土壤微生物多样性通过共现网络复杂性表征高寒草甸生态系统多功能性

土壤微生物多样性在生态系统功能的维持方面发挥着至关重要的作用,但是土壤生物多样性与生态系统功能（Biodiversity-ecosystem function,BEF）关系仍存在争议。以往的研究多基于简单多样性指标（如物种数、香浓多样性指数等）对BEF关系进行探究,忽略了物种间复杂的相互作用在BEF关系中的重要性。以青藏高原米拉山高寒草甸为研究对象,使用Illumina MiSeq高通量测序技术测定了6个海拔高度（3755 m、3994 m、4225 m、4534 m、4900 m、5120 m）土壤细菌和真菌群落特征,分析了简单微生物多样性指标（物种数）和共现网络复杂性与生态系统多功能性（Ecosystem multifunctionality,EMF）的关系,以期进一步揭示微生物多样性与EMF的关系。共现网络分析表明,表征土壤细菌和真菌网络复杂性的节点（Node）和边（Link）沿海拔高度的升高显著下降（P<0.05）。土壤细菌和真菌的多样性和网络复杂性均沿海拔的升高显著下降（P<0.05）,而且网络复杂性比相应的多样性下降明显。在未控制环境因素时,真菌和细菌的多样性和网络复杂性均与EMF显著正相关（P<0.05）;其中真菌和细菌网络复杂性对EMF的解释度高于相应多样性对EMF的解释度。通过偏回归分析（Partial least squares regression,PLSR）控制年降水、年均温、黏粒含量、盐基离子和酸性离子等气候及土壤环境因子影响后,土壤细菌和真菌物种多样性与EMF的显著正相关关系变为不相关（P>0.05）,而网络复杂性与EMF的显著正相关关系（P<0.05）仍然存在。利用方差分解分析（Variance partition analysis,VPA）将环境因子纳入对EMF的影响后发现,土壤微生物网络复杂性和环境因子对EMF变化的解释度可达80%,高于土壤微生物多样性与环境因子对EMF变化的解释度。结构方程模型（Structural equation model,SEM）分析进一步显示,土壤细菌多样性和真菌多样性通过促进对应共现网络的复杂性,间接对EMF产生正向影响。综上所述,相较于简单的多样性指标,土壤微生物网络复杂性对EMF具有更好的解释度和预测性,微生物多样性主要通过促进网络复杂性间接正向影响EMF。研究结果扩展了BEF关系的研究,证明微生物物种多样性主要通过促进对应的网络复杂性维持EMF。     

生态系统多功能性的指标选择与驱动因子: 研究现状与展望

全球变化和人类活动正以空前的速度在世界范围内改变着生物多样性, 这导致了全球生物多样性的锐减以及生产力的下降、病虫害的增加和抗入侵能力的减弱等生态问题。近30年来, 生态学家开始对于生物多样性的持续丧失是否以及如何影响生态系统功能的问题越来越感兴趣, 生物多样性与生态系统功能(biodiversity and ecosystem functioning, BEF)关系的研究应运而生, 并成为生态学研究的热点之一。但长期以来, 研究者更多地关注单一生态系统功能, 而忽略了生态系统能够同时提供多种生态系统功能的能力, 即生态系统多功能性(ecosystem multifunctionality, EMF)。本文综述了EMF研究中功能指标的选择、生物多样性的不同维度、微生物多样性对EMF的影响以及其他非生物因子对EMF的驱动等进展。因只考虑单一功能可能会低估生物多样性对整体生态系统功能的影响, 故生物多样性与生态系统多功能性(BEMF)关系的研究成为BEF关系研究的重点。近年来, BEMF关系的研究发展较快, 在不同生态系统(包括水生、草地、森林、旱地、农业等)、不同研究尺度(从区域到全球尺度)、BEMF关系的驱动机制(从单一驱动机制到多种驱动机制共同作用)、研究方法(包括新概念以及新的量化方法的提出和应用)等方面均取得了新的进展。但仍有不足之处, 如对于EMF研究中功能指标的选取没有统一的标准、对地下微生物多样性的关注度不够、涉及多营养级水平下的BEMF关系研究较少、驱动EMF的机制仍存在争论等。未来应加强对于功能指标选取的标准研究, 综合分析地上、地下生物多样性以及非生物因子对EMF的整体影响, 加强生态系统多服务性(ecosystem multiserviceability, EMS)方法的研究和应用。     

