Grazing exclusion is more effective for vegetation restoration and nutrient transfer in the heavily degraded desert steppe.

BACKGROUND: Grazing exclusion is an efficient practice to restore degraded grassland ecosystems by eliminating external disturbances and improving ecosystems' self-healing capacities, which affects the ecological processes of soil-plant systems. Grassland degradation levels play a critical role in regulating these ecological processes. However, the effects of vegetation and soil states at different degradation stages on grassland ecosystem restoration are not fully understood. To better understand this, desert steppe at three levels of degradation (light, moderate, and heavy degradation) was fenced for 6 years in Inner Mongolia, China. Community characteristics were investigated, and nutrient concentrations of the soil (0-10 cm depth) and dominant plants were measured. RESULTS: We found that grazing exclusion increased shoots' carbon (C) concentrations, C/N, and C/P, but significantly decreased shoots' nitrogen (N) and phosphorus (P) concentrations for Stipa breviflora and Cleistogenes songorica. Interestingly, there were no significant differences in nutrient concentrations of these two species among the three degraded desert steppes after grazing exclusion. After grazing exclusion, annual accumulation rates of aboveground C, N, and P pools in the heavily degraded area were the highest, but the aboveground nutrient pools were the lowest among the three degraded grasslands. Similarly, the annual recovery rates of community height, cover, and aboveground biomass in the heavily degraded desert steppe were the highest among the three degraded steppes after grazing exclusion. These results indicate that grazing exclusion is more effective for vegetation restoration in the heavily degraded desert steppe. The soil total carbon, total nitrogen, total phosphorus, available nitrogen, and available phosphorus concentrations in the moderately and heavily degraded desert steppes were significantly decreased after six years of grazing exclusion, whereas these were no changes in the lightly degraded desert steppe. Structural equation model analysis showed that the grassland degradation level mainly altered the community aboveground biomass and aboveground nutrient pool, driving the decrease in soil nutrient concentrations and accelerating nutrient transfer from soil to plant community, especially in the heavily degraded grassland. CONCLUSIONS: Our study emphasizes the importance of grassland degradation level in ecosystem restoration and provides theoretical guidance for scientific formulation of containment policies.

Composition and diversity of soil microbial communities change by introducing Phallus impudicus into a Gastrodia elata Bl.-based soil.

BACKGROUND: The Gastrodia elata Bl. is an orchid, and its growth demands the presence of Armillaria species. The strong competitiveness of Armillaria species has always been a concern of major threat to other soil organisms, thus disrupting the equilibrium of soil biodiversity. Introducing other species to where G. elata was cultivated, could possibly alleviate the problems associated with the disequilibrium of soil microenvironment; however, their impacts on the soil microbial communities and the underlying mechanisms remain unclear. To reveal the changes of microbial groups associated with soil chemical properties responding to different cultivation species, the chemical property measurements coupled with the next-generation pyrosequencing analyses were applied with soil samples collected from fallow land, cultivation of G. elata and Phallus impudicus, respectively. RESULTS: The cultivation of G. elata induced significant increases (p < 0.05) in soil pH and NO3-N content compared with fallow land, whereas subsequent cultivation of P. impudicus reversed these G. elata-induced increases and was also found to significantly increase (p < 0.05) the content of soil NH4+-N and AP. The alpha diversities of soil microbial communities were significantly increased (p < 0.01) by cultivation of G. elata and P. impudicus as indicated with Chao1 estimator and Shannon index. The structure and composition of soil microbial communities differed responding to different cultivation species. In particular, the relative abundances of Bacillus, norank_o_Gaiellales, Mortierella and unclassified_k_Fungi were significantly increased (p < 0.05), while the abundances of potentially beneficial genera such as Acidibacter, Acidothermus, Cryptococcus, and Penicillium etc., were significantly decreased (p < 0.05) by cultivation of G. elata. It's interesting to find that cultivation of P. impudicus increased the abundances of these genera that G. elata decreased before, which contributed to the difference of composition and structure. The results of CCA and heatmap indicated that the changes of soil microbial communities had strong correlations with soil nutrients. Specifically, among 28 genera presented, 50% and 42.9% demonstrated significant correlations with soil pH and NO3-N in response to cultivation of G. elata and P. impudicus. CONCLUSIONS: Our findings suggested that the cultivation of P. impudicus might have potential benefits as result of affecting soil microorganisms coupled with changes in soil nutrient profile.

