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We consider a set of data from 80 stations in the Venezuelan state of Gua  rico consisting of accumulated monthly rainfall in a time span of 16 years. The problem of modelling rainfall accumulated over ®xed periods of time and recorded at meteorological stations at different sites is studied by using a model based on the assumption that the data follow a truncated and transformed multivariate normal distribution. The spatial correlation is modelled by using an exponentially decreasing correlation function and an interpolating surface for the means. Missing data and dry periods are handled within a Markov chain Monte Carlo framework using latent variables. We estimate the amount of rainfall as well as the probability of a dry period by using the predictive density of the data. We considered a model based on a full second-degree polynomial over the spatial co-ordinates as well as the ®rst two Fourier harmonics to describe the variability during the year. Predictive inferences on the data show very realistic results, capturing the typical rainfall variability in time and space for that region. Important extensions of the model are also discussed.

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Irradiance and soil nitrogen effects on growth, net photosynthesis and radiation use efficiency (RUE) of Brachiaria decumbens were investigated in fertilized and non-fertilized stands. Three levels of photosynthetic photon flux (PPF: S0 = 100%, S1 = 50% and S2 = 30%) and two N supplies, with (N+) and without (NÀ), were used. Forage biomass and nutrient accumulation, specific leaf area (SLA), leaf area index (LAI), fractional intercepted photosynthetic photon flux (fPPF), leaf photosynthetic response to light and efficiency of radiation use at leaf (A/Q) and canopy (RUE) levels were measured. Shade effects were mostly independent of soil N. Final yield was decreased by 34% (S1) and 57% (S2). Shade increased SLA (25-46%), so maximum LAI (2Á4-3Á3) was similar among light regimes. In NÀ stands, reductions in leaf biomass (14%), SLA (17%) and LAI (27%) were recorded, although forage yield was similar between soil N conditions. Under shade, peaks of A were comparable to those at full light, so A/Q was higher around midday. Derived parameters of the A-PPF curves were similar between S0 and S2. A maximum fPPF = 0Á8 (S0N+, S1N+) was recorded at LAI = 3-4. Under limited sunlight, relatively high RUE (1Á6-2Á8 g MJ À1 ) were observed over both soil N conditions. We concluded that B. decumbens had a high plasticity to shade, thus explaining its success under silvopastoral systems.

Extreme weather continues to preoccupy society as a formidable public safety concern bearing huge economic costs. While attention has focused on global climate change and how it could intensify key elements of the water cycle such as precipitation and river discharge, it is the conjunction of geophysical and socioeconomic forces that shapes human sensitivity and risks to weather extremes. We demonstrate here the use of high-resolution geophysical and population datasets together with documentary reports of rainfall-induced damage across South America over a multi-decadal, retrospective time domain (1960–2000). We define and map extreme precipitation hazard , exposure , affected populations, vulnerability and risk , and use these variables to analyse the impact of floods as a water security issue. Geospatial experiments uncover major sources of risk from natural climate variability and population growth, with change in climate extremes bearing a minor role. While rural populations display greatest relative sensitivity to extreme rainfall, urban settings show the highest rates of increasing risk. In the coming decades, rapid urbanization will make South American cities the focal point of future climate threats but also an opportunity for reducing vulnerability, protecting lives and sustaining economic development through both traditional and ecosystem-based disaster risk management systems.