues in soil, including a continuous increase of predatory/exoparasitic bacteria in dryland and woodland, as well as a significant increase in pathogenic bacteria during the later stages in paddy fields. Overall, our study identified the impact of long-term reclamation on soil bacterial communities and functional groups, providing insight into the development of land-use-oriented ecological protection strategies.

Grazing exclusion is more beneficial for restoring soil organic carbon and nutrient balance than afforestation on degraded sandy land

Introduction

Vegetation restoration is an effective measure to improve the ecosystem service of degraded sandy land ecosystem. However, it is unclear how vegetation restoration on severely desertified land affect soil organic carbon (SOC) sequestration and nutrients balance. Therefore, this study was designed to clarify the response of SOC, total nitrogen (TN), total phosphorus (TP), and the resulting stoichiometric ratios (C:N:P) to afforestation and grazing exclusion, and to quantify their dynamics over time.

Methods

We conducted vegetation community investigation and soil sampling in natural sparse-forest grassland (the climax community stage), afforestation (Pinus sylvestris var. mongolica (40-year, 48-year), Caragana microphylla (20-year, 40-year)), and grazing exclusion (20-year, 40-year) in China's Horqin Sandy Land. Soil C:N:P stoichiometry and its driving factors under different restoration measures were then studied.

Results

Afforestation and grazing exclusion significantly (p < 0.05) increased SOC, TN, and TP concentrations. Vegetation restoration significantly increased C:N, C:P, and N:P ratios, indicating that nutrient limitations may occur in the later stages of restoration. The C:N, C:P, and N:P ratios after a 40-year grazing exclusion were closest to those of natural sparse-forest grassland. The N:P under grazing exclusion increased from 3.1 to 4.1 with increasing restoration age (from 20 to 40 years), which was close to the national mean values (4.2). Moreover, afforestation may lead to water deficit in the surface soil. Vegetation restoration is the main factor leading to changes in soil C:N:P stoichiometry, and indirectly affects soil C:N:P stoichiometry by altering soil structure and chemical properties.

Conclusion

In terms of ecological stoichiometry, grazing exclusion was more conducive to restore SOC and nutrient balance than afforestation on severely desertified land. Due to the poor soil nutrients, attentions should be paid to the soil nutrients and water conditions in the later stages of vegetation restoration. Those findings can provide valuable information for the restoration of degraded sandy land in semi-arid areas.

Soil aggregate-driven changes in nutrient redistribution and microbial communities after 10-year organic fertilization

Research studies on nutrient content and microbial communities after the application of organic manure have been reported, while available information about multi-interaction mechanisms of nutrient stoichiometry and microbial succession in soil aggregates remains limited. This work conducted a 10-year field experiment amended with cow manure (1.5 t/ha), during which the application of organic manure stimulated the fragmentation of soil macro-aggregates (>5 mm) and the agglomeration of soil micro-aggregates (<0.25 mm). Hence, the proportion of medium-size aggregates (0.25-5 mm) was increased in bulk soil, and there was an insignificant difference in the stability of soil aggregates. Meanwhile, the application of organic manure increased soil organic carbon (SOC), total nitrogen (TN) and phosphorus (TP) in all soil aggregate fractions. SOC, TN and TP were higher in micro-aggregates (<0.25 mm) after the application of organic manure, thus the dominating phylum of bacteria and fungi was more abundance in micro-aggregates due to the increase in nutrient level. During the organic fertilization process, fungal communities significantly changed because the variation of carbon-to-nitrogen ratio (C:N) in soil aggregates. Cultivated farmland in Northeast China showed a considerable capacity to sequestrate SOC during the organic fertilization process, but nitrogen may be a primary macro-element limiting soil productivity. Theoretically, organic manure amended with nitrogen fertilizer could be an effective measure to maintain microbial diversity and crop productivity in agro-ecosystems in Northeast China.