Functional Characterization of Core and Unique Calcite-Dissolving Bacteria Communities from Peanut Fields.

Calcium deficiency is a leading cause of reduced peanut (Arachis hypogaea) seed quality and has been linked to increased disease susceptibility, specifically to soilborne fungal pathogens. Sufficient calcium at flowering time is critical to ensure proper pod development. Calcite-dissolving bacteria (CDB) isolated from farming fields can dissolve calcite (CaCO3) on plates and increase soluble calcium levels in soil. However, the phylogenetic diversity and geographic distribution of CDB is unclear. Here, we surveyed soil samples from 15 peanut-producing fields in three regions in southern Georgia, representing distinct soil compositions. We isolated CDB through differentiating media and identified 52 CDB strains. CDB abundance was not associated with any of the soil characteristics we evaluated. Three core genera, represented by 43 strains, were found in all three regions. Paenibacillus was the most common CDB found in all regions, making up 30 of the 52 identified strains. Six genera, represented by eight strains, are unique to one region. Members of the core and unique communities showed comparable solubilization indexes on plates. We conclude that a diversified phylogenetic population of CDB is present in Georgia peanut fields. Despite the phylogenetic diversity, as a population, they exhibit comparable functions in solubilizing calcite on plates.

R3 strain and Fe-Mn modified biochar reduce Cd absorption capacity of roots and available Cd content of soil by affecting rice rhizosphere and endosphere key flora.

Microorganisms have a significant role in regulating the absorption and transportation of Cd in the soil-plant system. However, the mechanism by which key microbial taxa play a part in response to the absorption and transportation of Cd in rice under Cd stress requires further exploration. In this study, the cadmium-tolerant endophytic bacterium Herbaspirillum sp. R3 (R3) and Fe-Mn-modified biochar (Fe-Mn) were, respectively, applied to cadmium-contaminated rice paddies to investigate the effects of key bacterial taxa in the soil-rice system on the absorption and transportation of Cd in rice under different treatments. The results showed that both R3 and Fe-Mn treatments considerably decreased the content of cadmium in roots, stems and leaves of rice at the peak tillering stage by 17.24-49.28% in comparison to the control (CK). The cadmium content reduction effect of R3 treatment is better than that of Fe-Mn treatment. Further analysis revealed that the key bacterial taxa in rice roots under R3 treatment were Sideroxydans and Actinobacteria, and that their abundance showed a substantial positive correlation and a significant negative correlation with the capacity of rice roots to assimilate Cd from the surroundings, respectively. The significant increase in soil pH under Fe-Mn treatment, significant reduction in the relative abundances of Acidobacteria, Verrucomicrobia, Subdivision3 genera incertae sedis, Sideroxydans, Geobacter, Gp1, and Gp3, and the significant increase in the relative abundance of Thiobacillus among the soil bacterial taxa may be the main reasons for the decrease in available Cd content of the soil. In addition, both the R3 and Fe-Mn treatments showed some growth-promoting effects on rice, which may be related to their promotion of transformations of soil available nutrients. This paper describes the possible microbial mechanisms by which strain R3 and Fe-Mn biochar reduce Cd uptake in rice, providing a theoretical basis for the remediation of Cd contamination in rice and soil by utilizing key microbial taxa.

Altitudinal and aspect-driven variations in soil carbon storage potential in sub-tropical Himalayan forest ecosystem: assisting nature to combat climate change.

