Synanthropic plant communities: models of organization and features of classification

It is proposed to distinguish between three models of organization in synanthropic plant communities formed under the influence of man: R-modle, communities of segetal weeds in fields of annual crops and at initial stages of restoration successions; R --> CRS-model, serial communities of the later stages of restoration successions; CRS --> S-model, serial communities of allogenic successions under the influence of grazing and other external factors. The higher units of the ecological and faunistic classification (classes and orders) well represent the succession status and the soil and climate conditions under which synanthropic communities are formed. At the same time, the continual character of synanthropic vegetation makes recognition of plant associations inexpedient in some cases. It is preferable to use the deductive classification method of K. Kope?ky and S. Hejny.     

Holoprosencephaly: new models, new insights

Holoprosencephaly (HPE) is a common congenital malformation that is characterised by a failure to divide the forebrain into left and right hemispheres and is usually accompanied by defects in patterning of the midline of the face. HPE exists in inherited, autosomal dominant (familial) forms and mutation-associated sporadic forms, but environmental factors are also implicated. There are several features of HPE that are not well understood, including the extremely variable clinical presentation, even among obligate carriers of familial mutations, and the restriction of structural anomalies to the ventral anterior midline, despite association with defects in signal transduction pathways that regulate development of many additional body structures. The new animal models described in this review may help unravel these puzzles. Furthermore, these model systems suggest that human HPE arises from a complex interaction between the timing and strength of developmental signalling pathways, genetic variation and exposure to environmental agents.     

Spatiotemporal dynamic models of plant populations and communities

The idea of relating spatial patterns and temporal processes in plant community dynamics is not new, but its transformation into realistic spatiotemporal models is the result of quite recent methodological developments. There are now two classes of analytical model and a broad class of simulation models pertaining to the role of spatial structure in vegetation dynamics. They indicate that any community-dynamical theory intended to be predictive should not omit the spatial aspects of plant population dynamics, because these may radically change the conditions of persistence and coexistence.     

Building clone-consistent ecosystem models

Many ecological studies employ general models that can feature an arbitrary number of populations. A critical requirement imposed on such models is clone consistency: If the individuals from two populations are indistinguishable, joining these populations into one shall not affect the outcome of the model. Otherwise a model produces different outcomes for the same scenario. Using functional analysis, we comprehensively characterize all clone-consistent models: We prove that they are necessarily composed from basic building blocks, namely linear combinations of parameters and abundances. These strong constraints enable a straightforward validation of model consistency. Although clone consistency can always be achieved with sufficient assumptions, we argue that it is important to explicitly name and consider the assumptions made: They may not be justified or limit the applicability of models and the generality of the results obtained with them. Moreover, our insights facilitate building new clone-consistent models, which we illustrate for a data-driven model of microbial communities. Finally, our insights point to new relevant forms of general models for theoretical ecology. Our framework thus provides a systematic way of comprehending ecological models, which can guide a wide range of studies.     

Building better wildlife-habitat models

Wildlife-habitat models are an important tool in wildlife management today, and by far the majority of these predict aspects of species distribution (abundance or presence) as a proxy measure of habitat quality. Unfortunately, few are tested on independent data., and of those that are, few show useful predictive skill. We demonstrate that six critical assumptions underlie distribution based wildlife-habitat models, all of which must be valid for the model to predict habitat quality. We outline these assumptions in a meta-model, and discuss methods for their validation. Even where all six assumptions show a high level of validity, there is still a strong likelihood that the model will not predict habitat quality. However, the meta-model does suggest habitat quality can be predicted more accurately if distributional data are ignored, and variables more indicative of habitat quality are modelled instead.     

Species abundance models and patterns in dragonfly communities: effects of fish predators

We investigated if dragonfly larvae community composition and species abundance curves are sensitive to variation in predation intensity, and whether the fit to a particular niche partitioning model could be used to make inferences about mechanisms structuring communities. The approach taken was to compare communities in lakes either having or lacking fish predation. Dragonfly species classified as active, strongly dominated the dragonfly communities in fishless lakes, and low active species dominated fishless lakes. As activity level is known to correlate with susceptibility to fish predation this indicates that these communities are structured by fish predation. Fitting relative abundance data to five niche partitioning models showed that the same model fitted data from both types of habitats (fish/no fish). This means that the observed differences in relative abundances were substitutive, i.e. the relative abundance of a rank stayed constant, even though the identity of the species having this rank changed. The best fit to data from both types of lakes was found for the random assortment model, which is usually interpreted as an indication that the community is not structured by within-guild interactions. This interpretation for fishless lakes did not seem to agree with other community measures (i.e. lowered diversity and evenness and no relationship between species richness and dragonfly biomass), which indicate that the community is structured by within-guild interactions. Moreover, a detail in the fitting procedure, the number of species included in the analysis, affected which model that fitted data best. Thus, we question if fitting niche partitioning models to data can provide mechanistic understanding of how resources are partitioned in natural communities.     

