Determination Of Soil Properties Research Articles

Field testing of rocking foundations in cohesive soil: cyclic performance and footing mechanical response

This paper presents a field test program of a large-scale soil–footing-structure system designed with a rocking foundation in a cohesive soil to examine the behaviour of the system and to provide case histories for possible performance-based seismic design of foundations. The rocking system was subjected to slow cyclic loadings at various drift ratios up to 7%. Twenty-four tests were conducted for foundations with varying initial factors of safety against the bearing failure, loading directions, rotation amplitudes, and embedment. A geotechnical investigation was carried out to determine soil properties before and after the experiments. The system performance indices, such as damping, stiffness, settlement, and re-centering capability, were quantified and compared with the published literature. Field test results showed that the strength and unit weight of soils at footing edges were increased due to rocking, for the present cohesive soil. The rocking moment capacity increased slightly with the increasing soil strength. An empirical equation for the secant stiffness was developed. The rocking system on the cohesive soil exhibited superior performance in terms of small residual settlement and large re-centering capability. Footing’s mechanical response was quantified using strain gauge readings. The footing remained elastic in tension; the transient soil–footing contact areas were estimated with strain gauges, and they agreed very well with the measured or calculated contact areas.

Bacterial and archaeal spatial distribution and its environmental drivers in an extremely haloalkaline soil at the landscape scale.

BackgroundA great number of studies have shown that the distribution of microorganisms in the soil is not random, but that their abundance changes along environmental gradients (spatial patterns). The present study examined the spatial variability of the physicochemical characteristics of an extreme alkaline saline soil and how they controlled the archaeal and bacterial communities so as to determine the main spatial community drivers.MethodsThe archaeal and bacterial community structure, and soil characteristics were determined at 13 points along a 211 m transect in the former lake Texcoco. Geostatistical techniques were used to describe spatial patterns of the microbial community and soil characteristics and determine soil properties that defined the prokaryotic community structure.ResultsA high variability in electrolytic conductivity (EC) and water content (WC) was found. Euryarchaeota dominated Archaea, except when the EC was low. Proteobacteria, Bacteroidetes and Actinobacteria were the dominant bacterial phyla independent of large variations in certain soil characteristics. Multivariate analysis showed that soil WC affected the archaeal community structure and a geostatistical analysis found that variation in the relative abundance of Euryarchaeota was controlled by EC. The bacterial alpha diversity was less controlled by soil characteristics at the scale of this study than the archaeal alpha diversity.DiscussionResults indicated that WC and EC played a major role in driving the microbial communities distribution and scale and sampling strategies were important to define spatial patterns.

The steps in the soil nitrogen transformation process vary along an aridity gradient via changes in the microbial community

Rainfall patterns are predicted to change dramatically in many terrestrial landscapes, including drylands. The most limiting resources for plant growth in arid regions is nitrogen (N) as well as water. A natural aridity gradient provides appropriate candidate conditions for predicting the impacts of changes in rainfall on soil N dynamics. To comprehensively and mechanistically examine soil N dynamics, we focused on the steps of N transformation, their microbial drivers, and the determining soil properties. We divided the N transformation process into three steps: (i) organic matter degradation, (ii) N mineralization, and (iii) nitrification, which are driven primarily by fungi, prokaryotes, and ammonia oxidizers, respectively. Soil samples were collected from three black locust forests with mean annual precipitations ranging from 449 to 606 mm. Along the aridity gradient, all three steps changed while maintaining a balance. The degradation and mineralization steps varied with changes in the soil fungal and prokaryotic communities, respectively. The compositions of these communities were determined by soil substrate quality and quantity; saprotrophs and copiotrophs decreased along the aridity gradient. On the other hand, the abundance of ammonia-oxidizing bacteria, which correlated with the rate of nitrification, was likely determined by soil moisture. Therefore, if precipitation were to decrease, changes in the nitrification step might be the first mechanism to limit plant productivity in semi-arid forests. This limitation would extend to the other steps in the N cycling process via plant–soil feedback. Thus, N cycling dynamics are predicted to achieve new stable states suited to the changed precipitation regime.

