Effects of prescribed fire on surface soil in a Pinus pinaster plantation, northern Portugal

In order to decrease the risk of severe wildfire, prescribed fire has recently been adopted in Portugal and elsewhere in the Mediterranean as a major tool for reducing the fuel load instead of manual or mechanical removal of vegetation. There has been some research into its impact on soils in shrublands and grasslands, but to date little research has been conducted in forested areas in the region. As a result, the impact of prescribed fire on the physico-chemical soil characteristics of forest soils has been assumed to be minimal, but this has not been demonstrated. In this study, we present the results of a monitoring campaign of a detailed pre- and post-prescribed fire assessment of soil properties in a long-unburnt P. pinaster plantation, NW Portugal. The soil characteristics examined were pH, total porosity, bulk density, moisture content, organic matter content and litter/ash quantity. The results show that there was no significant impact on the measured soil properties, the only effect being confined to minor changes in the upper 1 cm of soil. We conclude that provided the fire is carried out according to strict guidelines in P. pinaster forest, a minimal impact on soil properties can be expected.

Impact of prescribed fire on the chemical properties of soil

Prescribed fire is a common forest management tool used in Portugal to reduce the fuel load availability and minimize the occurrence of wildfires. In addition, the use of this technique also causes an impact to ecosystems. In this presentation we propose to illustrate some results of our project in two forest sites, both located in Northwest Portugal, where the effect of prescribed fire on soil properties were recorded during a period of 6 months. Changes in soil moisture, organic matter, soil pH and iron, were examined by Principal Component Analysis multivariate statistics technique in order to determine impact of prescribed fire on these soil properties in these two different types of soils and determine the period of time that these forest soils need to recover to their pre-fire conditions, if they can indeed recover. Although the time allocated to this study does not allow for a widespread conclusion, the data analysis clearly indicates that the pH values are positively correlated with iron values at both sites. In addition, geomorphologic differences between both sampling sites, Gramelas and Anjos, are relevant as the soils’ properties considered have shown different performances in time. The use of prescribed fire produced a lower impact in soils originated from more amended bedrock and therefore with a ticker humus covering (Gramelas) than in more rocky soils with less litter covering (Anjos) after six months after the prescribed fire occurrence.

Effects of prescribed fire on surface soil in a Pinus pinaster plantation, northern Portugal

In order to decrease the risk of severe wildfire, prescribed fire has recently been adopted in Portugal and elsewhere in the Mediterranean as a major tool for reducing the fuel load instead of manual or mechanical removal of vegetation. There has been some research into its impact on soils in shrublands and grasslands, but to date little research has been conducted in forested areas in the region. As a result, the impact of prescribed fire on the physico-chemical soil characteristics of forest soils has been assumed to be minimal, but this has not been demonstrated. In this study, we present the results of a monitoring campaign of a detailed pre- and post-prescribed fire assessment of soil properties in a long-unburnt P. pinaster plantation, NW Portugal. The soil characteristics examined were pH, total porosity, bulk density, moisture content, organic matter content and litter/ash quantity. The results show that there was no significant impact on the measured soil properties, the only effect being confined to minor changes in the upper 1 cm of soil. We conclude that provided the fire is carried out according to strict guidelines in P. pinaster forest, a minimal impact on soil properties can be expected.

Soil CO2 efflux in central Amazonia: environmental and methodological effects

Soil respiration plays a significant role in the carbon cycle of Amazonian rainforests. Measurements of soil respiration have only been carried out in few places in the Amazon. This study investigated the effects of the method of ring insertion in the soil as well as of rainfall and spatial distribution on CO2 emission in the central Amazon region. The ring insertion effect increased the soil emission about 13-20% for sandy and loamy soils during the firsts 4-7 hours, respectively. After rainfall events below 2 mm, the soil respiration did not change, but for rainfall greater than 3 mm, after 2 hours there was a decrease in soil temperature and respiration of about 10-34% for the loamy and sand soils, with emissions returning to normal after around 15-18 hours. The size of the measurement areas and the spatial distribution of soil respiration were better estimated using the Shuttle Radar Topographic Mission (SRTM) data. The Campina reserve is a mosaic of bare soil, stunted heath forest-SHF and tall heath forest-THF. The estimated total average CO2 emissions from the area was 3.08±0.8 µmol CO2 m-2 s-1. The Cuieiras reserve is another mosaic of plateau, slope, Campinarana and riparian forests and the total average emission from the area was 3.82±0.76 µmol CO2 m-2 s-1. We also found that the main control factor of the soil respiration was soil temperature, with 90% explained by regression analysis. Automated soil respiration datasets are a good tool to improve the technique and increase the reliability of measurements to allow a better understanding of all possible factors driven by soil respiration processes.

