Unpredicted ecosystem response to compound human impacts in a European river.

Climate change elevates the threat of compound heat and drought events, with their ecological and socioeconomic impacts exacerbated by human ecosystem alterations such as eutrophication, salinization, and river engineering. Here, we study how multiple stressors produced an environmental disaster in a large European river, the Oder River, where a toxic bloom of the brackish-water planktonic haptophyte Prymnesium parvum (the "golden algae") killed approximately 1000 metric tons of fish and most mussels and snails. We uncovered the complexity of this event using hydroclimatic data, remote sensing, cell counts, hydrochemical and toxin analyses, and genetics. After incubation in impounded upstream channels with drastically elevated concentrations of salts and nutrients, only a critical combination of chronic salt and nutrient pollution, acute high water temperatures, and low river discharge during a heatwave enabled the riverine mass proliferation of B-type P. parvum along a 500 km river section. The dramatic losses of large filter feeders and the spreading of vegetative cells and resting stages make the system more susceptible to new harmful algal blooms. Our findings show that global warming, water use intensification, and chronic ecosystem pollution could increase likelihood and severity of such compound ecoclimatic events, necessitating consideration in future impact models.

OGUMI-A new mobile application to conduct common-pool resource experiments in continuous time.

OGUMI is an Android-based open source mobile application for conducting Common-Pool Resource Experiments, Choice Experiments, and Questionnaires in the field, in the laboratory, and online. A main feature of OGUMI is its capacity to capture real-time changes in human behaviour in response to a dynamically varying resource. OGUMI is simple (for example, likewise other existing software, it does not require expertise in behavioural game theory), stable, and extremely flexible with respect to the user-resource model running in the background. Here we present the motivation for the development of OGUMI and we discuss its main features with an example application.

Mechanisms shaping size structure and functional diversity of phytoplankton communities in the ocean.

The factors regulating phytoplankton community composition play a crucial role in structuring aquatic food webs. However, consensus is still lacking about the mechanisms underlying the observed biogeographical differences in cell size composition of phytoplankton communities. Here we use a trait-based model to disentangle these mechanisms in two contrasting regions of the Atlantic Ocean. In our model, the phytoplankton community can self-assemble based on a trade-off emerging from relationships between cell size and (1) nutrient uptake, (2) zooplankton grazing, and (3) phytoplankton sinking. Grazing 'pushes' the community towards larger cell sizes, whereas nutrient uptake and sinking 'pull' the community towards smaller cell sizes. We find that the stable environmental conditions of the tropics strongly balance these forces leading to persistently small cell sizes and reduced size diversity. In contrast, the seasonality of the temperate region causes the community to regularly reorganize via shifts in species composition and to exhibit, on average, bigger cell sizes and higher size diversity than in the tropics. Our results raise the importance of environmental variability as a key structuring mechanism of plankton communities in the ocean and call for a reassessment of the current understanding of phytoplankton diversity patterns across latitudinal gradients.

Human adaptive behavior in common pool resource systems.

Overexploitation of common-pool resources, resulting from uncooperative harvest behavior, is a major problem in many social-ecological systems. Feedbacks between user behavior and resource productivity induce non-linear dynamics in the harvest and the resource stock that complicate the understanding and the prediction of the co-evolutionary system. With an adaptive model constrained by data from a behavioral economic experiment, we show that users' expectations of future pay-offs vary as a result of the previous harvest experience, the time-horizon, and the ability to communicate. In our model, harvest behavior is a trait that adjusts to continuously changing potential returns according to a trade-off between the users' current harvest and the discounted future productivity of the resource. Given a maximum discount factor, which quantifies the users' perception of future pay-offs, the temporal dynamics of harvest behavior and ecological resource can be predicted. Our results reveal a non-linear relation between the previous harvest and current discount rates, which is most sensitive around a reference harvest level. While higher than expected returns resulting from cooperative harvesting in the past increase the importance of future resource productivity and foster sustainability, harvests below the reference level lead to a downward spiral of increasing overexploitation and disappointing returns.