Analytical results concerning linkage disequilibrium in models with genetic transformation and conjugation

Expressions are obtained for the expected levels of linkage disequilibrium under three different equilibrium neutral models that make different assumptions about how recombination takes place. A transformation model is considered in which exchange events involve only one locus at a time. Two conjugation models are considered one with a linear genome and one with a circular genome. In the conjugation models large blocks of genes can be transferred with each conjugation. Consistent with published simulation results, it is found that if the transformation rate per locus is more than twenty times the mutation rate per locus, then the levels of linkage disequilibrium are quite low. If the number of loci being sampled is greater than 10, conjugation with a circular genome can be considerably more effective than transformation in reducing linkage disequilibrium. When recombination rates are high, expected linkage disequilibrium is shown to be proportional to the inverse of the transformation rate (or conjugation rate.)     

Kinetics of microbial degradation of vascular plant material in two wetland ecosystems

Summary Vascular plant decomposition was followed during two different years in one freshwater and one marine wetland in southeastern Georgia, USA, using a modified litterbag technique. Chemical analysis of plant material revealed different rates of decomposition for different components of the plant material (soluble components, -cellulose, hemicellulose, and lignin) and, further, that rates of decomposition of each component changed over time, such that the specific rate of decay for each fraction decreased as decomposition proceeded. Three mathematical models which differen in their treatment of the biochemical heterogeneity of vascular plant detritus were investigated with regard to their relative abilities to describe decomposition kinetics from the field incubations as well as from laboratory microcosm studies with radiolabeled plant material. A decaying coefficient model, which treats plant detritus as a single component but allows for a decreasing specific decomposition rate as material ages, was most successful in describing kinetics of decomposition. This model accomodates the changes in quality of vascular plant detritus resulting from preferential decomposition of more labile components (e.g., non-lignocellulosic material and holocellulose) and the relative accumulation of more refractory components (e.g., lignin) observed with time. The model also accomodates the potential transformation of various plant components into more refractory compounds (humification) during the decomposition process.     

Structure-based kinetic modeling of excited-state transfer and trapping in histidine-tagged photosystem II core complexes from synechocystis

Chlorophyll fluorescence decay kinetics in photosynthesis are dependent on processes of excitation energy transfer, charge separation, and electron transfer in photosystem II (PSII). The interpretation of fluorescence decay kinetics and their accurate simulation by an appropriate kinetic model is highly dependent upon assumptions made concerning the homogeneity and activity of PSII preparations. While relatively simple kinetic models assuming sample heterogeneity have been used to model fluorescence decay in oxygen-evolving PSII core complexes, more complex models have been applied to the electron transport impaired but more highly purified D1-D2-cyt b(559) preparations. To gain more insight into the excited-state dynamics of PSII and to characterize the origins of multicomponent fluorescence decay, we modeled the emission kinetics of purified highly active His-tagged PSII core complexes with structure-based kinetic models. The fluorescence decay kinetics of PSII complexes contained a minimum of three exponential decay components at F(0) and four components at F(m). These kinetics were not described well with the single radical pair energy level model, and the introduction of either static disorder or a dynamic relaxation of the radical pair energy level was required to simulate the fluorescence decay adequately. An unreasonably low yield of charge stabilization and wide distribution of energy levels was required for the static disorder model, and we found the assumption of dynamic relaxation of the primary radical pair to be more suitable. Comparison modeling of the fluorescence decay kinetics from PSII core complexes and D1-D2-cyt b(559) reaction centers indicated that the rates of charge separation and relaxation of the radical pair are likely altered in isolated reaction centers.     

