Morphology as a key to behavioural flexibility: body shape and swimming variability in the dimorphic crucian carp

Swimming trajectories of length-matched deep-bodied and shallow-bodied crucian carp were quantified in the laboratory using motion analysis software and compared in terms of swimming velocity, turning behaviour and associated coefficients of variation. The mean velocities of the two morphs were similar, but slower than predicted, and there was no difference in turning behaviour. In line with predictions from analysis of power curve steepness, swimming velocities of deep-bodied, high-drag individuals were significantly less variable than shallow-bodied conspecifics, thus indicating an association between body shape behavioural flexibility in terms of swimming variability

Butterfly monitoring using systematically placed transects in contrasting climatic regions - exploring an established spatial design for sampling

Butterfly monitoring schemes are recording programs initiated to monitor nationwide butterfly abundance and distribution patterns, often with help from volunteers. The method generates high-resolution data, but may be associated with a degree of habitat sampling bias if volunteers prefer to survey areas perceived to be high-quality butterfly habitats. This can result in habitats becoming underrepresented in the data set, leading to less information about the butterfly populations there. In the present study, we investigate the possibility of applying a spatial design used by the Swedish Bird Survey for nationwide, grid-based sampling, with a goal to get butterfly monitoring data covering a representative sample of different habitats. We surveyed four 2x2 km sampling squares, split into 100 m segments, in the southernmost region of Sweden (Scania) and four in the northernmost region (Norrbotten). The grid-based transects were compared with volunteer-selected transects in a GIS analysis using a refined Swedish version of CORINE land cover data to see how well these two transect designs represent true habitat coverage. A total of 53 km transect was monitored, resulting in 490 individuals and 29 different species recorded. We found that transect cover correlated significantly with overall land cover using both monitoring methods, though standardised transects outperformed volunteer-selected transects in habitat representation in Scania, but not in Norrbotten. Butterflies were found to aggregate significantly in specific habitats, but with contrasting results for the two geographically different regions. Grasslands in both regions generated a high number of recorded butterflies, although so did clear-cut and residential areas in Norrbotten as well. The highest number of individuals recorded per transect was found in bogs in Scania. This study emphasises the value of complementing free site selection monitoring schemes with spatially representative schemes such as the Swedish Bird Survey, and sheds some light on general habitat preferences for Swedish butterflies in two contrasting climatic regions

Structural Kinetic Modeling of Metabolic Networks

To develop and investigate detailed mathematical models of cellular metabolic processes is one of the primary challenges in systems biology. However, despite considerable advance in the topological analysis of metabolic networks, explicit kinetic modeling based on differential equations is still often severely hampered by inadequate knowledge of the enzyme-kinetic rate laws and their associated parameter values. Here we propose a method that aims to give a detailed and quantitative account of the dynamical capabilities of metabolic systems, without requiring any explicit information about the particular functional form of the rate equations. Our approach is based on constructing a local linear model at each point in parameter space, such that each element of the model is either directly experimentally accessible, or amenable to a straightforward biochemical interpretation. This ensemble of local linear models, encompassing all possible explicit kinetic models, then allows for a systematic statistical exploration of the comprehensive parameter space. The method is applied to two paradigmatic examples: The glycolytic pathway of yeast and a realistic-scale representation of the photosynthetic Calvin cycle.Comment: 14 pages, 8 figures (color

Arbitrary Steady-State Solutions with the K-epsilon Model

Widely-used forms of the K-epsilon turbulence model are shown to yield arbitrary steady-state converged solutions that are highly dependent on numerical considerations such as initial conditions and solution procedure. These solutions contain pseudo-laminar regions of varying size. By applying a nullcline analysis to the equation set, it is possible to clearly demonstrate the reasons for the anomalous behavior. In summary, the degenerate solution acts as a stable fixed point under certain conditions, causing the numerical method to converge there. The analysis also suggests a methodology for preventing the anomalous behavior in steady-state computations

Integral representation of the linear Boltzmann operator for granular gas dynamics with applications

We investigate the properties of the collision operator associated to the linear Boltzmann equation for dissipative hard-spheres arising in granular gas dynamics. We establish that, as in the case of non-dissipative interactions, the gain collision operator is an integral operator whose kernel is made explicit. One deduces from this result a complete picture of the spectrum of the collision operator in an Hilbert space setting, generalizing results from T. Carleman to granular gases. In the same way, we obtain from this integral representation of the gain operator that the semigroup in L^1(\R \times \R,\d \x \otimes \d\v) associated to the linear Boltzmann equation for dissipative hard spheres is honest generalizing known results from the first author.Comment: 19 pages, to appear in Journal of Statistical Physic

