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This manuscript provides a methodology for the reconstruction of a rainfall field when there are scarce rain-gauge stations available. This situation typically arises when measurements are taken from meteorological stations across time, and the information for the complete field is required as an input for larger scale models. The proposed method is based on a wavelet reconstruction technique that requires no distributional assumptions, but relies on the relation between rainfall and normalized difference vegetation index to account for the unobserved spatial variability of the field. The methodology is applied over a region of the southern Peruvian Andes where data gathered from meteorological stations provide enough statistical significance. A comparison with respect to an alternative source of spatial variability and common practices is provided.

Data acquisition for parameterization is one of the most important limitations for the use of potato crop growth models. Non-destructive techniques such as remote sensing for gathering required data could circumvent this limitation. Our goal was to analyze the effects of incorporating ground-based spectral canopy reflectance data into two light interception models with different complexity. A dynamic- hourly scale- canopy photosynthesis model (DCPM), based on a non-rectangular hyperbola applied to sunlit and shaded leaf layers and considering carbon losses by respiration, was implemented (complex model). Parameters included the light extinction coefficient, the proportion of light transmitted by leaves, the fraction of incident diffuse photosynthetically active radiation and leaf area index. On the other hand, a simple crop growth model (CGM) based on daily scale of light interception, light use efficiency (LUE) and harvest index was parameterized using either canopy cover (CGMCC) or the weighted difference vegetation index (CGMWDVI). A spectroradiometer, a chlorophyll meter and a multispectral camera were used to derive the required parameters. CGMWDVI improved yield prediction compared to CGMCC. Both CGMWDVI and DCPM showed high degree of accuracy in the yield prediction. Since large LUE variations were detected depending on the diffuse component of radiation, the improvement of simple CGM using remotely sensed data is contingent on an appropriate LUE estimation. Our study suggests that the incorporation of remotely sensed data in models with different temporal resolution and level of complexity improves yield prediction in potato.

A soil carbon assessment was performed comparing agricultural cropping systems with natural vegetation along a sampling transect spanning different agro-ecologies on the eastern foot slopes of Mount Kenya in Embu county, 125 km from Nairobi, Kenya. The aim was to determine differences in soil carbon stocks and carbon recalcitrance and relate these to soil textural class, altitude, climatic parameters and land use. Soils from main agricultural systems as tea, coffee and maize-based intercropping, as well as from natural vegetation cover were sampled in triplicates, in five layers from 0 to 30 cm in depth and processed for total carbon analysis. The whole soil samples were also analysed using Laser-Induced Fluorescence Spectroscopy (LIFS) to assess carbon humification. Prototype portable equipment intended for future in situ analysis was used in the lab to ascertain the structure of the most recalcitrant and stable carbon present in different agro-ecosystems. In addition, Near Infrared Spectroscopy (NIRS) was tested for the quantitative analysis of soil carbon, showing that it is a reproducible and low-cost method that provided satisfactory results under the processing conditions of the samples. Results showed wide variation in the level and quality of carbon stored in the soils, depending on soil texture, land use, elevation, climate, agricultural practices and land use history. Considering the heterogeneous nature of sampled soils and the performance of NIRS and LIFS, these results can be used as a basis for the development of fully portable systems able to provide rapid, clean and potentially cost-effective relevant information for soil management.

Remotely sensed data are often used as proxies for indirect precipitation measures over data-scarce and complex-terrain areas such as the Peruvian Andes. Although this information might be appropriate for some research requirements, the extent at which local sites could be related to such information is very limited because of the resolution of the available satellite data. Downscaling techniques are used to bridge the gap between what climate modelers (global and regional) are able to provide and what decision-makers require (local). Precipitation downscaling improves the poor local representation of satellite data and helps end-users acquire more accurate estimates of water availability. Thus, a multifractal downscaling technique complemented by a heterogeneity filter was applied to TRMM (Tropical Rainfall Measuring Mission) 3B42 gridded data (spatial resolution ~ 28 km) from the Peruvian Andean high plateau or \\textit{Altiplano} to generate downscaled rainfall fields that are relevant at an agricultural scale (spatial resolution ~ 1 km).

