Towards an ecological index for tropical soil quality based on soil macrofauna

The objective of this work was to construct a simple index based on the presence/absence of different groups of soil macrofauna to determine the ecological quality of soils. The index was tested with data from 20 sites in South and Central Tabasco, Mexico, and a positive relation between the model and the field observations was detected. The index showed that diverse agroforestry systems had the highest soil quality index (1.00), and monocrops without trees, such as pineapple, showed the lowest soil quality index (0.08). Further research is required to improve this model for natural systems that have very low earthworm biomass (<10 g m-2) and a high number of earthworm species (5-7), as it is in the tropical rain forest, whose soil quality index was medium (0.5). The application of this index will require an illustrated guide for its users. Further studies are required in order to test the use of this index by farmers.

Tropical terrestrial model ecosystems for evaluation of soil fauna and leaf litter quality effects on litter consumption, soil microbial biomass and plant growth

The aim of this work was to evaluate whether terrestrial model ecosystems (TMEs) are a useful tool for the study of the effects of litter quality, soil invertebrates and mineral fertilizer on litter decomposition and plant growth under controlled conditions in the tropics. Forty-eight intact soil cores (17.5-cm diameter, 30-cm length) were taken out from an abandoned rubber plantation on Ferralsol soil (Latossolo Amarelo) in Central Amazonia, Brazil, and kept at 28ºC in the laboratory during four months. Leaf litter of either Hevea pauciflora (rubber tree), Flemingia macrophylla (a shrubby legume) or Brachiaria decumbens (a pasture grass) was put on top of each TME. Five specimens of either Pontoscolex corethrurus or Eisenia fetida (earthworms), Porcellionides pruinosus or Circoniscus ornatus (woodlice), and Trigoniulus corallinus (millipedes) were then added to the TMEs. Leaf litter type significantly affected litter consumption, soil microbial biomass and nitrate concentration in the leachate of all TMEs, but had no measurable effect on the shoot biomass of rice seedlings planted in top soil taken from the TMEs. Feeding rates measured with bait lamina were significantly higher in TMEs with the earthworm P. corethrurus and the woodlouse C. ornatus. TMEs are an appropriate tool to assess trophic interactions in tropical soil ecossistems under controlled laboratory conditions.

Seed priming and sulfur effects on soybean cell membrane stability and yield in saline soil

The objective of this work was to determine the effects of seed priming and sulfur application on cell membrane characteristics, seedling emergence, chlorophyll content and grain yield of soybean (Glycine max) in saline soil. A complete-block design in 4x3 factorial arrangement with three replicates was used to test four types of seed priming (water, auxin, gibberellin and non-priming) and three levels of sulfate availability (0, 70 and 140 kg ha-1 K2SO4). The soil had a silty loam texture with an electrical conductivity of 3.61 ds m-1, a pH of 8.2 and a saturation percentage of about 46%. Seed priming had significant effects on mean emergence rate (MER), emergence percentage, relative water content (RWC) of leaves, relative chlorophyll content, time of maturity, shoot length and grain yield. The highest values for these variables were observed in the priming treatments, except for the time of maturity. Sulfur application had significant effects on MER, shoot length, RWC, membrane injury index and grain yield. Priming treatments provide greater emergence rates and grain yields and interact sinergicaly with sulfur rates.

Averting risk in the face of large losses: Bernoulli vs. Tversky and Kahneman

We experimentally question the assertion of Prospect Theory that people display risk attraction in choices involving high-probability losses. Indeed, our experimental participants tend to avoid fair risks for large (up to ? 90), high-probability (80%) losses. Our research hinges on a novel experimental method designed to alleviate the house-money bias that pervades experiments with real (not hypothetical) loses.Our results vindicate Daniel Bernoulli?s view that risk aversion is the dominant attitude,But, contrary to the Bernoulli-inspired canonical expected utility theory, we do find frequent risk attraction for small amounts of money at stake.In any event, we attempt neither to test expected utility versus nonexpected utility theories, nor to contribute to the important literature that estimates value and weighting functions. The question that we ask is more basic, namely: do people display risk aversion when facing large losses, or large gains? And, at the risk of oversimplifying, our answer is yes.

