scholarly journals Modeling Root Exudate Accumulation Gradients to Estimate Net Exudation Rates by Peatland Soil Depth

Plants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 106
Author(s):  
Cameron Proctor ◽  
Yuhong He
Keyword(s):  
Soil Properties ◽  
Root Exudate ◽  
Soil Depth ◽  
Root Exudation ◽  
Efficiency Gain ◽  
Radial Gradient ◽  
Single Root ◽  
Methanogen Community ◽  
The Individual ◽  
Root Influx

Root exudates accumulate as a radial gradient around the root, yet little is known about variability at the individual root level. Vertical gradients in soil properties are hypothesized to cause greater accumulation of exudates in deeper soil through hindering diffusion, increasing sorption, and decreasing mineralization. To this end, a single root exudation model coupling concentration specific exudation and depth dependent soil properties was developed. The model was parameterized for a peatland ecosystem to explore deposition to the methanogen community. Numerical experiments indicate that exudates accumulated to a greater extent in deeper soil, albeit the effect was solute specific. Rhizosphere size for glucose doubled between the 10 and 80 cm depths, while the rhizoplane concentration was 1.23 times higher. Root influx of glucose increased from 1.431 to 1.758 nmol cm−1 hr−1, representing a recapture efficiency gain of 15.74% (i.e., 69.06% versus 84.8%). Driven by increased root influx, overall net exudation rates of select sugars and amino acids varied by a factor two. Model sensitivity analysis revealed that soil depth and root influx capability are key determinants of the rhizoplane concentration and subsequently net exudation, which determines whether effluxed compounds escape the root oxic shell and are available to the methanogen community.

scholarly journals Earthworms as an Ecological Indicator of Soil Recovery after Mechanized Logging Operations in Mixed Beech Forests

Forests ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Hadi Sohrabi ◽  
Meghdad Jourgholami ◽  
Mohammad Jafari ◽  
Farzam Tavankar ◽  
Rachele Venanzi ◽  
...  
Keyword(s):  
Soil Properties ◽  
Soil Depth ◽  
Biological Properties ◽  
Economic Benefits ◽  
Ecological Indicator ◽  
Traffic Intensity ◽  
Soil Biological Properties ◽  
Density And Biomass ◽  
Soil Recovery ◽  
The Impact

Soil damage caused by logging operations conducted to obtain and maximize economic benefits has been established as having long-term effects on forest soil quality and productivity. However, a comprehensive study of the impact of logging operations on earthworms as a criterion for soil recovery has never been conducted in the Hyrcanian forests of Iran. The aim of this study was to determine the changes in soil biological properties (earthworm density and biomass) and its recovery process under the influence of traffic intensity, slope and soil depth in various intervals according to age after logging operations. Soil properties were compared among abandoned skid trails with different ages (i.e., 3, 10, 20, and 25 years) and an undisturbed area. The results showed that earthworm density and biomass in the high traffic intensity and slope class of 20–30% at the 10–20 cm depth of the soil had the lowest value compared to the other treatments. Twenty-five years after the logging operations, the earthworm density at soil depth of 0–10 and 10–20 cm was 28.4% (0.48 ind. m−2) and 38.6% (0.35 ind. m−2), which were less than those of the undisturbed area, respectively. Meanwhile, the earthworm biomass at a soil depth of 0–10 and 10–20 cm was 30.5% (2.05 mg m−2) and 40.5% (1.54 mg m−2) less than the values of the undisturbed area, respectively. The earthworm density and biomass were positively correlated with total porosity, organic carbon and nitrogen content, while negatively correlated with soil bulk density and C/N ratio. According to the results, 25 years after logging operations, the earthworm density and biomass on the skid trails were recovered, but they were significantly different with the undisturbed area. Therefore, full recovery of soil biological properties (i.e., earthworm density and biomass) takes more than 25 years. The conclusions of our study reveal that the effects of logging operations on soil properties are of great significance, and our understanding of the mechanism of soil change and recovery demand that harvesting operations be extensively and properly implemented.

scholarly journals Investigation of soil properties influence on the heavy metals sorption by plants and possibilities for prediction of their bioaccumulation by response surface methodology

2016 ◽  
Vol 81 (8) ◽  
pp. 947-958 ◽  
Author(s):  
Zlate Velickovic ◽  
Negovan Ivankovic ◽  
Vanja Strikovic ◽  
Radovan Karkalic ◽  
Dalibor Jovanovic ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Response Surface Methodology ◽  
Soil Properties ◽  
Response Surface ◽  
Interactive Effects ◽  
Npk Fertilizers ◽  
Limit Value ◽  
Safety Regulations ◽  
Icp Ms ◽  
The Individual