Driving factors of community-level leaf stoichiometry patterns in a typical temperate mountain meadow ecosystem of northern China

In ecological stoichiometry, the stoichiometry and spatial distribution of leaf carbon, nitrogen, and phosphorus are important research topics. Various studies have assessed leaf stoichiometry and its relationships with environmental factors at different scales. However, how the leaf carbon, nitrogen and phosphorus stoichiometric characteristics of the same vegetation type at the community level vary with environmental factors along a continuous altitudinal gradient remains poorly understood. In this paper, 13 sampling sites along an altitudinal gradient of 1,800-3,011 m in a typical temperate mountain meadow ecosystem on the southern slope of the Wutai Mountain in North China were sampled to explore the response of leaf carbon, nitrogen and phosphorus stoichiometric characteristics to altitude change using correlation analysis, and then quantified the contribution of driving factors using canonical correspondence analysis (CCA) and variation partitioning. We found that the community-level leaf stoichiometry of mountain meadows differed significantly at different altitudes, and an increase in altitude significantly decreased community-level leaf total nitrogen (LTN) and leaf total phosphorus (LTP); however, the leaf total carbon (LTC), C∶N, C∶P, and N∶P increased with an increase in altitude. Additionally, with increasing altitude, soil properties showed significant trends. Soil organic carbon (SOC), soil total nitrogen (STN), soil total phosphorus (STP), soil water content and soil electrical conductivity increased significantly, but soil temperature, soil bulk density and soil pH exhibited the opposite trend. Our results suggested that altitude, soil electrical conductivity and soil bulk density significantly influenced the changes in the leaf stoichiometric characteristics, explaining 75.5% of the total variation, and altitude had the greatest influence (36.6%). In the temperate mountains, altitude played a decisive role in affecting patterns of meadow plant nutrients and stoichiometry and was more important than soil in explaining leaf C∶N∶P stoichiometry variations. Our findings provide important references to understand the responses of plant stoichiometry to altitudinal gradients.

Soil organic carbon primarily control the soil moisture characteristic during forest restoration in subtropical China

Soil organic carbon (SOC) is a crucial component of the soil carbon pool that regulates fundamental soil properties and water status. In the global context of restoring vegetation, the soil carbon-water coupling relationship has gained attention. In particular, the regulatory mechanism of SOC on soil moisture requires further research. In this study, three typical forests in subtropical China were chosen as restoration sequences to investigate the changes in SOC and soil moisture during subtropical forest restoration and its regulation mechanisms: broadleaf-conifer mixed forest (EF), broad-leaved forest (MF), and old-growth forest (LF). The soil water content (35.71 ± 1.52%), maximum water holding capacity (47.74 ± 1.91%), capillary water holding capacity (43.92 ± 1.43%), and field water holding capacity (41.07 ± 1.65%) in LF were significantly higher than those in EF (p &lt; 0.01). As forest restoration progressed, the amount of litter returning to the soil increased gradually, and the SOC content (0–100 cm) increased from 9.51 ± 1.42 g/kg (EF) to 15.60 ± 2.30 g/kg (LF). The SOC storage increased from 29.49 ± 3.59 to 42.62 ± 5.78 Mg/ha. On one hand, forest restoration led to a change in SOC content, which optimizes the soil structure and enhances soil porosity (path coefficient of 0.537, p &lt; 0.01), further leading to a change in soil water content (path coefficient of 0.940, p &lt; 0.01). On the other hand, the increase in SOC influenced the change in soil nutrient content, i.e., total nitrogen (TN) and total phosphorus (TP) (path coefficient of 0.842, p &lt; 0.01). Changes in SOC and soil nutrients stimulated changes in the stoichiometric ratio, i.e., C:P and N:P (path coefficients of 0.988 and –0.968, respectively, p &lt; 0.01), and the biological activity in soil changed appropriately, which eventually led to a change in soil water content (path coefficient of –0.257, p &lt; 0.01). These results highlight the changes in SOC and soil water content (SWC), as well as the mechanism of SOC controlling SWC as a result of vegetation restoration, which is of tremendous importance for advancing our understanding of the eco-hydrological process of subtropical forest restoration.