Forest soils serve as the greatest sink of terrestrial carbon (C) and have a significant impact on worldwide or regional C cycling. By reducing emissions and enhancing the C storage in forests, the environmental monitoring function of a forest ecosystem may be ensured. The study focused on measuring the densities of major nutrients in soil to gain insight into the C and nitrogen dynamics of the Himalayan sub-tropical forest ecosystem of India besides supplementing the information about the C storage potential of these forest soils. The study examined the physico-chemical properties and nutrient densities across three altitudinal ranges viz., 600-800 m (A1), 800-1000 m (A2) and 1000-1200 m (A3) and two aspects, i.e. Northern (N) and Southern (S) in a randomized complete block design and data collection was done from 24 main sample plots (3 altitudinal ranges × 2 aspects × 4 replications). The soil pH, electrical conductivity, and bulk density observed a decreasing pattern with an increase in altitude, whereas a reverse trend was observed in soil organic C (SOC), total nitrogen and available phosphorus. The SOC and total nitrogen densities ranged from 20.08 to 48.35 Mg ha-1 and 2.56 to 4.01 Mg ha-1, respectively in an increasing trend from A1 to A3. The northern aspect exhibited significantly higher SOC and nitrogen densities than the southern aspects. The C storage potential of forest soils followed the order A1 < A2 < A3 with significantly higher potential (nearly 1.5 times) compared to those on the southern aspect. There was a consistently significant increase in the C:N ratio (CNR) with a maximum value (10.51) at A3 and minimum value (8.37) at A1, however the effect of aspect remained insignificant. This research underscores the importance of considering altitude and aspect when planning forest restoration efforts, as these factors have a substantial influence on soil properties, C storage potential and CNR. Understanding the significance of CNR is critical, as it serves as a key indicator of greenhouse gas (GHG) emissions from forest soils. Ultimately, these findings empower policymakers and conservationists to make informed decisions that can contribute to the sustainable management of Himalayan forests and the global fight against climate change.

Leaf morphology, functional trait and altitude response in perennial vetch (Vicia unijuga A. Braun), alfalfa (Medicago sativa L.) and sainfoin (Onobrychis viciifolia Scop.).

MAIN CONCLUSION: Species have plasticity across altitude gradients in leaf morphology and function, and their response to high altitude conditions was mainly reflected in leaf cell metabolism and gas exchange. Leaf morphological and functional adaptation to altitude has received research attention in recent years, but there are no studies for forage legumes. Here we report differences in 39 leaf morphology and functional traits of three leguminous forages (alfalfa, sainfoin and perennial vetch) at three sites in Gansu Province, China, ranging from 1768 to 3074 m altitude to provide information for potential use in breeding programmes. With increasing altitude, plant water status increased, reflecting increase in soil water content and decreased average temperature, which lead to leaf intercellular CO2 concentration. Stomatal conductance and evapotranspiration increased significantly but water-use efficiency decreased. At high altitude, ΦPSII decreased but non-photochemical quenching and chlorophyll a:b ratio increased while spongy mesophyll tissue and leaf thickness increased. These changes may be due to UV or low-temperature damage of leaf protein and metabolic cost of plant protection or defence responses. Contrary to many other studies, leaf mass per area decreased significantly at higher altitude. This was consistent with predictions under the worldwide leaf economic spectrum on the basis that soil nutrients increased with increasing altitude. The key species differences were more irregularly shaped epidermal cells and larger stomatal size in perennial vetch compared to alfalfa or sainfoin that enhanced gas exchange and photosynthesis by generating mechanical force, increasing guard cell turgor, and promoting stomatal operation. The lower adaxial stomatal density also enhanced water-use efficiency. These adaptations might confer perennial vetch an advantage in environments with extreme diurnal temperature fluctuation or in frigid conditions.

A field incubation approach to evaluate the depth dependence of soil biogeochemical responses to climate change.

