Virtual reality in neuroscience research and therapy

Virtual reality (VR) environments are increasingly being used by neuroscientists to simulate natural events and social interactions. VR creates interactive, multimodal sensory stimuli that offer unique advantages over other approaches to neuroscientific research and applications. VR's compatibility with imaging technologies such as functional MRI allows researchers to present multimodal stimuli with a high degree of ecological validity and control while recording changes in brain activity. Therapists, too, stand to gain from progress in VR technology, which provides a high degree of control over the therapeutic experience. Here we review the latest advances in VR technology and its applications in neuroscience research.     

元基因组文库分析技术研究进展

随着新的分析技术的不断出现和成熟,促进了微生物分子生态学及相关学科的诞生和迅速发展。其中,元基因组文库分析技术即是近年来微生物分子生态学研究领域兴起的一种新的分析技术。就元基因组分析技术诞生的背景及该技术的原理进行了讨论,着重阐述了元基因组文库分析技术在寻找新基因、开发新的生物活性物质、研究群落中微生物多样性、人类元基因组测序等方面的应用。另外,归纳总结了目前国际上常用的诸如PCR为基础的筛选、荧光原位杂交（fluorescent in situ hybridization,FISH）、底物诱导的基因表达筛选（substrate induced gene expression screening,SIGEX）、基因芯片等元基因组文库筛选方法,并就不同方法的优缺点进行了分析和讨论,指出了目前元基因组文库分析技术存在的主要问题并对今后该技术的发展进行了展望。     

Many Possible Worlds: Expanding the Ecological Scenarios in Experimental Evolution

Experimental microbial evolution has focused on the particular ecological scenario where a population is placed suddenly in an environment where its fitness is low, and then adapts while the environment remains stable. In line with this, most microbial evolution studies use fitness measures that report how evolved genotypes fare when competed directly against their own distant ancestor while other studies compare life history traits (such as growth rates) of ancestral and evolved genotypes. This standard way of measuring and reporting changes in fitness has resulted in a consistent body of literature that explains adaptation when populations evolve in this “standard ecological scenario.” Here, I suggest that for experimental evolution to investigate adaptation in other ecological scenarios, such as fluctuating or persistently changing environments, measures of fitness must be expanded such that they not only continue to be comparable between experiments, but also account for evolution and demographic effects in all environments that an evolving lineage experiences. I examine two non-standard measures of fitness—fitness flux and the total number of reproductive events—as potential ways to quantify adaptation by integrating historical information about selection over many environments. This approach could allow us to make quantitative and biologically-meaningful comparisons of adaptation across diverse ecological scenarios. I use the case study of understanding how phytoplankton communities may respond to global change, where environmental variables change continuously, to explore concrete ways of using non-standard fitness measures that consider both demographic effects and selection in changing, rather than in changed, environments.     

Integrating models with data in ecology and palaeoecology: advances towards a model-data fusion approach

It is increasingly being recognized that global ecological research requires novel methods and strategies in which to combine process-based ecological models and data in cohesive, systematic ways. Model-data fusion (MDF) is an emerging area of research in ecology and palaeoecology. It provides a new quantitative approach that offers a high level of empirical constraint over model predictions based on observations using inverse modelling and data assimilation (DA) techniques. Increasing demands to integrate model and data methods in the past decade has led to MDF utilization in palaeoecology, ecology and earth system sciences. This paper reviews key features and principles of MDF and highlights different approaches with regards to DA. After providing a critical evaluation of the numerous benefits of MDF and its current applications in palaeoecology (i.e., palaeoclimatic reconstruction, palaeovegetation and palaeocarbon storage) and ecology (i.e. parameter and uncertainty estimation, model error identification, remote sensing and ecological forecasting), the paper discusses method limitations, current challenges and future research direction. In the ongoing data-rich era of today's world, MDF could become an important diagnostic and prognostic tool in which to improve our understanding of ecological processes while testing ecological theory and hypotheses and forecasting changes in ecosystem structure, function and services.     

