10.1007/s10750-012-1182-1Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. form, nor will it be during the first three months after its submission to Hydrobiologia."Corresponding author: Erik Jeppesen (ej@dmu.dk)We dedicate this paper to the late Prof. Jürgen Benndorf, a true pioneer and mentor in lake and reservoir management oriented research, who inspired a number of us to initiate longterm comprehensive experimental ecological studies on lakes and reservoirs. AbstractFish play a key role in the trophic dynamics of lakes. With climate warming, complex changes in fish assemblage structure may be expected owing to direct effects of temperature and indirect effects operating through eutrophication, water level changes, stratification and salinisation. We reviewed published and new long-term (10-100 years) fish data series from 24 European lakes (area: 0.04-5648 km 2 ; mean depth: 1-177m; a north-south gradient from 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 4 Sweden to Spain). Along with an annual temperature increase of about 0.15-0.3 °C per decade profound changes have occurred in either fish assemblage composition, body size and/or age structure during recent decades and a shift towards higher dominance of eurythermal species.These shifts have occurred despite a reduction in nutrient loading in many of the lakes that should have benefited the larger-sized individuals and the fish species typically inhabiting cold-water, low-nutrient lakes. The cold-stenothermic Arctic charr has been particularly affected and its abundance has decreased in the majority of the lakes where its presence was recorded. The harvest of cool-stenothermal trout has decreased substantially in two southern lakes. Vendace, whitefish and smelt show a different response depending on lake depth and latitude. Perch has apparently been stimulated in the north, with stronger year classes in warm years, but its abundance has declined in the southern Lake Maggiore, Italy. Where introduced, roach seems to take advantage of the higher temperature after years of low population densities. Eurythermal species such as common bream, pike-perch and/or shad are apparently on the increase in several of the lakes. The response of fish to the warming has been surprisingly strong and fast in recent decades, making them ideal sentinels for detecting and documenting climate-induced modifications of freshwater ecosystems.

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16 2 The influence of biogas flow rate (0, 0.3, 0.6 and 1.2 m 3 m -2 h -1 ) on the elemental and 17 macromolecular composition of the algal-bacterial biomass produced from biogas upgrading in a 18 180 L photobioreactor interconnected to a 2.5 L external bubbled absorption column was 19 investigated using diluted anaerobically digested vinasse as cultivation medium. The influence of 20 the external liquid recirculation/biogas ratio (0.5 < L/G < 67) on the removal of CO2 and H2S, 21and on the concentrations of O2 and N2 in the upgraded biogas was also evaluated. A L/G ratio of 22 10 was considered optimum to support CO2 and H2S removals of 80% and 100%, respectively, at 23 all biogas flow rates tested. Biomass productivity increased at increasing biogas flow rate, with a 24 maximum of 12±1 g m -2 d -1 at 1.2 m 3 m -2 h -1 , while the C, N and P biomass content remained 25 constant at 49±2%, 9±0% and 1±0%, respectively, over the 175 days of experimentation.

Diatoms, a kind of algae microorganisms with several species, are quite useful for water quality determination, one of the hottest topics in applied biology nowadays. At the same time, deep learning and convolutional neural networks (CNN) are becoming an extensively used technique for image classification in a variety of problems. This paper approaches diatom classification with this technique, in order to demonstrate whether it is suitable for solving the classification problem. An extensive dataset was specifically collected (80 types, 100 samples/type) for this study. The dataset covers different illumination conditions and it was computationally augmented to more than 160,000 samples. After that, CNNs were applied over datasets pre-processed with different image processing techniques. An overall accuracy of 99% is obtained for the 80-class problem and different kinds of images (brightfield, normalized). Results were compared to previous presented classification techniques with different number of samples. As far as the authors know, this is the first time that CNNs are applied to diatom classification.

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