土壤微生物网络复杂性预测黄土高原造林恢复生态系统多功能性

人类活动导致黄土高原土地退化和生物多样性丧失,进而降低了生态系统功能。人工造林是该区域退化土地恢复的重要措施。现有的生态修复研究通常侧重于微生物群落物种多样性的恢复对单一生态系统功能的影响,而忽略了微生物间存在的相互作用与生态系统多功能性(Ecosystem multifunctionality, EMF)的关系。为探究造林恢复过程中土壤微生物多样性和网络复杂性与EMF的关系,本研究采用时空代换法(space-time substitution method),沿50年造林恢复时间序列,分析了黄土高原地区造林恢复对土壤微生物群落多样性、土壤微生物网络复杂性以及与土壤养分循环相关的10个生态系统功能指标的影响,明确了土壤微生物群落特征与EMF的关系。结果表明,随造林恢复时间序列的增加,土壤微生物群落的综合多样性、网络复杂性和EMF均呈现出显著增加后下降的趋势(P<0.05),其中土壤微生物综合多样性和网络复杂性在第8年达到最高值,EMF在第20年达到最大值。在未控制土壤环境因素时,细菌和古菌多样性与EMF无显著相关性,真菌多样性与EMF呈显著正相关(P<0.001);土壤微生...     

羌塘高寒草地物种多样性与生态系统多功能关系格局

传统的生物多样性-生态系统功能研究大多侧重于单一生态系统功能与物种多样性的关系,忽略了生态系统的重要价值在于其能够同时提供多种功能或服务,即生态系统的多功能性。基于藏北羌塘高寒草地样带调查数据,选取植被地上生物量、地下生物量、土壤全氮、硝态氮及铵态氮含量、土壤全磷含量、土壤有机碳储量等7个与植物生长、养分循环、土壤有机碳蓄积相关的参数来表征生态系统多功能性。采用上述参数转换为Z分数后的平均值计算多功能性指数(M)。分析了不同生物多样性指数与生态系统多功能指数的关系以及年降水量和年均温度对物种多样性和生态系统多功能性指数的影响。结果表明,物种丰富度指数与生态系统多功能性之间呈极显著的正相关关系,Shannon-wiener和Simpson物种多样性指数也与多功能性指数间呈显著的正相关,但多功能性指数与Pielou均匀度指数没有表现出明显的相关关系。物种丰富度与表征植物生长、养分循环以及土壤有机碳蓄积的生态系统功能指数间也均呈极显著的正相关关系。降水格局显著影响羌塘高原物种丰富度和生态系统多功能指数,二者均随年降雨量的增加而显著增加,但物种多样性指数并未与年降水量呈现显著相关关系。研究强调了群落物种丰富度即群落物种数量对维持生态系统多功能性的重要意义,这意味着由于人类活动导致的物种丧失可能会给藏北高寒草地生态系统多功能和生态服务带来更为严重的后果。就退化草地恢复或草地可持续管理而言,在藏北羌塘地区,本地植物种的物种丰富度恢复和维持应作为重要目标之一。     

