基于过程的群落生态学理论框架

如何解释群落的物种多样性是群落生态学的核心问题之一,贯穿于群落生态学的整个发展过程,至今仍未得到圆满解决.与这个问题有关的理论层出不穷,使得群落生态学研究产生了很多混乱,这种状况促使一些生态学家开始反思群落生态学是否一定要从群落结构出发?最近,一个新的、基于过程的理论框架为群落生态学提供了更有前景的发展方向.该理论框架...     

农作物景观生态研究:概念框架与研究方向

针对当前农业系统中农作物景观变化迅速、人地关系趋于复杂、粮食安全保障需求迫切,提出景观生态学和农业科学交叉产生的农作物景观生态研究这一新兴研究方向。通过构建农作物景观生态研究的概念框架,辨明农业生产中复杂的景观等级结构,为农业可持续发展提供理论依据。综述从农业景观到农作物景观的研究变化,指出农作物景观具有高动态性、尺度性和格局复杂特征。针对由种植者、消费者、耕地及其周边自然环境组成的农业景观,需要遵循相应的生态和农业经济发展规律,研究农作物种植格局变化、农作物的社会-生态效应和农作物种植可持续性的景观生态途径。重点开展以下四个研究方面的内容,农作物景观时空动态及其形成机理、农作物种植的多功能评价与权衡、景观农艺管理措施及情景模拟、可持续的农作物景观生态评价。从而构建"格局-过程-服务-管理-可持续性"的农作物景观生态研究范式,为农业可持续发展提供综合的空间分析与管理途径,为实现农业农村现代化与城乡人类福祉提升提供科学支撑。     

Towards an eco‐phylogenetic framework for infectious disease ecology

Identifying patterns and drivers of infectious disease dynamics across multiple scales is a fundamental challenge for modern science. There is growing awareness that it is necessary to incorporate multi‐host and/or multi‐parasite interactions to understand and predict current and future disease threats better, and new tools are needed to help address this task. Eco‐phylogenetics (phylogenetic community ecology) provides one avenue for exploring multi‐host multi‐parasite systems, yet the incorporation of eco‐phylogenetic concepts and methods into studies of host pathogen dynamics has lagged behind. Eco‐phylogenetics is a transformative approach that uses evolutionary history to infer present‐day dynamics. Here, we present an eco‐phylogenetic framework to reveal insights into parasite communities and infectious disease dynamics across spatial and temporal scales. We illustrate how eco‐phylogenetic methods can help untangle the mechanisms of host–parasite dynamics from individual (e.g. co‐infection) to landscape scales (e.g. parasite/host community structure). An improved ecological understanding of multi‐host and multi‐pathogen dynamics across scales will increase our ability to predict disease threats.     

The ecology of The Netherlands wetlands: characteristics,threats, prospects and perspectives for ecological research

Wetlands are among the worlds' most important, but also most threatened, environmental resources. Wetland losses have been in progress particularly from the industrial revolution onwards, because wetland functions could not successfully compete for space with other land uses. Wetlands became recently foci of conservation efforts because of the increased awareness of their importance in water management and wildlife conservation, and because of the diversity of their habitats. The Netherlands are relatively rich in wetlands: 16% of its' territory is regarded as internationally important wetland and 7% has been registered as such. The major Dutch wetland types are: coastal ecosystems, large riverine systems, base-rich freshwater systems, and nutrient-poor freshwater systems. Most threats to the Dutch wetlands are of man-made origin. They comprise: (1) Changes in hydrology leading to changed discharges, currents and desiccation; (2) Acidification; (3) Eutrophication; and (4) Toxification. Long-term threats are largely climate-change related, and concern temperature rise and the UV-B increase in irradiation. General conservation goals also apply to wetlands but Ramsar-registered wetlands have a special status. Conservation of the Dutch wetlands is difficult, because of the high population density of the country and its inherent threats. However, ecological targets and standards are increasingly set in national Policy Plans and international agreements. Rehabilitation and creation of wetlands is presently widely advocated, and sometimes realised. For ecological research, the sustainability of wetlands should get top priority. Such a research programme would focus on understanding the underlying ecological processes in natural and man-dominated wetland systems to prescribe conservation, rehabilitation and management strategies that would enhance the sustainability of these systems. Within this framework special attention should be directed to studies (1) At the ecosystem level of ecosystem parameters, of which natural oscillations and trends in time, and on which the impact of disturbances are quantified. Particularly these studies, in which often simulation models are used as tools for interpretation, can provide the basis for extrapolations in space and time; (2) On adaptation capacity and mechanisms of (groups of) species to extreme environmental conditions; (3) On (mutual) relationships between plants, animals and microorganisms (e.g. competition, grazing and mineralization); (4) On dispersion between small wetlands. For the contemporary quantitative assessment of the long-term effects of climate changes, the effects of temperature rise and increase in UV-B irradiation on individual species, communities and ecosystems should also be studied.     

