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Comparing model output and observed data is an important step for assessing model performance and quality of simulation results. However, such comparisons are often hampered by differences in spatial scales between local point observations and large-scale simulations of grid cells or pixels. In this study, we propose a generic approach for a pixel-to-point comparison and provide statistical measures accounting for the uncertainty resulting from landscape variability and measurement errors in ecosystem variables. The basic concept of our approach is to determine the statistical properties of small-scale (within-pixel) variability and observational errors, and to use this information to correct for their effect when large-scale area averages (pixel) are compared to small-scale point estimates. We demonstrate our approach by comparing simulated values of aboveground biomass, woody productivity (woody net primary productivity, NPP) and residence time of woody biomass from four dynamic global vegetation models (DGVMs) with measured inventory data from permanent plots in the Amazon rainforest, a region with the typical problem of low data availability, potential scale mismatch and thus high model uncertainty. We find that the DGVMs under- and overestimate aboveground biomass by 25 % and up to 60 %, respectively. Our comparison metrics provide a quantitative measure for model–data agreement and show moderate to good agreement with the region-wide spatial biomass pattern detected by plot observations. However, all four DGVMs overestimate woody productivity and underestimate residence time of woody biomass even when accounting for the large uncertainty range of the observational data. This is because DGVMs do not represent the relation between productivity and residence time of woody biomass correctly. Thus, the DGVMs may simulate the correct large-scale patterns of biomass but for the wrong reasons. We conclude that more information about the underlying processes driving biomass distribution are necessary to improve DGVMs. Our approach provides robust statistical measures for any pixel-to-point comparison, which is applicable for evaluation of models and remote-sensing products.

Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus ε, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf : sapwood area ratio Al : As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait–trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.

The seasonal climate drivers of the carbon cycle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combination of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measurements and 35 litter productivity measurements), their associated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonality in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rainfall is −1 (water-limited forests) and to radiation otherwise (light-limited forests). On the other hand, independent of climate limitations, wood productivity and litterfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosynthetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest productivity in a drier climate in water-limited forest, and in current light-limited forest with future rainfall −1.

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.

Forest structure and dynamics vary across the Amazon Basin in an east-west gradient coincident with variations in soil fertility and geology. This has resulted in the hypothesis that soil fertility may play an important role in explaining Basin-wide variations in forest biomass, growth and stem turnover rates. Soil samples were collected in a total of 59 different forest plots across the Amazon Basin and analysed for exchangeable cations, carbon, nitrogen and pH, with several phosphorus fractions of likely different plant availability also quantified. Physical properties were additionally examined and an index of soil physical quality developed. Bivariate relationships of soil and climatic properties with above-ground wood productivity, stand-level tree turnover rates, above-ground wood biomass and wood density were first examined with multivariate regression models then applied. Both forms of analysis were undertaken with and without considerations regarding the underlying spatial structure of the dataset. Despite the presence of autocorrelated spatial structures complicating many analyses, forest structure and dynamics were found to be strongly and quantitatively related to edaphic as well as climatic conditions. Basin-wide differences in stand-level turnover rates are mostly influenced by soil physical properties with variations in rates of coarse wood production mostly related to soil phosphorus status. Total soil P was a better predictor of wood production rates than any of the fractionated organic- or inorganic-P pools. This suggests that it is not only the immediately available P forms, but probably the entire soil phosphorus pool that is interacting with forest growth on longer timescales. A role for soil potassium in modulating Amazon forest dynamics through its effects on stand-level wood density was also detected. Taking this into account, otherwise enigmatic variations in stand-level biomass across the Basin were then accounted for through the interacting effects of soil physical and chemical properties with climate. A hypothesis of self-maintaining forest dynamic feedback mechanisms initiated by edaphic conditions is proposed. It is further suggested that this is a major factor determining endogenous disturbance levels, species composition, and forest productivity across the Amazon Basin.

