Orthonormal transform to decompose the variance of a life-history trait across a phylogenetic tree

In recent years, there has been an increased interest in studying the variability of a quantitative life history trait across a set of species sharing a common phylogeny. However, such studies have su.ered from an insu.cient development of statistical methods aimed at decomposing the trait variance with respect to the topological structure of the tree. Here we propose, a new and generic approach that expresses the topological properties of the phylogenetic tree via an orthonormal basis, which is further used to decompose the trait variance. Such a decomposition provides a structure function, referred to as "orthogram," which is relevant to characterize in both graphical and statistical aspects the dependence of trait values on thetopology of the tree ("phylogenetic dependence"). We also propose four complementary test statistics to be computed from orthogram values that help to diagnose both the intensity and the nature of phylogenetic dependence. The relevance of the method is illustrated by the analysis of three phylogenetic data sets, drawn from the literature and typifying contrasted levels and aspects of phylogenetic dependence. Freely available routines which have been programmed in the R framework are also proposed

Stabilité d'une structure spatiale et compromis d'une analyse statistique multi-tableaux : application à la physico-chimie d'un lac réservoir

10 paramètres physico-chimiques sont mesurés en surface dans 10 stations à 12 dates sur le lac réservoir de la Sorme (Saône-et-Loire). L'article montre comment une analyse multitableaux peut caractériser la structure spatiale et préciser sa stabilité. Les notions d'interstructure et de compromis sont accessibles par une procédure simple et efficace.This paper is based on the observation that three-dimensional data matrices (sites x times x variables) often used in limnological investigations require statistical analyses fitted to experimental objectives. Many apparently different statistical tools (3-mode PCA of TUCKER, 1964; KROONENBERG, 1983; projection of variables WILLIAMS and STEPHENSON, 1973; DOLEDEC and CHESSEL, 1987) may be useful to clarify limnological problems such as : 1) the temporal variability of a pattern (elimination of spatial heterogenity) : 2) the spatial structure of a pattern (elimination of temporal effects, mapping of an average situation) : 3) the temporal variability of Lake stratification (stability, modification or inversion) : 4) the spatial structure of temporal variability, and 5) the between variables typology of a spatial and temporal structure. Our methodological approach allowed us to assess the temporal stability of the spatial structure of the Lake waters (question 3) using a multitable analysis known as triadic analysis (THIOULOUSE and CHESSEL, 1987).As part of the limnological study of a reservoir Lake (Sorme reservoir Lake, Saône-et-Loire, France) 10 commonly used physical and chemical variables were studied from July 1980 to October 1931. During this period, 12 water samples were taken near the surface at each of the 10 stations scattered along the Sorme Lake (see figure 1). Main morphometric features of the Sorme Lake are : 1) a surface area equal to 230 ha, 2) a 25 km long perimeter and 3) a volume of 9.5 106 m3 with a maximum depth of 13 meters upstream of the dam and an average depth of about 4 meters. Seasonal tidal range was only a few meters.Only 2 of the 3 concepts of triadic analysis stated by THIOULOUSE and CHESSEL, 1987 are developed here : 1) for each of the 12 tables (stations x variables) coming from the 12 sampling dates, data are first centered (elimination of mean) and standardized (division by standard deviation) (see figure 2). The resulting table Y called interstructure matrix, i.e. interstructure between each of the sampling dates matrix, is organized to have sampling dates as columns and the ten physical and chemical variables at each station successively as fines. Principal Component Analysis (PCA on the variance-covariance matrix) is then applied to the interstructure matrix. In our case it is a one-dimensional matrix, i.e. according to physical and chemical variables, there is only one spatial structure common to each sampling date (figure 3 and 2) compromise matrix are associated with the successive PCA factors of the interstructure (figure 4). According to the previous remark, only the first factor is considered. Data are reorganized to have physical and chemical variables as columns, and stations as fines. This last table defines a compromise matrix labelled Z. The mapping of the numerical values of matrix Z renders a ten-dimensional description of the permanent spatial structure (figure 5). To summarize the multivariate description, matrix Z is processed with a PCA on the variance-covariance matrix producing a three-dimensional compromise (figure 6).The interpretation of the compromise table by mapping the factorial scores of the PCA leads to a functional scheme of the reservoir Lake waters distinguishing five sectors (see figure 7) as a function of water depth, influence of tidal range, influence of tributaries and of the Sorme River. 3 stations are periodically isolated from the reservoir and produce 3 sectors with lower pH and temperature values and higher concentrations in ammonia and sulphate according to the influence of tributaries. The 4th sector is associated with the former submerged valley, i.e. main channel of the Sorme River prior to the dam closure, and demonstrated an ionic gradient concerning mainly nitrate and chloride-concentrations. The 5th sector, opposed to the latter, consists in the deeper area of the Sorme Lake which reveals rather homogeneous waters near the surface