Evaluación de la degradación del suelo en agroecosistemas del centro-sur de Córdoba mediante indicadores e índices. Assessment of soil degradation in agroecosystems of central-southern Córdoba by means of indicators and indices

Las actividades agropecuarias ejercen diferentes presiones sobre los recursos naturales. Esto ha llevado, en algunas áreas, a un deterioro del suelo que provoca un impacto sobre la sustentabilidad en los sistemas agropecuarios. Para evaluar la degradación del suelo se han propuesto listas de indicadores, sin embargo, se carece de una herramienta metodológica robusta, adaptada a las condiciones edafoclimáticas regionales. Además, existe una demanda de productores e instituciones interesados en orientar acciones para preservar el suelo. El objetivo de este proyecto es evaluar la degradación física, química y biológica de los suelos en agroecosistemas del centro-sur de Córdoba. Por ello se propone desarrollar una herramienta metodológica que consiste en un set de indicadores físicos, químicos y biológicos, con valores umbrales, integrados en índices de degradación, que asistan a los agentes tomadores de decisiones y productores, en la toma de decisiones respecto de la degradación del suelo. El área de trabajo será una región agrícola del centro-sur de Córdoba con más de 100 años de agricultura. La metodología comienza con la caracterización del uso del territorio y sistemas de manejo, su clasificación y la obtención de mapas base de usos y manejos, mediante sensores remotos y encuestas. Se seleccionarán sitios de muestreo mediante una metodología semi-dirigida usando un SIG, asegurando un mínimo de un punto de muestreo por unidad de mapeo. Se elegirán sitios de referencia lo más cercano a una condición natural. Los indicadores a evaluar surgen de listas propuestas en trabajos previos del grupo, seleccionados en base a criterios internacionales y a adecuados a suelos de la región. Se usarán indicadores núcleo y complementarios. Para la obtención de umbrales, se usarán por un lado valores provenientes de la bibliografía y por otro, umbrales generados a partir de la distribución estadística del indicador en suelos de referencia. Para estandarizar cada indicador se definirá una función de transformación. Luego serán ponderarán mediante análisis estadísticos mulivariados e integrados en índices de degradación física, química y biológica, y un índice general de degradación. El abordaje concluirá con el desarrollo de dos instrumentos para la toma de decisiones: uno a escala regional, que consistirá en mapas de degradación en base a unidades cartográficas ambientales, de uso del territorio y de sistemas de manejo y otro a escala predial que informará sobre la degradación del suelo de un lote en particular, en comparación con suelos de referencia. Los actores interesados contarán con herramientas robustas para la toma de decisiones respecto de la degradación del suelo tanto a escala regional como local. Agricultural activities exert different pressures on natural resources. In some areas this has led to soil degradation and has an impact on agricultural sustainability. To assess soil degradation a robust methodological tool, adapted to regional soil and climatic conditions, is lacking. In addition, there is a demand from farmers and institutions interested in direct actions to preserve the soil. The objective of this project is to assess physical, chemical and biological soil degradation in agroecosystems of Córdoba. We propose to develop a tool that consists of a set of physical, chemical and biological indicators, with threshold values, integrated in soil degradation indices. The study area is a region with more than 100 years of agriculture. The methodology begins with the characterization of land use and management systems and the obtaining of base maps by means of remote sensing and survey. Sampling sites will be selected through a semi-directed methodology using GIS, ensuring at least one sampling point by mapping unit. Reference sites will be chosen as close to a natural condition. The proposed indicators emerge from previous works of the group, selected based on international standards and appropriate for the local soils. To obtain the thresholds, we will use, by one side, values from the literature, and by the other, values generated from the statistical distribution of the indicator in the reference soils. To standardize indicators transformation functions will be defined. Indicators will be weighted by mans of multivariate analysis and integrated in soil degradation indices. The approach concluded with the development of two instruments for decision making: a regional scale one, consisting in degradation maps based on environmental, land use and management systems mapping units; and an instrument at a plot level which will report on soil degradation of a particular plot compared to reference soils.

