Efficient dynamic simulation of pH in processes associated to biofiltration of volatile inorganic pollutants

This work proposes a generic methodology to include the pH as a state variable in mathematical models of bioreactors. An ordinary differential equation for pH is stated and introduced into the general model structure of a biotrickling filter. All chemical equilibriums were considered and included into the model framework. A preliminary evaluation was performed by comparing results predicted by the model with experimental data obtained from the oxidation of thiosulfate by sulfide-oxidizing bacteria under alkaline conditions. The model was able to describe adequately the evolution of the main state variables including the pH for the initial complete oxidation of thiosulfate. The methodology presented here can be easily adapted to other mathematical models dealing with biological waste treatment processes in which pH appears as a key factor.Postprint (published version

Climatic vulnerabilities and ecological preferences of soil invertebrates across biomes.

Unlike plants and vertebrates, the ecological preferences, and potential vulnerabilities of soil invertebrates to environmental change, remain poorly understood in terrestrial ecosystems globally. We conducted a cross-biome survey including 83 locations across six continents to advance our understanding of the ecological preferences and vulnerabilities of the diversity of dominant and functionally important soil invertebrate taxa, including nematodes, arachnids and rotifers. The diversity of invertebrates was analyzed through amplicon sequencing. Vegetation and climate drove the diversity and dominant taxa of soil invertebrates. Our results suggest that declines in forest cover and plant diversity, and reductions in plant production associated with increases in aridity, can result in reductions of the diversity of soil invertebrates in a drier and more managed world. We further developed global atlases of the diversity of these important soil invertebrates, which were cross-validated using an independent database. Our study advances the current knowledge of the ecological preferences and vulnerabilities of the diversity and presence of functionally important soil invertebrates in soils from across the globe. This information is fundamental for improving and prioritizing conservation efforts of soil genetic resources and management policies

Frontshear and backshear instabilities of the mean longshore current

An analytical model based on Bowen and Holman [1989] is used to prove the existence of instabilities due to the presence of a second extremum of the background vorticity at the front side of the longshore current. The growth rate of the so-called frontshear waves depends primarily upon the frontshear but also upon the backshear and the maximum and the width of the current. Depending on the values of these parameters, either the frontshear or the backshear instabilities may dominate. Both types of waves have a cross-shore extension of the order of the width of the current, but the frontshear modes are localized closer to the coast than are the backshear modes. Moreover, under certain conditions both unstable waves have similar growth rates with close wave numbers and angular frequencies, leading to the possibility of having modulated shear waves in the alongshore direction. Numerical analysis performed on realistic current profiles confirm the behavior anticipated by the analytical model. The theory has been applied to a current profile fitted to data measured during the 1980 Nearshore Sediment Transport Studies experiment at Leadbetter Beach that has an extremum of background vorticity at the front side of the current. In this case and in agreement with field observations, the model predicts instability, whereas the theory based only on backshear instability fai led to do so

Global ecological predictors of the soil priming effect.

Identifying the global drivers of soil priming is essential to understanding C cycling in terrestrial ecosystems. We conducted a survey of soils across 86 globally-distributed locations, spanning a wide range of climates, biotic communities, and soil conditions, and evaluated the apparent soil priming effect using 13C-glucose labeling. Here we show that the magnitude of the positive apparent priming effect (increase in CO2 release through accelerated microbial biomass turnover) was negatively associated with SOC content and microbial respiration rates. Our statistical modeling suggests that apparent priming effects tend to be negative in more mesic sites associated with higher SOC contents. In contrast, a single-input of labile C causes positive apparent priming effects in more arid locations with low SOC contents. Our results provide solid evidence that SOC content plays a critical role in regulating apparent priming effects, with important implications for the improvement of C cycling models under global change scenarios

Antibiotic prophylaxis and reflux: Critical review and assessment

The use of continuous antibiotic prophylaxis (CAP) was critical in the evolution of vesicoureteral reflux (VUR) from a condition in which surgery was the standard of treatment to its becoming a medically managed condition. The efficacy of antibiotic prophylaxis in the management of VUR has been challenged in recent years, and significant confusion exists as to its clinical value. This review summarizes the critical factors in the history, use, and investigation of antibiotic prophylaxis in VUR. This review provides suggestions for assessing the potential clinical utility of prophylaxis

Microbial regulation of the soil carbon cycle: evidence from gene-enzyme relationships.

