Consistent patterns of common species across tropical tree communities

Trees structure the Earth’s most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1,2,3,4,5,6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth’s 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world’s most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees

Structural analysis and forecasts of commodity imports using cross-section relationships

The purpose of this paper is to propose alternative specifications which can be used for predicting imports by commodities for a large number of countries. Both "variety" and "scale" hypothesis have been made use of in suggesting simple cross-section relationships which can be easily used for predicting imports by commodities for any country of the world. Indeed, since detailed country characteristics are not taken into consideration in per capita income and population, it is likely that consistent under or overpredictions may result for a country when the estimated relationship is used. The extent of under or overprediction is reduced by using the variable elasticity formulation of the import demand function. Our estimates of cross-section relationships show remarkable stability in structural coefficients for the period 1967-1973 on the two-digit S.I.T.C. data. A set of eight different relationships is estimated and using 1970 cross-section relationships forecasts for 1973 and 1980 are given. Forecasts of imports of 45 commodities for 37 countries were derived and compared with the corresponding actual 1973 figures. The root mean square error predictive criterion suggests that per capita income and population in a constant elasticity form performs reasonably well