Quantum computing: a new paradigm for ecology

A global technology arms race is underway to build evermore powerful and precise quantum computers. Quantum computers have the potential to tackle certain quantitative problems quicker than classical computers. The current focus of quantum computing is on pushing the boundaries of fundamental quantum information and commercial applications in industrial sectors, financial services, and other profit-led sectors, particularly where improvements in optimisation and sampling can improve increased economic return. We believe that ecologists could exploit the computational power of quantum computers because the statistical approaches commonly used in ecology already have proven pathways on quantum computers. Moreover, quantum computing could ultimately leapfrog our understanding of complex ecological systems, if the hardware, opportunity, and creativity of quantitative ecologists all align.     

Synthetic biology: building the language for a new science brick by metaphorical brick

Changes in the biosciences and their relations to society over the last decades provide a unique opportunity to examine whether or not such changes leave traces in the language we use to talk about them. In this article we examine metaphors used in English-speaking press coverage to conceptualize a new type of (interdisciplinary) bioscience: synthetic biology. Findings show that three central metaphors were used between 2008 and May 2010. They exploit social and cultural knowledge about books, computers and engines and are linked to knowledge of three revolutions in science and society (the printing, information and industrial revolutions). These three central metaphors are connected to each other through the concepts of reading/writing, designing and mass production and they focus on science as a revolutionary process rather than on the end results or products of science. Overall, we observed the use of a complex bricolage of mixed metaphors and chains of metaphors that root synthetic biology in historical events and achievements, while at the same time extolling its promises for the future.     

Ecology after 100 years: Progress and pseudo-progress

Has the science of ecology fulfilled the promises made by the originators of ecological science at the start of the last century? What should ecology achieve? Have good policies for environmental management flowed out of ecological science? These important questions are rarely discussed by ecologists working on detailed studies of individual systems. Until we decide what we wish to achieve as ecologists we cannot define progress toward those goals. Ecologists desire to achieve an understanding of how the natural world operates, how humans have modified the natural world, and how to alleviate problems arising from human actions. Ecologists have made impressive gains over the past century in achieving these goals, but this progress has been uneven. Some sub-disciplines of ecology are well developed empirically and theoretically, while others languish for reasons that are not always clear. Fundamental problems can be lost to view as ecologists fiddle with unimportant pseudo-problems. Bandwagons develop and disappear with limited success in addressing problems. The public demands progress from all the sciences, and as time moves along and problems get worse, more rapid progress is demanded. The result for ecology has too often been poor, short-term science and poor management decisions. But since the science is rarely repeated and the management results may be a generation or two down the line, it is difficult for the public or for scientists to decide how good or bad the scientific advice has been. In ecology over the past 100 years we have made solid achievements in behavioural ecology, population dynamics, and ecological methods, we have made some progress in understanding community and ecosystem dynamics, but we have made less useful progress in developing theoretical ecology, landscape ecology, and natural resource management. The key to increasing progress is to adopt a systems approach with explicit hypotheses, theoretical models, and field experiments on a scale defined by the problem. With continuous feedback between problems, possible solutions, relevant theory and experimental data we can achieve our scientific goals.     

The role of ecological theory in microbial ecology

Microbial ecology is currently undergoing a revolution, with repercussions spreading throughout microbiology, ecology and ecosystem science. The rapid accumulation of molecular data is uncovering vast diversity, abundant uncultivated microbial groups and novel microbial functions. This accumulation of data requires the application of theory to provide organization, structure, mechanistic insight and, ultimately, predictive power that is of practical value, but the application of theory in microbial ecology is currently very limited. Here we argue that the full potential of the ongoing revolution will not be realized if research is not directed and driven by theory, and that the generality of established ecological theory must be tested using microbial systems.     

