辽宁中部城市群景观动态模拟与预测研究

辽宁中部城市群是我国城镇最密集的地区之一，经过几十年快速的城市发展和工业建设，造成了严重环境污染和生态破坏，区域的景观发生了巨大的变化。本文研究辽宁中部城市群城市空间增长和景观动态，为辽宁中部城市群的科学规划和管理提供决策支持，对辽宁省生态环境与社会经济的可持续发展具有重要的意义。 本文利用3S技术、转移矩阵和景观格局指数方法对辽宁中部城市群1988-- 2004 年的城市增长和景观变化进行了综合分析，采用历史数据对城市增长和景观变化模型SLEUTH进行校正，并对历史时期的城市增长和景观变化进行模拟重建；利用ROC曲线统计、Kappa指数系列和景观格局指数对SLEUTH的模拟结果进行精度评价；在五种不同的预案下对辽宁中部城市群未来（2005-2045年）城市增长和景观动态进行模拟预测。本文得到如下结论： 1. 1988-2004年间，辽宁中部城市群的城市面积持续增长，扩展强度不断增强，1997-2000年的城市扩展强度最大，增长速度最快。城市空间格局的变化表现出阶段性的特征，1988-1997年城市面积的增长速度较慢，结构紧凑，以边缘增长和填充增长为主；1997-2004年城市面积增长较快，城市向外蔓延，城市斑块形状变得复杂，以开发区的飞地式增长和扩散增长为主。 2. 1997-2004年间，辽宁中部城市群的景观变化明显，农村居民点的面积增长最大，其次为城市；林草地的面积减少最大，其次为耕地。各景观类型中城市的增长速度最快，林草地减少的速度最快。辽宁中部城市群的城市增长和景观变化主要集中在中部的城镇密集带。城镇密集带将是未来城市群规划和管理的关键区域。辽宁中部城市群景观格局受人类活动影响增强，景观破碎化程度加大。景观中林草地和耕地的优势地位有所减弱，破碎化程度增加，斑块形状日益复杂；在城镇密集带内，耕地面积流失较大，耕地占景观面积比例减少较快，破碎化程度较大。随着城市化进程的加快和人类活动的增强，辽宁中部城市群表现出复杂的格局变化特征。 3. 1988-2004年，辽宁中部城市群城市增长的主要驱动力是社会经济发展和政策因素，其中人口和经济的高速增长、国家及区域政策导致的城市开发、生 态环境保护政策、城市规划和基础设施建设等因素是城市群城市空间快速增长的主要因素。辽宁中部城市群的景观变化受到自然和人类两大类驱动因素的共同作用。气候、水文、矿产资源等自然驱动力对城市群景观变化的影响也较大。人口增长、城市和村镇聚落增长、农业开发、经济发展、政治政策和工业化等主要的人类驱动力对辽宁中部城市群景观变化影响较大。 4. 利用ROC 曲线统计、Kappa 指数系列和景观格局指数从城市增长总体预测能力、增长数量和空间格局上对SLEUTH 模型的城市增长模拟结果进行精度评估；利用Kappa 指数系列和景观格局指数对SLEUTH的景观变化预测结果进行评价。总体上讲，SLEUTH模型对辽宁中部城市群城市增长和景观动态模拟预测具有良好的可信精度，较好地模拟了1988-2004年的城市增长和1997-2004年城市群的景观动态。 5. SLEUTH 模型效力的主要影响因素包括模型结构、城市发展特征、模型应用的时空尺度和模型输入数据的获取与误差传递等。通过修改模型参数设置、开展模型敏感性与不确定性分析等可以提高SLEUTH 模型的模拟效力，并提出城市分类标准对SLEUTH准确性的影响，通过对部分研究区的检验研究，证明城市分类标准对SLEUTH模型的校正和模拟预测结果影响较大。 6. 基于SLEUTH模型，从城市群城市空间增长、景观要素和社会经济政策等方面设计了五种城市群发展和景观变化预案，即历史趋势预案（Historical Trend, HT），区域开发政策和城市规划预案（Regional development policy and Urban planning policy, RU），生态可持续发展预案（Ecological Sustainable development，ES），两个密集增长预案（Compact Growth，CG1和CG2）等。通过预案分析，考察不同的条件下未来城市群城市空间增长和景观动态特征，研究认为密集的城市增长预案是未来辽宁中部城市群发展的较好预案，为辽宁中部城市群的规划、管理和可持续发展提供决策支持。