Sweet potato (Ipomoea batatas L.) is a low production cost crop that is grown during almost the whole year, mainly in developing countries. In arid and semiarid regions, the presence of salinity and water stress can generate yield reductions and losses in the quality of the tuber roots. To address these issues, an experiment was performed to determine yield, N, P, K, Ca, Mg and Na uptake and proline content in plants belonging to two sweet potato cultivars with a different degree of salt tolerance, grown under three (0, 8 and 14 mmol NaCl) salt and two watering regimes (watering after two and four days), during summer-fall conditions of 2009. Salinity and watering frequencies were controlled by using the soilless culture technique. Both water and salt stresses reduced tuber root yields. The yield reduction is explained by a reduction in the uptake of N, P, K, Ca and Mg with the water stress treatment, and an increased Na uptake in the high salinity treatment. The salt and water stress adjustments were reflected in an increment in proline content in leaves and tuber roots. The results confirm the tolerant cultivar as a hardy variety adaptable to abiotic stresses, whereas the non-tolerant variety had lower yield and nutrient uptake. The results did not support the hypothesis that changes in proline content might be used as fast screening tools to discriminate between tolerant and susceptible sweet potato cultivars.

The phenotyping of secondary characters is a common practice in breeding programs aiming at finding physiological mechanism related to drought tolerance. However, the dynamics of these characters depend on crop phenology, levels of water shortage, and other factors that affect their relationship with yield and limit their capacity to be used for predictive purposes. In this work, we compared tuber yield with the temporal trend (using accumulated thermal time) of chlorophyll concentration (Chl SPAD ), osmotic potential, and relative water content under water restriction. UNICA, a potato variety characterized by its low drought susceptibility was tested under full irrigation (as a control) and different treatments of partial root-zone drying and deficit irrigation in greenhouse and field conditions. Chl SPAD was the only trait showing a concurrent changing trend (slope) with yields, particularly in field conditions. The rate of greenness loss or senescence was slower in the higher water restriction treatments, which indicates that the stay-green effect (delayed senescence) occurs in some potato varieties. Chl SPAD at the loss of half the maximum plant cover during senescence (between 1040 and 1170 °C days) was high and negatively correlated with final yield in all irrigation treatments. Our findings suggest that during senescence, chlorophyll increment is not related to a rise of carbon assimilation (non-functional stay-green), but could be associated with an oxidative stress occurrence, ultimately reducing yield.

The South American monsoon system (SAMS) is the most important climatic feature in South America and is characterized by pronounced seasonality in precipitation during the austral summer. This study compares several statistical properties of daily gridded precipitation from different data (1998–2008): 1) Physical Sciences Division (PSD), Earth System Research Laboratory [1.0° and 2.5° latitude (lat)/longitude (lon)]; 2) Global Precipitation Climatology Project (GPCP; 1° lat/lon); 3) Climate Prediction Center (CPC) unified gauge (CPC-uni) (0.5° lat/lon); 4) NCEP Climate Forecast System Reanalysis (CFSR) (0.5° lat/lon); 5) NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis (0.5° lat/0.3° lon); and 6) Tropical Rainfall Measuring Mission (TRMM) 3B42 V6 data (0.25° lat/lon). The same statistical analyses are applied to data in 1) a common 2.5° lat/lon grid and 2) in the original resolutions of the datasets. All datasets consistently represent the large-scale patterns of the SAMS. The onset, demise, and duration of SAMS are consistent among PSD, GPCP, CPC-uni, and TRMM datasets, whereas CFSR and MERRA seem to have problems in capturing the correct timing of SAMS. Spectral analyses show that intraseasonal variance is somewhat similar in the six datasets. Moreover, differences in spatial patterns of mean precipitation are small among PSD, GPCP, CPC-uni, and TRMM data, while some discrepancies are found in CFSR and MERRA relative to the other datasets. Fitting of gamma frequency distributions to daily precipitation shows differences in the parameters that characterize the shape, scale, and tails of the frequency distributions. This suggests that significant uncertainties exist in the characterization of extreme precipitation, an issue that is highly important in the context of climate variability and change in South America.