Effectif et taux de masculinité des groupes de chats dans les familles humaines (région lyonnaise)

International audienc

Altered leaf elemental composition with climate change is linked to reductions in photosynthesis, growth and survival in a semi‐arid shrubland

1. Climate change will increase heat and drought stress in many dryland areas, which could reduce soil nutrient availability for plants and aggravate nutrient limitation of primary productivity. Any negative impacts of climate change on foliar nutrient contents would be expected to negatively affect the photosynthetic capacity, water use efficiency and overall fitness of dryland vegetation. 2. We conducted a 4‐year manipulative experiment using open top chambers and rainout shelters to assess the impacts of warming (~2°C, W), rainfall reduction (~30%, RR) and their combination (W + RR) on the nutrient status and ecophysiological performance of six native shrub species of contrasting phylogeny in a semi‐arid ecosystem. Leaf nutrient status and gas exchange were assessed yearly, whereas biomass production and survival were measured at the end of the study. 3. Warming (W and W + RR) advanced shoot growth phenology and reduced foliar macro‐ (N, P, K) and micronutrient (Cu, Fe, Zn) concentrations (by 8%–18% and 14%–56% respectively), net photosynthetic rate (32%), above‐ground biomass production (28%–39%) and survival (23%–46%). Decreased photosynthesis and growth in W and W + RR plants were primarily linked to enhanced nutritional constraints on carbon fixation. Poor leaf nutrient status in W and W + RR plants partly decoupled carbon assimilation from water flux and led to drastic reductions in water use efficiency (WUEi; ~41%) across species. The RR treatment moderately decreased foliar macro‐ and micronutrients (6%–17%, except for Zn) and biomass production (22%). The interactive impacts of warming and rainfall reduction (W + RR treatment) on plant performance were generally smaller than expected from additive single‐factor effects. 4. Synthesis. Large decreases in plant nutrient pool size and productivity combined with increased mortality during hotter droughts will reduce vegetation cover and nutrient retention capacity, thereby disrupting biogeochemical processes and accelerating dryland degradation with impending climate change. Increased macro‐ and micronutrient co‐limitation of photosynthesis with forecasted climate change conditions may offset any gains in WUEi and productivity derived from anthropogenic CO2 elevation, thereby increasing dryland vegetation vulnerability to drought stress in a warmer and drier climate. The generalized reduction in leaf nutrient contents with warming compromises plant nutritional quality for herbivores, with potential cascading negative effects across trophic levels.This study was supported by the Spanish Ministerio de Economía y Competitividad (projects CGL2010‐21064, CGL2013‐48753‐R and CGL2013‐44661‐R co‐funded by European Union FEDER funds), Fundación Séneca (19477/PI/14) and the European Research Council (ERC Grant agreements 242658 [BIOCOM] and 647038 [BIODESERT]). L.L.‐S. and I.P. acknowledge support from the JAE‐CSIC and Juan de la Cierva Programs (FPDI‐2013‐16221) respectively

