如何设计与开展现代生态学研究——第五届“国际青年生态学者论坛”述评

为促进中国青年生态学者与海外生态学者的交流与合作,由中国生态学学会、中华海外生态学者协会和国际青年学者论坛委员会联合举办的第五届国际青年生态学者论坛,于2014年5月16日至18日在河南大学(开封)顺利召开。围绕"如何设计与开展现代生态学研究"的主题,本届论坛的科学议题包含了以下五个方面:(1)如何设计现代生态学的研究;(2)生态学不同领域的研究方法;(3)针对不同生态学问题所采用的数据分析方法;(4)撰写生态学领域研究项目申请书方面的成功经验交流;(5)英文论文写作过程中的注意事项,传授提高生态学英文论文写作能力的经验和技巧。国际青年生态学者论坛促进了青年生态学者与国际专家的交流,对我国生态学科的发展和生态学人才的成长具有重要意义。     

中国园林生态学发展综述

运用文献计量等方法对已有科研成果进行统计分析,结果表明:中国近50年园林生态学科领域科研发展经过了起步探索(1962-1981)、缓慢发展(1982-2001)、快速发展(2002-2011)3个时期,园林生态学作为生态学一个新的分支学科,于20世纪90年代末初见端倪,作为一门新兴独立的应用生态学分支学科于21世纪初已基本形成.中国园林生态学领域的研究包括园林生态系统中生物与环境相互作用关系问题、人与环境相互作用关系问题以及园林生态系统与其他生态系统之间相互作用关系问题.当代园林生态研究主要有生态效益研究、生物与环境研究、人的需求与行为研究、生态规划与生态管理研究4个方面,目前园林生态学研究主要侧重生物与环境研究和生态效益研究,两方面的研究成果占总体研究成果的76.3％.不同研究方面也有各自的侧重点,如生物与环境研究侧重对植物的研究,生态效益研究侧重净化环境、水土保持和防灾减灾,生态规划与生态管理研究则侧重生态规划与设计.对四个研究方面的论文主题词检索和高频主题关键词的分布进行统计,结果显示,研究的热点有多样性、群落、水土保持、防灾避险、净化环境、生态规划与设计等.对CNKI中4个研究方面成果中获基金资助项目论文进行统计(不排重),总体成果中基金项目论文所占比重为10.8％,国家和地方基金是园林生态学科研基金资助的主要来源,基金论文比例之和达到85.4％,且国家和地方基金资助论文较多的是“生态与环境研究”和“生态效益研究”,合计占基金论文79.1％.SCI-E中收录的文献基金论文率为47.1％,是CNKI数据库收录的文献基金论文率的4.3倍,且国际基金是基金论文的主要资助来源之一,说明中国园林生态学领域部分科研成果得到国际学界关注.基于CNKI相关主题词统计,“园林生态学”的研究成果只有“景观生态学”的1％,“城市生态学”的8.3％,“园林生态学”学科系统理论研究在相关生态学科研究中所占比重很低,其理论和方法研究还较薄弱.今后在进一步完善学科理论体系、持续开展生态效益和园林植物研究的同时,为更好地研究和解决人-自然复合生态系统问题,提供更多的科学理论支撑,还需拓展交叉生态心理学或环境心理学等其他相关理论,更多地关注人与环境互相作用关系以及生态规划与生态管理等方面的研究,既使环境更好地满足人的行为需求,也使人认识到改变一些行为能更好地保护环境.     

学术论文署名刍议

在缪世利博士和马克平研究员“展开生态学研究论文作者署名、排名的讨论”的倡议下,笔者结合自身所了解的情况,浅谈了“谁应包括为作者,谁被致谢”、“第一作者的职责与责任”和“通讯作者的定义及作用”这几个问题的个人看法。[编者按]     

论原子生态学学科的建立和发展

本文的部分作者 ,曾以“试论原子生态学成为一门生态学分支学科的可能性”为题进行过初步讨论。就目前了解到的情况看 ,人们对原子生态学的概念 ,似乎有所反映 ,这是令人高兴的事。这鼓励我们几个志同道合的微生态学和分子生态学工作者联合起来 ,一道作为本文的作者 ,对“原子生态学学科的建立和发展”进行略为深入的讨论 ,希望起到抛砖引玉的作用 ,以便众志成城 ,共同为创建原子生态学这一新的学科作出光辉的贡献。原子生态学是分子生态学的深入发展、这似乎易于理解 ,因为从分子到原子 ,好像只是一个层次之差。如果从生态学的角度看 ,则分…     

