Interrelations of soil micro-orgamisms and mulberry I.Phytohormone production by soil and rhizosphere bacteria and their effect on plant growth

Bacteria isolated from the rhizosphere of mulberry (Morus indica) as well as from control soil were tested for their effects on the growth of mulberry seedlings and for phytohormone production. About 12.8 per cent of the rhizosphere and 9.7 per cent of the soil isolates produced phytohormones in cultures. Rhizosphere isolates were more active in hormone synthesis than their soil counterparts. Soaking mulberry stem cuttings in culture filtrates of phytohormone synthesisers hastened their rooting. Culture filtrates of many isolates — hormone producers or not — stimulated or inhibited the growth of shoot and/or root of plants. Many cultures could also inhibit the germination of mulberry seeds.

Effect of associating anions on phosphorus retention in soil II. Under variable anion concentration

The results of the present investigation reveal that the presence of anions in the reacting medium greatly modify the reactions between soil and solution P. Associating anions reduce considerably the retention of phosphate in soils. Citrate, tartrate, and silicate are found to be superior to arsenate, oxalate, and fluoride in reducing phosphate retention in soil. The performance of associating anions depends on the pH and P concentration of the reacting medium. The nature and properties of soil also play a highly significant role on the effectiveness of associating anions.

Defoliation and patchy nutrient return drive grazing effects on plant and soil properties in a dairy cow pasture

Large herbivores can influence plant and soil properties in grassland ecosystems, but especially for belowground biota and processes, the mechanisms that explain these effects are not fully understood. Here, we examine the capability of three grazing mechanisms-plant defoliation, dung and urine return, and physical presence of animals (causing trampling and excreta return in patches)-to explain grazing effects in Phleum pratense-Festuca pratensis dairy cow pasture in Finland. Comparison of control plots and plots grazed by cows showed that grazing maintained original plant-community structure, decreased shoot mass and root N and P concentrations, increased shoot N and P concentrations, and had an inconsistent effect on root mass. Among soil fauna, grazing increased the abundance of fungivorous nematodes and Aporrectodea earthworms and decreased the abundance of detritivorous enchytraeids and Lumbricus earthworms. Grazing also increased soil density and pH but did not affect average soil inorganic-N concentration. To reveal the mechanisms behind these effects, we analyzed results from mowed plots and plots that were both mowed and treated with a dung and urine mixture. This comparison revealed that grazing effects on plant attributes were almost entirely explained by defoliation, with only one partly explained by excreta return. Among belowground attributes, however, the mechanisms were more mixed, with effects explained by defoliation, patchy excreta return, and cow trampling. Average soil inorganic-N concentration was not affected by grazing because it was simultaneously decreased by defoliation and increased by cow presence. Presence of cows created great spatial heterogeneity in soil N availability and abundance of fungivorous nematodes. A greenhouse trial revealed a grazing-induced soil feedback on plant growth, which was explained by patchiness in N availability rather than changes in soil biota. Our results show that grazing effects on plant attributes can be satisfactorily predicted using the effects of defoliation, whereas those on soil fauna and soil N availability need understanding of other mechanisms as well. The results indicate that defoliation-induced changes in plant ecophysiology and the great spatial variation in N availability created by grazers are the two key mechanisms through which large herbivores can control grassland ecosystems.

Ferrolysis induced soil transformation by natural drainage in Vertisols of sub-humid South India

In sub-humid South India, recent studies have shown that black soil areas (Vertisols and vertic Intergrades), located on flat valley bottoms, have been rejuvenated through the incision of streambeds, inducing changes in the pedoclimate and soil transformation. Joint pedological, geochemical and geophysical investigations were performed in order to better understand the ongoing processes and their contribution to the chemistry of local rivers. The seasonal rainfall causes cycles of oxidation and reduction in a perched watertable at the base of the black soil, while the reduced solutions are exported through a loamy sand network. This framework favours a ferrolysis process, which causes low base saturation and protonation of clay, leading to the weathering of 2:1 then 1:1 clay minerals. Maximum weathering conditions occur at the very end of the wet season, just before disappearance of the perched watertable. Therefore, the by-products of soil transformation are partially drained off and calcareous nodules, then further downslope, amorphous silica precipitate upon soil dehydration. The ferrolysed area is fringing the drainage system indicating that its development has been induced by the streambed incision. The distribution of C-14 ages of CaCO3 nodules suggests that the ferrolysis process started during the late Holocene, only about 2 kyr B.P. at the studied site and about 5 kyr B.P. at the watershed outlet. The results of this study are applied to an assessment of the physical erosion rate (4.8x10(-3) m/kyr) since the recent reactivation of the erosion process. (C) 2010 Elsevier B.V. All rights reserved.