Molecular ecology of fungal entomopathogens: molecular genetic tools and their applications in population and fate studies

The power of molecular genetic techniques to address ecological research questions has opened a distinct interdisciplinary research area collectively referred to as molecular ecology. Molecular ecology combines aspects of diverse research fields like population and evolutionary genetics, as well as biodiversity, conservation biology, behavioural ecology, or species-habitat interactions. Molecular techniques detect specific DNA sequence characteristics that are used as genetic markers to discriminate individuals or taxonomic groups, for instance in analyses of population and community structures, for elucidation of phylogenetic relationships, or for the characterization and monitoring of specific strains in the environment. Here, we summarize the PCR-based molecular techniques used in molecular ecological research on fungal entomopathogens and discuss novel techniques that may have relevance to the studies of entomopathogenic fungi in the future. We discuss the flow chart of the molecular ecology approaches and we highlight some of the critical steps involved. There are still many unresolved questions in the understanding of the ecology of fungal entomopathogens. These include population characteristics and relations of genotypes and habitats as well as host-pathogen interactions. Molecular tools can provide substantial support for ecological research and offer insight into this far inaccessible systems. Application of molecular ecology approaches will stimulate and accelerate new research in the field of entomophathogen ecology.     

奥德姆的生态思想是整体论吗?

奥德姆的生态思想是妥协的整体论,有还原论的一面。把生态系统看作是功能性整体、承认生态系统各层次的涌现属性属于整体论,把生态关系简化为能量关系、把生态系统看作是物理系统的分析方法则是还原论的。这种矛盾的生态思想决定了其方法论的先天不足:生态模型的内在逻辑关系没有理顺;较少考虑生态系统的进化;生态研究方法的排它性等。但是,它并不妨碍奥德姆的生态思想在夯实生态学的本体论基础、促进理论生态学和生态工程学的形成、协调生态整体论与还原论分歧、奠定生态系统服务功能研究基础等方面发挥重要作用。要超越生态整体论与还原论,繁荣发展生态复杂性理论也许是最好的选择。     

The rise of the individual-based model in ecology

Recent advances of three different kinds are driving a change in the way that modelling Is being done in ecology. First, the theory of chaos tells us that short-term predictions of nonlinear systems will be difficult, and long-term predictions will be impossible. The grave Implications this has for ecology are only just beginning to be understood. Second, ecologists have started to recognize the importance of local interactions between individuals in ecological systems. And third, improvements in computer power and software are making computers more inviting as a primary tool for modelling. The combination of these factors may have far-reaching consequences for ecological theory.     

Ecological engineering: A rationale for standardized curriculum and professional certification in the United States

The demand for engineering solutions to ecosystem–level problems has increased as the impact of human activities has expanded to global proportions. While the science of restoration ecology has been developed to address many critical ecosystem management issues, the high degree of complexity and uncertainty associated with these issues demands a more quantitative approach. Ecological engineering uses science-based quantification of ecological processes to develop and apply engineering-based design criteria for sustainable systems. We suggest that in the United States ecological engineering curricula should be offered at the graduate level and should require rigorous Accreditation Board of Engineering and Technology-accredited (or equivalent) undergraduate preparation in engineering fundamentals. In addition to strengthening students’ mastery of engineering theory and application, the graduate curriculum should provide core courses in ecosystem theory including quantitative ecology, systems ecology, restoration ecology, ecological engineering, ecological modeling, and ecological engineering economics. Advanced courses in limnology, environmental plant physiology, ecological economics, and specific ecosystem design should be provided to address students’ specific professional objectives. Finally, professional engineering certification must be developed to insure the credibility of this new engineering specialization.     

Temporal ecology in the Anthropocene

Two fundamental axes – space and time – shape ecological systems. Over the last 30 years spatial ecology has developed as an integrative, multidisciplinary science that has improved our understanding of the ecological consequences of habitat fragmentation and loss. We argue that accelerating climate change – the effective manipulation of time by humans – has generated a current need to build an equivalent framework for temporal ecology. Climate change has at once pressed ecologists to understand and predict ecological dynamics in non‐stationary environments, while also challenged fundamental assumptions of many concepts, models and approaches. However, similarities between space and time, especially related issues of scaling, provide an outline for improving ecological models and forecasting of temporal dynamics, while the unique attributes of time, particularly its emphasis on events and its singular direction, highlight where new approaches are needed. We emphasise how a renewed, interdisciplinary focus on time would coalesce related concepts, help develop new theories and methods and guide further data collection. The next challenge will be to unite predictive frameworks from spatial and temporal ecology to build robust forecasts of when and where environmental change will pose the largest threats to species and ecosystems, as well as identifying the best opportunities for conservation.     

The Ecosystem: Model or Metaphor?