The kinetics of cometabolism

Experimental observations indicate that the rates of cometabolic transformation are linked to the consumption of growth substrate during growth and to the consumption of cell mass and/or energy substrate in the absence of growth substrate. Three previously proposed models (models 1 through 3) describing the kinetics of cometabolism by resting cells are compared, and the interrelationships and underlying assumptions for these models are explored. Models 1 to 3 are shown to converge at high concentrations of the nongrowth substrate. An expression describing nongrowth substrate transformation in the presence of growth substrate is proposed, and this expression is integrated with an expression for cell growth to give a single unstructured model (model 4) that encompasses models 1 to 3 and describes cometabolism by both resting and growing cells. Model 4 couples transformation of nongrowth substrate to consumption of growth substrate and biomass, and predicts that cometabolism will result, and decreased specific growth rates for a cometabolizing population. Competitive inhibition can also be incorporated in the model. Experimental aspects of model calibration and verification are discussed. The need for models that distinguish between the exhaustion of cell activity and cell death is emphasized. (c) 1993 Wiley & Sons, Inc.     

Autumnal biomass and potential productivity of salt marsh fungi from 29 degrees to 43 degrees north latitude along the United States Atlantic Coast

It has been established that substantial amounts of fungal mass accumulate in standing decaying smooth cordgrass (Spartina alterniflora) marshes in the southeastern United States (e.g., in standing decaying leaf blades with a total fungal organic mass that accounts for about 20% of the decay system organic mass), but it has been hypothesized that in marshes farther north this is not true. We obtained samples of autumnal standing decaying smooth cordgrass from sites in Florida to Maine over a 3-year period. The variation in latitude could not explain any of the variation in the living fungal standing crop (as determined by ergosterol content) or in the instantaneous rates of fungal growth (as determined by acetate incorporation into ergosterol at a standard temperature, 20 degrees C), which led to the conclusion that the potential levels of fungal production per unit of naturally decaying grass are not different in northern and southern marshes. Twenty-one percent of the variation in the size of the living fungal standing crop could be explained by variation in the C/N ratio (the higher the C/N ratio the smaller the fungal crop), but the C/P ratio was not related to the size of the fungal crop. Instantaneous rates of fungal growth were negatively related to the size of the living fungal crop (r = -0.35), but these rates were not correlated with C/nutrient ratios. The same two predominant species of ascomycetes (one Phaeosphaeria species and one Mycosphaerella species) were found ejecting ascospores from standing decaying smooth cordgrass blades at all of the sites examined from Florida to Maine.     

Estimation of Thalamocortical and Intracortical Network Models from Joint Thalamic Single-Electrode and Cortical Laminar-Electrode Recordings in the Rat Barrel System

A new method is presented for extraction of population firing-rate models for both thalamocortical and intracortical signal transfer based on stimulus-evoked data from simultaneous thalamic single-electrode and cortical recordings using linear (laminar) multielectrodes in the rat barrel system. Time-dependent population firing rates for granular (layer 4), supragranular (layer 2/3), and infragranular (layer 5) populations in a barrel column and the thalamic population in the homologous barreloid are extracted from the high-frequency portion (multi-unit activity; MUA) of the recorded extracellular signals. These extracted firing rates are in turn used to identify population firing-rate models formulated as integral equations with exponentially decaying coupling kernels, allowing for straightforward transformation to the more common firing-rate formulation in terms of differential equations. Optimal model structures and model parameters are identified by minimizing the deviation between model firing rates and the experimentally extracted population firing rates. For the thalamocortical transfer, the experimental data favor a model with fast feedforward excitation from thalamus to the layer-4 laminar population combined with a slower inhibitory process due to feedforward and/or recurrent connections and mixed linear-parabolic activation functions. The extracted firing rates of the various cortical laminar populations are found to exhibit strong temporal correlations for the present experimental paradigm, and simple feedforward population firing-rate models combined with linear or mixed linear-parabolic activation function are found to provide excellent fits to the data. The identified thalamocortical and intracortical network models are thus found to be qualitatively very different. While the thalamocortical circuit is optimally stimulated by rapid changes in the thalamic firing rate, the intracortical circuits are low-pass and respond most strongly to slowly varying inputs from the cortical layer-4 population.     