微生物生态学理论框架

微生物是生态系统的重要组成部分,直接或间接地参与所有的生态过程。微生物生态学是基于微生物群体的科学,利用微生物群体DNA/RNA等标志物,重点研究微生物群落构建、组成演变、多样性及其与环境的关系,在生态学理论的指导和反复模型拟合下由统计分析得出具有普遍意义的结论。其研究范围从基因尺度到全球尺度。分子生物学技术的发展,使人们可以直接从基因水平上考查其多样性,从而使得对微生物空间分布格局及其成因的深入研究成为可能。进而可以从方法学探讨微生物生物多样性、分布格局、影响机制及其对全球变化的响应等。在微生物生态学研究中,群落构建与演化、分布特征(含植物-微生物相互关系)、执行群体功能的机理(生物地球化学循环等)、对环境变化的响应与反馈机理是今后需要关注的重点领域。概述了微生物生态学的概念,并初步提出其理论框架,在对比宏观生态学基础理论和模型的基础上,分析微生物多样性的研究内容、研究方法和群落构建的理论机制,展望了今后研究的重点领域。     

A phenazine-inspired framework for identifying biological functions of microbial redox-active metabolites

While the list of small molecules known to be secreted by environmental microbes continues to grow, our understanding of their in situ biological functions remains minimal. The time has come to develop a framework to parse the meaning of these “secondary metabolites,” which are ecologically ubiquitous and have direct applications in medicine and biotechnology. Here, we focus on a particular subset of molecules, redox active metabolites (RAMs), and review the well-studied phenazines as archetypes of this class. We argue that efforts to characterize the chemical, physical and biological makeup of the microenvironments, wherein these molecules are produced, coupled with measurements of the molecules' basic chemical properties, will enable significant progress in understanding the precise roles of novel RAMs.     

The potential contribution of vegetation ecology to biodiversity research

The contribution of vegetation ecology to the study of biodiversity depends on better communication between the different research paradigms in ecology. Recent developments in vegetation theory and associated statistical modelling techniques are reviewed for their relevance to biodiversity. Species composition and collective properties such as species richness vary as a continuum in a multi-dimensional environmental space; a concept which needs to be incorporated into biodiversity studies. Different kinds of environmental gradients can be recognised and species responses to them vary. Species response curves of eucalypts to an environmental gradient of mean annual temperature have been shown to exhibit a particular pattern of skewed response curves. Generalised linear modelling (GLM) and generalised additive modelling (GAM) techniques are important tools for biodiversity studies. They have successfully distinguished the contribution of environmental (climatic) and spatial (history and species dispersal ability) variables in determining forest tree composition in New Zealand. Species richness studies are examined at global, regional and local scales. At all scales, direct and resource environmental gradients need to be incorporated into the analysis rather than indirect gradients e.g. latitude which have no direct physiological influence on biota. Evidence indicates that species richness at the regional scale is sensitive to environment, confounding current studies on local/regional species richness relationships. Plant community experiments require designs based on environmental gradients rather than dependent biological properties such as productivity or species richness to avoid confounding the biotic components. Neglect of climatic and other environmental gradients and the concentration on the collective properties of species assemblages has limited recent biodiversity studies. Conservation evaluation could benefit from greater use of the continuum concepts and statistical modelling techniques of vegetation ecology. The future development of ecology will depend on testing the different assumptions of competing research paradigms and a more inclusive synthesis of ecological theory.     

人工湿地氮去除关键功能微生物生态学研究进展

人工湿地是一种能有效处理水体氮素污染的生态技术,其中微生物是驱动人工湿地系统中氮素去除的重要引擎。近20年来,随着分子生物学技术的广泛应用,有关人工湿地氮去除功能微生物生态学方面研究取得了一些重要进展。以硝化-反硝化作用和厌氧氨氧化作用这两种重要的人工湿地微生物脱氮途径为主,针对氨氧化细菌/古菌、厌氧氨氧化菌和反硝化菌等关键脱氮功能微生物的研究,重点归纳总结了目前有关这几类关键功能菌群在人工湿地中的丰度、活性、多样性、分布特征与影响因素,及其对废水中氮去除的作用,并在此基础上对今后的重点研究工作提出了展望。面向未来人工湿地氮去除关键功能微生物的研究应侧重其在污水净化和温室气体减排等方面的生态功能研究,同时加强其代谢过程与机制以及不同功能菌群间的关联研究。     

A testing framework for identifying susceptibility genes in the presence of epistasis