生物多样性与生态系统多功能性: 进展与展望

全球变化和人类活动引起的生物多样性丧失将会对生态系统功能产生诸多不利影响, 如生产力下降、养分循环失衡等。因此, 始于20世纪90年代的生物多样性与生态系统功能(biodiversity and ecosystem functioning, BEF)研究一直是生态学界关注的热点。然而, 随着研究的深入, 人们逐步认识到生态系统并非仅仅提供单个生态系统功能, 而是能同时提供多个功能, 这一特性被称之为“生态系统多功能性” (ecosystem multifunctionality, EMF)。尽管有此认识, 但直到2007年, 研究者才开始定量描述生物多样性与生态系统多功能性(biodiversity and ecosystem multifunctionality, BEMF)的关系。目前, BEMF研究已成为生态学研究的一个重要议题, 但仍存在很多问题和争议, 如缺少公认的多功能性测度标准、生态系统不同功能之间的权衡问题等。本文概述了BEMF研究的发展历程、常用的量化方法、EMF的维持机制和不同研究视角下BEMF的关系。针对现有研究中的不足, 本文还总结了需要进一步深入研究的地方, 特别强调了优化EMF测度方法和研究不同维度生物多样性与EMF间关系的重要性, 以期对未来的BEMF研究有所帮助。     

Testing the effects of diversity on ecosystem multifunctionality using a multivariate model

Most ecosystems provide multiple services, thus the impact of biodiversity losses on ecosystem functions may be considerably underestimated by studies that only address single functions. We propose a multivariate modelling framework for quantifying the relationship between biodiversity and multiple ecosystem functions (multifunctionality). Our framework consolidates the strengths of previous approaches to analysing ecosystem multifunctionality and contributes several advances. It simultaneously assesses the drivers of multifunctionality, such as species relative abundances, richness, evenness and other manipulated treatments. It also tests the relative importance of these drivers across functions, incorporates correlations among functions and identifies conditions where all functions perform well and where trade‐offs occur among functions. We illustrate our framework using data from three ecosystem functions (sown biomass, weed suppression and nitrogen yield) in a four‐species grassland experiment. We found high variability in performance across the functions in monocultures, but as community diversity increased, performance increased and variability across functions decreased.     

Limits on ecosystem trophic complexity: insights from ecological network analysis

Articulating what limits the length of trophic food chains has remained one of the most enduring challenges in ecology. Mere counts of ecosystem species and transfers have not much illumined the issue, in part because magnitudes of trophic transfers vary by orders of magnitude in power‐law fashion. We address this issue by creating a suite of measures that extend the basic indexes usually obtained by counting taxa and transfers so as to apply to networks wherein magnitudes vary by orders of magnitude. Application of the extended measures to data on ecosystem trophic networks reveals that the actual complexity of ecosystem webs is far less than usually imagined, because most ecosystem networks consist of a multitude of weak connections dominated by a relatively few strong flows. Although quantitative ecosystem networks may consist of hundreds of nodes and thousands of transfers, they nevertheless behave similarly to simpler representations of systems with fewer than 14 nodes or 40 flows. Both theory and empirical data point to an upper bound on the number of effective trophic levels at about 3–4 links. We suggest that several whole‐system processes may be at play in generating these ecosystem limits and regularities.     

生态网络分析方法研究综述

生态网络分析方法是分析生态系统作用关系、辨识系统内在、整体属性的一种有效的系统分析方法。总结了生态网络分析方法的主要研究成果:网络结构特性、网络稳定性、网络上升性、网络效能等;介绍了构建生态网络模型过程和群落构建规则;以德国西部城市诺伊斯河口氮循环为例,介绍David K是如何运用生态网络分析方法来揭示网络中的微动力流循环规律。生态网络分析方法的主要贡献:(1)对人们凭经验感知的生态系统分室间的关联关系,采用了严密的数学模型和推导进行了描述和证明;(2)为生态系统的微动力流循环的研究提供了方法,对生态系统中物质流的间接循环作用进行了科学论证;(3)不仅为分析生态系统提供了一种科学的数学方法,而且,它为探索生态系统提供了不同与牛顿世界观的崭新的认识论。总结与回顾生态网络分析方法,有益于该方法的运用和进一步完善。     

Investigating the evolution of floras: problems and progress — An introduction

The Cape flora of southern Africa is a remarkable hotspot for plant species diversity and endemism. At a meeting in Zurich in 2004 progress in understanding the evolution of this diversity was reviewed. In this symposium, four papers presenting several of the methods used in this investigation were reported. These papers deal with molecular dating methods, the reconstruction of ancestral habitats, with possible speciation scenarios for the Cape flora, and the importance of the correct sampling strategies.     

