Eurídice N. Honorio Coronado, Kyle G. Dexter, R. Toby Pennington, Simon L. Lewis, 7 Miguel N. Alexiades, Esteban Alvarez, Atila Alves de Oliveira, Iêda L. Amaral, 8 Alejandro Araujo-Murakami, Eric J.M.M. Arets, Gerardo A. Aymard, Christopher 9 Baraloto, Damien Bonal, Roel Brienen, Carlos Cerón, Jérôme Chave, Fernando 10 Cornejo Valverde, Anthony Di Fiore, William Farfan Rios, Ted R. Feldpausch, Niro 11 Higuchi, Isau Huamantupa-Chuquimaco, Susan G. Laurance, William F. Laurance, 12 Beatriz S. Marimon, Ben Hur Marimon-Junior, Abel Monteagudo Mendoza, David 13 Neill, Walter Palacios Cuenca, Maria Cristina Peñuela Mora, Nigel C.A. Pitman, 14 Adriana Prieto, Carlos A. Quesada, Hirma Ramirez Angulo, Agustín Rudas, Ademir 15 R. Ruschel, Norma Salinas Revilla, Rafael P. Salomão, Ana Segalin de Andrade, 16 Miles R. Silman, Wilson Spironello, Hans ter Steege, John Terborgh, Marisol Toledo, 17 Luis Valenzuela Gamarra, Ima C.G. Vieira, Emilio Vilanova Torre, Vincent Vos, and 18 Oliver L. Phillips 19

Aboveground tropical tree biomass and carbon storage estimates commonly ignore tree height (H). We estimate the effect of incorporating H on tropics-wide forest biomass estimates in 327 plots across four continents using 42 656 H and diameter measurements and harvested trees from 20 sites to answer the following questions:1. What is the best H-model form and geographic unit to include in biomass models to minimise site-level uncertainty in estimates of destructive biomass?2. To what extent does including H estimates derived in (1) reduce uncertainty in biomass estimates across all 327 plots?3. What effect does accounting for H have on plot- and continental-scale forest biomass estimates?The mean relative error in biomass estimates of destructively harvested trees when including H (mean 0.06), was half that when excluding H (mean 0.13). Power- and Weibull-H models provided the greatest reduction in uncertainty, with regional Weibull-H models preferred because they reduce uncertainty in smaller-diameter classes (≤40 cm D) 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 H 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 H 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 H. After accounting for variation in H, 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 H), then applying our regional relationships implies that carbon storage is overestimated by 35 Pg C (31–39 bootstrapped 95% CI) if H is ignored, assuming that the sampled plots are an unbiased statistical representation of all tropical forest in terms of biomass and height factors. Our results show that tree H is an important allometric factor that needs to be included in future forest biomass estimates to reduce error in estimates of tropical carbon stocks and emissions due to deforestation.

Abstract. The production of aboveground soft tissue represents an important share of total net primary production in tropical rain forests. Here we draw from a large number of published and unpublished datasets (n=81 sites) to assess the determinants of litterfall variation across South American tropical forests. We show that across old-growth tropical rainforests, litterfall averages 8.61±1.91 Mg ha−1 yr−1 (mean ± standard deviation, in dry mass units). Secondary forests have a lower annual litterfall than old-growth tropical forests with a mean of 8.01±3.41 Mg ha−1 yr−1. Annual litterfall shows no significant variation with total annual rainfall, either globally or within forest types. It does not vary consistently with soil type, except in the poorest soils (white sand soils), where litterfall is significantly lower than in other soil types (5.42±1.91 Mg ha−1 yr−1). We also study the determinants of litterfall seasonality, and find that it does not depend on annual rainfall or on soil type. However, litterfall seasonality is significantly positively correlated with rainfall seasonality. Finally, we assess how much carbon is stored in reproductive organs relative to photosynthetic organs. Mean leaf fall is 5.74±1.83 Mg ha−1 yr−1 (71% of total litterfall). Mean allocation into reproductive organs is 0.69±0.40 Mg ha−1 yr−1 (9% of total litterfall). The investment into reproductive organs divided by leaf litterfall increases with soil fertility, suggesting that on poor soils, the allocation to photosynthetic organs is prioritized over that to reproduction. Finally, we discuss the ecological and biogeochemical implications of these results.

Positive aboveground biomass trends have been reported from old‐growth forests across the Amazon basin and hypothesized to reflect a large‐scale response to exterior forcing. The result could, however, be an artefact due to a sampling bias induced by the nature of forest growth dynamics. Here, we characterize statistically the disturbance process in Amazon old‐growth forests as recorded in 135 forest plots of the RAINFOR network up to 2006, and other independent research programmes, and explore the consequences of sampling artefacts using a data‐based stochastic simulator. Over the observed range of annual aboveground biomass losses, standard statistical tests show that the distribution of biomass losses through mortality follow an exponential or near‐identical Weibull probability distribution and not a power law as assumed by others. The simulator was parameterized using both an exponential disturbance probability distribution as well as a mixed exponential–power law distribution to account for potential large‐scale blowdown events. In both cases, sampling biases turn out to be too small to explain the gains detected by the extended RAINFOR plot network. This result lends further support to the notion that currently observed biomass gains for intact forests across the Amazon are actually occurring over large scales at the current time, presumably as a response to climate change.