An efficient testing strategy called the "focused interaction testing framework" (FITF) was developed to identify susceptibility genes involved in epistatic interactions for case-control studies of candidate genes. In the FITF approach, likelihood-ratio tests are performed in stages that increase in the order of interaction considered. Joint tests of main effects and interactions are performed conditional on significant lower-order effects. A reduction in the number of tests performed is achieved by prescreening gene combinations with a goodness-of-fit chi2 statistic that depends on association among candidate genes in the pooled case-control group. Multiple testing is accounted for by controlling false-discovery rates. Simulation analysis demonstrated that the FITF approach is more powerful than marginal tests of candidate genes. FITF also outperformed multifactor dimensionality reduction when interactions involved additive, dominant, or recessive genes. In an application to asthma case-control data from the Children's Health Study, FITF identified a significant multilocus effect between the nicotinamide adenine dinucleotide (phosphate) reduced:quinone oxidoreductase gene (NQO1), myeloperoxidase gene (MPO), and catalase gene (CAT) (unadjusted P = .00026), three genes that are involved in the oxidative stress pathway. In an independent data set consisting primarily of African American and Asian American children, these three genes also showed a significant association with asthma status (P = .0008).     

2,000 Families: identifying the research potential of an origins-of-migration study

Despite recent advances, critical areas in the analysis of European migration remain underdeveloped. We have only a limited understanding of the consequences of migration for migrants and their descendants, relative to staying behind; and our insights of intergenerational transmission is limited to two generations of those living in the destination countries. These limitations stem from a paucity of studies that incorporate comparison with non-migrants – and return migrants – in countries of origin and which trace processes of intergenerational transmission over multiple generations. This paper outlines the theoretical and methodological discussions in the field, design and data of the 2,000 Families study. The study comprises almost 50,000 members of migrant and non-migrant Turkish families across three family generations, living in Turkey and eight European countries. We provide indicative findings from the study, framed within a theoretical perspective of “dissimilation” from origins, and reflect on its potential for future migration research.     

Toward a predictive macrosystems framework for migration ecology

Concern about the sustainability of intercontinental‐scale migration systems grows apace with global change. Traditional organism‐centred approaches to this problem have provided insights at the population level, but not at the systems level. We are sceptical that an accumulation of data from a species‐by‐species approach will yield an understanding of these systems in the near term. As an alternative, we advocate a new research programme that grows from an explicitly system‐based framework that leverages existing Earth observation infrastructure to make inferences directly at the macrosystem level. We illustrate how this approach can be used to generate and test system‐level predictions, using NEXRAD radar data as an example. We urge organismal ecologists to recognize that some of the most urgent migration questions are at the macrosystem scale and that tackling these questions requires an interdisciplinary approach if we are to make progress at a pace that exceeds that of climate change.     

A conceptual framework to deal with outliers in ecology

Research on ecology commonly involves the need to face datasets that contain extreme or unusual observations. The presence of outliers during data analysis has been of concern for researchers generating a lot of discussion on different methods and strategies on how to deal with them and became a recurrent issue of interest in debate forums. Systematic elimination or data transformation could lead to ignore important ecological processes and draw wrong conclusions. The importance of coping with extreme observations during data analysis in ecology becomes clear in the context of relevant environmental aspects such as impact assessment, pest control, and biodiversity conservation. In those contexts, misinterpretation of results due to an incorrect processing of outliers may difficult decision making or even lead to failing to adopt the best management program. In this work, I summarized different approaches to deal with extreme observations such as outlier labeling, accommodation, and identification, using calculation and visualization methods, and provide a conceptual workflow as a general overview for data analysis.     

A non-negative matrix factorization framework for identifying modular patterns in metagenomic profile data

Metagenomic studies sequence DNA directly from environmental samples to explore the structure and function of complex microbial and viral communities. Individual, short pieces of sequenced DNA (“reads”) are classified into (putative) taxonomic or metabolic groups which are analyzed for patterns across samples. Analysis of such read matrices is at the core of using metagenomic data to make inferences about ecosystem structure and function. Non-negative matrix factorization (NMF) is a numerical technique for approximating high-dimensional data points as positive linear combinations of positive components. It is thus well suited to interpretation of observed samples as combinations of different components. We develop, test and apply an NMF-based framework to analyze metagenomic read matrices. In particular, we introduce a method for choosing NMF degree in the presence of overlap, and apply spectral-reordering techniques to NMF-based similarity matrices to aid visualization. We show that our method can robustly identify the appropriate degree and disentangle overlapping contributions using synthetic data sets. We then examine and discuss the NMF decomposition of a metabolic profile matrix extracted from 39 publicly available metagenomic samples, and identify canonical sample types, including one associated with coral ecosystems, one associated with highly saline ecosystems and others. We also identify specific associations between pathways and canonical environments, and explore how alternative choices of decompositions facilitate analysis of read matrices at a finer scale.