Reconstructing past ecological networks: the reconfiguration of seed-dispersal interactions after megafaunal extinction

The late Quaternary megafaunal extinction impacted ecological communities worldwide, and affected key ecological processes such as seed dispersal. The traits of several species of large-seeded plants are thought to have evolved in response to interactions with extinct megafauna, but how these extinctions affected the organization of interactions in seed-dispersal systems is poorly understood. Here, we combined ecological and paleontological data and network analyses to investigate how the structure of a species-rich seed-dispersal network could have changed from the Pleistocene to the present and examine the possible consequences of such changes. Our results indicate that the seed-dispersal network was organized into modules across the different time periods but has been reconfigured in different ways over time. The episode of megafaunal extinction and the arrival of humans changed how seed dispersers were distributed among network modules. However, the recent introduction of livestock into the seed-dispersal system partially restored the original network organization by strengthening the modular configuration. Moreover, after megafaunal extinctions, introduced species and some smaller native mammals became key components for the structure of the seed-dispersal network. We hypothesize that such changes in network structure affected both animal and plant assemblages, potentially contributing to the shaping of modern ecological communities. The ongoing extinction of key large vertebrates will lead to a variety of context-dependent rearranged ecological networks, most certainly affecting ecological and evolutionary processes.     

Gene expression profiling: opening the black box of plant ecosystem responses to global change

The use of genomic techniques to address ecological questions is emerging as the field of genomic ecology. Experimentation under environmentally realistic conditions to investigate the molecular response of plants to meaningful changes in growth conditions and ecological interactions is the defining feature of genomic ecology. Because the impact of global change factors on plant performance are mediated by direct effects at the molecular, biochemical, and physiological scales, gene expression analysis promises important advances in understanding factors that have previously been consigned to the 'black box' of unknown mechanism. Various tools and approaches are available for assessing gene expression in model and nonmodel species as part of global change biology studies. Each approach has its own unique advantages and constraints. A first generation of genomic ecology studies in managed ecosystems and mesocosms have provided a testbed for the approach and have begun to reveal how the experimental design and data analysis of gene expression studies can be tailored for use in an ecological context.     

Metagenomic exploration of antibiotic resistance in soil

The ongoing development of metagenomic approaches is providing the means to explore antibiotic resistance in nature and address questions that could not be answered previously with conventional culture-based strategies. The number of available environmental metagenomic sequence datasets is rapidly expanding and henceforth offer the ability to gain a more comprehensive understanding of antibiotic resistance at the global scale. Although there is now evidence that the environment constitutes a vast reservoir of antibiotic resistance gene determinants (ARGDs) and that the majority of ARGDs acquired by human pathogens may have an environmental origin, a better understanding of their diversity, prevalence and ecological significance may help predict the emergence and spreading of newly acquired resistances. Recent applications of metagenomic approaches to the study of ARGDs in natural environments such as soil should help overcome challenges concerning expanding antibiotic resistances.     

Consequences of adaptive behaviour for the structure and dynamics of food webs

Species coexistence within ecosystems and the stability of patterns of temporal changes in population sizes are central topics in ecological theory. In the last decade, adaptive behaviour has been proposed as a mechanism of population stabilization. In particular, widely distributed adaptive trophic behaviour (ATB), the fitness-enhancing changes in individuals' feeding-related traits due to variation in their trophic environment, may play a key role in modulating the dynamics of feeding relationships within natural communities. In this article, we review and synthesize models and results from theoretical research dealing with the consequences of ATB on the structure and dynamics of complex food webs. We discuss current approaches, point out limitations, and consider questions ripe for future research. In spite of some differences in the modelling and analytic approaches, there are points of convergence: (1) ATB promotes the complex structure of ecological networks, (2) ATB increases the stability of their dynamics, (3) ATB reverses May's negative complexity-stability relationship, and (4) ATB provides resilience and resistance of networks against perturbations. Current knowledge supports ATB as an essential ingredient for models of community dynamics, and future research that incorporates ATB will be well positioned to address questions important for basic ecological research and its applications.     

