干旱地区山地荒漠草原阴坡植物群落空间异质性

在样线调查基础上 ,以 Shannon- Wiener指数 ,群落盖度 ,DCA排序轴为区域化随机变量 ,应用半方差、分形分析等方法 ,对干旱地区山坡植物群落空间异质性进行了研究。结果表明 ,在整个山坡尺度上植被格局的空间异质性不大 ,小尺度上植被格局的空间异质性较大 ,尺度依赖性较强 ,不同群落类型的空间格局不同 ,随尺度变化的规律也不一样。严重放牧干扰强烈影响干旱山地植物群落的空间格局 ,生境中的牧道格局 ,斑块格局使山坡植物群落多样性空间异质性更加复杂 ,牧道效应是导致群落空间格局周期性振荡的重要因子。去势对应分析 (DCA)排序第一轴特征值体现了综合生态因子对群落格局作用的结果 ,DCA第二轴半方差变化包含了大量信息 ,其变化具有周期性。群落多样性空间格局强烈影响着干旱山地生态系统的各种生态学过程 ,这些作用机制有待进一步研究     

鄂尔多斯高原沙地植被和两种优势克隆半灌木的空间格局

群落优势种重要值的变化可以表征植被的演替状况。研究了鄂尔多斯高原飞播后不同演替阶段的沙地植被 ,以及两种优势克隆植物羊柴 (H edysarum laeve)和油蒿 (Artemisia ordosica)种群的空间格局。结果表明 :在调查的尺度内 ,群落水平上 ,演替前期和演替中期的植被盖度空间自相关发生的尺度远小于演替后期。随着植被的演替和发育 ,小于抽样尺度 (<1m)的随机变异逐渐增加。暗示着植被盖度空间格局的变化与羊柴种群和油蒿种群在群落中的地位的变化有关。种群水平上 ,小尺度的空间自相关控制着羊柴种群在 3个演替阶段的空间格局 ;处于前 2个演替阶段的油蒿种群 ,空间格局受更大尺度的过程控制 ,并在自身为建群种的群落随机分布。对于 3个演替阶段的油蒿种群而言 ,发生在小于抽样尺度 (<1m)的随机变异都高于相应的羊柴种群。这两种克隆半灌木的种群空间格局的差异可能与二者克隆构型和克隆性的不同有关。本文还根据这两种植物的生物学特性探讨了二者对鄂尔多斯高原沙地植被恢复的不同作用     

退化生态系统植被恢复的生理生态学研究进展

自然的力量和人类的干预导致局部性、区域性甚至全球性植物群落格局的变化。不管这种变化的原因是什么,变化的强度如何,生态系统常常通过自然演替能够恢复它们大部分的特征,亦可以通过人类的介入进行修复,退化生态系统恢复的实质是群落演替,是生态系统结构和功能从简单到复杂、从低级向高级演变的过程,植物生理生态特性研究可以解释退化生态系统植被恢复的一些宏观现象,并为植被恢复构建先锋群落提供可靠的科学依据,本文综述退化生态系统植被恢复的生理生态学研究的进展。     

生态退耕与植被演替的时空格局

综述了多重尺度上生态退耕的时空格局及其对植被演替时空变异影响的研究进展,提出了生态退耕与植被演替的时空格局研究方向.在自然和人文等因子的驱动下,全球兴起了生态退耕的热潮,生态退耕类型正在由人工恢复为主向自然弃耕为主发展.尽管国内外很多学者开始关注不同尺度上生态退耕的时空格局及其影响因子,但是生态退耕的时空变异性研究仍然比较薄弱,尤其缺乏多重尺度上生态退耕时空格局及其驱动因子的综合研究,在很大程度上限制了研究结果外推.研究表明,受到多因子的综合影响,生态退耕后植被演替呈现出复杂多样的时空变化特征;退耕植被演替研究从植物群落结构特征分析为主向群落功能分析发展,从传统的演替过程规律分析转向退耕植被演替的时空变异性分析;相对来说,生态退耕后植被演替的时空分异、影响因子和机制方面的研究比较薄弱.加强多重尺度上生态退耕时空格局与植被演替时空变异的综合研究是将来的研究重点.     