Exploring the Origin of Power Law Distribution in Single-Molecule Conformation Dynamics: Energy Landscape Perspectives

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.

Diffusion and single molecule dynamics on biomolecular interface binding energy landscape

We propose a new approach to study the diffusion dynamics on biomolecular interface binding energy landscape. The resulting mean first passage time (MFPT) has 'U'curve dependence on the temperature. It is shown that the large specificity ratio of gap to roughness of the underlying binding energy landscape not only guarantees the thermodynamic stability and the specificity [P.A. Rejto, G.M. Verkhivker, in: Proc. Natl. Acad. Sci. 93 (1996) 8945; C.J. Tsai, S. Kumar, B. Ma, R. Nussinov, Protein Sci. 8 (1999) 1181; G.A. Papoian, P.G. Wolynes, Biopolymers 68 (2003) 333; J. Wang, G.M. Verkhivker, Phys. Rev. Lett. 90 (2003) 198101] but also the kinetic accessibility. The complex kinetics and the associated fluctuations reflecting the structures of the binding energy landscape emerge upon temperature changes. The theory suggests a way of connecting the models/simulations with single molecule experiments by analysing the kinetic trajectories.

Diffusion dynamics, moments, and distribution of first-passage time on the protein-folding energy landscape, with applications to single molecules

We study the dynamics of protein folding via statistical energy-landscape theory. In particular, we concentrate on the local-connectivity case with the folding progress described by the fraction of native conformations. We found that the first passage-time (FPT) distribution undergoes a dynamic transition at a temperature below which the FPT distribution develops a power-law tail, a signature of the intermittent nonexponential kinetic phenomena for the folding dynamics. Possible applications to single-molecule dynamics experiments are discussed.

Modelling the long-term sustainability of indigenous hunting in Manu National Park, Peru: landscape-scale management implications for Amazonia

P> Widespread hunting throughout Amazonia threatens the persistence of large primates and other vertebrates. Most studies have used models of limited validity and restricted spatial and temporal scales to assess the sustainability. We use human-demographi

Coupling of seagrass (Cymodocea nodosa) patch dynamics to subaqueous dune migratio

The coupling between patch dynamics - described by the patch growth (horizontal and vertical), patch mortality, and life-history of Cymodocea nodosa (Ucria) Aschers., and the disturbance caused by the migration of subaqueous dunes over the plants was examined in a shallow NW Mediterranean bay (Alfacs Bay) where this species maintains a patchy cover. C. nodosa shoots survived substantial burial rates (up to 2.4 mm/day) by growing vertically at rates proportional to, albeit four-fold slower than, burial rates. Patch death was caused by erosion as large subaqueous dunes migrated pass the plant patch. Patch growth was fastest over the progressing slope of the dunes ( similar to 2.5 m year super(-1)) and flowering was also stimulated by sand accretion. The time interval between the passage of consecutive dunes, which sets the time window available for patch development, ranged between 2 and 6 years. This time interval allowed C. nodosa to recolonize bare substrata, with patch formation occurring about half a year after the disturbance, and also allowed established shoots to complete their life-cycle and produce seeds and thus enable subsequent recolonization. The time windows available for patch development also set an upper limit to patch size of about 26 m. Significant cross correlations between dune topography and patch dynamics and plant flowering frequency provide evidence that the spatial heterogeneity in the vegetation is closely associated with the disturbance imposed by the migration of sand dunes. The migration of subaqueous dunes maintains C. nodosa in a continuous state of colonization involving spatially asynchronous patch growth and subsequent mortality, which is ultimately responsible for the characteristic patchy landscape of this Bay. 

