Phylogenetic and functional dissimilarity does not increase during temporal heathland succession.

Pipeline architectures provide a versatile and efficient mechanism for constructing visualizations, and they have been implemented in numerous libraries and applications over the past two decades. In addition to allowing developers and users to freely combine algorithms, visualization pipelines have proven to work well when streaming data and scale well on parallel distributed-memory computers. However, current pipeline visualization frameworks have a critical flaw: they are unable to manage time varying data. As data flows through the pipeline, each algorithm has access to only a single snapshot in time of the data. This prevents the implementation of algorithms that do any temporal processing such as particle tracing; plotting over time; or interpolation, fitting, or smoothing of time series data. As data acquisition technology improves, as simulation time-integration techniques become more complex, and as simulations save less frequently and regularly, the ability to analyze the time-behavior of data becomes more important. This paper describes a modification to the traditional pipeline architecture that allows it to accommodate temporal algorithms. Furthermore, the architecture allows temporal algorithms to be used in conjunction with algorithms expecting a single time snapshot, thus simplifying software design and allowing adoption into existing pipeline frameworks. Our architecture also continues to work well in parallel distributed-memory environments. We demonstrate our architecture by modifying the popular VTK framework and exposing the functionality to the ParaView application. We use this framework to apply time-dependent algorithms on large data with a parallel cluster computer and thereby exercise a functionality that previously did not exist.

AimGiant clams are iconic bivalves known to serve numerous ecological roles contributing to the functioning of coral reef ecosystems. In the next decade, giant clams will continue to face critical anthropogenic pressures from over‐exploitation for their meat and shells, the aquarium trade and global warming that threaten the persistence of their species. Here, we assess the relationships between different biodiversity components to inform conservation prioritization and management.LocationIndo‐Pacific marine realm.MethodsWe quantified taxonomic, functional and phylogenetic diversity measures throughout 25 marine provinces and assessed their relationships for all 12 giant clam species in the subfamily Tridacninae. These biodiversity measures were used to identify potentially threatened species that contribute disproportionately to trait and evolutionary diversity and to highlight areas for global conservation prioritization of giant clam species.ResultsAnalyses show positive correlations among species richness (SR), functional diversity (FD) and phylogenetic diversity (PD), with the strongest relationship between FD and PD. However, spatial patterns of higher‐than‐expected FD and PD are incongruent with SR patterns, indicating that SR omits information associated with functional and phylogenetic diversity. Among the giant clam species, Tridacna gigas and Hippopus spp. have the greatest functional and evolutionary diversity contributions within assemblies, respectively. Spatial analyses reveal that the Bay of Bengal, Andaman and numerous parts of the eastern Indo‐Pacific potentially hold higher‐than‐expected FD and PD levels relative to their SR and thus warrant more attention with respect to conserving the diversity of giant clams.ConclusionsOur findings underscore the importance of integrating functional trait contributions and evolutionary diversity into conservation planning to better differentiate giant clam assemblages, as it remains challenging to implement dedicated conservation given the limited resources. This study provides comprehensive biodiversity information for managers to initiate measures that holistically capture species' ecological and evolutionary standings across global reef ecosystems.

Evaluating the social impact indicators of engineered products is crucial to better understanding how products affect individuals’ lives and discover how to design for positive social impact. Most existing methods for evaluating social impact indicators require direct human interaction with users of a product, such as one-on-one interviews. These interactions produce high-fidelity data that are rich in information but provide only a single snapshot in time of the product’s impacts and are less frequently collected due to the significant human resources and cost associated with obtaining them. A framework is proposed that describes how low-fidelity data passively obtained using remote sensors, satellites, and digital technology can be collected and correlated with high-fidelity, low-frequency data using machine learning. Using this framework provides an inexpensive way to continuously monitor the social impact indicators of products by augmenting high-fidelity, low-frequency data with low-fidelity, continuously-collected data using machine learning. We illustrate an application of this framework by demonstrating how it can be used to examine the gender-related social impact indicators of water pumps in Uganda. The provided example uses a deep learning model to correlate pump handle movement (measured via an integrated motion unit) with user type (man, woman, or child) of 1,200 hand pump users.