Aridity and High Salinity, Rather Than Soil Nutrients, Regulate Nitrogen and Phosphorus Stoichiometry in Desert Plants from the Individual to the Community Level

The stoichiometric characteristics of plant nitrogen (N) and phosphorus (P) and their correlations with soil properties are regarded as key for exploring plant physiological and ecological processes and predicting ecosystem functions. However, quantitative studies on the relative contributions of water–salt gradients and nutrient gradients to plant stoichiometry are limited. In addition, previous studies have been conducted at the plant species and individual levels, meaning that how community-scale stoichiometry responds to soil properties is still unclear. Therefore, we selected typical sample strips from 13 sampling sites in arid regions to assess the leaf N and P levels of 23 species of desert plants and measure the corresponding soil water content, total salt content, total nitrogen content, and total phosphorus content. The aim was to elucidate the main soil properties that influence the stoichiometric characteristics of desert plants and compare the individual and community responses to those soil properties. Our results indicated that the growth of desert plants is mainly limited by nitrogen, with individual plant leaf nitrogen and phosphorus concentrations ranging from 4.08 to 31.39 mg g−1 and 0.48 to 3.78 mg g−1, respectively. Community stoichiometry was significantly lower than that of individual plants. A significant correlation was observed between the mean N concentration, P concentration, and N:P ratio of plant leaves. At the individual plant scale, aridity significantly reduced leaf N and P concentrations, while high salt content significantly increased leaf N concentrations. At the community scale, aridity had no significant effects on leaf nitrogen or phosphorus stoichiometry, while high salinity significantly increased the leaf N:P ratio and there were no significant interactions between the aridity and salinity conditions. No significant effects of soil nutrient gradients were observed on plant N and P stoichiometric characteristics at the individual or community levels. These results suggest that individual desert plants have lower leaf N and P concentrations to adapt to extreme drought and only adapt to salt stress through higher leaf N concentrations. The N and P stoichiometric characteristics of desert plant communities are not sensitive to variations in aridity and salinity in this extreme habitat. The results of this study could enhance our perceptions of plant adaptation mechanisms to extreme habitats within terrestrial ecosystems.

Distribution Characteristics and Controlling Factors of Soil Total Nitrogen: Phosphorus Ratio Across the Northeast Tibetan Plateau Shrublands

Nitrogen (N) and phosphorus (P) stoichiometry have significant effects on nutrient cycles in terrestrial ecosystems. However, our understanding of the patterns and the driving factors of soil N:P ratios in the Tibetan Plateau shrublands remains limited. Our study aimed to quantify the distribution of soil N:P ratio and its controlling factors based on soil, plant, and climate factors from 59 sites in shrublands across the northeast Tibetan Plateau. The kriging interpolation method was used to quantify the soil N:P distribution. Spatially, the soil N:P ratio was higher in the south than in the north and lower in the west than in the east. The soil N:P ratio in the northeast Tibetan Plateau shrublands was mainly explained by edaphic factors, which also played an important role in regulating the effects of plant and climate factors on soil N:P ratios. Mean annual precipitation, instead of mean annual temperature, significantly controlled the soil N:P ratios, and its effect on the pattern of soil N:P ratios differed between alpine shrublands and desert shrublands. The N:P ratios of different organs in shrublands also played different roles in shaping the soil N:P ratios in alpine and desert shrublands. These results provide support for the hypothesis that edaphic factors were the dominant drivers of spatial variation in soil N:P ratios across the northeast Tibetan Plateau shrublands, and our study contributes to a deeper understanding of biogeochemical cycling at high altitudes.

A global meta-analysis of the impacts of exotic plant species invasion on plant diversity and soil properties

Plant diversity and biogeochemical cycles are rapidly changing in response to exotic plant species invasion. However, there are conflicting conclusions regarding the quantification of such changes in the soil properties and plant diversity. Moreover, the relationships between soil properties and plant diversity are unclear. Here, a global meta-analysis was conducted on the impact of exotic species invasion on soil physicochemistry, microbial activity, and plant diversity using data from 123 published reports and 332 samples. Exotic species invasion significantly enhanced the soil pH, soil microbial activity, and soil nutrient content. The impact was more substantial for grass than for shrub and tree. Exotic species invasion did not significantly affect soil texture, but significantly reduced the plant diversity, richness, and evenness by 36.97%, 64.72%, and 47.21%, respectively. Soil pH, soil organic carbon, and total nitrogen were significantly correlated with plant diversity reduction. The response ratio of plant richness and evenness gradually increased with precipitation. However, the response ratio of phosphatase, microbial biomass nitrogen, microbial biomass phosphorus, total nitrogen, and soil moisture gradually decreased with precipitation. Overall, exotic species invasion significantly increased the soil nutrient content and soil microbial activity, but significantly decreased plant diversity. These effects were influenced by exotic species types and precipitation.

