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An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to highquality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochrono-logical requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful

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This paper analyses the behavior of extreme events of surface precipitation and temperature inside the Pacific and Caribbean Catchment Basins in Colombia using several datasets such as observations, reconstructed data, NCEP-NCAR and ERA-40 reanalyses and data from the regional model REMO. We use an extreme value method that selects the time series excesses over a nonstationary threshold and adjusts them to a generalized Pareto distribution. The goodness of fit is evaluated through a test that includes the Cramer-von Mises, Kolmogorov-Smirnov and Anderson-Darling statistics and the p values generated by parametric bootstrap resampling. The test not only evaluates the goodness of fit but also the threshold choice. The parameters are presented in maps that allow recognition of the features of the extreme behaviour inside the catchment basins, and differences and similarities between them. Maps of return periods for the maximum extreme events are also presented. A strong influence of the El Niño-Southern oscillation on the extreme events of both temperature and precipitation is found in the two catchment basins. © 2012 Springer-Verlag

Abstract. Many natural and social phenomena depend on river flow regimes that are being altered by global change. Understanding the mechanisms behind such alterations is crucial for predicting river flow regimes in a changing environment. Here we introduce a novel physical interpretation of the scaling properties of river flows and show that it leads to a parsimonious characterization of the flow regime of any river basin. This allows river basins to be classified as regulated or unregulated, and to identify a critical threshold between these states. We applied this framework to the Amazon river basin and found both states among its main tributaries. Then we introduce the “forest reservoir” hypothesis to describe the natural capacity of river basins to regulate river flows through land–atmosphere interactions (mainly precipitation recycling) that depend strongly on the presence of forests. A critical implication is that forest loss can force the Amazonian river basins from regulated to unregulated states. Our results provide theoretical and applied foundations for predicting hydrological impacts of global change, including the detection of early-warning signals for critical transitions in river basins.