Open Access

In the past few years, studies have been carried out to record and analyse the consumer behaviour of manual dishwashing. Manual dishwashing in households is performed in many ways that influence the use of resources. Furthermore, knowledge has been gained on the basis of experiments on how to optimize the use of resources in manual dishwashing. Optimization here means achieving the best possible cleaning performance with a minimum input of resources. This experimental knowledge, combined with the experience of everyday life, was transferred into Best Practice Tips. The aim of this study is to verify whether it is possible to save resources while applying these Best Practice Tips in comparison with the consumers' previous behaviour. In a laboratory study, 53 consumers from Europe (23 Germans, 30 other Europeans) were asked to apply the Best Practice Tips while washing up 12 place settings of dishes. The data gained were compared with that of previous studies recording consumers' everyday behaviour while washing up the same amount of dishes. The sample consisted of 113 European consumers and the sample of the second study consisted of 60 Europeans. On average, the 53 test participants applying the Best Practice Tips used around 60% less water, 70% less energy and 30% less detergent compared with the average everyday behaviour the other subjects used. Additionally, they achieved a slightly better cleaning result. An evaluation questionnaire showed that the Best Practice Tips were, in general, highly accepted; however, some concerns were given about their exact application in everyday life. Because of the wide variation of washing-up habits and resource consumption among individuals, the confidence intervals of the studies are rather large. The results should therefore be seen as tendencies on how resource savings are possible when people are trained how to optimize resources in manual dishwashing. Nevertheless, this study should be the basis for further ones in which the learning is verified in everyday life and over a longer period of time.

The conservation of freshwater ecosystems has lagged behind that of marine and terrestrial ecosystems and often requires the integration of large-scale approaches and transboundary considerations. This study aims to set the foundations of a spatial conservation strategy by identifying the most important catchments for the conservation of freshwater biodiversity in Europe. Using data on 1296 species of fish, mollusc, odonate and aquatic plant, and the key biodiversity area criteria (species Red List status, range restriction and uniqueness of species assemblages), we identified a network of Critical Catchments for the conservation of freshwater biodiversity. Applying spatial prioritisation, we show how the prioritised network differs from the ideal case of protecting all Critical Catchments and how it changes when protected areas are included, and we also identify gaps between the prioritised network and existing protected areas. Critical Catchments (n = 8423) covered 45% of the area of Europe, with 766 qualifying (‘trigger’) species located primarily in southern Europe. The prioritised network, limited to 17% of the area of Europe, comprised 3492 catchments mostly in southern and eastern Europe and species targets were met for at least 96% of the trigger species. We found the majority of Critical Catchments to be inadequately covered by protected areas. However, our prioritised network presents a possible solution to augment protected areas to meet policy targets while also achieving good species coverage. Policy implications. While Critical Catchments cover almost half of Europe, priority catchments are mostly in southern and eastern Europe where the current level of protection is not sufficient. This study presents a foundation for a Europe-wide systematic conservation plan to ensure the persistence of freshwater biodiversity. Our study provides a powerful new tool for optimising investment on the conservation of freshwater biodiversity and for meeting targets set forth in international biodiversity policies, conventions and strategies.

The distribution of a species along a thermal gradient is commonly approximated by a unimodal response curve, with a characteristic single optimum near the tempera‐ture where a species is most likely to be found, and a decreasing probability of occur‐rence away from the optimum. We aimed at identifying thermal response curves (TRCs) of European freshwater species and evaluating the potential impact of climate warming across species, taxonomic groups, and latitude. We first applied generalized additive models using catchment‐scale global data on distribution ranges of 577 freshwater species native to Europe and four different temperature variables (the current annual mean air/water temperature and the maximum air/water temperature of the warmest month) to describe species TRCs. We then classified TRCs into one of eight curve types and identified spatial patterns in thermal responses. Finally, we in‐tegrated empirical TRCs and the projected geographic distribution of climate warm‐ing to evaluate the effect of rising temperatures on species’ distributions. For the different temperature variables, 390–463 of 577 species (67.6%–80.2%) were char‐acterized by a unimodal TRC. The number of species with a unimodal TRC decreased from central toward northern and southern Europe. Warming tolerance (WT = maxi‐mum temperature of occurrence—preferred temperature) was higher at higher lati‐tudes. Preferred temperature of many species is already exceeded. Rising temperatures will affect most Mediterranean species. We demonstrated that fresh‐water species’ occurrence probabilities are most frequently unimodal. The impact of the global climate warming on species distributions is species and latitude depend‐ent. Among the studied taxonomic groups, rising temperatures will be most detri‐mental to fish. Our findings support the efforts of catchment‐based freshwater management and conservation in the face of global warming.

Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a–nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic–eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.