Two field experiments were conducted in two semi-arid areas in northern China to test the response of three potato varieties to supplemental irrigation. Conventional furrow irrigation was compared to the partial root-zone drying (PRD) irrigation system at different watering levels, with and without plastic mulching. Reducing the supplementary water to one half, under both soil-climate conditions tested, did not affect fresh tuber yield; whereas water use efficiency (WUE) was equally incremented by all the reduced water treatments. When this reduction in the amount of supplementary water was managed through the PRD system, the distribution of moisture in the soil seemed to be improved and the potential evaporation was decreased due to the reduced evaporative surface exposed by PRD. The results showed that application of irrigation water per unit area can be reduced relative to common practice in Inner Mongolia and Gansu, maintaining the tuber yields currently obtained by local farmers. A further reduction in the amount of supplemental water, without a substantial decrease in yield, might be feasible with the PRD technique but this may require a more sophisticated irrigation management; and further research to estimate the cost-benefit ratio of such sophistication is needed. Results also showed that under low precipitation and low water retention capacity, the use of plastic mulching and a potato variety selected for drought-prone environments can make the difference for maintaining a high yield while reducing the wasteful use of the water resources.

Quantifying rainfall from remotely sensed data is crucial for regions where meteorological stations are scarce. This might be one of the only options for analysing rainfall patterns at different temporal and spatial scales in data-scarce environments, particularly in developing countries. The Tropical Rainfall Measuring Mission (TRMM) provides rainfall estimation over the tropics. Rainfall estimates from the TRMM satellite exhibit inaccuracies over topographically complex regions, thus warranting suitable corrections. Multi-resolution analysis (MRA) was applied to improve TRMM 3B42 daily rainfall estimation at 19 meteorological stations located over the Andean Plateau. The detailed signal from each meteorological station was added to the trend signal of each TRMM data cell. Comparing raw and corrected TRMM with gauged rainfall revealed that wavelet-based correction of TRMM 3B42 on average improved several metrics: entropy difference (15.45−1.32), determination coefficient (0.07−0.92), bias (0.68−1.01) and...

Potato bacterial wilt, caused by the bacterium Ralstonia solanacearum race 3 biovar 2 (R3bv2), affects potato production in several regions in the world. The disease becomes visually detectable when extensive damage to the crop has already occurred. Two greenhouse experiments were conducted to test the capability of a remote sensing diagnostic method supported by multispectral and multifractal analyses of the light reflectance signal, to detect physiological and morphological changes in plants caused by the infection. The analysis was carried out using the Wavelet Transform Modulus Maxima (WTMM) combined with the Multifractal (MF) analysis to assess the variability of high-resolution temporal and spatial signals and the conservative properties of the processes across temporal and spatial scales. The multispectral signal, enhanced by multifractal analysis, detected both symptomatic and latently infected plants, matching the results of ELISA laboratory assessment in 100 and 82%, respectively. Although the multispectral method provided no earlier detection than the visual assessment on symptomatic plants, the former was able to detect asymptomatic latent infection, showing a great potential as a monitoring tool for the control of bacterial wilt in potato crops. Applied to precision agriculture, this capability of the remote sensing diagnostic methodology would provide a more efficient control of the disease through an early and full spatial assessment of the health status of the crop and the prevention of spreading the disease.

Quantifying rainfall at spatial and temporal scales in regions where meteorological stations are scarce is important for agriculture, natural resource management and land-atmosphere interactions science. We describe a new approach to reconstruct daily rainfall from rain gauge data and the normalized difference vegetation index (NDVI) based on the fact that both signals are periodic and proportional. The procedure combines the Fourier Transform (FT) and the Wavelet Transform (WT). FT was used to estimate the lag time between rainfall and the vegetation response. Subsequently, third level decompositions of both signals with WT were used for the reconstruction process, determined by the entropy difference between levels and R^2. The low-frequency NDVI data signal, to which the high frequency signal (noise) extracted from the rainfall data was added, was the base for the reconstruction. The reconstructed and the measured rainfall showed similar entropy levels and better determination coefficients (>0.81) than the estimates with conventional statistical relations reported in the literature where this level of precision is only found for comparisons at the seasonal levels. Cross-validation resulted in @?10% entropy differences, compared to more than 45% obtained for the standard method when the NDVI was used to estimate the rainfall in the same pixel where the weather station was located. This methodology based on high resolution NDVI fields and data from a limited number of meteorological stations improves spatial reconstruction of rainfall.