Not that clean: Aquaculture-mediated translocation of cleaner fish has led to hybridization on the northern edge of the species' range

publishedVersionPaid Open AccessUNIT agreemen

Environmental variables, habitat discontinuity and life history shaping the genetic structure of Pomatoschistus marmoratus

Coastal lagoons are semi-isolated ecosystems exposed to wide fluctuations of environmental conditions and showing habitat fragmentation. These features may play an important role in separating species into different populations, even at small spatial scales. In this study, we evaluate the concordance between mitochondrial (previous published data) and nuclear data analyzing the genetic variability of Pomatoschistus marmoratus in five localities, inside and outside the Mar Menor coastal lagoon (SE Spain) using eight microsatellites. High genetic diversity and similar levels of allele richness were observed across all loci and localities, although significant genic and genotypic differentiation was found between populations inside and outside the lagoon. In contrast to the FST values obtained from previous mitochondrial DNA analyses (control region), the microsatellite data exhibited significant differentiation among samples inside the Mar Menor and between lagoonal and marine samples. This pattern was corroborated using Cavalli-Sforza genetic distances. The habitat fragmentation inside the coastal lagoon and among lagoon and marine localities could be acting as a barrier to gene flow and contributing to the observed genetic structure. Our results from generalized additive models point a significant link between extreme lagoonal environmental conditions (mainly maximum salinity) and P. marmoratus genetic composition. Thereby, these environmental features could be also acting on genetic structure of coastal lagoon populations of P. marmoratus favoring their genetic divergence. The mating strategy of P. marmoratus could be also influencing our results obtained from mitochondrial and nuclear DNA. Therefore, a special consideration must be done in the selection of the DNA markers depending on the reproductive strategy of the species

Analysis with respect to instrumental variables for the exploration of microarray data structures

BACKGROUND: Evaluating the importance of the different sources of variations is essential in microarray data experiments. Complex experimental designs generally include various factors structuring the data which should be taken into account. The objective of these experiments is the exploration of some given factors while controlling other factors. RESULTS: We present here a family of methods, the analyses with respect to instrumental variables, which can be easily applied to the particular case of microarray data. An illustrative example of analysis with instrumental variables is given in the case of microarray data investigating the effect of beverage intake on peripheral blood gene expression. This approach is compared to an ANOVA-based gene-by-gene statistical method. CONCLUSION: Instrumental variables analyses provide a simple way to control several sources of variation in a multivariate analysis of microarray data. Due to their flexibility, these methods can be associated with a large range of ordination techniques combined with one or several qualitative and/or quantitative descriptive variables

Should We Abandon the t-Test in the Analysis of Gene Expression Microarray Data: A Comparison of Variance Modeling Strategies

High-throughput post-genomic studies are now routinely and promisingly investigated in biological and biomedical research. The main statistical approach to select genes differentially expressed between two groups is to apply a t-test, which is subject of criticism in the literature. Numerous alternatives have been developed based on different and innovative variance modeling strategies. However, a critical issue is that selecting a different test usually leads to a different gene list. In this context and given the current tendency to apply the t-test, identifying the most efficient approach in practice remains crucial. To provide elements to answer, we conduct a comparison of eight tests representative of variance modeling strategies in gene expression data: Welch's t-test, ANOVA [1], Wilcoxon's test, SAM [2], RVM [3], limma [4], VarMixt [5] and SMVar [6]. Our comparison process relies on four steps (gene list analysis, simulations, spike-in data and re-sampling) to formulate comprehensive and robust conclusions about test performance, in terms of statistical power, false-positive rate, execution time and ease of use. Our results raise concerns about the ability of some methods to control the expected number of false positives at a desirable level. Besides, two tests (limma and VarMixt) show significant improvement compared to the t-test, in particular to deal with small sample sizes. In addition limma presents several practical advantages, so we advocate its application to analyze gene expression data