Inherent Soil Properties Research Articles

Soil fertility status under mixed pastures in irrigated Tsitsikamma dairy farms: case studies

Animal manures are increasingly receiving renewed interest as an alternative to synthetic fertilizers. While they may improve ecosystem functions, there is limited information on short-term effects of organic amendments on soil reaction and nutrient dynamics in irrigated mixed dairy pastures, especially in the context of the Tsitsikamma region, South Africa. This study examined the soil fertility status of minimum tilled 6-year-old pasture-mixed dairy farms (F1, F2, F3, F4 and F5) in the Upper (UT) and Lower (LT) Tsitsikamma regions treated with different rates of NPK (nitrogen, phosphorus, potassium) fertilizer alone or in combination with poultry manure (PM) and/or dairy effluent (DE). Soil samples were collected at 0–15, 15–30, 30–45 and 45–60 cm depth intervals and analysed for soil pH, P, K, Ca and Mg. Results of this study revealed variable trends on soil pH and nutrient changes between farms, suggesting an influence of some inherent soil properties in addition to the 6-year applied management practices. When averaged over sampled farms, surface placement of soil amendments and limited soil disturbance resulted in surface stratification of soil pH, P, K, Ca and Mg. On the other hand, integration of organic and inorganic fertilizers induced significant changes in nutrient contents and stocks to a depth of 60 cm, especially in the LT region. A combination of NPK fertilizer, PM and/or DE applied in pasture mixtures generally showed potential to improve soil fertility in both regions. As such, adoption of this combination by farmers could cut down reliance on expensive synthetic fertilizers and costs of dairy production. However, studies are still necessary in this region to validate the observed results.

Integrating rhizosphere bacterial structure and metabolites with soil Cd availability in different parent paddy soils

Soil bacterial community structure and rhizosphere metabolites are important pathways for rice to respond to external Cd stress. The specific correlations between these microorganisms, metabolites and inherent soil properties, as well as the mechanisms they utilize to regulate Cd availability across different parent soils remain underexplored, emphasizing the need for deeper understanding to inform effective soil management strategies. In this study, five typical parent soils with large differences in properties (quaternary red clay soil (hereby defined as Q), granite soil (G), river sandy mud (R), yellow mud soil (Y), stucco field (S)) in Chinese paddy soils were collected, and extra Cd were added (CK: 0 mg·kg−1, Cd: 2.4 mg·kg−1).The result indicated that the toxicity impact of Cd in rice grains in G was the weakest, and the highest Cd bioavailability in S. The abundance of Proteobacteria, Bacteroidota and Firmicutes showed an increasing trend in G, while they decreased significantly in S. The contents of Cis-9-palmitoleic acid and phosphoethanolamine increased by 170.02 % and 154.03 % in G, decreased by 218.62 % and 181.58 % in S. MBNT15 and Desulfobacterota showed a significant negative correlation with humic acid molecular weight (MW) extracted from parent soils and Clay (montmorillonite, illite, kaolinite) contents, while they exhibited a positive correlation with soil organic matter (OM) content (P < 0.01). The MW played a crucial role in shaping rhizosphere metabolites with R2 value of 0.8498. These results elucidate how soil bacterial communities, rhizosphere metabolites, and inherent soil properties interact to regulate Cd availability across different parent soils.

Spatial variation of gully erosion determinants across subtropical regions of China