Wetlands are valuable for their function as C sinks, water conservation and filtering, flood control, and as a recreational landscape. In the Central and Southern Andes, peatlands (a.k.a., bofedales) are also a source of good quality pastures for wild and domestic South American camelids (Vicugna pacos, Lama glama, and Vicugna vicugna). In the present study, whole soil samples from seasonally and permanently flooded bofedales were analyzed using laser-induced fluorescence spectroscopy (LIFS) and electron paramagnetic resonance (EPR) to assess soil organic matter (SOM) stability. The results obtained by both techniques were comparable (R 2 = 0.88) and proven to be reliable indicators of increased or reduced SOM stability and thus suitable methods for assessing its humification index. The humification values determined in the permanently flooded bofedal were lower than for the seasonally flooded one. Deeper in the soil profiles of both bofedal types, the humification process of SOM attains more advanced stages, with a relative increase of more recalcitrant organic compounds. An important factor is the presence of water in permanently flooded bofedales, which slows down organic matter decomposition due to anaerobiosis. Results from a portable LIFS system also showed significant correlations when compared with both the bench LIFS system (R 2 = 0.88) and the EPR (R 2 = 0.62). The portable system constitutes an affordable option for the in situ characterization of SOM. This assessment is of outmost importance in agroecosystems acting as green house gases sink or sources under variable climatic conditions.

A spatial curdling index [Formula: see text] is presented for studying income concentration in two-dimensional fields originated by a cascade process, resembling resource allocation maps. Computational simulations of spatial distributions show that the relation between [Formula: see text] and measures of income inequality such as the Gini coefficient [Formula: see text] forms a concave area. Acknowledgment of this fact brings additional information for formulating geopolitical strategies for income inequality reduction, and for comparison purposes in a set of countries or across time within a country. With the aim of showing the importance of index [Formula: see text], a prototype of the empirical application is shown based on the Peruvian and Swedish income maps.

Understanding spatial patterns is a critical and under‐explored aspect of remote sensing. This paper describes how multifractal theory can be applied to characterize these heterogeneous patterns in remotely sensed data as well as to determine the operational scale. An example based on the characterization of ulexite distribution on the world's largest salt flat (10 000 km2), located in Bolivia, using a binarized Landsat Thematic Mapper (TM) 4/7 ratio image, is used to describe the step‐by‐step procedure. Distribution was well characterized by the multifractal parameters and expressed through the f–α, τ–q and D–q relationships. Moments from q = −2 to 5 showed a linear trend in scales from approximately 0.007 to 10 000 km2. This implies that the attribute analysed could be measured at different scales, within defined boundaries, and up‐ and down‐scaled using the multifractal parameters. In addition, the asymmetry shown by the f–α spectrum indicates the presence of clusters with high probability of finding u...

Spatial arrangement of soil pores determines soil structure and is important to model soil processes. Geometric properties of individual pores can be estimated from thin sections, but there is no satisfactory method to quantify the complexity of their spatial arrangement. The objective of this work was to apply a multifractal technique to quantify properties of ten contrasting soil pore systems. Binary images (500 by 750 pixels, 74.2 μm pixel ') were obtained from thin sections and analyzed to obtain f(α) spectra. Pore area and pore perimeter were measured from each image and used to estimate a shape factor for pores with area larger than 0.27 × 10 6 μm 2 . Mean area of the lower (MA L ) and upper (MA U ) one-half of cumulative pore area distributions were calculated. Pore structures with large (MA U > 10 x 10 6 μm 2 ) and elongated pores exhibited flat f(α)-spectra typical of homogenous systems (three soils). Massive type structure with small (MA U < 1 × 10 16 μm 2 ) rounded and irregular pores resulted in asymmetric f(α)-spectra (two soils). Well defined and symmetric f(α)-spectra were obtained with soil structures having elongated pores of intermediate size (1 X 10 6 < MA U < 10 × 10 6 μm 2 ) clustered around relatively small structural units (five soils). Multifractal parameters defining the maximum of the f(α)-spectra were correlated to total porosity (P < 0.001), and silt content (P < 0.05). This study demonstrates that the spatial arrangement of contrasting soil structures can be quantified and separated by the properties of their f(α)-spectra. Multifractal parameters quantifying spatial arrangement of soil pores could be used to improve classifications of soil structure.