Soil biogeochemical processes may present depth-dependent responses to climate change, due to vertical environmental gradients (e.g., thermal and moisture regimes, and the quantity and quality of soil organic matter) along soil profile. However, it is a grand challenge to distinguish such depth dependence under field conditions. Here we present an innovative, cost-effective and simple approach of field incubation of intact soil cores to explore such depth dependence. The approach adopts field incubation of two sets of intact soil cores: one incubated right-side up (i.e., non-inverted), and another upside down (i.e., inverted). This inversion keeps soil intact but changes the depth of the soil layer of same depth origin. Combining reciprocal translocation experiments to generate natural climate shift, we applied this incubation approach along a 2200 m elevational mountainous transect in southeast Tibetan Plateau. We measured soil respiration (Rs) from non-inverted and inverted cores of 1 m deep, respectively, which were exchanged among and incubated at different elevations. The results indicated that Rs responds significantly (p < .05) to translocation-induced climate shifts, but this response is depth-independent. As the incubation proceeds, Rs from both non-inverted and inverted cores become more sensitive to climate shifts, indicating higher vulnerability of persistent soil organic matter (SOM) to climate change than labile components, if labile substrates are assumed to be depleted with the proceeding of incubation. These results show in situ evidence that whole-profile SOM mineralization is sensitive to climate change regardless of the depth location. Together with measurements of vertical physiochemical conditions, the inversion experiment can serve as an experimental platform to elucidate the depth dependence of the response of soil biogeochemical processes to climate change.

Biochar alleviates the crop failure of rice production induced by low-nitrogen cultivation mode by regulating the soil microbes taxa composition.

To improve the nitrogen utilization efficiency and a series of environmental problems caused by excessive application of nitrogen fertilizer, actual agricultural production often reduced the usage ratio of nitrogen fertilizer. However, the reduction in nitrogen fertilizer not only affects the soil microenvironment but also leads to adverse effects on rice yield. Due to its unique properties, biochar can regulate soil nutrient distribution and significantly affect soil microbial community structure/functions. To further understand the effects of different levels of biochar on soil nutrient indicators, soil microorganisms and crop growth under the nitrogen-reduction condition, our experiment with four groups was set up as followed: 0%, 2.5% and 5% biochar application rates with 99 kg/hm2 nitrogen fertilizer and one control group (the actual fertilizer standard used in the field:110 kg/hm2) without no exogenous biochar supplement. The rice yield and soil nutrient indexes were observed, and the differences between groups were analyzed based on multiple comparisons. 16S ribosomal RNA and ITS sequencing were used to analyze the community structure of soil bacteria and fungi. Redundancy analysis was performed to obtain the correlation relationships between microbial community marker species, soil nutrient indexes, and rice yield. Path analysis was used to determine the mechanism by which soil nutrient indexes affect rice yield. The results showed that a higher application rate of biochar led to a significant increased trend in the soil pH, organic matter and total nitrogen content. In addition, a high concentration of biochar under nitrogen-reduction condition decreased the soil bacterial diversity but elevated the fungal diversity. Different concentrations of biochar resulted in these changes in the relative abundance of soil bacteria/fungi but did not alter the dominant species taxa. Taken together, appropriate usage for biochar under the nitrogen-reduction background could induce alteration in soil nutrient indicators, microbial communities and crop yields. These results provide a theoretical basis for exploring scientific, green and efficient fertilization strategies in the rice cultivation industry. Notably, the interaction relationship between rhizosphere microorganisms in rice and soil microbial taxa are not yet clear, so further research on its detailed effects on rice production is needed. In addition, the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis for the physiological functions of the soil microbes could only predict the potential metabolic pathways. Therefore, the next-generation metagenome techonology might be performed to explore detailed metabolic differences and accurate taxa alteration at the "species" level.

Nitrogen Deposition Effects on Invasive and Native Plant Competition: Implications for Future Invasions.