This study presents a methodology for quantifying the tradeoffs between sampling costs and local concentration estimation errors in an existing groundwater monitoring network. The method utilizes historical data at a single snapshot in time to identify potential spatial redundancies within a monitoring network. Spatially redundant points are defined to be monitoring locations that do not appreciably increase local estimation errors if they are not sampled. The study combines nonlinear spatial interpolation with the nondominated sorted genetic algorithm (NSGA) to identify the tradeoff curve (or Pareto frontier) between sampling costs and local concentration estimation errors. Guidelines are given for using theoretical relationships from the field of genetic and evolutionary computation for population sizing and niching to ensure that the NSGA is competently designed to navigate the problem's decision space. Additionally, both a selection pressure analysis and a niching-based elitist enhancement of the NSGA are presented, which were integral to the algorithm's efficiency in quantifying the Pareto frontier for costs and estimation errors. The elitist NSGA identified 34 of 36 members of the Pareto optimal set attained from enumerating the monitoring application's decision space; this represents a substantial improvement over the standard NSGA, which found at most 21 of 36 members.

Genotyping tumor tissue in search of somatic genetic alterations for actionable information has become routine practice in clinical oncology. Although these sequence alterations are highly informative, sampling tumor tissue has significant inherent limitations; tumor tissue is a single snapshot in time, is subject to selection bias resulting from tumor heterogeneity, and can be difficult to obtain. Cell-free fragments of DNA are shed into the bloodstream by cells undergoing apoptosis or necrosis, and the load of circulating cell-free DNA (cfDNA) correlates with tumor staging and prognosis. Moreover, recent advances in the sensitivity and accuracy of DNA analysis have allowed for genotyping of cfDNA for somatic genomic alterations found in tumors. The ability to detect and quantify tumor mutations has proven effective in tracking tumor dynamics in real time as well as serving as a liquid biopsy that can be used for a variety of clinical and investigational applications not previously possible.

RWB and Institutional Change The current version of the NPC is a “representation within bounds” parliament. Deputies convey citizen grievances but shy away from sensitive political issues, and the government in turn displays partial responsiveness to their concerns. Deputies are socialized into this behavioral pattern and are punished or rewarded depending on the quality of their representative behavior. They also enjoy substantial rents for their services. The analysis in this book is focused on a single snapshot in time, the 11th NPC (2008–12) under the Hu-Wen administration. This decision was made largely on the basis of data availability, but it leaves open the question of how the CCP regime arrived at this equilibrium. How has representation in the NPC changed over time? How long has the representation within bounds system been in place, and what precisely spurred its creation? And importantly, can we expect it to continue in the future? The purpose of this chapter is to explore and explain the historical evolution of the National People's Congress. I will use the ideas from the formal theory in Chapter 2 to aid in the presentation and interpretation of the history. This approach has been referred to as an “analytic narrative” or a “theory guided narrative” (Bates et al. 2000; Buthe 2002; Levi 2002; Capoccia and Kelemen 2007), and it can be helpful in assessing the plausibility of a particular framework and identifying relevant actors and trends (Buthe 2002). In line with rational-choice institutionalism, I ascribe to the view that institutions can be manipulated to meet the ends of different political actors (Shepsle 2006; Pepinsky 2014). I will also draw on concepts developed by proponents of historical institutionalism, particularly the idea that institutional development is often the result of rapid change followed by institutional reproduction (Thelen 1999; Capoccia and Kelemen 2007). Recall from the model in Chapter 2 that for the Autocrat, the ideal level of representation is a function of the probability of a revolution being successful, π . At extremely low values of π , the Citizen cannot credibly threaten the regime, and there is no need for policy responsiveness. The Autocrat can get away with minimal representation and prefers the Stable Nonresponsive equilibrium E 2 . 1.

Scorpion venoms are mixtures of proteins, peptides and small molecular compounds with high specificity for ion channels and are therefore considered to be promising candidates in the venoms-to-drugs pipeline. Transcriptomes are important tools for studying the composition and expression of scorpion venom. Unfortunately, studying the venom gland transcriptome traditionally requires sacrificing the animal and therefore is always a single snapshot in time. This paper describes a new way of generating a scorpion venom gland transcriptome without sacrificing the animal, thereby allowing the study of the transcriptome at various time points within a single individual. By comparing these venom-derived transcriptomes to the traditional whole-telson transcriptomes we show that the relative expression levels of the major toxin classes are similar. We further performed a multi-day extraction using our proposed method to show the possibility of doing a multiple time point transcriptome analysis. This allows for the study of patterns of toxin gene activation over time a single individual, and allows assessment of the effects of diet, season and other factors that are known or likely to influence intraindividual venom composition. We discuss the gland characteristics that may allow this method to be successful in scorpions and provide a review of other venomous taxa to which this method may potentially be successfully applied.