Gully erosion, with an enormous threat to global economic development and ecological security, results from the comprehensive effect of soil inherent properties and external geo-environmental factors. Previous studies on gully causative factors were mainly conducted on a specific site, case, or region, and limited systematic investigation has been performed on their spatial variation. Based on gully inventory in the seven provinces of southern China, this study investigated the spatial variation of thresholds for fifteen potential causative factors by the frequency ratio model, and analyzed the contribution of these factors to gully erosion by the Boruta algorithm. The results showed that gully density generally increased from north to south, characterized by a clustered distribution within a specific range, but the threshold of each potential factor exhibited a slight difference. Particularly, gully formation was predominantly influenced by multi-year average rainfall erosivity, multi-year average rainfall, and population density. However, the relative importance of these factors to gully erosion showed significant spatial heterogeneity. The relative importance increased from north to south for the factors of rainfall erosivity (8.25 %-13.56 %), rainfall (8.62 %-12.01 %), and slope aspect (0.35 %-1.22 %), but decreased for the factors of slope gradient (2.93 %-6.24 %), temperature (5.23 %-8.89 %), normalized difference vegetation index (NDVI) (5.25 %-7.80 %), and fraction vegetation coverage (FVC) (4.11 %-7.23 %). Overall, climatic factors exhibited an increasing contribution to gully erosion from north to south, whereas the influence of topography and vegetation coverage decreased along the same gradient. These findings will facilitate a better gully erosion control in southern China.

Nature versus nurture: Quantifying the effects of management, region, and hillslope position on soil health indicators in an on‐farm survey in Minnesota

AbstractA major challenge to implementing effective soil health assessments is how to distinguish the effects of management from underlying soil variability driven by inherent soil properties. This challenge has important consequences for the use of soil health indicators as tools for monitoring and assessment because soil‐forming factors constrain the range of indicator values and the magnitude of management‐induced changes. Here, we present results from a statewide survey of 15 soil health indicators measured on 30 fields on commercial farms across four major land resource areas in Minnesota. Fields included in the study differed in tillage, cover crop implementation, and crop rotation. Within each field, we collected samples from upper and lower hillslope positions to quantify the effect of topography. We consistently detected differences in soil health indicators between regions (13/15 indicators) and hillslope positions (8/15 indicators). However, only wet aggregate stability was sensitive to management across regions and years, highlighting the importance of physical indicators of soil health. This result was surprising in light of existing literature supporting the sensitivity of many soil health indicators to management, but it is consistent with other studies conducted in high organic matter soils in the Upper US Midwest. Our results highlight the need for regionally representative datasets to guide the development of interpretations and benchmarks for soil health indicators. This is particularly important when soil health indicators are applied outside traditional research contexts (such as in commercial soil health testing), where interpretation must take place without the benefit of historical baseline data.

Distribution coefficient prediction using multimodal machine learning based on soil adsorption factors, XRF, and XRD spectrum data

The distribution coefficient (Kd) plays a crucial role in predicting the migration behavior of radionuclides in the soil environment. However, Kd depends on the complexities of geological and environmental factors, and existing models often do not reflect the unique soil properties. We propose a multimodal technique to predict Kd values for radionuclide adsorption in soils surrounding nuclear facilities in Republic of Korea. We integrated and trained three sub-networks reflecting different data domains: soil adsorption factors for physicochemical conditions, X-ray fluorescence (XRF) data, and X-ray diffraction (XRD) spectra for inherent soil properties. Our multimodal model achieved high performance, with a coefficient of determination (R2) of 0.84 and root mean squared error (RMSE) of 0.89 for natural log-transformed Kd. This is the first study to develop a multimodal model that simultaneously incorporates inherent soil properties and adsorption factors to predict Kd. We investigated influential peaks in XRD spectra and also revealed that pH and calcium oxide (CaO) were significant variables in soil adsorption factors and XRF data, respectively. These results promote the use of a multimodal model to predict Kd values by integrating data from different domains, providing a cost-effective and novel approach to elucidate the mechanisms of radionuclide adsorption in soil.

A data‐driven topsoil classification framework to support soil health assessment in Minnesota