Anthropogenic N Deposition Increases Soil C Storage by Decreasing the Extent of Litter Decay: Analysis of Field Observations with an Ecosystem Model

Recent meta-analyses of experimental studies simulating increased anthropogenic nitrogen (N) deposition in forests reveal greater soil carbon (C) storage under elevated levels of atmospheric N deposition. However, these effects have not yet been included in ecosystem-scale models of soil C and N cycling and it is unclear whether increased soil C storage results from slower decomposition rates or a reduced extent of decomposition (for example, an increase in the amount of litter entering slowly decaying humus pools). To test these alternatives, we conducted a meta-analysis of litter decomposition data. We then used the results from our meta-analysis to model C and N cycling in four sugar maple forests in Michigan using an ecosystem process model (TRACE). We compared model results testing our alternative hypotheses to field data on soil C storage from a 17-year N deposition experiment. Using data from published litter decomposition studies in forests, we determined that, on average, exogenous N inputs decreased lignin decomposition rates by 30% and increased cellulose decomposition by 9%. In the same set of litter decomposition studies increased exogenous N availability increased the amount of litter entering slowly decaying humus pools in a manner significantly related to the lignocellulose index of decaying litter. Incorporating changes to decomposition rates in TRACE did not accurately reproduce greater soil C storage observed in our field study with experimentally elevated N deposition. However, when changes in the extent of decomposition were incorporated in TRACE, the model produced increased soil C storage by increasing the amount of litter entering the humus pool and accurately represented C storage in plant and soil pools under experimental N deposition. Our modeling results and meta-analysis indicate that the extent of litter decay as humus is formed, rather than slower rates of litter decay, is likely responsible for the accumulation of organic matter, and hence soil C storage, under experimental N deposition. This effect should be incorporated in regional to global-scale models simulating the C balance of forest ecosystems in regions receiving elevated N deposition.     

Autumnal Biomass and Potential Productivity of Salt Marsh Fungi from 29° to 43° North Latitude along the United States Atlantic Coast

It has been established that substantial amounts of fungal mass accumulate in standing decaying smooth cordgrass (Spartina alterniflora) marshes in the southeastern United States (e.g., in standing decaying leaf blades with a total fungal organic mass that accounts for about 20% of the decay system organic mass), but it has been hypothesized that in marshes farther north this is not true. We obtained samples of autumnal standing decaying smooth cordgrass from sites in Florida to Maine over a 3-year period. The variation in latitude could not explain any of the variation in the living fungal standing crop (as determined by ergosterol content) or in the instantaneous rates of fungal growth (as determined by acetate incorporation into ergosterol at a standard temperature, 20°C), which led to the conclusion that the potential levels of fungal production per unit of naturally decaying grass are not different in northern and southern marshes. Twenty-one percent of the variation in the size of the living fungal standing crop could be explained by variation in the C/N ratio (the higher the C/N ratio the smaller the fungal crop), but the C/P ratio was not related to the size of the fungal crop. Instantaneous rates of fungal growth were negatively related to the size of the living fungal crop (r = −0.35), but these rates were not correlated with C/nutrient ratios. The same two predominant species of ascomycetes (one Phaeosphaeria species and one Mycosphaerella species) were found ejecting ascospores from standing decaying smooth cordgrass blades at all of the sites examined from Florida to Maine.     

Woody Debris Volume Depletion Through Decay: Implications for Biomass and Carbon Accounting

Woody debris decay rates have recently received much attention because of the need to quantify temporal changes in forest carbon stocks. Published decay rates, available for many species, are commonly used to characterize deadwood biomass and carbon depletion. However, decay rates are often derived from reductions in wood density through time, which when used to model biomass and carbon depletion are known to underestimate rate loss because they fail to account for volume reduction (changes in log shape) as decay progresses. We present a method for estimating changes in log volume through time and illustrate the method using a chronosequence approach. The method is based on the observation, confirmed herein, that decaying logs have a collapse ratio (cross-sectional height/width) that can serve as a surrogate for the volume remaining. Combining the resulting volume loss with concurrent changes in wood density from the same logs then allowed us to quantify biomass and carbon depletion for three study species. Results show that volume, density, and biomass follow distinct depletion curves during decomposition. Volume showed an initial lag period (log dimensions remained unchanged), even while wood density was being reduced. However, once volume depletion began, biomass loss (the product of density and volume depletion) occurred much more rapidly than density alone. At the temporal limit of our data, the proportion of the biomass remaining was roughly half that of the density remaining. Accounting for log volume depletion, as demonstrated in this study, provides a comprehensive characterization of deadwood decomposition, thereby improving biomass-loss and carbon-accounting models.     