Eco-evolutionary feedbacks in community and ecosystem ecology: interactions between the ecological theatre and the evolutionary play

Interactions between natural selection and environmental change are well recognized and sit at the core of ecology and evolutionary biology. Reciprocal interactions between ecology and evolution, eco-evolutionary feedbacks, are less well studied, even though they may be critical for understanding the evolution of biological diversity, the structure of communities and the function of ecosystems. Eco-evolutionary feedbacks require that populations alter their environment (niche construction) and that those changes in the environment feed back to influence the subsequent evolution of the population. There is strong evidence that organisms influence their environment through predation, nutrient excretion and habitat modification, and that populations evolve in response to changes in their environment at time-scales congruent with ecological change (contemporary evolution). Here, we outline how the niche construction and contemporary evolution interact to alter the direction of evolution and the structure and function of communities and ecosystems. We then present five empirical systems that highlight important characteristics of eco-evolutionary feedbacks: rotifer–algae chemostats; alewife–zooplankton interactions in lakes; guppy life-history evolution and nutrient cycling in streams; avian seed predators and plants; and tree leaf chemistry and soil processes. The alewife–zooplankton system provides the most complete evidence for eco-evolutionary feedbacks, but other systems highlight the potential for eco-evolutionary feedbacks in a wide variety of natural systems.     

Quantifying a virtual water metabolic network of the Metropolitan District of Quito,Ecuador using ecological network methods

Current human population is mostly located in urban areas making cities the center of attention in terms of achieving sustainability goals. Evidence shows that ecosystems have evolved over time toward a balanced configuration between resource efficiency and functional redundancy. For this reason, they are exemplary models to follow in terms of sustainability. Here, we apply similar ecological network-based methods to study the virtual water metabolic network (VWMN) of the Metropolitan District of Quito. The VWMN was obtained using novel bottom-up, survey-based methods to generate the urban metabolic network. We compare the VWMN results with those previously obtained from ecological food webs, to learn if there are insights about the sustainability of urban metabolic processes. We conclude that VWMN does not exhibit characteristics observed in sustainable ecological networks because this socioeconomic network exhibits higher levels of path redundancy. Urban metabolism studies are gaining in popularity as a research tool aimed at informing resource management and this is one of the first covering a city in the Global South and using a bottom-up survey method.     

杭州湾北岸大型围隔海域人工生态系统的能量流动和网络分析

根据2006年在杭州湾北岸大型围隔海域进行的生态调查数据,利用EwE软件构建围隔海域人工生态系统的能量流动模型.模型由13个功能组构成,分别是肉食性鱼类、底栖捕食鱼类、浮游动物性鱼类、草食性鱼类、蟹类、虾类、软体动物、底栖动物、肉食性浮游动物、植食性浮游动物、大型藻类、浮游植物和有机碎屑,每一组都代表在生态系统中具有相似地位的有机体,基本覆盖了该人工生态系统能量流动的主要过程.能量流动分析表明,围隔海域人工生态系统中能量流动主要以碎屑食物链途径为主,其中植食性浮游动物在能量从低级向高层次转换中起关键作用.人工生态系统的营养级范围为1.00～3.90级,系统的能量流动主要有6级,来自初级生产者的能流效率为9.4%,来自碎屑的转换效率为9.8%,平均能量转换效率为9.6%.经生态网络分析,直接来源于碎屑的比例占总流量的57%,而直接来源于初级生产者的比例为43%,生态系统特征参数:总初级生产计算量/总呼吸量(TPP/TR)、系统物质和能量循环率(FCI)和系统聚合度(A)值分别为2.672、0.25、0.315,表明围隔海域人工生态系统目前正处于发育时期.该研究为首次利用Ecopath模型分析大型围隔海域人工生态系统的结构和能量流动,旨在为富营养化近岸海域的生态修复提供理论依据.     