The aim of this study was to determine soil properties influence on the heavy metals sorption by vegetables which are used in the diet and possibilities for prediction of their bioaccumulation by response surface methodology (RSM). Lettuce was used as biosorbent, and cadmium (Cd) and lead (Pb) were used as contaminants. Lettuce is grown on compost (previously contaminated with different concentrations of Cd and Pb) which pH was adjusted with different amounts of NPK fertilizers. The content of heavy metals was determined by ICP-MS. Results showed that Cd content in lettuce was below the toxic values, but Pb concentration was above allowable, which indicates that limit value for Pb is not set in accordance with the food safety regulations. It was found that the heavy metals accumulation in plants depends not only on its content in the soil, but also on the plant affinity to the specific metal, and the individual or the interactive effects of different soil properties. Through the transfer factor it was found that lettuce has a much higher affinity to Cd in relation to Pb. RSM has proved to be very good for the examination of a large number of variables with a small number of experiments.

scholarly journals Partitioning snowmelt and rainfall in the critical zone: effects of climate type and soil properties

2019 ◽  
Vol 23 (9) ◽  
pp. 3553-3570 ◽  
Author(s):  
John C. Hammond ◽  
Adrian A. Harpold ◽  
Sydney Weiss ◽  
Stephanie K. Kampf
Keyword(s):  
Soil Properties ◽  
Soil Depth ◽  
Annual Runoff ◽  
Deep Drainage ◽  
Deep Soil ◽  
Climate Type ◽  
Event Scale ◽  
Antecedent Moisture ◽  
Physically Based ◽  
Dry Climates

Abstract. Streamflow generation and deep groundwater recharge may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. We developed model experiments using observed climate from mountain regions and artificial climate inputs that convert all precipitation to rain, and then evaluated how climate variability affects partitioning in soils with different hydraulic properties and depths. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. Annual runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer timescales. Soil texture modifies daily wetting and drying patterns but has limited effect on annual water budget partitioning, whereas increases in soil depth lead to lower runoff and greater deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates, whereas the effects of snowpack decline on deep drainage are less consistent. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and highlight the importance of developing strategies to plan for changes in water budgets in areas most at risk for shifts from snow to rain.

The effects of replaced topsoil of different depths on the vegetation and soil properties of reclaimed coal mine spoils in an alpine mining area

2019 ◽  
Vol 65 (3-4) ◽  
pp. 92-105
Author(s):  
Xinguang Yang ◽  
Xilai Li ◽  
Mingming Shi ◽  
Liqun Jin ◽  
Huafang Sun
Keyword(s):  
Plant Growth ◽  
Soil Properties ◽  
Coal Mine ◽  
Growth Parameters ◽  
Soil Depth ◽  
Mining Area ◽  
Vegetation Coverage ◽  
Mine Spoils ◽  
Plant Soil ◽  
Different Depths

Replacement of topsoil to an appropriate depth is one of the key methods for ecological restoration. The objective of this study was to investigate the effects of topsoil replacement depth on vegetation and soil properties, and to identify the optimum soil depth for reclamation of coal mine spoils in a cold alpine mining area. We sowed 3 herbaceous species after coal mine spoil heaps were treated with topsoil to 3 depths (0, 20‒25, 40‒45 cm). The variations in vegetation community structure, plant growth, soil properties were measured at different replaced topsoil depths. The correlations between plant and soil properties were analyzed statistically. The results showed species richness, diversity and evenness were not significantly different among different depths of topsoil (P > 0.05). Vegetation coverage, density, height and aboveground biomass increased significantly (P < 0.05) with increasing topsoil depth. Soil properties did not change significantly with increasing topsoil depth (P > 0.05), but soil organic matter was significantly higher at 40‒45 cm topsoil depth than at other two depths (P < 0.05). All soil properties, with the exception of total potassium, were positively correlated with the plant growth parameters. The 40‒45 cm topsoil depth of replacement should be considered as effective method in reclaiming coal mine spoils. The use of both topsoil replacement to a depth of 40‒45 cm and sowing of suitable herbaceous seeds is found to be an effective restoration strategy. Additionally, fertilization might be used as a substitute for artificial topsoil replacement to improve soil quality and speed up revegetation process by the positive plant-soil interactions.