A lack of empirical evidence for the microbial regulation of ecosystem processes, including carbon (C) degradation, hinders our ability to develop a framework to directly incorporate the genetic composition of microbial communities in the enzyme-driven Earth system models. Herein we evaluated the linkage between microbial functional genes and extracellular enzyme activity in soil samples collected across three geographical regions of Australia. We found a strong relationship between different functional genes and their corresponding enzyme activities. This relationship was maintained after considering microbial community structure, total C and soil pH using structural equation modelling. Results showed that the variations in the activity of enzymes involved in C degradation were predicted by the functional gene abundance of the soil microbial community (R2>0.90 in all cases). Our findings provide a strong framework for improved predictions on soil C dynamics that could be achieved by adopting a gene-centric approach incorporating the abundance of functional genes into process models

Compared to conventional, ecological intensive management promotes beneficial proteolytic soil microbial communities for agro-ecosystem functioning under climate change-induced rain regimes

Projected climate change and rainfall variability will affect soil microbial communities, biogeochemical cycling and agriculture. Nitrogen (N) is the most limiting nutrient in agroecosystems and its cycling and availability is highly dependent on microbial driven processes. In agroecosystems, hydrolysis of organic nitrogen (N) is an important step in controlling soil N availability. We analyzed the effect of management (ecological intensive vs. conventional intensive) on N-cycling processes and involved microbial communities under climate change-induced rain regimes. Terrestrial model ecosystems originating from agroecosystems across Europe were subjected to four different rain regimes for 263 days. Using structural equation modelling we identified direct impacts of rain regimes on N-cycling processes, whereas N-related microbial communities were more resistant. In addition to rain regimes, management indirectly affected N-cycling processes via modifications of N-related microbial community composition. Ecological intensive management promoted a beneficial N-related microbial community composition involved in N-cycling processes under climate change-induced rain regimes. Exploratory analyses identified phosphorus-associated litter properties as possible drivers for the observed management effects on N-related microbial community composition. This work provides novel insights into mechanisms controlling agro-ecosystem functioning under climate change

Storm characterization and simulation for damage evolution models of maritime structures

This paper presents a new approach to statistically characterize and simulate the wave climate under storm conditions. The methodology includes the joint selection of the parameters that identify storm events (significant wave height threshold, minimum storm duration and minimum interarrival time between consecutive storms) by means of hypothesis testing on the distribution functions of the number of storm events and the elapsing time between storms, providing an improved characterization of the parameters that define storm events. The main wave variables and their temporal dependence are characterized by non-stationary mixture distribution functions and a vector autoregressive model. This allows to adequately reproduce the random temporal evolution of storm events, crucial for the study of damage progression in maritime structures without the use of predefined geometries. The long-term time series of storm events and calm periods is obtained using copula functions which analyze the joint dependence of storm duration and interarrival time for separate climate intervals. The model is applied to hindcast data at a location of the Mediterranean sea close to the Granada coast in Spain to show its ability to reproduce wave storm conditions accounting for the time variability of the storminess. An example of application, using a large number of simulations and a damage progression model in a maritime structure, is presented

MarineTools.temporal: A Python package to simulate Earth and environmental time series

The assessment of the uncertainty about the evolution of complex processes usually requires different realizations consisting of multivariate temporal signals of environmental data. However, it is common to have only one observational set. MarineTools.temporal is an open-source Python package for the non-stationary parametric statistical analysis of vector random processes suitable for environmental and Earth modelling. It takes a single timeseries of observations and allows the simulation of many time series with the same probabilistic behavior. The software generalizes the use of piecewise and compound distributions with any number of arbitrary continuous distributions. The code contains, among others, multi-model negative log-likely functions, wrappednormal distributions, and generalized Fourier timeseries expansion. Its programming philosophy significantly improves the computing time and makes it compatible with future extensions of scipy.stats. We apply it to the analysis of freshwater river discharge, water currents, and the simulation of ensemble projections of sea waves, to show its capabilities