Laboratory Visible and Near-Infrared Spectroscopy with Genetic Algorithm-Based Partial Least Squares Regression for Assessing the Soil Phosphorus Content of Upland and Lowland Rice Fields in Madagascar

As a laboratory proximal sensing technique, the capability of visible and near-infrared (Vis-NIR) diffused reflectance spectroscopy with partial least squares (PLS) regression to determine soil properties has previously been demonstrated. However, the evaluation of the soil phosphorus (P) content—a major nutrient constraint for crop production in the tropics—is still a challenging task. PLS regression with waveband selection can improve the predictive ability of a calibration model, and a genetic algorithm (GA) has been widely applied as a suitable method for selecting wavebands in laboratory calibrations. To develop a laboratory-based proximal sensing method, this study investigated the potential to use GA-PLS regression analyses to estimate oxalate-extractable P in upland and lowland soils from laboratory Vis-NIR reflectance data. In terms of predictive ability, GA-PLS regression was compared with iterative stepwise elimination PLS (ISE-PLS) regression and standard full-spectrum PLS (FS-PLS) regression using soil samples collected in 2015 and 2016 from the surface of upland and lowland rice fields in Madagascar (n = 103). Overall, the GA-PLS model using first derivative reflectance (FDR) had the best predictive accuracy (R2 = 0.796) with a good prediction ability (residual predictive deviation (RPD) = 2.211). Selected wavebands in the GA-PLS model did not perfectly match wavelengths of previously known absorption features of soil nutrients, but in most cases, the selected wavebands were within 20 nm of previously known wavelength regions. Bootstrap procedures (N = 10,000 times) using selected wavebands also confirmed the improvements in accuracy and robustness of the GA-PLS model compared to those of the ISE-PLS and FS-PLS models. These results suggest that soil oxalate-extractable P can be predicted from Vis-NIR spectroscopy and that GA-PLS regression has the advantage of tuning optimum bands for PLS regression, contributing to a better predictive ability.

Distribution patterns and controlling factors for the soil organic carbon in four mangrove forests of China

Although several studies have assessed soil organic carbon (SOC) of individual mangrove forests in China, no study has comprehensively investigated mangrove SOC and quantitatively estimated carbon sources ranging in latitude from tropical to subtropical latitudes. Therefore, this study explored the distribution patterns and factors controlling the deposition of SOC in four national mangroves nature reserves of southeastern China, specifically Yunxiao in Fujian Province, Gaoqiao in Guangdong Province, and Dongzhaigang and Wenchang in Hainan Province. Sediment core samples were collected and sectioned into subsamples to determine soil properties, including pH, salinity, moisture, bulk density, content and density of SOC, as well as carbon stable isotope ratios (δ13C). SOC contents varied with sampling sites and different mangrove communities, with 1.19 ± 0.06%, 2.52 ± 0.11%, 0.81 ± 0.101% and 4.78 ± 0.35% for Yunxiao, Gaoqiao, Dongzhaigang and Wenchang sites, respectively. Soil pH, salinity, and bulk density were negatively correlated with SOC contents at all four sites. The Yunxiao site had the highest SOC δ13C value (−25.2 ± 0.2‰), likely attributable to the severe invasion of Spartina alterniflora (a C4 plant with higher δ13C value than typical mangrove species). Significant negative correlations were also found between SOC and the δ13C values in three sites except Wenchang. Our results suggest that soil texture, dominant mangrove species and biological invasion had marked effects on SOC contents and distribution patterns of tropical and subtropical mangrove forests in China.

Nutrient status and their relationship with soil properties of dalo (Colocasia esculenta (L.) Schott) growing areas of Rewa district in Fiji

This study was conducted in dalo (Colocasia esculenta (L.) Schott) growing areas of Rewa district in Fiji to know nutrient status and their relationship with soil properties. Representative soil samples were collected to determine soil properties and nutrient status. The soils of the study area were found acidic in nature with the mean pH of 5.6. The electrical conductivity varied from 0.07-0.31 dSm-1with a mean 0.17 dSm-1. Organic carbon varied from 0.30 to 5.5 % with the mean value of 2.1%. Total nitrogen varied from 0.07-0.43 % with a mean of 0.19%. The values of available phosphorus (mg kg-1) varied from 1.0-44.0 mg kg-1 with a mean value 12.9 mg kg-1and that of potassium varied from 27.37-762.45 mg kg-1 with a mean of 169.56 mg kg-1. It was concluded that soils of the dalo growing areas of Rewa district are moderately acidic, having low electrical conductivity and are characterized as non-saline soils. Soils are high in organic carbon, medium in total nitrogen and low in available phosphorus and exchangeable potassium.