Influence of conservation tillage practices on soil properties and crop yields for maize and wheat cultivation in Beijing, China

Soil Research ◽  
2009 ◽  
Vol 47 (4) ◽  
pp. 362 ◽  
Author(s):  
Xirui Zhang ◽  
Hongwen Li ◽  
Jin He ◽  
Qingjie Wang ◽  
Mohammad H. Golabi
Keyword(s):  
Soil Properties ◽  
Crop Yields ◽  
Conservation Tillage ◽  
Soil Depth ◽  
Chemical Properties ◽  
Conventional Tillage ◽  
Production Costs ◽  
Long Term Effects ◽  
Available N ◽  
Beijing Area

Conservation tillage is becoming increasingly attractive to farmers because it involves lower production costs than does conventional tillage. The long-term effects of sub-soiling tillage (ST), no tillage (NT), and conventional tillage (CT) on soil properties and crop yields were investigated over an 8-year period (2000–07). The study was conducted in a 2-crop-a-year region (Daxing) and a 1-crop-a-year region (Changping) of the Beijing area in China. At 0–0.30 m soil depth, water stability of macro-aggregates (>0.25 mm) was much greater for ST (22.1%) and NT (12.0%) than for CT in Daxing, and the improvements in Changping were 18.9% and 9.5%, respectively. ST and NT significantly (P < 0.05) improved aeration porosity by 14.5% and 10.6%, respectively, at Daxing and by 17.0% and 8.6% at Changping compared with CT treatment. Soil bulk density after 8 years was 0.8–1.5% lower in ST and NT treatments than in CT at both sites. Soil organic matter and available N and P followed the same order ST ≈ NT > CT at both sites. Consequently, crop yields in ST and NT plots were higher than in CT plots due to improved soil physical and chemical properties. Within the conservation tillage treatments, despite similar economic benefit, the effects on crop yields for ST were better than for NT. Mean (2000–07) crop yields for ST were 0.2% and 1.5% higher than for NT at Daxing and Changping, respectively. We therefore conclude that ST is the most suitable conservation tillage practice for annual 2-crop-a-year and 1-crop-a-year regions in the Beijing area.

scholarly journals Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models

2017 ◽  
Author(s):  
Madlene Nussbaum ◽  
Lorenz Walthert ◽  
Marielle Fraefel ◽  
Lucie Greiner ◽  
Andreas Papritz
Keyword(s):  
High Resolution ◽  
Soil Properties ◽  
Agricultural Land ◽  
Model Building ◽  
Soil Depth ◽  
Environmental Data ◽  
Gradient Boosting ◽  
Validation Data ◽  
Large Sets ◽  
Skill Scores

Abstract. High-resolution maps of soil properties are a prerequisite for assessing soil threats and soil functions and to foster sustainable use of soil resources. For many regions in the world precise maps of soil properties are missing, but often sparsely sampled and discontinuous (legacy) soil data are available. Soil property data (response) can then be related by digital soil mapping (DSM) to spatially exhaustive environmental data that describe soil forming factors (covariates) to create spatially continuous maps. With air- and spaceborne remote sensing data and multi-scale terrain analysis large sets of covariates have become common. Building parsimonious models, amenable to pedological interpretation, is then a challenging task. We propose a new boosted geoadditive modelling framework (geoGAM) for DSM. A geoGAM models smooth nonlinear relations between responses and single covariates and combines these model terms additively. Residual spatial autocorrelation is captured by a smooth function of spatial coordinates and nonstationary effects are included by interactions between covariates and smooth spatial functions. The core of fully automated model building for geoGAM is componentwise gradient boosting. We illustrate the application of the geoGAM framework by using soil data from the Canton of Zurich, Switzerland. We modelled effective cation exchange capacity (ECEC) in forest topsoils as continuous response. For agricultural land we predicted the presence of waterlogged horizons in given soil depth layers as binary and drainage classes as ordinal responses. For the latter we used proportional odds geoGAM taking the ordering of the response properly into account. Fitted geoGAM contained only few covariates (7 to 17) selected from large sets (333 covariates for forests, 498 for agricultural land). Model sparsity allowed covariate interpretation by partial effects plots. Prediction intervals were computed by model-based bootstrapping for ECEC. Predictive performance of the fitted geoGAM, tested with independent validation data and specific skill scores (SS) for continuous, binary and ordinal responses, compared well with other studies that modelled similar soil properties. SS of 0.23 up to 0.53 (with SS = 1 for perfect predictions and SS = 0 for zero explained variance) were achieved depending on response and type of score. geoGAM combines efficient model building from large sets of covariates with ease of effect interpretation and therefore likely raises the acceptance of DSM products by end-users.