Many plant traits covary in a non-random manner reflecting interdependencies associated with "ecological strategy" dimensions. To understand how plants integrate their structural and physiological investments, data on leaf and leaflet size and the ratio of leaf area to sapwood area (ΦLS) obtained for 1020 individual trees (encompassing 661 species) located in 52 tropical forest plots across the Amazon Basin were incorporated into an analysis utilising existing data on species maximum height (Hmax), seed size, leaf mass per unit area (MA), foliar nutrients and δ13C, and branch xylem density (ρx). Utilising a common principal components approach allowing eigenvalues to vary between two soil fertility dependent species groups, five taxonomically controlled trait dimensions were identified. The first involves primarily cations, foliar carbon and MA and is associated with differences in foliar construction costs. The second relates to some components of the classic "leaf economic spectrum", but with increased individual leaf areas and a higher ΦLS newly identified components for tropical tree species. The third relates primarily to increasing Hmax and hence variations in light acquisition strategy involving greater MA, reductions in ΦLS and less negative δ13C. Although these first three dimensions were more important for species from high fertility sites the final two dimensions were more important for low fertility species and were associated with variations linked to reproductive and shade tolerance strategies. Environmental conditions influenced structural traits with ρx of individual species decreasing with increased soil fertility and higher temperatures. This soil fertility response appears to be synchronised with increases in foliar nutrient concentrations and reductions in foliar [C]. Leaf and leaflet area and ΦLS were less responsive to the environment than ρx. Thus, although genetically determined foliar traits such as those associated with leaf construction costs coordinate independently of structural characteristics such as maximum height, others such as the classical "leaf economic spectrum" covary with structural traits such as leaf size and ΦLS. Coordinated structural and physiological adaptions are also associated with light acquisition/shade tolerance strategies with several traits such as MA and [C] being significant components of more than one ecological strategy dimension. This is argued to be a consequence of a range of different potential underlying causes for any observed variation in such "ambiguous" traits. Environmental effects on structural and physiological characteristics are also coordinated but in a different way to the gamut of linkages associated with genotypic differences.

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. stand-level 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 amedian −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.

Vertical profiles in leaf mass per unit leaf area (MA), foliar 13C composition (δ13C), nitrogen (N), phosphorus (P), carbon (C) and major cation concentrations were estimated for 204 rain forest trees growing in 57 sites across the Amazon Basin. Data was analysed using a multilevel modelling approach, allowing a separation of gradients within individual tree canopies (within-tree gradients) as opposed to stand level gradients occurring because of systematic differences occurring between different trees of different heights (between-tree gradients). Significant positive within-tree gradients (i.e. increasing values with increasing sampling height) were observed for MA and [C]DW (the subscript denoting on a dry weight basis) with negative within-tree gradients observed for δ13C, [Mg]DW and [K]DW. No significant within-tree gradients were observed for [N]DW, [P]DW or [Ca]DW. The magnitudes of between-tree gradients were not significantly different to the within-tree gradients for MA, δ13C, [C]DW, [K]DW, [N]DW, [P]DW and [Ca]DW. But for [Mg]DW, although there was no systematic difference observed between trees of different heights, strongly negative within-tree gradients were found to occur. When expressed on a leaf area basis (denoted by the subscript "A"), significant positive gradients were observed for [N]A, [P]A and [K]A both within and between trees, these being attributable to the positive intra- and between-tree gradients in MA mentioned above. No systematic within-tree gradient was observed for either [Ca]A or [Mg]A, but with a significant positive gradient observed for [Mg]A between trees (i.e. with taller trees tending to have a higher Mg per unit leaf area). Significant differences in within-tree gradients between individuals were observed only for MA, δ13C and [P] A. This was best associated with the overall average [P]A for each tree, this also being considered to be a surrogate for a tree's average leaf area based photosynthetic capacity, Amax. A new model is presented which is in agreement with the above observations. The model predicts that trees characterised by a low upper canopy Amax should have shallow, or even non-existent, within-canopy gradients in Amax, with optimal intra-canopy gradients becoming sharper as a tree's upper canopy Amax increases. Nevertheless, in all cases it is predicted that the optimal within-canopy gradient in Amax should be substantially less than for photon irradiance. Although this is also shown to be consistent with numerous observations as illustrated by a literature survey of gradients in photosynthetic capacity for broadleaf trees, it is also in contrast to previously held notions of optimality. A new equation relating gradients in photosynthetic capacity within broadleaf tree canopies to the photosynthetic capacity of their upper canopy leaves is presented.

Soil samples were collected in six South American countries in a total of 71 different 1 ha forest plots across the Amazon Basin as part of the RAINFOR project. They were analysed for total and exchangeable cations, C, N, pH with various P fractions also determined. Physical properties were also examined and an index of soil physical quality proposed. A diverse range of soils was found. For the western areas near the Andean cordillera and the southern and northern fringes, soils tend to be distributed among the lower pedogenetic levels, while the central and eastern areas of Amazonia have more intensely weathered soils. This gives rise to a large variation of soil chemical and physical properties across the Basin, with soil properties varying predictably along a gradient of pedogenic development. Nutrient pools generally increased slightly in concentration from the youngest to the intermediate aged soils after which a gradual decline was observed with the lowest values found in the most weathered soils. Soil physical properties were strongly correlated with soil fertility, with favourable physical properties occurring in highly weathered and nutrient depleted soils and with the least weathered, more fertile soils having higher incidence of limiting physical properties. Soil phosphorus concentrations varied markedly in accordance with weathering extent and appear to exert an important influence on the nitrogen cycle of Amazon forest soils.

