Succession of bacteria and archaea involved in the nitrogen cycle of a seasonally stratified lake.

Human-driven changes affect nutrient inputs, oxygen solubility, and the hydrodynamics of lakes, which affect biogeochemical cycles mediated by microbial communities. However, information on the succession of microbes involved in nitrogen cycling in seasonally stratified lakes is still incomplete. Here, we investigated the succession of nitrogen-transforming microorganisms in Lake Vechten over a period of 19 months, combining 16S rRNA gene amplicon sequencing and quantification of functional genes. Ammonia-oxidizing archaea (AOA) and bacteria (AOB) and anammox bacteria were abundant in the sediment during winter, accompanied by nitrate in the water column. Nitrogen-fixing bacteria and denitrifying bacteria emerged in the water column in spring when nitrate was gradually depleted. Denitrifying bacteria containing nirS genes were exclusively present in the anoxic hypolimnion. During summer stratification, abundances of AOA, AOB, and anammox bacteria decreased sharply in the sediment, and ammonium accumulated in hypolimnion. After lake mixing during fall turnover, abundances of AOA, AOB, and anammox bacteria increased and ammonium was oxidized to nitrate. Hence, nitrogen-transforming microorganisms in Lake Vechten displayed a pronounced seasonal succession, which was strongly determined by the seasonal stratification pattern. These results imply that changes in stratification and vertical mixing induced by global warming are likely to alter the nitrogen cycle of seasonally stratified lakes.

Dataset of occurrence and incidence of pine processionary moth in Andalusia, south Spain.

This dataset provides information about infestation caused by the pine processionary moth (Thaumetopoeapityocampa ([Denis & Schiffermüller], 1775)) in pure or mixed pine woodlands and plantations in Andalusia. It represents a long-term series (1993-2015) containing 81,908 records that describe the occurrence and incidence of this species. Data were collected within a monitoring programme known as COPLAS, developed by the Regional Ministry of Environment and Territorial Planning of the Andalusian Regional Government within the frame of the Plan de Lucha Integrada contra la Procesionaria del Pino (Plan for Integrated Control Against the Pine Processionary Moth). In particular, this dataset includes 4,386 monitoring stands which, together with the campaign year, define the dataset events in Darwin Core Archive. Events are related with occurrence data which show if the species is present or absent. In turn, the event data have a measurement associated: degree of infestation.

Toward an Ecologically Optimized N:P Recovery from Wastewater by Microalgae.

Global stores of important resources such as phosphorus (P) are being rapidly depleted, while the excessive use of nutrients has led to the enrichment of surface waters worldwide. Ideally, nutrients would be recovered from wastewater, which will not only prevent eutrophication but also provide access to alternative nutrient stores. Current state-of-the-art wastewater treatment technologies are effective in removing these nutrients from wastewater, yet they can only recover P and often in an insufficient way. Microalgae, however, can effectively assimilate P and nitrogen (N), as well as other macro- and micronutrients, allowing these nutrients to be recovered into valuable products that can be used to close nutrient cycles (e.g., fertilizer, bioplastics, color dyes, and bulk chemicals). Here, we show that the green alga Chlorella sorokiniana is able to remove all inorganic N and P present in concentrated toilet wastewater (i.e., black water) with N:P ratios ranging between 15 and 26. However, the N and P uptake by the algae is imbalanced relative to the wastewater N:P stoichiometry, resulting in a rapid removal of P but relatively slower removal of N. Here, we discuss how ecological principles such as ecological stoichiometry and resource-ratio theory may help optimize N:P removal and allow for more effective recovery of N and P from black water.

SIMONI (smart integrated monitoring) as a novel bioanalytical strategy for water quality assessment: Part i-model design and effect-based trigger values.

It is virtually impossible to reliably assess water quality with target chemical analyses only. Therefore, a complementary effect-based risk assessment by bioanalyses on mixtures of bioavailable micropollutants is proposed: the Smart Integrated Monitoring (SIMONI) strategy. The goal of this strategy is to obtain more reliable information on the water quality to select optimum measures for improvement. The SIMONI strategy is 2-tiered. Tier 1 is a bioanalytical hazard identification of sites. A tier 2 ecological risk assessment is carried out only at a limited number of sites where increased hazards are detected in tier 1. Tier 2 will be customized, based on tier 1 evaluation and additional knowledge of the aquatic system. The present study focuses on the tier 1 bioanalytical hazard identification to distinguish "hot spots" of chemical pollution. First, a selection was made of relevant and cost-effective bioanalytical endpoints to cover a wide spectrum of micropollutant modes of action. Specific endpoints may indicate which classes of chemicals might cause adverse effects. Second, effect-based trigger values (EBT) were derived for these bioassays to indicate potential ecological risks. Comparison of EBT with bioassay responses should discriminate sites exhibiting different chemical hazards. Third, a model was designed to estimate the overall risks for aquatic ecosystems. The associated follow-up for risk management is a "toxicity traffic light" system: green, low hazard (no action required); orange, potential risk (further research needed); and red, high risk (mitigation measures). Thanks to cost-effectiveness, flexibility, and relevance, the SIMONI strategy has the potential to become the first bioanalytical tool to be applied in regular water quality monitoring programs. Environ Toxicol Chem 2017;36:2385-2399. © 2017 SETAC.