AbstractSoil health assessments aim to quantify soil health status using indicators linked to ecosystem services such as yield, nutrient cycling, water cycling, or carbon storage. Many indicators are related to soil biological processes, which can be challenging to interpret because they are sensitive not only to management, but also to nonmanagement variables such as soil inherent properties, topography, and climate. Existing studies address this challenge by grouping similar soils by taxonomy, geography, or a combination of these and other variables for soil health assessment. We investigated whether grouping soils based on multiple quantitative topsoil properties could be an alternative to taxonomic or geographic groups. We used an unsupervised classification algorithm, k‐means, to cluster publicly available soil and climate data for Minnesota. Clustering into eight conceptual groups (“clusters”) based on 10 topsoil properties was determined to be the optimal algorithm output. We evaluated the ability of our soil clusters and other grouping methods to explain variance in eight soil health indicators. We found the combination of Major Land Resource Area (MLRA) and soil cluster performed best, explaining as much or more variance than other groupings for five of the eight indicators. The clusters distinguish zones of topsoil variation at the field scale, and MLRAs account for broader scale variation in climate and other landscape factors. The approach we describe is flexible and could be applied at different locations and scales to produce conceptual soil groups and associated maps to support soil health test sampling and interpretation at the field scale.

Modeling the carbon dynamics of ecosystem in a typical permafrost area

Climate change poses mounting threats to fragile alpine ecosystem worldwide. Quantifying changes in carbon stocks in response to the shifting climate was important for developing climate change mitigation and adaptation strategies. This study utilized a process-based land model (Community Land Model 5.0) to analyze spatiotemporal variations in vegetation carbon stock (VCS) and soil organic carbon stock (SOCS) across a typical permafrost area - Qinghai Province, China, from 2000 to 2018. Multiple potential factors influencing carbon stocks dynamics were analyzed, including climate, vegetation, soil hydrothermal status, and soil properties. The results indicated that provincial vegetation carbon storage was 0.22 PgC (0.32 kg/m2) and soil organic carbon pool was 9.12 PgC (13.03 kg/m2). VCS showed a mild increase while SOCS exhibited fluctuating uptrends during this period. Higher carbon stocks were observed in forest (21.74 kg/m2) and alpine meadow (18.08 kg/m2) compared to alpine steppes (9.63 kg/m2). Over 90 % of the carbon was stored in the 0-30 cm topsoil layer. The contribution rates of soil carbon in the 30-60 cm and 60-100 cm soil layers were significantly small, despite increasing stocks across all depths. Solar radiation, temperature, and NDVI emerged as primary influential factors for overall carbon stocks, exhibiting noticeable spatial variability. For SOCS at different depths, the normalized differential vegetation index (NDVI) was the foremost predictor of landscape-level carbon distributions, which explained 52.8 % of SOCS variability in shallow layers (0-30 cm) but dropped to just 12.97 % at the depth of 30-60 cm. However, the dominance of NDVI diminished along the soil depth gradients, superseded by radiation and precipitation. Additionally, with an increase in soil depth, the influence of inherent soil properties also increased. This simulation provided crucial insights for landscape-scale carbon responses to climate change, and offered valuable reference for other climate change-sensitive areas in terms of ecosystem carbon management.

Scaling of soil organic carbon in space and time in the Southern Coastal Plain, USA

Soil organic carbon (SOC) is a dynamic soil property (DSP) that represents the largest portion of terrestrial carbon. Its relevance to carbon sequestration and the potential effects of land use on SOC storage, make it imperative to map across both space and time. Most regional-scale studies mapping SOC give static estimates and train different models for different periods with varying accuracies. We developed a flexible modeling approach called DSP-Scale to map SOC in both space and time. DSP-Scale uses ecological concepts and empirical data to predict DSP dynamics using inherent soil properties (static factors) and land cover changes (dynamic factors). We compiled SOC data for the 0–20 cm depth (SOC20) from 1441 points spanning a 25 million ha study area in the southeastern U.S. Coastal Plain, incorporating data from the Rapid Carbon Assessment, National Cooperative Soil Survey Soil Characterization database, and other regional studies. We developed a random forest model using climate, topography, soil survey, and land cover changes to predict SOC20 dynamics for five-year periods between 2001 and 2019. Our model explained 66 % and 59 % of the variation for the training and test data, respectively. Top predictors included mean annual precipitation, slope, and soil erosion class. Land cover 10 years before measurements of SOC20 was more important than current land cover for estimating SOC20. We estimated total SOC stocks of 207.1 and 208.3 Tg for 2001 and 2019, respectively. Highest gains of total SOC stock (0.9 Tg from 2001 to 2019) were associated with land cover change from mixed to evergreen forest. The greatest loss of total SOC stock (0.2 Tg) in the same period was associated with land cover change from pasture/hay to evergreen forest. We concluded that the DSP-Scale approach provides a flexible way to use dynamic and static factors affecting SOC stocks to predict changes in space and time at regional scales.

