Case studies and mathematical models of ecological speciation. 1. Cichlids in a crater lake.

A recent study of a pair of sympatric species of cichlids in Lake Apoyo in Nicaragua is viewed as providing probably one of the most convincing examples of sympatric speciation to date. Here, we describe and study a stochastic, individual-based, explicit genetic model tailored for this cichlid system. Our results show that relatively rapid (<20,000 generations) colonization of a new ecological niche and (sympatric or parapatric) speciation via local adaptation and divergence in habitat and mating preferences are theoretically plausible if: (i) the number of loci underlying the traits controlling local adaptation, and habitat and mating preferences is small; (ii) the strength of selection for local adaptation is intermediate; (iii) the carrying capacity of the population is intermediate; and (iv) the effects of the loci influencing nonrandom mating are strong. We discuss patterns and timescales of ecological speciation identified by our model, and we highlight important parameters and features that need to be studied empirically to provide information that can be used to improve the biological realism and power of mathematical models of ecological speciation.

Local and global error models to improve uncertainty quantification

In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

PKS2: A link between phototropin signalling and auxin transport - a study on how plants sense and respond to light.

The blue light photoreceptors phototropins (phot1 and phot2 in Arabidopsis thaliana (L.)) carry out various light responses of great adaptive value that optimize plant growth. These processes include phototropism (the bending of an organ induced by unequal light distribution), chloroplast movements, stomatal opening, leaf flattening and solar tracking. The biochemical pathways controlling these important blue light responses are just starting to be elucidated. The PHYTOCHROME KINASE SUBSTRATE (PKS1-4) proteins - the subject of this research - have recently been identified as novel phototropism signalling components. PKS1 (the founding member of this family) interacts in a same complex in vivo with phot1 and the important phot1 signalling element NON-PHOTOTROPIC HYPOCOTYL 3 (NPH3). This suggested that the PKS may act as early components of phot signalling. This work further investigates the role of this protein family during phototropin signalling Genetic experiments clearly showed that the PKS do not control chloroplast movements or stomatal opening. However, PKS2 plays a critical role with NPH3 during leaf flattening and solar tracking. Epistasis data indicated that both proteins act in phot1 and phot2 pathways, which is consistent with their in vivo interaction with both phototropins. Because phototropism, leaf flattening and solar tracking are developmental processes regulated by the hormone auxin, the role of PKS2 and NPH3 during auxin homeostasis was also investigated. Interestingly, PKS2 loss-of-function restores leaf flattening in the auxin transporter mutant aux1. Moreover, PKS2 and NPH3 are found in a same complex with AUX1 in vivo. Taken together, these results suggest that PKS2 may act with NPH3 as a connecting point between phot signalling and auxin transport. Further experiments were performed to explore the molecular mode of action of PKS2 and NPH3 in this process. The significance of these results is discussed.

Combining food web and species distribution models for improved community projections

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradient is subject to the interplay of biotic interactions in complement to abiotic environmental filtering. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose to use food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant-herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve both species distribution and community forecasts. Most importantly, this combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may be recurrent. Our combined approach points a promising direction forward to model the spatial variation of entire species interaction networks. Our work has implications for studies of range shifting species and invasive species biology where it may be unknown how a given biota might interact with a potential invader or in future climate.

Repression and Protest Structural Models and Strategic Interactions

The recent wave of upheavals and revolts in Northern Africa and the Middle East goes back to an old question often raised by theories of collective action: does repression act as a negative or positive incentive for further mobilization? Through a review of the vast literature devoted to this question, this article aims to go beyond theoretical and methodological dead-ends. The article moves on to non-Western settings in order to better understand, via a macro-sociological and dynamic approach, the causal effects between mobilizations and repression. It pleads for a meso- and micro-level approach to this issue: an approach that puts analytical emphasis both on protest organizations and on individual activists' careers.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

SESAM - a new framework integrating macroecological and species distribution models for predicting spatio-temporal patterns of species assemblages

Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.

Native homing endonucleases can target conserved genes in humans and in animal models.