Nutrient status and their relationship with soil properties of dalo (Colocasia esculenta (L.) Schott) growing areas of Rewa district in Fiji

This study was conducted in dalo (Colocasia esculenta (L.) Schott) growing areas of Rewa district in Fiji to know nutrient status and their relationship with soil properties. Representative soil samples were collected to determine soil properties and nutrient status. The soils of the study area were found acidic in nature with the mean pH of 5.6. The electrical conductivity varied from 0.07-0.31 dSm-1with a mean 0.17 dSm-1. Organic carbon varied from 0.30 to 5.5 % with the mean value of 2.1%. Total nitrogen varied from 0.07-0.43 % with a mean of 0.19%. The values of available phosphorus (mg kg-1) varied from 1.0-44.0 mg kg-1 with a mean value 12.9 mg kg-1and that of potassium varied from 27.37-762.45 mg kg-1 with a mean of 169.56 mg kg-1. It was concluded that soils of the dalo growing areas of Rewa district are moderately acidic, having low electrical conductivity and are characterized as non-saline soils. Soils are high in organic carbon, medium in total nitrogen and low in available phosphorus and exchangeable potassium.

Shoot Nutrient Content and Nutrient Resorption of Leymus chinensis in Various Legume Mixtures

The objective was to determine soil properties, and shoot nutrients and nutrient resorption of typical Eurasian steppe species Leymus chinensis in various legume mixtures (legume abundance was 0, 25, 50, and 75%). Mixtures with 25 or 50% legume significantly increased soil moisture and soil [N, P] availabilities. Increasing legume abundance enhanced stem and total biomass of green L. chinensis shoots, further enhanced the proportion of stem biomass by 14–24% in senesced L. chinensis shoots. Legume mixtures, especially 50% legume, enhanced green and senesced organs N concentrations and N pools of L. chinensis. Similarly, mixtures with 25 or 50% legume enhanced P concentration and pool of senesced L. chinensis shoots, whereas both were decreased by 75% legume. As legume abundance increased, contribution ratios of stem to total N and P pools of senesced chinensis shoots increased from 25 to 32 and 25 to 33%, respectively. Mixtures, especially 25 or 50% legume, decreased N and P resorption efficiency (NRE) of L. chinensis shoots, whereas 75% legume increased PRE of L. chinensis. Total resorbed nutrients may remain stable under varying soil conditions for L. chinensis, and resorption of nutrients was symmetric between leaf and stem. In conclusion, legume abundance affected nutrient uptake and return of grass in mixed grasslands, but high legume abundance meant no low N resorption and high litter N content of grass. Furthermore, with increasing legume abundance, stems had more important roles in driving plant production, nutrient utilization, and nutrient return of L. chinensis.

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon.

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it regulates the gravity-driven soil movement induced by runoff and tillage activities. The recent application of Light Detection and Ranging (LiDAR) data holds promise for generating high spatial resolution topographic metrics that can be used to investigate soil property variability. In this study, fifteen topographic metrics derived from LiDAR data were used to investigate topographic impacts on redistribution of soil and spatial distribution of soil organic carbon (SOC). Specifically, we explored the use of topographic principal components (TPCs) for characterizing topography metrics and stepwise principal component regression (SPCR) to develop topography-based soil erosion and SOC models at site and watershed scales. Performance of SPCR models was evaluated against stepwise ordinary least square regression (SOLSR) models. Results showed that SPCR models outperformed SOLSR models in predicting soil redistribution rates and SOC density at different spatial scales. Use of TPCs removes potential collinearity between individual input variables, and dimensionality reduction by principal component analysis (PCA) diminishes the risk of overfitting the prediction models. This study proposes a new approach for modeling soil redistribution across various spatial scales. For one application, access to private lands is often limited, and the need to extrapolate findings from representative study sites to larger settings that include private lands can be important.