基于无人机影像的草方格生态恢复区植被空间格局演化研究

理解植物群落组成结构的演化对于阐明荒漠化的过程与驱动机制、制定有效的干旱区生态系统恢复措施具有重要价值。研究干旱区植物群落的空间格局的演化过程有助于深入理解荒漠化和生态恢复的过程与机理。目前大量研究关注于植被退化过程中的群落组成结构变化,而对于生态恢复过程中的植物群落空间格局演化的研究尚不多见。干旱区生态系统中植物通常较为稀疏且个体较小,准确提取植物的分布往往需要分辨率极高的遥感数据。近年来,低空无人机遥感技术的快速发展为精细尺度上植被空间格局的研究提供重要技术支持。利用2 cm空间分辨率的低空无人机遥感数据结合地面群落调查,在精细尺度上研究了宁夏沙坡头草方格生态恢复区内植物群落的空间格局变化。研究结果表明,沙坡头地区草方格生态恢复工程实验区域,相对于未实施生态恢复工程的裸露沙丘区域,植物物种多样性和植被盖度显著提高。恢复工程实施4年后,平均植被盖度增加3倍,物种丰富度增加1倍。在植被恢复过程中,随着植被盖度的增加,植被斑块表现出规模上升、破碎化程度下降、形状复杂化、空间自相关减弱等格局特征变化。这些空间格局特征的变化表明大型植被斑块趋于恢复,整体微环境的改善有利于单独生长的植物个体存活,整体上生态系统退化为裸地的风险降低。利用低空无人机遥感手段,对草方格生态恢复工程的植被恢复过程进行了详细、高分辨率的空间格局调查及分析,结合地面群落调查,从多个方面证明了草方格生态恢复措施的有效性。基于无人机的系统格局连续长期监测有助于深入理解干旱区生态恢复机理,对于科学开展荒漠化生态恢复措施也具有重要价值。     

干扰的类型、特征及其生态学意义

干扰是自然界中无时无处不在的一种现象,是在不同时空尺度上偶然发生的不可预知的事件,直接影响着生态系统的结构和功能演替。根据不同分类原则,干扰可以分为自然干扰和人为干扰,内部干扰和外部干扰,物理干扰、化学干扰和生物干扰,局部干扰和跨边界干扰。觉的干扰类型包括火、放牧、土壤物理干扰、土壤物理干扰、土壤化学干扰、践踏、外来种入入侵、洪水泛滥、森林采伐、矿山开发、道路建设和旅游等。干扰主要具有以下一些特点     

森林更新与空间异质性

森林更换是一个重要的生态学过程,一直是森林生态系统动态研究中的主要领域之一。森林更新受物理环境、自然干扰、人为干扰、更新树种特性、树种对干扰的反应等因素及其相互作用的影响。这些生物和非生物的因素随空间和时间而不断变化,构成了森林的空间异质性和时间异质性,使森林更新具有空间和时间上的变化特点,表现在异质性的格局和过程中。探索森林更新与空间异质性的内在规律,可揭示空间格局对更新的生态学过程的潜在作用机制。本文主要综述了近年来有关森林更新与空间异质性研究的主要内容和一些观点,分析了更新中空间异质性的来源,着重评述了空间异质性的生境及更新树种的反应、小尺度的空间异质性与更新动态、林分中光有效性的空间异质性与更新格局以及土壤和更新的空间异质性尺度的关联性等方面的研究。     