Effect of Phanerochaete chrysosporium induced phosphate precipitation on bacterial diversity during the soil remediation process.

Biomineralization by phosphate minerals and phosphate solubilizing fungi (PSF) has attracted great interest as a novel remediation method for heavy metal(loid) co-contaminated soil. It was very essential to investigate the microenvironment response with the application of amendments. In this study, three grain sizes of hydroxyapatites (HAP) and Phanerochaete chrysosporium (P. chrysosporium) were used to investigate the change in heavy metal(loid) fractions, soil physicochemical properties, and bacterial community during the remediation of Mangchang and Dabaoshan acidic mine soils. The results showed that the residual fractions in the two soils increased significantly after 35 days of remediation, especially that of As and Zn in Dabaoshan soils were presented at over 87%. In addition, soil pH, organic matter (OM), and available phosphorous (AP) were almost improved. 16S rRNA sequencing analysis indicated that the introduction of culture medium and P. chrysosporium alone changed bacterial abundance, but the addition of HAP changed the bacterial diversity and community composition by altering environmental conditions. The amendments in the research showed good performance on immobilizing heavy metal(loid)s and reducing their bioavailability. Moreover, the research suggested that environmental factors and soil inherent properties could influence the microbial community structure and composition.

Soil health characteristics

Soil health characteristics Lynette Abbott from The University of Western Australia, places the spotlight on soil health, including its physical, chemical, biological and hydrological characteristics. Soil health encompasses its physical, chemical, biological, and hydrological characteristics. Inherent soil properties underpin how components of soil health combine to support productive agricultural or natural ecosystems. Soil health encompasses its physical, chemical, biological, and hydrological characteristics. Inherent soil properties underpin how components of soil health combine to support productive agricultural or natural ecosystems. The origin of the underlying parent rock materials and the extent to which they are weathered, influences naturally occurring nutrient cycling processes in soil. Hence, some soils have inherently high levels of nutrients available for plants, but others have more limited plant-available nutrient resources.

Soil, climate, time and site factors as drivers of soil structure evolution in agricultural soils from a temperate-boreal region

The evolution of soil structure in agricultural soils is driven by natural and anthropogenic factors including inherent soil properties, climate and soil management interventions, all acting at different spatial and temporal scales. Although the causal relationships between soil structure and these individual factors are increasingly understood, their relative importance and complex interactive effects on soil structure have so far not been investigated across a geo-climatic region.Here we present the first attempt to identify the relative importance of factors that drive the evolution of soil structure in agricultural soils as well as their direction of effect with a focus on the temperate-boreal zone. This was done using a random forest (RF) approach including soil, climate, time, and site factors as covariates. Relative entropy, as quantified by the Kullback-Leibler (KL) divergence, was used as a quantitative index of soil structure, which is derived from the particle-size distribution and soil water retention data, and integrates the effects of soil structure on pores from the micrometre-scale to large macropores. Our dataset includes 431 intact topsoil and subsoil samples from 89 agricultural sites across Sweden and Norway, which were sampled between 1953 and 2017. The relative importance of covariates for the evolution of soil structure was identified and their non-linear and non-monotonic effects on the KL divergence were investigated through partial dependence analysis. To reveal any differences between topsoils (0–30 cm; n = 174) and subsoils (30–100 cm; n = 257), the same analysis was repeated separately on these two subsets.The covariates were able to explain on average more than 50% of the variation in KL divergence for all soil samples and when only subsoil samples were included. However, the predictions were poorer for topsoil samples (≈ 35%), underlining the complex dynamics of soil structure in agricultural topsoils. Parent material was the most important predictor for the KL divergence, followed by clay content for all soil samples and sampling year for only subsoil samples. Mean annual air temperature ranked third and annual precipitation ranked fourth for subsoil samples. However, it remains unclear whether the effects of climate factors are direct (e.g., freezing and thawing, wetting and drying, rainfall impact) or indirectly expressed through interactions with soil management. The partial dependence analysis revealed a soil organic carbon threshold of around 3% below which soil structure starts to deteriorate. Besides this, our results suggest that subsoil structure in the agricultural land of Sweden deteriorated steadily during the 1950′s to 1970′s, which we attribute to traffic compaction as a consequence of agricultural intensification. We discuss our findings in the light of data bias, laboratory methods and multicollinearity and conclude that the approach followed here gave valuable insights into the drivers of soil structure evolution in agricultural soils of the temperate-boreal zone. Theses insights will be of use to inform soil management interventions that address soil structure or soil properties and functions related to it.

