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Long-term surveys of entire communities of species are needed to measure fluctuations in natural populations and elucidate the mechanisms driving population dynamics and community assembly. We analysed changes in abundance of over 4000 tree species in 12 forests across the world over periods of 6-28 years. Abundance fluctuations in all forests are large and consistent with population dynamics models in which temporal environmental variance plays a central role. At some sites we identify clear environmental drivers, such as fire and drought, that could underlie these patterns, but at other sites there is a need for further research to identify drivers. In addition, cross-site comparisons showed that abundance fluctuations were smaller at species-rich sites, consistent with the idea that stable environmental conditions promote higher diversity. Much community ecology theory emphasises demographic variance and niche stabilisation; we encourage the development of theory in which temporal environmental variance plays a central role.

Species spatial turnover, or β-diversity, induces a decay of community similarity with geographic distance known as the distance–decay relationship. Although this relationship is central to biodiversity and biogeography, its theoretical underpinnings remain poorly understood. Here, we develop a general framework to describe how the distance–decay relationship is influenced by population aggregation and the landscape-scale species-abundance distribution. We utilize this general framework and data from three tropical forests to show that rare species have a weak influence on distance–decay curves, and that overall similarity and rates of decay are primarily influenced by species abundances and population aggregation respectively. We illustrate the utility of the framework by deriving an exact analytical expression of the distance–decay relationship when population aggregation is characterized by the Poisson Cluster Process. Our study provides a foundation for understanding the distance–decay relationship, and for predicting and testing patterns of beta-diversity under competing theories in ecology. Ecology Letters (2008) 11: 904–917

Tropical forests vary substantially in the densities of trees of different sizes and thus in above-ground biomass and carbon stores. However, these tree size distributions show fundamental similarities suggestive of underlying general principles. The theory of metabolic ecology predicts that tree abundances will scale as the -2 power of diameter. Demographic equilibrium theory explains tree abundances in terms of the scaling of growth and mortality. We use demographic equilibrium theory to derive analytic predictions for tree size distributions corresponding to different growth and mortality functions. We test both sets of predictions using data from 14 large-scale tropical forest plots encompassing censuses of 473 ha and > 2 million trees. The data are uniformly inconsistent with the predictions of metabolic ecology. In most forests, size distributions are much closer to the predictions of demographic equilibrium, and thus, intersite variation in size distributions is explained partly by intersite variation in growth and mortality.

The theory of metabolic ecology predicts specific relationships among tree stem diameter, biomass, height, growth and mortality. As demographic rates are important to estimates of carbon fluxes in forests, this theory might offer important insights into the global carbon budget, and deserves careful assessment. We assembled data from 10 oldgrowth tropical forests encompassing censuses of 367 ha and > 1.7 million trees to test the theory’s predictions. We also developed a set of alternative predictions that retained some assumptions of metabolic ecology while also considering how availability of a key limiting resource, light, changes with tree size. Our results show that there are no universal scaling relationships of growth or mortality with size among trees in tropical forests. Observed patterns were consistent with our alternative model in the one site where we had the data necessary to evaluate it, and were inconsistent with the predictions of metabolic ecology in all forests.