Variability in Soil Macronutrient Stocks across a Chronosequence of Masson Pine Plantations

Plantations play a vital role in the global nutrient cycle because they have large stocks of soil macronutrients. However, the impacts of plantations on soil macronutrient stocks combined with stand age and soil physicochemical properties have not been well quantified. We compared soil macronutrient stocks at soil depths of 0−20 and 20−40 cm across a 7-, 14-, 25-, and 30-year chronosequence of Masson pine (Pinus massoniana Lamb.) plantations. The results showed that the nitrogen (N), phosphorus (P), and potassium (K) stocks first increased and then decreased with stand age. The highest N and P stocks were observed in the 14-year-old plantation, and the 25-year-old plantation displayed the highest K stock. The C, N, and P stocks declined with increasing soil depth across all sites, whereas the reverse trend was found in the K stock. Carbon stocks were highest for all plantations, followed by the K, N, and P stocks. Plantation soils exhibited a higher C:P ratio and a lower P:K ratio at various soil depths. The dominant controlling factors for the soil macronutrient stocks varied significantly at different stand ages and soil depths according to statistical analysis. For the total soil system, the C stock was affected by the available nutrients, organic matter, and stoichiometry; the available nutrients and organic matter were the determinant factors of the N and P stocks. Aggregate stability could be the primary parameter affecting the K stock. Organic matter explained most of the variation in soil macronutrient stocks, followed by the P:K ratio and available K. Collectively, our results suggest that the response of soil macronutrient stocks to stand age and soil depth will be dependent on different soil physicochemical properties, and P and K may be important limiting factors in Masson pine plantation ecosystems.

Dynamics of soil metallic nutrients across a 6000-km temperature transect in China

Global warming has exerted profound effects on terrestrial ecosystems. Soil metallic nutrients, an integrated part of soil nutrient fertility, play a significant role in the maintenance of ecosystem functions. However, how soil metallic nutrients respond to global warming remains poorly understood. Spatial observations across a temperature gradient provide a solid evidence in clarifying the long-term responses of soil metallic nutrients to global warming. But due to the collinearity between temperature and precipitation in the geographical patterns, the influence of temperature on soil metallic nutrients might be interfered by the precipitation effect. To minimize the precipitation effect, this study conducted a soil sampling over broad geographical scale along the 400 mm isohyet in China, which extends about 6000 km. Variations in soil potassium (K), calcium (Ca), magnesium (Mg) and iron (Fe) concentrations across the temperature transect were investigated. These four elements all increased until mean annual temperature (MAT) increased to about 2 °C and then decreased with increasing MAT. Temperature, soil property and vegetation type were responsible for the changes of soil metallic nutrients at MAT below 2 °C; altitude, soil property, vegetation type and soil parent material were dominant influential factors of soil metallic nutrients at MAT above 2 °C. Temperature exerted an indirect influence on soil metallic nutrients through its effects on soil property, vegetation type, rock weathering, microbial decomposition and plant growth. It could be expected based on our results that the effects of global warming on soil K, Ca, Mg and Fe might depend on local MAT. Different regions with different climates should adopt different strategies to cope with the effect of global warming on soil metallic nutrients so that ecosystems maintain stable.

Soil C, N, P and K stoichiometry affected by vegetation restoration patterns in the alpine region of the Loess Plateau, Northwest China

The Grain-for-Green project is an important ecological restoration measure to address the degradation of alpine ecosystems in China, which has an important impact on the ecological stoichiometry of soil carbon (C), nitrogen (N), phosphorus (P) and potassium (K). However, soil stoichiometry changes under different vegetation restoration patterns and at different soil depths remain poorly understood in the alpine region of the Loess Plateau. To clarify these soil stoichiometry changes, a 0–60 cm soil profile was sampled from two typical vegetation restoration patterns: grassland (GL) and forestland (FL), including Picea crassifolia (PC), Larix principis-rupprechtii (LR), Populus cathayana (PR) and Betula platyphylla (BP). The control was a wheat field (WF). In all soil layers, the soil organic carbon (SOC), total nitrogen (TN), soil available nitrogen and potassium (AN and AK, respectively) and C:P, C:K, N:P and N:K ratios of FL were higher than those of GL and WF. The TN content and N:P and N:K ratios of GL were higher than those of WF in each soil layer. Additionally, the soil nutrients (except TK) of all vegetation types and stoichiometry of PR and GL (except the N:P ratio of GL) were greater at 0–20 cm than at 20–60 cm. Moreover, the SOC and TN showed the strongest correlation with the soil stoichiometry (except P:K ratio); thus, C and N had the greatest effect on the soil stoichiometry. Furthermore, soil fertility was limited by N. Our results indicated that different vegetation restoration patterns and soil depths had significant effects on the soil nutrients and stoichiometry in the alpine region of the Loess Plateau. The recovery of farmland to forestland promoted better improvements of soil nutrients, and PR had the most significant positive effect on soil surface nutrients.