Resolving plant development in space and time with single-cell genomics

This chapter focuses on cross-sectional and longitudinal studies. cross-sectional studies involve the analysis of usually quantitative data collected at a single snapshot in time. The unit of observation might be people or countries, and those are measured only once, all at approximately the same time. In contrast, longitudinal studies (also referred to as repeated measures studies) involve analysis on multiple occasions over time, where the same individuals (or countries) — the panel — are measured on each occasion. As such, the unit of observation is occasions, and there are multiple occasions/measures of each individual. A subcategory of longitudinal studies is event-history/survival/duration analysis, where the dependent variable is binary and the focus is on causes of changes between the two states of the outcome. Note that in comparison, time series analysis typically involves fewer individuals (often only one) and a larger number of time points. A third type of study, situated in between longitudinal and cross-sectional studies, is repeated cross-sectional analysis, which involves the analysis of multiple cross-sectional data sets over time, and different individuals are measured in each wave of the survey. Here, the unit of observation is individuals, and there are multiple individuals measured in each survey wave.

Colorectal cancers (CRCs) evolve by a reiterative process of genetic diversification and clonal evolution. The molecular profile of CRC is routinely assessed in surgical or bioptic samples. Genotyping of CRC tissue has inherent limitations; a tissue sample represents a single snapshot in time, and it is subjected to spatial selection bias owing to tumor heterogeneity. Repeated tissue samples are difficult to obtain and cannot be used for dynamic monitoring of disease progression and response to therapy. We exploited circulating tumor DNA (ctDNA) to genotype colorectal tumors and track clonal evolution during treatment with the epidermal growth factor receptor (EGFR)-specific antibodies cetuximab or panitumumab. We identified alterations in ctDNA of patients with primary or acquired resistance to EGFR blockade in the following genes: KRAS, NRAS, MET, ERBB2, FLT3, EGFR and MAP2K1. Mutated KRAS clones, which emerge in blood during EGFR blockade, decline upon withdrawal of EGFR-specific antibodies, indicating that clonal evolution continues beyond clinical progression. Pharmacogenomic analysis of CRC cells that had acquired resistance to cetuximab reveals that upon antibody withdrawal KRAS clones decay, whereas the population regains drug sensitivity. ctDNA profiles of individuals who benefit from multiple challenges with anti-EGFR antibodies exhibit pulsatile levels of mutant KRAS. These results indicate that the CRC genome adapts dynamically to intermittent drug schedules and provide a molecular explanation for the efficacy of rechallenge therapies based on EGFR blockade.

The efficacy of currently available repair techniques has been assessed for a wide variety of defect types encountered on advanced lithographic masks. Focused ion beam (FIB) with gas-assisted etching and deposition, electron beam induced chemical processing (EBIC), and atomic force microscope based nano-machining (RAVE) were among the different methodologies evaluated. Various types of optical phase-shifting masks for the 45nm lithographic node, as well as nano-imprint lithography (NIL) templates, were used as test vehicles. Defect imaging resolution, spatial process confinement, repair edge placement, end-pointing control, sample damage (undesired changes in topographic or optical properties), and future extendibility served as the primary metrics for gauging repair performance. The primary aim of this study was to provide a single snapshot in time of the current development status of each tool for the context of 45nm node mask repair specifications and by no means were there any expectations for a final solution to already be commercially available. However, the results obtained from these tests should provide useful feedback and information to help improve the learning cycle for the development of 45nm lithographic node mask repair systems.

Functional diversity is a component of biodiversity that generally concerns the range of things that organisms do in communities and ecosystems. Here, we review how functional diversity can explain and predict the impact of organisms on ecosystems and thereby provide a mechanistic link between the two. Critical points in developing predictive measures of functional diversity are the choice of functional traits with which organisms are distinguished, how the diversity of that trait information is summarized into a measure of functional diversity, and that the measures of functional diversity are validated through quantitative analyses and experimental tests. There is a vast amount of trait information available for plant species and a substantial amount for animals. Choosing which traits to include in a particular measure of functional diversity will depend on the specific aims of a particular study. Quantitative methods for choosing traits and for assigning weighting to traits are being developed, but need much more work before we can be confident about trait choice. The number of ways of measuring functional diversity is growing rapidly. We divide them into four main groups. The first, the number of functional groups or types, has significant problems and researchers are more frequently using measures that do not require species to be grouped. Of these, some measure diversity by summarizing distances between species in trait space, some by estimating the size of the dendrogram required to describe the difference, and some include information about species' abundances. We show some new and important differences between these, as well as what they indicate about the responses of assemblages to loss of individuals. There is good experimental and analytical evidence that functional diversity can provide a link between organisms and ecosystems but greater validation of measures is required. We suggest that non-significant results have a range of alternate explanations that do not necessarily contradict positive effects of functional diversity. Finally, we suggest areas for development of techniques used to measure functional diversity, highlight some exciting questions that are being addressed using ideas about functional diversity, and suggest some directions for novel research.