Nitrogen (N) deposition has increased dramatically in recent decades, which is significantly affecting the invasion and growth of exotic plants. Whether N deposition leads to invasive alien species becoming competitively superior to native species remains to be investigated. In the present study, an invasive species (Oenothera biennis L.) and three co-occurring native species (Artemisia argyi Lévl. et Vant., Inula japonica Thunb., and Chenopodium album L.) were grown in a monoculture (two seedlings of the same species) or mixed culture (one seedling of O. biennis and one seedling of a native species) under three levels of N deposition (0, 6, and 12 g∙m-2∙year-1). Nitrogen deposition had no effect on soil N and P content. Nitrogen deposition enhanced the crown area, total biomass, leaf chlorophyll content, and leaf N to phosphorus ratio in both invasive and native plants. Oenothera biennis dominated competition with C. album and I. japonica due to its high resource acquisition and absorption capacity (greater height, canopy, leaf chlorophyll a to chlorophyll b ratio, leaf chlorophyll content, leaf N content, leaf mass fraction, and lower root-to-shoot ratio). However, the native species A. argyi exhibited competitive ability similar to O. biennis. Thus, invasive species are not always superior competitors of native species; this depends on the identities of the native species. High N deposition enhanced the competitive dominance of O. biennis over I. japonica by 15.45% but did not alter the competitive dominance of O. biennis over C. album. Furthermore, N deposition did not affect the dominance of O. biennis or A. argyi. Therefore, the species composition of the native community must be considered when preparing to resist future biological invasions. Our study contributes to a better understanding of the invasion mechanisms of alien species under N-loading conditions.

Wireless Sensor Networks for Precision Agriculture: A Review of NPK Sensor Implementations.

The integration of Wireless Sensor Networks (WSNs) into agricultural areas has had a significant impact and has provided new, more complex, efficient, and structured solutions for enhancing crop production. This study reviews the role of Wireless Sensor Networks (WSNs) in monitoring the macronutrient content of plants. This review study focuses on identifying the types of sensors used to measure macronutrients, determining sensor placement within agricultural areas, implementing wireless technology for sensor communication, and selecting device transmission intervals and ratings. The study of NPK (nitrogen, phosphorus, potassium) monitoring using sensor technology in precision agriculture is of high significance in efforts to improve agricultural productivity and efficiency. Incorporating Wireless Sensor Networks (WSNs) into the ongoing progress of proposed sensor node placement design has been a significant facet of this study. Meanwhile, the assessment based on soil samples analyzed for macronutrient content, conducted directly in relation to the comparison between the NPK sensors deployed in this research and the laboratory control sensors, reveals an error rate of 8.47% and can be deemed as a relatively satisfactory outcome. In addition to fostering technological innovations and precision farming solutions, in future this research aims to increase agricultural yields, particularly by enabling the cultivation of certain crops in locations different from their original ones.

Effective Striga control and yield intensification on maize farms in western Kenya with N fertilizer and herbicide-resistant variety.

Context: Maize production in western Kenya is limited by the spread of parasitic weed Striga hermonthica and depletion of soil nutrient stocks. Nitrogen (N) fertilizer and imidazolinone resistant (IR) maize are key elements in the agronomic toolbox to control infestations and enhance yields. Research question: The circumstances under which their use, individually or combined, is most effective on farmer fields have not been well documented. Inappropriate management decisions and low returns on investments arise from this knowledge gap, causing hunger and poverty in smallholder communities to persist. Methods: Experiments were carried out on 60 fields in three different agroecosystems of western Kenya using full-factorial treatments with non-herbicide treated maize (DH) and herbicide treated maize (IR), and N fertilizer omission and application. Trials were stratified on a field with low and high soil fertility within individual farms and repeated over two seasons. Results: Cultivating IR maize instead of DH maize decreased the emergence of Striga with 13 shoots m-2 on average while applying N fertilizer on DH maize led to a reduction of 5 shoots m-2 on average. Decreases of Striga by use of IR maize and N fertilizer were between 6 and 23 shoots m-2 larger at the site with high levels of infestation than at the sites with medium or low emergence. Input of N fertilizer increased grain harvests by 0.59 ton ha-1 on average while use of IR maize enhanced the productivity with 0.33 ton ha-1 on average. Use of N fertilizer had similar yield effects in all three sites, whereas use of IR maize at the site with high Striga emergence increased maize production by 0.26-0.39 ton ha-1 more than at the sites with medium or low emergence. Conclusions: The greater Striga responses to IR maize and the greater yield responses to N fertilizer demonstrate their use could be optimized according to field conditions and management goals. Combining IR maize and N fertilizer has larger added yield benefits where their individual effects on grain productivity are smaller. Significance: Findings from this study indicate that farmers in western Kenya require guidance on how to align the use of herbicide resistant maize and inorganic N inputs with the level of Striga infestation and maize yield on their fields for effectively controlling the pernicious weed and enhancing food production.

