We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N-23.4 S) of 375 Pg dry mass, 9-18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15-21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha(-1) vs. 21 and 28 Mg ha(-1) for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.

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 ...

We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha−1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha−1) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha−1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes.

Tropical forests are global centres of biodiversity and carbon storage. Many tropical countries aspire to protect forest to fulfil biodiversity and climate mitigation policy targets, but the conservation strategies needed to achieve these two functions depend critically on the tropical forest tree diversity-carbon storage relationship. Assessing this relationship is challenging due to the scarcity of inventories where carbon stocks in aboveground biomass and species identifications have been simultaneously and robustly quantified. Here, we compile a unique pan-tropical dataset of 360 plots located in structurally intact old-growth closed-canopy forest, surveyed using standardised methods, allowing a multi-scale evaluation of diversity-carbon relationships in tropical forests. Diversity-carbon relationships among all plots at 1 ha scale across the tropics are absent, and within continents are either weak (Asia) or absent (Amazonia, Africa). A weak positive relationship is detectable within 1 ha plots, indicating that diversity effects in tropical forests may be scale dependent. The absence of clear diversity-carbon relationships at scales relevant to conservation planning means that carbon-centred conservation strategies will inevitably miss many high diversity ecosystems. As tropical forests can have any combination of tree diversity and carbon stocks both require explicit consideration when optimising policies to manage tropical carbon and biodiversity.

Aim To test the extent to which the vertical structure of tropical forests is determined by environment, forest structure or biogeographical history. Location Pan‐tropical. Methods Using height and diameter data from 20,497 trees in 112 non‐contiguous plots, asymptotic maximum height (H AM) and height–diameter relationships were computed with nonlinear mixed effects (NLME) models to: (1) test for environmental and structural causes of differences among plots, and (2) test if there were continental differences once environment and structure were accounted for; persistence of differences may imply the importance of biogeography for vertical forest structure. NLME analyses for floristic subsets of data (only/excluding Fabaceae and only/excluding Dipterocarpaceae individuals) were used to examine whether family‐level patterns revealed biogeographical explanations of cross‐continental differences. Results H AM and allometry were significantly different amongst continents. H AM was greatest in Asian forests (58.3 ± 7.5 m, 95% CI), followed by forests in Africa (45.1 ± 2.6 m), America (35.8 ± 6.0 m) and Australia (35.0 ± 7.4 m), and height–diameter relationships varied similarly; for a given diameter, stems were tallest in Asia, followed by Africa, America and Australia. Precipitation seasonality, basal area, stem density, solar radiation and wood density each explained some variation in allometry and H AM yet continental differences persisted even after these were accounted for. Analyses using floristic subsets showed that significant continental differences in H AM and allometry persisted in all cases. Main conclusions Tree allometry and maximum height are altered by environmental conditions, forest structure and wood density. Yet, even after accounting for these, tropical forest architecture varies significantly from continent to continent. The greater stature of tropical forests in Asia is not directly determined by the dominance of the family Dipterocarpaceae, as on average non‐dipterocarps are equally tall. We hypothesise that dominant large‐statured families create conditions in which only tall species can compete, thus perpetuating a forest dominated by tall individuals from diverse families.

Climate and land-use change drive a suite of stressors that shape ecosystems and interact to yield complex ecological responses, i.e. additive, antagonistic and synergistic effects.Currently we know little about the spatial scale relevant for the outcome of such interactions and about effect sizes. This knowledge gap needs to be filled to underpin future land management decisions or climate mitigation interventions, for protecting and restoring freshwater ecosystems. The study combines data across scales from 33 mesocosm experiments with those from 14 river basins and 22 cross-basin studies in Europe producing 174 combinations of paired-stressor effects on a biological response variable. Generalised linear models showed that only one of the two stressors had a significant effect in 39% of the analysed cases, 28% of the paired-stressor combinations resulted in additive and 33% in interactive (antagonistic, synergistic, opposing or reversal) effects. For lakes the frequency of additive and interactive effects was similar for all spatial scales addressed, while for rivers this frequency increased with scale. Nutrient enrichment was the overriding stressor for lakes, generally exceeding those of secondary stressors. For rivers, the effects of nutrient enrichment were dependent on the specific stressor combination and biological response variable. These results vindicate the traditional focus of lake restoration and management on nutrient stress, while highlighting that river management requires more bespoke management solutions.