Functional Diversity Measures

Darwin’s naturalisation hypothesis posing that phylogenetic distance of alien species to native residents predicts invasion success, and Elton’s diversity–invasibility hypothesis posing that diversity of native communities confers resistance to invasion, are both rooted in ideas of species coexistence. Because the two hypotheses are inherently linked, the mechanisms underlying them may interact in driving the invasion success. Even so, these links and interactions have not been explicitly disentangled in one experimental study before. To disentangle the links between the two hypotheses, we used 36 native grassland herbs to create greenhouse mesocosms with 90 grassland communities of different diversities, and introduced each of five herbaceous alien species as seeds and seedlings. We used phylogeny and four functional traits (plant height, specific leaf area, leaf size, and seed mass) to calculate different measures of phylogenetic and functional distance and diversity. Specifically, we tested how the alien–native distance (phylogenetic or functional) and the native diversity (phylogenetic or functional) affected each other in their effects on germination, seedling survival, growth, and reproduction of the aliens. Overall, our results supported both hypotheses. Multivariate functional distance based on four traits jointly had stronger positive effects than phylogenetic distance and the univariate ones based on each trait separately. Moreover, the aliens were more successful if they were more competitive by being taller and having larger leaves with a lower SLA than the native residents. Univariate functional diversity based on each trait separately had stronger negative effects than phylogenetic and multivariate functional diversity. Most importantly, we found that the effects of alien–native phylogenetic and multivariate functional distance became stronger as diversity increased. Our analyses with single traits also showed that the strength of the effects of both alien–native hierarchical functional distances (indicative of competitive inequalities) and absolute functional distances (indicative of niche differences) increased at higher diversities, where competition is more severe. Synthesis. Our study explicitly demonstrates for the first time how the mechanisms underlying the two classical invasion hypotheses interact in driving invasion success in grassland communities. This may help to explain some of the puzzling results of studies testing either of the two hypotheses.

In forested ecosystems, it remains unclear whether environmental conditions, resource competition or their joint effects explain non-randomly distributed species pattern. Recently, trait-based approaches have been recognized as an important tool to infer processes governing community assembly patterns. In this study, we quantify patterns of functional composition and diversity to study how tree species coexistence is influenced by abiotic factors and biotic interactions in a species-rich temperate old-growth forest. In a 25 ha (500 × 500 m) fully mapped forest plot, we calculated functional composition (community weighted mean) and diversity of five key traits considering two spatial scales (20 × 20 and 50 × 50 m quadrats). We compared the observed patterns in functional diversity with randomly generated null communities to test for the presence of non-random patterns in community assembly, and studied the variation of functional composition and diversity along gradients of soil conditions to test for the shift in assembly processes along resource gradients. Functional diversity differed from null expectations depending on the spatial scale considered. In broad-scale quadrats (50 × 50 m), functional diversity in wood specific gravity (WSG) and leaf area (LA) was lower than expected by chance, whereas functional diversity in specific root length (SRL) was greater than expected. In small quadrats (20 × 20 m), functional diversity was lower than expected by chance in specific leaf area (SLA) and when considering all traits in combination. Functional composition and diversity varied along the soil resource gradient but the results were dependent on the scale considered. We found an increase in functional composition in maximum height (H) and WSG and a reduction in the functional diversity in most of traits suggesting an increase in competition with the increase in soil water content at small scale. The trait dispersion pattern for all traits in combination had no directional changes with some of individual traits generating more clear dispersion trend when the dominant competitor Pinus koraiensis was removed from the community dataset. The results presented here suggest that community assembly is governed by non-random processes in the studied forests. Interestingly, the choice of quadrat size seems to be crucial to describe community patterns and infer the forces governing community assembly. The consideration of different traits and environmental gradients allowed us to discover that different assembly mechanisms operate simultaneously in the studied forest.