Industrial ecology offers an original way of looking at economic activities. The approach is based on an analogy between certain objects studied by the science of ecology (ecosystems, metabolisms, symbiosis, biocenosis, etc.) and industrial systems. However, this analogical relationship raises difficulties due to the various interpretations to which it is open. Although there is agreement regarding its heuristic function, the analogy can nevertheless be understood either as a model or as a metaphor. The present article first attempts to show how models differ from metaphors. It then sets out to justify the epistemological relevance of this distinction for industrial ecology research. The reflection should thus contribute to clarifying the debate on the (supposed or desired) role of analogy in the field of industrial ecology and heighten the interest this field of investigation represents for implementing sustainable development.     

Quantitative Industrial Ecology & Ecological Economics

This article presents a theoretical foundation for integrating three otherwise disparate areas of human thought and understanding: technology, ecology, and economics. The article presents the mathematical foundations for quantifying the biophysical (mass, energy, and informational) aspects of economic production systems and their interaction with natural systems. These mathematical relationships are required for the on-going ecological and economic design of technological production networks by enterprise management, thereby extending the scope and scale of quantitative engineering design from the domain of individual technologies to networks of technologies at enterprise, corporate, and industrial levels of technological organization.
The analytical framework extends the practical utility of ecology, as an applied natural science, from passive environmental monitoring and prediction to active institutional participation in an informational feedback control strategy pursuant to economically abating the ecological risks of industrial growth, development, and modernization at local, regional, and global levels of ecological organization. And it provides the applied natural-science underpinnings and the informational feedback control institutions required to support economics as an applied social science. In this context ecological risk-control pricing is presented as a supplement to conventional economic policies at local, regional, and national levels of economic organization.     

自然生态价值、生态资产管理及价值实现的生态经济学基础研究——科学概念、基础理论及实现途径

自然界的生态系统为人类繁衍发展提供各式各样的生活、生产和生计的环境条件与自然资源。基于自然规律的生态系统管理是人类社会不断认知自然生态价值、保护利用自然环境和资源、创造积累生态资产、维持社会经济系统永续发展的基本途径。以此为核心认知的区域生态经济学或经济生态学,正在成为探讨人类世地球系统演变及社会经济可持续发展问题的科学研究前沿。本文以大尺度区域宏观生态系统科学为学术视角,以生态系统的多功能性与多元价值观为基础,综合论述了自然生态价值、生态资产、生态产品等基本概念;从生态学、社会学和经济学融合角度,分析讨论了生态资产形成与变化、生态产品生产与消费、生态投资与生态资产损益等过程原理;提出了区域生态资产的系统经营与生态价值实现途径,期望为我国及区域生态系统价值及生态资产的评估,生态产业及生态价值实现体系的发展提供理论和方法学参考。     

Linking biodiversity and ecosystems: towards a unifying ecological theory

Community ecology and ecosystem ecology provide two perspectives on complex ecological systems that have largely complementary strengths and weaknesses. Merging the two perspectives is necessary both to ensure continued scientific progress and to provide society with the scientific means to face growing environmental challenges. Recent research on biodiversity and ecosystem functioning has contributed to this goal in several ways. By addressing a new question of high relevance for both science and society, by challenging existing paradigms, by tightly linking theory and experiments, by building scientific consensus beyond differences in opinion, by integrating fragmented disciplines and research fields, by connecting itself to other disciplines and management issues, it has helped transform ecology not only in content, but also in form. Creating a genuine evolutionary ecosystem ecology that links the evolution of species traits at the individual level, the dynamics of species interactions, and the overall functioning of ecosystems would give new impetus to this much-needed process of unification across ecological disciplines. Recent community evolution models are a promising step in that direction.     