Excel和SAS在生物统计学的应用比较

对Excel和SAS在生物统计学的应用特点及存在问题进行了比较,指出Excel制作的统计图形美观Z函数可直接给出结果,公式编辑简便实用,具有“数据分析”功能,但也存在fx和“数据分析”结果不一致的地方,加载“数据分析”工具时需要插入“Microsoft Office”初始安装盘,不能进行平均数的多重比较以及高级试验统计的结果分析。SAS的生物统计功能齐全,操作界面直观,程序模式化;但与Excel相比,相对烦琐而复杂。因此,在生物统计教学和科研工作中,应针对所处理问题的性质和目的选用不同的统计分析软件。     

生物类本科毕业论文“讨论”存在的问题与指导实践

"讨论"是学生毕业论文写作的重要环节,但也是常常被忽视、存在问题较多的环节之一。指出了生物类大学生论文"讨论"过程中经常发生的几个问题,并提出了解决这些问题的具体措施,为今后改进本科毕业论文写作质量提供参考。     

正文

正文是科技论文的核心部分,占全文的主要篇幅,是作者研究成果的学术性和创造性的集中表现,它决定着论文写作的成败和学术、技术水平的高低。将科学研究的全过程按研究内容的实际情况划分为几个阶段,由于研究对象、研究方法和研究成果的不同,以及学科的不同,对正文的写作和编排不能作出统一的规定,但一般的正文部分都应包括研究的对象、方法、结果和讨论这几个部分。试验与观察、数据处理与分析、实验研究结果的得出是正文的主要部分,应该给予有重点的详细论述。     

16S rRNA基因在微生物生态学中的应用

16S rRNA(Small subunit ribosomal RNA)基因是对原核微生物进行系统进化分类研究时最常用的分子标志物(Biomarker),广泛应用于微生物生态学研究中。近些年来随着高通量测序技术及数据分析方法等的不断进步,大量基于16S rRNA基因的研究使得微生物生态学得到了快速发展,然而使用16S rRNA基因作为分子标志物时也存在诸多问题,比如水平基因转移、多拷贝的异质性、基因扩增效率的差异、数据分析方法的选择等,这些问题影响了微生物群落组成和多样性分析时的准确性。对当前使用16S rRNA基因分析微生物群落组成和多样性的进展情况做一总结,重点讨论当前存在的主要问题以及各种分析方法的发展,尤其是与高通量测序技术有关的实验和数据处理问题。     

《生态科学》投稿须知

1 《生态科学》学报是经国家新闻出版署和科技部批准于1982年正式创刊的国内外公开发行的学术双月刊。刊登论文被“万方数字化期刊群”、“中国科学引文数据库”、“中国核心期刊（遴选）数据库”等全文收录。据《中国学术期刊综合引证报告（2008）》统计，本刊2007年影响因子为0．793，在本学科领域名列前茅。主要刊登生态学、环境科学、资源保护、可持续发展研究及相关领域的最新研究成果和原刨性论文，     

正文

正文是科技论文的核心部分,占全文的主要篇幅,是作者研究成果的学术性和创造性的集中表现,它决定着论文写作的成败和学术、技术水平的高低。将科学研究的全过程按研究内容的实际情况划分为几个阶段,由于研究对象、研究方法和研究成果的不同,以及学科的不同,对正文的写作和编排不能作出统一的规定,但一般的正文部分都应包括研究的对象、方法、结果和讨论这几个部分。试验与观察、数据处理与分析、实验研究结果的得出是正文的主要部分,应该给予有重点的详细论述。论文不必要讲求词藻华丽,但要求思路清晰、合乎逻辑,用语简洁准确、明快流畅。应…     

Trouble with the Gray Literature

In much of the tropics, the gray literature—published by nongovernmental organizations, governments, intergovernmental organizations, consultancies, private companies, and individuals—has a greater volume than the peer‐reviewed scientific literature in ecology and conservation. I discuss why this is a problem in terms of quality, discovery, access, and archiving. Unpublished dissertations and theses are another vast untapped source of information in tropical biology. Internet search engines can potentially integrate access to all information sources, but only if the producers of gray literature and theses greatly improve electronic access. Digital repositories can provide both this accessibility and permanent archiving.     