SCNIC: Sparse correlation network investigation for compositional data

Microbiome studies are often limited by a lack of statistical power due to small sample sizes and a large number of features. This problem is exacerbated in correlative studies of multi-omic datasets. Statistical power can be increased by finding and summarizing modules of correlated observations, which is one dimensionality reduction method. Additionally, modules provide biological insight as correlated groups of microbes can have relationships among themselves. To address these challenges, we developed SCNIC: Sparse Cooccurrence Network Investigation for compositional data. SCNIC is open-source software that can generate correlation networks and detect and summarize modules of highly correlated features. Modules can be formed using either the Louvain Modularity Maximization (LMM) algorithm or a Shared Minimum Distance algorithm (SMD) that we newly describe here and relate to LMM using simulated data. We applied SCNIC to two published datasets and we achieved increased statistical power and identified microbes that not only differed across groups, but also correlated strongly with each other, suggesting shared environmental drivers or cooperative relationships among them. SCNIC provides an easy way to generate correlation networks, identify modules of correlated features and summarize them for downstream statistical analysis. Although SCNIC was designed considering properties of microbiome data, such as compositionality and sparsity, it can be applied to a variety of data types including metabolomics data and used to integrate multiple data types. SCNIC allows for the identification of functional microbial relationships at scale while increasing statistical power through feature reduction.     

道路网络理论在景观破碎化效应研究中的运用——以浙江省公路网络为例

随着道路的不断建设,道路网络对自然生态环境的影响效应日益显著,众多生态学家开始从道路网络与自然景观的空间位置入手,研究不同组织形式的道路网络对自然生态系统产生的不同影响,从而探讨生态最优化的道路网络组织模式.旨在研究浙江省的干线公路网络对自然生态环境造成的影响,从而探讨生态最优化的道路网络组织模式.总结了道路网路理论的最新研究进展,介绍了由R. T. T. Forman和J. A. G. Jaeger提出的两个道路网络影响模型;随后运用Forman教授的道路网络理论分析了浙江省干线公路网络对森林景观的破碎化影响,并运用公路影响阈值分析方法对破坏较为严重的森林景观斑块进行了更为深入的分析,结果表明:国道、省道网络侵占的森林面积较大,对森林生态服务功能的发挥有着较大的影响;高速公路网络则使得森林景观斑块严重降级和破碎,极大地影响着生物多样性的保护.若按照目前的公路规划,到2020年底,由国道、省道和高速公路共同形成的道路网络将对浙江省的森林景观系统造成严重破坏;最后,对浙江省公路网络的布局提出了5点调整建议.     

Effects of vegetation state on biodiversity and nitrogen retention in created wetlands: a test of the biodiversity–ecosystem functioning hypothesis

1. Nitrogen retention in wetlands provides an example of an ecosystem function that is desired by human society, and is a rationale for the creation of wetlands to decrease nitrogen fluxes from nitrate‐loaded river catchments to coastal waters. 2. Here, we tested the impact of different vegetation states on species diversity and nitrogen retention during 4 years in surface‐flow wetlands receiving nitrate‐rich water. Tall emergent vegetation or submerged vegetation was introduced to six experimental wetlands each and six wetlands were left as unplanted controls for free development of vegetation. This resulted in three vegetation states dominated by emergent vegetation, by a mixture of submerged vegetation and filamentous green algae or by filamentous green algae. 3. Species diversity (species richness and Shannon diversity) of plants was initially lowest in free development wetlands, but during the study became lower in the emergent vegetation wetlands than in the other wetlands. Diversity of macroinvertebrates was initially lower in the submerged vegetation wetlands than in the other wetlands, but this difference disappeared during the study. Nitrogen retention was consistently higher in emergent vegetation wetlands than in the other wetlands throughout the study. 4. We conclude that plant diversity in wetlands dominated by tall emergent vegetation gradually became lower than in other wetlands, due to dominant species competitively excluding other plants. However, these wetlands were more efficient at removing nitrogen than those dominated by filamentous algae or submerged macrophytes. 5. Management of wetlands often aims to decrease the dominance of tall emergent vegetation for the benefit of plant species diversity and habitat heterogeneity. Our results demonstrate a biodiversity benefit, but also show that this strategy may decrease the ability of wetlands to remove nitrogen. In this case, there is no support for the hypothesis that biodiversity enhances ecosystem function.     