Developing a flexible learning activity on biodiversity and spatial scale concepts using open‐access vegetation datasets from the National Ecological Observatory Network

Biodiversity is a complex, yet essential, concept for undergraduate students in ecology and other natural sciences to grasp. As beginner scientists, students must learn to recognize, describe, and interpret patterns of biodiversity across various spatial scales and understand their relationships with ecological processes and human influences. It is also increasingly important for undergraduate programs in ecology and related disciplines to provide students with experiences working with large ecological datasets to develop students’ data science skills and their ability to consider how ecological processes that operate at broader spatial scales (macroscale) affect local ecosystems. To support the goals of improving student understanding of macroscale ecology and biodiversity at multiple spatial scales, we formed an interdisciplinary team that included grant personnel, scientists, and faculty from ecology and spatial sciences to design a flexible learning activity to teach macroscale biodiversity concepts using large datasets from the National Ecological Observatory Network (NEON). We piloted this learning activity in six courses enrolling a total of 109 students, ranging from midlevel ecology and GIS/remote sensing courses, to upper‐level conservation biology. Using our classroom experiences and a pre/postassessment framework, we evaluated whether our learning activity resulted in increased student understanding of macroscale ecology and biodiversity concepts and increased familiarity with analysis techniques, software programs, and large spatio‐ecological datasets. Overall, results suggest that our learning activity improved student understanding of biological diversity, biodiversity metrics, and patterns of biodiversity across several spatial scales. Participating faculty reflected on what went well and what would benefit from changes, and we offer suggestions for implementation of the learning activity based on this feedback. This learning activity introduced students to macroscale ecology and built student skills in working with big data (i.e., large datasets) and performing basic quantitative analyses, skills that are essential for the next generation of ecologists.     

Accumulating evidence in ecology: Once is not enough

Many published studies in ecological science are viewed as stand‐alone investigations that purport to provide new insights into how ecological systems behave based on single analyses. But it is rare for results of single studies to provide definitive results, as evidenced in current discussions of the “reproducibility crisis” in science. The key step in science is the comparison of hypothesis‐based predictions with observations, where the predictions are typically generated by hypothesis‐specific models. Repeating this step allows us to gain confidence in the predictive ability of a model, and its corresponding hypothesis, and thus to accumulate evidence and eventually knowledge. This accumulation may occur via an ad hoc approach, via meta‐analyses, or via a more systematic approach based on the anticipated evolution of an information state. We argue the merits of this latter approach, provide an example, and discuss implications for designing sequences of studies focused on a particular question. We conclude by discussing current data collection programs that are preadapted to use this approach and argue that expanded use would increase the rate of learning in ecology, as well as our confidence in what is learned.     

The role of expert systems in vegetation science

An area of artificial intelligence known as experts systems (or knowledge-based systems) is being applied in many areas of science, technology and commerce. It is likely that the techniques will have an impact on vegetation science and ecology in general. This paper discusses some of those impacts and concludes that the main effects will be in areas of applied ecology especially where ecological expertise is needed either quickly (e.g. disaster management) or across a wide range of ecological disciplines (e.g. land management decisions). Expert systems will provide ecologists with valuable tools for managing data and interacting with other fields of expertise. The impact of expert systems on ecological theory will depend on the degree to which deep knowledge (i.e. knowledge based on first principles rather than on more empirical rules) is used in formulating knowledge bases.     

Multiplicative moments and measures of persistence in ecology

Ecologists and epidemiologists have begun focusing on demographic stochasticity and spatial heterogeneity as important biological factors. With high-powered computers simulation of such systems is a common modelling technique; however we lack a detailed understanding of the processes involved. Moment closure approximations provide a simple method which can be used to capture the main features of a wide variety of stochastic models and to gain a more intuitive understanding. In this paper we give an alternative variation based on multiplicative moments which is equivalent to taking a novel third-order cumulant approximation. The differential equations for these multiplicative moments are far more robust than their additive counterparts. We use this technique to consider the behaviour and persistence of finite metapopulations for two common ecological systems.     

The relativity of Darwinian populations and the ecology of endosymbiosis

If there is a single discipline of science calling the basic concepts of biology into question, it is without doubt microbiology. Indeed, developments in microbiology have recently forced us to rethink such fundamental concepts as the organism, individual, and genome. In this paper I show how microorganisms are changing our understanding of natural aggregations and develop the concept of a Darwinian population to embrace these discoveries. I start by showing that it is hard to set the boundaries of a Darwinian population, and I suggest thinking of a Darwinian population as a relative property of a Darwinian individual. Then I argue, in contrast to the commonly held view, that Darwinian populations are multispecies units, and that in order to accept the multispecies account of Darwinian populations we have to separate fitness from natural selection. Finally, I show how all these ideas provide a theoretical framework leading to a more precise understanding of the ecology of endosymbiosis than is afforded by poetic metaphors such as ‘slavery’.