Simulated morphological landscape of polymer single crystals by phase-field model

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.

Potential Landscape and Flux Framework of Nonequilibrium Networks: Robustness, Dissipation, and Coherence of Biochemical Oscillations

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.

Robustness and dissipation of mitogen-activated protein kinases signal transduction network: Underlying funneled landscape against stochastic fluctuations

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.

Kinetics and Statistical Distributions of Single-Molecule Conformational Dynamics

We developed a coarse-grained yet microscopic detailed model to study the statistical fluctuations of single-molecule protein conformational dynamics of adenylate kinase. We explored the underlying conformational energy landscape and found that the system has two basins of attractions, open and closed conformations connected by two separate pathways. The kinetics is found to be nonexponential, consistent with single-molecule conformational dynamics experiments. Furthermore, we found that the statistical distribution of the kinetic times for the conformational transition has a long power law tail, reflecting the exponential density of state of the underlying landscape. We also studied the joint distribution of the two pathways and found memory effects.

Potential energy landscape and robustness of a gene regulatory network: Toggle switch

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.

Quantifying robustness and dissipation cost of yeast cell cycle network: The funneled energy landscape perspectives

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.

Dominant kinetic paths on biomolecular binding-folding energy landscape

The identification of kinetic pathways is a central issue in understanding the nature of flexible binding. A new approach is proposed here to study the dynamics of this binding-folding process through the establishment of a path integral framework on the underlying energy landscape. The dominant kinetic paths of binding and folding can be determined and quantified. In this case, the corresponding kinetic paths of binding are shown to be intimately correlated with those of folding and the dynamics becomes quite cooperative. The kinetic time can be obtained through the contributions from the dominant paths and has a U-shape dependence on temperature.

Single-molecule dynamics reveals cooperative binding-folding in protein recognition

The study of associations between two biomolecules is the key to understanding molecular function and recognition. Molecular function is often thought to be determined by underlying structures. Here, combining a single-molecule study of protein binding with an energy-landscape-inspired microscopic model, we found strong evidence that biomolecular recognition is determined by flexibilities in addition to structures. Our model is based on coarse-grained molecular dynamics on the residue level with the energy function biased toward the native binding structure ( the Go model). With our model, the underlying free-energy landscape of the binding can be explored. There are two distinct conformational states at the free-energy minimum, one with partial folding of CBD itself and significant interface binding of CBD to Cdc42, and the other with native folding of CBD itself and native interface binding of CBD to Cdc42. This shows that the binding process proceeds with a significant interface binding of CBD with Cdc42 first, without a complete folding of CBD itself, and that binding and folding are then coupled to reach the native binding state.

First-passage time distribution and non-Markovian diffusion dynamics of protein folding

We study the kinetics of protein folding via statistical energy landscape theory. We concentrate on the local-connectivity case, where the configurational changes can only occur among neighboring states, with the folding progress described in terms of an order parameter given by the fraction of native conformations. The non-Markovian diffusion dynamics is analyzed in detail and an expression for the mean first-passage time (MFPT) from non-native unfolded states to native folded state is obtained. It was found that the MFPT has a V-shaped dependence on the temperature. We also find that the MFPT is shortened as one increases the gap between the energy of the native and average non-native folded states relative to the fluctuations of the energy landscape. The second- and higher-order moments are studied to infer the first-passage time distribution. At high temperature, the distribution becomes close to a Poisson distribution, while at low temperatures the distribution becomes a Levy-type distribution with power-law tails, indicating a nonself-averaging intermittent behavior of folding dynamics. We note the likely relevance of this result to single-molecule dynamics experiments, where a power law (Levy) distribution of the relaxation time of the underlined protein energy landscape is observed.