Advancing understanding of the complex nature of urban systems

Cities and urbanized regions are complex, dynamic, and highly integrated systems linking social, ecological, and technical infrastructure domains in ways that create deep challenges for good governance, policymaking, and planning. The combination of impacts from climate change in cities, air pollution, rapid population growth, multiple sources of development pressure and overall urban system complexity make it difficult for decision-makers to develop and guide development trajectories along more livable, equitable, and at the same time, more resilient pathways. Advancing urban sustainability and resilience agendas requires expanding the scope of inter- and trans-disciplinarity approaches, moving beyond the historically separate social–ecological and socio-technical approaches to jointly study social–ecological–technical infrastructure systems in cities. We take urban complexity as a given and suggest that in both research and practice we need to better capture and understand feedbacks, interdependencies, and non-linearities which create uncertainties and challenge the efficacy of governance practices to achieve normative goals for society. Here, we explore new methods, tools, and approaches to advance our understanding of urban system complexity through a series of journal special issue articles that examine urban structure–function relationships, urban sustainability transitions, green space availability, social–ecological memory, functional traits, and urban land use scenarios.     

Molecular approaches: advantages and artifacts in assessing bacterial diversity

Bacteria account for a major proportion of Earth’s biological diversity. They play essential roles in quite diverse environments and there has been an increasing interest in bacterial biodiversity. Research using novel and efficient tools to identify and characterize bacterial communities has been the key for elucidating biological activities with potential for industrial application. The current approach used for defining bacterial species is based on phenotypic and genomic properties. Traditional and novel DNA-based molecular methods are improving our knowledge of bacterial diversity in nature. Advances in molecular biology have been important for studies of diversity, considerably improving our knowledge of morphological, physiological, and ecological features of bacterial taxa. DNA–DNA hybridization, which has been used for many years, is still considered the golden standard for bacteria species identification. PCR-based methods investigating 16S rRNA gene sequences, and other approaches, such as the metagenome, have been used to study the physiology and diversity of bacteria and to identify novel genes with potential pharmaceutical and other biotechnological applications. We examined the advantages and limitations of molecular methods currently used to analyze bacterial diversity; these are mainly based on the 16S rRNA gene. These methods have allowed us to examine microorganisms that cannot be cultivated by routine methods and have also been useful for phylogenetic studies. We also considered the importance of improvements in microbe culture techniques and how we can combine different methods to allow a more appropriate assessment of bacterial diversity and to determine their real potential for industrial applications.     

Fluorescent nanoparticles as tools in ecology and physiology

Fluorescent nanoparticles (FNPs) have been widely used in chemistry and medicine for decades, but their employment in biology is relatively recent. Past reviews on FNPs have focused on chemical, physical or medical uses, making the extrapolation to biological applications difficult. In biology, FNPs have largely been used for biosensing and molecular tracking. However, concerns over toxicity in early types of FNPs, such as cadmium-containing quantum dots (QDs), may have prevented wide adoption. Recent developments, especially in non-Cd-containing FNPs, have alleviated toxicity problems, facilitating the use of FNPs for addressing ecological, physiological and molecule-level processes in biological research. Standardised protocols from synthesis to application and interdisciplinary approaches are critical for establishing FNPs in the biologists’ tool kit. Here, we present an introduction to FNPs, summarise their use in biological applications, and discuss technical issues such as data reliability and biocompatibility. We assess whether biological research can benefit from FNPs and suggest ways in which FNPs can be applied to answer questions in biology. We conclude that FNPs have a great potential for studying various biological processes, especially tracking, sensing and imaging in physiology and ecology.     