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Landscape topography is a critical factor affecting soil formation and plays an important role in determining soil properties on the earth surface, as it regulates the gravity-driven soil movement induced by runoff and tillage activities. The recent application of Light Detection and Ranging (LiDAR) data holds promise for generating high spatial resolution topographic metrics that can be used to investigate soil property variability. In this study, fifteen topographic metrics derived from LiDAR data were used to investigate topographic impacts on redistribution of soil and spatial distribution of soil organic carbon (SOC). Specifically, we explored the use of topographic principal components (TPCs) for characterizing topography metrics and stepwise principal component regression (SPCR) to develop topography-based soil erosion and SOC models at site and watershed scales. Performance of SPCR models was evaluated against stepwise ordinary least square regression (SOLSR) models. Results showed that SPCR models outperformed SOLSR models in predicting soil redistribution rates and SOC density at different spatial scales. Use of TPCs removes potential collinearity between individual input variables, and dimensionality reduction by principal component analysis (PCA) diminishes the risk of overfitting the prediction models. This study proposes a new approach for modeling soil redistribution across various spatial scales. For one application, access to private lands is often limited, and the need to extrapolate findings from representative study sites to larger settings that include private lands can be important.

Context-Dependency of Agricultural Legacies in Temperate Forest Soils

Anthropogenic activities have affected forests for centuries, leading to persistent legacies. Observations of agricultural legacies on forest soil properties have been site specific and contrasting. Sites and regions vary along gradients in intrinsic soil characteristics, phosphorus (P) management and nitrogen (N) deposition which could affect the magnitude of soil property responses to past cultivation. A single investigation along these gradients could reconcile contradictions and elucidate context-dependency in agricultural legacies. We analysed soil from 24 paired post-agricultural (established after approx. 1950) and ancient (in existence before 1850) forests in eight European regions. Post-agricultural forest soil had higher pH, higher P-concentration and lower carbon (C) to N ratio compared to ancient forest. Importantly, gradients of soil characteristics, regional P surplus and N deposition affected the magnitude of these legacies. First, we found that three soil groups, characterising inherent soil fertility, determined extractable base cations, pH and concentrations of total N, organic C and total P. Second, regions with greater current P surplus from agriculture correlated with the highest P legacy in post-agricultural forests. Finally, we found that N deposition lowered pH across forests and increased total N and organic C concentrations in post-agricultural forest. These results suggest that (1) legacies from cultivation consistently determine soil properties in post-agricultural forest and (2) these legacies depend on regional and environmental context, including soil characteristics, regional P surplus and N deposition. Identifying gradients that influence the magnitude of agricultural legacies is key to informing how, where and why forest ecosystems respond to contemporary environmental change.

Soil fertility assessment by Vis-NIR spectroscopy: Predicting soil functioning rather than availability indices

Soil fertility is typically assessed by chemical analysis, which is expensive and time-consuming, and hence impractical for site-specific fertilizer management. Visible and near infrared (Vis–NIR) spectroscopy has been used for determining soil properties and chemically extractable plant nutrients. However, the suitability of Vis–NIR for accurate assessment of nutrient availability to plants has not yet been fully explored. In this work, we examined the accuracy of this technique as a new nutrient availability index, and in the case of P as a proxy for plant-available P. To this end, total plant-available P in soil was quantified in a P-depletion experiment with crops, and the availability of Ca, Mg, K, and Fe was assessed by chemical extraction.Vis–NIR spectroscopy allowed us to accurately estimate plant-available P, which depends not only on soil factors but also on the crop performance to take up P. Vis–NIR spectroscopy proved effective in identifying P, Ca, Mg, K, and Fe responsive sites. Precise estimation of plant-available P was a result of accurately predicting soil properties governing P availability to plants by Vis–NIR spectroscopy. In addition, this technique provided accurate predictions of soil properties influencing the dynamics of applied P and K fertilizer, which can be useful to adapt fertilization practices to soil properties. Vis–NIR spectroscopy can therefore enable a qualitative leap to cost-effective integral assessment of soil fertility by providing accurate predictions of soil functioning rather than mere estimates of availability indices, thereby facilitating more sustainable use of resources in agriculture.

