795 resultados para Landscape indices


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Chinese Academy of Sciences ; National Science Foundation of China [41071059]; National Key Technology R&D Program of China [2008BAK50B06-02]; National Basic Research Program of China [2010CB950900, 2010CB950704]; Natural Sciences and Engineering Research Council of Canada

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The relationships between ecological diversity and ecosystem functions such as stability and productivity have long been debated and have no final conclusion until now. It is ignored that the debate should be firstly based on the same diversity index, which should be theoretically complete, and on same observation scale. For the issue on the scale of ecotope observation, ecosystems should be distinguished according to intensity of human disturbance. For the issue on the scale of species observation, either number diversity or biomass diversity should be identified. This paper takes grassland ecosystems located within the Bayin Xile grassland of Xilin Gol League of Inner Mongolia Autonomous Region as an example to analyze effects of different diversity indices and spatial scales on the conclusions of ecological diversity and its relationships with ecosystem functions. The analysis results both on the scale of ecotope observation and on the scale of species observation show that different diversity indices might give different conclusions and spatial resolution has a great effect on the relative conclusions. (c) 2005 Elsevier B.V. All rights reserved.

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Land-cover changes in China are being powered by demand for food for its growing population and by the nation's transition from a largely rural society to one in which more than half of its people are expected to live in cities within two decades. Here we use an analysis of remotely sensed data gathered between 1990 and 2000, to map the magnitude and pattern of changes such as the conversion of grasslands and forests to croplands and the loss of croplands to urban expansion. With high-resolution ( 30 m) imagery from Landsat TM for the entire country, we show that between 1990 and 2000 the cropland area increased by 2.99 million hectares and urban areas increased by 0.82 million hectares. In northern China, large areas of woodlands, grasslands and wetlands were converted to croplands, while in southern China large areas of croplands were converted to urban areas. The land-cover products presented here give the Chinese government and international community, for the first time, an unambiguous understanding of the degree to which the nation's landscape is being altered. Documentation of these changes in a reliable and spatially explicit way forms the foundation for management of China's environment over the coming decades.

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Four models are employed in the landscape change detection of the newly created wetland. The models include ones for patch connectivity. ecological diversity, human impact intensity and mean center of land cover. The landscape data of the newly created wetland in Yellow River Delta in 1984, 1991, and 1996 are produced from the unsupervised classification and the supervised classification on the basis of integrating Landsat TM images of the newly created wetland in the four seasons of the each year. The result from operating the models into the data shows that the newly created wetland landscape in Yellow River Delta had a great chance. The driving focus of the change are mainly from natural evolution of the newly created wetland and rapid population growth, especially non-peasant population growth in Yellow River Delta because a considerable amount of oil and gas fields have been found in the Yellow River Delta. For preventing the newly created wetland from more destruction and conserving benign Succession of the ecosystems in the newly created wetland, six measures are suggested on the basis of research results. (C) 2003 Elsevier Science B.V. All rights reserved.

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GIMMS NDVI database and geo-statistics were used to depict the spatial distribution and temporal stability of NDVI on the Mongolian Plateau. The results demonstrated that: (1) Regions of interest with high NDVI indices were distributed primarily in forested mountainous regions of the east and the north, areas with low NDVI indices were primarily distributed in the Gobi desert regions of the west and the southwest, and areas with moderate NDVI values were mainly distributed in a middle steppe strap from northwest to southeast. (2) The maximum NDVI values maintained for the past 22 years showed little variation. The average NDVI variance coefficient for the 22-year period was 15.2%. (3) NDVI distribution and vegetation cover showed spatial autocorrelations on a global scale. NDVI patterns from the vegetation cover also demonstrated anisotropy; a higher positive spatial correlation was indicated in a NW-SE direction, which suggested that vegetation cover in a NW-SE direction maintained increased integrity, and vegetation assemblage was mainly distributed in the same specific direction. (4) The NDVI spatial distribution was mainly controlled by structural factors, 88.7% of the total spatial variation was influenced by structural and 11.3% by random factors. And the global autocorrelation distance was 1178 km, and the average vegetation patch length (NW-SE) to width (NE-SW) ratio was approximately 2.4:1.0.

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The novel phase field model with the "polymer characteristic" was established based on a nonconserved spatiotemporal Ginzburg-Landau equation (TDGL model A). Especially, we relate the diffusion equation with the crystal growth faces of polymer single crystals. Namely, the diffusion equations are discretized according to the diffusion coefficient of every lattice site in various crystal growth faces and the shape of lattice is selected based on the real proportion of the unit cell dimensions.

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We established a theoretical framework for studying nonequilibrium networks with two distinct natures essential for characterizing the global probabilistic dynamics: the underlying potential landscape and the corresponding curl flux. We applied the idea to a biochemical oscillation network and found that the underlying potential landscape for the oscillation limit cycle has a distinct closed ring valley (Mexican hat-like) shape when the fluctuations are small. This global landscape structure leads to attractions of the system to the ring valley.

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We uncovered the underlying energy landscape of the mitogen-activated protein kinases signal transduction cellular network by exploring the statistical natures of the Brownian dynamical trajectories. We introduce a dimensionless quantity: The robustness ratio of energy gap versus local roughness to measure the global topography of the underlying landscape. A high robustness ratio implies funneled landscape. The landscape is quite robust against environmental fluctuations and variants of the intrinsic chemical reaction rates.

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We explored the origin of power law distribution observed in single-molecule conformational dynamics experiments. By establishing a kinetic master equation approach to study statistically the microscopic state dynamics, we show that the underlying landscape with exponentially distributed density of states leads to power law distribution of kinetics. The exponential density of states emerges when the system becomes glassy and landscape becomes rough with significant trapping.

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Three-protein circadian oscillations in cyanobacteria sustain for weeks. To understand how cellular oscillations function robustly in stochastic fluctuating environments, we used a stochastic model to uncover two natures of circadian oscillation: the potential landscape related to steady-state probability distribution of protein concentrations; and the corresponding flux related to speed of concentration changes which drive the oscillations. The barrier height of escaping from the oscillation attractor on the landscape provides a quantitative measure of the robustness and coherence for oscillations against intrinsic and external fluctuations. The difference between the locations of the zero total driving force and the extremal of the potential provides a possible experimental probe and quantification of the force from curl flux. These results, correlated with experiments, can help in the design of robust oscillatory networks.

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Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers.

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We study the origin of robustness of yeast cell cycle cellular network through uncovering its underlying energy landscape. This is realized from the information of the steady-state probabilities by solving a discrete set of kinetic master equations for the network. We discovered that the potential landscape of yeast cell cycle network is funneled toward the global minimum, G1 state. The ratio of the energy gap between G1 and average versus roughness of the landscape termed as robustness ratio ( RR) becomes a quantitative measure of the robustness and stability for the network. The funneled landscape is quite robust against random perturbations from the inherent wiring or connections of the network. There exists a global phase transition between the more sensitive response or less self-degradation phase leading to underlying funneled global landscape with large RR, and insensitive response or more self-degradation phase leading to shallower underlying landscape of the network with small RR. Furthermore, we show that the more robust landscape also leads to less dissipation cost of the network. Least dissipation and robust landscape might be a realization of Darwinian principle of natural selection at cellular network level. It may provide an optimal criterion for network wiring connections and design.