Predation and fragmentation portrayed in the statistical structure of prey time series

<p>Abstract</p> <p>Background</p> <p>Statistical autoregressive analyses of direct and delayed density dependence are widespread in ecological research. The models suggest that changes in ecological factors affecting density dependence, like predation and landscape heterogeneity are directly portrayed in the first and second order autoregressive parameters, and the models are therefore used to decipher complex biological patterns. However, independent tests of model predictions are complicated by the inherent variability of natural populations, where differences in landscape structure, climate or species composition prevent controlled repeated analyses. To circumvent this problem, we applied second-order autoregressive time series analyses to data generated by a realistic agent-based computer model. The model simulated life history decisions of individual field voles under controlled variations in predator pressure and landscape fragmentation. Analyses were made on three levels: comparisons between predated and non-predated populations, between populations exposed to different types of predators and between populations experiencing different degrees of habitat fragmentation.</p> <p>Results</p> <p>The results are unambiguous: Changes in landscape fragmentation and the numerical response of predators are clearly portrayed in the statistical time series structure as predicted by the autoregressive model. Populations without predators displayed significantly stronger negative direct density dependence than did those exposed to predators, where direct density dependence was only moderately negative. The effects of predation versus no predation had an even stronger effect on the delayed density dependence of the simulated prey populations. In non-predated prey populations, the coefficients of delayed density dependence were distinctly positive, whereas they were negative in predated populations. Similarly, increasing the degree of fragmentation of optimal habitat available to the prey was accompanied with a shift in the delayed density dependence, from strongly negative to gradually becoming less negative.</p> <p>Conclusion</p> <p>We conclude that statistical second-order autoregressive time series analyses are capable of deciphering interactions within and across trophic levels and their effect on direct and delayed density dependence.</p

Bayesian uncertainty analysis for complex systems biology models: emulation, global parameter searches and evaluation of gene functions

Many mathematical models have now been employed across every area of systems biology. These models increasingly involve large numbers of unknown parameters, have complex structure which can result in substantial evaluation time relative to the needs of the analysis, and need to be compared to observed data of various forms. The correct analysis of such models usually requires a global parameter search, over a high dimensional parameter space, that incorporates and respects the most important sources of uncertainty. This can be an extremely difficult task, but it is essential for any meaningful inference or prediction to be made about any biological system. It hence represents a fundamental challenge for the whole of systems biology

Inhibiting the Thermal Gelation of Copolymer Stabilized Nonaqueous Dispersions and the Synthesis of Full Color PMMA Particles

Polymeric particle dispersions have numerous potential applications; currently one of the most relevant is their use as inks in electrophoretic displays. These colloidal particles are synthesized from the appropriate monomer using nonaqueous dispersion (NAD) polymerization in a nonpolar solvent, which requires a stabilizer to control particle size and morphology. We have previously reported the facile synthesis of poly(methyl methacrylate)-block-poly(octadecyl acrylate) (PMMA-b-PODA) by atom transfer radical polymerization (ATRP), and its use in the NAD polymerization of MMA in hexane/dodecane solvent mixtures. Here we report the synthesis of monodisperse PMMA particles in dodecane following a standard “industrial” procedure using these PMMA-b-PODA stabilizers. However, it was observed that the particle suspensions solidified when they were left at temperatures below ?18 °C yet redispersed upon being heated. Differential scanning calorimetry, dynamic light scattering, and rheological studies demonstrated that this thermoresponsive behavior was due to a liquid–gel transition occurring at 17.5 °C as a consequence of the upper critical solution temperature of PODA in dodecane being traversed. Consequently, new copolymers were synthesized by ATRP with an ethylhexyl acrylate (EHA) co-monomer incorporated into the lyophilic (dodecane compatible) block. Dispersions stabilized by these PMMA-b-P(ODA-co-EHA) polymers with high EHA contents exhibited lower gelation temperatures because of the greater solvent compatibility with dodecane. The use of a PMMA65-b-(ODA10-co-EHA45) copolymer stabilizer (with the highest EHA content) gave PMMA dispersions that showed no gelation down to 4 °C and monodisperse cross-linked PMMA particles containing organic dyes (cyan, magenta, red, and black) giving colored particles across the size range of approximately 100–1300 nm

Pre-operative serum vascular endothelial growth factor can select patients for adjuvant treatment after curative resection in colorectal cancer

We aim to determine the clinical usefulness of pre-operative serum vascular endothelial growth factor (VEGF) as a predictor of outcome in patients undergoing curative resection for colorectal cancer. Serum VEGF was assayed by quantitative ELISA in 81 patients prior to curative resection for node-negative (n = 53) and node-positive (n = 28) disease. Median follow-up for patients without cancer death was 27 months (range 21–37). Pre-operative serum VEGF was significantly higher in patients who went on to develop metastases than those who did not (median, 713 pg ml–1 vs. 314 pg ml–1, P < 0.0001). Using multivariate Cox regression analysis, pre-operative serum VEGF was the most important prognostic factor independent of nodal status and adjuvant chemotherapy, and was superior to nodal status in predicting outcome (P < 0.00001). At 575 pg ml–1, pre-operative serum VEGF was 64% sensitive and 89% specific in predicting the development of metastases in curative resections, with a positive predictive value of 73% and a negative predictive value of 85%. Pre-operative serum VEGF is a powerful predictor of outcome following curative surgery for colorectal cancer. These data support the measurement of pre-operative serum VEGF as a method for selecting patients who require adjuvant therapy. © 2000 Cancer Research Campaign http://www.bjcancer.co

