Predictive Models for Freshwater Biological Assessment: Statistical Approaches,Biological Elements and the Iberian Peninsula Experience: A Review

In the last three decades, predictive models have been developed and applied worldwide for freshwater bioassessment. They consist of statistical tools that follow the concept of the Reference Condition Approach. Composed of several sequential steps, these assessment tools assess the deviation of given site assemblages from the expected biological condition in the absence of human disturbance. The most common approaches (RIVPACS/AUSRIVAS and BEAST) are based on a posteriori classifications that use the biological composition of a community to classify reference sites in groups, and afterwards to establish which environmental features best discriminate the biological groups obtained. Here, we review the predictive modeling procedures used in freshwaters bioassessment (RIVPACS/AUSRIVAS, BEAST, ANNA, Artificial Neural Networks, Bayesian Belief Networks and others) as well as the biological elements to which they have been applied. We also review the Spanish and Portuguese experiences in the development and application of predictive models, with particular attention to regional environmental conditions, the different modeling approaches, and the available implementation tools. Moreover, and considering the natural continuity within the Iberian Peninsula (which include several transnational rivers), we discuss the possibilities of the development of common predictive models across the region, considering all factors that may influence their performance, such as the target scale used to develop the models (regional or peninsular); common reference criteria; sampling and sorting procedures; the taxonomic resolution used in the models; the temporal variability (mainly in the Iberian Mediterranean region); and the biological elements to consider. We concluded that there are good technical conditions for the implementations of a common predictive approach throughout the Iberian Peninsula, which should allow a global biological assessment of streams with different biological elements and seasons that could be used by water managers in the context of the Water Framework Directive. (© 2011 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Technology transfer from worms and flies to vertebrates: transposition-based genome manipulations and their future perspectives

To meet the increasing demand of linking sequence information to gene function in vertebrate models, genetic modifications must be introduced and their effects analyzed in an easy, controlled, and scalable manner. In the mouse, only about 10% (estimate) of all genes have been knocked out, despite continuous methodologic improvement and extensive effort. Moreover, a large proportion of inactivated genes exhibit no obvious phenotypic alterations. Thus, in order to facilitate analysis of gene function, new genetic tools and strategies are currently under development in these model organisms. Loss of function and gain of function mutagenesis screens based on transposable elements have numerous advantages because they can be applied in vivo and are therefore phenotype driven, and molecular analysis of the mutations is straightforward. At present, laboratory harnessing of transposable elements is more extensive in invertebrate models, mostly because of their earlier discovery in these organisms. Transposons have already been found to facilitate functional genetics research greatly in lower metazoan models, and have been applied most comprehensively in Drosophila. However, transposon based genetic strategies were recently established in vertebrates, and current progress in this field indicates that transposable elements will indeed serve as indispensable tools in the genetic toolkit for vertebrate models. In this review we provide an overview of transposon based genetic modification techniques used in higher and lower metazoan model organisms, and we highlight some of the important general considerations concerning genetic applications of transposon systems.     

Hydrodynamic properties of rigid particles: comparison of different modeling and computational procedures.

The hydrodynamic properties of rigid particles are calculated from models composed of spherical elements (beads) using theories developed by Kirkwood, Bloomfield, and their coworkers. Bead models have usually been built in such a way that the beads fill the volume occupied by the particles. Sometimes the beads are few and of varying sizes (bead models in the strict sense), and other times there are many small beads (filling models). Because hydrodynamic friction takes place at the molecular surface, another possibility is to use shell models, as originally proposed by Bloomfield. In this work, we have developed procedures to build models of the various kinds, and we describe the theory and methods for calculating their hydrodynamic properties, including approximate methods that may be needed to treat models with a very large number of elements. By combining the various possibilities of model building and hydrodynamic calculation, several strategies can be designed. We have made a quantitative comparison of the performance of the various strategies by applying them to some test cases, for which the properties are known a priori. We provide guidelines and computational tools for bead modeling.     

The evolution of mobile DNAs: when will transposons create phylogenies that look as if there is a master gene?