1992—2018年内蒙古自治区植被动态演替特征及驱动力

人类的建设与破坏活动是植被动态变化的重要根源之一,利用遥感探究植被演替的量化监测过程及驱动力能够很好揭示人类活动对生态本底的影响。本研究利用欧洲航天局逐年土地覆被数据及地理学信息图谱方法,从植被型组、植被型尺度分析1992—2018年内蒙古自治区植被动态演替方向、演替速度及演替序列,明晰植被演替特征并量化其演替驱动力。结果表明: 研究期间,内蒙古自治区植被数量结构为“植增荒减”,具体年增长速率依次为耕地(353.10 km²)>草原(243.92 km²)>森林(-16.22 km²)>灌丛(-120.37 km²)>荒漠(-556.31 km²),并且空间相邻分布的草原、荒漠、灌丛三者的面积变化存在权衡关系。植被演替空间呈“绿进沙退”格局,演替热点集中于西辽河平原、内蒙古中部荒漠-草原交界处及黄河沿岸;植被演替序列结构复杂,进展、逆行演替相互交错,不同群落演替流量的截流率差距突出,其中,植被型组草原、灌丛与植被型草地、雨养农田群落在演替过程中截获最多演替流量。植被动态演替的核心驱动力为农牧业生产、经济发展水平、人口规模、生态工程、气候变化。作为“植物群落学-景观生态学”的实例研究,本研究结果可为植被格局优化、演替等级提升等生态措施实施空间的划定提供科学依据。     

基于空间分析的保护生物学研究

 保护生物学家和生态学家早就认识到只有准确地辨识保护对象的空间位置、 范围、 及其相邻的关系(例如边缘)和连接度, 以及依存的地形和气候等生境条件, 才能发现生物种群和生境在空间的扩散与收缩、 增长与灭绝的动态, 揭示分布的格局, 从而系统、 全面地了解保护对象和生境的存在状态、 破碎程度和变化趋势, 进行有效的自然保护。 得益于新兴的空间分析技术, 保护生物学自20世纪90年代以来取得了很大的进步。基于空间分析的保护生物学研究是最近10年左右大力发展的新保护生物学的重要基础。 该文结合作者的研究工作,综述了基于空间分析的保护生物学项目, 探讨了保护生物学发展历史、 主要研究方法与应用、 以及今后的可能发展趋势。 在生物多样性的丰度和分布的空间解绎部分,通过综述世界保护监测中心的图解全球生物多样性的工作, 如国家尺度的生物多样性水平、 植物多样性的分布中心和维管束植物科的多样性等的空间分布 ,介绍了 Dobson等图示美国主要濒危植物、 鸟类、 鱼类和软体动物等4个主要类群在县(County) 为基本空间单位上分布的空间格局, 讨论了生物多样性空间解绎的意义。在第二部分用世界资源研究所的全球森林监测(Global forest watch)项目, 美国的国家保护缺失区分析(GAP analysis)项目, 美国林务局的无路自然区域(Roadless area)保护项目和加拿大自然审计(Nature audit)项目, 以及北美和东亚生物多样性空间分布的比较分析和生物入侵的空间分析等具体实例来说明生物多样性空间分布变化比较分析方法的应用。 过去20年来, 面向空间格局的生态学和保护生物学研究得到了快速的发展, 特别是空间格局的描述、 由地统计演变而成的空间统计、 地理信息系统、 基于个体(或栅格)的空间解绎模拟模型、 基于斑块(Patch)的种群理论及其发展(如复合种群理论, 源 汇模型等)等。在第三部分, 以美国森林破碎度空间格局分析和美国太平洋西北演替后期森林的空间格局分析为例, 介绍了空间格局分析在保护生物学中的应用。 同时介绍了澳大利亚保护生态学家Lindenmayer 和美国著名景观生态学家Franklin 2002年提出的模板(Matrix)保护理论,把保护的眼光不局限在面积不多而且分散的保护区中,应注意景观模板和保护区相邻的原生区域的综合保护, 这样将大大扩展保护的范围, 并且平衡保护与发展的关系。最后, 介绍了在保护生物学中已有一定应用的空间模型和模拟, 包括了空间解绎模型(Spatial explicit model)、 基于过程(Process-based)的空间模拟模型、 面向代理(Agent-based)的空间适应模拟模型(SWAM)以及与此有关的动态全球植被模型(DGVM)。 通过上面的讨论和综述, 预测一个新的保护生物学的分支: 空间保护生物学, 已经逐渐成熟问世, 这门基于现代信息技术和空间技术的新学科已经而且还将为全球生物多样性的研究和保育作出重大的贡献。     

