Has habitat heterogeneity promoted phenotypic and ecological sub‐structuring among a Coregonus lavaretus population in a large Scottish lake?

Differences in stable‐isotope values, morphology and ecology in whitefish Coregonus lavaretus were investigated between the three basins of Loch Lomond. The results are discussed with reference to a genetic investigation to elucidate any substructuring or spawning site fidelity. Foraging fidelity between basins of Loch Lomond was indicated by δ¹³C and δ¹⁵N values of C. lavaretus muscle tissue. There was, however, no evidence of the existence of sympatric morphs in the C. lavaretus population. A previous report of two C. lavaretus‘species’ in Loch Lomond probably reflects natural variation between individuals within a single mixed population.     

Soft sensor based on 2D‐fluorescence and process data enabling real‐time estimation of biomass in Escherichia coli cultivations

In bioprocesses, specific process responses such as the biomass cannot typically be measured directly on‐line, since analytical sampling is associated with unavoidable time delays. Accessing those responses in real‐time is essential for Quality by Design and process analytical technology concepts. Soft sensors overcome these limitations by indirectly measuring the variables of interest using a previously derived model and actual process data in real time. In this study, a biomass soft sensor based on 2D‐fluorescence data and process data, was developed for a comprehensive study with a 20‐L experimental design, for Escherichia coli fed‐batch cultivations. A multivariate adaptive regression splines algorithm was applied to 2D‐fluorescence spectra and process data, to estimate the biomass concentration at any time during the process. Prediction errors of 4.9% (0.99 g/L) for validation and 3.8% (0.69 g/L) for new data (external validation), were obtained. Using principal component and parallel factor analyses on the 2D‐fluorescence data, two potential chemical compounds were identified and directly linked to cell metabolism. The same wavelength pairs were also important predictors for the regression‐model performance. Overall, the proposed soft sensor is a valuable tool for monitoring the process performance on‐line, enabling Quality by Design.     

Geometric morphometric study of populations of the social wasp,Polistes dominulus (Christ, 1791) from Zanjan province,north‐west Iran

Abstract

We analysed morphological variation among 17 forewing characters within five populations of the paper wasp, Polistes dominulus, in Iran. The raw planar coordinate data were aligned using geometric and mathematical calculations in Kendall's shape space. After transfer of the data to a linear Euclidean space, i.e., tangent space, multi‐variate analysis of 135 images of forewings were made using their geometric morphometric characters (30 in the forewings). We observed a direct correlation between morphological characters and the geographically easiest travel distance along river valleys and mountain ranges.     

Modeling spatial trajectories in dynamics testing using basis splines: application to tracking human volunteers in low-speed frontal impacts

Designing motor vehicle safety systems requires knowledge of whole body kinematics during dynamic loading for occupants of varying size and age, often obtained from sled tests with postmortem human subjects and human volunteers. Recently, we reported pediatric and adult responses in low-speed (<4 g) automotive-like impacts, noting reductions in maximum excursion with increasing age. Since the time-based trajectory shape is also relevant for restraint design, this study quantified the time-series trajectories using basis splines and developed a statistical model for predicting trajectories as a function of body dimension or age. Previously collected trajectories of the head, spine, and pelvis were modeled using cubic basis splines with eight control points. A principal component analysis was conducted on the control points and related to erect seated height using a linear regression model. The resulting statistical model quantified how trajectories became shorter and flatter with increasing body size, corresponding to the validation data-set. Trajectories were then predicted for erect seated heights corresponding to pediatric and adult anthropomorphic test devices (ATDs), thus generating performance criteria for the ATDs based on human response. This statistical model can be used to predict trajectories for a subject of specified anthropometry and utilized in subject-specific computational models of occupant response.     