La teoría fractal y multifractal son herramientas muy promisorias para la caractelización de las propiedades hídricas de los suelos. La aplicación de un método o del otro, dependerá de la distribución y del tipo de variabilidad de las propiedades que se esta estudiando. La conductividad hidráulica saturada (Ks) es un importante parámetro físico para establecer el transporte de fluidos en suelos. Se ha demostrado que la medida de la conductividad hidráulica en el laboratorio esta influenciada por el tamaño de la muestra extraída en el campo. En este trabajo hemos aplicado la teoría multifractal para estudiar la dependencia del tamaño de las muestras, en forma de columnas, extraídas de tres horizontes diferentes de un suelo (Ap. Ct y C2) a lo largo de una transecta. Los parámetros multifractales calculados fueron funciones tanto de la longitud como del área de las muestras. Volúmenes más pequeños de muestras, resultado de muestras más cortas o de menores áreas perpendiculares al flujo, exhibieron distribuciones más heterogéneas y por lo tanto una fuerte propiedad multifractal, que aquellas por ejemplo, de volúmenes más grandes. El espectro multifractal fue también sensible a los diferentes horizontes del perfil del suelo muestreado. La mayor heterogeneidad, típico de un horizonte superficial, se observa en el espectro multifractal más ancho del horizonte Ap. si comparamos con los espectros de los horizontes C1 o C2, los cuales muestran una pequeña diferencia entre ellos. Por otro lado, los parámetros multifractales ofrecen información en un rango de escala donde el semivariograma (geo estadística) no mostró ningún resultado relevante., Fractal and multifractal concepts are promising tools for characterizing hydraulic properties in soils. The application of one method or the other will depend on the distributión and type of variability of the properties that are being studied. The saturated hydraulic conductivity (K,) is an important soil physics parameter to establish fluid transpon in soils. The measurement of hydraulic conductivity in the laboratory has showed to be much influenced by column size. In this work we have applied multifractal theory to study the dependence of column sample size in three different soil horizons (Ap. c. and C2) and along of a transect. The multifractal parameters calculated were functions of both sample length and sample area. Smaller volumes, resulting from shorter samples or smaller area perpendicular to flow, exhibited more heterogeneous distribution and, therefore, stronger multifractal properties than larger sample volumes. The multifractal spectrum was also sensitive to the different soil horizons present in a profile. The Iarge heterogeneity, typical of surface horizons, is manifested in the wider multiracial spectrum of the Ap horizon as compared to the spectra of either Ct or C2, which show very little difference between them. On the other hand, the multifractal results as compared to semi variograms obtained using geostatistical theory; yield information in a scale range where the semi variogram did not show any relevant rcsults.© 2003 CSI. All rights reserved

Scaling of mass within soil aggregates is characterized with a power-law model relating mass, M, and radius, r, of aggregates. When distribution of mass is fractal, the constants of the power-law model are the fractal dimension of mass, Dm, with a value 1 cm and r 1Þ of the Gladstone and Holmdel soils. For the wooded Gladstone and Holmdel soils, mass scaling of intact and eroded aggregates was statistically characterized by the same values of Dm and km, suggesting a concentric arrangement of mass, but only within aggregates that are not subjected to tillage. The km values of intact and eroded aggregates were correlated ðR ¼ 0:97Þ to aggregate bulk density of intact aggregates. Typically, small aggregates ðr < 1c mÞ, aggregates from wooded sites, and intact aggregates had larger values of lacunarity than their corresponding counterparts. This study indicates that fractal scaling of mass cannot be assumed for all soils, but it can be maintained in cultivated soils despite changes in mass scaling introduced by tillage. # 2002 Elsevier Science B.V. All rights reserved.

In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study.