Cold Climate Factors in Nitrogen Management for Maize

Among essential crop nutrients, nitrogen is the greatest management challenge in maize (Zea mays L.) production due to high requisite rates as well as dynamic transformations and losses. Climate plays a role in N management through changes in crop calendars, soil properties, agronomic practices, and yield effects. This study focuses on climate influences on maize N management and the objectives are to (i) review cold climate factors impacting economic optimum N rates (EONR), (ii) discuss approaches and climate considerations in estimating optimum N rates, and (iii) illustrate unexplored climate aspects related to optimum N rate assessment. Cold climate effects are expressed through inherent soil properties, agronomic management, and N fertilizer management. Most current N rate calculators do not explicitly account for climate factors, but implicitly integrate them through regional calibrations. Yield and EONR data from the US Corn Belt region indicate a positive correlation where lower means are associated with colder climates. High variability within climate regions is explained by differences in annual production environments, notably seasonal weather. Soil health models show that colder climates in the US are associated with higher stocks of soil organic matter, especially labile fractions. Adapt-N model simulations of a colder (North Central Wisconsin; 45.50, −89.70) and warmer (South Central Illinois; 38.50, −89.70) Corn Belt location show that higher soil organic N stocks do not increase crop N availability, presumably due to temperature-constrained N mineralization rates. The EONR for the colder site is 58 kg N ha−1 lower than the warmer site, which is well explained by differences in yield potential. Overall, abductive inferences suggest that colder climates are generally associated with higher levels of organic N stocks, but lower yields and crop N demands lessen EONRs. Seasonal weather and interactions with soil and agronomic factors also critically impact EONR, which can be assessed with model-based decision tools.

Temperature-induced changes in DTPA-extractable trace elements: Predicting the potential impact of climate change on the availability of soil elements

The extraction of trace elements from soil with DTPA is a widely used protocol across laboratories. There is a possible “hidden” discrepancy regarding the results obtained from the extractions, i.e., ambient laboratory temperature and soil properties. In this study, the possible influence of these factors on the extractability of the available forms of Cu, Fe, Pb, Mn, Ni, and Zn, measured with DTPA were studied. Α series of extractions was carried out on a soil sample under normal laboratory temperatures, which fluctuated throughout the year, from 15 to 33.9 °C. In other 144 soil samples, the prevailing physico-chemical properties of soil were evaluated (pH, organic C, clay, CaCO3) that affected the percentage of DTPA extractability relative to the pseudo-total determined content. A strong positive correlation of all metals versus increased ambient temperature was found. Cu had an R2 of 0.897, Fe 0.970, Mn 0.957, Ni 0.938, Pb 0.876, and, Zn 0.922, all highly significant. Extracted Mn exhibited a 6.5-fold increase at the highest temperature of 33.9 οC compared to the lowest. Similar increasing trend was observed for Fe, and Ni, and smaller for Cu, Zn, and Pb. Inherent soil properties affected the percentage of extractability relative to the total content: extractability of Cu, Fe, Mn, and Ni was affected negatively by pH, and the extractability of the studied metals with CaCO3 content. Other soil properties (organic C and clay/sand content) also had an effect, not as pronounced as that of pH and CaCO3. This signifies the necessity of employing standard conditions for routine extractions such as DTPA so that data may be comparable. Also these identified discrepancies may have consequences in the extractability and availability of soil micronutrients and toxic elements regarding climate change. This study aspires to play the role of an initial step towards more robust investigations that would suggest ways of correcting temperature and soil characteristics discrepancies across laboratories.