Alcohol and genetics: new animal models.

In recent years, it has become increasingly evident that there is a genetic component to alcoholism. Attempts to isolate alcoholism genes have met with modest success, in part because alcoholism is a multigenic trait. Recently, experimental animal models and novel genetic manipulations have provided several clues as to the specific genes involved in alcoholism, and extensive research has identified many genes that might influence responses to alcohol. Although not all of these might be proven to influence drug sensitivity, research has provided evidence for the involvement of a few genes. Ultimately, findings from animal models that investigate the function of specific genes could aid the development of pharmacotherapies to treat alcohol dependence.     

Building structural models of peptides: a semi-automatic software

We present a software package that allows the construction anddisplay of structural models of proteins starting from the aminoacid sequence written in the one-letter code of standard databank format. The software includes a very fast and efficientalgorithm aimed at finding the global energy minimum of thepotential function describing the molecular interactions. Thewhole package is conceived to have maximum flexibility. Completelyautomatic procedures are envisaged for standard problems. Fornon-standard problems, the construction procedure can be interactivelyadopted to meet with different options. Received on February 19, 1990; accepted on August 31, 1990     

Building population models for large-scale neural recordings: Opportunities and pitfalls

Modern recording technologies now enable simultaneous recording from large numbers of neurons. This has driven the development of new statistical models for analyzing and interpreting neural population activity. Here, we provide a broad overview of recent developments in this area. We compare and contrast different approaches, highlight strengths and limitations, and discuss biological and mechanistic insights that these methods provide.     

Fuzzy species distribution models: a way to represent plant communities spatially

Fuzzy set theory has generally been applied to smooth classification cut‐offs, with an unavoidable loss of information. In this commentary, I rely on both advantages and disadvantages of the methods proposed in Duff et al., in this issue of the Journal of Vegetation Science, to map the variability over space of vegetation classes based on fuzzy sets and species distribution models.     

Opinion: Building epithelial architecture: insights from three-dimensional culture models

How do individual cells organize into multicellular tissues? Here, we propose that the morphogenetic behaviour of epithelial cells is guided by two distinct elements: an intrinsic differentiation programme that drives formation of a lumen-enclosing monolayer, and a growth factor-induced, transient de-differentiation that allows this monolayer to be remodelled.     

Power law rank-abundance models for marine phage communities

Metagenomic analyses suggest that the rank-abundance curve for marine phage communities follows a power law distribution. A new type of power law dependence based on a simple model in which a modified version of Lotka-Volterra predator-prey dynamics is sampled uniformly in time is presented. Biologically, the model embodies a kill the winner hypothesis and a neutral evolution hypothesis. The model can match observed power law distributions and uses very few parameters that are readily identifiable and characterize phage ecosystems. The model makes new untested predictions: (1) it is unlikely that the most abundant phage genotype will be the same at different time points and (2) the long-term decay of isolated phage populations follows a power law.     

UniFrac: a new phylogenetic method for comparing microbial communities

We introduce here a new method for computing differences between microbial communities based on phylogenetic information. This method, UniFrac, measures the phylogenetic distance between sets of taxa in a phylogenetic tree as the fraction of the branch length of the tree that leads to descendants from either one environment or the other, but not both. UniFrac can be used to determine whether communities are significantly different, to compare many communities simultaneously using clustering and ordination techniques, and to measure the relative contributions of different factors, such as chemistry and geography, to similarities between samples. We demonstrate the utility of UniFrac by applying it to published 16S rRNA gene libraries from cultured isolates and environmental clones of bacteria in marine sediment, water, and ice. Our results reveal that (i) cultured isolates from ice, water, and sediment resemble each other and environmental clone sequences from sea ice, but not environmental clone sequences from sediment and water; (ii) the geographical location does not correlate strongly with bacterial community differences in ice and sediment from the Arctic and Antarctic; and (iii) bacterial communities differ between terrestrially impacted seawater (whether polar or temperate) and warm oligotrophic seawater, whereas those in individual seawater samples are not more similar to each other than to those in sediment or ice samples. These results illustrate that UniFrac provides a new way of characterizing microbial communities, using the wealth of environmental rRNA sequences, and allows quantitative insight into the factors that underlie the distribution of lineages among environments.     

Building kinetic models for metabolic engineering

1. Download : Download high-res image (84KB)
2. Download : Download full-size image