区域尺度生态修复空间辨识研究进展

区域尺度辨识生态修复空间是进行生态恢复与重建的重要前提,对区域生态文明建设和可持续发展具有重要作用。如何构建科学合理、面向政策和民众需求的生态修复空间辨识指标体系,目前已成为生态学研究的热点问题之一。系统梳理生态空间评价理论,综合构建生态修复空间辨识框架,包括评价对象的选择、评价指标筛选的原则、指标体系构建的主要方法和评价指标权重设定等方面,在区域生态评价的基础上,强调政策目标、民众需求,构建了生态质量、生态系统服务、生态系统健康3个方面18个指标,能够较全面反映区域生态空间主要特征,以期为构建区域尺度生态修复空间辨识指标体系提供参考,为生态恢复和重建提供科学依据。研究还展望了区域尺度下生态修复空间辨识的重点发展方向,即加强复合生态系统理论的应用,统筹社会、经济、自然因子开展综合评价,并推动多尺度评价结果的融合与应用。     

不同放牧强度下冷蒿种群小尺度空间格局

时间、空间格局的发展和维持及其对种群和生态系统的影响一直是生态学研究的中心议题 ,这些问题的核心是观察的尺度怎样影响格局的描述。冷蒿 (Artemisia frigida)种群伴随着典型草原退化演替的各个阶段 ,对其所在群落的结构和功能具有重要的影响。应用 Ripley's K函数以及蒙特卡罗 (Monte Carlo)随机模拟方法 ,定量分析了 4种放牧强度下冷蒿种群在 0～10 0 cm尺度上的空间格局及其随尺度的变化规律 ;研究了放牧对冷蒿种群空间格局的影响以及冷蒿在放牧胁迫下的生态适应对策。并以放牧条件下冷蒿的生活史特征、生态适应对策以及群落内植物种间的相互作用为基础 ,探讨产生和维持这些格局的机理。研究结果表明 :1放牧对冷蒿种群空间格局有显著影响。同一放牧强度下冷蒿种群在不同尺度 (0～ 10 0 cm)上的空间格局存在显著差异 ;2在 0～ 10 0 cm尺度上 ,无牧、轻牧条件下冷蒿种群的空间格局为聚集分布 ;中牧条件下在 0～ 6 0 cm尺度上冷蒿种群的空间格局为聚集分布 ,而在 6 0～ 10 0 cm尺度上为均匀分布 ;重牧条件下在 0～ 72 cm尺度上冷蒿种群的空间格局为聚集分布 ,而在 72～ 10 0 cm尺度上为均匀分布 ,这与其自身的生物学特性和种群对放牧压力的生态适应对策密切相关 ;3放牧活动的加剧改变了群落中的各种     