Soil health benefits associated with urban horticulture

As the global population grows and is increasingly concentrated in urban environments, the quality of urban horticultural soils is of mounting importance. Until now, most urban horticultural soil assessments have been applied in nations and continents outside North America, and none have been conducted in Canada—an important agricultural region. Here, we present the first Canadian study to evaluate soil health in urban horticultural soil (gardens producing fruit and vegetables), benchmarked against conventional agricultural soil in surrounding rural areas (producing cereals, oilseeds, and legumes). We assessed a range of soil health indicators (total C, soil organic C [SOC], active C, CO2 evolution, wet aggregate stability [WAS], total N, autoclave citrate extractable [ACE] protein, potentially mineralizable N [PMN], and N2O production), soil fertility indicators (inorganic N, available P, and available K), and inherent soil properties (texture, electrical conductivity [EC], and pH). We found that carbon- and nitrogen-based soil attributes in urban horticultural soils were 200 % that of the agricultural soils, indicating superior soil health—which had significant implications for interpreting soil health scores. As for soil fertility, inorganic N and available K did not differ between the two systems, but available P was 400 % higher in urban horticulture than agriculture soils, indicating that management practices which build soil health might risk also building excessive soil P levels. Our findings suggest that urban horticulture soils may provide superior ecosystem services and function as a reservoir for SOC, likely due to the soil health management practices implemented by gardeners—but care should be taken to manage soil health alongside managing soil fertility. Urban horticulture soil is an ideal platform for expanding research and governance not only for food production but for valuable ecosystem services.

Product-inhibition feedbacks, not microbial population level tradeoffs or soil pH, regulate decomposition potential under nutrient eutrophication

Global eutrophication of growth-limiting nutrients for plants and microbes, including nitrogen (N) and phosphorus (P), can cause enzymatic feedbacks at different levels of biological organization that in turn drive soil organic matter (SOM) decomposition. Because land management practices, such as fire in mesic grasslands, also impact nutrient availability, it is important to understand how soil feedbacks may manifest under multifactorial change. Here, using a thirty-year field experiment that crosses N- and P-fertilization (alone and in combination) with contrasting fire treatments (annual burning and fire suppression) in a tallgrass prairie ecosystem, we evaluated evidence for three possible feedbacks (product-inhibition, enrichment of fast-growing copiotrophic taxa, and soil pH shift) by measuring soil extracellular enzyme activities (EEAs) and microbial community composition (16S rRNA genes) monthly for a year. Consistent with product-inhibition feedback predictions, both N-fertilization and fire suppression (which increases soil N availability) decreased N-acquiring relative to C-acquiring EEAs, suggesting reduced N limitation. P-fertilization did not lower acid phosphatase activity, thus the product-inhibition feedback hypothesis was not supported under P eutrophication conditions. Although N- and P-fertilization, alone and in combination, did decrease putatively oligotrophic populations in favor of putatively copiotrophic populations, the hypothesized tradeoff for faster growth, a concomitant decrease in all soil EEAs, was only observed in unburned soils fertilized with N. Finally, observed changes in EEAs were not driven by acidification, in contrast to other fertilization experiments. Overall, results suggest that higher N availability affects enzymatic feedbacks primarily through product-inhibition, but a threshold-like growth tradeoff (copiotrophic) response is possible under the combination of fire suppression and N-fertilization. Inherent soil properties may modulate site-specific responses to fertilization, as evidenced by weak pH and EEA responses to N- and P-fertilization, respectively. Finally, soil microbial community change following chronic fertilization did not reliably predict the “copiotrophic” feedback of reduced SOM decomposition potential.