Potential Production of CH4 And N2O in Soil Profiles from Organic and Conventional Rice Fields

The horizons in soil profile will determine the magnitude of greenhouse gas production due to the difference of total organic carbon and other chemical properties. This study aimed to determine the potential production of methane (CH<sub>4</sub>) and nitrous oxide (N<sub>2</sub>O) in each horizon of soil profile from organic and conventional rice fields. Soil samples which were taken from Imogiri Bantul D.I. Yogyakarta were used to determine soil properties, the potential of CH<sub>4</sub>, and N<sub>2</sub>O productions. The correlation analysis was used to determine the relationship between the production of CH<sub>4</sub> and N<sub>2</sub>O with soil properties. The results showed that production of CH<sub>4</sub> and N<sub>2</sub>O will be decreased with the increase of soil depth. Production of CH<sub>4</sub> and N<sub>2</sub>O was higher in organic rice field than in conventional rice field. The total organic carbon (TOC) correlated positively with CH<sub>4</sub>-production (<em>r=0</em><em>.89, P<0.001, n=8</em>) and N<sub>2</sub>O-production (<em>r=0</em><em>.87, P<0.001, n=8</em>). The nitrogen content also correlated positively with CH<sub>4</sub>-production (<em>r=0</em><em>.87, P<0.001, n=8</em>) and N<sub>2</sub>O-production (r=0.94, P<0.001, n=8). Mitigation of CH<sub>4</sub> and N<sub>2</sub>O emissions should consider of C and N in the soil.

Evaluation of Undrained Shear Strength of Clay Using the CPTU Pore Pressure Method

Difficulties in obtaining high-quality undisturbed soil samples have necessitated the increased use of cone penetration test (CPT) or piezocone penetration test (CPTU) to determine soil properties at geotechnical engineering sites. Undrained shear strength (a key parameter for most clay investigations) traditionally is evaluated by cone tip resistance or effective cone tip resistance. In this paper a method of using the clay's excess pore pressure was used to estimate the undrained shear strength. A correlation of pore pressure ratio and cone factor was discovered and compared with results from the published literature and with those from field vane tests.

Comparison of aboveground vegetation and soil seed bank composition at sites of different grazing intensity around a savanna-woodland watering point in West Africa.

Grazing removes a plant's aboveground vegetative and reproductive tissues and can modify the soil seed bank, potentially impacting the restoration of preferred species. Knowledge about aboveground vegetation and species composition of soil seed bank and the processes that contribute to vegetation recovery on and surrounding watering points subjected to grazing is lacking. Successful restoration strategies hinge on addressing these knowledge gaps. We assessed the effects of livestock grazing on aboveground vegetation and soil seed bank characteristics along a river bank and surrounding areas subject to different grazing intensities and draw implications for restoration. Plots (50 × 50m) were established along five transects representing differing levels of grazing intensity. Soil samples were taken from three layers within each plot to determine soil properties and species composition of soil seed bank using the seedling emergence method. Heavy grazing resulted in the disappearance of perennial grasses, a reduction in species diversity and a decrease in soil nutrients with increased soil depth. Overall, the similarity between the extant aboveground vegetation and flora within the soil seed bank was low. The soil seed bank was dominated by herbaceous species and two woody species, suggesting that many woody species are not accumulating in the soil. With increasing soil depth, the seed density and richness declined. Canonical correspondence analyses (CCAs) showed that emerged seedlings from the soil seed bank were significantly influenced by soil carbon, organic matter, total nitrogen, total potassium and soil cation exchange capacity. This finding suggests that current grazing practices have a negative impact on the vegetation surrounding watering points; hence there is a need for improved grazing management strategies and vegetation restoration in these areas. The soil seed bank alone cannot restore degraded river banks; active transfer of propagules from adjacent undisturbed forest areas is essential.

