This work investigates the impact of municipal solid waste compost (MSW-compost) application (0, 50, and 100 t/ha) on the growth, and on nutrient and trace elements content in lettuce and tomato plants grown in large, 40-L pots. Our findings showed inhibition of plants’ growth with increasing dose of MSW-compost, compared to plants receiving conventional fertilization. Growth inhibition was associated with a sharp decrease in soil NO₃–N content. On the other hand, a slower decrease in soil NO₃–N content occurred in non-planted pots amended with MSW-compost. These findings provide evidence that N immobilization and/or decreased N mineralization were responsible for inhibited growth by constraining N availability. With regard to the other macro-nutrients, K, P, Mg, Ca, and Fe, their contents in leaves of both crops were maintained at optimum levels. Higher zinc and copper content was measured in leaves of both crops but they did not exceed the optimum range for growth. No accumulation of trace elements was found in the fruits. The content of heavy metals in the tissues of plants grown in MSW-compost amended soil, remained at levels similar to those of the non-amended soil, suggesting that they do not pose a significant risk either for plant growth or public health. The findings of our study suggest that further emphasis should be given on the investigation of the factors regulating N mineralization and availability in order to avoid reductions in crop yield.

Crete is a Mediterranean, karst-dominated island, characterized by long drought periods. The Karst-SWAT model, combined with 11 climate change scenarios, was run to assess climate change impacts on the island under two set-ups, both using the auto-irrigation function of the model: (1) with water drawn from the shallow or deep aquifer, and (2) with irrigated water derived from an unlimited outside source. The first set-up provided insight into the fluctuation of future irrigation needs, and when compared to the second set-up, enabled quantification of the future water deficit. The Water Exploitation Index was used to describe the spatial variability of future water stress on Crete. A decrease in both surface and karstic spring flows is foreseen, especially after 2060 (24.2 and 16.5%, respectively). Simulated irrigation water demand and water deficit show continuous increase throughout the projection period (2020–2098).

Distributed environmental research infrastructures are important to support assessments of the effects of global change on landscapes, ecosystems and society. These infrastructures need to provide continuity to address long-term change, yet be flexible enough to respond to rapid societal and technological developments that modify research priorities. We used a horizon scanning exercise to identify and prioritize emerging research questions for the future development of ecosystem and socio-ecological research infrastructures in Europe. Twenty research questions covered topics related to (i) ecosystem structures and processes, (ii) the impacts of anthropogenic drivers on ecosystems, (iii) ecosystem services and socio-ecological systems and (iv), methods and research infrastructures. Several key priorities for the development of research infrastructures emerged. Addressing complex environmental issues requires the adoption of a whole-system approach, achieved through integration of biotic, abiotic and socio-economic measurements. Interoperability among different research infrastructures needs to be improved by developing standard measurements, harmonizing methods, and establishing capacities and tools for data integration, processing, storage and analysis. Future research infrastructures should support a range of methodological approaches including observation, experiments and modelling. They should also have flexibility to respond to new requirements, for example by adjusting the spatio-temporal design of measurements. When new methods are introduced, compatibility with important long-term data series must be ensured. Finally, indicators, tools, and transdisciplinary approaches to identify, quantify and value ecosystem services across spatial scales and domains need to be advanced.

Riverbank erosion affects river morphology and local habitat, and results in riparian land loss, property and infrastructure damage, and ultimately flood defence weakening. An important issue concerning riverbank erosion is the identification of the vulnerable areas in order to predict river changes and assist stream management/restoration. An approach to predict areas vulnerable to erosion is to quantify the erosion probability by identifying the underlying relations between riverbank erosion and geomorphological or hydrological variables that prevent or stimulate erosion. In the present work, a statistical methodology is proposed to predict the probability of the presence or absence of erosion in a river section. A physically based model determines the locations vulnerable to erosion by quantifying the potential eroded area. The derived results are used to determine validation locations for the evaluation of the statistical tool performance. The statistical tool is based on a series of independent local variables and employs the logistic regression methodology. It is developed in two forms, logistic regression and locally weighted logistic regression, which both deliver useful and accurate results. The second form, though, provides the most accurate results as it validates the presence or absence of erosion at all validation locations. The proposed tool is easy to use and accurate and can be applied to any region and river.