5 resultados para Resilience, watershed governance

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP)


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In this paper we determine the local and global resilience of random graphs G(n,p) (p >> n(-1)) with respect to the property of containing a cycle of length at least (1 - alpha)n. Roughly speaking, given alpha > 0, we determine the smallest r(g) (G, alpha) with the property that almost surely every subgraph of G = G(n,p) having more than r(g) (G, alpha)vertical bar E(G)vertical bar edges contains a cycle of length at least (1 - alpha)n (global resilience). We also obtain, for alpha < 1/2, the smallest r(l) (G, alpha) such that any H subset of G having deg(H) (v) larger than r(l) (G, alpha) deg(G) (v) for all v is an element of V(G) contains a cycle of length at least (1 - alpha)n (local resilience). The results above are in fact proved in the more general setting of pseudorandom graphs.

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The transfer of carbon (C) from Amazon forests to aquatic ecosystems as CO(2) supersaturated in groundwater that outgases to the atmosphere after it reaches small streams has been postulated to be an important component of terrestrial ecosystem C budgets. We measured C losses as soil respiration and methane (CH(4)) flux, direct CO(2) and CH(4) fluxes from the stream surface and fluvial export of dissolved inorganic C (DIC), dissolved organic C (DOC), and particulate C over an annual hydrologic cycle from a 1,319-ha forested Amazon perennial first-order headwater watershed at Tanguro Ranch in the southern Amazon state of Mato Grosso. Stream pCO(2) concentrations ranged from 6,491 to 14,976 mu atm and directly-measured stream CO(2) outgassing flux was 5,994 +/- A 677 g C m(-2) y(-1) of stream surface. Stream pCH(4) concentrations ranged from 291 to 438 mu atm and measured stream CH(4) outgassing flux was 987 +/- A 221 g C m(-2) y(-1). Despite high flux rates from the stream surface, the small area of stream itself (970 m(2), or 0.007% of watershed area) led to small directly-measured annual fluxes of CO(2) (0.44 +/- A 0.05 g C m(2) y(-1)) and CH(4) (0.07 +/- A 0.02 g C m(2) y(-1)) per unit watershed land area. Measured fluvial export of DIC (0.78 +/- A 0.04 g C m(-2) y(-1)), DOC (0.16 +/- A 0.03 g C m(-2) y(-1)) and coarse plus fine particulate C (0.001 +/- A 0.001 g C m(-2) y(-1)) per unit watershed land area were also small. However, stream discharge accounted for only 12% of the modeled annual watershed water output because deep groundwater flows dominated total runoff from the watershed. When C in this bypassing groundwater was included, total watershed export was 10.83 g C m(-2) y(-1) as CO(2) outgassing, 11.29 g C m(-2) y(-1) as fluvial DIC and 0.64 g C m(-2) y(-1) as fluvial DOC. Outgassing fluxes were somewhat lower than the 40-50 g C m(-2) y(-1) reported from other Amazon watersheds and may result in part from lower annual rainfall at Tanguro. Total stream-associated gaseous C losses were two orders of magnitude less than soil respiration (696 +/- A 147 g C m(-2) y(-1)), but total losses of C transported by water comprised up to about 20% of the +/- A 150 g C m(-2) (+/- 1.5 Mg C ha(-1)) that is exchanged annually across Amazon tropical forest canopies.

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The recognition of temporally stable locations with respect to soil water content is of importance for soil water management decisions, especially in sloping land of watersheds. Neutron probe soil water content (0 to 0.8 m), evaluated at 20 dates during a year in the Loess Plateau of China, in a 20 ha watershed dominated by Ust-Sandiic Entisols and Aeolian sandy soils, were used to define their temporal stability through two indices: the standard deviation of relative difference (SDRD) and the mean absolute bias error (MABE). Specific concerns were (a) the relationship of temporal stability with soil depth, (b) the effects of soil texture and land use on temporal stability, and (c) the spatial pattern of the temporal stability. Results showed that temporal stability of soil water content at 0.2 m was significantly weaker than those at the soil depths of 0.6 and 0.8 m. Soil texture can significantly (P<0.05) affect the stability of soil water content except for the existence of an insignificant difference between sandy loam and silt loam textures, while temporal stability of areas covered by bunge needlegrass land was not significantly different from those covered by korshinsk peashrub. Geostatistical analysis showed that the temporal stability was spatially variable in an organized way as inferred by the degree of spatial dependence index. With increasing soil depth, the range of both temporal stability indices showed an increasing trend, being 65.8-120.5 m for SDRD and 148.8-214.1 m for MABE, respectively. This study provides a valuable support for soil water content measurements for soil water management and hydrological applications on sloping land areas. (C) 2010 Elsevier B.V. All rights reserved.