Soil spectral library and its use in soil classification

Soil science has sought to develop better techniques for the classification of soils, one of which is the use of remote sensing applications. The use of ground sensors to obtain soil spectral data has enabled the characterization of these data and the advancement of techniques for the quantification of soil attributes. In order to do this, the creation of a soil spectral library is necessary. A spectral library should be representative of the variability of the soils in a region. The objective of this study was to create a spectral library of distinct soils from several agricultural regions of Brazil. Spectral data were collected (using a Fieldspec sensor, 350-2,500 nm) for the horizons of 223 soil profiles from the regions of Matão, Paraguaçu Paulista, Andradina, Ipaussu, Mirandópolis, Piracicaba, São Carlos, Araraquara, Guararapes, Valparaíso (SP); Naviraí, Maracajú, Rio Brilhante, Três Lagoas (MS); Goianésia (GO); and Uberaba and Lagoa da Prata (MG). A Principal Component Analysis (PCA) of the data was then performed and a graphic representation of the spectral curve was created for each profile. The reflectance intensity of the curves was principally influenced by the levels of Fe2O3, clay, organic matter and the presence of opaque minerals. There was no change in the spectral curves in the horizons of the Latossolos, Nitossolos, and Neossolos Quartzarênicos. Argissolos had superficial horizon curves with the greatest intensity of reflection above 2,200 nm. Cambissolos and Neossolos Litólicos had curves with greater reflectance intensity in poorly developed horizons. Gleisols showed a convex curve in the region of 350-400 nm. The PCA was able to separate different data collection areas according to the region of source material. Principal component one (PC1) was correlated with the intensity of reflectance samples and PC2 with the slope between the visible and infrared samples. The use of the Spectral Library as an indicator of possible soil classes proved to be an important tool in profile classification.

Portable penetrometer for agricultural soil: sensitivity test to identify critical compaction depth

To express the negative effects of soil compaction, some researchers use critical values for soil mechanical strength that severely impair plant growth. The aim of this study was to identify this critical compaction depth, to test the functionality of a new, portable penetrometer developed from a spring dynamometer, and compare it to an electronic penetrometer traditionally used in compaction studies of agricultural soils. Three soils with distinct texture were conventionally tilled using a disk plow, and cultivated with different plant species. The critical soil resistance defined to establish critical compaction depth was equal to 1.5 MPa. The results of the new equipment were similar to the electronic penetrometer, indicating its viability as a tool for assessing the soil physical conditions for plant growth.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.

Three-dimensional interpolation of soil data: fertility and pedomorphological features in southern Brazil

The graphical representation of spatial soil properties in a digital environment is complex because it requires a conversion of data collected in a discrete form onto a continuous surface. The objective of this study was to apply three-dimension techniques of interpolation and visualization on soil texture and fertility properties and establish relationships with pedogenetic factors and processes in a slope area. The GRASS Geographic Information System was used to generate three-dimensional models and ParaView software to visualize soil volumes. Samples of the A, AB, BA, and B horizons were collected in a regular 122-point grid in an area of 13 ha, in Pinhais, PR, in southern Brazil. Geoprocessing and graphic computing techniques were effective in identifying and delimiting soil volumes of distinct ranges of fertility properties confined within the soil matrix. Both three-dimensional interpolation and the visualization tool facilitated interpretation in a continuous space (volumes) of the cause-effect relationships between soil texture and fertility properties and pedological factors and processes, such as higher clay contents following the drainage lines of the area. The flattest part with more weathered soils (Oxisols) had the highest pH values and lower Al3+ concentrations. These techniques of data interpolation and visualization have great potential for use in diverse areas of soil science, such as identification of soil volumes occurring side-by-side but that exhibit different physical, chemical, and mineralogical conditions for plant root growth, and monitoring of plumes of organic and inorganic pollutants in soils and sediments, among other applications. The methodological details for interpolation and a three-dimensional view of soil data are presented here.

NITROGEN LOSS BY EROSION FROM MECHANICALLY TILLED AND UNTILLED SOIL UNDER SUCCESSIVE SIMULATED RAINFALLS

The description of the fate of fertilizer-derived nitrogen (N) in agricultural systems is an essential tool to enhance management practices that maximize nutrient use by crops and minimize losses. Soil erosion causes loss of nutrients such as N, causing negative effects on surface and ground water quality, aside from losses in agricultural productivity by soil depletion. Studies correlating the percentage of fertilizer-derived N (FDN) with soil erosion rates and the factors involved in this process are scarce. The losses of soil and fertilizer-derived N by water erosion in soil under conventional tillage and no tillage under different rainfall intensities were quantified, identifying the intervening factors that increase loss. The experiment was carried out on plots (3.5 × 11 m) with two treatments and three replications, under simulated rainfall. The treatments consisted of soil with and soil without tillage. Three successive rainfalls were applied in intervals of 24 h, at intensities of 30 mm/h, 30 mm/h and 70 mm/h. The applied N fertilizer was isotopically labeled (15N) and incorporated into the soil in a line perpendicular to the plot length. Tillage absence resulted in higher soil losses and higher total nitrogen losses (TN) by erosion induced by the rainfalls. The FDN losses followed another pattern, since FDN contributions were highest from tilled plots, even when soil and TN losses were lowest, i.e., the smaller the amount of eroded sediment, the greater the percentage of FDN associated with these. Rain intensity did not affect the FDN loss, and losses were greatest after less intense rainfalls in both treatments.