Successional theories

Succession is a fundamental concept in ecology because it indicates how species populations, communities, and ecosystems change over time on new substrate or after a disturbance. A mechanistic understanding of succession is needed to predict how ecosystems will respond to land-use change and to design effective ecosystem restoration strategies. Yet, despite a century of conceptual advances a comprehensive successional theory is lacking. Here we provide an overview of 19 successional theories (‘models’) and their key points, group them based on conceptual similarity, explain conceptual development in successional ideas and provide suggestions how to move forward. Four groups of models can be recognised. The first group (patch & plants) focuses on plants at the patch level and consists of three subgroups that originated in the early 20th century. One subgroup focuses on the processes (dispersal, establishment, and performance) that operate sequentially during succession. Another subgroup emphasises individualistic species responses during succession, and how this is driven by species traits. A last subgroup focuses on how vegetation structure and underlying demographic processes change during succession. A second group of models (ecosystems) provides a more holistic view of succession by considering the ecosystem, its biota, interactions, diversity, and ecosystem structure and processes. The third group (landscape) considers a larger spatial scale and includes the effect of the surrounding landscape matrix on succession as the distance to neighbouring vegetation patches determines the potential for seed dispersal, and the quality of the neighbouring patches determines the abundance and composition of seed sources and biotic dispersal vectors. A fourth group (socio-ecological systems) includes the human component by focusing on socio-ecological systems where management practices have long-lasting legacies on successional pathways and where regrowing vegetations deliver a range of ecosystem services to local and global stakeholders. The four groups of models differ in spatial scale (patch, landscape) or organisational level (plant species, ecosystem, socio-ecological system), increase in scale and scope, and reflect the increasingly broader perspective on succession over time. They coincide approximately with four periods that reflect the prevailing view of succession of that time, although all views still coexist. The four successional views are: succession of plants (from 1910 onwards) where succession was seen through the lens of species replacement; succession of communities and ecosystems (from 1965 onwards) when there was a more holistic view of succession; succession in landscapes (from 2000 onwards) when it was realised that the structure and composition of landscapes strongly impact successional pathways, and increased remote-sensing technology allowed for a better quantification of the landscape context; and succession with people (from 2015 onwards) when it was realised that people and societal drivers have strong effects on successional pathways, that ecosystem processes and services are important for human well-being, and that restoration is most successful when it is done by and for local people. Our review suggests that the hierarchical successional framework of Pickett is the best starting point to move forward as this framework already includes several factors, and because it is flexible, enabling application to different systems. The framework focuses mainly on species replacement and could be improved by focusing on succession occurring at different hierarchical scales (population, community, ecosystem, socio-ecological system), and by integrating it with more recent developments and other successional models: by considering different spatial scales (landscape, region), temporal scales (ecosystem processes occurring over centuries, and evolution), and by taking the effects of the surrounding landscape (landscape integrity and composition, the disperser community) and societal factors (previous and current land-use intensity) into account. Such a new, comprehensive framework could be tested using a combination of empirical research, experiments, process-based modelling and novel tools. Applying the framework to seres across broadscale environmental and disturbance gradients allows a better insight into what successional processes matter and under what conditions.     

Latitudinal patterns of forest ecosystem stability across spatial scales as affected by biodiversity and environmental heterogeneity

Our planet is facing a variety of serious threats from climate change that are unfolding unevenly across the globe. Uncovering the spatial patterns of ecosystem stability is important for predicting the responses of ecological processes and biodiversity patterns to climate change. However, the understanding of the latitudinal pattern of ecosystem stability across scales and of the underlying ecological drivers is still very limited. Accordingly, this study examines the latitudinal patterns of ecosystem stability at the local and regional spatial scale using a natural assembly of forest metacommunities that are distributed over a large temperate forest region, considering a range of potential environmental drivers. We found that the stability of regional communities (regional stability) and asynchronous dynamics among local communities (spatial asynchrony) both decreased with increasing latitude, whereas the stability of local communities (local stability) did not. We tested a series of hypotheses that potentially drive the spatial patterns of ecosystem stability, and found that although the ecological drivers of biodiversity, climatic history, resource conditions, climatic stability, and environmental heterogeneity varied with latitude, latitudinal patterns of ecosystem stability at multiple scales were affected by biodiversity and environmental heterogeneity. In particular, α diversity is positively associated with local stability, while β diversity is positively associated with spatial asynchrony, although both relationships are weak. Our study provides the first evidence that latitudinal patterns of the temporal stability of naturally assembled forest metacommunities across scales are driven by biodiversity and environmental heterogeneity. Our findings suggest that the preservation of plant biodiversity within and between forest communities and the maintenance of heterogeneous landscapes can be crucial to buffer forest ecosystems at higher latitudes from the faster and more intense negative impacts of climate change in the future.     