Introducing a Hybrid Model SAE-BP for Regression Analysis of Soil Temperature With Hyperspectral Data

Soil temperature, as one of the critical meteorological parameters, plays a key role in physical, chemical and biological processes in terrestrial ecosystems. Accurate estimation of dynamic soil temperature is crucial for underground soil ecological research. In this work, a hybrid model SAE-BP is proposed by combining stacked auto-encoders (SAE) and back propagation (BP) algorithm to estimate soil temperature using hyperspectral remote sensing data. Experimental results show that the proposed SAE-BP model achieves a more stable and effective performance than the existing logistic regression (LR), support vector regression (SVR) and BP neural network with an average value of mean square error (MSE) = 1.926, mean absolute error (MAE) = 0.962 and coefficient of determination (R2) = 0.910. In addition, the effect of hidden structures and labeled training data ratios in SAE-BP is further explored. The SAE-BP model demonstrates the potential in high-dimensional and small hyperspectral datasets, representing a significant contribution to soil remote sensing.

Effects of grassland degradation on ecological stoichiometry of soil ecosystems on the Qinghai-Tibet Plateau

Grasslands across the world are being degraded due to the impacts of overgrazing and climate change. However, the influences of grassland degradation on carbon (C), nitrogen (N), and phosphorus (P) dynamics and stoichiometry in soil ecosystems are not well studied, especially at high elevations where ongoing climate change is most pronounced. Ecological stoichiometry facilitates understanding the biogeochemical cycles of multiple elements by studying their balance in ecological systems. This study sought to assess the responses of these soil elements to grassland degradation in the Qinghai Lake watershed on the Qinghai-Tibet Plateau (QTP), which has an average elevation of >4000 m and is experiencing serious grassland degradation due to its sensitivity and vulnerability to external disturbances. Substituting space for time, we quantified normalized difference vegetation index to gauge grassland degradation. C, N, and P concentrations and their molar ratios in soil and in soil microbial biomass were also measured. The results showed that grassland degradation decreased the concentrations of C and N, as well as the ratios of C:P and N:P in soil. The soil became relatively more P rich and thus N limitation is anticipated to be more apparent with grassland degradation. Moreover, C, N, and P concentrations in soil microbial biomass decreased with increased grassland degradation. C:N:P ratios of soil microbial biomass were highly constrained, suggesting that soil microorganisms exhibited a strong homeostatic behavior, while the variations of microbial biomass C:N:P ratios suggest changes in microbial activities and community structure. Overall, our study revealed that grassland degradation differentially affects soil C, N, and P, leading to decreased C:N and N:P in soil, as well as decreased C, N, and P concentrations in soil microbial biomass. This study provides insights from a stoichiometric perspective into microbial and biogeochemical responses of grassland ecosystems as they undergo degradation on the QTP.

Plant response to N availability in permafrost-affected alpine wetlands in arid and semi-arid climate zones