Simultaneous determination of Pu and Am radioisotopes in environmental samples: a tool for determining origin and release date

A radiochemical procedure was developed for the sequential determination of Pu and Am radioisotopes in environmental samples. The radioisotope activities were then used to assess the origin and release date of the environmental plutonium. The radioanalytical procedure is based on the separation of Pu and Am on selective extraction chromatographic resins (Eichrom TEVA and DGA). Alpha sources were prepared by electrodeposition on stainless steel discs, and the alpha emitting radionuclides (238Pu, 239,240Pu and 241Am) were measured by alpha spectrometry. For the determination of the beta emitting 241Pu, the Pu alpha source was leached in hot concentrated nitric acid and the Pu fraction further purified by extraction chromatography on a small column of TEVA resin (100 μg of resin in a pipette tip). 241Pu is then measured by ultra low level liquid scintillation counting. Due to the lack of reference material for 241Pu, the proposed radiochemical method was nevertheless validated using four IAEA reference sediments with information values of 241Pu. The proposed method was then used to determine the 238Pu, 239,240Pu, 241Pu and 241Am activity concentrations in alpine soils of France and Switzerland. The soil is the primary receptor of the atmospheric radioactive fallout and, because of the strong binding interaction with soils particles, the isotopes are little fractionated. Therefore, the activity ratios 241Pu/239+240Pu and 238Pu/239,240Pu in soil samples were used to determine the origin (source) and date of the Pu contamination in the investigated alpine sites. The 241Pu/239,240Pu and 238Pu/239,240Pu activity ratios confirmed that the main origin of Pu in the alpine soils was the global fallout from the nuclear bomb tests (NBT) in the fifties and sixties. Furthermore, the 241Pu/241Am activity ratios were used to determine the age of the Pu contamination, which is also an important data for distinguishing the Pu sources. The estimation of the date of the contamination, by the 241Pu/241Am age-dating method, further confirmed the NBT as the Pu source. However, the 241Pu/241Am dating method was limited to samples where Pu-Am fractionation was insignificant. If any, the contribution of the Chernobyl accident in the studied sites is negligible.

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.

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.

Chemical and biological attributes of a lowland soil affected by land leveling

The objective of this work was to evaluate the relationship between soil chemical and biological attributes and the magnitude of cuts and fills after the land leveling process of a lowland soil. Soil samples were collected from the 0 - 0.20 m layer, before and after leveling, on a 100 point grid established in the experimental area, to evaluate chemical attributes and soil microbial biomass carbon (MBC). Leveling operations altered the magnitude of soil chemical and biological attributes. Values of Ca, Mg, S, cation exchange capacity, Mn, P, Zn, and soil organic matter (SOM) decreased in the soil profile, whereas Al, K, and MBC increased after leveling. Land leveling decreased in 20% SOM average content in the 0 - 0.20 m layer. The great majority of the chemical attributes did not show relations between their values and the magnitude of cuts and fills. The relation was quadratic for SOM, P, and total N, and was linear for K, showing a positive slope and indicating increase in the magnitude of these attributes in cut areas and stability in fill areas. The relationships between these chemical attributes and the magnitude of cuts and fills indicate that the land leveling map may be a useful tool for degraded soil recuperation through amendments and organic fertilizers.

Solution scanning as a key policy tool: identifying management interventions to help maintain and enhance regulating ecosystem services

The major task of policy makers and practitioners when confronted with a resource management problem is to decide on the potential solution(s) to adopt from a range of available options. However, this process is unlikely to be successful and cost effective without access to an independently verified and comprehensive available list of options. There is currently burgeoning interest in ecosystem services and quantitative assessments of their importance and value. Recognition of the value of ecosystem services to human well-being represents an increasingly important argument for protecting and restoring the natural environment, alongside the moral and ethical justifications for conservation. As well as understanding the benefits of ecosystem services, it is also important to synthesize the practical interventions that are capable of maintaining and/or enhancing these services. Apart from pest regulation, pollination, and global climate regulation, this type of exercise has attracted relatively little attention. Through a systematic consultation exercise, we identify a candidate list of 296 possible interventions across the main regulating services of air quality regulation, climate regulation, water flow regulation, erosion regulation, water purification and waste treatment, disease regulation, pest regulation, pollination and natural hazard regulation. The range of interventions differs greatly between habitats and services depending upon the ease of manipulation and the level of research intensity. Some interventions have the potential to deliver benefits across a range of regulating services, especially those that reduce soil loss and maintain forest cover. Synthesis and applications: Solution scanning is important for questioning existing knowledge and identifying the range of options available to researchers and practitioners, as well as serving as the necessary basis for assessing cost effectiveness and guiding implementation strategies. We recommend that it become a routine part of decision making in all environmental policy areas.