EFFECT OF COVER CROPS ON SOIL ATTRIBUTES, PLANT NUTRITION, AND IRRIGATED TROPICAL RICE YIELD

ABSTRACT In flood plains, cover crops are able to alter soil properties and significantly affect rice nutrition and yield. The aims of this study were to determine soil properties, plant nutrition, and yield of tropical rice cultivated on flood plains after cover crop cultivation with conventional tillage (CT) and no-tillage system (NTS) at low and high nitrogen (N) fertilization levels. The experimental design was a randomized block in a split-split-plot scheme with four replications. In the main plots were cover crops [sunhemp (Crotalaria juncea and C. spectabilis), velvet bean (Mucuna aterrima), jackbean (Canavalia ensiformis), pigeon pea (Cajanus cajan), Japanese radish (Raphanus sativus), cowpea (Vigna unguiculata)] and a fallow field. In the subplots were the tillage systems (CT or NTS). The nitrogen fertilization levels in the sub-subplots were (10 kg N ha-1 and 45 kg N ha-1). All cover crops except Japanese radish significantly increased mineral soil nitrogen and nitrate concentrations. Sunhemp, velvet bean, and cowpea significantly increased soil ammonium content. The NTS provides higher mineral nitrogen and ammonium content than that by CT. Overall, cover crops provided higher levels of nutrients to rice plants in NTS than in CT. Cover crops provide greater yield than fallow treatments. Rice yield was higher in NTS than in CT, and greater at a higher rather than lower nitrogen fertilization level.

Effects of land use and cover type on the risks of runoff and water erosion: infiltration tests in the Ourika watershed (High Atlas, Morocco)

The upstream section of the Ourika watershed is located in the northwest slopes of the High Atlas Mountains of Morocco. It is characterized by rugged topography and sparse vegetation, and is under increasing human-induced pressures, exacerbated by climate variability and change. Its vulnerability to water erosion is high and, thus, wadi flows with significant solid loads are a constant risk. Infiltration measures through rain simulations, using a simple irrigator ramp, were carried out as part of an investigation to highlight the role of vegetation cover in mitigating soil erosion in the watershed. The methodology assessed the effect of land use and cover type on the soil surface state and properties on 1-m2 plots. Seventeen experimental sites were considered with reference to both land use and plant cover, with three test plots per site, making it a total of 51 test plots for the rainfall simulations. Soil samples were collected at different depths from each site to determine soil properties. Results obtained show that dense forests protect the soil, produce organic matter improving soil aggregation, and hence ensuring adequate infiltration. In woodlands, bare soil is susceptible to crusting, runoff, and water erosion. In overgrazed scrublands, soil compaction due to animal trampling, induces significant runoff. Croplands are poor in organic matter and are consequently very susceptible to crusting, losing infiltration capability. Infiltration was positively correlated with initial abstraction (R = 0.71), covered and non-crusted soil surfaces (R = 0.84 and R = 0.83, respectively), organic matter content (R = 0.62) and aggregate soil stability (R = 0.69). By contrast, it was negatively correlated with soil detachability (R = − 0.65), penetration resistance (R = − 0.81), and shear strength (R = − 0.64). However, a weak correlation between infiltration and either of bulk density, total porosity, or texture was observed. Findings showed that total infiltration was not correlated with the physical parameters of the soil but rather with the surface state of soils. Covered surface greatly decreased runoff and soil erosion by increasing the surface roughness and decreasing the runoff velocity in the study zone.

Spatial variation of soil macrofauna and nutrients in tropical agricultural systems influenced by historical charcoal production in South Nandi, Kenya

