998 resultados para ORGANIC NETWORKS
Resumo:
Citrus plants are the most important fruit species in the world, with emphasis to oranges, mandarins and lemons. In Rio Grande do Sul, Brazil, most fruit production is found on small properties under organic cultivation. Soil compaction is one of the factors limiting production and due to the fixed row placement of this crop, compaction can arise in various manners in the interrows of the orchard. The aim of this study was to evaluate soil physical properties and water infiltration capacity in response to interrow management in an orchard of mandarin (Citrus deliciosa Tenore 'Montenegrina') under organic cultivation. Interrow management was performed through harrowing, logs in em "V", mowing, and cutting/knocking down plants with a knife roller. Soil physical properties were evaluated in the wheel tracks of the tractor (WT), between the wheel tracks (BWT), and in the area under the line projection of the canopy (CLP), with undisturbed soil samples collected in the 0.00-0.15, 0.15-0.30, 0.30-0.45, and 0.45-0.60 m layers, with four replicates. The soil water infiltration test was performed using the concentric cylinder method, with a maximum time of 90 min for each test. In general, soil analysis showed a variation in the physical-hydraulic properties of the Argissolo Vermelho-Amarelo distrófico arênico (sandy loam Typic Paleudalf) in the three sampling sites in all layers, regardless of the management procedure in the interrows. Machinery traffic leads to heterogeneity in the soil physical-hydraulic properties in the interrows of the orchard. Soil porosity and bulk density are affected especially in the wheel tracks of the tractor (WT), which causes a reduction in the constant rate of infiltration and in the accumulated infiltration of water in this sampling site. The use of the disk harrow and mower leads to greater harmful effects on the soil, which can interfere with mandarin production.
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We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well-defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology, and spectral graph analysis.
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We demonstrate that the self-similarity of some scale-free networks with respect to a simple degree-thresholding renormalization scheme finds a natural interpretation in the assumption that network nodes exist in hidden metric spaces. Clustering, i.e., cycles of length three, plays a crucial role in this framework as a topological reflection of the triangle inequality in the hidden geometry. We prove that a class of hidden variable models with underlying metric spaces are able to accurately reproduce the self-similarity properties that we measured in the real networks. Our findings indicate that hidden geometries underlying these real networks are a plausible explanation for their observed topologies and, in particular, for their self-similarity with respect to the degree-based renormalization.
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We develop a theoretical approach to percolation in random clustered networks. We find that, although clustering in scale-free networks can strongly affect some percolation properties, such as the size and the resilience of the giant connected component, it cannot restore a finite percolation threshold. In turn, this implies the absence of an epidemic threshold in this class of networks, thus extending this result to a wide variety of real scale-free networks which shows a high level of transitivity. Our findings are in good agreement with numerical simulations.
Resumo:
We develop a full theoretical approach to clustering in complex networks. A key concept is introduced, the edge multiplicity, that measures the number of triangles passing through an edge. This quantity extends the clustering coefficient in that it involves the properties of two¿and not just one¿vertices. The formalism is completed with the definition of a three-vertex correlation function, which is the fundamental quantity describing the properties of clustered networks. The formalism suggests different metrics that are able to thoroughly characterize transitive relations. A rigorous analysis of several real networks, which makes use of this formalism and the metrics, is also provided. It is also found that clustered networks can be classified into two main groups: the weak and the strong transitivity classes. In the first class, edge multiplicity is small, with triangles being disjoint. In the second class, edge multiplicity is high and so triangles share many edges. As we shall see in the following paper, the class a network belongs to has strong implications in its percolation properties.
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The application of pig slurry may have a different effect on nitrogen dynamics in soil compared to mineral fertilization. Thus, the aim of this study was to determine the different forms of organic N in a Latossolo Vermelho distroférrico (Typic Hapludox) and their relationship to N uptake by crops in response to 10 years of annual application of pig slurry and mineral fertilizer. The treatments were application rates of 0, 25, 50, 100, and 200 m3 ha-1 of pig slurry, in addition to mineral fertilizer, organized in a randomized block design with four replications. The N contents were determined in the plant tissue and in the forms of total N and acid hydrolyzed fractions: ammonium-N, hexosamine-N, α-amino-N, amide-N, and unidentified-N. Annual application of pig slurry or mineral fertilizer increased the total-N content in the 0-10 cm depth layer. The main fractions of organic N in the soil were α-amino-N when pig slurry was applied and unidentified-N in the case of mineral fertilizers. Pig slurry increased the N fractions considered as labile: α-amino-N, ammonium-N, and amide-N. The increase in these labile organic N fractions in the soil through pig slurry application allows greater N uptake by the maize and oat crops in a no-tillage system.
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We develop a general theory for percolation in directed random networks with arbitrary two-point correlations and bidirectional edgesthat is, edges pointing in both directions simultaneously. These two ingredients alter the previously known scenario and open new views and perspectives on percolation phenomena. Equations for the percolation threshold and the sizes of the giant components are derived in the most general case. We also present simulation results for a particular example of uncorrelated network with bidirectional edges confirming the theoretical predictions.