Comparative analysis of rhizobial and bacterial communities in experimental cotton fields: Impacts of conventional and conservation soil management in the Texas High Plains

Conservative agricultural management strategies pursue long-term ecological benefits through practices such as no-tillage, cover crop, and inherent soil properties management. Farmers, however, are often hesitant to adopt such practices due to lack of experience, initial expense, and concern for low crop productivity. Overcoming this barrier requires novel approaches, such as effectively managing the soil microbiome to attain high productivity at a low cost, especially in a semi-arid region. To study the potential of conservation agriculture, we investigated components of soil bacterial community and rhizobial diversity in long-term experimental cotton fields divided into conventional tillage monoculture systems with winter fallow (CT) and no-tillage with mixed cover crop (M-NT) system on the Texas High Plain (THP). We conducted next-generation amplicon sequencing targeting rpoB gene with collected soil samples from different soil managements and seasons. Our research revealed that although CT had significantly greater bacterial diversity and species richness than the M-NT management, rhizobial diversity and species richness were higher in M-NT than in CT management. Both bacterial and rhizobial diversity and richness were greater in summer than in fall. The abundance of the order Rhizobiales was consistently high in M-NT than in CT fields in both seasons. Soil management altered the dominant rhizobial genus associated with cotton production systems; Rhizobium and Pararhizobium dominated M-NT management, while Bradyrhizobium and Sinorhizobium were dominant under CT management. These outcomes suggest that incorporating legumes into a cover crop in this semi-arid cotton-growing region can initiate beneficial changes to the dynamics of the indigenous rhizobial assemblage. The high prediction accuracy of our machine learning model using bacterial community data classifying the managements as CT or M-NT validates the possibilities of a strong underlying relationship between soil management and the bacterial diversity in the soil.

Soil health, microbial communities, and annual ryegrass yield under contrasting management practices

AbstractBiological indicators are often used to evaluate the effect of management practices on soil health. However, determining which indicators can detect changes in soil health after implementation of conservation practices and how these indicators relate to plant growth in grass seed production systems remains unclear. The goal of this study was to explore the relationships between management practice history, soil health metrics, plant growth, and soil microbial communities in annual ryegrass grown under greenhouse conditions. Soils were collected from 12 annual ryegrass [Lolium multiflorum (L.) Husnot] fields managed under conventional (till/bale) or conservation (no‐till/full straw) management practices, with three silt loams and three silty clay loams collected for each practice. Annual ryegrass was grown for 5 months on each of the 12 soils in a greenhouse. Soils with a history of conservation management improved the majority of the carbon cycling‐related metrics for the silt loam soils. Management practices had no effect on seed yield, however, conservation management significantly improved aboveground biomass in silty clay loam soils. Contrasting management practices resulted in distinct microbial communities, making them sensitive indicators of changes in soil conditions. Soil health and plant metrics were positively associated with the microbial communities in soils under conservation management. Total C and organic matter were positively correlated to plant parameters in silt loams, while few indicators were correlated to plant metrics in silty clay loams. These results highlight the complex interplay between microbial communities, soil health, and plant growth and the importance of considering inherent soil properties like texture.

Soil health explains the yield-stabilizing effects of soil organic matter under drought

Soil organic matter (SOM) serves as an important indicator of soil health. Soils with high SOM are associated with high crop yield under drought conditions. However, a critical question remains unanswered: is the yield-stabilizing effect of SOM attributable to inherent soil properties, such as soil texture and taxonomy? Or is it driven by dynamic soil properties that reflect the overall health of the soil? Following the Soil Health Assessment Protocol and Evaluation, we derived a soil health score (SHS; range: 0–1) from the SOM concentration by accounting for site-specific variables, including climate, texture, and soil suborder. Using county-level data of rainfed corn across the U.S. from 2000 to 2016, we found that higher SHS were associated with higher yields. During the most severe drought events, an increase of 0.5 in SHS was associated with a 1.15 ​± ​0.18 ​Mg ​ha−1 increment in corn yield, suggesting that high SHS helps to stabilize yield in drought. Interestingly, smaller but statistically significant effects of SHS on yield were found during less intensive droughts. The SOM concentration was a slightly better predictor of corn yield than the SHS. We also found similar effects of SHS on corn yield across different soil types, i.e., different textures or soil suborders, under severe drought conditions. Our results suggest that soil health is a main factor in explaining the yield benefits of SOM, while the effects of soil health were not driven by differences in soil texture or suborder. We argue that the resilience of corn yield against drought can be potentially increased by adopting agronomic practices aimed at augmenting SOM and improving overall soil health across a broad spectrum of geographical locations and site characteristics.