Some families of mammalian interspersed repetitive DNA, such as the Alu SINE sequence, appear to have evolved by the serial replacement of one active sequence with another, consistent with there being a single source of transposition: the "master gene." Alternative models, in which multiple source sequences are simultaneously active, have been called "transposon models." Transposon models differ in the proportion of elements that are active and in whether inactivation occurs at the moment of transposition or later. Here we examine the predictions of various types of transposon model regarding the patterns of sequence variation expected at an equilibrium between transposition, inactivation, and deletion. Under the master gene model, all bifurcations in the true tree of elements occur in a single lineage. We show that this property will also hold approximately for transposon models in which most elements are inactive and where at least some of the inactivation events occur after transposition. Such tree shapes are therefore not conclusive evidence for a single source of transposition.     

Research frontiers in null model analysis

Null models are pattern‐generating models that deliberately exclude a mechanism of interest, and allow for randomization tests of ecological and biogeographic data. Although they have had a controversial history, null models are widely used as statistical tools by ecologists and biogeographers. Three active research fronts in null model analysis include biodiversity measures, species co‐occurrence patterns, and macroecology. In the analysis of biodiversity, ecologists have used random sampling procedures such as rarefaction to adjust for differences in abundance and sampling effort. In the analysis of species co‐occurrence and assembly rules, null models have been used to detect the signature of species interactions. However, controversy persists over the details of computer algorithms used for randomizing presence–absence matrices. Finally, in the newly emerging discipline of macroecology, null models can be used to identify constraining boundaries in bivariate scatterplots of variables such as body size, range size, and population density. Null models provide specificity and flexibility in data analysis that is often not possible with conventional statistical tests.     

The maximum entropy formalism and the idiosyncratic theory of biodiversity

Why does the neutral theory, which is based on unrealistic assumptions, predict diversity patterns so accurately? Answering questions like this requires a radical change in the way we tackle them. The large number of degrees of freedom of ecosystems pose a fundamental obstacle to mechanistic modelling. However, there are tools of statistical physics, such as the maximum entropy formalism (MaxEnt), that allow transcending particular models to simultaneously work with immense families of models with different rules and parameters, sharing only well‐established features. We applied MaxEnt allowing species to be ecologically idiosyncratic, instead of constraining them to be equivalent as the neutral theory does. The answer we found is that neutral models are just a subset of the majority of plausible models that lead to the same patterns. Small variations in these patterns naturally lead to the main classical species abundance distributions, which are thus unified in a single framework.     

Transposable elements in fish functional genomics: technical challenges and perspectives

The recent introduction of several transposable elements in zebrafish opens new frontiers for genetic manipulation in this important vertebrate model. This review discusses transposable elements as mutagenesis tools for fish functional genomics. We review various mutagenesis strategies that were previously applied in other genetic models, such as Drosophila, Arabidopsis, and mouse, that may be beneficial if applied in fish. We also discuss the forthcoming challenges of high-throughput functional genomics in fish.     

Regulated transport as a mechanism for pattern generation: Capabilities for phyllotaxis and beyond

Large-scale pattern formation is a frequently occurring phenomenon in biological organisms, and several local interaction rules for generating such patterns have been suggested. A mechanism driven by feedback between the plant hormone auxin and its polarly localized transport mediator PINFORMED1 has been proposed as a model for phyllotactic patterns in plants. It has been shown to agree with current biological experiments at a molecular level as well as with respect to the resulting patterns. We present a thorough investigation of variants of models based on auxin-regulated polarized transport and use analytical and numerical tools to derive requirements for these models to drive spontaneous pattern formation. We find that auxin concentrations in neighboring cells can feed back either on exocytosis or endocytosis and still produce patterns. In agreement with mutant experiments, the active cellular efflux is shown to be more important for pattern capabilities as compared to active influx. We also find that the feedback must originate from neighboring cells rather than from neighboring walls and that intracellular competition for the transport mediator is required for patterning. The importance of model parameters is investigated, especially regarding robustness to perturbations of experimentally estimated parameter values. Finally, the regulated transport mechanism is shown to be able to generate Turing patterns of various types.     

Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa

Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations.     

