基于GIS的煤矿区景观格局时空变化分析——以呼伦贝尔市某煤矿为例

在GIS平台和Fragstats 4．1软件的支持下,本文以1989年和1999年的TM影像,2012年的资源三号卫星影像为数据源,利用景观／斑块类型面积、斑块所占景观面积的比例、斑块密度、最大斑块指数、总边缘长度、边缘密度、香农多样性指数、蔓延度指数等景观特征指标,对呼伦贝尔市某煤矿区的景观特征动态变化进行分析。结果显示：该煤矿区20多年来景观格局有了很大变化,景观类型由1989年的水域、草地、未利用地为主导变为2012年以未利用地、草地、耕地为主导,其中因人类工业活动和人工复垦导致工矿景观、道路景观、林地景观和耕地景观面积增加,而原来占绝对优势的水域景观面积则大幅减小。     

基于环境科学优化城市公园的设计研究

基于环境科学优化城市公园的设计研究,中国城市公园存在着环境品质不高的状况.为实现公园景观的整体优化,引入环境科学理论,关注环境与人在行为之间的作用.从对城市公园的设计,制定研究框架,并根据研究结果确立景观设计的策略.关于公园的设计表明,基于环境科学的城市公园设计研究是可行的,它从城市公园空间建设的本质入手,抓住提高城市公园环境品质的实质,才能满足城市公园的设计,同时也可以考虑优化城市公园的设计的推广性.     

南昌典型园林树种燃烧性实验研究

选择南昌西郊和北郊12个园林树种不同器官理化性状测定分析和燃烧试验,根据各树种的含水率、燃点、热值、粗灰分、粗脂肪、木质素、粗纤维、燃烧时间、火烧强度和生物生态学特性等10个因子,应用DPS聚类分析法,对12个园林树种的燃烧性进行了排序,结果表明,难燃树种有5个,依次是：乐昌含笑、珊瑚树、大叶黄杨、白玉兰和海桐;较难燃树种有4个,依次是：女贞、山茶、夹竹桃和含笑;易燃树种有3个,依次是：桂花、巴东木连和红花檵木。为南方防火林带的建设提供了目前公认以外的防火树种。     

黄河中上游能源化工区重点产业发展战略生态风险评价

结合黄河中上游能源化工区重点产业发展战略生态风险宏观性、综合性、复杂性的特点,论文以生态风险景观评价方法及3S技术等为研究手段,综合考虑重点产业发展战略人为风险源及自然风险源,以生态风险受体和终点选择、风险源分析、暴露危害分析、生态风险综合评价及生态风险分区为评价步骤,揭示了重点产业发展战略潜在生态风险空间分异特征。研究结果表明：黄河中上游重点产业战略实施区可划分为三类生态风险监控区,生态风险重点监控区自然风险源分布集中,重点产业人为风险源和自然风险源交织在一起,极易发生生态风险放大效应,生态风险次重点监控区自然生态风险源分布较单一,局部重点产业人为风险源强度增强,将增加区域生态风险水平,生态风险监控区自然生态风险源分布范围较小,潜在生态风险水平相对较低。论文探索了战略环评生态风险评价方法和评价思路,为国内重点产业发展战略生态风险评价提供了借鉴。     

基于RS/GIS的大辽河口湿地景观格局时空变化研究

基于1988、1995、2001和2007年的四期TM数据,应用GIS/RS技术与景观格局分析软件FRAGSTATS,定量分析大辽河口地区湿地景观格局的动态变化。结果表明,自1988年以来,大辽河口地区的湿地面积逐年增加,湿地景观多样性指数和均匀度指数呈现先降后升的趋势,景观破碎化程度增强。湿地类型变化主要表现在大量的自然湿地转化为人工湿地或人工景观,具体表现在转化为建筑用地、水稻田、养殖区。1988~1995年期间,大辽河口地区的环境质量下降,该地区生物生活环境的多样性降低,造成了一些物种种群数量的减少甚至消失;但是自1995年以后,该地区的景观多样性和均匀性升高,抗干扰能力增强,环境质量有所提高。研究区湿地景观格局的动态变化主要是受自然条件和人为活动干扰共同作用的结果。     

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.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

基于景观中性模型的不同竞争力外来种入侵对栖息地毁坏的响应

栖息地毁坏和生物入侵被认为是全球物种多样性的两大威胁,也是当前研究的热点。同时,两者的共同作用将比单独作用所带来的物种多样性丧失更大。本文基于竞争-扩散均衡机制,考虑了外来种的不同竞争力,结合景观中性模型和元胞自动机模型,模拟了外来种入侵对栖息地毁坏（栖息地破碎和面积丧失）的响应。研究结果表明：1）外来种入侵成功将首先威胁竞争力与其相邻的弱物种;2）栖息地毁坏与种间竞争共同决定着外来种入侵的成功与否。当栖息地破碎促进了与外来种竞争力相邻的本地强物种时,将会抑制入侵;当其抑制了与外来种竞争力相邻的本地强物种时,则会促进入侵。当栖息地丧失促进了外来种相邻的本地强物种时,将会抑制入侵;当栖息地丧失抑制了外来种相邻的本地强物种,将一定程度地促进入侵,但随着丧失面积的增加,则转为抑制。因此,为了抑制不同竞争力的外来种入侵,应采取不同的栖息地保护策略,并保护和促进其竞争力相邻的本地强物种。     

流域景观格局对大型底栖动物群落结构的影响研究——以太子河山区段为例

为研究太子河山区段大型底栖动物群落结构与陆地景观因子之间的相互关系,以水生态调查和遥感解译数据为基础,采用主成分分析和回归分析的方法分析了景观格局指数与大型底栖动物群落结构指数的关系,结果表明:大型底栖动物的物种数、EPT科级分类单元数(蜉蝣目、襀翅目、毛翅目)和ASPT指数与景观聚集度指数、最大斑块指数、连通度指数呈显著正相关,与景观香农多样性指数、分离度指数、景观形状指数呈显著负相关。研究结果反映了流域景观斑块的破碎化和人为干扰会对底栖动物群落结构产生负面影响,可以指导以保护河流大型底栖动物群落为目标的流域景观格局优化。     

Multiple structural modifications to dendritic ecological networks produce simple responses

Structural modifications to landscapes affect the ability of organisms to access different habitat patches. There exist, however, very few general methods by which to relate modifications to expectations of effects, and even fewer that enable understanding of how multiple modifications may interact. In the absence of any guiding principles, ecologists have assumed that interactions will result in complex landscape-scale effects. One way of understanding such effects is through rendering a landscape as a graph or network, among the simplest of which are dendritic networks typified by stream systems. Yet even for stream networks, there are no known general principles concerning the nature of interactions between multiple modifications. We developed a model to describe the ability of fish to access and use different habitat patches within dendritic networks. We used mathematical and numerical analyses of the model to investigate how the habitat value of a network is affected by changes in connectivity and habitat quality, and then to examine interactions between multiple modifications. Rather than showing complex interactions, our analytic and simulation-based results show that the combined effect of multiple modifications approximately equals the sum of individually predicted effects. Dendritic networks thus appear to respond far more simply to multiple modifications than has previously been assumed. These results have implications for stream management planning, and offer a firm foundation from which to better understand population processes within dendritic networks.