On the edge: The use of infrared thermography in monitoring responses of intertidal organisms to heat stress

Monitoring changes in the environment and the corresponding effects on biological systems still represents a major challenge in many marine and terrestrial ecological studies. Infrared thermography (IRT), and its application within the marine environment, represents an effective non-invasive tool for measuring the temperatures of organisms and their surrounding environment in situ. The use of IRT within the intertidal zone is particularly useful since habitat and organismal temperatures are highly variable across both fine spatial and temporal scales. We review the growing number of intertidal studies that utilise IRT to investigate the role of small-scale temperature variability in contributing to various demographic and ecological processes. In particular, we introduce two indicators of the thermal quality of intertidal habitats that can be readily used by ecologists but also management and conservation policy makers to assess the suitability of a given habitat for a range of species under actual and predicted climatic conditions. We also outline a range of potential applications involving IRT that have yet to be explored for monitoring coastal environments. These include combining photogrammetry, unmanned aerial vehicles and IRT to large-scale three-dimensional thermal maps of intertidal habitats. We also suggest ways in which this technology could facilitate environmental management objectives in a warming world, such as the identification and quantification of thermal refugia across various spatial and temporal scales. We affirm with previous studies that such thermal refugia are vital for the adaptation of intertidal communities to climate change and that IRT could facilitate more effective management and conservation of these areas. The IRT applications outlined in this review are by no means exhaustive or limited to rocky intertidal environments. We envision that IRT will become increasingly popular as environmental management agencies become increasingly concerned about global climate change and how to combat its negative consequences on ecosystems.     

Forecasting species range dynamics with process‐explicit models: matching methods to applications

Knowing where species occur is fundamental to many ecological and environmental applications. Species distribution models (SDMs) are typically based on correlations between species occurrence data and environmental predictors, with ecological processes captured only implicitly. However, there is a growing interest in approaches that explicitly model processes such as physiology, dispersal, demography and biotic interactions. These models are believed to offer more robust predictions, particularly when extrapolating to novel conditions. Many process–explicit approaches are now available, but it is not clear how we can best draw on this expanded modelling toolbox to address ecological problems and inform management decisions. Here, we review a range of process–explicit models to determine their strengths and limitations, as well as their current use. Focusing on four common applications of SDMs – regulatory planning, extinction risk, climate refugia and invasive species – we then explore which models best meet management needs. We identify barriers to more widespread and effective use of process‐explicit models and outline how these might be overcome. As well as technical and data challenges, there is a pressing need for more thorough evaluation of model predictions to guide investment in method development and ensure the promise of these new approaches is fully realised.     

Isolation by environment

The interactions between organisms and their environments can shape distributions of spatial genetic variation, resulting in patterns of isolation by environment (IBE) in which genetic and environmental distances are positively correlated, independent of geographic distance. IBE represents one of the most important patterns that results from the ways in which landscape heterogeneity influences gene flow and population connectivity, but it has only recently been examined in studies of ecological and landscape genetics. Nevertheless, the study of IBE presents valuable opportunities to investigate how spatial heterogeneity in ecological processes, agents of selection and environmental variables contributes to genetic divergence in nature. New and increasingly sophisticated studies of IBE in natural systems are poised to make significant contributions to our understanding of the role of ecology in genetic divergence and of modes of differentiation both within and between species. Here, we describe the underlying ecological processes that can generate patterns of IBE, examine its implications for a wide variety of disciplines and outline several areas of future research that can answer pressing questions about the ecological basis of genetic diversity.     

Seevögel im Südpolarmeer

Seabirds face a number of challenges in Antarctic and Subantarctic breeding areas, such as variations in food supply and changes in the ecosystem due to climate change, aggregation and competition from the limited number of suitable breeding areas, and inaccessible breeding areas due to changes in precipitation. Adjustments to irregular food supplies, such as flexible incubation and nesting times, and torpor in chicks can help seabirds keep pace with changes occurring due to climate change. Data loggers are used to better understand the responses of adult birds to changes in the ecosystem and the resulting population trends. Various data loggers are used for a variety of applications, from one gram light loggers for long‐term tracking across large scales to high‐resolution GPS loggers with acquisition of acceleration data that can also be used to model energy expenditure. In order to fully understand the movement ecology of seabirds, several approaches need to be considered: ecological segregation in space, time and choice of food, energy landscapes and the non‐lethal effects of predation (landscapes of fear).     