Accumulation in nutrient acquisition strategies of arbuscular mycorrhizal fungi and plant roots in poor and heterogeneous soils of karst shrub ecosystems.

BACKGROUND: Arbuscular mycorrhizal (AM) fungi and roots play important roles in plant nutrient acquisition, especially in nutrient poor and heterogeneous soils. However, whether an accumulation strategy of AM fungi and root exists in such soils of karst shrubland ecosystems remains unclear. Root traits related to nutrient acquisition (root biomass, AM colonisation, root acid phosphatase activity and N2 fixation) were measured in two N2-fixing plants (i.e. Albizia odoratissima (Linn. f.) Benth. and Cajanus cajan (Linn.) Millsp.) that were grown in heterogeneous or homogeneous nutrient (ammonium) soil with and without AM fungi inoculation. RESULTS: Both of these plants had higher AM colonisation, root biomass and relative growth rate (RGR), but lower N2 fixation and root acid phosphatase activity in the rhizosphere in the heterogeneous soil environment, than that in the homogeneous soil environment. Plants grown in the AM fungi-inoculated heterogeneous soil environment had increased root biomass and root acid phosphatase activity compared with those grown in soil without inoculation. AM colonisation was negatively correlated with the N2 fixation rate of A. odoratissima, while it was not significantly correlated with the root phosphatase activity. CONCLUSIONS: Our results indicated that enhanced AM symbiosis and root biomass increased the absorptive surfaces for nutrient acquisition, highlighting the accumulation strategies of AM and root traits for plant nutrient acquisition in nutrient poor and heterogeneous soils of the karst shrubland ecosystem.

Holm oak decline is determined by shifts in fine root phenotypic plasticity in response to belowground stress.

Climate change and pathogen outbreaks are the two major causes of decline in Mediterranean holm oak trees (Quercus ilex L. subsp. ballota (Desf.) Samp.). Crown-level changes in response to these stressful conditions have been widely documented but the responses of the root systems remain unexplored. The effects of environmental stress over roots and its potential role during the declining process need to be evaluated. We aimed to study how key morphological and architectural root parameters and nonstructural carbohydrates of roots are affected along a holm oak health gradient (i.e. within healthy, susceptible and declining trees). Holm oaks with different health statuses had different soil resource-uptake strategies. While healthy and susceptible trees showed a conservative resource-uptake strategy independently of soil nutrient availability, declining trees optimized soil resource acquisition by increasing the phenotypic plasticity of their fine root system. This increase in fine root phenotypic plasticity in declining holm oaks represents an energy-consuming strategy promoted to cope with the stress and at the expense of foliage maintenance. Our study describes a potential feedback loop resulting from strong unprecedented belowground stress that ultimately may lead to poor adaptation and tree death in the Spanish dehesa.

Agrobot Lala-An Autonomous Robotic System for Real-Time, In-Field Soil Sampling, and Analysis of Nitrates.

This paper presents an autonomous robotic system, an unmanned ground vehicle (UGV), for in-field soil sampling and analysis of nitrates. Compared to standard methods of soil analysis it has several advantages: each sample is individually analyzed compared to average sample analysis in standard methods; each sample is georeferenced, providing a map for precision base fertilizing; the process is fully autonomous; samples are analyzed in real-time, approximately 30 min per sample; and lightweight for less soil compaction. The robotic system has several modules: commercial robotic platform, anchoring module, sampling module, sample preparation module, sample analysis module, and communication module. The system is augmented with an in-house developed cloud-based platform. This platform uses satellite images, and an artificial intelligence (AI) proprietary algorithm to divide the target field into representative zones for sampling, thus, reducing and optimizing the number and locations of the samples. Based on this, a task is created for the robot to automatically sample at those locations. The user is provided with an in-house developed smartphone app enabling overview and monitoring of the task, changing the positions, removing and adding of the sampling points. The results of the measurements are uploaded to the cloud for further analysis and the creation of prescription maps for variable rate base fertilization.