Xylem density is a physical property of wood that varies between individuals, species and environments. It reflects the physiological strategies of trees that lead to growth, survival and reproduction. Measurements of branch xylem density, ρx, were made for 1653 trees representing 598 species, sampled from 87 sites across the Amazon basin. Measured values ranged from 218 kg m−3 for a Cordia sagotii (Boraginaceae) from Mountagne de Tortue, French Guiana to 1130 kg m−3 for an Aiouea sp. (Lauraceae) from Caxiuana, Central Pará, Brazil. Analysis of variance showed significant differences in average ρx across regions and sampled plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that species identity (family, genera and species) accounted for 33% with environment (geographic location and plot) accounting for an additional 26%; the remaining "residual" variance accounted for 41% of the total variance. Variations in plot means, were, however, not only accountable by differences in species composition because xylem density of the most widely distributed species in our dataset varied systematically from plot to plot. Thus, as well as having a genetic component, branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing in a predictable manner. Within the analysed taxa, exceptions to this general rule seem to be pioneer species belonging for example to the Urticaceae whose branch xylem density is more constrained than most species sampled in this study. These patterns of variation of branch xylem density across Amazonia suggest a large functional diversity amongst Amazonian trees which is not well understood.

The net primary productivity (NPP) of tropical forests is one of the most important and least quantified components of the global carbon cycle. Most relevant studies have focused particularly on the quantification of the above-ground coarse wood productivity, and little is known about the carbon fluxes involved in other elements of the NPP, the partitioning of total NPP between its above- and below-ground components and the main environmental drivers of these patterns. In this study we quantify the above- and below-ground NPP of ten Amazonian forests to address two questions: (1) How do Amazonian forests allocate productivity among its above- and below-ground components? (2) How do soil and leaf nutrient status and soil texture affect the productivity of Amazonian forests? Using a standardized methodology to measure the major elements of productivity, we show that NPP varies between 9.3±1.3 Mg C ha−1 yr−1 (mean±standard error), at a white sand plot, and 17.0±1.4 Mg C ha−1 yr−1 at a very fertile Terra Preta site, with an overall average of 12.8±0.9 Mg C ha−1 yr−1. The studied forests allocate on average 64±3% and 36±3% of the total NPP to the above- and below-ground components, respectively. The ratio of above-ground and below-ground NPP is almost invariant with total NPP. Litterfall and fine root production both increase with total NPP, while stem production shows no overall trend. Total NPP tends to increase with soil phosphorus and leaf nitrogen status. However, allocation of NPP to below-ground shows no relationship to soil fertility, but appears to decrease with the increase of soil clay content.

Xylem density is a physical property of wood that varies between individuals, species and environments. It reflects the physiological strategies of trees that lead to growth, survival and reproduction. Measurements of branch xylem density,ρx , were made for 1653 trees representing 598 species, sampled from 87 sites across the Amazon basin. Measured values ranged from 218 kg m −3 for aCordia sagotii (Boraginaceae) from Mountagne de Tortue, French Guiana to 1130 kg m−3 for anAioueasp. (Lauraceae) from Caxiuana, Central Par ́ , Brazil. Analysis of variance showed significant differences in average ρx across regions and sampled plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that species identity (family, genera and species) accounted for 33% with environment (geographic location and plot) accounting for an additional 26%; the remaining “residual” variance accounted for 41% of the total variance. Variations in plot means, were, however, not only accountable by differences in species composition because xylem density of the most widely distributed species in our dataset varied systematically from plot to plot. Thus, as well as having a genetic component, branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing in a predictable manner. Within the analysed taxa, exceptions to this general rule seem to be pioneer species belonging for example to the Urticaceaewhose branch xylem density is more constrained than most species sampled in this study. These patterns of variation of branch xylem density across Amazonia suggest a large functional diversity amongst Amazonian trees which is not well understood.

Measurements of branch xylem density, Dx, were made for 1466 trees representing 503 species, sampled from 80 sites across the Amazon basin. Measured values ranged from 240 kg m?3 for a Brosimum parinarioides from Tapajos in West Para, Brazil to 1130 kg m?3 for an Aiouea sp. from Caxiuana, Central Para, Brazil. Analysis of variance showed significant differences in average Dx across the sample plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that geographic location and plot accounted for 33% of the variation with species identity accounting for an additional 27%; the remaining residual 40% of the variance accounted for by tree to tree (within species) variation. Variations in plot means, were, however, hardly accountable at all by differences in species composition. Rather, it would seem that variations of xylem density at plot level must be explained by the effects of soils and/or climate. This conclusion is supported by the observation that the xylem density of the more widely distributed species varied systematically from plot to plot. Thus, as well as having a genetic component branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing and in a predictable manner. Exceptions to this general rule may be some pioneers belonging to Pourouma and Miconia and some species within the genera Brosimum, Rinorea and Trichillia which seem to be more constrained in terms of this plasticity than most species sampled as part of this study.

Measurements of branch xylem density, D x , were made for 1466 trees representing 503 species, sampled from 80 sites across the Amazon basin. Measured values ranged from 240 kg m ?3 for a Brosimum parinarioides from Tapajos in West Para, Brazil to 1130 kg m ?3 for an Aiouea sp. from Caxiuana, Central Para, Brazil. Analysis of variance showed significant differences in average D x across the sample plots as well as significant differences between families, genera and species. A partitioning of the total variance in the dataset showed that geographic location and plot accounted for 33% of the variation with species identity accounting for an additional 27%; the remaining "residual" 40% of the variance accounted for by tree to tree (within species) variation. Variations in plot means, were, however, hardly accountable at all by differences in species composition. Rather, it would seem that variations of xylem density at plot level must be explained by the effects of soils and/or climate. This conclusion is supported by the observation that the xylem density of the more widely distributed species varied systematically from plot to plot. Thus, as well as having a genetic component branch xylem density is a plastic trait that, for any given species, varies according to where the tree is growing and in a predictable manner. Exceptions to this general rule may be some pioneers belonging to Pourouma and Miconia and some species within the genera Brosimum, Rinorea and Trichillia which seem to be more constrained in terms of this plasticity than most species sampled as part of this study.