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.

We explored the floristic composition of terra firme forests across Amazonia using 55 plots. Firstly, we examined the floristic patterns using both genus- and species-level data and found that the species-level analysis more clearly distinguishes among forests. Next, we compared the variation in plot floristic composition at regional- and continental-scales, and found that average among-pair floristic similarity and its decay with distance behave similarly at regional- and continental-scales. Nevertheless, geographical distance had different effects on floristic similarity within regions at distances

We analysed 1040 individual trees, located in 62 plots across the Amazon Basin for leaf mass per unit area (MA), foliar carbon isotopic composition (δ13C) and leaf level concentrations of C, N, P, Ca, Mg, K and Al. All trees were identified to the species level with the dataset containing 58 families, 236 genera and 508 species, distributed across a wide range of soil types and precipitation regimes. Some foliar characteristics such as MA, [C], [N] and [Mg] emerge as highly constrained by the taxonomic affiliation of tree species, but with others such as [P], [K], [Ca] and δ13C also strongly influenced by site growing conditions. By removing the environmental contribution to trait variation, we find that intrinsic values of most trait pairs coordinate, although different species (characterised by different trait suites) are found at discrete locations along a common axis of coordination. Species that tend to occupy higher fertility soils are characterised by a lower MA and have a higher intrinsic [N], [P], [K], [Mg] and δ13C than their lower fertility counterparts. Despite this consistency, different scaling patterns were observed between low and high fertility sites. Inter-relationships are thus substantially modified by growth environment. Analysing the environmental component of trait variation, we found soil fertility to be the most important predictor, influencing all leaf nutrient concentrations and δ13C and reducing MA. Mean annual temperature was negatively associated with leaf level [N], [P] and [K] concentrations. Total annual precipitation positively influences MA, [C] and δ13C, but with a negative impact on [Mg]. These results provide a first basis for understanding the relationship between the physiological functioning and distribution of tree species across Amazonia.

The Amazon basin, one of the most substantial biomass carbon pools on earth, is characterised by strong macroecological gradients in biomass, mortality rates, and wood density from west to east. These gradients could affect necromass stocks, but this has not yet been tested. This study aims to assess the stocks and determinants of necromass across Amazonian forests. Field-based and literature data were used to find relationships between necromass and possible determinants. Furthermore, a simple model was applied to estimate and extrapolate necromass stocks across terra firma Amazonian forests. In eight northwestern and three northeastern Amazonian permanent plots, volumes of coarse woody debris (≥10 cm diameter) were measured in the field and the density of each decay class was estimated. Forest structure and historical mortality data were used to determine the factors controlling necromass. Necromass is greater in forests with low stem mortality rates (northeast) rather than in forests with high stem mortality rates (northwest) (58.5±10.6 and 27.3±3.2 Mg ha−1, respectively). Using all published necromass values, we find that necromass across terra firma forests in Amazonia is positively related to both forest dynamics (mortality mass inputs and a surrogate for decomposition rate (average wood density of living trees)) and forest structure (biomass), but is better explained by forest dynamics. We propose an improved method to estimate necromass for plots where necromass has not been measured. The estimates, together with other actual measurements of necromass, were scaled-up to project a total Amazonian necromass of 9.6±1.0 Pg C. The ratio of necromass (on average weighted by forest region) to coarse aboveground biomass is 0.127. Overall, we find (1) a strong spatial trend in necromass in parallel with other macroecological gradients and (2) that necromass is a substantial component of the carbon pool in the Amazon.

Leaf size influences many aspects of tree function such as rates of transpiration and photosynthesis and, consequently, often varies in a predictable way in response to environmental gradients. The recent development of pan-Amazonian databases based on permanent botanical plots has now made it possible to assess trends in leaf size across environmental gradients in Amazonia. Previous plot-based studies have shown that the community structure of Amazonian trees breaks down into at least two major ecological gradients corresponding with variations in soil fertility (decreasing from southwest to northeast) and length of the dry season (increasing from northwest to south and east). Here we describe the geographic distribution of leaf size categories based on 121 plots distributed across eight South American countries. We find that the Amazon forest is predominantly populated by tree species and individuals in the mesophyll size class (20.25–182.25 cm2). The geographic distribution of species and individuals with large leaves (>20.25 cm2) is complex but is generally characterized by a higher proportion of such trees in the northwest of the region. Spatially corrected regressions reveal weak correlations between the proportion of large-leaved species and metrics of water availability. We also find a significant negative relationship between leaf size and wood density.