IoT-Based Systems for Soil Nutrients Assessment in Horticulture.

Soil nutrients assessment has great importance in horticulture. Implementation of an information system for horticulture faces many challenges: (i) great spatial variability within farms (e.g., hilly topography); (ii) different soil properties (e.g., different water holding capacity, different content in sand, sit, clay, and soil organic matter, different pH, and different permeability) for different cultivated plants; (iii) different soil nutrient uptake by different cultivated plants; (iv) small size of monoculture; and (v) great variety of farm components, agroecological zone, and socio-economic factors. Advances in information and communication technologies enable creation of low cost, efficient information systems that would improve resources management and increase productivity and sustainability of horticultural farms. We present an information system based on different sensing capability, Internet of Things, and mobile application for horticultural farms. An overview on different techniques and technologies for soil fertility evaluation is also presented. The results obtained in a botanical garden that simulates the diversity of environment and plant diversity of a horticultural farm are discussed considering the challenges identified in the literature and field research. The study provides a theoretical basis and technical support for the development of technologies that enable horticultural farmers to improve resources management.

Rotation cropping and organic fertilizer jointly promote soil health and crop production.

Identifying field management practices to promote crop production, while conserving soil health is essential to maintain long-term food production in a changing world. Also, providing experimental evidence to support the use of traditional agricultural practices is necessary to secure sustainable agriculture. Here, we conducted a long-term 12-year experiment to investigate the impact of different combinations of fertilization type (control, inorganic fertilizer, organic fertilizer) and cropping regimes (continuous cropping and rotation cropping) on the crop (tobacco) production and multiple soil attributes associated with soil health, including proportions of soil-borne pathogens and decomposers, soil microbial diversity, microbial network stability and biomass, nutrient pools and microbial resource limitations. Our long-term experiment supports that the combination of organic fertilizer with rotation cropping increased crop production by at least 40% compared to the other management combinations and improved soil nutrient pools (e.g. the content of soil organic matter), improved the relative proportion of soil decomposers, and promoted bacterial and fungal network stability and biodiversity. Furthermore, this combination treatment relieved microbial resource limitation and reduced the abundance of potential fungal plant pathogens by at least 20% compared to other management combinations. In summary, we provide experimental evidence to support that the combined use of organic fertilization and rotation cropping management can help maintain long-term soil health, crop production, and economic outputs.

Spatiotemporal variation in soil degradation and economic damage caused by wind erosion in Northwest China.

Wind erosion causes significant dust emissions in northwest China, resulting in large amounts of soil organic matter and nutrient losses. It has a significant impact on air quality, climate change, vegetation growth, and economic growth at the regional scale. In this work, the Weather Research Forecasting with Chemistry atmospheric chemical transport model was used to simulate the temporal and spatial processes of dust emissions in northwest China from 1980 to 2015. The temporal and spatial variation characteristics of the loss of soil organic matter and nutrients (total nitrogen and total phosphorus) due to dust emissions, and the economic damage from wind erosion, were simulated and calculated. Spatial patterns of soil organic matter and nutrient losses are consistent with dust emission rates across the research region. The average annual dust emissions were approximately 65.17 million tons, with losses of soil organic matter, total nitrogen, and total phosphorus resulting from dust emissions of 531,494 tons, 30,754 tons, and 37,095 tons, respectively. In addition, the average annual economic loss caused by wind erosion was 309.25 million yuan in northwest China during the entire study period. This research is valuable for understanding the role of wind erosion on the carbon and nutrient cycles and the mechanism of soil degradation in northwest China and estimating the economic impacts of wind erosion.

Soil fungal mycelia have unexpectedly flexible stoichiometric C:N and C:P ratios.