Health consultation : Tails A Waggin' Pet Resort -- arsenic soil contamination, 210 41st Avenue Drive SW, Cedar Rapids, Linn County, Iowa (2006)

The Iowa Department of Natural Resources (IDNR) requested the Iowa Department of Public Health (IDPH) Hazardous Waste Site Health Assessment Program to evaluate the health impacts of exposure to soil contaminated with heavy metals at a commercial property located in Cedar Rapids, Iowa. The specific request was to evaluate the health impacts from exposure to contaminants that were above IDNR statewide standards. This health consultation addresses potential health risks to people from exposure to the soil within the property. The information in this health consultation was current at the time of writing. Data that emerges later could alter this document’s conclusions and recommendations.

Health consultation : Pesticide contamination of residential soil, Des Moines, Polk County, Iowa (2005)

The Iowa Department of Natural Resources (IDNR) has requested the Iowa Department of Public Health (IDPH) Hazardous Waste Site Health Assessment Program to evaluate the health impacts of exposures to residential soil contaminated with pesticides. The residence is located in Des Moines, Iowa. This health consultation addresses potential health risks to people from exposure to the soil within the property. The information in this health consultation was current at the time of writing. Data that emerges later could alter this document’s conclusions and recommendations.

Leaf plasticity in successive selection cycles of 'Saracura' maize in response to periodic soil flooding

The objective of this work was to assess the effect of successive selection cycles on leaf plasticity of 'Saracura' maize BRS-4154 under periodical flooding in field conditions. Soil flooding started at the six-leaf stage with the application of a 20-cm depth water layer three times a week. At flowering, samples of leaves were collected and fixed. Paradermic and transverse sections were observed under photonic microscope. Several changes were observed throughout the selection cycles, such as modifications in the number and size of the stomata, higher amount of vascular bundles and the resulting decrease of the distance between them, smaller diameter of the metaxylem, decrease of cuticle and epidermis thickness, decrease of number and size of bulliform cells, increase of phloem thickness, smaller sclerenchyma area. Therefore, the successive selection cycles of 'Saracura' maize resulted in changes in the leaf anatomy, which might be favorable to the plant's tolerance to the intermittent flooding of the soil.

1199-000 Soil Nutrient Mass Balance Study

Key Points: • Iowa’s exceptional agricultural productivity is dependent upon nutrient‐rich soils with high carbon and nitrogen stocks. • Soil carbon and nitrogen stocks in Iowa corn‐soybean rotations are at significant risk of long‐term decline. • Soil carbon and nitrogen stocks are a function of crop residue inputs. • Nutrient input levels that do not maximize crop yield and residue production are likely to reduce soil carbon and nitrogen stocks. • If soil carbon and nitrogen stocks decline, water quality improvements become more difficult. • Soil carbon and nitrogen balances are extremely difficult to measure, but positive balances are essential to the future of Iowa agriculture. Recommended Actions: • Accurate measurement of soil carbon and nitrogen balances is exceptionally difficult, but can be accomplished with sufficient investment and long‐term planning. • The ideal approach will include a combination of measurements from farms and experimental networks that manipulate nutrient inputs. • With proper planning and cooperation, Iowa State University and the Iowa Department of Agriculture and Land Stewardship can address the concerns raised in this report regarding the future of Iowa’s soil resource and agricultural productivity.

Development of Sclerotium rolfsii sclerotia on soybean, corn, and wheat straw, under different soil temperatures and moisture contents

The objective of this work was to evaluate the effect of moisture and temperature on the development of Sclerotium rolfsii on soybean, corn, and wheat straw. Wheat straw produced the lowest number of sclerotia. Intermediate soil moisture level (70% of field capacity), and temperatures ranging between 25-30ºC favored sclerotia development. No sclerotia were formed at temperatures between 30-35ºC, on any type of straw.

