Annelies J. Veraart

Recovery rates reflect distance to a tipping point in a living system

Tipping points, at which complex systems can shift abruptly from one state to another, are notoriously difficult to predict. Theory proposes that early warning signals may be based on the phenomenon that recovery rates from small perturbations should tend to zero when approaching a tipping point; however, evidence that this happens in living systems is lacking. Here we test such ‘critical slowing down’ using a microcosm in which photo-inhibition drives a cyanobacterial population to a classical tipping point when a critical light level is exceeded. We show that over a large range of conditions, recovery from small perturbations becomes slower as the system comes closer to the critical point. In addition, autocorrelation in the subtle fluctuations of the system’s state rose towards the tipping point, supporting the idea that this metric can be used as an indirect indicator of slowing down. Although stochasticity prohibits prediction of the timing of critical transitions, our results suggest that indicators of slowing down may be used to rank complex systems on a broad scale from resilient to fragile.

Warming Can Boost Denitrification Disproportionately Due to Altered Oxygen Dynamics

Background Global warming and the alteration of the global nitrogen cycle are major anthropogenic threats to the environment. Denitrification, the biological conversion of nitrate to gaseous nitrogen, removes a substantial fraction of the nitrogen from aquatic ecosystems, and can therefore help to reduce eutrophication effects. However, potential responses of denitrification to warming are poorly understood. Although several studies have reported increased denitrification rates with rising temperature, the impact of temperature on denitrification seems to vary widely between systems. Methodology/Principal Findings We explored the effects of warming on denitrification rates using microcosm experiments, field measurements and a simple model approach. Our results suggest that a three degree temperature rise will double denitrification rates. By performing experiments at fixed oxygen concentrations as well as with oxygen concentrations varying freely with temperature, we demonstrate that this strong temperature dependence of denitrification can be explained by a systematic decrease of oxygen concentrations with rising temperature. Warming decreases oxygen concentrations due to reduced solubility, and more importantly, because respiration rates rise more steeply with temperature than photosynthesis. Conclusions/Significance Our results show that denitrification rates in aquatic ecosystems are strongly temperature dependent, and that this is amplified by the temperature dependencies of photosynthesis and respiration. Our results illustrate the broader phenomenon that coupling of temperature dependent reactions may in some situations strongly alter overall effects of temperature on ecological processes.

Predicting microbial nitrogen pathways from basic principles

Nitrogen compounds are transformed by a complicated network of competing geochemical processes or microbial pathways, each performed by a different ecological guild of microorganisms. Complete experimental unravelling of this network requires a prohibitive experimental effort. Here we present a simple model that predicts relative rates of hypothetical nitrogen pathways, based only on the stoichiometry and energy yield of the performed redox reaction, assuming competition for resources between alternative pathways. Simulating competing pathways in hypothetical freshwater and marine sediment situations, we surprisingly found that much of the variation observed in nature can simply be predicted from these basic principles. Investigating discrepancies between observations and predictions led to two important biochemical factors that may create barriers for the viability of pathways: enzymatic costs for long pathways and high ammonium activation energy. We hypothesize that some discrepancies can be explained by non-equilibrium dynamics. The model predicted a pathway that has not been discovered in nature yet: the dismutation of nitrite to the level of nitrate and dinitrogen gas.

Successive DNA extractions improve characterization of soil microbial communities

Currently, characterization of soil microbial communities relies heavily on the use of molecular approaches. Independently of the approach used, soil DNA extraction is a crucial step, and success of downstream procedures will depend on how well DNA extraction was performed. Often, studies describing and comparing soil microbial communities are based on a single DNA extraction, which may not lead to a representative recovery of DNA from all organisms present in the soil. The use of successive DNA extractions might improve soil microbial characterization, but the benefit of this approach has only been limitedly studied. To determine whether successive DNA extractions of the same soil sample would lead to different observations in terms of microbial abundance and community composition, we performed three successive extractions, with two widely used commercial kits, on a range of clay and sandy soils. Successive extractions increased DNA yield considerably (1–374%), as well as total bacterial and fungal abundances in most of the soil samples. Analysis of the 16S and 18S ribosomal RNA genes using 454-pyrosequencing, revealed that microbial community composition (taxonomic groups) observed in the successive DNA extractions were similar. However, successive DNA extractions did reveal several additional microbial groups. For some soil samples, shifts in microbial community composition were observed, mainly due to shifts in relative abundance of a number of microbial groups. Our results highlight that performing successive DNA extractions optimize DNA yield, and can lead to a better picture of overall community composition.