Applying lessons from ecological succession to the restoration of landslides

Landslides are excellent illustrations of the dynamic interplay of disturbance and succession. Restoration is difficult on landslide surfaces because of the high degree of spatial and temporal heterogeneity in soil stability and fertility. Principles derived from more than a century of study of ecological succession can guide efforts to reduce chronic surface soil erosion and restore both biodiversity and ecosystem function. Promotion of the recovery of self-sustaining communities on landslides is feasible by stabilization with native ground cover, applications of nutrient amendments, facilitation of dispersal to overcome establishment bottlenecks, emphasis on functionally redundant species and promotion of connectivity with the adjacent landscape. Arrested succession through resource dominance by a single species can be beneficial if that species also reduces persistent erosion, yet the tradeoff is often reduced biodiversity. Restoration efforts can be streamlined by using techniques that promote successional processes.     

基于植物多样性的生态系统恢复动力学原理

生态系统恢复动力学是生态学的重要问题.本研究利用岛屿生物地理学、植物群落演替、生物多样性维持机制及生态系统功能等有关理论,推导了生态系统恢复动力学模型,并用半湿润常绿阔叶林次生演替阶段数据作了初步验证.基于动力学模型讨论了动力学原理.结果表明,生态系统恢复的动力学过程决定于生态系统恢复力F1、干扰力F2和环境阻力F3的综合作用.植物多样性恢复速度的变率与植物种丰富度呈反比,与生态系统恢复总动力F呈正比.生态系统恢复力F1和环境阻力F3是初始物种丰富度s0、特定地理区域资源环境状况的函数.干扰力是干扰强度系数b和物种丰富度s的函数.当生态系统存在有害干扰的条件下,物种丰富度不能达到生态系统最高物种丰富度sm.动力学模型显示,初始物种丰富度s0越小,生态系统恢复过程越具有逻辑斯蒂性.建立了生态系统恢复力、环境阻力和干扰力的计算模型和植物多样性、干扰对生态系统恢复的作用模型.生态系统恢复动力模型显示,植物多样性能增加生态系统恢复力,促进生态系统稳定性.     

Fractal analysis of plant spatial patterns: a monitoring tool for vegetation transition shifts

Spatial heterogeneity, like species diversity, is an important ecosystem property. We examine the effects of land use on the diversity and spatial distribution of plants in five semi-arid communities of eastern Spain using non-linear methods to assess the spatialtemporal dynamics of plant populations. Specifically, we are interested in detecting long-term structural changes or drift in an ecosystem before it is too late to prevent irreversible degradation. Fractal analysis is used to characterize the complexity of plant spatial patterns and Information Theory indices are used to measure change in information flow with land use changes and soil substrate. We found that grazing favored diversity and heterogeneity of species distribution on the impoverished gypsum and saline substrate community, as opposed to the detrimental effect of grazing in the Alpha steppe community. Indeed, old-field succession after 30 years of abandonment showed a recovery of species diversity but not the spatial structure of the vegetation. Further, Information Fractal Dimension, representing the unpredictability of plant spatial patterns in the landscape, increased as we moved from a highly diverse to a less diverse community, revealing the change to a more scattered and homogeneous spatial plant distribution. The Information Fractal Dimension is a good estimator of ecosystem disturbance, independent of scale, and thus can be used to monitor ecosystem dynamics.     