Rates of decay in wood measured by carbon dioxide production

The applicability of two methods of respirometry to measurement of the carbon dioxide output of naturally decaying branches and wood of standing trees was studied. The Warburg respirometer was judged unsuitable for general use on decaying wood. A conductivity respirometer was found satisfactory. Carbon dioxide production was essentially unaffected by fragmentation suggesting that the measurements obtained are likely to be a valuable indication of decay in the intact tree or branch. The carbon dioxide production of samples was fairly stable when conditions were kept constant but responded promptly to increased or decreased moisture. Wood from branches infested with Polyporus tulipiferae in which moisture was increased from approximately 20%–50% (fresh weight basis) increased its carbon dioxide output over a 4-day period by some seven times. Comparable wood in which the moisture content was reduced from 45 to 20 % showed an almost linear reduction in rate over a similar period to about one-sixth the original rate. Rate of decay in stained and unstained zones of living trees showed no consistent effect of the stain. However, rates of decay in heart-rot of poplar caused by Fomes igniarius were only one-third those reported by Verrall (1937) for decay in culture.     

The influence of substrate quality and stream size on wood decomposition dynamics

Woody materials decayed more rapidly in a first order stream than in larger streams in eastern Quebec, Canada. The rate of annual mass loss (k) was highest (k=1.20) for alder wood chips in a first order stream and lowest (k=0.04) for black spruce wood chips in a ninth order stream. Decay rates for woody materials in a first order stream were inversely related to their initial lignin to nitrogen ratios. In larger streams, decay rates of woody materials were inversely related to their initial lignin concentrations. A number of quantifiable relationships were found to exist between the initial lignin and nitrogen contents of woody materials and the nitrogen dynamics of decaying wood.     

Identifying conversion efficiency as a key mechanism underlying food webs adaptive evolution: a step forward,or backward?

Body size or mass is one of the main factors underlying food webs structure. A large number of evolutionary models have shown that indeed, the adaptive evolution of body size (or mass) can give rise to hierarchically organised trophic levels with complex between and within trophic interactions. However, these models generally make strong arbitrary assumptions on how traits evolve, casting doubts on their robustness. In particular, biomass conversion efficiency is always considered independent of the predator and prey size, which contradicts with the literature. In this paper, we propose a general model encompassing most previous models which allows to show that relaxing arbitrary assumptions gives rise to unrealistic food webs. We then show that considering biomass conversion efficiency dependent on species size is certainly key for food webs adaptive evolution because realistic food webs can evolve, making obsolete the need of arbitrary constraints on traits' evolution. We finally conclude that, on the one hand, ecologists should pay attention to how biomass flows into food webs in models. On the other hand, we question more generally the robustness of evolutionary models for the study of food webs.     

Mechanisms and Rates of Decay of Marine Viruses in Seawater

Loss rates and loss processes for viruses in coastal seawater from the Gulf of Mexico were estimated with three different marine bacteriophages. Decay rates in the absence of sunlight ranged from 0.009 to 0.028 h^-1, with different viruses decaying at different rates. In part, decay was attributed to adsorption by heat-labile particles, since viruses did not decay or decayed very slowly in seawater filtered through a 0.2-μm-pore-size filter (0.2-μm-filtered seawater) and in autoclaved or ultracentrifuged seawater but continued to decay in cyanide-treated seawater. Cyanide did cause decay rates to decrease, however, indicating that biological processes were also involved. The observations that decay rates were often greatly reduced in 0.8- or 1.0-μm-filtered seawater, whereas bacterial numbers were not, suggested that most bacteria were not responsible for the decay. Decay rates were also reduced in 3-μm-filtered or cycloheximide-treated seawater but not in 8-μm-filtered seawater, implying that flagellates consumed viruses. Viruses added to flagellate cultures decayed at 0.15 h^-1, corresponding to 3.3 viruses ingested flagellate^-1 h^-1. Infectivity was very sensitive to solar radiation and, in full sunlight, decay rates were 0.4 to 0.8 h^-1. Even when UV-B radiation was blocked, rates were as high as 0.17 h^-1. Calculations suggest that in clear oceanic waters exposed to full sunlight, most of the virus decay, averaged over a depth of 200 m, would be attributable to solar radiation. When decay rates were averaged over 24 h for a 10-m coastal water column, loss rates of infectivity attributable to sunlight were similar to those resulting from all other processes combined. Consequently, there should be a strong diel signal in the concentration of infectious viruses. In addition, since sunlight destroys infectivity more quickly than virus particles, a large proportion of the viruses in seawater is probably not infective.     