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Inorganic phosphorus (Pi) usually controls the P availability in tropical soils, but the contribution of organic P (Po) should not be neglected, mainly in systems with low P input or management systems that promote organic matter accumulation. The aims of this study were to evaluate the changes in the Po fractions over time in soil fertilized and not fertilized with cattle manure and to correlate Po forms with available P extracted by anion exchange resin. The experiment was carried out under field conditions, in a sandy-clay loam Haplustox. The experimental design was a 2 × 9 randomized complete block factorial design, in which the first factor was manure application (20 t ha-1) or absence, and the second the soil sampling times (3, 7, 14, 21, 28, 49, 70, 91, and 112 days) after manure incorporation. Labile, moderately labile and non-labile Po fractions were determined in the soil material of each sampling. Manure fertilization increased the Po levels in the moderately labile and non-labile fractions and the total organic P, but did not affect the Po fraction proportions in relation to total organic P. On average, 5.1 % of total Po was in the labile, 44.4 % in the moderately labile and 50.5 % in the non-labile fractions. Available P (resin P) was more affected by the manure soluble Pi rather than by the labile Po forms. The labile and non-labile Po fractions varied randomly with no defined trend in relation to the samplings; for this reason, the data did not fit any mathematical model.
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The use of organic fertilizers and the inoculation of mycorrhizal fungi in the cultivation of oil crops is essential to reduce production costs and minimize negative impacts on natural resources. A field experiment was conducted in an Argissolo Amarelo (Ultisol) with the aim of evaluating the effects of fertilizer application and inoculation of arbuscular mycorrhizal fungi on the growth attributes of sunflower (Helianthus annuus L.) and on soil chemical properties. The experiment was conducted at the Federal University of Rio Grande do Norte, Brazil, using a randomized block design with three replicates in a 4 × 2 factorial arrangement consisting of four treatments in regard to application of organic fertilizer (liquid biofertilizer, cow urine, mineral fertilizer, and unfertilized control) and two treatments in regard to arbuscular mycorrhizal fungi (with and without mycorrhizal fungi). The results showed that the physiological attributes of relative growth rate and leaf weight ratio were positively influenced by fertilization, compared to the control treatment, likely brought about by the supply of nutrients from the fertilizers applied. The growth and productivity attributes were positively affected by mycorrhization.
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The percolation properties of clustered networks are analyzed in detail. In the case of weak clustering, we present an analytical approach that allows us to find the critical threshold and the size of the giant component. Numerical simulations confirm the accuracy of our results. In more general terms, we show that weak clustering hinders the onset of the giant component whereas strong clustering favors its appearance. This is a direct consequence of the differences in the k-core structure of the networks, which are found to be totally different depending on the level of clustering. An empirical analysis of a real social network confirms our predictions.
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We present a generator of random networks where both the degree-dependent clustering coefficient and the degree distribution are tunable. Following the same philosophy as in the configuration model, the degree distribution and the clustering coefficient for each class of nodes of degree k are fixed ad hoc and a priori. The algorithm generates corresponding topologies by applying first a closure of triangles and second the classical closure of remaining free stubs. The procedure unveils an universal relation among clustering and degree-degree correlations for all networks, where the level of assortativity establishes an upper limit to the level of clustering. Maximum assortativity ensures no restriction on the decay of the clustering coefficient whereas disassortativity sets a stronger constraint on its behavior. Correlation measures in real networks are seen to observe this structural bound.
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Veredas are humid tropical ecosystems, generally associated to hydromorphic soils and a shallow water table. The soils of these ecosystems are affected by the use of the areas around these veredas. The objective of this study was to determine soil organic matter (SOM) fractions in veredas adjacent to preserved (native savanna) and disturbed environments (agricultural areas and pastures) in the Cerrado biome. Soil samples were collected from the 0-10 and 10-20 cm layers along reference lines drawn along the relief following the upper, middle and lower positions of one of the slopes, in the direction of the draining line of the vereda. The soil analysis determined: total soil OC, total nitrogen and C:N ratio; C and N contents and C:N ratio in particulate and mineral-associated fractions (of SOM); fulvic acids, humic acids and humin fractions and ratio between humic and fulvic acids. The agricultural use around the veredas induced changes in the SOM fractions, more pronounced in the lower part of the slope. In the soil surface of this part, the OC levels in the humic substances and the particulate fraction of SOM, as well as total soil OC were reduced in the vereda next to crop fields.
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Organic matter plays an important role in many soil properties, and for that reason it is necessary to identify management systems which maintain or increase its concentrations. The aim of the present study was to determine the quality and quantity of organic C in different compartments of the soil fraction in different Amazonian ecosystems. The soil organic matter (FSOM) was fractionated and soil C stocks were estimated in primary forest (PF), pasture (P), secondary succession (SS) and an agroforestry system (AFS). Samples were collected at the depths 0-5, 5-10, 10-20, 20-40, 40-60, 60-80, 80-100, 100-160, and 160-200 cm. Densimetric and particle size analysis methods were used for FSOM, obtaining the following fractions: FLF (free light fraction), IALF (intra-aggregate light fraction), F-sand (sand fraction), F-clay (clay fraction) and F-silt (silt fraction). The 0-5 cm layer contains 60 % of soil C, which is associated with the FLF. The F-clay was responsible for 70 % of C retained in the 0-200 cm depth. There was a 12.7 g kg-1 C gain in the FLF from PF to SS, and a 4.4 g kg-1 C gain from PF to AFS, showing that SS and AFS areas recover soil organic C, constituting feasible C-recovery alternatives for degraded and intensively farmed soils in Amazonia. The greatest total stocks of carbon in soil fractions were, in decreasing order: (101.3 Mg ha-1 of C - AFS) > (98.4 Mg ha-1 of C - FP) > (92.9 Mg ha-1 of C - SS) > (64.0 Mg ha-1 of C - P). The forms of land use in the Amazon influence C distribution in soil fractions, resulting in short- or long-term changes.