Variation in the post‐mating fitness landscape in fruit flies

Sperm competition is pervasive and fundamental to determining a male's overall fitness. Sperm traits and seminal fluid proteins (Sfps) are key factors. However, studies of sperm competition may often exclude females that fail to remate during a defined period. Hence, the resulting data sets contain fewer data from the potentially fittest males that have most success in preventing female remating. It is also important to consider a male's reproductive success before entering sperm competition, which is a major contributor to fitness. The exclusion of these data can both hinder our understanding of the complete fitness landscapes of competing males and lessen our ability to assess the contribution of different determinants of reproductive success to male fitness. We addressed this here, using the Drosophila melanogaster model system, by (i) capturing a comprehensive range of intermating intervals that define the fitness of interacting wild‐type males and (ii) analysing outcomes of sperm competition using selection analyses. We conducted additional tests using males lacking the sex peptide (SP) ejaculate component vs. genetically matched (SP⁺) controls. This allowed us to assess the comprehensive fitness effects of this important Sfp on sperm competition. The results showed a signature of positive, linear selection in wild‐type and SP⁺ control males on the length of the intermating interval and on male sperm competition defence. However, the fitness surface for males lacking SP was distinct, with local fitness peaks depending on contrasting combinations of remating intervals and offspring numbers. The results suggest that there are alternative routes to success in sperm competition and provide an explanation for the maintenance of variation in sperm competition traits.     

Drought-driven growth reduction in old beech (Fagus sylvatica L.) forests of the central Apennines, Italy

Productivity of old‐growth beech forests in the Mediterranean Basin was measured by average stem basal area increment (BAI) of dominant trees at two mountain sites in the Italian Apennines. Both forests could be ascribed to the old‐growth stage, but they differed markedly with regard to elevation (1000 vs. 1725 m a.s.l.), soil parent material (volcanic vs. calcareous), mean tree age (less than 200 years vs. 300 years), and stand structure (secondary old‐growth vs. primary old‐growth forest). Drought at the two sites was quantified by the self‐calibrated Palmer Moisture Anomaly Index (Z‐index), and by the self‐calibrating Palmer Drought Severity Index (PDSI) for summer (June through August) and the growing season (May through September). Dendroclimatological analyses revealed a moisture limitation of beech BAI at interannual (water availability measured by Z‐index) and decadal scales (water availability measured by PDSI). Both BAI and water availability increased from 1950 to 1970, and decreased afterwards. Trees were grouped according to their BAI trends in auxological groups (growth‐type chronologies), which confirmed that growth of most trees at both sites declined in recent decades, in agreement with increased drought. Because BAI is not expected to decrease without an external forcing, the patterns we uncovered suggest that long‐term drought stress has reduced the productivity of beech forests in the central Apennines, in agreement with similar trends identified in other Mediterranean mountains, but opposite to growth trends reported for many forests in central Europe.     

Predicting tree death for Fagus sylvatica and Abies alba using permanent plot data

Question: How well can mortality probabilities of deciduous trees(Fagus sylvatica) and conifers (Abies alba) be predicted using permanent plot data that describe growth patterns, tree species, tree size and site conditions? Location: Fagus forests in the montane belt of the Jura folds (Switzerland). Method: Permanent plot data were used to develop and validate logistic regression models predicting survival probabilities of individual trees. Backward model selection led to a reduced model containing the growth‐related variable ‘relative basal area increment’ (growth‐dependent mortality) and variables not directly reflecting growth such as species, size and site (growth‐independent mortality). Results: The growth‐mortality relationship was the same for both species (growth‐dependent mortality). However, species, site and tree size also influenced mortality probabilities (growth‐independent mortality). The predicted survival probabilities of the final model were well calibrated, and the model showed an excellent discriminatory power (area under the receiver operating characteristic curve = 0.896). Conclusion: Mortality probabilities of Fagus sylvatica and Abies alba can be predicted with high discriminatory power using a well calibrated logistic regression model. Extending this case study to a larger number of tree species and sites could provide species‐ and site‐specific tree mortality models that allow for more realistic projections of forest succession.     

Identifying latent clusters of variability in longitudinal data

Means or other central tendency measures are by far the most common focus of statistical analyses. However, as Carroll (2003) noted, "systematic dependence of variability on known factors" may be "fundamental to the proper solution of scientific problems" in certain settings. We develop a latent cluster model that relates underlying "clusters" of variability to baseline or outcome measures of interest. Because estimation of variability is inextricably linked to estimation of trend, assumptions about underlying trends are minimized by using nonparametric regression estimates. The resulting residual errors are then clustered into unobserved clusters of variability that are in turn related to subject-level predictors of interest. An application is made to psychological affect data.