The Effects of Vector Movement and Distribution in a Mathematical Model of Dengue Transmission

Background

Mathematical models have been used to study the dynamics of infectious disease outbreaks and predict the effectiveness of potential mass vaccination campaigns. However, models depend on simplifying assumptions to be tractable, and the consequences of making such assumptions need to be studied. Two assumptions usually incorporated by mathematical models of vector-borne disease transmission is homogeneous mixing among the hosts and vectors and homogeneous distribution of the vectors.

Methodology/Principal Findings

We explored the effects of mosquito movement and distribution in an individual-based model of dengue transmission in which humans and mosquitoes are explicitly represented in a spatial environment. We found that the limited flight range of the vector in the model greatly reduced its ability to transmit dengue among humans. A model that does not assume a limited flight range could yield similar attack rates when transmissibility of dengue was reduced by 39%. A model in which mosquitoes are distributed uniformly across locations behaves similarly to one in which the number of mosquitoes per location is drawn from an exponential distribution with a slightly higher mean number of mosquitoes per location. When the models with different assumptions were calibrated to have similar human infection attack rates, mass vaccination had nearly identical effects.

Conclusions/Significance

Small changes in assumptions in a mathematical model of dengue transmission can greatly change its behavior, but estimates of the effectiveness of mass dengue vaccination are robust to some simplifying assumptions typically made in mathematical models of vector-borne disease.     

Possible forms for dwell-time histograms from single-channel current records

Certain macromolecules embedded in the cell membranes of a variety of cells behave as gated ion-selective pores or channels. The length of time that a channel remains open or closed is not deterministic in nature and must be described in terms of relative probabilities. If channels act independently of each other and appropriate experimental conditions can be maintained, the behavior of a channel can be described by a homogeneous Markov process. Using this representation, the relative probability of observing openings (or closings) of various durations can be described by a sum of discrete components which are related to the underlying model of the kinetic behavior of the channel. Generally, these discrete components are taken to be simple decaying exponentials; however, exponentially decaying oscillatory components (as well as certain others which are discussed) are consistent with the Markov process representation. The presence of components other than simple decaying exponentials is shown to imply the violation of detailed balance in the steady-state (which requires energy), and thus, the presence of cyclic pathways in models which accurately represent the kinetic behavior of the channel. Oscillatory components, if present, will in general decay at a faster rate than the slowest decaying component, which, except under a very restricted set of conditions, will be a simple exponential.     

Comparison of Arrhenius-type and Bêlehrádek-type models for prediction of bacterial growth in foods

D.A. RATKOWSKY, T. ROSS, T.A. WCMEEKIN AND J. OLLEY. 1991. The development of Arrhenius-type ('Schoolfield') and Bêlehrádek-type (square root) models that describe microbial growth rates is briefly described. Both types of model have been advocated for use in predictive microbiology. On the basis of published data sets for the growth of bacteria, the consequences of mathematical transformation of data and the use of invalid stochastic assumptions upon model predictions are demonstrated. Mean square error is shown to be an inappropriate criterion by which to compare the performance of predictive models. The data show that bacterial growth responses such as generation time and lag time become more variable as their mean magnitude increases. The practical consequences of such variability for predictive microbiology are discussed.     

Measurement of protein turnover in rat liver. Analysis of the complex curve for decay of label in a mixture of proteins.

