The response of terrestrial vegetation to a globally changing environment is central to predictions of future levels of atmospheric carbon dioxide. The role of tropical forests is critical because they are carbon-dense and highly productive. Inventory plots across Amazonia show that old-growth forests have increased in carbon storage over recent decades, but the response of one-third of the world's tropical forests in Africa is largely unknown owing to an absence of spatially extensive observation networks. Here we report data from a ten-country network of long-term monitoring plots in African tropical forests. We find that across 79 plots (163 ha) above-ground carbon storage in live trees increased by 0.63 Mg C ha(-1) yr(-1) between 1968 and 2007 (95% confidence interval (CI), 0.22-0.94; mean interval, 1987-96). Extrapolation to unmeasured forest components (live roots, small trees, necromass) and scaling to the continent implies a total increase in carbon storage in African tropical forest trees of 0.34 Pg C yr(-1) (CI, 0.15-0.43). These reported changes in carbon storage are similar to those reported for Amazonian forests per unit area, providing evidence that increasing carbon storage in old-growth forests is a pan-tropical phenomenon. Indeed, combining all standardized inventory data from this study and from tropical America and Asia together yields a comparable figure of 0.49 Mg C ha(-1) yr(-1) (n = 156; 562 ha; CI, 0.29-0.66; mean interval, 1987-97). This indicates a carbon sink of 1.3 Pg C yr(-1) (CI, 0.8-1.6) across all tropical forests during recent decades. Taxon-specific analyses of African inventory and other data suggest that widespread changes in resource availability, such as increasing atmospheric carbon dioxide concentrations, may be the cause of the increase in carbon stocks, as some theory and models predict.

Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical countries. Utilising this database, our objectives were: 1. to determine if H:D relationships differ by geographic region and forest type (wet to dry forests, including zones of tension where forest and savanna overlap). 2. to ascertain if the H:D relationship is modulated by climate and/or forest structural characteristics (e.g. standlevel basal area, A). 3. to develop H:D allometric equations and evaluate biases to reduce error in future local-to-global estimates of tropical forest biomass. Annual precipitation coefficient of variation (PV), dry season length (SD), and mean annual air temperature (TA) emerged as key drivers of variation in H:D relationships at the pantropical and region scales. Vegetation structure also played a role with trees in forests of a high A being, on average, taller at any given D. After the effects of environment and forest structure are taken into account, two main regional groups can be identified. Forests in Asia, Africa and the Guyana Shield all have, on average, similar H:D relationships, but with trees in the forests of much of the Amazon Basin and tropical Australia typically being shorter at any given D than their counterparts elsewhere. The region-environment-structure model with the lowest Akaike's information criterion and lowest deviation estimated stand-level H across all plots to within a median -2.7 to 0.9% of the true value. Some of the plot-to-plot variability in H:D relationships not accounted for by this model could be attributed to variations in soil physical conditions. Other things being equal, trees tend to be more slender in the absence of soil physical constraints, especially at smaller D. Pantropical and continental-level models provided less robust estimates of H, especially when the roles of climate and stand structure in modulating H:D allometry were not simultaneously taken into account.Additional co-authors: T. F. Domingues, M. Drescher, P. M. Fearnside, M. B. Franca, N. M. Fyllas, G. Lopez-Gonzalez, A. Hladik, N. Higuchi, M. O. Hunter, Y. Iida, K. A. Salim, A. R. Kassim, M. Keller, J. Kemp, D. A. King, J. C. Lovett, B. S. Marimon, B. H. Marimon-Junior, E. Lenza, A. R. Marshall, D. J. Metcalfe, E. T. A. Mitchard, E. F. Moran, B.W. Nelson, R. Nilus, E. M. Nogueira, M. Palace, S. Patino, K. S.-H. Peh, M. T. Raventos, J. M. Reitsma, G. Saiz, F. Schrodt, B. Sonke, H. E. Taedoumg, S. Tan, H. Woll, and J. Lloy

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Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (<i>H</i>). We estimate the effect of incorporating <i>H</i> on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 <i>H</i> and diameter measurements and harvested trees from 20 sites to answer the following questions: <br><br> 1. What is the best <i>H</i>-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass? <br><br> 2. To what extent does including <i>H</i> estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots? <br><br> 3. What effect does accounting for <i>H</i> have on plot- and continental-scale forest biomass estimates? <br><br> The mean relative error in biomass estimates of destructively harvested trees when including <i>H</i> (mean 0.06), was half that when excluding <i>H</i> (mean 0.13). Power- and Weibull-<i>H</i> models provided the greatest reduction in uncertainty, with regional Weibull-<i>H</i> models preferred because they reduce uncertainty in smaller-diameter classes (&le;40 cm <i>D</i>) that store about one-third of biomass per hectare in most forests. Propagating the relationships from destructively harvested tree biomass to each of the 327 plots from across the tropics shows that including <i>H</i> reduces errors from 41.8 Mg ha⁻¹ (range 6.6 to 112.4) to 8.0 Mg ha⁻¹ (−2.5 to 23.0). For all plots, aboveground live biomass was −52.2 Mg ha⁻¹ (−82.0 to −20.3 bootstrapped 95% CI), or 13%, lower when including <i>H</i> estimates, with the greatest relative reductions in estimated biomass in forests of the Brazilian Shield, east Africa, and Australia, and relatively little change in the Guiana Shield, central Africa and southeast Asia. Appreciably different stand structure was observed among regions across the tropical continents, with some storing significantly more biomass in small diameter stems, which affects selection of the best height models to reduce uncertainty and biomass reductions due to <i>H</i>. After accounting for variation in <i>H</i>, total biomass per hectare is greatest in Australia, the Guiana Shield, Asia, central and east Africa, and lowest in east-central Amazonia, W. Africa, W. Amazonia, and the Brazilian Shield (descending order). Thus, if tropical forests span 1668 million km² and store 285 Pg C (estimate including <i>H</i>), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if <i>H</i> is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height ...

Aim Large trees (d.b.h.≥70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location Pan-tropical. Methods Aboveground biomass (AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights (AICc-wi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean)±105.0 (SD) Mg ha -1 versus Palaeotropical forests (Africa 418.3±91.8 Mg ha-1; Asia 393.3±109.3 Mg ha-1). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees. (Résumé d'auteur