Erosion is a major threat to soil resources in Europe, and may impair their ability to deliver a range of ecosystem goods and services. This is reflected by the European Commission's Thematic Strategy for Soil Protection, which recommends an indicator-based approach for monitoring soil erosion. Defined baseline and threshold values are essential for the evaluation of soil monitoring data. Therefore, accurate spatial data on both soil loss and soil genesis are required, especially in the light of predicted changes in climate patterns, notably frequency, seasonal distribution and intensity of precipitation. Rates of soil loss are reported that have been measured, modelled or inferred for most types of soil erosion in a variety of landscapes, by studies across the spectrum of the Earth sciences. Natural rates of soil formation can be used as a basis for setting tolerable soil erosion rates, with soil formation consisting of mineral weathering as well as dust deposition. This paper reviews the concept of

The MALDI-TOF spectra of peptides from the sera of normal and myocardial infarction patients produced patterns that provided an accurate diagnostic of MI. In myocardial infarction, the spectral pattern originated from the cleavage of complement C3 alpha chain to release the C3f peptide and cleavage of fibrinogen to release peptide A. The fibrinogen peptide A and complement C3f peptide were in turn progressively truncated by aminopeptidases to produce two families of fragments that formed the characteristic spectral pattern of MI. Time course and inhibitor studies demonstrated that the peptide patterns in the serum reflect the balance of disease-specific-protease and aminopeptidase activity ex vivo.

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There is growing interest in models of marine ecosystems that deal with the effects of climate change through the higher trophic levels. Such end-to-end models combine physicochemical oceanographic descriptors and organisms ranging from microbes to higher-trophic-level (HTL) organisms, including humans, in a single modeling framework. The demand for such approaches arises from the need for quantitative tools for ecosystem-based management, particularly models that can deal with bottom-up and top-down controls that operate simultaneously and vary in time and space and that are capable of handling the multiple impacts expected under climate change. End-to-end models are now feasible because of improvements in the component submodels and the availability of sufficient computing power. We discuss nine issues related to the development of end-to-end models. These issues relate to formulation of the zooplankton submodel, melding of multiple temporal and spatial scales, acclimation and adaptation, behavioral movement, software and technology, model coupling, skill assessment, and interdisciplinary challenges. We urge restraint in using end-to-end models in a true forecasting mode until we know more about their performance. End-to-end models will challenge the available data and our ability to analyze and interpret complicated models that generate complex behavior. End-to-end modeling is in its early developmental stages and thus presents an opportunity to establish an open-access, community-based approach supported by a suite of true interdisciplinary efforts

Abstract. We describe Global Atmosphere 6.0 and Global Land 6.0: the latest science configurations of the Met Office Unified Model and JULES land surface model developed for use across all timescales. Global Atmosphere 6.0 includes the ENDGame dynamical core, which significantly increases mid-latitude variability improving a known model bias. Alongside developments of the model’s physical parametrisations, ENDGame also increases variability in the tropics, which leads to an improved representation of tropical cyclones and other tropical phenomena. Further developments of the atmospheric and land surface parametrisations improve other aspects of model performance, including the forecasting of surface weather phenomena. We also describe Global Atmosphere 6.1 and Global Land 6.1, which include a small number of long-standing differences from our main trunk configurations that we continue to require for operational global weather prediction. Since July 2014, GA6.1/GL6.1 has been used by the Met Office for operational global NWP, whilst GA6.0/GL6.0 was implemented in its remaining global prediction systems over the following year.