A particle-size distribution (PSD) constitutes a fundamental soil property correlated to many other soil properties. Accurate representations of PSDs are, therefore, needed for soil characterization and prediction purposes. A power-law dependence of particle mass on particle diameter has been used to model soil PSDs, and such power-law dependence has been interpreted as being the result of a fractal distribution of particle sizes characterized with a single fractal dimension. However, recent studies have shown that a single fractal dimension is not sufficient to characterize a distribution for the entire range of particle sizes. The objective of this study was to apply multifractal techniques to characterize contrasting PSDs and to identify multifracfal parameters potentially useful for classification and prediction. The multifractal spectra of 30 PSDs covering a wide range of soil textural classes were analyzed. Parameters calculated from each multifractal spectrum were: (i) the Hausdorff dimension, f(α); (ii) the singularities of strength, α; (iii) the generalized fractal dimension, D q ; and (iv) their conjugate parameter the mass exponent, τ (q), calculated in the range of moment orders (q) of between -10 and -10 taken at 0.5 lag increments. Multifractal scaling was evident by an increase in the difference between the capacity D 0 and the entropy D 1 dimensions for soils with more than 10% clay content, Soils with

Experiments of water infiltration in a vertical plane through layered soils were carried out in the laboratory. We have followed the fingering dynamics by using image techniques. The fractal theory has been applied to describe the fingering phenomena. We also have simulated a modified site gradient invasion percolation model where most of the physical ingredients relevant to the problem have been incorporated. In contrast to what occurs with the standard gradient invasion percolation model, we have found the formation of many fingers. Taking into account the bond number, the number of fingers, and the wetted area of the experiments, we have fitted the parameters of our model. This opens the possibility of a theoretical prediction of the pore size distribution of the soil. The results are then compared with the experimental data.

Las tareas de resolución y planteamiento de problemas posibilitan indagar sobre aprendizajes específicos de los estudiantes. Plantear un problema significa idear un problema preconcibiendo un plan para su resolución. En la actualidad, sabemos poco de los procesos cognitivos usados por los estudiantes que pueden ser efectivos para plantear problemas de matemáticas. Para dar cuenta de cómo estudiantes universitarios construyen conocimiento relativo al teorema de Bayes cuando realizan tareas de planteamiento de problemas, usamos el modelo de la abstracción en contexto de acciones epistémicas anidadas de Hershkowitz, Schwarz y Dreyfus (2001). Los resultados muestran características distintas en el proceso de construcción del teorema de Bayes que ponen de manifiesto el potencial de las tareas de plantear problemas para desencadenar procesos de abstracción., Problem posing and problem solving are suitable tasks for inquiring into the learning of specific concepts. Posing a problem involves setting up a text for the problem and thinking about a plan to solve it. Currently, we have scarce knowledge about students’ effective cognitive process when posing mathematical problems. We have used the theoretical framework of nested epistemic actions (Hershkowitz, Schwarz and Dreyfus, 2001) in order to study how university students built knowledge about Bayes’ Theorem when they solve problem posing tasks. We have identified different characteristics in the process of constructing Bayes’ Theorem and the potential of posing problem activities to generate the abstraction process.

The study of water movement in soils is of fundamental importance in hydrologic science. It is generally accepted that in most soils, water and solutes flow through unsaturated zones via preferential paths or fingers. This paper combines magnetic resonance imaging (MRI) with both fractal and multifractal theory to characterize preferential flow in three dimensions. A cubic double-layer column filled with fine and coarse textured sand was placed into a 500 gauss MRI system. Water infiltration through the column (0.15×0.15×0.15 m3) was recorded in steady state conditions. Twelve sections with a voxel volume of 0.1×0.1×10 mm3 each were obtained and characterized using fractal and multifractal theory. The MRI system provided a detailed description of the preferential flow under steady state conditions and was also useful in understanding the dynamics of the formation of the fingers. The f(α) multifractal spectrum was very sensitive to the variation encountered at each horizontally-oriented slice of the column and provided a suitable characterization of the dynamics of the process identifying four spatial domains. In conclusion, MRI and fractal and multifractal analysis were able to characterize and describe the preferential flow process in soils. Used together, the two methods provide a good alternative to study flow transport phenomena in soils and in porous media.

Grazing systems in harsh environments are common throughout the world, and animal production is the mainstay of the livelihoods of many resource-poor farmers. The energy cost of the various activities involved in the process of harvesting the pasture to transform it into animal product can be estimated through an energy balance. This cost would be the difference between the metabolizable energy intake (MEI) and the energy expenditures for maintenance (MEm), temperature regulation (MEtr), and the energy for production (MEp). Each of the ME has its own net energy (NE) and its associated efficiency (K). When MEI>MEm+MEtr+MEp, the difference is attributable to the energy dissipated during grazing. The efficiency of converting the energy consumed into animal products depends on the magnitude of the dissipation. The inefficiency is associated with the energy spent in locomotion and the stress produced when there is low availability of energy in the pasture. This paper presents a method to quantify the dissipation of energy by grazing animals by considering it as a function of available energy. Such an understanding is required in order to develop management strategies to increase conversion efficiency.