New and extended parameterization of the thermodynamic model AIOMFAC: calculation of activity coefficients for organic-inorganic mixtures containing carboxyl, hydroxyl, carbonyl, ether, ester, alkenyl, alkyl, and aromatic functional groups

We present a new and considerably extended parameterization of the thermodynamic activity coefficient model AIOMFAC (Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients) at room temperature. AIOMFAC combines a Pitzer-like electrolyte solution model with a UNIFAC-based group-contribution approach and explicitly accounts for interactions between organic functional groups and inorganic ions. Such interactions constitute the salt-effect, may cause liquid-liquid phase separation, and affect the gas-particle partitioning of aerosols. The previous AIOMFAC version was parameterized for alkyl and hydroxyl functional groups of alcohols and polyols. With the goal to describe a wide variety of organic compounds found in atmospheric aerosols, we extend here the parameterization of AIOMFAC to include the functional groups carboxyl, hydroxyl, ketone, aldehyde, ether, ester, alkenyl, alkyl, aromatic carbon-alcohol, and aromatic hydrocarbon. Thermodynamic equilibrium data of organic-inorganic systems from the literature are critically assessed and complemented with new measurements to establish a comprehensive database. The database is used to determine simultaneously the AIOMFAC parameters describing interactions of organic functional groups with the ions H^+, Li^+, Na^+, K^+, NH_(4)^+, Mg^(2+), Ca^(2+), Cl^−, Br^−, NO_(3)^−, HSO_(4)^−, and SO_(4)^(2−). Detailed descriptions of different types of thermodynamic data, such as vapor-liquid, solid-liquid, and liquid-liquid equilibria, and their use for the model parameterization are provided. Issues regarding deficiencies of the database, types and uncertainties of experimental data, and limitations of the model, are discussed. The challenging parameter optimization problem is solved with a novel combination of powerful global minimization algorithms. A number of exemplary calculations for systems containing atmospherically relevant aerosol components are shown. Amongst others, we discuss aqueous mixtures of ammonium sulfate with dicarboxylic acids and with levoglucosan. Overall, the new parameterization of AIOMFAC agrees well with a large number of experimental datasets. However, due to various reasons, for certain mixtures important deviations can occur. The new parameterization makes AIOMFAC a versatile thermodynamic tool. It enables the calculation of activity coefficients of thousands of different organic compounds in organic-inorganic mixtures of numerous components. Models based on AIOMFAC can be used to compute deliquescence relative humidities, liquid-liquid phase separations, and gas-particle partitioning of multicomponent mixtures of relevance for atmospheric chemistry or in other scientific fields

Controlling magnetic order and quantum disorder in molecule-based magnets.

We investigate the structural and magnetic properties of two molecule-based magnets synthesized from the same starting components. Their different structural motifs promote contrasting exchange pathways and consequently lead to markedly different magnetic ground states. Through examination of their structural and magnetic properties we show that [Cu(pyz)(H 2 O)(gly) 2 ](ClO 4 ) 2 may be considered a quasi-one-dimensional quantum Heisenberg antiferromagnet whereas the related compound [Cu(pyz)(gly)](ClO 4 ) , which is formed from dimers of antiferromagnetically interacting Cu 2+ spins, remains disordered down to at least 0.03 K in zero field but shows a field-temperature phase diagram reminiscent of that seen in materials showing a Bose-Einstein condensation of magnons

How predation and landscape fragmentation affect vole population dynamics

Background: Microtine species in Fennoscandia display a distinct north-south gradient from regular cycles to stable populations. The gradient has often been attributed to changes in the interactions between microtines and their predators. Although the spatial structure of the environment is known to influence predator-prey dynamics of a wide range of species, it has scarcely been considered in relation to the Fennoscandian gradient. Furthermore, the length of microtine breeding season also displays a north-south gradient. However, little consideration has been given to its role in shaping or generating population cycles. Because these factors covary along the gradient it is difficult to distinguish their effects experimentally in the field. The distinction is here attempted using realistic agent-based modelling. Methodology/Principal Findings: By using a spatially explicit computer simulation model based on behavioural and ecological data from the field vole (Microtus agrestis), we generated a number of repeated time series of vole densities whose mean population size and amplitude were measured. Subsequently, these time series were subjected to statistical autoregressive modelling, to investigate the effects on vole population dynamics of making predators more specialised, of altering the breeding season, and increasing the level of habitat fragmentation. We found that fragmentation as well as the presence of specialist predators are necessary for the occurrence of population cycles. Habitat fragmentation and predator assembly jointly determined cycle length and amplitude. Length of vole breeding season had little impact on the oscillations. Significance: There is good agreement between our results and the experimental work from Fennoscandia, but our results allow distinction of causation that is hard to unravel in field experiments. We hope our results will help understand the reasons for cycle gradients observed in other areas. Our results clearly demonstrate the importance of landscape fragmentation for population cycling and we recommend that the degree of fragmentation be more fully considered in future analyses of vole dynamics