Systems approaches in global change and biogeochemistry research

Systems approaches have great potential for application in predictive ecology. In this paper, we present a range of examples, where systems approaches are being developed and applied at a range of scales in the field of global change and biogeochemical cycling. Systems approaches range from Bayesian calibration techniques at plot scale, through data assimilation methods at regional to continental scales, to multi-disciplinary numerical model applications at country to global scales. We provide examples from a range of studies and show how these approaches are being used to address current topics in global change and biogeochemical research, such as the interaction between carbon and nitrogen cycles, terrestrial carbon feedbacks to climate change and the attribution of observed global changes to various drivers of change. We examine how transferable the methods and techniques might be to other areas of ecosystem science and ecology.     

Genomics, environmental genomics and the issue of microbial species

A microbial species concept is crucial for interpreting the variation detected by genomics and environmental genomics among cultivated microorganisms and within natural microbial populations. Comparative genomic analyses of prokaryotic species as they are presently described and named have led to the provocative idea that prokaryotes may not form species as we think about them for plants and animals. There are good reasons to doubt whether presently recognized prokaryotic species are truly species. To achieve a better understanding of microbial species, we believe it is necessary to (i) re-evaluate traditional approaches in light of evolutionary and ecological theory, (ii) consider that different microbial species may have evolved in different ways and (iii) integrate genomic, metagenomic and genome-wide expression approaches with ecological and evolutionary theory. Here, we outline how we are using genomic methods to (i) identify ecologically distinct populations (ecotypes) predicted by theory to be species-like fundamental units of microbial communities, and (ii) test their species-like character through in situ distribution and gene expression studies. By comparing metagenomic sequences obtained from well-studied hot spring cyanobacterial mats with genomic sequences of two cultivated cyanobacterial ecotypes, closely related to predominant native populations, we can conduct in situ population genetics studies that identify putative ecotypes and functional genes that determine the ecotypes' ecological distinctness. If individuals within microbial communities are found to be grouped into ecologically distinct, species-like populations, knowing about such populations should guide us to a better understanding of how genomic variation is linked to community function.     

Essence of life: essential genes of minimal genomes

Essential genes are absolutely required for cell survival. Determination of the universal minimal set of genes needed to sustain life is, therefore, expected to contribute greatly to our understanding of life at its simplest level, with applications in medicine and synthetic biology. The search for the minimal genome has led to the identification of often variable gene sets. We argue here that, based on the outcome of these analyses, it is becoming increasingly evident that some genes, and the functions encoded by them, are absolutely necessary for the survival of any living entity, whereas others can be omitted. We also examine ways of determining the minimal genome and discuss possible practical applications of a minimal cell.     

Unruly Places: Urban Governance and the Persistence of Illegality in Hong Kong's Urban Squatter Areas

Our knowledge of the governance of cities has expanded in recent years with the application of Foucauldian approaches. However, the majority of such work has concentrated on areas where governmental control is heightened, such as prisons and asylums. In this article, I discuss unruly places where governments have less control than usual: squatter settlements. Hong Kong has had substantial numbers of squatters throughout its postwar rise from dire poverty to contemporary prosperity. This article draws on documentary analysis and field research from 1982–85 and 1999–2000 to examine changes in the way that the government attempts to regulate these illegally occupied spaces and the ways in which interaction between administrative interventions and the responses of those living there makes the persistence of illegal occupation possible. I argue that three different phases of regulation can be identified: repression, resettlement, and exclusion. While there is considerable continuity in some practices of intervention such as toleration, the nature and outcomes of such practices vary with the changing context and other features of the regulatory regime, [regulation, squatters, governance, illegality, Hong Kong]