Soil ecological stoichiometry provides powerful theories to integrate the complex interplay of element cycling and microbial communities into biogeochemical models. One essential assumption is that microbes maintain stable C:N:P (carbon:nitrogen:phosphorus) ratios independent of resource supply, although such homeostatic regulations have rarely been assessed in individual microorganisms. Here, we report an unexpected high flexibility in C:N and C:P values of saprobic fungi along nutrient supply gradients, overall ranging between 7-126 and 20-1488, respectively, questioning microbial homeostasis. Fungal N:P varied comparatively less due to simultaneous reductions in mycelial N and P contents. As a mechanism, internal recycling processes during mycelial growth and an overall reduced N and P uptake appear more relevant than element storage. The relationships among fungal stoichiometry and growth disappeared in more complex media. These findings affect our interpretation of stoichiometric imbalances among microbes and soils and are highly relevant for developing microbial soil organic carbon and nitrogen models.

Truffle species strongly shape their surrounding soil mycobiota in a Pinus armandii forest.

Truffles contribute to crucial soil systems dynamics, being involved in plentiful ecological functions important for ecosystems. Despite this, the interactions between truffles and their surrounding mycobiome remain unknown. Here, we investigate soil mycobiome differences between two truffle species, Tuber indicum (Ti) and Tuber pseudohimalayense (Tp), and their relative influence on surrounding soil mycobiota. Using traditional chemical analysis and ITS Illumina sequencing, we compared soil nutrients and the mycobiota, respectively, in soil, gleba, and peridium of the two truffle species inhabiting the same Pinus armandii forest in southwestern China. Tp soil was more acidic (pH 6.42) and had a higher nutrient content (total C, N content) than Ti soil (pH 6.62). Fungal richness and diversity of fruiting bodies (ascomata) and surrounding soils were significantly higher in Tp than in Ti. Truffle species recruited unique soil mycobiota around their ascomata: in Ti soil, fungal taxa, including Suillus, Alternaria, Phacidium, Mycosphaerella, Halokirschsteiniothelia, and Pseudogymnoascus, were abundant, while in Tp soil species of Melanophyllum, Inocybe, Rhizopogon, Rhacidium, and Lecanicillium showed higher abundances. Three dissimilarity tests, including adonis, anosim, and MRPP, showed that differences in fungal community structure between the two truffle species and their surrounding soils were stronger in Tp than in Ti, and these differences extended to truffle tissues (peridium and gleba). Redundancy analysis (RDA) further demonstrated that correlations between soil fungal taxa and soil properties changed from negative (Tp) to positive (Ti) and shifted from a moisture-driven (Tp) to a total N-driven (Ti) relationship. Overall, our results shed light on the influence that truffles have on their surrounding soil mycobiome. However, further studies are required on a broader range of truffle species in different soil conditions in order to determine causal relationships between truffles and their soil mycobiome.

Soil Nutrient Estimation and Mapping in Farmland Based on UAV Imaging Spectrometry.

Soil nutrient is one of the most important properties for improving farmland quality and product. Imaging spectrometry has the potential for rapid acquisition and real-time monitoring of soil characteristics. This study aims to explore the preprocessing and modeling methods of hyperspectral images obtained from an unmanned aerial vehicle (UAV) platform for estimating the soil organic matter (SOM) and soil total nitrogen (STN) in farmland. The results showed that: (1) Multiplicative Scattering Correction (MSC) performed better in reducing image scattering noise than Standard Normal Variate (SNV) transformation or spectral derivatives, and it yielded a result with higher correlation and lower signal-to-noise ratio; (2) The proposed feature selection method combining Successive Projections Algorithm (SPA) and Competitive Adaptive Reweighted Sampling algorithm (CARS), could provide selective preference for hyperspectral bands. Exploiting this method, 24 and 22 feature bands were selected for SOM and STN estimation, respectively; (3) The particle swarm optimization (PSO) algorithm was employed to obtain optimized input weights and bias values of the extreme learning machine (ELM) model for more accurate prediction of SOM and STN. The improved PSO-ELM model based on the selected preference bands achieved higher prediction accuracy (R2 of 0.73 and RPD of 1.91 for SOM, R2 of 0.63, and RPD of 1.53 for STN) than support vector machine (SVM), partial least squares regression (PLSR), and the ELM model. This study provides an important guideline for monitoring soil nutrient for precision agriculture with imaging spectrometry.