Climate change-integrated conservation strategies

Aim Conservation strategies currently include little consideration of climate change. Insights about the biotic impacts of climate change from biogeography and palaeoecology, therefore, have the potential to provide significant improvements in the effectiveness of conservation planning. We suggest a collaboration involving biogeography, ecology and applied conservation. The resulting Climate Change‐integrated Conservation Strategies (CCS) apply available tools to respond to the conservation challenges posed by climate change. Location The focus of this analysis is global, with special reference to high biodiversity areas vulnerable to climate change, particularly tropical montane settings. Methods Current tools from climatology, biogeography and ecology applicable to conservation planning in response to climate change are reviewed. Conservation challenges posed by climate change are summarized. CCS elements are elaborated that use available tools to respond to these challenges. Results Five elements of CCS are described: regional modelling; expanding protected areas; management of the matrix; regional coordination; and transfer of resources. Regional modelling uses regional climate models, biotic response models and sensitivity analysis to identify climate change impacts on biodiversity at a regional scale appropriate for conservation planning. Expansion of protected areas management and systems within the planning region are based on modelling results. Management of the matrix between protected areas provides continuity for processes and species range shifts outside of parks. Regional coordination of park and off‐park efforts allows harmonization of conservation goals across provincial and national boundaries. Finally, implementation of these CCS elements in the most biodiverse regions of the world will require technical and financial transfer of resources on a global scale. Main conclusions Collaboration across disciplines is necessary to plan conservation responses to climate change adequately. Biogeography and ecology provide insights into the effects of climate change on biodiversity that have not yet been fully integrated into conservation biology and applied conservation management. CCS provide a framework in which biogeographers, ecologists and conservation managers can collaborate to address this need. These planning exercises take place on a regional level, driven by regional climate models as well as general circulation models (GCMs), to ensure that regional climate drivers such as land use change and mesoscale topography are adequately represented. Sensitivity analysis can help address the substantial uncertainty inherent in projecting future climates and biodiversity response.     

基于点云技术的乡村景观遗产空间信息记录与可视化方法研究

点云技术为提升乡村景观遗产保护方法带来了重要机遇。从乡村景观的遗产价值保护出发,以识别乡村景观空间模式为目标,探索如何运用点云技术定量化记录和表现乡村景观的空间信息。以贵州安顺鲍家屯古村落为研究案例,全面集成数字近景摄影测量技术、激光雷达技术和点云可视化技术,构建了一套多尺度的空间信息数字化采集、处理和分析方法,能够快速、精确、全面地记录和表现乡村景观的空间特征,为识别其空间模式提供数据基础,也为遗产保护和发展提供新的视角和工具。     

The FaceBase Consortium: a comprehensive program to facilitate craniofacial research

The FaceBase Consortium consists of ten interlinked research and technology projects whose goal is to generate craniofacial research data and technology for use by the research community through a central data management and integrated bioinformatics hub. Funded by the National Institute of Dental and Craniofacial Research (NIDCR) and currently focused on studying the development of the middle region of the face, the Consortium will produce comprehensive datasets of global gene expression patterns, regulatory elements and sequencing; will generate anatomical and molecular atlases; will provide human normative facial data and other phenotypes; conduct follow up studies of a completed genome-wide association study; generate independent data on the genetics of craniofacial development, build repositories of animal models and of human samples and data for community access and analysis; and will develop software tools and animal models for analyzing and functionally testing and integrating these data. The FaceBase website (http://www.facebase.org) will serve as a web home for these efforts, providing interactive tools for exploring these datasets, together with discussion forums and other services to support and foster collaboration within the craniofacial research community.     

Equivalent genetic regulatory networks in different contexts recover contrasting spatial cell patterns that resemble those in Arabidopsis root and leaf epidermis: a dynamic model

In Arabidopsis thaliana, leaf and root epidermis hairs exhibit contrasting spatial arrangements even though the genetic networks regulating their respective cell-fate determination have very similar structures and components. We integrated available experimental data for leaf and root hair patterning in dynamic network models which may be reduced to activator-inhibitor models. This integration yielded expected results for these kinds of dynamic models, including striped and dotted cell patterns which are characteristic of root and leaf epidermis, respectively. However, these formal tools have led us to novel insights on current data and to put forward precise hypotheses which can be addressed experimentally. In particular, despite subtle differences in the root and leaf networks, these have equivalent dynamical behaviors. Our simulations also suggest that only when a biasing signal positively affects an activator in the network, the system recovers striped cellular patterns similar to those of root epidermis. We also postulate that cell shape may affect pattern stability in the root. Our results thus support the idea that in this and other cases, contrasting spatial cell patterns and other evolutionary morphogenetic novelties originate from conserved genetic network modules subject to divergent contextual traits.     

