Effects Of Stochastic Processes Research Articles

Ecological evolution of algae in connected reservoirs under the influence of water transfer: Algal density, community structure, and assembly processes

Reservoir connectivity provides a solution for regional water shortages. Understanding the water quality of reservoirs and the response of algal communities to water transfer could provide the basis for a long-term evolutionary model of reservoirs. In this study, a water-algal community model was established to study the effects of water transfer on water quality and algal communities in reservoirs. The results showed that water transfer significantly decreased total nitrogen and nitrate concentrations. However, the water transfer resulted in an increase in the CODMn concentration and conductivity in the receiving reservoir. Additionally, the algal density and chlorophyll-a (chl-a) concentration showed an increase with water transfer. Bacillariophyta, Cyanophyta, and Chlorophyta were the dominant algal phyllum in all three reservoirs. Water transfer induced the evolution of the algal community by driving changes in the chemical parameters of the receiving reservoir and led to more complex relationships within the algal community. The effects of stochastic processes on algal communities were also enhanced in the receiving reservoirs. These results provide specific information for water quality safety management and eutrophication prevention in connected reservoirs.

Stochastic processes drive the soil fungal communities in a developing mid-channel bar.

Intricate associations between rhizosphere microbial communities and plants play a critical role in developing and maintaining of soil ecological functioning. Therefore, understanding the assembly patterns of rhizosphere microbes in different plants and their responses to environmental changes is of great ecological implications for dynamic habitats. In this study, a developing mid-channel bar was employed in the Yangtze River to explore the assembly processes of rhizosphere fungal communities among various plant species using high-throughput sequencing-based null model analysis. The results showed a rare significant variation in the composition and alpha diversity of the rhizosphere fungal community among various plant species. Additionally, the soil properties were found to be the primary drivers instead of plant species types. The null model analysis revealed that the rhizosphere fungal communities were primarily driven by stochastic processes (i.e., undominated processes of ecological drift), and the predominance varied with various plant species. Moreover, the assembly processes of rhizosphere fungal communities were significantly related to the changes in soil properties (i.e., soil total carbon, total nitrogen, organic matter, and pH). The co-occurrence network analysis revealed that many keystone species belonged to unclassified fungi. Notably, five network hubs were almost unaffected by the measured soil properties and aboveground plant traits, indicating the effect of stochastic processes on the rhizosphere fungal community assembly. Overall, these results will provide insights into the underlying mechanisms of fungal community assembly in the rhizosphere soils, which are significant for maintaining the functional stability of a developing ecosystem.

Stochastic Variational Method for Viscous Hydrodynamics

In this short review, we focus on some of the subjects, related to J. Cleymans’ pioneering contribution of statistical approaches to the particle production process in heavy-ion collisions. We discuss these perspectives from the effects of stochastic processes in collective variables of hydrodynamic description, which is described by a stochastic variational method. In this connection, we stress also the necessity of the inclusion of surface and quantum effects in the study of relativistic heavy-ion reactions.

Effect of stochastic processes on structure formation in nanocrystalline materials under severe plastic deformation.

Based on the nonequilibrium evolution thermodynamics, the structure refinement of metals during severe plastic deformation is investigated. To describe the formation of stationary (limiting) submicrocrystalline or nanocrystalline structures, a two-defect approximation, including the grain boundaries and dislocations, is used. Introduction of the additive noise for the main parameters into the governing equations allowed us to describe the self-consistent behavior of structural defects during the stationary structure formation. Conditions of achieving the stationary state are investigated and possible scenarios of structure refinement modes are determined. Obtained grain boundary density distributions help to estimate the composition of grain structure in the bulk of metal sample quantitatively. The analysis of time evolution of the grain boundaries density shows the presence of correlated fluctuations. The autocorrelation function, describing the frequency characteristics of the structure refinement, is determined.

Use of phytoplankton functional groups as a model of spatial and temporal patterns in reservoirs: a case study in a reservoir of central Brazil

We analyzed the temporal (dry and rainy periods) and spatial (zones) phytoplankton biomass variation (FGs—functional groups) in a tropical reservoir, and determined the main drivers. We hypothesized that water flow negatively affects the FG–environment relationship because high flow promotes dispersal stochasticity. Our results indicated that the FG–environment relationship was affected mainly by the rainfall regime. Periods with intermediate precipitation showed greater predictability than periods with extreme precipitation. This suggests that the effect of stochastic processes on the phytoplankton community is more important in both the highest and lowest water flow, and deterministic processes are more important at intermediate flow. The longitudinal gradient of nutrients, light, and water-column mixing influenced the distribution of the FG biomass. The riverine zone showed high nutrient concentrations, low light availability, and a high biomass of organisms related to highly enriched systems (FG J—chlorophyceans) and shade-adapted taxa (FG S1—cyanobacteria). The lacustrine zone showed high light availability and a high biomass of heterocytous cyanobacteria (FGs S N and H1) and meroplanktonic diatoms (FG MP). The functional approach can be applied to understand the processes responsible for species coexistence and for the organization of aquatic ecosystems.

Letters to the Editor

Sir, Comments on ‘Observation of enhanced efficiency in the excitation of ion-induced LiF:Mg,Ti thermoluminescent peaks’ G. Massillon., I. Gamboa-deBuen and M.E. Brandan, J. Appl. Phys. 100, 103521–1 (2006). In the above paper by Massillon et al., the authors have described experimental measurements of the heavy-ion relative TL efficiency of the high-temperature peaks in LiF:Mg,Ti (TLD-100) and, as well, their interpretation of the data in the framework of Track Structure Theory (TST)(1) and Modified Track Structure Theory (MTST)(2). In order to allow the reader an appreciation of the errors and conceptual failings involved in the efforts of Massillon et al. to interpret/analyse their data, a brief review of TST and MTST is required as well as a short description of what is commonly referred to as ‘high-temperature thermoluminescence’ or HTTL in LiF:Mg,Ti (TLD-100). The basic premise in the calculation of heavy charged particle (HCP) radiation effects in both TST and MTST is that the radiation effects of HCPs are due to the average dose delivered by the secondary electrons created by the HCP slowing down; and can therefore be predicted by the experimentally measured gamma-ray/electron dose–response folded into the radial dose distribution of the HCP. Radial dose profiles explicitly neglect the stochastic processes of the secondary electrons liberated by the HCP which, of course, are considered to be important in the microdosimetric treatment of radiobiological systems. In TL, these stochastic processes can be neglected since the TL signal is obtained or is measurable from the HCP interaction only at high levels of fluence, i.e. >105 cm−2 where the effects of stochastic processes which might arise in single tracks are completely averaged out. Of course, in solid-state systems, the radial dose distribution cannot be directly measured experimentally as in gaseous systems. These, therefore, have been calculated analytically(3) or obtained by track segment Monte Carlo calculations(4). In general, for low-energy proton and helium ions in the energy range 1–10 MeV, the calculated dose values start at MGy levels near the track axis, with a dependence on radial distance decreasing approximately as r−2 and reaching ∼Gy dose levels at distances of several hundreds to a few thousand Å from the track axis. More recently, full track radial dose profiles have been calculated for low-energy proton and helium ions using the Monte Carlo code FLUKA in nanometer-sized volumes(5). At these low proton and helium energies, the ions are stopped in the TL sample so that the nanometric FLUKA full track calculations describe the HCP slowing down and stopping process in a manner far more resembling the experimental situation than track segment calculations, and this particular point will be touched on later in this comment.