REDUCTION OF SECONDARY TILLAGE IN MOULDBOARD-PLOUGHED SYSTEMS FOR SILAGE CORN AND SPRING CEREALS IN MEDIUM-TEXTURED SOILS

1990 ◽  
Vol 70 (1) ◽  
pp. 1-9 ◽  
Author(s):  
M. R. CARTER ◽  
R. P. WHITE ◽  
R. G. ANDREW
Keyword(s):  
Soil Properties ◽  
Crop Yield ◽  
Prince Edward Island ◽  
Crop Production ◽  
Sandy Loam ◽  
Soil Depth ◽  
Nutrient Content ◽  
Slight Reduction ◽  
Hordeum Vulgare L ◽  
Spring Cereals

Minimum tillage for soils that require regular cultivation consists of reducing the degree of secondary tillage and number of passes over the field. This study was conducted to determine whether one-pass mouldboard-ploughed systems were suitable for production of silage corn (Zea mays L.) and spring cereals (Hordeum vulgare L., Triticum aestivum L.) on loam to sandy loam soils (Humo-Ferric Podzol and Gray Luvisol) in the perhumid soil climate of Prince Edward Island. The effects of reduction in secondary tillage were gauged by characterizing crop yield and nutrient content, soil properties and structure, and relative economics. Plant growth, crop yield, and nutrient content were similar in all the mouldboard-ploughed systems. Soil chemical properties were not affected by reduction in secondary tillage, but the one-pass plough system did result in a macro-aggregate distribution with a greater proportion of large soil aggregates (9.5–16 mm) and a slight reduction in soil strength over the 10- to 25-cm soil depth. Macroporosity and soil density in the top 8 cm of soil were similar between tillage systems. Reducing both the degree of secondary tillage and number of tillage operations decreased both estimated cultivation costs and time of tillage per hectare by 26 and 39%, respectively. One-pass mouldboard-ploughed systems appear suitable for annual crop production on medium-textured soils under the soil environment of Prince Edward Island. Key words: One-pass tillage, soil properties, crop growth

scholarly journals Effect of soil texture on water infiltration in semiarid reclaimed land

2015 ◽  
Vol 51 (1) ◽  
pp. 33-41 ◽  
Author(s):  
Wenmei Ma ◽  
Xingchang Zhang ◽  
Qing Zhen ◽  
Yanjiang Zhang
Keyword(s):  
Hydraulic Conductivity ◽  
Soil Properties ◽  
Soil Texture ◽  
Soil Depth ◽  
Water Infiltration ◽  
Empirical Coefficient ◽  
Reclaimed Land ◽  
Essential Information ◽  
Disturbed Land ◽  
Cumulative Infiltration

The infiltration of water and its influencing factors in disturbed or reclaimed land are not well understood. A better understanding would provide essential information for assessing the hydrological processes in disturbed ecosystems. We measured the infiltration of water in soils from loamy and sandy reclaimed land. The relationships between infiltration and soil properties were analyzed based on three models: the Kostiakov, Philip, and Green–Ampt equations. Our objectives were to understand water infiltration in reclaimed land with a variety of soil textures and to establish the dependence of water infiltration on soil properties. Both the rate of infiltration and the cumulative infiltration were higher in sandy than in loamy soils. The rate of infiltration and the cumulative infiltration decreased with soil depth in undisturbed land. The sorptivity rate (S) from the Philip equation, empirical coefficient (K) from the Kostiakov equation, and the satiated hydraulic conductivity (Ksl) from the Green–Ampt equation were 22%, 16%, and 7.1% higher, respectively, in sandy than in loamy soils. The Ksl increased significantly with Ks (saturated hydraulic conductivity) in both sandy and loamy soils. These indicated that the Green–Ampt equation can be used to describe Ks and the characteristics of infiltration for soils on disturbed land.

scholarly journals Soil-Landscape Modeling and Remote Sensing to Provide Spatial Representation of Soil Attributes for an Ethiopian Watershed

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Nurhussen Mehammednur Seid ◽  
Birru Yitaferu ◽  
Kibebew Kibret ◽  
Feras Ziadat
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Soil Properties ◽  
Vegetation Index ◽  
Soil Depth ◽  
Statistical Prediction ◽  
Field Observations ◽  
Linear Regression Models ◽  
Alternative Source ◽  
Soil Attributes

Information about the spatial distribution of soil properties is necessary for natural resources modeling; however, the cost of soil surveys limits the development of high-resolution soil maps. The objective of this study was to provide an approach for predicting soil attributes. Topographic attributes and the normalized difference vegetation index (NDVI) were used to provide information about the spatial distribution of soil properties using clustering and statistical techniques for the 56 km2Gumara-Maksegnit watershed in Ethiopia. Multiple linear regression models implemented within classified subwatersheds explained 6–85% of the variations in soil depth, texture, organic matter, bulk density, pH, total nitrogen, available phosphorous, and stone content. The prediction model was favorably comparable with the interpolation using the inverse distance weighted algorithm. The use of satellite images improved the prediction. The soil depth prediction accuracy dropped gradually from 98% when 180 field observations were used to 65% using only 25 field observations. Soil attributes were predicted with acceptable accuracy even with a low density of observations (1-2 observations/2 km2). This is because the model utilizes topographic and satellite data to support the statistical prediction of soil properties between two observations. Hence, the use of DEM and remote sensing with minimum field data provides an alternative source of spatially continuous soil attributes.

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