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Climate change is expected to increase temperature and decrease summer precipitation in Central Europe. Little is known about how warming and drought will affect phenological patterns of oaks, which are considered to possess excellent adaptability to these climatic changes. Here, we investigated bud burst and intra-annual shoot growth of Quercus robur, Q. petraea and Q. pubescens grown on two different forest soils and exposed to air warming and drought. Phenological development was assessed over the course of three growing seasons. Warming advanced bud burst by 1–3 days °C−1 and led to an earlier start of intra-annual shoot growth. Despite this phenological shift, total time span of annual growth and shoot biomass were not affected. Drought changed the frequency and intensity of intra-annual shoot growth and advanced bud burst in the subsequent spring of a severe summer drought by 1–2 days. After re-wetting, shoot growth recovered within a few days, demonstrating the superior drought tolerance of this tree genus. Our findings show that phenological patterns of oaks are modified by warming and drought but also suggest that ontogenetic factors and/or limitations of water and nutrients counteract warming effects on the biomass and the entire span of annual shoot growth. PLoS ONE, 9 (2) ISSN:1932-6203

The charged-particle production ratios $\bar{p}/p$, $K^-/K^+$, $��^-/��^+$, $(p + \bar{p})/(��^+ + ��^-)$, $(K^+ + K^-)/(��^+ + ��^-)$ and $(p + \bar{p})/(K^+ + K^-)$ are measured with the LHCb detector using $0.3 {\rm nb^{-1}}$ of $pp$ collisions delivered by the LHC at $\sqrt{s} = 0.9$ TeV and $1.8 {\rm nb^{-1}}$ at $\sqrt{s} = 7$ TeV. The measurements are performed as a function of transverse momentum $p_{\rm T}$ and pseudorapidity $��$. The production ratios are compared to the predictions of several Monte Carlo generator settings, none of which are able to describe adequately all observables. The ratio $\bar{p}/p$ is also considered as a function of rapidity loss, $��y \equiv y_{\rm beam} - y$, and is used to constrain models of baryon transport. Incorrect entries in Table 2 corrected. No consequences for rest of paper

Even with state of the art forecasting methods, the short-term generation of wind farms cannot be predicted with a high degree of accuracy. In a market situation, these forecasting errors lead to commercial risk through imbalance costs when advance contracting. This situation is one that needs to be addressed due to the steady increase in the amount of grid connected wind generation, combined with the rise of deregulated, market orientated electricity systems. In the presence of imbalance prices and uncertain generation, a method is required to determine the optimum level of contract energy to be sold on the advance markets. Such a method is presented here using Markov probabilities for a wind farm and demonstrates substantial reductions in the imbalance costs. The effect of market closure delays and forecasting window lengths are also shown.