Groupings by locality in community ecology and paleoecology: tests of significance

Harper, Charles W. Jr. 1978 07 15: Groupings by locality in community ecology and paleoecology: tests of significance. Lethaia , Vol. 11, pp. 251–257. Oslo. ISSN 0024–1164.
Ecologic sample localities are commonly classified into groups on the basis of their species content; distinctive groups of localities are then commonly used to define discrete biofacies or communities. Yet, such locality groups and, by extension, the communities or biofacies inferred from them are almost never tested for statistical significance. Two approximate randomization tests are proposed as a step in this direction. One evaluates whether or not a given data set on which one or more locality groups are based exhibits a degree of clustering by locality that is statistically significant. The second evaluates the statistical significance of the degree of mappability exhibited by a given collection of inferred locality groups.     

The ecology of information: an overview on the ecological significance of making informed decisions

Information is characterized as the reduction of uncertainty and by a change in the state of a receiving organism. Thus, organisms can acquire information about their environment that reduces uncertainty and increases their likelihood of choosing a best‐matching strategy. We define the ecology of information as the study of how organisms acquire and use information in decision‐making and its significance for populations, communities, landscapes and ecosystems. As a whole, it encompasses the reception and processing of information, decision‐making, and the ecological consequences of making informed decisions. The first two stages constitute the domains of, e.g. sensory ecology and behavioral ecology. The exploration of the consequences of information use at larger spatial and temporal scales in ecology has lagged behind these other disciplines. In our overview we characterize information, discuss statistical decision theory as a quantitative framework to analyze information and decision‐making, and discuss potential ecological ramifications. Rather than attempt a cursory review of the enormity of the scope of information we highlight information use in development, breeding habitat selection, and interceptive eavesdropping on alarm calls. Through these topics we discuss specific examples of ecological information use and the emerging ecological consequences. We emphasize recurring themes: information is collected from multiple sources, over varying temporal and spatial scales, and in many cases links heterospecifics to one another. We conclude by breaking from specific ecological contexts to explore implications of information as a central organizing principle, including: information webs, information as a component of the niche concept, and information as an ecosystem process. With information having such an enormous reach in ecology we further cast a spotlight on the potential harmful effects of anthropogenic noise and info‐disruption.     

Statistical mechanics unifies different ecological patterns

Recently there has been growing interest in the use of maximum relative entropy (MaxREnt) as a tool for statistical inference in ecology. In contrast, here we propose MaxREnt as a tool for applying statistical mechanics to ecology. We use MaxREnt to explain and predict species abundance patterns in ecological communities in terms of the most probable behaviour under given environmental constraints, in the same way that statistical mechanics explains and predicts the behaviour of thermodynamic systems. We show that MaxREnt unifies a number of different ecological patterns: (i) at relatively local scales a unimodal biodiversity-productivity relationship is predicted in good agreement with published data on grassland communities, (ii) the predicted relative frequency of rare vs. abundant species is very similar to the empirical lognormal distribution, (iii) both neutral and non-neutral species abundance patterns are explained, (iv) on larger scales a monotonic biodiversity-productivity relationship is predicted in agreement with the species-energy law, (v) energetic equivalence and power law self-thinning behaviour are predicted in resource-rich communities. We identify mathematical similarities between these ecological patterns and the behaviour of thermodynamic systems, and conclude that the explanation of ecological patterns is not unique to ecology but rather reflects the generic statistical behaviour of complex systems with many degrees of freedom under very general types of environmental constraints.     

Why do plants silicify?

Despite seminal papers that stress the significance of silicon (Si) in plant biology and ecology, most studies focus on manipulations of Si supply and mitigation of stresses. The ecological significance of Si varies with different levels of biological organization, and remains hard to capture. We show that the costs of Si accumulation are greater than is currently acknowledged, and discuss potential links between Si and fitness components (growth, survival, reproduction), environment, and ecosystem functioning. We suggest that Si is more important in trait-based ecology than is currently recognized. Si potentially plays a significant role in many aspects of plant ecology, but knowledge gaps prevent us from understanding its possible contribution to the success of some clades and the expansion of specific biomes.     