Stoichiometric distribution models: ecological stoichiometry at the landscape extent

Human activities are altering the fundamental geography of biogeochemicals. Yet we lack an understanding of how the spatial patterns in organismal stoichiometry affect biogeochemical processes and the tools to predict the impacts of global changes on biogeochemical processes. In this contribution we develop stoichiometric distribution models (StDMs), which allow us to map spatial structure in resource elemental composition across a landscape and evaluate spatial responses of consumers. We parameterise StDMs for a consumer‐resource (moose‐white birch) system and demonstrate that we can develop predictive models of resource stoichiometry across a landscape and that such models could improve our predictions of consumer space use. With results from our study system application, we argue that explicit consideration of the spatial patterns in organismal elemental composition may uncover emergent individual, population, community and ecosystem properties that are not revealed at the local extents routinely used in ecological stoichiometry. We discuss perspectives for further developments and application of StDMs to advance three emerging frameworks for spatial ecosystem ecology in an era of global change; meta‐ecosystem theory, macroecological stoichiometry and remotely sensed biogeochemistry. Progress on these emerging frameworks will allow for the integration of ecological stoichiometry and individual space use and fitness.     

应用生态网络分析方法评价中国经济系统的可持续性

将生态网络分析方法应用于中国经济系统的可持续性分析。依据1987—2010年的投入产出数据,构建中国经济系统的货币网络流,用生态网络指标量化经济系统的网络特征和变化情况,探讨中国经济系统中增长与发展的变化及其可持续性。主要结论有:(1)1987—2010年间中国经济系统的总吞吐量呈指数增长趋势,网络规模不断增长。(2)1987—2010年间中国经济的系统效率在波动中呈增加趋势,但增长幅度较小。从长期阶段看,1997—2010年间的系统效率和组织能力比1987—1995年间有明显提高,表明经济系统在后期获得了一定程度的发展。但系统效率在2002年达到高点后呈现下降趋势。(3)1987—2010年间中国经济系统的上升性和发展能力都在持续提高,但主要来自规模增长。增长和发展的量化结果表明,1987—2010年间中国经济系统上升性的提高,90%来自总吞吐量(增长),只有10%来自效率改进(发展)。(4)1987—2010年间的中国经济系统的α平均值为0.138,远小于0.37或0.33的可持续性最优平衡点,系统处于缺乏效率的不可持续的状态。要提高经济系统的可持续性,需要提高经济系统的效率(结构)和组织能力。     

基于生态系统服务供需的雄安新区生态网络构建与优化

城市生态网络构建是城市生态系统服务有效发挥作用的保障,构建完善的生态网络对于城市生态格局的优化具有重要的意义。结合雄安新区总体规划,通过雄安新区生态系统服务供给、需求两个层面识别生态源地。基于源地-缓冲区-廊道-节点框架,构建新区生态网络。其中,基于生态源地与城镇用地驱动因子,运用最小累积阻力方法得到累积阻力差,构建新区三生空间布局。根据成本距离分析和路径分析,结合雄安新区规划绿带分布,生成生态廊道,并在廊道与廊道交汇点、重要生态功能与脆弱的关键点以及道路轨道交汇点识别生态节点。得出：（1）新区生态源地主要位于白洋淀、公园绿地与其他绿地,分为水域生态源和林地生态源两类生态源地,面积总共728 km²。城镇源地主要位于新区东部容城县与雄县城区以及一些零星的农村居民点区域,面积为166 km²。（2）在新区三生空间布局下,加强生态廊道的构建,提升生态源地之间、生态源地与城镇源地之间的连通性,新区生态廊道主要依赖河流廊道和林地廊道两种类型。（3）在新区未来生态网络的建设中,需要重点关注河流廊道交汇点、河流廊道与城区的交汇处、交通道路与生态用地交汇处等的生态节点的建设及其生态功能的提升。