城市化对流域生态系统服务价值空间异质性的影响——以南京市九乡河流域为例

以南京市九乡河流域为研究区域,以2003、2009年两期遥感影像数据为基本信息源,在调整生态系统服务价值系数的基础上,计算流域生态系统服务价值,并利用ArcGIS的空间分析功能,研究流域生态系统服务价值的空间异质性及其变化,以及城市化与生态系统服务价值之间的关系。结果表明:2003-2009年,流域生态系统服务价值损失2.63%,达643.1×10⁴元,其中上游生态系统服务价值增加1.57%,而中游和下游则分别减少2.18%和10.58%,耕地流失是中游、下游和流域总生态系统服务价值减少的主要原因;食物生产、保持土壤等单项生态系统服务价值降低,而水文调节和提供美学功能的生态服务价值增加;九乡河流域生态系统服务价值的空间异质性发生了明显的变化,生态系统服务价值降低的区域主要集中在下游的仙林大学城以及中游靠近主城区的西村一带,而升高的区域主要分布在九乡河沿岸;城市化对流域生态系统服务价值的负效应明显。制定严格的生态规划,加强对流域开发建设的分类指导,是恢复和维护九乡河流域生态系统服务功能的有效途径。     

Continuous versus binary representations of landscape heterogeneity in spatially-explicit models of mobile populations

How a landscape is represented is an important structural assumption in spatially-explicit simulation models. Simple models tend to specify just habitat and non-habitat (binary), while more complex models may use multiple levels or a continuum of habitat quality (continuous). How these different representations influence model projections is unclear. To assess the influence of landscape representation on population models, I developed a general, individual-based model with local dispersal and examined population persistence across binary and continuous landscapes varying in the amount and fragmentation of habitat. In binary and continuous landscapes habitat and non-habitat were assigned a unique mean suitability. In continuous landscapes, suitability of each individual site was then drawn from a normal distribution with fixed variance. Populations went extinct less often and abundances were higher in continuous landscapes. Production in habitat and non-habitat was higher in continuous landscapes, because the range of habitat suitability sampled by randomly dispersing individuals was higher than the overall mean habitat suitability. Increasing mortality, dispersal distance, and spatial heterogeneity all increased the discrepancy between continuous and binary landscapes. The effect of spatial structure on the probability of extinction was greater in binary landscapes. These results show that, under certain circumstances, model projections are influenced by how variation in suitability within a landscape is represented. Care should be taken to assess how a given species actually perceives the landscape when conducting population viability analyses or empirical validation of theory.     

晋西黄土区林草复合界面雨后土壤水分空间变异规律研究

利用统计学方法对晋西黄土区林草复合系统界面上雨后表层（0～10 cm）、亚表层（10～20 cm）和20～40 cm土层土壤水分空间变异性进行研究。结果表明：草地、林地以及二者组成的林草界面的土壤水分含量、变异系数差别均不大,土壤水分含量随着深度的增加而减少,但土壤水分变异系数则相反;移动窗口法分析表明,林草界面对表层和亚表层的土壤水分影响范围均为4.0 m;草地土壤质量含水量的变异函数模型可以拟合成高斯模型,林地和林草界面则可以拟合球状模型,草地土壤水分总体空间异质性要大于林地和林草界面,草地土壤水分变异函数的平均变程为10.96 m,林草界面及林地土壤水分的平均变程分别为5.37 m和4.31 m。对于描述界面土壤水分分布情况,克立格制图直观性强,具有良好效果。     

Factors promoting or inhibiting Turing instability in spatially extended prey-predator systems

The emergence of inhomogeneities in the distributions of the abundances of spatially extended prey-predator systems is investigated. The method of analysis, based on the notion of diffusive (Turing) instability, is systematically applied to nine different models obtained by introducing an extra-factor into the standard Rosenzweig-MacArthur prey-predator model. The analysis confirms that the standard model is critical in the context of Turing instability, and that the introduction of any small amount of the extra-factor can easily promote or inhibit the emergence of spatial patterns.     

Robustness and vulnerability of community irrigation systems: The case of the Taos valley acequias

Traditional economic and policy analysis theory has emphasized the implementation of private or public property rights regimes in order to sustainably manage natural resources. More recent work has challenged this approach by examining the strengths and weakness of common property governance of such resources. This paper contributes to this literature by analyzing the acequia irrigation communities in northern New Mexico. Through statistical analysis, we find that the acequias’ ability to maintain collective-action as estimated by a critical performance function, crop production, is aided by water sharing agreements and access to groundwater, and that it is hampered by property rights fragmentation and urbanization.     