Disturbance-level-dependent post-disturbance succession in a Eurasian steppe

Anthropogenic disturbances may decrease as we take measures to control them. However, the patterns and mechanisms of post-disturbance ecosystem succession have rarely been studied. Here we reported that disturbance level determined the importance of stochastic relative to deterministic changes in ecosystem components (plant community composition, soil microbial community composition, and soil physicochemical indices), and thus predefined the pattern of post-disturbance ecosystem succession. We proposed a theoretical framework with five disturbance levels corresponding to distinct succession patterns. We conducted a nitrogen addition experiment in a temperate steppe, monitored these ecosystem components during “disturbance” treatment (2010–2014) and post-treatment “succession” (2014–2018). The disturbance level experienced by each component in each treatment was inferred by fitting the observed succession patterns into the theoretical framework. The mean disturbance level of these components was found to increase quadratically with nitrogen addition rate. This was because increasing nitrogen addition reduced the importance of stochastic relative to deterministic changes in these components, and these changes had a quadratic relationship with disturbance level. Overall, our results suggested that by monitoring the importance of stochastic relative to deterministic changes in an ecosystem, we can estimate disturbance levels and predict succession patterns, as well as propose disturbance-level-dependent strategies for post-disturbance restoration.

     

Ecosystem stability in space: α, β and γ variability

The past two decades have seen great progress in understanding the mechanisms of ecosystem stability in local ecological systems. There is, however, an urgent need to extend existing knowledge to larger spatial scales to match the scale of management and conservation. Here, we develop a general theoretical framework to study the stability and variability of ecosystems at multiple scales. Analogously to the partitioning of biodiversity, we propose the concepts of alpha, beta and gamma variability. Gamma variability at regional (metacommunity) scale can be partitioned into local alpha variability and spatial beta variability, either multiplicatively or additively. On average, variability decreases from local to regional scales, which creates a negative variability–area relationship. Our partitioning framework suggests that mechanisms of regional ecosystem stability can be understood by investigating the influence of ecological factors on alpha and beta variability. Diversity can provide insurance effects at the various levels of variability, thus generating alpha, beta and gamma diversity–stability relationships. As a consequence, the loss of biodiversity and habitat impairs ecosystem stability at the regional scale. Overall, our framework enables a synthetic understanding of ecosystem stability at multiple scales and has practical implications for landscape management.     

交通通达度对生态系统健康的影响——以长江中游城市群为例

完善的交通基础设施网络是形成高度同城化和高度一体化城市群的前提和基础,科学探测城市群地区交通通达度对生态系统健康状况的影响机理对城市群地区生态系统保护以及区域可持续发展具有重要实践意义和价值。基于多源数据分别测度了1995—2015年长江中游城市群交通通达度以及生态系统健康水平,并借助双变量空间自相关与空间回归模型从全局和局部的角度揭示了交通通达度对生态系统健康的影响机理。研究结果显示：(1)研究期间长江中游城市群生态系统健康状况总体呈现降低态势,山区生态系统健康水平显著高于平原地区;(2)双变量空间自相关分析结果显示交通通达度和生态系统健康水平之间存在显著的空间依赖性,二者之间主要的关系类型包括低交通通达度水平-低生态系统健康水平、高交通通达度水平-低生态系统健康水平和低交通通达度水平-高生态系统健康水平三种类型;(3)空间回归结果显示交通通达度的增加会导致生态系统健康状况的恶化,而且交通通达度对生态系统健康的影响具有显著的空间异质性。研究发现可以为长江中游城市群地区生态系统健康保护宏观调控政策制定以及差异化管控政策制定提供科学依据。     

植被的镶嵌体系

植被是一个镶嵌体，其镶嵌单位具有特定的时空尺度和等级系统．在空间上构成了镶嵌群落、镶嵌生态系统的镶嵌体或镶嵌复合体等静态镶嵌．在时间上则构成了镶嵌季相、镶嵌更新和镶嵌演替等动态镶嵌．静态镶嵌和动态镶嵌是相对的并彼此密切相关．它们构成了一个完整的植被镶嵌体系．