Silicon Deficiency Induces Alkaline Phosphatase Enzyme Activity in Cultures of Four Marine Diatoms

Alkaline phosphatase (AP) was detected using ELF-97® in silicon-starved Pseudo-nitzschia multiseries cells; thus, we tested two, alternative hypotheses: Pseudo-nitzschia multiseries has a high phosphate demand, showing signs of phosphate deficiency even when concentrations of orthophosphate are high, or silicate deficiency can stimulate the AP enzyme in this species. We also studied the effect of silicon deficiency on AP in three other common marine diatoms: Thalassiosira pseudonana, Nitzschia pusilla, and Nitschia closterium. Each of the species tested showed a different pattern of AP regulation. AP levels, however, increased in the four diatoms as a result of silicon deficiency, suggesting that AP may be involved in a variety of intracellular processes related to silicon deficiency. Additionally, the results of this study indicate that AP could be stimulated by stressors other than phosphate deficiency, such as silicon deficiency; therefore, it should be used cautiously as an indicator of phosphate limitation.     

Methoxychlor bioremediation by defined consortium of environmental Streptomyces strains

Methoxychlor is an organochlorine pesticide used worldwide against several insect pests, resulting in human exposure. This pesticide mimics endocrine hormone functions, interfering with normal endocrine activity in humans and wildlife. For this reason, it is imperative to develop methods to remove this pesticide from the environment, and though, bioremediation using microorganisms results as an excellent strategy. Five Streptomyces spp. strains previously isolated from organochlorine-polluted sites and capable to grow and remove methoxychlor were combined as different mixed cultures to increase methoxychlor removal. From the 39 consortia tested, one consortium (Streptomyces spp. A6, A12, A14, M7) was selected because of its high pesticide removal and specific dechlorinase activity to be assayed on slurry and soil systems. This consortium showed higher biomass values (8.3 × 10⁶ ± 5.7 × 10⁵ CFU mL^?1) and methoxychlor removal (56.2 ± 2.3 %) on enriched slurry than in non-enriched slurry (7.3 × 10⁵ ± 1.2 × 10⁵ CFU mL^?1 and 45.6 ± 7.4 % of pesticide removal). In soil systems, Streptomyces consortium showed higher growth (1.0 × 10¹¹ ± 5.0 × 10¹⁰ CFU g^?1) than in enriched slurry, although differences in methoxychlor removal between both culture conditions were not statistically significant. Therefore, the selected Streptomyces consortium may be suitable for the development of in situ (soil) and ex situ (slurry bioreactor) bioremediation methods because of their potential to remove methoxychlor from different systems.     

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

Long‐term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, such as Central America, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information—to locally observed discharge—can be used to constrain model parameter uncertainty for ungauged catchments. Given the strong influence that climatic large‐scale processes exert on streamflow variability in the Central American region, we explored the use of climate variability knowledge as process constraints to constrain the simulated discharge uncertainty for a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty, we first rejected parameter relationships that disagreed with our understanding of the system. Then, based on this reduced parameter space, we applied the climate‐based process constraints at long‐term, inter‐annual, and intra‐annual timescales. In the first step, we reduced the initial number of parameters by 52%, and then, we further reduced the number of parameters by 3% with the climate constraints. Finally, we compared the climate‐based constraints with a constraint based on global maps of low‐flow statistics. This latter constraint proved to be more restrictive than those based on climate variability (further reducing the number of parameters by 66% compared with 3%). Even so, the climate‐based constraints rejected inconsistent model simulations that were not rejected by the low‐flow statistics constraint. When taken all together, the constraints produced constrained simulation uncertainty bands, and the median simulated discharge followed the observed time series to a similar level as an optimized model. All the constraints were found useful in constraining model uncertainty for an—assumed to be—ungauged basin. This shows that our method is promising for modelling long‐term flow data for ungauged catchments on the Pacific side of Central America and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.     

Improvement to the intergranular strain model for larger numbers of repetitive cycles

The analysis of geotechnical problems involving saturated soils under cyclic loading requires the use of advanced constitutive models. These models need to describe the main characteristics of the material under cyclic loading and undrained conditions, such as the rate of the pore water pressure accumulation and the stress attractors. When properly doing so, the models are expected to be reliable for their use in boundary value problems. In this work, an extension of the widely implemented intergranular strain model by Niemunis and Herle (Mech Cohes Frict Mater 2(4):279–299, 1997) is proposed. The modification is aimed to improve the capabilities of the model when simulating a number of repetitive cycles, where a proper reduction of the strain accumulation is expected. For validation purposes, the reference model and proposed improvement are compared against some monotonic and cyclic triaxial tests. The results indicate that the intergranular strain improvement model provides a more realistic prediction of the accumulation rates under cyclic loading, without spoiling the advantages of the original formulation.