The need for stochastic replication of ecological neural networks

Artificial neural networks are becoming increasingly popular as predictive statistical tools in ecosystem ecology and as models of signal processing in behavioural and evolutionary ecology. We demonstrate here that a commonly used network in ecology, the three-layer feed-forward network, trained with the backpropagation algorithm, can be extremely sensitive to the stochastic variation in training data that results from random sampling of the same underlying statistical distribution, with networks converging to several distinct predictive states. Using a random walk procedure to sample error-weight space, and Sammon dimensional reduction of weight arrays, we demonstrate that these different predictive states are not artefactual, due to local minima, but lie at the base of major error troughs in the error-weight surface. We further demonstrate that various gross weight compositions can produce the same predictive state, suggesting the analogy of weight space as a 'patchwork' of multiple predictive states. Our results argue for increased inclusion of stochastic training replication and analysis into ecological and behavioural applications of artificial neural networks.     

Learning from clinical medicine to improve the use of surrogates in ecology

Surrogates are used widely in ecology to detect or monitor changes in the environment that are too difficult or costly to assess directly. Yet most work on surrogates to date has been correlative, with little work on their predictive capacity or the circumstances under which they work. Our suggestion is to revisit and learn from research in the clinical medical sciences, including the causal statistical frameworks available to validate relationships between treatments, surrogate variables, and the outcome of interest. We adapt this medical thinking to ecology by providing a new framework that involves specification of the surrogate model, statistical validation, and subsequent evaluation in a range of spatial and temporal contexts. An inter‐disciplinary surrogate concept will allow for a more rigorous approach to validating and evaluating proxy variables, thus advancing the selection and application of surrogates in ecology. Synthesis We draw together ideas from the medical sciences to define an explicit surrogate concept that has not previously been used in ecology. We present a new framework for specifying surrogate models involving validation using a causal framework, and subsequent re‐evaluation in different spatial and temporal contexts – an approach closely aligned with that used by researchers in the clinical medical sciences. This rigorous method can advance the science underpinning the application of surrogates in ecology by shifting the focus away from correlative understanding to one that focuses instead on causation and prediction. An improved use of surrogates is imperative if we are to meet the challenge of properly measuring and understanding the multifarious and complex problems in contemporary ecology.     

Fifty years of mycological studies at the White Sea Biological Station of Moscow State University: Challenges,results, and outlook

This review covers the history of the mycological studies performed at Pertsov White Sea Biological Station, Moscow State University (WSBS MSU). The WSBS was established more than 70 years ago; presently, it is one of the main divisions of the university, where numerous educational and research marine programs are fulfilled. Mycological studies have been performed here for more than half a century, focusing on biodiversity and ecology of marine, littoral, and soil fungi and fungi-like protists. Various research projects resulted as a number of scientific publications, diploma (MSc) theses, and dissertations. Presently, WSBS MSU and its vicinity is the northernmost area researching the best in regard to mycobiota. However, a number of blind spots still exist; thus, the future studies in this region should focus on diversity and biology of epiphyte fungi, ecology of fungi and fungi-like protists, and on fungi phylogeny.     

Limitations of entropy maximization in ecology

Applying ideas of statistical mechanics in ecology have recently received quite some attention. The entropy maximization (EM) formalism looks particularly attractive, as it provides a simple algorithm to infer detailed system variables from a limited number of constraints. However, we point out that a blind application of this formalism can easily lead to wrong conclusions. To illustrate this, we reanalyze an ecological data set that has been used to claim the good performance of EM in predicting species abundances from trait measurements. We show that these results are entirely due to the restrictive constraints, and do not provide any support for the applicability of EM in ecology. By comparing with a simple example from physics, we indicate which characteristic mechanism of EM, and of statistical mechanics in general, is missing for the ecological example. This analysis introduces a series of methods to evaluate future attempts to apply EM in ecology.     

Human macroecology: linking pattern and process in big‐picture human ecology

Humans have a dual nature. We are subject to the same natural laws and forces as other species yet dominate global ecology and exhibit enormous variation in energy use, cultural diversity, and apparent social organization. We suggest scientists tackle these challenges with a macroecological approach—using comparative statistical techniques to identify deep patterns of variation in large datasets and to test for causal mechanisms. We show the power of a metabolic perspective for interpreting these patterns and suggesting possible underlying mechanisms, one that focuses on the exchange of energy and materials within and among human societies and with the biophysical environment. Examples on human foraging ecology, life history, space use, population structure, disease ecology, cultural and linguistic diversity patterns, and industrial and urban systems showcase the power and promise of this approach.