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Forest structure and dynamics vary across the Amazon Basin in an east-west gradient coincident with variations in soil fertility and geology. This has resulted in the hypothesis that soil fertility may play an important role in explaining Basin-wide variations in forest biomass, growth and stem turnover rates. Soil samples were collected in a total of 59 different forest plots across the Amazon Basin and analysed for exchangeable cations, carbon, nitrogen and pH, with several phosphorus fractions of likely different plant availability also quantified. Physical properties were additionally examined and an index of soil physical quality developed. Bivariate relationships of soil and climatic properties with above-ground wood productivity, stand-level tree turnover rates, above-ground wood biomass and wood density were first examined with multivariate regression models then applied. Both forms of analysis were undertaken with and without considerations regarding the underlying spatial structure of the dataset. Despite the presence of autocorrelated spatial structures complicating many analyses, forest structure and dynamics were found to be strongly and quantitatively related to edaphic as well as climatic conditions. Basin-wide differences in stand-level turnover rates are mostly influenced by soil physical properties with variations in rates of coarse wood production mostly related to soil phosphorus status. Total soil P was a better predictor of wood production rates than any of the fractionated organic- or inorganic-P pools. This suggests that it is not only the immediately available P forms, but probably the entire soil phosphorus pool that is interacting with forest growth on longer timescales. A role for soil potassium in modulating Amazon forest dynamics through its effects on stand-level wood density was also detected. Taking this into account, otherwise enigmatic variations in stand-level biomass across the Basin were then accounted for through the interactin

Many serious ecosystem consequences of climate change will take decades or even centuries to emerge. Long-term ecological responses to global change are strongly regulated by slow processes, such as changes in species composition, carbon dynamics in soil and by long-lived plants, and accumulation of nutrient capitals. Understanding and predicting these processes require experiments on decadal time scales. But decadal experiments by themselves may not be adequate because many of the slow processes have characteristic time scales much longer than experiments can be maintained. This article promotes a coordinated approach that combines long-term, large-scale global change experiments with process studies and modeling. Long-term global change manipulative experiments, especially in high-priority ecosystems such as tropical forests and high-latitude regions, are essential to maximize information gain concerning future states of the earth system. The long-term experiments should be conducted in tandem with complementary process studies, such as those using model ecosystems, species replacements, laboratory incubations, isotope tracers, and greenhouse facilities. Models are essential to assimilate data from long-term experiments and process studies together with information from long-term observations, surveys, and space-for-time studies along environmental and biological gradients. Future research programs with coordinated long-term experiments, process studies, and modeling have the potential to be the most effective strategy to gain the best information on long-term ecosystem dynamics in response to global change.