The curve for decay of 14C in rat liver protein labelled by injection of NaH14CO3 was analysed to obtain the average turnover rate of mixed liver protein. Three different methods of analysis were used. (1) Unlike decay curves from homogeneous proteins, the curve did not fit a single exponential, but a good fit was obtained with three exponentials. By assuming that the mixture contained three major components with different turnover rates, the calculated value for the average turnover rate (k) was close to 40% per day. (2) k was also calculated from the area under the decay curve, a method which makes no assumptions about the number of proteins in the mixture. This method also gave a value close to 40% per day. (3) It was shown empirically, both by simulation of decay of label in model mixtures of protein and with the decay curve measured in vivo, that k can be calculated from the time taken for the specific radioactivity to fall to 10% of its maximum value. This is an advantage, since the other two methods require the decay curve to be measured over a much longer period of time.     

Decomposition Patterns of Foliar Litter and Deadwood in Managed and Unmanaged Stands: A 13-Year Experiment in Boreal Mixedwoods

Litter decomposition is a major driver of carbon (C) and nitrogen (N) cycles in forest ecosystems and has major implications for C sequestration and nutrient availability. However, empirical information regarding long-term decomposition rates of foliage and wood remains rare. In this study, we assessed long-term C and N dynamics (12–13 years) during decomposition of foliage and wood for three boreal tree species, under a range of harvesting intensities and slash treatments. We used model selection based on the second-order Akaike’s Information Criterion to determine which decomposition model had the most support. The double-exponential model provided a good fit to C mass loss for foliage of trembling aspen, white spruce, and balsam fir, as well as aspen wood. These litters underwent a rapid initial phase of leaching and mineralisation, followed by a slow decomposition. In contrast, for spruce and fir wood, the single-exponential model had the most support. The long-term average decay rate of wood was faster than that of foliage for aspen, but not of conifers. However, we found no evidence that fir and spruce wood decomposed at slower rates than the recalcitrant fraction of their foliage. The critical C:N ratios, at which net N mineralisation began, were higher for wood than for foliage. Long-term decay rates following clear-cutting were either similar or faster than those observed in control stands, depending on litter material, tree species, and slash treatment. The critical C:N ratios were reached later and decreased for all conifer litters following stem-only clear-cutting, indicating increased N retention in harvested sites with high slash loads. Partial harvesting had weak effects on C and N dynamics of decaying litters. A comprehensive understanding of the long-term patterns and controls of C and N dynamics following forest disturbance would improve our ability to forecast the implications of forest harvesting for C sequestration and nutrient availability.     

The application of Artificial Neural Network (ANN) model to the simulation of denitrification rates in mesocosm-scale wetlands

Denitrification and its regulating factors are of great importance to aquatic ecosystems, as denitrification is a critical process to nitrogen removal. Additionally, a by-product of denitrification, nitrous oxide, is a much more potent greenhouse gas than carbon dioxide. However, the estimation of denitrification rates is usually clouded with uncertainty, mainly due to high spatial and temporal variations, as well as complex regulating factors within wetlands. This hampers the development of general mechanistic models for denitrification as well, as most previously developed models were empirical or exhibited low predictability with numerous assumptions. In this study, we tested Artificial Neural Network (ANN) as an alternative to classic empirical models for simulating denitrification rates in wetlands. ANN, multiple linear regression (MLR) with two different methods, and simplified mechanistic models were applied to estimate the denitrification rates of 2-year observations in a mesocosm-scale constructed wetland system. MLR and simplified mechanistic models resulted in lower prediction power and higher residuals compared to ANN. Although the stepwise linear regression model estimated similar average values of denitrification rates, it could not capture the fluctuation patterns accurately. In contrast, ANN model achieved a fairly high predictability, with an R² of 0.78 for model validation, 0.93 for model calibration (training), and a low root mean square error (RMSE) together with low bias, indicating a high capacity to simulate the dynamics of denitrification. According to a sensitivity analysis of the ANN, non-linear relationships between input variables and denitrification rates were well explained. In addition, we found that water temperature, denitrifying enzyme activity (DEA), and DO accounted for 70% of denitrification rates. Our results suggest that the ANN developed in this study has a greater performance in simulating variations in denitrification rates than multivariate linear regressions or simplified nonlinear mechanistic model.