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The knowledge of soil water storage (SWS) of soil profiles is crucial for the adoption of vegetation restoration practices. With the aim of identifying representative sites to obtain the mean SWS of a watershed, a time stability analysis of neutron probe evaluations of SWS was performed by the means of relative differences and Spearman rank correlation coefficients. At the same time, the effects of different neutron probe calibration procedures were explored on time stability analysis. mean SWS estimation. and preservation of the spatial variability of SWS. The selected watershed, with deep gullies and undulating slopes which cover an area of 20 ha, is characterized by an Ust-Sandiic Entisol and an Aeolian sandy soil. The dominant vegetation species are bunge needlegrass (Stipa bungeana Trim) and korshinsk peashrub (Carugano Korshinskii kom.). From June 11, 2007 to July 23,2008, SWS of the top1 m soil layer was evaluated for 20 dates, based on neutron probe data of 12 sampling sites. Three calibration procedures were employed: type 1, most complete, with each site having its own linear calibration equation (TrE); type II. with TrE equations extended over the whole field: and type III, with one single linear calibration curve for the whole field (UnE) and also correcting its intercept based on site specific relative difference analysis (RdE) and on linear fitting of data (RcE), both maintaining the same slope. A strong time stability of SWS estimated by TrE equations was identified. Soil particle size and soil organic matter content were recognized as the influencing factors for spatial variability of SWS. Land use influenced neither the spatial variability nor the time stability of SWS. Time stability analysis identified one site to represent the mean SWS of the whole watershed with mean absolute percentage errors of less than 10%, therefore. this site can be used as a predictor for the mean SWS of the watershed. Some equations of type II were found to be unsatisfactory to yield reliable mean SWS values or in preserving the associated soil spatial variability. Hence, it is recommended to be cautious in extending calibration equations to other sites since they might not consider the field variability. For the equations with corrected intercept (type III), which consider the spatial variability of calibration in a different way in relation to TrE, it was found that they can yield satisfactory means and standard deviation of SWS, except for the RdE equations, which largely leveled off the SWS values in the watershed. Correlation analysis showed that the neutron probe calibration was linked to soil bulk density and to organic matter content. Therefore, spatial variability of soil properties should be taken into account during the process of neutron probe calibration. This study provides useful information on the mean SWS observation with a time stable site and on distinct neutron probe calibration procedures, and it should be extended to soil water management studies with neutron probes, e.g., the process of vegetation restoration in wider area and soil types of the Loess Plateau in China. (C) 2009 Elsevier B.V. All rights reserved.

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The relationship between the structure and function of biological networks constitutes a fundamental issue in systems biology. Particularly, the structure of protein-protein interaction networks is related to important biological functions. In this work, we investigated how such a resilience is determined by the large scale features of the respective networks. Four species are taken into account, namely yeast Saccharomyces cerevisiae, worm Caenorhabditis elegans, fly Drosophila melanogaster and Homo sapiens. We adopted two entropy-related measurements (degree entropy and dynamic entropy) in order to quantify the overall degree of robustness of these networks. We verified that while they exhibit similar structural variations under random node removal, they differ significantly when subjected to intentional attacks (hub removal). As a matter of fact, more complex species tended to exhibit more robust networks. More specifically, we quantified how six important measurements of the networks topology (namely clustering coefficient, average degree of neighbors, average shortest path length, diameter, assortativity coefficient, and slope of the power law degree distribution) correlated with the two entropy measurements. Our results revealed that the fraction of hubs and the average neighbor degree contribute significantly for the resilience of networks. In addition, the topological analysis of the removed hubs indicated that the presence of alternative paths between the proteins connected to hubs tend to reinforce resilience. The performed analysis helps to understand how resilience is underlain in networks and can be applied to the development of protein network models.