In recent years, both homing endonucleases (HEases) and zinc-finger nucleases (ZFNs) have been engineered and selected for the targeting of desired human loci for gene therapy. However, enzyme engineering is lengthy and expensive and the off-target effect of the manufactured endonucleases is difficult to predict. Moreover, enzymes selected to cleave a human DNA locus may not cleave the homologous locus in the genome of animal models because of sequence divergence, thus hampering attempts to assess the in vivo efficacy and safety of any engineered enzyme prior to its application in human trials. Here, we show that naturally occurring HEases can be found, that cleave desirable human targets. Some of these enzymes are also shown to cleave the homologous sequence in the genome of animal models. In addition, the distribution of off-target effects may be more predictable for native HEases. Based on our experimental observations, we present the HomeBase algorithm, database and web server that allow a high-throughput computational search and assignment of HEases for the targeting of specific loci in the human and other genomes. We validate experimentally the predicted target specificity of candidate fungal, bacterial and archaeal HEases using cell free, yeast and archaeal assays.

Subalpine-nival gradient of species richness for vascular plants, lichens and bryophytes in the Swiss Inner Alps

In the European GLORIA project, 12 summits (treeline to nival belt) were inventoried in three regions of Switzerland: two in the Swiss National Park Graubünden and one in Valais. Vascular plants were recorded in all three regions and bryophytes and lichens were recorded only in Valais. On each summit, vegetation and temperature data were sampled using sampling protocols for the GLORIA project (Global Observation Research Initiative in Alpine environment) on large summit sections and in clusters of four 1x1-m quadrats. We observed a general decrease of species richness for all three systematic groups with increasing elevation in the summit sections, but only for vascular plants in the quadrats. In Valais, there was higher species richness for vascular plants than for bryophytes and lichens on the lower summits, but as the decrease in species richness was less pronounced for cryptogams, the latter were more numerous than vascular plants on the highest summit. Vascular species showed a clear shift of the dominant life form with elevation, with chamaephytes replacing hemicryptophytes. Bryophytes and lichens showed a weak trend among the life forms at the summit section scale, but a stronger shift of the dominant forms was seen in the quadrats, with cushion replacing turf bryophytes and crustaceous replacing fruticose lichens. Altogether, these results sustain the temperature-physiographic hypothesis to explain the species richness decrease along the altitudinal gradient: the harsh climatic conditions of the alpine-nival belts act as a filter for species, but the diminishing diversity of microhabitats is also an important factor. Because cryptogams depend more on humidity than temperature and more on smaller microhabitats than vascular plants, the decrease of species richness is more gradual with elevation for bryophytes and lichens.

On the problematic of reserving and stochastic loss models

Abstract Traditionally, the common reserving methods used by the non-life actuaries are based on the assumption that future claims are going to behave in the same way as they did in the past. There are two main sources of variability in the processus of development of the claims: the variability of the speed with which the claims are settled and the variability between the severity of the claims from different accident years. High changes in these processes will generate distortions in the estimation of the claims reserves. The main objective of this thesis is to provide an indicator which firstly identifies and quantifies these two influences and secondly to determine which model is adequate for a specific situation. Two stochastic models were analysed and the predictive distributions of the future claims were obtained. The main advantage of the stochastic models is that they provide measures of variability of the reserves estimates. The first model (PDM) combines one conjugate family Dirichlet - Multinomial with the Poisson distribution. The second model (NBDM) improves the first one by combining two conjugate families Poisson -Gamma (for distribution of the ultimate amounts) and Dirichlet Multinomial (for distribution of the incremental claims payments). It was found that the second model allows to find the speed variability in the reporting process and development of the claims severity as function of two above mentioned distributions' parameters. These are the shape parameter of the Gamma distribution and the Dirichlet parameter. Depending on the relation between them we can decide on the adequacy of the claims reserve estimation method. The parameters have been estimated by the Methods of Moments and Maximum Likelihood. The results were tested using chosen simulation data and then using real data originating from the three lines of business: Property/Casualty, General Liability, and Accident Insurance. These data include different developments and specificities. The outcome of the thesis shows that when the Dirichlet parameter is greater than the shape parameter of the Gamma, resulting in a model with positive correlation between the past and future claims payments, suggests the Chain-Ladder method as appropriate for the claims reserve estimation. In terms of claims reserves, if the cumulated payments are high the positive correlation will imply high expectations for the future payments resulting in high claims reserves estimates. The negative correlation appears when the Dirichlet parameter is lower than the shape parameter of the Gamma, meaning low expected future payments for the same high observed cumulated payments. This corresponds to the situation when claims are reported rapidly and fewer claims remain expected subsequently. The extreme case appears in the situation when all claims are reported at the same time leading to expectations for the future payments of zero or equal to the aggregated amount of the ultimate paid claims. For this latter case, the Chain-Ladder is not recommended.