El camote (Ipomoea batatas L.) es un cultivo de bajo costo de producción que se produce casi todo el año, principalmente en países en vías de desarrollo. En regiones áridas y semiáridas, la presencia de estrés hídrico y salino puede generar dis- minución de los rendimientos y pérdidas en la calidad de las raíces tuberosas. Se realizó un experimento para determinar el rendimiento, la absorción de nitrógeno, fósforo, potasio, calcio, magnesio y sodio, y contenido de prolina en plantas de dos cultivares de camote con diferente grado de tolerancia a la salinidad, cultivadas bajo tres regímenes de sales (0, 8 y 14 mmol NaCl) y dos regímenes de frecuencia de riego (riego cada dos y cada cuatro días), en condiciones del verano-otoño de 2009. La salinidad y las frecuencias de riego se controlaron mediante un sistema de cultivo sin suelo. Ambos estreses redujeron los rendimientos de raíces tuberosas. La reducción del rendimiento se explica por la reducción de la absorción de nitrógeno, fósforo, potasio, calcio y magnesio con el tratamiento de estrés hídrico, y un incremento de la absorción de sodio con el tratamiento de mayor salinidad. Los ajustes de salinidad y estrés hídrico se expresaron con un incremento en los con- tenidos de prolina en hojas y raíces tuberosas. Los resultados confirmaron que el cultivar tolerante es adaptable a los estreses abióticos, mientras que el otro cultivar obtuvo menor rendimiento y menor absorción de nutrimentos. Los resultados no apoyaron la hipótesis de que cambios en los contenidos de prolina podrían ser usados como una herramienta rápida para discriminar los cultivares de camote tolerantes de los que son susceptibles.

A spatial curdling index $(\mathcal{C})$ is presented for studying income concentration in two-dimensional fields originated by a cascade process, resembling resource allocation maps. Computational simulations of spatial distributions show that the relation between $\mathcal{C}$ and measures of income inequality such as the Gini coefficient $(\mathcal{G})$ forms a concave area. Acknowledgment of this fact brings additional information for formulating geopolitical strategies for income inequality reduction, and for comparison purposes in a set of countries or across time within a country. With the aim of showing the importance of index $\mathcal{C}$, a prototype of the empirical application is shown based on the Peruvian and Swedish income maps.

Carbon accumulation and sequestration in Andean soils are scarcely documented. Carbon contents, carbon stocks, and stability were determined in five Peruvian agroecologies, along a 1,000 km (621 mi) transect covering the arid Pacific coast, the Andean high plateau, and the tropical highland rainforest in the eastern flank of the Andes. It was hypothesized that the carbon stocks and stability varied with land use and altitudinal gradient. Results showed that the soils in the tropical highland rainforest site presented the higher (p > 0.05) carbon contents (134 g kg -1 [13.4%]). Coffee plantations in the tropical highland rainforest and alfalfa under irrigation in the dry valleys presented larger (p > 0.05) carbon stocks (83 Mg ha -1 [37 tn ac -1 ]) than primary rainforests.The dry lowlands showed the lowest carbon contents (51 g kg -1 [5.1%]) and carbon stocks (40 Mg ha -1 [18 tn ac -1 ]). Soil organic carbon increased with elevation in the arid environments. In the high plateau potato systems, low carbon contents (68 g kg -1 [6.8%]) and carbon stocks (47 Mg ha -1 [21 tn ac -1 ]) were found. The soils in both the tropical highland rainforest and the dry valleys presented lower humification index, when compared to other agroecologies. Humification increased with soil depth due to the presence of recalcitrant carbon, while at the surface the presence of labile carbon dominates as a result of a constant input of plant residues. Results suggest that diversified production systems with crops and livestock are more stable for carbon stocks, which might be essential to help farmers adapting to the effects of climate change. Therefore, viable land uses, from the carbon economy perspective, must be promoted to support sustainable agricultural practices for most important ecological conditions.