Effect of soil tillage on erosion and nutrient transport in plough layer runoff

Yhteenveto: Viljelymenetelmien vaikutus eroosioon ja ravinteiden huuhtoutumiseen

An application of a physically based SOIL model to the Bowen ratio data

Yhteenveto: Haihdunnan mittaamisesta ja mallintamisesta peltoalueella

Water content variations of sandy soil under winter conditions

Yhteenveto: Maankosteusvaihtelut talvella hiekkamaassa

Optimum Design for External Seismic Stability of Geosynthetic Reinforced Soil Walls: Reliability Based Approach

In this paper, an analytical study considering the effect of uncertainties in the seismic analysis of geosynthetic-reinforced soil (GRS) walls is presented. Using limit equilibrium method and assuming sliding wedge failure mechanism, analysis is conducted to evaluate the external stability of GRS walls when subjected to earthquake loads. Target reliability based approach is used to estimate the probability of failure in three modes of failure, viz., sliding, bearing, and eccentricity failure. The properties of reinforced backfill, retained backfill, foundation soil, and geosynthetic reinforcement are treated as random variables. In addition, the uncertainties associated with horizontal seismic acceleration and surcharge load acting on the wall are considered. The optimum length of reinforcement needed to maintain the stability against three modes of failure by targeting various component and system reliability indices is obtained. Studies have also been made to study the influence of various parameters on the seismic stability in three failure modes. The results are compared with those given by first-order second moment method and Monte Carlo simulation methods. In the illustrative example, external stability of the two walls, Gould and Valencia walls, subjected to Northridge earthquake is reexamined.

Optimum Design for External Seismic Stability of Geosynthetic Reinforced Soil Walls: Reliability Based Approach

In this paper, an analytical study considering the effect of uncertainties in the seismic analysis of geosynthetic-reinforced soil (GRS) walls is presented. Using limit equilibrium method and assuming sliding wedge failure mechanism, analysis is conducted to evaluate the external stability of GRS walls when subjected to earthquake loads. Target reliability based approach is used to estimate the probability of failure in three modes of failure, viz., sliding, bearing, and eccentricity failure. The properties of reinforced backfill, retained backfill, foundation soil, and geosynthetic reinforcement are treated as random variables. In addition, the uncertainties associated with horizontal seismic acceleration and surcharge load acting on the wall are considered. The optimum length of reinforcement needed to maintain the stability against three modes of failure by targeting various component and system reliability indices is obtained. Studies have also been made to study the influence of various parameters on the seismic stability in three failure modes. The results are compared with those given by first-order second moment method and Monte Carlo simulation methods. In the illustrative example, external stability of the two walls, Gould and Valencia walls, subjected to Northridge earthquake is reexamined.

Probabilistic evaluation of seismic soil liquefaction potential based on SPT data

The performance-based liquefaction potential analysis was carried out in the present study to estimate the liquefaction return period for Bangalore, India, through a probabilistic approach. In this approach, the entire range of peak ground acceleration (PGA) and earthquake magnitudes was used in the evaluation of liquefaction return period. The seismic hazard analysis for the study area was done using probabilistic approach to evaluate the peak horizontal acceleration at bed rock level. Based on the results of the multichannel analysis of surface wave, it was found that the study area belonged to site class D. The PGA values for the study area were evaluated for site class D by considering the local site effects. The soil resistance for the study area was characterized using the standard penetration test (SPT) values obtained from 450 boreholes. These SPT data along with the PGA values obtained from the probabilistic seismic hazard analysis were used to evaluate the liquefaction return period for the study area. The contour plot showing the spatial variation of factor of safety against liquefaction and the corrected SPT values required for preventing liquefaction for a return period of 475 years at depths of 3 and 6 m are presented in this paper. The entire process of liquefaction potential evaluation, starting from collection of earthquake data, identifying the seismic sources, evaluation of seismic hazard and the assessment of liquefaction return period were carried out, and the entire analysis was done based on the probabilistic approach.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Prediction of swelling pressure of soil using artificial intelligence techniques

The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg's limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.

Surface freshwater from Bay of Bengal runoff and Indonesian Throughflow in the Tropical Indian Ocean

According to recent estimates, the annual total continental runoff into the Bay of Bengal (BoB) is about 2950 km 3, which is more than half that into the entire tropical Indian Ocean (IO). Here we use climatological observations to trace the seasonal pathways of near surface freshwater from BoB runoff and Indonesian Throughflow (ITF) by removing the net contribution from precipitation minus evaporation. North of 20 degrees S, the amount of freshwater from BoB runoff and ITF changes with season in a manner consistent with surface currents from drifters. BoB runoff reaches remote regions of the Arabian Sea; it also crosses the equator in the east to join the ITF. This freshwater subsequently flows west across the southern tropical IO in the South Equatorial Current.