The landscape epidemiology of foot-and-mouth disease in South Africa: A spatially explicit multi-agent simulation

This study aimed at understanding how landscape heterogeneity influences outbreaks of contagious diseases in southern Africa. Landscape attributes influence patterns of movement and behaviour of animal hosts, virus spread and survival, as well as land use practices. A multi-agent simulation was developed to represent the spatial and temporal dynamics of pathogens between human-livestock and wildlife interfaces at the fringe of large wildlife conservation areas. The model represents the three main elements associated with epidemics - populations, space, and time - to simulate direct contacts between wildlife and livestock. The dynamics of these populations emerge from interactions between agents and the landscape. The model was calibrated to represent the transmission of foot-and-mouth disease through direct contact at the border of the Kruger National Park in South Africa. In the region, African buffaloes (Syncerus caffer) act as reservoirs of the virus and spread the infection to domestic cattle bordering the park. We tested the sensitivity of various factors influencing contact rate between buffaloes and cattle, and thus the risk of foot-and-mouth disease transmission. Results show that cattle-buffalo contacts mostly depend on the range of displacements of cattle and buffaloes, as influenced by the landscape configuration, and on the number of fence breakages multiplied by the time between breakage and repair. Contacts take place not only close to water-points but also in grazing areas, within an area up to 6 km from the fence.     

Forecasting population trend from the scaling pattern of occupancy

Forecasting the temporal trend of a focal species, its range expansion or retraction, provides crucial information regarding population viability. To this end, we require the accumulation of temporal records which is evidently time consuming. Progress in spatial data capturing has enabled rapid and accurate assessment of species distribution across large scales. Therefore, it would be appealing to infer the temporal trends of populations from the spatial structure of their distributions. Based on a combination of models from the fields of range dynamics, occupancy scaling and spatial autocorrelation, here I present a model for forecasting the population trend solely from its spatial distribution. Numerical tests using cellular automata confirm a positive correlation, as inferred from the model, between the temporal change in species range sizes and the exponent of the power-law scaling pattern of occupancy. The model is thus recommended for rapid estimation of species range dynamics from a single snapshot of its current distribution. Further applications in biodiversity conservation could provide a swift risk assessment, especially, for endangered and invasive species.     

Predicting modes of spatial change from state-and-transition models

State-and-transition models (STMs) can represent many different types of landscape change, from simple gradient-driven transitions to complex, (pseudo-) random patterns. While previous applications of STMs have focused on individual states and transitions, this study addresses broader-scale modes of spatial change based on the entire network of states and transitions. STMs are treated as mathematical graphs, and several metrics from algebraic graph theory are applied—spectral radius, algebraic connectivity, and the S-metric. These indicate, respectively, the amplification of environmental change by state transitions, the relative rate of propagation of state changes through the landscape, and the degree of system structural constraints on the spatial propagation of state transitions. The analysis is illustrated by application to the Gualalupe/San Antonio River delta, Texas, with soil types as representations of system states. Concepts of change in deltaic environments are typically based on successional patterns in response to forcings such as sea level change or river inflows. However, results indicate more complex modes of change associated with amplification of changes in system states, relatively rapid spatial propagation of state transitions, and some structural constraints within the system. The implications are that complex, spatially variable state transitions are likely, constrained by local (within-delta) environmental gradients and initial conditions. As in most applications, the STM used in this study is a representation of observed state transitions. While the usual predictive application of STMs is identification of local state changes associated with, e.g., management strategies, the methods presented here show how STMs can be used at a broader scale to identify landscape scale modes of spatial change.     

Simulation and analysis of outbreaks of bark beetle infestations and their management at the stand level

Outbreaks of bark beetles in forests can result in substantial economic losses. Understanding the factors that influence the development and spread of bark beetle outbreaks is crucial for forest management and for predicting outbreak risks, especially with the expected global warming. Although much research has been done on the ecology and phenology of bark beetles, the complex interplay between beetles, host trees, beetle antagonists and forest management makes predicting beetle population development especially difficult. Using the recent infestations of the European Spruce Bark Beetle (Ips typographus L. Col. Scol.) in the Bavarian Forest National Park (Germany) as a case study, we developed a spatially explicit agent-based simulation model (SAMBIA) that takes into account individual trees and beetles. This model primarily provides a tool for analysing and understanding the spatial and temporal aspects of bark beetles outbreaks at the stand scale. Furthermore, the model should allow an estimation of the effectiveness of concurrent impacts of both antagonists and management to confine outbreak dynamics in practice. We also used the model to predict outbreak probabilities in various settings. The simulation results indicated a distinct threshold behaviour of the system in response to pressure by antagonists or management of the bark beetle population. Despite the different scenarios considered, we were able to extract from the simulations a simple rule of thumb for the successful control of an outbreak: if roughly 80% of individual beetles are killed by antagonists or foresters, outbreaks will rarely take place. Our model allows the core dynamics of this complex system to be reduced to this inherent common denominator.     

广州主要工业源排放的气态污染物扩散模拟研究

以广州省控工业污染源排放的气态污染物(SO₂、NO_x为主要研究对象,通过中尺度气象模式MM5与空气质量模式CALPUFF耦合,模拟11月典型气象条件下, SO₂和NO_x的扩散传输过程,研究其时空分布特征,并分析省控工业污染源排放对特定区域(主要针对2010年亚运场馆)空气质量的影响。结果表明,主要受典型风速的影响,SO₂和NO_x浓度具有明显的时空分布不均匀性。浓度高峰值主要出现在晚间至凌晨时段,而浓度低峰值主要出现在白天至中午时段。受污染源分布、排放高度和风向的影响,荔湾区和越秀区污染物浓度较高,且在广州西南部形成较明显的污染带;且这些省控污染源对南沙体育馆空气质量有较大影响。 研究结果对广州空气污染来源分析具有一定参考意义。