Leaves in tropical forests come in an enormous variety of sizes and shapes, each of which can be ultimately viewed as an adaptation to the complex problem of optimising the capture of light for photosynthesis. However, the fact that many different shape "strategies" coexist within a habitat demonstrate that there are many other intrinsic and extrinsic factors involved, such as the differential investment in support tissues required for different leaf lamina shapes. Here, we take a macrogeographic approach to understanding the function of different lamina shape categories. Specifically, we use 106 permanent plots spread across the Amazon rainforest basin to: 1) describe the geographic distribution of some simple metrics of lamina shape in plots from across Amazonia, and; 2) identify and quantify relationships between key environmental parameters and lamina shape in tropical forests. Because the plots are not randomly distributed across the study area, achieving this latter objective requires the use of statistics that can account for spatial auto-correlation. We found that between 60–70% of the 2791 species and 83 908 individual trees in the dataset could be classified as having elliptic leaves (= the widest part of the leaf is on an axis in the middle fifth of the long axis of the leaf). Furthermore, the average Amazonian tree leaf is 2.5 times longer than it is wide and has an entire margin. Contrary to theoretical expectations we found little support for the hypothesis that narrow leaves are an adaptation to dry conditions. However, we did find strong regional patterns in leaf lamina length-width ratios and several significant correlations with precipitation variables suggesting that water availability may be exerting an as yet unrecognised selective pressure on leaf shape of rainforest trees. Some support was found for the hypothesis that narrow leaves are an adaptation to low nutrient soils. Furthermore, we found a strong correlation between the proportion of trees with non-entire laminas (dissected, toothed, etc.) and mean annual temperature once again supporting the well documented association that provides a basis for reconstructing past temperature regimes.

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.

Understanding the relationships between plant traits and ecosystem properties at large spatial scales is important for predicting how compositional change will affect carbon cycling in tropical forests. In this study, we examine the relationships between species wood density, maximum height and above-ground, coarse wood production of trees ≥10 cm diameter (CWP) for 60 Amazonian forest plots. Average species maximum height and wood density are lower in Western than Eastern Amazonia and are negatively correlated with CWP. To test the hypothesis that variation in these traits causes the variation in CWP, we generate plot-level estimates of CWP by resampling the full distribution of tree biomass growth rates whilst maintaining the appropriate tree-diameter and functional-trait distributions for each plot. These estimates are then compared with the observed values. Overall, the estimates do not predict the observed, regional-scale pattern of CWP, suggesting that the variation in community-level trait values does not determine variation in coarse wood productivity in Amazonian forests. Instead, the regional gradient in CWP is caused by higher biomass growth rates across all tree types in Western Amazonia. Therefore, the regional gradient in CWP is driven primarily by environmental factors, rather than the particular functional composition of each stand. These results contrast with previous findings for forest biomass, where variation in wood density, associated with variation in species composition, is an important driver of regional-scale patterns in above-ground biomass. Therefore, in tropical forests, above-ground wood productivity may be less sensitive than biomass to compositional change that alters community-level averages of these plant traits.

Countries are required to generate baselines of carbon emissions, or Forest Reference Emission Levels, for implementing REDD+ under the United Nations Framework Convention on Climate Change and to access results-based payments. Developing these baselines requires accurate maps of carbon stocks and historical deforestation. Global remote sensing products provide low-cost solutions for this information, but there has been little validation of these products at national scales. This study compares the ability of currently available products obtained from remote sensing data to deliver estimates of deforestation and associated carbon emissions in Guinea-Bissau, a West African country encompassing the climate and vegetation gradients that are typical of sub-Saharan Africa. We show that disagreements in estimates of deforestation are striking, and this variation leads to high uncertainty in derived emissions. For Guinea-Bissau, we suggest that higher temporal resolution of remote sensing products is required to reduce this uncertainty by overcoming current limitations in differentiating deforestation from seasonality. In contrast, existing datasets of carbon stocks show better agreement, and contribute much less to the variation in estimated emissions. We conclude that using global datasets based on Earth Observation data is a cost-effective solution to make REDD+ operational, but deforestation maps in particular should be derived carefully and their uncertainty assessed.