Effects of microtopography on within-field spatial variation of inherent soil properties in Andosols of Tokachi district, Hokkaido

ABSTRACT In large-scale upland cropping systems, understanding the magnitude of soil property variations and mapping the distribution are essential to improve soil nutrient management. The Tokachi district of Hokkaido has large-scale upland fields, and the soils are dominated by Andosols that inherently have characteristic clay minerals and high soil organic carbon content. In the region, microtopography is known to exist that can affect soil formation and within-field variation of the inherent soil properties. However, limited information exists about the relationship between microtopography and the spatial variation of inherent soil properties that are important for nutrient dynamics. Therefore, this study aimed to assess the effect of microtopography on the within-field variation of inherent soil properties in Andosols of Tokachi district, Hokkaido. Within a 6.6-ha field with an elevation difference of 3.2 m, four soil profiles were surveyed at different topographical positions, and 530 surface soil samples were collected at 12-m intervals. Samples were analyzed for total carbon (TC), acid-oxalate extractable Al, Fe, and Si (Alo, Feo, and Sio), pyrophosphate extractable Al and Fe (Alp and Fep), cation exchange capacity (CEC), and phosphate absorption coefficient (PAC). Geostatistical analysis was applied to understand the spatial structure of the surface soil properties. All soil profiles were dominated by volcanic parent materials, and they were classified into different types of Andosols. An exceptional variation of inherent soil properties was found in the surface soil, with TC content ranging from 35.2 to 124 g kg−1 and CEC from 20.3 to 55.7 cmolc kg−1. Geostatistical analysis showed that TC content varied over a large distance (range: 226 m) while allophane content varied at a shorter distance (range: 118 m). Our findings revealed that microtopography affected the soil water dynamics and erosion of the surface soil particles which caused the variation of TC, CEC, and allophane. Further studies must be conducted to understand the effects of the variation of these inherent soil properties on soil nutrient availability and crop productivity.

Drivers of field-saturated soil hydraulic conductivity: Implications for restoring degraded tropical landscapes

Water security represents a major challenge in East Africa, affecting the livelihoods of millions of people and hindering sustainable development. Predicted increases in rainfall intensity and variability are expected to exacerbate water insecurity and land degradation. Improving soil infiltrability is an effective strategy for addressing water insecurity and land degradation. Research on soil infiltrability is often highly localized; therefore, scientific understanding of the drivers of infiltrability on larger spatial scales is limited. The aim of this study was to understand the main drivers of infiltrability across five contrasting landscapes in Kenya. We measured field-saturated hydraulic conductivity (Kfs) in 257 plots and collected data for variables representing soil properties (sand content, soil organic carbon (SOC) and pH), land degradation (grazing pressure and presence of erosion), vegetation quantity (woody aboveground biomass), and vegetation quality (functional properties and diversity). We used generalized mixed-effects models to test for the effects of these variables on Kfs. Median Kfs for the five sites ranged between 23.8 and 101.8 mm h−1. We found that Kfs was positively associated with sand content (standardized effect 0.39), SOC content (0.15), and functional diversity of woody vegetation (0.09), while it had a negative relationship with the presence of erosion (−0.24) and grazing pressure (−0.09). Subsequently, we conclude that infiltrability can be enhanced through using land restoration strategies which specifically target parameters that affect Kfs. The results further support that Kfs is not solely dictated by inherent soil properties, and that management interventions which boost SOC, reduce erosion, and minimize unsustainable grazing can help address water scarcity by restoring soil hydrological function.