Nutrient cycling in alpine permafrost-affected wetlands remains insufficiently studied, as it is influenced by a complex network of interrelated climatic and environmental factors, at both regional and local scale. Therefore, we applied mathematical models to examine relationship between environmental factors and plant functional traits reflecting N availability in wetland communities developed under locally variable conditions in a geographic and climatic gradient of high-altitude habitats. Moreover, we assessed impact of local differences in soil chemistry on plant fractionation of N isotopes as a response to N availability. Based on environmental data and chemistry of biomass from 192 study sites from the Pamir Mountains (Tajikistan) and Khangai and Khentei Mountains (Mongolia), a matrix of rank correlations was prepared for regional and local factors and community level plant functional traits. For the traits that were highly correlated either with regional or with local drivers (that is plant N:P ratio and plant δ¹⁵N), linear models were built, with a limited set of predictors selected according to the Risk Inflation Criterion and the SOS algorithm. The models were fitted for each of the studied regions. Presented regional models indicated significant influence of soil NH₄⁺ and/or PO₄^3- content on plant N:P ratio, which showed increase with altitude and lowering precipitation. Thus, its values clearly distinguished between the Pamir Mountains (high N:P) and the Mongolian ranges (low N:P). Models for plant δ¹⁵N showed its strong positive correlations with soil δ¹⁵N and soil salinity. Average values of plant δ¹⁵N were comparable for both study areas. The studied plant functional traits showed different response to regional and local drivers. Plant N:P ratio was controlled by regional drivers via their influence on soil NH₄⁺ content. Contrastingly, plant δ¹⁵N was significantly affected by local factors, namely soil δ¹⁵N and soil salinity expressed as Na:EC.

Mapping of Soil Total Nitrogen Content in the Middle Reaches of the Heihe River Basin in China Using Multi-Source Remote Sensing-Derived Variables

Soil total nitrogen (STN) is an important indicator of soil quality and plays a key role in global nitrogen cycling. Accurate prediction of STN content is essential for the sustainable use of soil resources. Synthetic aperture radar (SAR) provides a promising source of data for soil monitoring because of its all-weather, all-day monitoring, but it has rarely been used for STN mapping. In this study, we explored the potential of multi-temporal Sentinel-1 data to predict STN by evaluating and comparing the performance of boosted regression trees (BRTs), random forest (RF), and support vector machine (SVM) models in STN mapping in the middle reaches of the Heihe River Basin in northwestern China. Fifteen predictor variables were used to construct models, including land use/land cover, multi-source remote sensing-derived variables, and topographic and climatic variables. We evaluated the prediction accuracy of the models based on a cross-validation procedure. Results showed that tree-based models (RF and BRT) outperformed SVM. Compared to the model that only used optical data, the addition of multi-temporal Sentinel-1A data using the BRT method improved the root mean square error (RMSE) and the mean absolute error (MAE) by 17.2% and 17.4%, respectively. Furthermore, the combination of all predictor variables using the BRT model had the best predictive performance, explaining 57% of the variation in STN, with the highest R2 (0.57) value and the lowest RMSE (0.24) and MAE (0.18) values. Remote sensing variables were the most important environmental variables for STN mapping, with 59% and 50% relative importance in the RF and BRT models, respectively. Our results show the potential of using multi-temporal Sentinel-1 data to predict STN, broadening the data source for future digital soil mapping. In addition, we propose that the SVM, RF, and BRT models should be calibrated and evaluated to obtain the best results for STN content mapping in similar landscapes.

Elevation Gradient Altered Soil C, N, and P Stoichiometry of Pinus taiwanensis Forest on Daiyun Mountain

Researches focused on soil carbon (C), nitrogen (N), and phosphorus (P) content and the stoichiometry characteristics along elevation gradients are important for effective management of forest ecosystems. Taking the soil of different elevations from 900 to 1700 m on Daiyun Mountain as the object, the elevation distribution of total C, N, and P in soil and their stoichiometry characteristics were studied. Also, the driving factors resulting in the spatial heterogeneity of soil stoichiometry are presented. The results show the following: (1) The average soil C and N content was 53.03 g·kg−1 and 3.82 g·kg−1, respectively. The content of C and N at high elevation was higher than that of at low elevation. Soil phosphorus fluctuated with elevation. (2) With increasing elevation, soil C:N ratio increased initially to 17.40 at elevation between 900–1000 m, and then decreased to 12.02 at elevation 1600 m. The changing trends of C:P and N:P were similar, and they all fluctuated with elevation. (3) Elevation, soil bulk density, and soil temperature were the main factors influencing the variation of soil C, N, and C:N. Soil pH and slope position were the driving factors for soil P, C:P, and N:P. The soil is rich in C and N, and has less total phosphorus on Daiyun Mountain. Raising the level of phosphate fertilizer appropriately can help to improve soil fertility and promote plant growth as well. In light of this information, in the near future, it will be necessary to conduct separation management of C, N, and P with regular monitoring systems to maintain favorable conditions for soil.