The charcoal sector constitutes an important source of employment and revenue for many tropical agroecosystems. Better understanding of the effects of charcoal-making is thus warranted to guide actions aimed at minimising environmental externalities. Conversion of trees to charcoal eliminates canopy effects associated with the living trees while at the same time creates new conditions in and around spots where the charcoal is produced due to increased concentration of pyrogenic organic matter (PyOM). It is unclear, whether such unintentional PyOM additions play a role in the abundance and distribution patterns of soil macrofauna. A study was conducted in South Nandi (Kenya) to assess effects of PyOM on soil macrofauna, taking advantage of abandoned traditional earth-mound charcoal kilns, where Croton megalocarpus Hutch. and Zanthoxylum gilletii (De Wild.) P.G.Waterman trees were used in charcoal making. Soil and soil macrofauna samples were collected at increasing distances from the centre of the spots. Total C, non-pyrogenic C (non-PyC) and total N progressively increased with increasing distance from the centre of the spots, whereas soil pH, pyrogenic C (PyC), available P and exchangeable K decreased. The number of earthworms and centipedes in Z. gilletii spots (119 and 14 individuals m−2, respectively) was twice as high as in kilns where C. megalocarpus was used. Notably, while the number of earthworms in spots rich in Z. gilletii PyOM significantly increased with increasing distance from the centre of the spots, the opposite trend was observed for centipedes. In contrast, no significant differences in the spatial distribution of earthworms or centipedes were found in spots rich in C. megalocarpus PyOM. Furthermore, beetles, termites and crickets were significantly higher in C. megalocarpus than Z. gilletii spots, but sampling distance also had no significant influence. As hypothesised, source of PyOM played a major role in determining soil properties and macrofauna distribution patterns thus showing the value of abandoned charcoal-making spots in contributing to a mosaic of soil conditions that could ultimately affect soil productivity in tropical agricultural systems.

Load testing and settlement of shallow foundation on desert sands

Shallow foundation load tests were performed on desert sands. Previously, cone penetration tests (CPT) and pressuremeter tests (PMT) had been done at each location to determine soil properties. Settlements were calculated from CPT and PMT data using common empirical methods. CPT data were employed to predict settlement behaviours utilising methods proposed by Schmertmann in 1970, Schmertmann and co-workers in 1978, Meyerhof in 1974 and DeBeer in 1965. PMT results were used to predict settlement behaviours using the method offered by Menard in 1975. Standard penetration test N60-values were estimated from CPT results using an artificial neural network model developed by Tarawneh in 2016. It is concluded that the method proposed by Menard in 1975 is reliable, as it over-predicted by an average ratio of 1·27. When using CPT data for settlement estimates, the methods of both Meyerhof and DeBeer over-predicted by an average ratio of 2·84 and 1·96, respectively, and that of Schmertmann by a 2·38 average when using soil modulus Es = 2·5qc (it dropped to 1·19 when using Es = 5qc in the calculations).

Water erosion and soil properties patterns along selected rainfall events in cultivated and abandoned terraced fields under renaturalisation

Current cultivated soils (C) and soils under different age of agricultural abandonment and plant cover like forest (F), meadows (M) and scrubs (S) were surveyed at any high (H) or low (L) rainfall event generating runoff to record erosion and both dissolved and eroded carbon and nitrogen. This survey was conducted from January 2009 to April 2010 and was also addressed to determine soil properties such as surface temperature (ST), moisture (SM), bulk density (BD), shear strength (SS), pH, organic carbon (SOC), total nitrogen (NT), total phosphorus (PT), CO2 emission, glomalin (GRSP), and β-Glucosidase, Phosphatase and Protease activities. The overall data set allowed accomplishing with the objective of the research, seeking differences in soil properties according to the previous land use, land abandonment and repeated fire occurrence. ANOVA of repeated measures showed runoff variance statistically significant within soil uses at L rainfall (p<0.05). Eroded soil and eroded carbon varied significantly among soil environments (p<0.05) at both H and L rainfall. However, erosion rates were low when compared to other Spanish sites. Soils under meadows (M) showed higher SOC and GRSP, and higher enzyme activities, and were identified as important natural firebreaks, besides their susceptibility to sediment and nutrient depletion. Similarly, soils F and S, though repeatedly affected by fire, showed satisfactory soil properties. The poorest soil properties were found in cultivated soils (C) that increased their erosion rates by 838%, 733% and 188% with respect to F, S and M soils along the observed period. In general, soils with higher organic carbon content (M>S>F) showed proportionally lesser CO2 emission, indicating their tendency to act as carbon sink. The shallowness of the soil profiles, overgrazing and frequent fire occurrence were found to be soil ecosystems threatening elements in areas deserving special attention for the risk of irreversible degradation processes. Unpredictable and erratic fire occurrence all over the area also suggests environmental protection through prevention plans.