This study assesses crop residues in the EU from major crops using empirical models to predict crop residues from yield statistics; furthermore it analyses the inter-annual variability of those estimates over the period 1998-2015, identifying its main drivers across Europe. The models were constructed based on an exhaustive collection of experimental data from scientific papers for the crops: wheat, barley, rye, oats, triticale, rice, maize, sorghum, rapeseed, sunflower, soybean, potato and sugarbeet. We discuss the assumptions on the relationship between yield and the harvest index, adopted by previous studies, to interpret the experimental data, quantify the uncertainties of these models, and establish the premises to implement them at regional scale -i.e., NUTS level 3-within the EU. To cope this, we created a consolidated sub-national statistical data along with an algorithm able to aggregate (figures are provided at country level) and disaggregate (production at 25 km grid is provided as supplementary material) estimates. The total lignocellulosic biomass production in the EU28 over the review period, according to our models, is 419 Mt, from which wheat is the major contributor (155 Mt). Our results show that maize and rapeseed are the two crops with the highest residue yield, respectively 8.9 and 8.6 t ha-1. The spatial analysis revealed that these three crops, which, according to our results, are feedstocks highly suitable a priori for second generation biofuels in the EU and are unevenly distributed across Europe. Weather fluctuation was identified as the major driver in residue production from cereals, while, in the case of starch crops and oilseeds -which are predominant in northern Europe -corresponded to the marked production trend likely influenced by the agricultural policies and agro-management over the review period. Our results, among others, could help to understand and quantify the ecological boundaries of the bioeconomy from agriculture. K E Y W O R D Sadvanced biofuels, cereals, downscaling, harvest index, oilseeds, production trends, spatially explicit assessment, statistics, sugar crops, weather impacts This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

ABSTRACT1. Boat surveys aimed at studying sperm whales in the Tyrrhenian Sea were conducted between 2002 and 2011. During 768 daily surveys, a total effort of 32 602 km was achieved within an area of 8800 km 2 resulting in 92 encounters with 229 sperm whale individuals. 2. Average encounter rates of sperm whales was 0.5 groups per 100 km 2 , with a higher concentration in the vicinity of the submarine canyon of Cuma, confirming the importance for the species of this small hotspot in the Mediterranean Sea. 3. Encounter rates increased with increasing distance from the coast. It is possible that the intense boat traffic and anthropogenic disturbance in the area may be moving animals away from the coast leading to habitat loss.4. The species-habitat relationship documented in this study has implications for conservation.

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near-and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

1. This study presents data on a local population of short-beaked common dolphin monitored in the waters off Ischia Island (Gulf of Naples, Italy) over a 16-year period (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). We examine dolphin occurrence and distribution and perform photoidentification analysis.2. The data presented support the hypothesis that the waters around Ischia Island represent a feeding area, as well as a calving and an important nursery area for this local population, providing favourable conditions in which to give birth and raise calves.3. The levelling-off of the photoidentification curves together with the continuous decline of the encounter rate lead us to believe that the area has been a hotspot for a local population (mainly resident) for years and that now this population is dying (has died) or is moving (has moved) to other locations. 4. Several expanding human activities at sea have the potential to impact on the common dolphin in the study area, the most significant possibly being habitat disturbance and degradation (including traffic and noise pollution) and overexploitation of food resources by the fishery.5. The data presented in this study offer a strong argument for explicit and urgent population-specific conservation and management strategies to be developed and applied locally for common dolphins, considering that they rely on the region for important biological processes.

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