Shedding Light on Class-Specific Wiring: Development of Intrinsically Photosensitive Retinal Ganglion Cell Circuitry

Neural circuits associated with retinal ganglion cells have long been used as models for investigating the mechanisms that govern circuit development and function. Similar to neurons in the brain, retinal ganglion cells are subdivided into distinct classes based upon their morphology, physiology, and patterns of connectivity. Newly developed transgenic tools in which individual classes of retinal ganglion cells are labeled with reporter proteins have recently provided a method to study the development of their class-specific circuitry. Here, we examine a single class of intrinsically photosensitive retinal ganglion cells and discuss their class-specific circuitry, as well as the cellular and molecular mechanisms that govern assembly of this circuitry.     

A machine‐learning approach for extending classical wildlife resource selection analyses

Resource selection functions (RSFs) are tremendously valuable for ecologists and resource managers because they quantify spatial patterns in resource utilization by wildlife, thereby facilitating identification of critical habitat areas and characterizing specific habitat features that are selected or avoided. RSFs discriminate between known‐use resource units (e.g., telemetry locations) and available (or randomly selected) resource units based on an array of environmental features, and in their standard form are performed using logistic regression. As generalized linear models, standard RSFs have some notable limitations, such as difficulties in accommodating nonlinear (e.g., humped or threshold) relationships and complex interactions. Increasingly, ecologists are using flexible machine‐learning methods (e.g., random forests, neural networks) to overcome these limitations. Herein, we investigate the seasonal resource selection patterns of mule deer (Odocoileus hemionus) by comparing a logistic regression framework with random forest (RF), a popular machine‐learning algorithm. Random forest (RF) models detected nonlinear relationships (e.g., optimal ranges for slope and elevation) and complex interactions which would have been very challenging to discover and characterize using standard model‐based approaches. Compared with standard RSF models, RF models exhibited improved predictive skill, provided novel insights about resource selection patterns of mule deer, and, when projected across a relevant geographic space, manifested notable differences in predicted habitat suitability. We recommend that wildlife researchers harness the strengths of machine‐learning tools like RF in addition to “classical” tools (e.g., mixed‐effects logistic regression) for evaluating resource selection, especially in cases where extensive telemetry data sets are available.     

HyPaLib: a database of RNAs and RNA structural elements defined by hybrid patterns

The database, called HyPaLib (for Hybrid Pattern Library), contains annotated structural elements characteristic for certain classes of structural and/or functional RNAs. These elements are described in a language specifically designed for this purpose. The language allows convenient specification of hybrid patterns, i.e. motifs consisting of sequence features and structural elements together with sequence similarity and thermodynamic constraints. We are currently developing software tools that allow a user to search sequence databases for any pattern in HyPaLib, thus providing functionality which is similar to PROSITE, but dedicated to the more complex patterns in RNA sequences. HyPaLib is available at http://bibiserv. techfak.uni-bielefeld.de/HyPa/.     

Transposable elements.

Transposable elements comprise a major fraction of eukaryotic genomes. They are studied both because of their intrinsic biological interest and because they can be exploited as valuable research tools. Many interesting papers dealing with various aspects of the biology of these elements have been published during the past year and a number of new elements have been reported. Four areas in which particularly valuable contributions have been made are the mechanisms of transposition, the regulation of transposition, the use of transposable elements as research tools, and the biological function of transposable elements.     

Legume genomes: more than peas in a pod

A growing array of sequence-based tools is helping to reveal the organization, evolution and syntenic relationships of legume genomes. The results indicate that legumes form a coherent taxonomic group with frequent and widespread macro- and microsynteny. This is good news for two model legume systems, Medicago truncatula and Lotus japonicus. Indeed, both models have recently been used to clone and characterize genes for nodulation-related receptors that were originally described in legumes with more complex genomes. Studies of legume genomes have also provided insight into genome size, gene clustering, genome duplications and repetitive elements. To understand legume genomes better, it will be necessary to develop tools for studying under-represented taxa beyond the relatively small group of economically important species that have been examined so far.