Evaluating range-expansion models for calculating nonnative species' expansion rate

Species range shifts associated with environmental change or biological invasions are increasingly important study areas. However, quantifying range expansion rates may be heavily influenced by methodology and/or sampling bias. We compared expansion rate estimates of Roesel's bush-cricket (Metrioptera roeselii, Hagenbach 1822), a nonnative species currently expanding its range in south-central Sweden, from range statistic models based on distance measures (mean, median, 95th gamma quantile, marginal mean, maximum, and conditional maximum) and an area-based method (grid occupancy). We used sampling simulations to determine the sensitivity of the different methods to incomplete sampling across the species' range. For periods when we had comprehensive survey data, range expansion estimates clustered into two groups: (1) those calculated from range margin statistics (gamma, marginal mean, maximum, and conditional maximum: similar to 3 km/year), and (2) those calculated from the central tendency (mean and median) and the area-based method of grid occupancy (similar to 1.5 km/year). Range statistic measures differed greatly in their sensitivity to sampling effort; the proportion of sampling required to achieve an estimate within 10% of the true value ranged from 0.17 to 0.9. Grid occupancy and median were most sensitive to sampling effort, and the maximum and gamma quantile the least. If periods with incomplete sampling were included in the range expansion calculations, this generally lowered the estimates (range 16-72%), with exception of the gamma quantile that was slightly higher (6%). Care should be taken when interpreting rate expansion estimates from data sampled from only a fraction of the full distribution. Methods based on the central tendency will give rates approximately half that of methods based on the range margin. The gamma quantile method appears to be the most robust to incomplete sampling bias and should be considered as the method of choice when sampling the entire distribution is not possible

Measurement of the Slope Parameter for the eta->3pi0 Decay in the pp->pp eta Reaction

The CELSIUS/WASA setup is used to measure the 3pi0 decay of eta mesons produced in pp interactions with beam kinetic energies of 1.36 and 1.45 GeV. The efficiency-corrected Dalitz plot and density distributions for this decay are shown, together with a fit of the quadratic slope parameter alpha yielding alpha = -0.026 +/- 0.010(stat) +/- 0.010(syst). This value is compared to recent experimental results and theoretical predictions.Comment: 4 pages, 7 Postscript figures, uses revtex4.st

Potassium, chlorine, and sulfur in ash, particles, deposits, and corrosion during wood combustion in a circulating fluidized-bed boiler

The effect of the addition of chlorine and/or sulfur to the fuel on fly ash composition, deposit formation, and superheater corrosion has been studied during biomass combustion in a circulating fluidized-bed boiler. The chlorine (HCl (aq)) and sulfur (SO2 (g)) were added in proportions of relevance for the potassium chemistry. The composition of the bottom and the fly ashes was analyzed. Gas and particle measurements were performed downstream of the cyclone before the convection pass and the flue gas composition was recorded in the stack with a series of standard instruments and an FTIR analyzer. At the position downstream of the cyclone, a deposit probe was situated, simulating a superheater tube. Deposits on the probe and initial corrosion were examined. It is concluded that addition of sulfur and chlorine increases the formation of submicron particles leading to deposition of potassium sulfate and chloride. The results compare well with earlier work based on laboratory-scale experiments concerning effects of chlorine and sulfur on potassium chemistry

Uncertainty quantification for kinetic models in socio-economic and life sciences

Kinetic equations play a major rule in modeling large systems of interacting particles. Recently the legacy of classical kinetic theory found novel applications in socio-economic and life sciences, where processes characterized by large groups of agents exhibit spontaneous emergence of social structures. Well-known examples are the formation of clusters in opinion dynamics, the appearance of inequalities in wealth distributions, flocking and milling behaviors in swarming models, synchronization phenomena in biological systems and lane formation in pedestrian traffic. The construction of kinetic models describing the above processes, however, has to face the difficulty of the lack of fundamental principles since physical forces are replaced by empirical social forces. These empirical forces are typically constructed with the aim to reproduce qualitatively the observed system behaviors, like the emergence of social structures, and are at best known in terms of statistical information of the modeling parameters. For this reason the presence of random inputs characterizing the parameters uncertainty should be considered as an essential feature in the modeling process. In this survey we introduce several examples of such kinetic models, that are mathematically described by nonlinear Vlasov and Fokker--Planck equations, and present different numerical approaches for uncertainty quantification which preserve the main features of the kinetic solution.Comment: To appear in "Uncertainty Quantification for Hyperbolic and Kinetic Equations