Soil carbon and nitrogen mineralization caused by pig slurry application under different soil tillage systems

The objective of this work was to evaluate the change in soil C and N mineralization due to successive pig slurry application under conventional tillage (CT) and no tillage (NT) systems. The experiment was carried out in a clayey Latossolo Vermelho eutrófico (Rhodic Eutrudox) in Palotina, PR, Brazil. Increasing doses of pig slurry (0, 30, 60 and 120 m³ ha-1 per year) were applied in both tillage systems, with three replicates. Half of the pig slurry was applied before summer soil preparation, and the other half before the winter crop season. The areas were cultivated with soybean (Glycine max L.) and maize (Zea mays L.) in the summers of 1998 and 1999, respectively, and with wheat (Triticum sativum Lam.) in the winters of both years. Soil samples were collected at 0-5, 5-10, and 10-20 cm depths. Under both CT and NT systems, pig slurry application increased C and N mineralization. However, increasing pig slurry additions decreased the C to N mineralization ratio. Under the NT system, C and N mineralization was greater than in CT system.

Analysis of sensitivity with respect to a compositional parameter : A comment on 'Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling' by L. Loosvelt and co-authors

A comment about the article “Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling” writen by L. Loosvelt and co-authors. The present comment is centered in three specific points. The first one is related to the fact that the authors avoid the use of ilr-coordinates. The second one refers to some generalization of sensitivity analysis when input parameters are compositional. The third tries to show that the role of the Dirichlet distribution in the sensitivity analysis is irrelevant

Leaf mineral composition of grafted eggplant grown in soil infested with Verticillium and root-knot nematodes

The objective of this work was to determine differences in leaf mineral composition between ungrafted and grafted onto (Solanum torvum) eggplant (Solanum melongena), cultivars 'Faselis' and 'Pala', grown in a soil infested with Verticillium dahliae and Meloidogyne incognita, or in a noninfested soil. Grafting increased leaf P and Mn concentrations, and decreased N concentrations, in both soils. Grafting also enhanced leaf Ca concentration of 'Pala', but it did not affect that of 'Faselis' depending on the cropping year. Leaf Mg concentration of grafted plants in infested soil was lower than that of ungrafted ones in noninfested soil. Results showed that, under the same fertilization program, the grafted 'Faselis' plants used the nutrients more efficiently than the 'Pala' ones. Use of S. torvum as a rootstock for 'Faselis' resulted in an effective protection against multiple pathogen infestation. Fertilization may be necessary when grafted 'Faselis' plants are grown in a soil infested with the pathogens, since grafting and infestation generally decrease leaf N, Mg, Ca and Fe concentrations, either by reducing the nutrient concentrations directly or by increasing leaf Mn concentration.

On the diurnal soil water content dynamics during evaporation using dielectric methods

The water content dynamics in the upper soil surface during evaporation is a key element in land-atmosphere exchanges. Previous experimental studies have suggested that the soil water content increases at the depth of 5 to 15 cm below the soil surface during evapo- ration, while the layer in the immediate vicinity of the soil surface is drying. In this study, the dynamics of water content profiles exposed to solar radiative forcing was monitored at a high temporal resolution using dielectric methods both in the presence and absence of evaporation. A 4-d comparison of reported moisture content in coarse sand in covered and uncovered buckets using a commercial dielectric-based probe (70 MHz ECH2O-5TE, Decagon Devices, Pullman, WA) and the standard 1-GHz time domain reflectometry method. Both sensors reported a positive correlation between temperature and water content in the 5- to 10-cm depth, most pronounced in the morning during heating and in the afternoon during cooling. Such positive correlation might have a physical origin induced by evaporation at the surface and redistribution due to liquid water fluxes resulting from the temperature- gradient dynamics within the sand profile at those depths. Our experimental data suggest that the combined effect of surface evaporation and temperature-gradient dynamics should be considered to analyze experimental soil water profiles. Additional effects related to the frequency of operation and to protocols for temperature compensation of the dielectric sensors may also affect the probes' response during large temperature changes.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.